Article Per Year (5 Year)
p-Index From 2020 - 2025
0.23
P-Index
This Author published in this journals
All Journal JURNAL MEDIA INFORMATIKA BUDIDARMA
Rendi Kustiawan
Telkom University, Bandung
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
A Multi-label Classification on Topic of Hadith Verses in Indonesian Translation using CART and Bagging Rendi Kustiawan; Adiwijaya Adiwijaya; Mahendra Dwifebri Purbolaksono
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 6, No 2 (2022): April 2022
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v6i2.3787

Abstract

Hadith is a source of law for Muslims after the al-qur'an, in which there are instructions in the form of words, actions, attitudes, and others. Hadith must be studied and practiced by Muslims, then used as a way of life after the al-qur'an. Classifying hadith is a way to make it easier for Muslims to learn hadith by looking at the text pattern in the translation of Bukhari hadith based on three classes or categories based on suggestions, prohibitions, and information. The classification carried out is a multi-label classification. The classification process uses N-gram and TF-IDF as feature extraction, CART and bagging as classification methods, and hamming loss as evaluation methods. Bagging is used to cover the shortcomings of CART, namely, the CART model is less stable, which, if there is a slight change in the training data, will have a significant effect on the resulting learning model. Several testing methods were carried out to obtain the best hammer loss value in this study. Based on several tests that have been carried out, the best hamming loss value is 0.1914 or 80.86%. These results indicate that the use of bagging can help increase accuracy by 5%.
Co-Authors Adiwijaya Mahendra Dwifebri Purbolaksono