Implementasi Metode JST-Backpropagation untuk Klasifikasi Rumah Layak Huni (Studi Kasus: Desa Kidal Kecamatan Tumpang Kabupaten Malang) - Riza Rizqiana Perdana Putri; Muhammad Tanzil Furqon; Bayu Rahayudi (Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya, 2018)
The house has a big role for each individual and family because house is not only a place to live but house should be comfortable and safe and can maintain the privacy of each family member in accordance with the function of the house as a medium for the implementation of family guidance and education. But in reality, there are still many houses in Indonesia that still do not meet the requirements of a habitable home. The government created a program to assist repairing of uninhabitable homes to provide assistance in order to be right on target, the government must determine whether a person has a habitable home or an uninhabitable home. Therefore, to overcome these problems created an intelligent system for the classification of habitable home using backpropagation algorithm. this study uses 160 data from the Village Kidal Tumpang District Malang Regency which is divided into two categories that are habitable and unhabitable. Backpropagation method is one of the classification method that has excellent performance. This algorithm is very effective in performing various predictions on a problem. This study also uses nguyen widrow for initialization of initial weight. The final test of this research yields the highest accuracy score of 59% by using 15 input layer, 3 hidden layers, learning rate of 0.2.