Open AccessElectronic Credit and Furniture Decision Support Systems Using the Weighted Product Method
Author(s) -
Helita Sari,
R. Mahdalena Simanjorang
Publication year - 2021
Publication title -
deleted journal
Language(s) - English
DOI - 10.35335/ijobas.v10i1.5
Subject(s) - computer science , product (mathematics) , ranking (information retrieval) , decision support system , process (computing) , credit card , value (mathematics) , database , operations research , data mining , artificial intelligence , machine learning , world wide web , mathematics , programming language , geometry , payment
To do Electronic Credit and furniture is quite difficult and less effective and efficient. Because the system used is still manual or not computerized, and the number of consumers who want to credit goods in Metro, it takes a few days or a long time to make a decision so that a system is needed, namely a Decision Support System using the Weighted Product method. The Weighted Product method is a method that uses multiplication to relate the attribute rating, where the rating of each attribute must first be ranked with the attribute's weight. The Weighted Product method uses multiplication as a liaison for attribute ratings, where the rating of each attribute must be ranked first with the weight in question. This research will produce an application or a furniture and electronic credit decision support system that can help make the credit granting process in the metro easier and more precise. The criteria used in this study are income, BPKB guarantee, KTP, family card (KK), home status, tutoring concerned and child dependents. Of the 5 examples of consumers who have been given in this study from A1, A2, A3, A4, to A5 then the highest ranking result of these 5 consumers is given to alternative A1 because the value obtained by A1 is higher than other alternatives. This system is designed using UML with the programming language PHP, CSS, Java script and HTML with the MySQL database.