JTIM : Jurnal Teknologi Informasi dan Multimedia
Vol 2 No 1 (2020): May

Penerapan Fuzzy SAW untuk Rekomendasi Penentuan Penerima Bantuan Pembangunan Rumah Tidak Layak Huni

Rony Arzian (Universitas Bumigora Mataram)
Zaenal Abidin (Universitas Bumigora Mataram)
Pahrul Irfan (Universitas Bumigora Mataram)
Muhammad Yunus (Politeknik Negeri Jember)

Article Info

Publish Date
27 May 2020


Construction of Non-Habitable Homes (RTLH) is a government program managed by thesupervision of the Social Service (Dinas Sosial) in the form of housing construction assistancefunds for the poor. In its realization, assistance is still often found to be lacking on target. It isbecause the determination of beneficiaries is not correctly selected, and there are no standardmethods based on existing criteria. These problems require a system that can providerecommendations that conform to clear standards and use techniques that accounted. FuzzySimple Additive Weighting (SAW) method is one method used in decision making. This methodcalculates criteria to get ranking weights to support decision making. The process of selectingcriteria and determining fuzzy variables carried out as a primary process in this method. Afterthe fuzzification weight value obtained, ranking done to use as a reference in the decision makingof recipients. Based on the results of manual testing, the system made is under the effects ofmanual calculations with a level of accuracy reaching 100%, so that implemented as a basis formaking decisions. While testing, the black box system found that all the requirements tested canrun following the overall system functionality. With this recommendation system, it can help thedecision to find the recipients of the Fund for Non-Occupable Homes Construction Assistanceso that it is more targeted.

Copyrights © 2020

Journal Info





Computer Science & IT


Cakupan dan ruang lingkup JTIM terdiri dari Databases System, Data Mining/Web Mining, Datawarehouse, Artificial Integelence, Business Integelence, Cloud & Grid Computing, Decision Support System, Human Computer & Interaction, Mobile Computing & Application, E-System, Machine Learning, Deep Learning, ...