Sinkron : jurnal dan penelitian teknik informatika https://www.polgan.ac.id/jurnal/index.php/sinkron <p><a href="https://sinta.kemdikbud.go.id/journals/detail?id=3320"><strong>Sinkron</strong> <strong>: Jurnal dan Penelitian Teknik Informatika</strong></a> is<strong> The<a href="http://polgan.ac.id/jurnal/sinkrons3.pdf"> Kemdikbud Accredited National Scientific Journal Rank 3 (Sinta 3), Number: 148 / M / KPT / 2020 on August 3, 2020</a></strong>. Start from 2022, SinkrOn is published Quarterly, namely in January, April, July and October. SinkrOn aims to promote research in the field of Informatics Engineering which focuses on publishing quality papers about the latest information about computer science. Submitted papers will be reviewed by the Journal and Association technical committee. All articles submitted must be original reports, previously published research results, experimental or theoretical, and will be reviewed by colleagues. Articles sent to the Sinkron journal may not be published elsewhere. The manuscript must follow the writing style provided by SinkrOn and must be reviewed and edited.</p> <p>Sinkron is published by <strong><span style="text-decoration: underline;"><a href="https://www.polgan.ac.id">Politeknik Ganesha Medan</a></span></strong>, a Higher Education in Medan, North Sumatra, Indonesia. </p> <p><strong>E- ISSN: <a href="https://issn.lipi.go.id/terbit/detail/1472194336">2541-2019</a> </strong>(Indonesian | LIPI)<strong> | </strong><strong>P-ISSN: <a href="http://issn.pdii.lipi.go.id/issn.cgi?daftar&amp;1474367655&amp;1&amp;&amp;">2541-044X</a> </strong>(Indonesian | LIPI)<strong> | </strong><strong>DOI Prefix: 10.33395</strong></p> <p><strong>E- ISSN: <a href="https://portal.issn.org/resource/ISSN/2541-2019">2541-2019</a> </strong>(International)<strong> | </strong><strong>P-ISSN: <a title="International ISSN" href="https://portal.issn.org/resource/ISSN/2541-044X">2541-044X</a> </strong>(International)</p> Politeknik Ganesha Medan en-US Sinkron : jurnal dan penelitian teknik informatika 2541-044X Learning Fuzzy Neural Networks by Using Improved Conjugate Gradient Techniques https://www.polgan.ac.id/jurnal/index.php/sinkron/article/view/11442 <p>One of the optimal approaches for learning a Takagi Sugeno-based fuzzy neural network model is the conjugate gradient method proposed in this research. For the PRP and the LS approaches, a novel algorithm based on the Liu-Storey (LS) approach is created to overcome the slow convergence. The developed method becomes descent and convergence by assuming some hypothesis. The numerical results show that the developed method for classifying data is more efficient than the other methods, as shown in Table (2), where the new method outperforms the others in terms of average training time, average training accuracy, average test accuracy, average training MSE, and average test MSE.</p> Hisham M. Khudhur Khalil K. Abbo Copyright (c) 2022 Hisham M. Khudhur, Khalil K. Abbo http://creativecommons.org/licenses/by-nc/4.0 2022-07-01 2022-07-01 7 3 767 776 10.33395/sinkron.v7i3.11442 Detection of Room Cleanliness Based on Digital Image Processing using SVM and NN Algorithm https://www.polgan.ac.id/jurnal/index.php/sinkron/article/view/11479 <p>A clean environment can prevent us from disease and can increase productivity. A neat and clean room arrangement can affect health, avoiding the possibility of stress, lethargy, and depression. The room recognition process based on its neatness is carried out through a process of matching and comparing the images that are used as training and testing sets. Technological developments make it possible to detect room conditions through image. Detection uses image processing by classifying images into 2 categories, clean and messy. It has been widely used in various fields, one of which is hospitality. In determining the clean room and messy room has problems due to image quality, different lighting, and image similarity. This study aims to detect clean and messy spaces by comparing the Support Vector Machine and Neural Network methods on a dataset of 199 images. Based on the test, the highest accuracy classification value was 98.0% for the Neural Network method with an AUC of 0.999</p> Suparni suparni Hilda Rachmi Ahmad Al Kaafi Copyright (c) 2022 Suparni suparni, Hilda Rachmi, Ahmad Al Kaafi http://creativecommons.org/licenses/by-nc/4.0 2022-07-01 2022-07-01 7 3 777 783 10.33395/sinkron.v7i3.11479 Arduino Implementation for Development Digital Capacitance Meters as Laboratory Measurement Devices https://www.polgan.ac.id/jurnal/index.php/sinkron/article/view/11456 <p>Electronics Practicum in the Laboratory is a routine activity carried out to support student skills. Capacitors are one of the components that are often used in practice. Capacitors are one of the passive electronic components that have a magnitude value in the form of capacitance in Farad units. The capacitance value indicates the capacitor's ability to store electric charge. However, the value contained on the capacitor label is not necessarily the actual value because the capacitor has a tolerance range. Of course, this is very influential in the measurement and performance of electronic circuits that use capacitors. In addition, another factor that supports this research is that the available measuring instruments, such as the multimeter, are not yet equipped with capacitance measurements. Capacitance meters available in the market are still analog. The purpose of this study is to design a device that can measure the capacitance value of capacitors as a measurement device in a digital laboratory, namely the Digital Capacitance Meter. This device is made using Arduino Uno as a microprocessor for data processing. The method used is to apply the process of charging and discharging the capacitor. In this case, Arduino Uno activates a timer to measure the time required to charge and discharge the capacitor so that the Time Constant value is obtained. By using the formula T = 0.693RC, the capacitance value can be obtained. In testing using 3 different capacitors and 10 times testing on each capacitor, the accuracy of the device is 97.76% and a relative error of 2.24%.</p> Denny Hardiyanto Prabakti Endramawan Ridho Nur Taufiqul Manan Dyah Anggun Sartika Copyright (c) 2022 Denny Hardiyanto, Prabakti Endramawan, Ridho Nur Taufiqul Manan, Dyah Anggun Sartika http://creativecommons.org/licenses/by-nc/4.0 2022-07-02 2022-07-02 7 3 784 790 10.33395/sinkron.v7i3.11456 Multiple Linear Regression Analysis on Factors that Influence Employees Work Motivation https://www.polgan.ac.id/jurnal/index.php/sinkron/article/view/11453 <p>This study aims to analyze the factors that influence employee motivation at PT XYZ. The analysis was carried out using four variables, namely Facilities, Work Environtment, Salary and Jobdesk. In collecting data, this study used primary and secondary data. Primary data were collected by distributing questionnaires to employees at PT XYZ using the Voluntary Sampling Technique, questionnaires were distributed to employees with a willingness to participate in the research. From the questionnaire obtained 71 data as primary data. Secondary data used results of previous&nbsp; studies and data from PT XYZ which was given to assist the research. Furthermore, data processing is done by using multiple linear regression algorithm. The data is processed and analyzed using the RStudio software. Parameter significance test and classical assumption test performed with RStudio. From this research, it is concluded that the variables that have the most influence on employee motivation at PT XYZ are Facilities and Jobdesk, where these variables have a positive effect on employee motivation at PT XYZ. The results of the analysis show that an increase in facilities will increase work motivation by 20,659% and jobdesk will increase work motivation by 27,901%. This research is expected to be the company's decision in its efforts to increase employee motivation.</p> Gracia Theofani Eko Sediyono Copyright (c) 2022 Gracia Theofani, Eko Sediyono http://creativecommons.org/licenses/by-nc/4.0 2022-07-02 2022-07-02 7 3 791 798 10.33395/sinkron.v7i3.11453 Information System Audit Using COBIT and ITIL Framework: Literature Review https://www.polgan.ac.id/jurnal/index.php/sinkron/article/view/11476 <p>Improved IT performance drives business growth, enhances competitive advantage, and enables strategic improvements in IT management and governance. This condition is increasingly important because business organizations and systems and technology are increasingly complex. In the application and use of technology, information technology audits require a framework based on principles that drive the desired behavior. In writing this literature review, the information technology audit method used is ITIL, and COBIT as guidelines for corporate information technology governance and audit processes. In its use, the ITIL framework is designed to ensure a flexible, coordinated and integrated system for the effective governance and management of IT services. While the COBIT framework is designed from a number of components that function to adjust, maintain, and shape system governance. To conduct an information system audit, the authors need to pay attention to things that can affect IT performance. This study produces a model to determine the factors that affect the Information System Audit. Researchers conducted a literature review from various sources that discussed Information System Auditing Using the COBIT and ITIL Frameworks which were collected from some of the literature found. Several factors that influence the Information System Audit are Design Factors, Knowledge Worker factors, Operational factors, Risk Assessment Factors, and Gather Evidence Factors. The author also conducted a systematic mapping study to find research gaps, namely the method of mapping the relationship between research topics and how much research has covered each topic and the relationship between topics.</p> Arif Rusman Reny Nadlifatin Apol Pribadi Subriadi Copyright (c) 2022 Arif Rusman, Reny Nadlifatin, Apol Pribadi Subriadi http://creativecommons.org/licenses/by-nc/4.0 2022-07-03 2022-07-03 7 3 799 810 10.33395/sinkron.v7i3.11476 Internet of Things-based Gas Leak Detection with Alerts Via SMS and Blynk App https://www.polgan.ac.id/jurnal/index.php/sinkron/article/view/11477 <p><em>Gas cylinders are one of the needs that humans use every day. The use of gas cylinders is often used for cooking, both for household needs and industrial needs. Gas leaks are a big problem that can give rise to explosions and fires due to combustible gas. Explosions and fires that occur as a result of this gas leak can cause a lot of losses. This study aims to build an Internet of Things-based gas leak detection tool using NodeMCU ESP8266 as a microcontroller that functions as a brain to execute commands that have been made. Blynk App and SMS to provide information to users in case of gas leaks detected by MQ-6 sensors. This tool will detect gas leaks that occur by receiving data from the MQ-6 sensor which is then processed by NodeMCU ESP8266. If a gas leak is detected, the buzzer will sound and the tool will give an alert by popping up a notification on the Blynk application with an internet connection and sending an alert via SMS so that the alert can be sent even in the absence of an internet connection. With this tool, users can find out earlier if there is a gas leak by getting a notification on the Blynk application and receiving a gas leak SMS, to avoid explosions and minimize damage and losses caused by gas leaks.</em></p> Revy Muhammad Yusuf Ari Purno Wahyu W Copyright (c) 2022 Revy Muhammad Yusuf, Ari Purno Wahyu W http://creativecommons.org/licenses/by-nc/4.0 2022-07-03 2022-07-03 7 3 811 816 10.33395/sinkron.v7i3.11477 Perfomance analysis of Naive Bayes method with data weighting https://www.polgan.ac.id/jurnal/index.php/sinkron/article/view/11516 <p>Classification using naive bayes algorithm for air quality dataset has an accuracy rate of 39.97%. This result is considered not good and by using all existing data attributes. By doing pre-processing, namely feature selection using the gain ratio algorithm, the accuracy of the Naive Bayes algorithm increases to 61.76%. This proves that the gain ratio algorithm can improve the performance of the naive bayes algorithm for air quality dataset classification. Classification using naive bayes algorithm for air quality dataset. While the Water Quality dataset has an accuracy rate of 93.18%. These results are considered good and by using all the existing data attributes. By doing pre-processing, namely feature selection using the gain ratio algorithm, the accuracy of the Naive Bayes algorithm increases to 95.73%. This proves that the gain ratio algorithm can improve the performance of the naive bayes algorithm for air quality dataset classification. Classification using Naive Bayes algorithm for Water Quality dataset. Based on the tests that have been carried out on all data, it can be seen that the Weight nave Bayes classification model can provide better accuracy values ​​because there is a change in the weighting of the attribute values ​​in the dataset used. The value of the weighted Gain ratio is used to calculate the probability in Nave Bayes, which is a parameter to see the relationship between each attribute in the data, and is used as the basis for the weighting of each attribute of the dataset. The higher the Gain ratio of an attribute, the greater the relationship to the data class. So that the accuracy value increases than the accuracy value generated by the Naïve Bayes classification model. The increase in accuracy in the Naïve Bayes classification model is due to the number of weights from the attribute selection in the Gain ratio.</p> Afdhaluzzikri Afdhaluzzikri Herman Mawengkang Opim Salim Sitompul Copyright (c) 2022 Afdhaluzzikri Afdhaluzzikri, Herman Mawengkang, Opim Salim Sitompul http://creativecommons.org/licenses/by-nc/4.0 2022-07-06 2022-07-06 7 3 817 821 10.33395/sinkron.v7i3.11516 Application of Hot Fit Model to Analyze Information Technology Ams (Academic Management System) https://www.polgan.ac.id/jurnal/index.php/sinkron/article/view/11462 <p>Bina Insan University has applied a computer-based information system. This system is named AMS (Academic Management System). The application of AMS (Academic Management System) at this time is still experiencing various obstacles and obstacles at the level of user acceptance. This study aims to analyze the results of the evaluation of the success factors for implementing AMS (Academic Management System) using the Hot-Fit Model (Human Organization Technology – Net benefits). This model was chosen because this model can provide an explanation and provide an evaluation of the factors that influence the implementation of a system at the University of Bina Insan Lubuklinggau in terms of Human (Human), Organization (Organization), Technology (Technology), and Net benefits. In addition, the success of implementing AMS (Academic Management System) at the University of Bina Insan Lubklinggau, is also influenced by the support and encouragement from universities to AMS (Academic Management System) users, as well as the availability of adequate facilities within the Bina Insan Lubuklinggau University to use AMS (Academic Management Systems). From the analysis that has been carried out on 80 respondents who have filled out the research questionnaire, the results show that to test the validity of the variables (Human), Organization (Organization), Technology (Technology), and Net benefit, it shows that each question measured on all variables is valid, which indicated by Corrected Item – Total Correlation or (rcount) the entire score of Corrected Item – Total Correlation or (rcount) greater than rtable of 0.220, and for the F test results obtained a value of F = 13.334 with a significance of 0.000. meaning that the variables of human, organization and technology together have a significant effect on net-benefit (Y).</p> Elmayati Elmayati Bunga Intan Deni Nurdiansyah Aprilsa Milenia Yogi Kelpin Copyright (c) 2022 Elmayati http://creativecommons.org/licenses/by-nc/4.0 2022-07-08 2022-07-08 7 3 822 833 10.33395/sinkron.v7i3.11462 Mobile Positioning Data Based-Application for Medan Tourism Objects https://www.polgan.ac.id/jurnal/index.php/sinkron/article/view/11464 <p>Tourism Object is a fundamental component in the tourism industry and one of the reasons visitors travel. The State of Indonesia is one of the various countries whose number of tourist objects is very large and varied. One of these attractions is natural tourism, for example, the sea, beaches, rivers, lakes, and mountains, as well as for the building objects including historical heritage sites, forts, museums and so on. The method used in this study uses qualitative research by applying the method of mobile positioning data to help the manager of tourist attractions promote the location of tourist attractions. The mobile positioning system model can be used to understand and determine the mobile position based on location coordinates. This mobile positioning system uses GPS technology, a tool to get or generate the coordinates of the position of the online map technology that Google provides to show the position that has been stored in the system. The research results from this Tourism Object application can detect the user's location according to the mobile positioning data method. This Android-based Tourist Object application can display a list of tourist objects according to the area occupied by the user. This tourist attraction application can add new tourist objects by admin. It is hoped that in the future this application can be run on the iOS system and can add images to new tourist attractions.</p> Vedi Yordan Wilsen Polfan Khavitanjali Khavitanjali Paskah Kurniawan Gari Saut Dohot Siregar Copyright (c) 2022 Vedi Yordan, Wilsen Polfan, Khavitanjali Khavitanjali, Paskah Kurniawan Gari http://creativecommons.org/licenses/by-nc/4.0 2022-07-08 2022-07-08 7 3 834 845 10.33395/sinkron.v7i3.11464 Internet of Things-based Agricultural Land Monitoring https://www.polgan.ac.id/jurnal/index.php/sinkron/article/view/11416 <p>Agriculture is an industrial sector that produces raw materials such as rice, corn, and agricultural products. In the current era, there should be no problem if there is a food shortage because society, industry, and education do not make a real contribution to supporting the agricultural industry. The state also needs good agricultural land, so that the state can fulfill the needs of its people. Without good agriculture, a country will not be able to meet the needs of its people. Modern society today is not or is rarely concerned with agriculture. Agriculture is carried out only by providing fertilizer, water, and land, paying attention to the quality of the agricultural land. One of the problems of declining agricultural production is crop failure. One of the reasons island for agriculture. Soil is the most important part of the world of agriculture. If the land is not cultivated then the land is difficult to become an ideal place for agriculture. The Internet of Things can be used as a solution to problems by tilling the soil and monitoring soil conditions. In conditions in the dry season, soil moisture needs to be done by water. In the rainy season, the land should not be flooded, let alone submerged and flooded. In order to maintain the balance of moisture and waterlogged soil, the Internet of Things is a solution for monitoring and managing agricultural land. Internet of Things is a device that can communicate with each other from one device to another, such as sensors and actuators. Good land cultivation makes agricultural land fertile. Agricultural land processing is maximized by adding a monitoring system for agricultural land using a micro-controller Arduino Uno, NodeMCU ESP8266, several sensors, and integrated devices. The purpose of this research is to make a prototype that is useful for monitoring agricultural land</p> Andrew Andrew Haryono Haryono Copyright (c) 2022 Andrew http://creativecommons.org/licenses/by-nc/4.0 2022-05-09 2022-05-09 7 3 846 852 10.33395/sinkron.v7i3.11416 K-NN Based Air Classification as Indicator of the Index of Air Quality in Palembang https://www.polgan.ac.id/jurnal/index.php/sinkron/article/view/11469 <p>Good air quality is something that is wanted by every human who lives in big cities. Clean air and no pollution is one of the proper environmental requirements. One of the most severe causes of air pollution is due to large-scale forest fires due to the long dry season or is carried out by irresponsible persons which they commonly refer to as land clearing in an easy and inexpensive way by utilizing the reason of the dry season. The purpose of this study is to classify air quality in Palembang using a data mining approach. Then use the results of the classification as an indicator of the level of air quality in the city of Palembang. The data mining approach that researchers use is the K-Nearest Neighbor algorithm. Based on the test results of K-NN calculations and measured using a confusion matrix produce an accuracy of 80 percent, 82.3 percent for precision, and 93.3 percent for recall. The measurement results show that the calculation using the K-NN algorithm can be used as an indicator in measuring air quality, of the 20 that have been trained and tested only 4 inaccurate data, this inaccuracy occurs because the source data has unbalanced classes such as unhealthy and very unhealthy healthy have 1 sample each. So it proves that the performance of classifiers using the K-NN algorithm relevant as an indicator of air quality levels in the city of Palembang.</p> Ahmad Sanmorino Juhaini Alie Nining Ariati Sanza Vittria Wulanda Copyright (c) 2022 Ahmad Sanmorino, Juhaini Alie, Nining Ariati, Sanza Vittria Wulanda http://creativecommons.org/licenses/by-nc/4.0 2022-07-09 2022-07-09 7 3 853 859 10.33395/sinkron.v7i3.11469 Code Mixing and Switching Used in Breakout Music Program of Net TV https://www.polgan.ac.id/jurnal/index.php/sinkron/article/view/11472 <p>Bilingual and multilingual people present language variety called Code – Mixing and Code – Switching. The purpose of this study is to find the kinds of code mixing and code switching that used by the hosts in Breakout a music program in Net TV and to conclude the factor that influence the hosts mix and switch their utterances. This study was done by using description/qualitative method. This study used three of selected episodes, each utterances in each episode changed into the scripts, and the scripts made into the table form. As the result of this study, in generally, the hosts used two kinds of Code Mixing, they are Intra sentential code mixing and extra sentential code mixing, and five kinds of Code Switching on their utterances (Situational, Metaphorical, Tag Code switching, Inter-sentential switching, and Intra-sentential switching). The hosts mix and switch their utterances influenced by the setting and scene, participants, ends, key, norm of interaction as described by Dell Hymes, and also found the other factors, they are background of language, topic and the limited Indonesian vocabularies which can be hazy if it puts in Indonesian.</p> Syahrul Efendi Lubis Dicky Hendrawan Copyright (c) 2022 Syahrul Efendi Lubis, Dicky Hendrawan http://creativecommons.org/licenses/by-nc/4.0 2022-07-11 2022-07-11 7 3 860 873 10.33395/sinkron.v7i3.11472 Development of Android-Based Early Reading Learning Media https://www.polgan.ac.id/jurnal/index.php/sinkron/article/view/11549 <p>Early reading is a skill that students should have. This skill becomes a provision for the next stage of skills .Learning to recognize letters, especially early reading in Golan Kindergarten during the pandemic, experienced problems. Students feel less interested when the learning process is carried out conventionally. In addition, parents also have difficulties when it comes to delivering material to children.&nbsp; Through the use of android-based learning media, the learning process is expected to attract students. The method developed the Borg &amp; Gall model, which consisted of ten stages. The data collection techniques used include observation, interviews, and questionnaires. Observation is used to find out the learning conditions in schools. Interviews, conducted with teachers to find out the use value of the media created. Meanwhile, the questionnaire is used as a reference to find out the level of needs in schools. The resulting learning media is tested through media expert validation tests and practicality tests. Validation of media experts to assess whether media is suitable for use as an alternative to learning media in schools. Practicality test, used to assess the level of practicality of the resulting medium. &nbsp;The results of media expert validation obtained a percentage of 81.5, stating that the media was valid. The practicality test was 8,262, and the mean score of students was 77. The two results presented that the android-based learning media for early reading was feasible</p> Estuning Dewi Hapsari Yoga Prisma Yuda Yoga Akmal Mubarok Copyright (c) 2022 Estuning Dewi Hapsari, Yoga Prisma Yuda, Yoga Akmal Mubarok http://creativecommons.org/licenses/by-nc/4.0 2022-07-13 2022-07-13 7 3 874 882 10.33395/sinkron.v7i3.11549 Optimization of Transaction Database Design with MySQL and MongoDB https://www.polgan.ac.id/jurnal/index.php/sinkron/article/view/11528 <p>Database is one of the most important parts in running an application. Databases can be used to store data. However, in running an application, the selection of an appropriate database needs to be considered, so that the resulting information can be in accordance with user needs. In developing applications, more people use RDBMS design which has a very structured nature, but technological developments have introduced NoSQL as a database development method. In this research, MySQL and MongoDB databases will be tested in transaction processing. The tests carried out include comparisons of database designs, comparisons of defining table structures, comparisons of running time in the insert, update, delete, search processes. The test results show that MongoDB has a simpler table description structure than MySQL. The results of the running time test show that MongoDB has a faster running time difference than MySQL. In the insert process there is a time difference of 0.005625 sec, update 0.001688 sec, delete 0.00075 sec and search 0.006875 sec.</p> Hani Atun Mumtahana Copyright (c) 2022 Hani Atun Mumtahana http://creativecommons.org/licenses/by-nc/4.0 2022-07-13 2022-07-13 7 3 883 890 10.33395/sinkron.v7i3.11528 Superior Class to Improve Student Achievement Using the K-Means Algorithm https://www.polgan.ac.id/jurnal/index.php/sinkron/article/view/11458 <p>The accumulation of new student data every year makes searching and processing data difficult, including selecting superior class students according to their talents and abilities. Therefore, the application of the K-Means Clustering data mining method is carried out to support decisions in grouping superior classes. The report card values ​​for each class were used as parameters with a data sample of 80 students and 3 clusters were taken which then resulted in the selection and distribution of superior classes. The purpose of the study was to classify students in the superior class so that they could improve student achievement at SMK Raksana 2 Medan. Results Based on the calculation of the variable distance at the initial centroid with a sample of 80 students and the third iteration, the WCV value is 360.9745 and the BCV value is 7.3575 with a ratio value of 0.0203. Each cluster, namely: Cluster 1 has 43 students including the superior class category. Cluster 2 has 18 students and Cluster 3 has 19 students. Clusters 2 and 3 are included in the regular class category with a total of 37 students. The web-based K-Means application can provide information and solutions needed by schools to classify and determine superior classes so that they can improve student achievement in schools. These results can be used by the school to analyze student achievement and can assist teachers in forming superior classes so as to motivate students to study harder.</p> Yopi Hendro Syahputra Juniar Hutagalung Copyright (c) 2022 Yopi Hendro Syahputra, Juniar Hutagalung http://creativecommons.org/licenses/by-nc/4.0 2022-07-14 2022-07-14 7 3 891 899 10.33395/sinkron.v7i3.11458 Sentiment Analysis About COVID-19 Booster Vaccine on Twitter Using Deep Learning https://www.polgan.ac.id/jurnal/index.php/sinkron/article/view/11485 <p>The rapid spread of COVID-19 cases to various countries has made the COVID-19 outbreak a global pandemic by the World Health Organization (WHO). The effect of the designation of COVID-19 as a pandemic has prompted the government to take preventive action against vaccination, as well as the WHO which has asked the public to immediately get a third or booster dose of vaccine. Various responses regarding the COVID-19 booster vaccine continue to emerge on social media such as Twitter. Twitter is often used by its users to express emotions about something either positive or negative. People tend to believe what they find on social networks, which makes them vulnerable to rumors and fake news. Sentiment analysis or opinion mining is one solution to overcome the problem of automatically classifying opinions or reviews into positive or negative opinions. In this study, the Deep Learning algorithm was used to analyze public opinion sentiment regarding the COVID-19 booster vaccine on Twitter. The data collection method used is crawling data using an access token obtained from the Twitter API. Meanwhile, to evaluate the model, the K-fold Cross-Validation method is used. The results of testing the model obtained the highest accuracy value at iterations = 10, which is 82.78% with AUC value = 0.836, precision = 83.33% and recall = 95.89%.</p> Elly Indrayuni Achmad Nurhadi Copyright (c) 2022 Elly Indrayuni, Achmad Nurhadi http://creativecommons.org/licenses/by-nc/4.0 2022-07-15 2022-07-15 7 3 900 905 10.33395/sinkron.v7i3.11485 The application of online practicum in assisting learning process of database courses using Waterfall method https://www.polgan.ac.id/jurnal/index.php/sinkron/article/view/11486 <p>The Open University is a State University prioritizing independent learning. Independent learning would certainly succeed if the students owned a strong determination in effectively and efficiently manage their time. In the Information Systems Study Program curriculum, there are several practical courses that must be conducted offline. In 2019 however, the phenomenon of the COVID-19 pandemic outbreak requiring all educational units to carry out learning from home had impacted on the learning process, especially the implementation of practicum at the Open University. The implementation of practicum activities usually held in collaboration with several institutions has become constrained. This triggered the possibility of not achieving student learning outcomes related to learning materials learned through practicum. Therefore, as an alternative solution, an application is required that could assist the students in carrying out practicum learning activities independently which is adapted to each teaching material. This practical application would be developed in a study using the Waterfall method consisting of analysis, design, implementation, testing and maintenance. From the results of test using the System Usability Scale (SUS), the score obtained is 64.44 (margin low). This means that the application online practicum can be used but does not meet the requirements to be implemented into existing learning systems until it gets a score of more than 80 (Acceptable).</p> Andri Suryadi Unggul Utan Sufandi Dian Nurdiana Copyright (c) 2022 Andri Suryadi, Unggul Utan Sufandi, Dian Nurdiana http://creativecommons.org/licenses/by-nc/4.0 2022-07-15 2022-07-15 7 3 906 914 10.33395/sinkron.v7i3.11486 Explanatory Data Analysis to Evaluate Keyword Searches for Educational Videos on YouTube with a Machine Learning Approach https://www.polgan.ac.id/jurnal/index.php/sinkron/article/view/11502 <p>One of the most important parts of data science is the process of explanatory data analysis. This study aims to analyze learning videos on YouTube using search keywords such as learning biology, chemistry, physics, computers, mathematics, management, accounting, citizenship, history, and culture. The method used is the explanatory data analysis technique with a Machine Learning approach. The dataset used in this study uses learning video search keywords found on the YouTube digital platform. After doing a thorough analysis of all existing variables, we found that in the context of searching for learning video keywords on YouTube, the viewing variable has a heatmap correlation of 0.97 on the likes variable, 0.97 on the subscribers variable, -0.15 on the duration variable and 0.95 on the comment variable. The duration variable negatively correlates with all variables based on the analysis using a correlation heatmap using the seaborn library. Our analysis found that the number of learning videos with the search keyword Mathematics had the highest number of views among other variables. Further research can use existing variables or also add variables and add search keywords on YouTube. The data analysis approach can also be done using SPSS, R and also a Machine Learning approach with different libraries.</p> Mambang Mambang Ahmad Hidayat Johan Wahyudi Finki Dona Marleny Copyright (c) 2022 Mambang Mambang, Ahmad Hidayat, Johan Wahyudi, Finki Dona Marleny http://creativecommons.org/licenses/by-nc/4.0 2022-07-19 2022-07-19 7 3 915 922 10.33395/sinkron.v7i3.11502 Analyze application Building Management of The Bank Indonesia representative office West Java https://www.polgan.ac.id/jurnal/index.php/sinkron/article/view/11443 <p>One of the facilities and assets owned by Bank Indonesia is an official residence intended for permanent employees, office buildings, and other facilities such as borrowing rooms and goods that can be used by employees to support office activities. But in the implementation of maintenance of official houses and office buildings as well as the process of requesting room loan and goods still done manually. Therefore, a Building Management application is needed that can help the maintenance activities of official house buildings and office buildings as well as the process of requesting the loan of rooms and goods. Building Management application is a software that is used for building maintenance and management of all building needs including borrowing space and goods in an office building. This study aims to accelerate the process of requesting repairs to official office buildings and office buildings as well as borrowing rooms and goods. In addition, this application also generates automatic report recording output. The method in this study use V-Model is an extension of the waterfall model and is based on the association of the testing phase to each appropriate development phase. The result in this study is application to be built is based on the website using the CodeIgniter framework and the V Models system development method with stages arranged starting from verification which contains the needs analysis stage, design to the coding phase and also the validation process that contains testing of the application to determine application functionality and also know the level application usability for the user.</p> Robby Rohman Sukarya Ade Yuliana Yudi Taryana Hizkia Samuel Ferlin Firdaus Turnip Copyright (c) 2022 Robby Rohman Sukarya, Ade Yuliana, Yudi Taryana, Hizkia Samuel, Ferlin Firdaus Turnip http://creativecommons.org/licenses/by-nc/4.0 2022-07-20 2022-07-20 7 3 923 934 10.33395/sinkron.v7i3.11443 Detection Malaria Base Microscope Digital Image with Convolutional Neural Network https://www.polgan.ac.id/jurnal/index.php/sinkron/article/view/11488 <p>Malaria is a tropical disease that infects human red blood cells caused by infection with the plasmodium parasite. Plasmodium parasites spread to humans through female Anopheles mosquitoes and can reproduce in human blood cells. Malaria is a health problem that is at risk of causing other health problems such as anemia and even death. The current gold standard for malaria diagnosis is laboratory diagnosis by microscopic examination to find the malaria parasite through the blood cells of the patient. However, the diagnosis of malaria through microscopic observation of blood cells has the potential to take a long time, because the plasmodium parasite has a very small size. The malaria detection system using the Convolutional Neural Network (CNN) method is designed to detect malaria in human blood cells. CNN is a machine learning method designed to classify objects in an image. The system was built in three stages of development, namely the development of a CNN model for malaria detection, software development and hardware development. The hardware components used in the system include Raspberry pi, Raspberry Pi camera module, and LCD. The results of the malaria detection test using the CNN model gave an accuracy of 98.76% which was tested on blood cell images from a microscope</p> Meida Cahyo Untoro Muhammad Muttaqin Copyright (c) 2022 Meida Cahyo Untoro, Muhammad Muttaqin http://creativecommons.org/licenses/by-nc/4.0 2022-07-23 2022-07-23 7 3 935 943 10.33395/sinkron.v7i3.11488 Performance Comparison of K-Means and DBScan Algorithms for Text Clustering Product Reviews https://www.polgan.ac.id/jurnal/index.php/sinkron/article/view/11569 <p>The purpose of this study was to compare the accuracy performance of the K-Means and DBScan algorithms in clustering product reviews. This comparison evaluated to determine which algorithm is better in terms of accuracy. The two algorithms were chosen because they have different methods of clustering, K-Means uses centroid-based while DBScan uses density-based. Text clustering results can be implemented on e-commerce platforms, marketplaces or product review platforms. This can help customers in deciding what product they will buy. One of the factors that customers have difficulty in determining what product they will buy is the number of reviews that each product has, and the difficulty in concluding the advantages of each product that will be matched their needs or desires. With text clustering, it can be easier and faster for customer to determine whether the product is worth buying or not based on the product reviews they read. The data set used in this study is a review of the Cetaphil Facial Wash product from the Female Daily website. Firstly, data set goes through the Text Pre-Processing stage; then it will be clustered using two algorithms, K-Means and DBScan. After that, the results of the clustering of the two algorithms calculated for their accuracy performance and the performance results obtained. From the results of this study, it concluded that, in the review clustering of Cetaphil Facial Wash products, DBScan has 99.80% accuracy, which higher to compare with K-Means with only has 99.50% accuracy.</p> Fitri Andriyani Yan Puspitarani Copyright (c) 2022 Fitri Andriyani, Yan Puspitarani http://creativecommons.org/licenses/by-nc/4.0 2022-07-25 2022-07-25 7 3 944 949 10.33395/sinkron.v7i3.11569 Case Study: Improved Round Robin Algorithm https://www.polgan.ac.id/jurnal/index.php/sinkron/article/view/11530 <p>In this journal, discussion is given to analyse the improved round robin algorithm more thoroughly. Round robin algorithm plays a significant role to be used in embedded systems. Round robin algorithm usually applied in real-time systems. Here, three case studies are given, and also the analysis of each case study. Comparisons are given about the average turn around time and average waiting time, also number of context switching between the three case studies. Improved round robin algorithm, is a modification from the generic round robin algorithm. In improved round robin algorithm if the remaining burst time is less than the time slice that is allocated, then the currently running process is continue to be executed. Then finish the currently running process from ready queue and execute the next ready queue. Three case studies are given with three different time quantum, which are 3, 4, and 5 ms. The result of this case study analysis is that, the efficiency of the quantum 5 ms is the most effective one. There is an increase of 50% context switching from quantum 3 to quantum 5. And for average turn around time we get 13.13% reduction in efficiency. While in average waiting time we get reduction 12.08% efficiency.</p> Tri Dharma Putra Rakhmat Purnomo Copyright (c) 2022 Rakhmat Purnomo, Tri Dharma Putra http://creativecommons.org/licenses/by-nc/4.0 2022-07-26 2022-07-26 7 3 950 956 10.33395/sinkron.v7i3.11530 Product Recommendation System Application Using Web-Based Equivalence Class Transformation (Eclat) algorithm https://www.polgan.ac.id/jurnal/index.php/sinkron/article/view/11454 <p><em>The use of saved transaction data can provide a lot of knowledge that useful to the company in making policy and find the strategy in Alfamidi. In applying that goal, that is using Market Business Analysis. One of the techniques of Data Mining is Association Rule, which is the procedure of Market Basket Analysis to find the customer buying patterns. This pattern can be one of the ways in making policy and business strategy. One pattern determined by two parameters, they are support (support value) and confidence (certainly value). This analysis used algorithm Equivalence Class Transformation (ECLAT). One of the patterns resulted from analysis to the 30 transaction data with 12 category items. As an instance, if we buy strawberry jam then buy essence of bread with confidence value = 1%. The results obtained an also be used in helping the Alfamidi to help in determine the inventory decisions. So, the conclusion may be taken if consumers could buy strawberry jam then bought essence of bread simultaneously, then the Alfamidi should at least maintain the availability stock of both these items in order to remain the same.</em></p> Mochzen Gito Resmi Teguh Iman Hermanto Miftah Al Ghozali Copyright (c) 2022 Mochzen Gito Resmi, Teguh Iman Hermanto, Miftah Al Ghozali http://creativecommons.org/licenses/by-nc/4.0 2022-07-26 2022-07-26 7 3 957 961 10.33395/sinkron.v7i3.11454 UI/UX Design of Ineffable Psychological Counseling Mobile Application Using Design Thinking Method https://www.polgan.ac.id/jurnal/index.php/sinkron/article/view/11582 <p>Application design is one of the important things in application development because the application that has a bad design will cause discomfort and confusion for users, especially in health applications, which have their own difficulties where application design must focus on what users need to be easy to understand, especially mental health application because there are still few application for mental health or self-care even though since the pandemic, mental health problems have increased drastically, this makes many people seek help in mental help. Design thinking is a method used to solve a problem where the solution comes from that user’s experiences or needs. The Design Thinking method consists of five stages: Empathize, Define, Ideate, Prototype, and Test. In the test step, testing was carried out using the Cognitive Walkthrough method with the help of the Maze tool with a learnability value of 97%, an error rate of 0.04, time-based efficiency of 0.05 task/second, and the MIUS value of each task were obtained a fairly high value indicating that design prototype is easy to use, easy to understand and efficient. While the MAUS score got a score of 94, which was included in the high level, indicating that the interface design was feasible to be implemented.</p> Meriska Defriani Lintang Nuril Islami Teguh Iman Hermanto Copyright (c) 2022 Meriska Defriani, Lintang Nuril Islami, Teguh Iman Hermanto http://creativecommons.org/licenses/by-nc/4.0 2022-07-27 2022-07-27 7 3 962 973 10.33395/sinkron.v7i3.11582 The prototype of IOT-Based weight scale and calorie tracking application https://www.polgan.ac.id/jurnal/index.php/sinkron/article/view/11580 <p>This research designs the prototype of Internet of Things based scale with calorie tracking application in purpose to help optimize the application of healthy lifestyle. This research is done through numerous steps including analysis of needs, designing the devices and system, software programming, device integration, device testing, and maintenance. This research developed Internet of Things based scale with sensor load cell and HX711 module as weight sensor component, Node MCU as microcontroller component, battery as voltage source, and firebase as database to store the result of body weight measurement. Android application developed with Android Studio, visual studio code, and java programming language. Internet of Things based scale is functioned to measure body weight in real-time which connected to android application to display body weight, calculate Body Mass Index (BMI), calculate daily calories needs including Basal Metabolic Rate (BMR) and Total Energy Expenditure (TEE), provide information of food calories and exercise and total calories recording to monitor daily intake and output.</p> Dita Ayu Chairunnisa Ahmad Taqwa Irma Salamah Copyright (c) 2022 Dita Ayu Chairunnisa, Ahmad Taqwa, Irma Salamah http://creativecommons.org/licenses/by-nc/4.0 2022-07-27 2022-07-27 7 3 974 983 10.33395/sinkron.v7i3.11580 Forecasting of Health Sector Stock Prices During Covid-19 Pandemic Using Arima And Winter Methods https://www.polgan.ac.id/jurnal/index.php/sinkron/article/view/11572 <p>This study aims to compare the accuracy of the ARIMA and WINTER methods in forecasting or predicting the daily stock price of the health sector. The data used in this study is secondary data in the form of historical data on the daily share price of PT. Darya Varia Laboratori, PT. Indofara Persero, PT. Kimia Farma, PT. Kalbe Farma, and PT. Merck Indonesia from March 14, 2020 to April 14, 2021. From the results of the research, PT. Kimia Farma is suitable to use the ARIMA (1, 0, 1) model, while others use the Additive and Multiplicative WINTER method. The daily stock price predictions of the five issuers from April 14, 2021 to July 15, 2021 tend to increase. This is presumably because investors tend to increase their capital due to the effect of health protocols that are getting tighter during the second wave and the assumption is that when the level of virus spread has begun to decline, the health sector shares will continue to rise, although not significantly.</p> Tamamudin Tamamudin Wilda Yulia Rusyida Copyright (c) 2022 Tamamudin, Wilda Yulia Rusyida http://creativecommons.org/licenses/by-nc/4.0 2022-07-28 2022-07-28 7 3 984 994 10.33395/sinkron.v7i3.11572 Tiktok Social Media Sentiment Analysis Using the Nave Bayes Classifier Algorithm https://www.polgan.ac.id/jurnal/index.php/sinkron/article/view/11579 <p>Social media is a computer application designed to make it simpler to communicate with others without having to do it face-to-face, as well as a tool for having fun and reducing feelings of isolation. Existing social media applications include games, music, and media for communicating with distant individuals, among others. These social media are utilized by parents, adolescents, and even young children. The application Tik-Tok is frequently used by children as a social networking platform. Tik-Tok has succeeded in grabbing the interest of youngsters, such that children are curious about creating short movies on the platform. Due to the fact that this application is used by children, the researcher seeks to use the <em>Naïve Bayes Classifier</em> Algorithm to recognize and differentiate unfavorable remarks on TikTok's social media. The rising number of negative remarks in the TikTok comments column can hinder the mental development of youngsters, and it is hoped that this algorithm would encourage users to post positive comments on this application. Based on the data gathering until the results of classification are obtained. There are 600 comments data randomly collected from TikTok users, gathered through the export comments website. After evaluating, the accuracy of the application of the <em>Naïve Bayes Classifier</em> algorithm in conducting sentiment analysis is 80% while the result of the AUC is 46%</p> Putri Suci Rahmadani Fenny Chintya Tampubolon Adelia Nurfattul Jannah Novia Lucky Halen Hutabarat Allwin M. Simarmata Copyright (c) 2022 Putri Suci Rahmadani, Fenny Chintya Tampubolon, Adelia Nurfattul Jannah, Novia Lucky Halen Hutabarat, Allwin M. Simarmata http://creativecommons.org/licenses/by-nc/4.0 2022-07-28 2022-07-28 7 3 995 999 10.33395/sinkron.v7i3.11579 Application of Huffman Algorithm and Unary Codes for Text File Compression https://www.polgan.ac.id/jurnal/index.php/sinkron/article/view/11567 <p>Technique in carrying out data compression is an important point in technological developments. With compression in data in the form of text can include many uses, including for data transfer, copying and for backing up data. From its uses, this aspect is important for data security. There are many compression techniques on the data, including using huffman algorithms and unary code. One of its applications will be implemented on a text data that is widely used by digital actors in storing important data. The data must not be known by unauthorized parties in accessing the data. Therefore, huffman algorithms and unary code can solve this problem. By compressing the selected data also encrypts it as an extra security. The Huffman algorithm is a lossless compression algorithm or a technique that does not change the original data, by converting the unit of data content into bits. So this algorithm is widely used in the compression process. The Unary Codes algorithm is also a lossless compression technique that is generally used by combining several modification techniques. In this unary codes algorithm, each symbol in the string will be searched for its frequency. Then sorted from the last order (descending). The use of these two text data compression techniques results in a file size that is smaller than the original but can be returned to the original data</p> Bayu Angga Wijaya Sarwando Siboro Mahendra Brutu Yelita Kristiani Lase Copyright (c) 2022 Bayu Angga Wijaya, Sarwando Siboro, Mahendra Brutu, Yelita Kristiani Lase http://creativecommons.org/licenses/by-nc/4.0 2022-07-30 2022-07-30 7 3 1000 1007 10.33395/sinkron.v7i3.11567 Api Service Infrastructure Using Kubernetes And Terraform Based On Microservices Ngoorder.Id https://www.polgan.ac.id/jurnal/index.php/sinkron/article/view/11522 <p>The growing number of ngorder.id service users causes traffic to Api Ngorder to be higher, so a new infrastructure is needed in order to maintain Api Ngorder uptime during high traffic and also maintain service stability. In the implementation process, Api scripts that are currently running on a monolith cluster will be divided into several categories and will be split into several kubernetes clusters. To support autoscale, a Horizontal Pod Autoscaler was added, and to route traffic it would use the Api Gateway from Amazon Web Service. In this infrastructure test, it is done by testing the logic script function using Katalon Studio and testing at the infrastructure level by doing a crash test in the form of failing to deploy and terminating the pod, as well as performing a stress test to test autoscaling in the cluster, the entire test can be run by performing a stress test on the php service pods. by setting the autoscaler parameter Memory Utilization Percentage 125%, 150% and 250%, proving that the HorizontalPodAutoscaler (HPA) as an autoscaler handler can function according to the targets and parameters that have been determined.</p> Azwar Riza Habibi Copyright (c) 2022 Azwar Riza Habibi http://creativecommons.org/licenses/by-nc/4.0 2022-07-30 2022-07-30 7 3 1008 1016 10.33395/sinkron.v7i3.11522 Analysis of e-Service quality performance at BKPSDM Lubuklinggau web-based using E-Govqual and Importance Perfomance Analysis (IPA) methods https://www.polgan.ac.id/jurnal/index.php/sinkron/article/view/11444 <p>The Agency for Personnel and Human Resources Development (BKPSDM) uses the E–Kinerja service system. E-performance is a system for measuring employee performance. E- Govqual is a method that has attributes for assessing service quality. E-Government Importance Performance Analysis (IPA) is an assessment analysis method to measure the quality of a service based on the level of importance and level of performance perceived by the user. The research was conducted with the concept of measuring service quality in the form of electronic services focused on a government website called E-Government Quality (E-Govqual). The results of the gap analysis at this stage are carried out to determine the level of gap or difference in expectations between user interests and perceived system performance or user perceptions of the service quality of the E-Kinerja system. In the analysis of the level of conformity, the measurement is carried out by calculating the comparison between the reality of the service perceived by the user and the expectation of the service that the user wants. Furthermore, the analysis process is carried out with Importance Performance Analysis (IPA) using quadrant analysis whose results are mapped into Cartesian with the importance and performance axes. Based on the final results, the calculation shows the average level of conformity of each indicator in the four E-Govqual variables. From the table, it can be seen that all the average values ​​of the suitability level of the 4 dimensions are 101%. These results indicate that the performance of each attribute in the E-Kinerja application can meet the expectations of users. Based on the final result of the variable calculation, the largest gap occurs in the Trust variable with an average value of 0.05, then the smallest gap is in the Reliability Variable with an average value of -0.05 variable.</p> Tri Puja Astuti Elmayati Elmayati Tri Hasanah Copyright (c) 2022 Tri Puja Astuti, Elmayati Elmayati, Tri Hasanah http://creativecommons.org/licenses/by-nc/4.0 2022-07-31 2022-07-31 7 3 1017 1027 10.33395/sinkron.v7i3.11444 Comparison of Drug Type Classification Performance Using KNN Algorithm https://www.polgan.ac.id/jurnal/index.php/sinkron/article/view/11487 <p>The error of decommissioning is a serious problem that is often faced in medicine. In the face of these problems, information technology has a very important role. One of the information technologies that can be used is to use the machine learning classification algorithm K-Nearest Neighbor KNN. KNN is a type of machine learning algorithm that can be applied to problems with classification and regression prediction. The classification of types of drugs for patients greatly affects the health of the patient. The patient data is processed and transformed to numbers, which are then divided into training data and test data from 90:10, 80:20, 70:30 and using the Cross Validation model. KNN works through the nearest neighboring value with a value of k = 3 calculated by the calculation of Euclidean Distance, and then evaluated using the Confusion Matrix. The performance of the KNN algorithm resulted in the highest Accuracy value of 98.33%, a Precision value of 98.8%, a Recall value of 96.2%, and an F-measure value of 97.48%. The performance is obtained from the sharing of training data and 90:10 test data. The data share results in high performance compared to other data shares, including using the Cross Validation model. And the lower the k value, the higher the value of the resulting performance. The results show that the performance of the KNN algorithm is working well.</p> Febri Aldi Irohito Nozomi Soeheri Soeheri Copyright (c) 2022 Febri Aldi, Irohito Nozomi, Soeheri http://creativecommons.org/licenses/by-nc/4.0 2022-07-31 2022-07-31 7 3 1028 1034 10.33395/sinkron.v7i3.11487 Customer Profile Prediction model based on classification through approach Support Vector Machine (SVM) https://www.polgan.ac.id/jurnal/index.php/sinkron/article/view/11608 <p>Nowadays the market is characterized globally, products and services are almost identical and there are many suppliers. The most important aspect in classifying data in data mining is classification. Classification techniques have been widely used in many problems in research. The purpose of this research is to build a model that can predict behavior based on the information of each customer<u>. </u>This research was conducted by making a Prediction Model of Customer Profile Based on Classification Through the Support Vector Machine Approach which aims to obtain a package prediction accuracy value that is suitable for WO (Wedding Organizer) customers in classifying based on the profile of prospective customers. In the optimization results on the SVM model kernel function, the linear and polynomial kernels get the same accuracy value on the training data of 99.29% and the testing data of 94.92%. The lowest accuracy value was obtained in the RBF kernel function of 97.16% on training data and 96.61% on testing data. the best precision class value in the data testing was obtained in the basic package at 100%. The total value of the appropriate prediction on the training data was obtained by 56 samples from a total of 59 samples, and 3 samples that did not match the prediction with an accuracy of 94.92% on the data testing</p> Ogiana Kiro Herman Mawengkang Elviawaty Muisa Zamzami Copyright (c) 2022 Ogiana Kiro, Herman Mawengkang , Muisa http://creativecommons.org/licenses/by-nc/4.0 2022-07-31 2022-07-31 7 3 1035 1043 10.33395/sinkron.v7i3.11608 UI/UX Design for Language Learning Mobile Application Chob Learn Thai Using the Design Thinking Method https://www.polgan.ac.id/jurnal/index.php/sinkron/article/view/11585 <p>Thai language is one of the most difficult languages to learn because the Thai language itself has a variety of consonants, vowels, and tones to determine vocabulary. The problem is people currently have in learning Thai is the lack of knowledge about each consonant, vowels, or tones. So that it makes some people who want to learn Thai feel confused. Therefore, a Thai language learning application design was made which aims to make it easier for people who want to learn Thai language and of course it is more practical because it is in a mobile form that can be accessed anywhere and anytime easily. Design thinking is a method known as a comprehensive thinking process that aims to create a solution. In design thinking are have five stages, namely Empathize, Define, Ideate, Prototype and Test. At the test stage, the method used is Single Ease Question. The Single Ease Question has seven Likert scales where for a value range of 4 – 5.9 it is included in the interpretation quite easily, and in the range of 6 – 6.9 the interpretation is easy and for a value of 7, the interpretation is very easy. The result obtained after testing the prototype to the respondents the value obtained is 6.6 with a minimum value of 6 and a maximum value of 7. Thus, the result of 6.6 are included in the category of being easy to use by users.</p> Ayumas Aura Krishnavarty Meriska Defriani Teguh Iman Hermanto Copyright (c) 2022 Ayumas Aura Krishnavarty, Meriska Defriani, Teguh Iman Hermanto http://creativecommons.org/licenses/by-nc/4.0 2022-08-01 2022-08-01 7 3 1044 1053 10.33395/sinkron.v7i3.11585 Edge Detection Of Potato Leaf Damage With Laplacian Of Gaussian Algorithm https://www.polgan.ac.id/jurnal/index.php/sinkron/article/view/11583 <p>The Potato plants are type young plant that easily attacked by pests and diseases, part of plant that often attacked by disease is leaves which can affect growth process and reduce crop yields. One way to determine if potato leaf is healthy or unhealthy is by using the edge detection method. Crop failure in potato plants can be detected through damage to leaves. The purpose of this study was to help facilitate identification type of damage to leaf margins of potato plants by applying the Laplacian of Gaussian algorithm. Based on results of testing on several research datasets sourced from the Agricultural Sector of the Karo Regency Government through an application of edge image detection on potato plant leaves through a grayscale, threshold and detection process with the Laplacian of Gaussian algorithm. It takes the longest time of 12.34 s with an error of 1.45 on the type of damage caused by aphids and at least 6.03 s with an error of 0.71 on the normal leaf edge detection results. Based on test results on 17 potato leaf images, the average test time is 8.45 s</p> <p>&nbsp;</p> Mawaddah Harahap Adrian Christian Wijaya Samuel Henock Hasangapon Pasaribu Giovan Sembiring Kenjiro Christian Ginting Copyright (c) 2022 Mawaddah Harahap, Adrian Christian Wijaya, Samuel Henock Hasangapon Pasaribu, Giovan Sembiring, Kenjiro Christian Ginting http://creativecommons.org/licenses/by-nc/4.0 2022-08-01 2022-08-01 7 3 1054 1058 10.33395/sinkron.v7i3.11583 Supervised Model for Sentiment Analysis Based on Hotel Review Clusters using RapidMiner https://www.polgan.ac.id/jurnal/index.php/sinkron/article/view/11564 <p>Customer feedback in the modern era like today is mostly presented in the form of digital reviews, including customer feedback at an inn or hotel, customer feedback is very valuable data where from this data the management can find out, identify and analyze the customer experience and what they need. With customer feedback in the form of digital reviews, it will allow a lot of data that can be obtained by hotel management and will provide many benefits if the data is processed correctly. To take advantage of large&nbsp; text review data, a combination of data mining and natural language processing techniques was chosen to process text in depth and efficiently. &nbsp;Text mining in the form of creating an opinion mining model using the Naïve Bayes classification algorithm is applied to find information and measure the main sentiments expressed in the reviewed text dataset, then the application of K-Means text grouping aims to group texts and get information about the main topics discussed from the content of the review dataset text in each group . By applying the constructed sentiment analysis model, approximately 90.90% accuracy results were obtained in reading texts and measuring sentiments related to hotel customer feedback data.</p> Revin Novian Juliadi Yan Puspitarani Copyright (c) 2022 Revin Novian Juliadi, Yan Puspitarani http://creativecommons.org/licenses/by-nc/4.0 2022-08-01 2022-08-01 7 3 1059 1066 10.33395/sinkron.v7i3.11564 Comparative Analysis of SAW and TOPSIS on Best Employee Decision Support System https://www.polgan.ac.id/jurnal/index.php/sinkron/article/view/11475 <p>The decision-making process has many assessment criteria needed as the basis for its assessment. A large number of problems regarding the length of time required in the decision-making process require decision-makers to find solutions. Decision Support System is one option that can be developed by decision makers because it can help improve efficiency and accuracy in the decision-making process.</p> <p>The process of developing decision support requires certain calculation methods as part of the processing. The methods that are quite widely used to build a decision support system include the Simple Additive Weighting (SAW) method and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method. This research aims to analyze the accuracy of the cases raised as solutions to decision-making problems. A dynamic decision support system has been successfully created to design dynamics in the calculation of the SAW method and the TOPSIS method. The system is evaluated and analyzed for its accuracy level based on manual calculations. The results obtained are the SAW system has an accuracy value of 65% and the TOPSIS system is 100%. Furthermore, the calculation of the accuracy value of the SAW and TOPSIS methods in order to find out the best method to use by taking parameters in the form of the same value results generated from the calculations of the two methods. The results obtained are the accuracy value of the SAW method of 40% and the TOPSIS method of 100% based on testing using 60 employee data and 8 criteria used.</p> Arizona Firdonsyah Budi Warsito Adi Wibowo Copyright (c) 2022 Arizona Firdonsyah, Budi Warsito, Adi Wibowo http://creativecommons.org/licenses/by-nc/4.0 2022-08-02 2022-08-02 7 3 1067 1077 10.33395/sinkron.v7i3.11475 Analysis of Air Quality Measuring Device Using Internet of Things-Based MQ-135 Sensor https://www.polgan.ac.id/jurnal/index.php/sinkron/article/view/11618 <p>Air is a gas that is indispensable for the survival of living beings. As the times progress, the air we breathe is increasingly not good for the health of living beings. In most situations, humans cannot tell the difference between good and bad air conditions. The purpose of this research is to design a tool that can monitor air quality in many places using an Internet of Things-based concept, the MQ-135 gas sensor and display it on a 16x2 LCD and Blynk application. This study uses a direct test method to identify gases around the MQ-135 sensor with the NodeMCU ESP 8266 as a controller. Air quality is divided into 5 categories, which consists of good, average, unhealthy, very unhealthy, and dangerous. After the air quality value is displayed on the 16x2 LCD screen, the user can monitor the air quality remotely using the blynk application on the smartphone. It can be concluded that the design of this tool can detect air quality in classrooms, vehicle exhaust fumes, gas lighters, house rooms, and burned paper. If the air quality is bad, the buzzer will release the sound to notify that the air quality is poor according to the index of air quality.</p> Delima Sitanggang Chris Samuel Sitompul Jao Han Suyanto Sharen Kumar Evta Indra Copyright (c) 2022 Delima Sitanggang, Chris Samuel Sitompul, Jao Han Suyanto, Sharen Kumar, Evta Indra http://creativecommons.org/licenses/by-nc/4.0 2022-08-05 2022-08-05 7 3 1078 1084 10.33395/sinkron.v7i3.11618 Classification of Covid-19 Patient Spread Rate By Age and Region With K-Means Algorithm https://www.polgan.ac.id/jurnal/index.php/sinkron/article/view/11603 <p>The Covid-19 virus is a new type of disease, the first case of covid-19 was found in Wuhan Province, China in 2019 with general symptoms such as pneumonia. This virus can grow rapidly and can cause serious infections and even death. Due to the very fast transmission of the virus, the WHO declared the Covid-19 virus a pandemic on March 11, 2020. Anyone can be infected with the covid-19 virus, from small children to the elderly. However, various ways have been done, but the cases of covid-19 continue to increase. Various ways have been done to reduce the spread of COVID-19 so that the Covid-19 virus does not spread quickly. Then data mining techniques are needed by implementing the K-Means algorithm because the K-Means algorithm can group data. In this study, 790 patient data were used for COVID-19 patients. The test resulted in 3 clusters grouped based on low, medium, and high categories with a DBI value of -0.332. In cluster 0 with a low category there are 3 districts, in cluster 1 with a medium category there is 1 sub-district, in cluster 2 with a high category, there are 6 districts. From the results of the test, it can be seen that the age susceptible to COVID-19 is 26 to 45 years.</p> Adya Zizwan Putra Ryan Wijaya Pinem Sehat Silalahi Fendianu Gulo Juan Antonio Adityo Liukhoto Copyright (c) 2022 Adya Zizwan Putra, Ryan Wijaya Pinem, Sehat Silalahi, Fendianu Gulo, Juan Antonio Adityo Liukhoto http://creativecommons.org/licenses/by-nc/4.0 2022-08-05 2022-08-05 7 3 1085 1989 10.33395/sinkron.v7i3.11603 E-government in the public health sector: kansei engineering method for redesigning website https://www.polgan.ac.id/jurnal/index.php/sinkron/article/view/11648 <p>The role of government health websites as a source of referrals and credible health information is very important, especially now that everything is digital. People use the internet and make health websites as the first step in finding health information, government policies related to health, and public health services. So it is very important to consider the user aspect in designing the appearance of an appropriate health website. This study utilizes the Kansei Engineering KEPack type 1 in analyzing various emotional factors related to the e-government website interface in the health sector. So that it can be found that the psychological emotional factors of users are important and become the main recommendations in the design of the website interface. We are focuses on user preferences for the e-government site interface of the Karawang District Health Office with the Kansei Engineering Type I approach. The Kansei Engineering study was conducted to analyze various emotional factors related to the user interface by comparing 5 specimens of e-Government sites in the health sector. A total of 20 kansei words were identified which were then processed using the multivariate statistical method Cronbach's Alpha (CA), Coefficient Correlation Analysis (CCA), Factor Analysis (FA). The result is that 4 kansei words have a high influence and successfully present a matrix of design element recommendations with 7 main elements and 45 sub-criteria for specific design elements.</p> Candra Zonyfar Maharina Maharina Copyright (c) 2022 Candra Zonyfar, Maharina http://creativecommons.org/licenses/by-nc/4.0 2022-08-07 2022-08-07 7 3 1990 1997 10.33395/sinkron.v7i3.11648 Combination Grouping Techniques and Association Rules For Marketing Analysis based Customer Segmentation https://www.polgan.ac.id/jurnal/index.php/sinkron/article/view/11571 <p>Changes in people's transaction behavior using the internet resulted in the exponential growth of e-commerce. With the growth of digital shopping transactions, it is difficult to predict customer segments and patterns using traditional mathematical models. Timely identification of emerging trends from large volumes of data plays a major role in business processes and decision making. This is different from previous research works that apply the RFM model based on K-Means Clustering to find potential customers as an ingredient in determining marketing targets. In this study, a clustering technique approach is proposed to classify customer data which is evaluated using the Davies Bouldin, Calinski Harabasz and Silhouette methods to determine the optimal number of clusters, then the results are used in the Apriori algorithm to find patterns of goods that are often purchased together. Based on the test results on the K-Means Clustering, Spectral Clustering, and Gaussian Mixture Model techniques produced 5 clusters with 76% more accurate the K-Means Clustering method than the other two methods so that it was determined as a method in the RMF model, then the results of customer grouping were used on the Apriori algorithm to find patterns of concurrent product purchases by customers that are expected to be useful in future marketing management.</p> Amir Mahmud Husein Dodi Setiawan Andika Rahmad Kolose Sumangunsong Andreas Simatupang Shela Aura Yasmin Copyright (c) 2022 Amir Mahmud Husein, Dodi Setiawan, Andika Rahmad Kolose Sumangunsong, Andreas Simatupang, Shela Aura Yasmin http://creativecommons.org/licenses/by-nc/4.0 2022-08-07 2022-08-07 7 3 1998 2007 10.33395/sinkron.v7i3.11571 Rice Plants Disease Identification Using Deep Learning with Convolutional Neural Network Method https://www.polgan.ac.id/jurnal/index.php/sinkron/article/view/11540 <p>Indonesia is an agricultural country where most of the population grows rice and most farmers cannot detect early if there is a pest attack on rice plants . This research discuss about deep learning implementation to classify or identify diseases in rice leaves using mobile application. This system will make users easily to diagnose diseases by displaying diagnostic results in the form of the name of the disease along with its taxonomy, disease description and drug recommendations for disease solutions. There are four classes of leaves used in this research, including healthy leaves, leaf blight, brown spot and potassium deficiency. The design of the model uses two approaches, one of them are modeling convolutional neural network from the scratch and modeling with transfer learning using inception v3 architecture. Both models will go through training process to produce a model that is ready to be used for classification. In application testing, a comparison is made between two models. From the tests that have been carried out, it is concluded that the system with model made using transfer learning approach, produce good accuracy with an accuracy of 90%. Meanwhile the System with the other model gain an accuracy of 62%. So when the data used in research are extremely low, it is best to use transfer learning as an approach to design a mode.</p> Sunu Jatmika Danang Eka Saputra Copyright (c) 2022 Sunu Jatmika, Danang Eka Saputra http://creativecommons.org/licenses/by-nc/4.0 2022-08-08 2022-08-08 7 3 2008 2016 10.33395/sinkron.v7i3.11540