House ownership credit decision for prospective customers using Regular Grammar Web based - Muhammad Noval Riswandha; Abdul Rasyid (JOINCS (Journal of Informatics, Network, and Computer Science), 2019)
This research aims to facilitate the process of MORTGAGE (home ownership credit) by conducting analysis on customer's income, customer spending, age, customer's disease history, and also most importantly DP (do WN p ayme nt) customer. This analysis is useful to find customer eligibility for MORTGAGE collection.From data sourced to Marketing Green Mansion system testing will be done in a simulation. Between the developer and the customer will make a transaction according to the available data. In the customer process, there are facilities to complete the requirements that are equipped with Regular Grammar methods and proceed to the Fuzzy logic Tsukamoto, to provide information on the ability of instalment that can be achieved by customers. Next with a collaboration between the Fuzzy logic results Tsukamoto with the result of installments that proceed from the previous Regular Grammar Grammar, then the customer will be determined by the system meets or not. If it meets then it will proceed with payment and upload to get a report to submit a SHGB (building rights Letter).