Implementasi Data Mining Menggunakan Algoritma ID3 pada Klasifikasi Produktifitas Wakaf

Abstract

The development of information technology encourages the use of data mining in various fields, including in waqf data management. Waqf is an Islamic economic instrument that has great potential to improve community welfare if managed productively and sustainably. However, the level of waqf asset productivity in each region tends to vary, so a method capable of grouping waqf productivity effectively and systematically is needed. This study aims to implement the Iterative Dichotomiser 3 (ID3) algorithm to classify waqf productivity in Karangasem Regency into high, medium, and low categories. The method used in this study is data mining with a decision tree-based classification technique using the ID3 algorithm. The data used is waqf data from Karangasem Regency, Bali, with several attributes that influence the level of waqf productivity. The research stages include data collection, preprocessing, entropy and information gain calculations, decision tree formation, and testing the classification results. The results show that the ID3 algorithm is able to classify waqf productivity well based on the attributes used and produces easy-to-understand decision rules. The best model produced achieved an accuracy rate of 88.89%. The implementation of the ID3 algorithm is expected to assist the management process and decision-making related to waqf productivity more quickly, effectively, and objectively.