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Jurnal Informatika: Jurnal Pengembangan IT
Published by Politeknik Harapan Bersama Tegal
ISSN : 24775126     EISSN : 25489356     DOI : https://doi.org/10.30591
Core Subject : Science,
Computer Science & IT
The scope encompasses the Informatics Engineering, Computer Engineering and information Systems., but not limited to, the following scope: 1. Information Systems Information management e-Government E-business and e-Commerce Spatial Information Systems Geographical Information Systems IT Governance and Audits IT Service Management IT Project Management Information System Development Research Methods of Information Systems Software Quality Assurance 2. Computer Engineering Intelligent Systems Network Protocol and Management Robotic Computer Security Information Security and Privacy Information Forensics Network Security Protection Systems 3. Informatics Engineering Software Engineering Soft Computing Data Mining Information Retrieval Multimedia Technology Mobile Computing Artificial Intelligence Games Programming Computer Vision Image Processing, Embedded System Augmented/ Virtual Reality Image Processing Speech Recognition
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 431 Documents
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Sistem Informasi Identifikasi Faktor yang Mempengaruhi Prestasi Siswa MAN Karo Menggunakan Pendekatan Data Mining Mariam, Ai Siti; Suendri, Suendri
Jurnal Informatika: Jurnal Pengembangan IT Vol 11, No 1 (2026)
Publisher : Politeknik Harapan Bersama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30591/jpit.v11i1.10035

Abstract

Student academic achievement is a key indicator of learning success and is influenced by various internal factors (such as motivation, learning style, and attendance) as well as external factors (such as parental support and learning facilities). This study aims to identify the main factors that determine students academic achievement by implementing a web-based information system using the Apriori algorithm. The study applied a quantitative descriptive approach using data from 300 students of MAN Karo, collected through questionnaires and academic records. The Apriori algorithm was implemented with a minimum support threshold of 0.05 and a minimum confidence threshold of 0.6, producing 1,621 association rules. The results indicate that a combination of internal and external factors is strongly associated with high academic achievement. The strongest association rule shows that students who attend tutoring classes tend to achieve high report card scores (?85) and have complete learning facilities, with a confidence value of 67.6% and a lift ratio of 3.12. Overall, internal factors such as motivation (77.33%) and high attendance (63.67%), along with external factors including parental support, learning facilities, and tutoring participation, significantly contribute to improving students academic performance. These findings demonstrate that the Apriori algorithm can effectively support schools in identifying dominant academic factors and can be used as a basis for data-driven decision making.

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