Penerapan Data Mining untuk Menemukan Pola Asosiasi Aktivitas Belajar dan Prestasi Santri Menggunakan Algoritma Apriori

Education in Islamic boarding schools is unique, integrating cognitive, character, and spiritual development. This study aims to uncover the relationship between students' learning activities and academic achievement using data mining techniques with the Apriori algorithm. A quantitative approach was applied, analyzing data on learning activities and academic performance. Data preprocessing and the Apriori algorithm were employed using RapidMiner software to identify association patterns between variables. Findings indicate a significant relationship between class attendance, study hours, discussion participation, and extracurricular achievements with academic performance. The association rules revealed that consistent attendance and active learning participation positively influence academic achievement, with confidence levels of 70-80% for "Good" performance categories. This study offers actionable insights for Islamic boarding schools to design more effective learning strategies and emphasizes the potential of data-driven education to enhance student outcomes..

Authors

Publication Details

Journal
TRILOGI Jurnal Ilmu Teknologi Kesehatan dan Humaniora
Published
2024-12-21
DOI
https://doi.org/10.33650/trilogi.v5i4.9919
Primary Topic
Data Mining and Machine Learning Applications
Type
article
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article

Penerapan Data Mining untuk Menemukan Pola Asosiasi Aktivitas Belajar dan Prestasi Santri Menggunakan Algoritma Apriori

Choirul Anam, Ahmad Hudawi, Miftahur Rahman
TRILOGI Jurnal Ilmu Teknologi Kesehatan dan Humaniora
Data Mining and Machine Learning Applications
article

Penerapan Data Mining untuk Menemukan Pola Asosiasi Aktivitas Belajar dan Prestasi Santri Menggunakan Algoritma Apriori

Choirul Anam, Ahmad Hudawi, Miftahur Rahman
article en

Abstract

Education in Islamic boarding schools is unique, integrating cognitive, character, and spiritual development. This study aims to uncover the relationship between students' learning activities and academic achievement using data mining techniques with the Apriori algorithm. A quantitative approach was applied, analyzing data on learning activities and academic performance. Data preprocessing and the Apriori algorithm were employed using RapidMiner software to identify association patterns between variables. Findings indicate a significant relationship between class attendance, study hours, discussion participation, and extracurricular achievements with academic performance. The association rules revealed that consistent attendance and active learning participation positively influence academic achievement, with confidence levels of 70-80% for "Good" performance categories. This study offers actionable insights for Islamic boarding schools to design more effective learning strategies and emphasizes the potential of data-driven education to enhance student outcomes..

TRILOGI Jurnal Ilmu Teknologi Kesehatan dan HumanioraVol. 5(4)
Quality Education
Openalex Percentile: Top 60%
Data Mining and Machine Learning Applications
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