Rekomendasi Perbaikan Rumah Tidak Layak Huni Menggunakan Metode TOPSIS Studi Kasus Badan Keswadayaan Masyarakat Di Kelurahan Bekasi Jaya - Muhammad Fakhri Mubarak; Nurul Hidayat; Marji Marji (Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya, 2019)
Houses that are habitable, clean and have good infrastructure are the hopes of every human being. Conversely, non-habitable homes can cause discomfort for residents, and can also be a source of disease that should be avoided by residents. To avoid this, residents of the house must spend not a little money to improve the infrastructure for their place of residence. The problem is that there are still families who do not have excessive financial resources to repair their homes, which makes them have to survive in places that are not suitable for habitation. To overcome this, the governments of each region prepared a variety of programs to help disadvantaged communities, one of which was responsible to the Badan Keswadayaan Masyarakat. Unfortunately, these funds cannot be given to all applicants for repairing unfit for housing. Due to the imbalance in the number of applicants for repairs to improper housing, with funds owned by the Community Self-Help Agency. So the Badan Keswadayaan Masyarakat needs a system that is used to help provide recommendations for homes that are preferred to be repaired. The application of the TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) method will be used to get home improvement recommendations that will be repaired. This system uses data as much as 50 data which form the basis of calculations and 8 home recommendation data which become test data. The application of the TOPSIS method in determining recommendations for repairing uninhabitable homes uses several factors, namely: the status of the house, the walls of the house, the floor of the house, the roof of the house and family income. From this study, it was obtained an accuracy of 75% obtained from testing of decision-making data in the Community Empowerment Agency and ranking using the TOPSIS method.