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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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Integrated MCDM-AHP and MABAC for Selection Head of Branch Offices Akmaludin, Akmaludin; Suriyanto, Adhi Dharma; Iriadi, Nandang; Widianto, Kudiantoro
Sinkron : jurnal dan penelitian teknik informatika Vol. 8 No. 4 (2024): Article Research Volume 8 Issue 4, October 2024
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v8i4.13669

Abstract

Leadership changes are very urgent in maintaining organizational stability. A good relay can build significant strength in carrying out organizational operational activities, of course this must be done with good selection. The purpose of this writing is to provide a consistent picture of the selection of branch heads in carrying out business competition which is measured based on the competencies possessed by the selected employees. The barometer is determined based on eight criteria as an assessment that is declared objective by the leadership, namely critical thinking, communication, analyzing, creative and innovation, leadership, adaptation, cooperation, and public speaking. The method used will be implemented in an integrated manner from the two MCDM-AHP methods and the MABAC method. These two methods have similar applications to the selection process. MCDM-AHP is used to select eight criteria as determinants of weighting and the MABAC method is used to determine the ranking process assessment for integrated decision making. The results obtained based on the weighted matrices of the branch head office selection process were measurably obtained, namely that the first priority was held by A11 with a weight of 1,406. The results of the integrity of both methods can provide evidence of decision support for the branch head selection process consistently with optimal results. The ranking system can be regulated and utilized for the purposes of selecting leaders to be placed in other positions.
Designing Claim Systems in Health Insurance Companies with Microservices and Event-Driven Architecture Approach Sentosa, Steve; Makmur, Amelia; Santoso, Handri
Sinkron : jurnal dan penelitian teknik informatika Vol. 8 No. 3 (2024): Research Artikel Volume 8 Issue 3, July 2024
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v8i3.13677

Abstract

Through digital transformation, insurance companies, especially in the health sector, are increasingly adopting modern technologies to enhance efficiency and service quality. Health insurance allows individuals or families to mitigate the financial risks associated with high and unexpected medical expenses. One crucial area is insurance claim, where a fast and accurate process is key to customer satisfaction. This study proposes the design and architecture of an insurance claim system using a microservices and event-driven approach. This approach enables insurance companies to break down applications into separate components, facilitating scalability, flexibility, and easier maintenance. Additionally, with an event-driven approach, the system can quickly respond to changes and events in the business environment. A comprehensive analysis shows that implementing microservices and event-driven architecture in the insurance claim system can enhance overall system performance, scalability, and resilience. For insurance companies, adopting microservices and event-driven architecture can lead to increased operational efficiency, reduced time to market for new products, and improved customer experiences through faster claim processing. Policyholders will benefit from quicker claim resolutions and a more transparent and responsive claim process. This study provides valuable insights for health insurance companies looking to upgrade their IT infrastructure to meet future challenges. The findings from this research will be documented to support the development of insurance business technology, specifically for health insurance claims in Indonesia.
UX Analysis on SpeedID Application Using Usability Testing Method and System Usability Scale Arslayandi, Fiqhan; Sudipa, I Gede Iwan; Pramita, Dewa Ayu Kadek; Suryawan, I Gede Totok; Widiartha, Komang Kurniawan
Sinkron : jurnal dan penelitian teknik informatika Vol. 8 No. 3 (2024): Research Artikel Volume 8 Issue 3, July 2024
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v8i3.13678

Abstract

The SpeedID application is a smart city application developed by a subsidiary of PT Bamboomedia Cipta Persada, namely PT Inovasi Solusi Nusantara since 5 years ago. The SpeedID application wants to present a solution to the city's problems to become a new digital identity for the smart city community. Because it was only developed 5 years ago, the SpeedID application is classified as a new application and has never been analyzed for usability before. Usability analysis is carried out to improve user experience, so that the SpeedID application can be accepted and used more easily by users. This research uses Usability Testing method with Performance Measurement and Retrospective Think Aloud (RTA) techniques and System Usability Scale (SUS). The results obtained are the SpeedID application has a quality that cannot be said to be effective, efficient and meet user satisfaction. In addition, the average score of the System Usability Scale (SUS) Questionnaire is 70.33. The score is rated "C" with an adjective rating of "Good" with the acceptance range included in the "Marginal" category, and finally the net promotion score (NPS) is included in the "Passive" category, which explains that the use of the SpeedID application gets an assessment that is still marginalized by its users. This shows that the SpeedID application still urgently needs correction to improve quality to its users and design improvements also need to be made so that the SpeedID application is even better at meeting user expectations in the future.
Implementing Moving Average Forecasting System for Apparel Sales: Predicting Inventory Needs with Enhanced Accuracy Tazkiyah, Ivfa Tut; Wardoyo, Ari Eko; Rintyarna, Bagus Setya
Sinkron : jurnal dan penelitian teknik informatika Vol. 8 No. 3 (2024): Research Artikel Volume 8 Issue 3, July 2024
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v8i3.13686

Abstract

Forecasting the supply of goods is one of the company's planning strategies to increase sales. However, there are several obstacles in forecasting the supply of goods in one of the boutiques in Jember Regency such as manual sales data collection, namely by recording clothing sales data in the sales book. So that   there can be errors in predicting the supply of goods in the future. The purpose of this study is to apply a clothing sales forecasting system using the moving average method to forecast the supply of goods. This study applies the waterfall model to build a system with stages of analysis, design, implementation and testing. Analysis will be carried out by collecting data related to system requirements through observation, interviews and literature studies. While at the design stage there are usecase diagrams and system flow diagrams. Furthermore, the implementation stage was carried out in boutiques in Jember Regency by piloting the boutique owners. System testing uses black box testing to ensure there are no system functional errors. The findings show that the system in the form of a website can be run properly and can be accessed as long as there is an internet network. In addition, our system is already running well based on the results of black box testing. So that this system can be used by companies as forecasting considerations in providing inventory of goods.
A Modification Depth First Search (DFS) Algorithm for Troubleshoot Rotating Equipment Diagnosis Urva, Gellysa; Desriyati, Welly
Sinkron : jurnal dan penelitian teknik informatika Vol. 8 No. 3 (2024): Research Artikel Volume 8 Issue 3, July 2024
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v8i3.13690

Abstract

Rotating Equipment has a role in the industrial production process. There are times when the equipment that is being operated has trouble. Operators have difficulty dealing with problems of rotating equipment due to limited knowledge. To solve this problem we must have an  expert with knowledge and experience. Based on this, the problem is building an expert system application to diagnose troubleshoot on rotating equipment which aims to transfer the knowledge that an expert has into the computer so that operator can find out what problems occur. This paper use  Depht First Search (DFS) method, namely inward tracing techniques and Forward Chaining, namely the inference method that uses reasoning where to test a hypothesis starts from a fact. This system is equipped with an expert menu for knowledge management, so that experts can add, edit, and delete knowledge. The results showed that DFS and Forward Chaining are very suitable for diagnosing troubleshooting on Rotating Equipment. Based on the reasoning of the experts in their field and adjusted to the symptoms experienced by equipment so that the type of damage is found. It can also assist operators in diagnosing troubleshoot on Rotating Equipment so that operators can take preventive action to prevent further damage to the equipment.
Comparative Analysis of Machine Learning Algorithm Performance in Predicting Stunting in Toddlers Syahfitri, Nur’aini Indah; Juledi, Angga Putra; Muti’ah, Rahma
Sinkron : jurnal dan penelitian teknik informatika Vol. 8 No. 3 (2024): Research Artikel Volume 8 Issue 3, July 2024
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v8i3.13698

Abstract

Stunting is a condition where the growth of children and toddlers is stunted, which causes children to be shorter than they should be. In the long term, stunting can reduce reproductive health, study concentration, and work productivity, thereby causing significant state losses. The prevalence of stunting in Indonesia, which is still above 20 percent, shows that there are still chronic nutritional problems among toddlers. To prevent this from happening, identification as early as possible can be done using machine learning for predictions. The aim of this research is to conduct a comparative analysis of the performance of machine learning algorithms for predicting stunting in toddlers. Random Forest, K-Nearest Neighbors, and Extreme Gradient Boosting are the algorithms that are compared for their performance. The performance of each algorithm is measured using evaluation matrices such as accuracy, precision, recall, and f1-score. The research method starts with data collection, data preprocessing, data splitting, application of machine learning algorithms, evaluation of algorithm performance, and comparison of results. The performance evaluation matrix measurement results show that Random Forest has an accuracy of 99.95%, precision of 99.89%, recall of 99.94%, and f1-score of 99.91%. K-Nearest Neighbors has an accuracy of 99.93%, precision of 99.87%, recall of 99.88%, and f1-score of 99.88%. Meanwhile, Extreme Gradient Boosting has an accuracy of 99.36%, precision of 98.86%, recall of 98.95%, and f1-score of 98.90%. From the results of all performance evaluation matrices, it can be concluded that the random forest algorithm is the best algorithm for predicting stunting in toddlers.
Breast Cancer Classification Through CT Scan Using Convolutional Neural Network (CNN) Loi, Anita; Panjaitan, Ruth N; Siregar, Saut Dohot; Simarmata, Allwin M
Sinkron : jurnal dan penelitian teknik informatika Vol. 8 No. 3 (2024): Research Artikel Volume 8 Issue 3, July 2024
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v8i3.13706

Abstract

A common disease suffered by Indonesian women is breast cancer. Early awareness of breast cancer is very important to minimize the negative impact and increase the chances of recovery for breast cancer patients. Breast cancer detection efforts using CT scan image technology. CT scan images provide a detailed picture of the internal structure of the breast, allowing the identification of pathological changes that may be early signs of breast cancer. The purpose of the study is to utilize CNN algorithm for breast cancer classification using CT scan images. The dataset used consists of three labels namely benign cancer, malignant cancer, normal. The three data sets consist of 1096 data. CNN is a type of algorithm in the field of artificial intelligence that has proven successful in pattern recognition on image data. The collected breast CT scan image dataset includes breast cancer and non-breast cancer cases. The data is used to train and test the CNN model. Furthermore, breast cancer classification through CT scans is carried out by applying the CNN method. The results of the research conducted obtained an accuracy of 97.26%. In Benign classification with precision 0.99 (99%), recall 0.96 (96%), f1-score 0.98 (98%), support 186, then Malignant classification with precision 93% or with points 0.93, recall 98% with points 0.98, and f1-score 96% with points 0.96, and support 202. The last is the normal classification with 99% precision with 0.99 points, 97% recall with 0.97 points, 98% f1-score with 0.93 points, and 269 support.
Augmented Reality Learning Media Application In Computer Networking Courses Adi, Novi Hendri; Lubis, Arina Luthfini; Basriadi , Ali; Dewi, Ika Parma; Wahdi, Yera Wahda
Sinkron : jurnal dan penelitian teknik informatika Vol. 8 No. 3 (2024): Research Artikel Volume 8 Issue 3, July 2024
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v8i3.13707

Abstract

In computer network learning, there is still little use of media which has an impact on students' understanding of device material and computer network topology. Augmented Reality (AR) based learning media can answer these problems by providing dynamic visualization and interactive simulations. The research objective is that AR applications can be used to help visualize abstract concepts for understanding and structure of an object model. The development method used is MDLC (Multimedia Development Life Cycle) which consists of six stages, namely concept, design, material collecting, assembly, testing, and distribution. The results of the AR application research show that the value of the learning media application in terms of material is declared valid at 0.85 and in terms of design it is declared valid at 0.86. The AR application was also stated to be very practical, this can be seen from the responses of lecturers and students with the practicality of the learning media application being 87% as seen from ease, motivation, attractiveness, and usefulness. From the results of this research, the AR learning media application is very practical to apply to students, especially in computer networking courses.
A Literature Review: Development of Electronic Medical Records In Hospital Management Information Systems Yudhistira, Dhau 'Atha; Ernawaty; Nadena Majeda Dien Pratami
Sinkron : jurnal dan penelitian teknik informatika Vol. 8 No. 3 (2024): Research Artikel Volume 8 Issue 3, July 2024
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v8i3.13713

Abstract

Introduction: Health technology today is developing very quickly from the initially conventional using paper to being computerized. This literature review aims to map and critically summarize the scientific evidence on the cost-effectiveness and acceptability of Computerized Physician Order Entry (CPOE) and Electronic Health Reports. This Journal have Question that need to be answered how does the development of CPOE in medical records affect cost-effectiveness improvement so that it can be accepted by many parties? Method used in this journal is literature review is conducted on journal articles related to costs and receipts in CPOE. The systematic search was conducted from 5 databases namely PubMed, Science Direct, ProQuest, DOAJ and Ebscohost. Journal articles are selected and selected following PRISMA guidelines. Twenty-five journal articles qualified based on predetermined criteria. At the end as result, Cost-effectiveness with CPOE is more likely to be found that it is easier to reach compared to conventional methods. In addition, the acceptance of patients and health workers is also high. These factors can have a positive or negative influence on the hospital management system because developing countries still need adequate resources so that they can run these methods. Discussion and conclusion CPOE systems can improve patient safety by detecting drug interactions and actions. It is necessary to develop medical records in order to provide effective financing and acceptance.
Sentiment Analysis of Genshin Impact on X: Mental Health Implications Using TF-IDF and Support Vector Machine Jaya, Sava Irhab Atma; Junta Zeniarja
Sinkron : jurnal dan penelitian teknik informatika Vol. 8 No. 3 (2024): Research Artikel Volume 8 Issue 3, July 2024
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v8i3.13716

Abstract

Genshin Impact are now an integral part of daily life for many, potentially influencing mental well-being. Sentiment analysis window into these emotional effects, especially given the varied findings on gaming's impact on mental health. Analyzing X responses Genshin Impact using Support Vector Machine crucial, given its effectiveness in sentiment analysis. This study aims to deepen our understanding game's psychological impact and support development mental health interventions for gamers. The SVM classification report shows promising precision: 0.68 for Negative, 0.63 for Neutral, and 0.72 for Positive sentiment. However, recall rates favor Positive reviews (0.87) over Negative (0.56) and Neutral (0.51), reflected in the F1 score, highest for Positive sentiment at 0.79. With 174 Negative, 216 Neutral, and 333 Positive support counts, model achieved an overall accuracy of 0.69, effectively classifying Genshin Impact reviews based on sentiment. Analysis findings suggest a prevalence of positive opinions, indicating widespread player satisfaction with the game.

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