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Journal of Computer Science and Informatics Engineering
Published by Ali Institute of Research and Publication
ISSN : -     EISSN : 28278356     DOI : -
Core Subject : Science,
Computer Science & IT
Artificial Intelligence Machine Learning Natural Language Processing Computer Vision Text Speech Text Mining Data mining Cryptography Data visualization Expert System Deep Learning Fuzzy Logic IoT and smart environments Neural Networks Pattern Recognition Image Processing Optimization Digital Signal Processing Networking Technology Web intelligence
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 3 Documents
 1 
Search results for , issue "Vol 5 No 2 (2026): April" : 3 Documents clear
Implementation of TOPSIS Method in Determining UKK and UKM Interests Among Students at UIN Bukittinggi Furqon, Jamaluddin Effendi; Annas, Firdaus; Yuspita, Yulifda Elin; Darmawati, Gusnita
Journal of Computer Science and Informatics Engineering Vol 5 No 2 (2026): April
Publisher : Ali Institute of Research and Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55537/cosie.v5i2.1644

Abstract

This study is motivated by the declining level of student interest in UKM and UKK organizations on campus over the years. One of the main issues is that many students feel mismatched with the UKK/UKM they selected after joining. Therefore, a decision support system is proposed to address this problem. The objective of this research is to analyze the implementation of a Decision Support System (DSS) using the TOPSIS method in determining students’ preferences for UKK/UKM at UIN Sjech M. Djamil Djambek Bukittinggi. This study applies an applied research approach with TOPSIS as the data analysis method. The evaluation includes accuracy testing between manual calculations and system results, as well as sensitivity testing using the SAW method. The results show that the TOPSIS-based DSS utilizes eight benefit criteria: interest, talent, UKK/UKM description, activity division, activity schedule, recruitment system, membership requirements, and flagship programs. The alternatives include all UKK/UKM at UIN SMDD Bukittinggi. The accuracy test produced a score of 73.23% from 1,188 student data samples, indicating that the system is feasible. Furthermore, the sensitivity test shows a comparison value of 0.13% for SAW and 15.58% for TOPSIS, indicating that TOPSIS is more relevant for this case.
E-Commerce Customer Segmentation using the CLARANS Algorithm Berutu, Elimiana; Lubis, Andre Hasudungan
Journal of Computer Science and Informatics Engineering Vol 5 No 2 (2026): April
Publisher : Ali Institute of Research and Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55537/cosie.v5i2.1656

Abstract

Customer segmentation is an important step in supporting marketing strategies on E-Commerce platforms. This study aims to cluster customers based on their characteristics and transaction behavior using the CLARANS (Clustering Large Applications based upon Randomized Search) algorithm. The dataset used consists of E-Commerce customer attributes, including age, average transaction value, total orders, customer loyalty, and churn risk. The research stages include data collection, data cleaning, feature engineering, exploratory data analysis (EDA), algorithm implementation, and clustering evaluation. The evaluation was conducted using Silhouette Score, Davies–Bouldin Index, and Calinski–Harabasz Index, and benchmarked against K-Means and Hierarchical Clustering methods. The results show that the CLARANS algorithm provides the best performance with a Silhouette Score of 0.381991, Davies–Bouldin Index of 1.061123, and Calinski–Harabasz Index of 3458.564. These findings indicate that CLARANS is capable of producing more compact and well-separated clusters, making it effective for customer segmentation in E-Commerce data
Football Player Position Decision Support System Using MOORA Hamidah, Huwanda; Musril, Hari Antoni; Zakir, Supratman; Darmawati, Gusnita
Journal of Computer Science and Informatics Engineering Vol 5 No 2 (2026): April
Publisher : Ali Institute of Research and Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55537/cosie.v5i2.1663

Abstract

This study aims to design a decision support system to determine football player positions objectively in extracurricular activities at SMA N 1 Matur. The main problem is that player positioning is still determined subjectively based on the coach’s observations, resulting in less optimal placement. This research used the Research and Development (R&D) method with the Agile development model. The system was developed as a web-based application using PHP and MySQL, while the MOORA method was applied to calculate and determine player positions based on several assessment criteria. System testing referred to the ISO/IEC 25010 standard, including functional suitability, compatibility, and usability aspects. The testing results showed that functional suitability and compatibility achieved 100%, while usability obtained a score of 0.928 in the very feasible category. The system validity result reached an average score of 0.938, and the system calculation results were consistent with manual calculations. The novelty of this study lies in the implementation of the MOORA method in a web-based decision support system to determine football player positions more objectively and systematically.

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