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Sinkron : Jurnal dan Penelitian Teknik Informatika
Published by Politeknik Ganesha Medan
ISSN : 2541044X     EISSN : 25412019     DOI : 10.33395/sinkron.v8i3.12656
Core Subject : Science,
Computer Science & IT
Scope of SinkrOns Scientific Discussion 1. Machine Learning 2. Cryptography 3. Steganography 4. Digital Image Processing 5. Networking 6. Security 7. Algorithm and Programming 8. Computer Vision 9. Troubleshooting 10. Internet and E-Commerce 11. Artificial Intelligence 12. Data Mining 13. Artificial Neural Network 14. Fuzzy Logic 15. Robotic
Arjuna Subject : Ilmu Komputer (semua kategori) - Visi Komputer dan Pengenalan Pola
Articles 1,196 Documents
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Forecasting of Health Sector Stock Prices During Covid-19 Pandemic Using Arima And Winter Methods Tamamudin, Tamamudin; Rusyida, Wilda Yulia
Sinkron : jurnal dan penelitian teknik informatika Vol. 6 No. 3 (2022): Article Research Volume 6 Number 3, July 2022
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v7i3.11572

Abstract

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.
ANALISIS SENTIMEN TIK TOK PADA MEDIA SOSIAL DENGAN ALGORITMA NAIVE BAYES CLASSIFIER Rahmadani, Putri Suci; Tampubolon, Fenny Chintya; Jannah, Adelia Nurfattul; Hutabarat, Novia Lucky Halen; Simarmata, Allwin M.
Sinkron : jurnal dan penelitian teknik informatika Vol. 6 No. 3 (2022): Article Research Volume 6 Number 3, July 2022
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v7i3.11579

Abstract

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 Naïve Bayes Classifier 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 Naïve Bayes Classifier algorithm in conducting sentiment analysis is 80% while the result of the AUC is 46%
UI/UX Design of Ineffable Psychological Counseling Mobile Application Using Design Thinking Method Defriani, Meriska; Lintang Nuril Islami; Teguh Iman Hermanto
Sinkron : jurnal dan penelitian teknik informatika Vol. 6 No. 3 (2022): Article Research Volume 6 Number 3, July 2022
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v7i3.11582

Abstract

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.
Edge Detection Of Potato Leaf Damage With Laplacian Of Gaussian Algorithm Harahap, Mawaddah; Wijaya, Adrian Christian; Pasaribu, Samuel Henock Hasangapon; Sembiring, Giovan; Ginting, Kenjiro Christian
Sinkron : jurnal dan penelitian teknik informatika Vol. 6 No. 3 (2022): Article Research Volume 6 Number 3, July 2022
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v7i3.11583

Abstract

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
UI/UX Design for Language Learning Mobile Application Chob Learn Thai Using the Design Thinking Method Krishnavarty, Ayumas Aura; Defriani, Meriska; Hermanto, Teguh Iman
Sinkron : jurnal dan penelitian teknik informatika Vol. 6 No. 3 (2022): Article Research Volume 6 Number 3, July 2022
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v7i3.11585

Abstract

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.
Klasifikasi Tingkat Penyebaran Pasien Covid-19 Berdasarkan Usia dan Wilayah Dengan Algoritma K-Means Putra, Adya Zizwan; Pinem, Ryan Wijaya; Silalahi, Sehat; Gulo, Fendianu; Liukhoto, Juan Antonio Adityo
Sinkron : jurnal dan penelitian teknik informatika Vol. 6 No. 3 (2022): Article Research Volume 6 Number 3, July 2022
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v7i3.11603

Abstract

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.
MODEL PREDIKSI PROFIL PELANGGAN BERDASARKAN KLASIFIKASI MELALUI PENDEKATAN SUPPORT VECTOR MACHINE Kiro, Ogiana; Mawengkang , Herman; Zamzami, Elviawaty Muisa
Sinkron : jurnal dan penelitian teknik informatika Vol. 6 No. 3 (2022): Article Research Volume 6 Number 3, July 2022
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v7i3.11608

Abstract

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. 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
Analysis of Air Quality Measuring Device Using Internet of Things-Based MQ-135 Sensor Sitanggang, Delima; Sitompul, Chris Samuel; Suyanto, Jao Han; Kumar, Sharen; Indra, Evta
Sinkron : jurnal dan penelitian teknik informatika Vol. 6 No. 3 (2022): Article Research Volume 6 Number 3, July 2022
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v7i3.11618

Abstract

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.
E-government in the public health sector: kansei engineering method for redesigning website Zonyfar, Candra; Maharina, Maharina
Sinkron : jurnal dan penelitian teknik informatika Vol. 6 No. 3 (2022): Article Research Volume 6 Number 3, July 2022
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v7i3.11648

Abstract

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.
Discrete Optimization Model in Constructing Optimal Decision Tree Azwar, Nurul Azri; Gultom, Parapat; Sawaluddin, Sawaluddin
Sinkron : jurnal dan penelitian teknik informatika Vol. 6 No. 3 (2022): Article Research Volume 6 Number 3, July 2022
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v7i3.11592

Abstract

Decision trees have been well studied and widely used in knowledge discovery and decision support systems. One of the applications of binary integer programming to form decision trees or decision making is the knapsack problem. The knapsack problem is an integer programming problem that involves only one constraint. The knapsack problem is generally illustrated with a bag and an item. The problem to be solved is to maximize the price of goods with a certain capacity that can be loaded by a bag with a certain capacity too. In solving the knapsack problem, it can generally be done directly. In this paper we are interested to show how the implicit enumeration method solves the knapsack problem to form an optimal decision tree

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