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All Journal Computer Based Information System Journal Edu Cendikia: Jurnal Ilmiah Kependidikan Computer & Science Industrial Engineering Journal
Darmansah Darmansah
Universitas Putera Batam
Humanities Computer Science & IT Control & Systems Engineering Education Languange, Linguistic, Communication & Media Library & Information Science Social Sciences Other

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Penerapan Model Support Vector Machine dalam Prediksi Keberhasilan Belajar Pemrograman: Application of Support Vector Machine Model in Predicting Programming Learning Success Sarah Astiti; Budy Satria; Yeyi Gusla Nengsih; Sandi Fadilah; Darmansah Darmansah
Edu Cendikia: Jurnal Ilmiah Kependidikan Vol. 6 No. 01 (2026): Research Articles, April 2026
Publisher : ITScience (Information Technology and Science)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/educendikia.v6i01.8061

Abstract

Programming learning success is an important indicator in information technology education; many students still struggle to understand algorithmic concepts, logic, and code implementation. This problem indicates that a data-driven approach is needed to identify students' initial successes and failures in programming learning. The purpose of this study is to develop and validate a predictive model for programming learning success using Support Vector Machine (SVM), a classification algorithm. This research method includes steps such as data collection and preprocessing, feature selection, splitting the dataset into training and test sets, training the SVM model with parameter optimization, and evaluating performance using the test set. The results show that the SVM model achieves good classification performance with an accuracy of 87.5%, precision of 85.7%, F1 score of 87.8%, and AUC of 0.91, placing it in the excellent category. These findings indicate that the model has strong discriminatory power in distinguishing between successful and unsuccessful students. Therefore, the SVM method has been proven effective as a data-driven prediction system. This also allows for the development of more targeted and adaptive learning intervention strategies and academic decision-making.
IMPLEMENTASI FRAMEWORK DELONE DAN MCLEAN UNTUK MENGUKUR KEPUASAN DAN KEAMANAN PADA PENGGUNA APLIKASI M-BANKING Winson Winson; Darmansah Darmansah
Computer Science and Industrial Engineering Vol 14 No 01 (2026): Comasie Vol 14 No 1
Publisher : LPPM Universitas Putera Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33884/comasiejournal.v14i01.11096

Abstract

The development of digital technology has transformed conventional banking services into application-based services, one of which is mobile banking. MyBCA Mobile is the latest application from Bank Central Asia that offers various modern features, but still faces user complaints regarding system stability, slow OTP (On-Time Transaction) requests, and login issues. This condition necessitates a more in-depth evaluation of user satisfaction and perceived security. This study uses the Information System Success Model framework from DeLone & McLean with the addition of a security dimension to measure system quality, information quality, service quality, user satisfaction, and perceived net benefits. The research method used is quantitative, through the distribution of questionnaires to MyBCA Mobile users. Data were analyzed using validity and reliability tests, and multiple linear regression analysis. The results show that system quality, service quality, and security have a significant effect on user satisfaction, while information quality and usage have no significant effect. User satisfaction has been shown to have a significant effect on net benefits. The conclusion of this study indicates that system stability, service quality, and security are the main factors in increasing satisfaction and perceived benefits of using MyBCA Mobile.
EKSPLORASI DATA PENJUALAN DI PT ABP UNTUK MENGUNGKAP FAKTA-FAKTA SEGMENTASI KONSUMEN PROPERTI MENGGUNAKAN ALGORITMA K-MEANS CLUSTERING Stefanus Stefanus; Darmansah Darmansah
Computer Science and Industrial Engineering Vol 14 No 01 (2026): Comasie Vol 14 No 1
Publisher : LPPM Universitas Putera Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33884/comasiejournal.v14i01.11099

Abstract

Housing sales data in property companies are commonly utilized only for administrative purposes, limiting their potential to generate strategic insights into consumer behavior and purchasing patterns. PT Adi Bintan Permata possesses a substantial volume of housing sales transaction data, yet this data has not been systematically analyzed to support data-driven marketing decisions. This study aims to identify consumer segmentation in the property sector at PT Adi Bintan Permata by applying the K-Means clustering algorithm. A quantitative descriptive research approach was employed using housing sales data from January 2022 to June 2025. The variables analyzed include housing selling price, housing unit type, and payment method. Data processing followed the Knowledge Discovery in Databases (KDD) framework, while the optimal number of clusters was determined using the Elbow Method and Silhouette Coefficient. The clustering process was conducted using RapidMiner and Google Colaboratory. The results reveal three distinct consumer clusters with different purchasing characteristics. These findings indicate that K-Means clustering is effective for property consumer segmentation and provides meaningful insights to support more targeted and effective marketing strategies.
EKPLORASI DATA PENJUALAN DI OTOXPERT MENGGUNAKAN ALGORITMA APRIORI Jeky Jeky; Darmansah Darmansah
Computer Science and Industrial Engineering Vol 14 No 01 (2026): Comasie Vol 14 No 1
Publisher : LPPM Universitas Putera Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33884/comasiejournal.v14i01.11210

Abstract

This study aims to explore sales transaction data of spare parts at OTOXPERT Batam usingthe Apriori algorithm to identify association patterns among products. The main problemaddressed is that transaction data, although available in large quantities, has not beenoptimally utilized to uncover relationships between spare parts, so the potential use of thesepatterns to support cross-selling activities and stock management has not been fullyrealized. The data used in this study were sales transactions from January 1 to March 31,2025. The research method includes data preprocessing, transformation of transaction datainto basket form, descriptive analysis, and the application of the Apriori algorithm usingsupport, confidence, and lift parameters. The results show that the Apriori algorithm is ableto discover frequent itemsets and association rules that describe the tendency of spareparts to be purchased together. These patterns provide meaningful information aboutcustomer purchasing behavior and can be used as supporting information in decisionmaking related to sales strategies and inventory management. Therefore, this studydemonstrates that the Apriori algorithm is effective in transforming transaction data intovaluable information for business analysis at OTOXPERT Batam.
Perancangan Sistem Informasi Geografis Untuk Pemetaan Rumah Kos Berbasis Web Di Kota Batam les lie mervin; Darmansah Darmansah
Computer Based Information System Journal Vol. 13 No. 1 (2025): CBIS Journal
Publisher : Universitas Putera Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33884/cbis.v13i1.9577

Abstract

The design of this system is done to develop a web-based Geographic Information System (GIS) to help map boarding houses in Batam City. The development of this system is done using the Extreme Programming (XP) method, which emphasizes short iterations, and collaboration between developers and users. This system is designed by providing information about boarding houses. such as, boarding house location, facilities, prices, boarding house photos, boarding house types, boarding house web addresses, and their availability. The main features developed are mapping of boarding house locations with leaflet and OpenStreetMap integration, filters for searching based on price, facilities and type, and the ability for boarding house owners to add, edit, or delete boarding house data. Testing of this system is done using the black-box testing method, which shows that the entire system functions according to plan without any failures and errors. The results of the study of this system increase the ease of access to information for prospective boarding house tenants and provide a platform for boarding house owners to market their properties, as well as attract prospective boarding house tenants. The implementation system is expected to be a solution to overcome the problem of marketing boarding houses in Batam City, as well as making it easier for prospective boarding house tenants to find boarding house locations that suit their needs.
Co-Authors Budy Satria Jeky Jeky les lie mervin Sandi Fadilah Sarah Astiti Stefanus Stefanus Winson Winson Yeyi Gusla Nengsih