Implementation Of Fuzzy-Simple Additive Weighting (F-SAW) Method For Housing Assistance Recipients System in Amarasi District, Kupang Regency

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Yuyun Saudale
Kornelis Letelay
Arfan Y Mauko


Recipients of housing assistance for poor people are government assistance programs that have a limited budget so that not all people receive housing assistance. Criteria for recipients of housing assistance can be seen from 13 criteria such as age, education, occupations, income, land ownership, home ownership, number of occupants, roof conditions, wall conditions, floor conditions, ownership of bathrooms, water sources, electricity sources. To get a decent recipient, a Decision Support System (DSS) is needed to make it easier for the government to provide housing assistance for poor people. Fuzzy Method Simple Additive Weighting (F-SAW) is one method in DSS that can help resolve unstructured problems and can accommodate weakness of SAW method in linguistic and numerical assessments. System testing conducted use sensitivity testing that is with change value weight each criteria in a manner gradually. From sensitivity test above that has been done, the most sensitive is education criteria because when tested three times of high weight is changed to very high has experienced one change, low has 4 times changed and very low has 4 times the change, with these changes the results got 90% presentation for education criteria. From the results of comparisons that have been made between Dinas Sosial and system, data quota that deserves to receive housing assistance as much as 30 data from dinas sosial showed that total data quota is 20 which is same with system and 10 data is not same with system.



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Saudale, Y., Letelay, K., & Mauko, A. (2019). Implementation Of Fuzzy-Simple Additive Weighting (F-SAW) Method For Housing Assistance Recipients System in Amarasi District, Kupang Regency. Jurnal Komputer Dan Informatika, 7(2), 116-123.


[1] Fishburn, P.C., 1967, Additive Utilities with Incomplete Product Set: Application to Priorities and Assignments. Operations Research Society of America (ORSA), Baltimore, MD, U.S.A.
[2] Tettamanzi, A., & Tomassini, M., 2001, Soft Computing Integrating Evalutionary Neural and Fuzzy System,
Springer-verlag, Berlin.

[3] Turban, E., Aronson, J.E., & Liang, T.P., 2005, Karakteristik dan Kapabilitas Kunci dari Sistem pendukung Keputusan, Dalam: D. Prabantini, Penyunting, Decision Support Systems and Intelligent Systems, ANDI, Yogyakarta.
[4] Wibowo, S.H., Amalia, R., Fadlun, M.A., & Kurnia, A., 2008, Sistem Pendukung Keputusan Untuk Menentukan Penerima Beasiswa Bank BRI menggunakan FMADM (Studi kasus: Mahasiswa Fakultas Teknologi Industri Universitas Islam Indonesia), Prosiding Seminar Nasional Aplikasi Teknologi Informasi, Yogyakarta, Hal. 62-67.
[5] Yanar, L., Tozan, H., & Hloch, S., 2012, Selection of Equipment for Soft Tissue Cutting Using Fuzzy AHP and Fuzzy ANP With A Proposed Decision Support System, Manufacturing Engineering & Management The Proceedings, Turkish.
[6] Zadeh, L.A., 1965, Fuzzy Sets Information and Control, Vol. 8, Hal. 338-353.

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