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All Journal Journal of Information Systems and Business Technology Journal of Information Technology and Informatics Engineering
Winona Septi Aulia
Universitas Pamulang
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Engineering Library & Information Science

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Analisis Sistem Informasi Pengaduan Masyarakat Berbasis Web Menggunakan Metode Agile Siti Khodijah; Winona Septi Aulia
Journal of Information Systems and Business Technology Vol 1 No 1 (2025): Journal of Information Systems and Business Technology
Publisher : PT Jurnal Cendekia Indonesia

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Abstract

The public complaint system plays an important role in improving the quality of public services, especially in government institutions such as the DPR RI Building. This study aims to design and test a web-based complaint information system with a software development method using the Agile approach. System development is carried out through several sprint stages, including identifying needs, creating features, and testing the system. The type of testing used is Black Box Testing, focusing on key features such as login, dashboard, navigation menu, data management, and form validation. The test results show that all features run as expected, and this system can manage complaints in an efficient, transparent, and orderly manner. Therefore, this system is declared successful in improving the efficiency of complaint handling in the DPR RI environment.
Klasterisasi Mahasiswa Berdasarkan Performa Akademik Menggunakan Algoritma K-Means pada RapidMiner: Studi Kasus dengan Dataset Student Academic Performance Siti Khodijah; Athaya Rima Hariyanto; Berliani Salsabiilah; Winona Septi Aulia; Maulana Fanyusri
Journal of Information Technology and Informatics Engineering Vol 1 No 1 (2025): Journal of Information Technology and Informatics Engineering (JITIE)
Publisher : PT Jurnal Cendekia Indonesi

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Abstract

One of the primary indicators used to convey the effectiveness of the learning process and to create more efficient teaching methods is student academic performance. This study uses the RapidMiner application to use the K-Means Clustering method in order to group students according to their academic performance. The synthetic data, which includes details about student involvement, attendance rates, and academic grades, is taken from the Kaggle platform. This study was carried out in a number of steps, including cluster quality assessment, attribute selection, algorithm application, and data pre-processing.Based on the results, three student groups with characteristics of high, medium, and low academic performance were examined. The Davies-Bouldin Index examination indicated that the clustering results were optimal. These findings are expected to serve as a guide for educational institutions to develop more appropriate and successful teaching strategies.
Co-Authors Athaya Rima Hariyanto Berliani Salsabiilah Maulana Fanyusri Siti Khodijah