Article Per Year (5 Year)
p-Index From 2021 - 2026
0.408
P-Index
This Author published in this journals
All Journal Journal of Information Systems and Business Technology Journal of Information Technology and Informatics Engineering
Berliani Salsabiilah
Universitas Pamulang
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Engineering Library & Information Science

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
Implementasi Dan Analisis Sistem Informasi Manajemen Data Mahasiswa Berbasis Web Berliani Salsabiilah; Athaya Rima Hariyanto
Journal of Information Systems and Business Technology Vol 1 No 2 (2025): Journal of Information Systems and Business Technology
Publisher : PT Jurnal Cendekia Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

This research focuses on the development and implementation of a web-based Student Data Management Information System. The goal is to support more effective, organized, and accurate data management. The system was developed using the Waterfall method, which includes the stages of requirement analysis, design, implementation, testing, and maintenance. Black Box Testing was used during the testing phase to ensure that each system function operates as expected by the user, without examining the internal code. The test results show that all key features—such as login, data input, editing, deletion, search, and logout—function properly. It is expected that this system will speed up administrative services and minimize errors in managing student data.  
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

Show Abstract | Download Original | Original Source | Check in Google Scholar

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 Athaya Rima Hariyanto Maulana Fanyusri Siti Khodijah Winona Septi Aulia