Agus Komarudin
Universitas Indonesia Mandiri, Lampung

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Integrasi WhatsApp Gateway dan Cloud Computing pada Sistem Absensi Digital Terpadu Siswa (SAGITA) Gustiawan Maula Rizki; Fathoni Dwiatmoko; Agus Komarudin
Jurnal JEETech Vol. 7 No. 1 (2026): May
Publisher : Universitas Darul Ulum

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32492/jeetech.v7i1.7111

Abstract

The integration of Information and Communication Technology (ICT) in vocational high schools demands agile and accurate administrative governance. Manual attendance monitoring often collides with data accuracy issues and recapitulation inefficiency. This study aimed to design, develop, and evaluate the Integrated Student Digital Attendance System (SAGITA) utilizing a cloud computing architecture at SMK NU Kaplongan, accommodating 1,186 students across 38 study groups. The system integrated the Google Workspace ecosystem (Google Forms and Sheets) with Google Apps Script (GAS) and a local WhatsApp Gateway API for real-time information broadcasting. Employing an applied research methodology with a prototyping approach, the evaluation was conducted through functional testing (Black-box) and administrative impact testing (Pre-test/Post-test). The results showed that the system successfully sent notifications with an average latency of 3-5 seconds. The administrative evaluation indicated a measurable efficiency in recapitulation time and a decrease in reporting delays. The system's continuity relies heavily on physical supporting infrastructure, including the availability of a Virtual Private Server (VPS), a Public IP, and an Uninterruptible Power Supply (UPS). This low-code model offers a cost-effective alternative administrative solution for large-scale educational institutions
K-Means Clustering for Primary Education Inequality in Serang City Ari Sopiandi; Muawan Bisri; Eko Aziz Apriadi; Agus Komarudin
Jurnal JEETech Vol. 7 No. 1 (2026): May
Publisher : Universitas Darul Ulum

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32492/jeetech.v7i1.7115

Abstract

Educational inequality remains a persistent issue in various regions, including Serang City. Differences in access to and quality of education across areas are influenced by several factors such as the number of schools, students, and teaching staff. However, available educational data are generally presented only in the form of descriptive statistics, which are not sufficient to provide in-depth insights into the patterns of inequality. Therefore, a computational-based approach is needed to analyze educational data more effectively. This study aims to analyze trends in educational development and map educational inequality in Serang City using a data mining approach with the K-Means algorithm. The data used in this study consist of educational data obtained from the Serang City Education Office, Dapodik, and BPS, including the number of schools, the number of students, and the number of teaching staff. The analysis process is carried out through data preprocessing, normalization, and data clustering using the K-Means algorithm with the help of RapidMiner software. The results show that educational data can be grouped into several clusters representing the level of educational conditions across regions. Each cluster has different characteristics, which can be used to identify areas with high and low levels of educational inequality. Thus, the data mining approach is able to provide a more systematic overview of educational conditions and support data-driven decision-making