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All Journal Journal of Computer Networks, Architecture and High Performance Computing
Laia, Endang Mistaorina
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Computer Science & IT Education

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Decision Support System to Determine Applicant Housing Credits With SAW Method on the House Complex of J. City Residence by Capital Property Laia, Endang Mistaorina; Sihotang, Hengki Tamando
Journal of Computer Networks, Architecture and High Performance Computing Vol. 2 No. 2 (2020): Computer Networks, Architecture and High Performance Computing
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnapc.v2i2.402

Abstract

J. City Residence provides subsidized housing loans facilities for people who earn below the average. The number of credit applicants with different criteria requires carefulness of the Credit Analyst in making decisions. This problem can be solved by building a Decision Support System (DSS) in determining the provision of subsidized mortgage loans using the Simple Additive Weighting (SAW) method. The criteria used are house condition (cost attribute), income (cost attribute), employment (benefit attribute), credit history (benefit attribute) and marital status (benefit attribute). The process is to normalize the credit applicant value matrix, then multiply the results of the normalization by the weight value. If the result of the calculation is above the credit line is not feasible, then the applicant is declared eligible to receive credit. Application can be used to help to determine the eligibility of consumers in obtaining subsidized housing loans with the SAW method in J. City Residence by Capital Property Housing.
Co-Authors Hengki Tamando Sihotang Sihotang, Hengki Tamando