Perbandingan Algoritma C4.5 dan Naive Bayes Untuk Menentukan Penerima Bantuan Bedah Rumah di Kabupaten Tanggamus - Arbi Gunawan; M Said Hasibuan (Jurnal SIMADA (Sistem Informasi dan Manajemen Basis Data), 2023)
A livable house is a basic human need, a livable house is said to be if the home owner has a sense of peace and comfort living in that house. A livable house is interpreted as a house that has facilities to meet human needs in carrying out daily activities. The government assistance has not been distributed evenly to the homes of the residents of Tiga Dolok Village, because the program that has been running so far is very complicated, the system that runs is still manual in processing community data. Therefore, the authors provide a solution to classify the eligibility level of the house using the C4.5 algorithms and the Naïve Bayes algorithm. This algorithm was chosen because it is one of the methods in the Decision Tree that is widely used to make predictions about a case. Thus, government subsidies for renovating uninhabitable houses can be channeled in an appropriate manner. The research objective is to use a decision tree based on the C4.5 algorithms, which is expected to increase the accuracy of receiving housing feasibility renovation assistance. The research method used is Data Mining. Analysis and calculations using this algorithm really help the decision-making process to determine people who are eligible to receive housing renovation assistance and people who are not eligible to receive housing renovation assistance. Keywords: Livable House; C4.5 Algorithm; Decision tree, Naïve