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All Journal ComEngApp : Computer Engineering and Applications Journal EDUMATIC: Jurnal Pendidikan Informatika
Arif Bramantoro
Faculty of Computing and Information Technology, King Abdulaziz University, Jeddah, Saudi Arabia
Computer Science & IT Education Engineering

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Arabic Translation Web Services: An Implementation Survey Towards Arabic Language Grid Arif Bramantoro
Computer Engineering and Applications Journal Vol 6 No 3 (2017)
Publisher : Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (427.765 KB) | DOI: 10.18495/comengapp.v6i3.216

Abstract

This research proposes the development of Arabic language service. It is a servlet-based Webservice which provides a translation from English into Arabic, using techniques to develop Webservices such as Restful and API in Java language. This API is part of Language Grid, aproject in Japan to collect, share and combine as many language resources as possible bywrapping the language resources as web services, which is also known as Everything as a Service(XaaS) technology. By having Arabic language services connected in the Language Grid, therewill be a wider use of Arabic language resource in the world. An evaluation of running theservice is provided to enhance the performance and reliability of the service.
Behaviorally Interpretable Transactional Features for Customer Segmentation Using K-Means in Grocery Retail Aprizal, Rendy Muhammad; Sari, Oktalia Kumala; Bramantoro, Arif
Jurnal Pendidikan Informatika (EDUMATIC) Vol 10 No 1 (2026): Edumatic: Jurnal Pendidikan Informatika
Publisher : Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/edumatic.v10i1.34163

Abstract

Customer segmentation based on transactional data is widely used to understand purchasing behavior in retail. However, many existing studies tend to emphasize algorithm performance, with limited discussion on how transactional variables represent actual customer behavior. This study adopts a quantitative approach using transactional sales data from a grocery retail store (Toko Solo Latri), consisting of 10,000 item-level records collected during June 2025. The analysis follows the CRISP-DM framework, covering data understanding, preparation, modeling, and evaluation stages. Customer behavior is represented through several aggregated variables, including transaction frequency, total items purchased, and product diversity. The K-Means clustering algorithm is applied to group customers into meaningful segments. The number of clusters is determined using the Elbow Method and further evaluated using Silhouette analysis. The results reveal three distinct customer segments with different levels of purchase intensity and product diversity. The Silhouette Score of 0.464 indicates a moderate clustering structure. In addition, one-way ANOVA shows significant differences across the observed variables, with large effect sizes (η² ranging from 0.736 to 0.822). These findings suggest that constructing behavior-based transactional features can improve the interpretability of customer segmentation results.
Co-Authors Aprizal, Rendy Muhammad Sari, Oktalia Kumala