Optimation Hybrid Model in Selecting Banks for Housing Loans - Linda Perdana Wanti (KLIK: Kajian Ilmiah Informatika dan Komputer, 2023)
Public housing loans (KPR) have so far become an alternative solution to the problem of the people who wish to have a house but do not have sufficient funds to buy or build it. The obstacle people often faced is finding the best bank from various sides to finance the housing loans. The concept of Islamic banks has recently become a quite reliable competitor for conventional banks in financing KPR. Its presence needs to be taken into account in terms of which bank people chooses to finance KPR, whether with conventional banks or Islamic banks. The research aims to provide alternative decisions for people who look for housing and intend to use public housing credit facilities by optimizing two methods of decision making. Some banks have become alternatives used as a comparison to each other. The alternatives used have their respective characteristics along with its advantages and disadvantages. Decision making methods used are analytical hierarchy process (AHP) and weighted product (WP) methods. Both of these methods are optimized to get banks that have the highest preference weights. The system development method used is user-centered design that captures all the needs of the end user. The parameters used in the selection of banks used for mortgages are the types of banks which consist of two types, namely conventional banks and Islamic banks, interest given by each type of bank, developers working with the bank, administration fees charged by the bank, contract and settlement based on the type of bank, and the last is the duration of the process which is calculated from the start of the contract agreement until the house is ready for occupancy. The output of this study is the weighting result using two methods as an alternative, in which the highest weight used as the best bank solution to finance the KPR. The most effective decision is obtained, namely BTN as a bank that is eligible to finance KPR with the highest preference weight of 14,969.