Implementasi Fuzzy Logic Dalam Menentukan Kondisi Rumah Tidak Layak Huni (RTLH) Dan Rumah Layak Huni (RLH)
DOI:
https://doi.org/10.37253/telcomatics.v9i2.9516Keywords:
Fuzzy Inference System, Mamdani, Classification, PriceAbstract
The Use of Fuzzy Logic to Select Between Uninhabitable House Conditions (RTLH) and Livable Houses (RLH) is focused on the running system as the subject of research. Starting with identifying issues, literature studies, data collection, problem analysis, fuzzy logic needs analysis, data analysis (variable classification), fuzzy system design, testing with the Sugeno method, testing with MATLAB software. The results of the program testing are in accordance with the diagram below. We get results that match the input member values of the established rules. If the roof is good enough, the floor is not good enough, and the walls are very good, then the house is not livable. The fuzzy control system involves three fuzzy inputs and one fuzzy output. Each of these variables has a membership function that groups values into four categories: Less Good, Fairly Good, Good, and Very Good. There are 64 fuzzy rules that link the combination of roof, floor, and wall conditions with the category of house eligibility. This fuzzy control system is then utilized to manage these rules. By simulating the conditions of the roof, floor, and walls, the system will calculate the value of the house's eligibility. If the eligibility value exceeds 50, the house is considered suitable for habitation; on the other hand, if the value is below 50, the house is considered uninhabitable. Therefore, this system can assess whether a house is livable or not based on its physical condition, providing a more objective and consistent decision than traditional assessment methods. This application shows that the use of fuzzy logic can be effective in assessing the livability of a house, especially in evaluating the subjective and complex physical condition of a house.
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References
A. Siti, “Analisis komparasi metode tsukamoto dan sugeno dalam prediksi jumlah siswa baru,” J. Teknol. Inf. dan Komun., vol. 8, no. 2, pp. 57–63, 2016.
K. Hamdi, “Analisis Data Sistem Informasi Geografis Rumah Tidak Layak Huni (RTLH) Menggunakan Metode Fuzzy Logic,” J. RESTI (Rekayasa Sist. dan Teknol. Informasi), vol. 4, no. 6, pp. 1179–1189, 2020, doi: 10.29207/resti.v4i6.2658.
B. Sunaryo, M. I. Rusydi, A. Manab, A. Luthfi, . R., and T. Septiana, “Sistem Informasi Manajamen Perangkat Elektronik Berbasis Web,” J. Nas. Teknol. dan Sist. Inf., vol. 2, no. 1, pp. 75–82, 2016, doi: 10.25077/teknosi.v2i1.2016.75-82.
A. A. Chamid, “Penerapan Metode Topsis Untuk Menentukan Prioritas Kondisi Rumah,” Simetris J. Tek. Mesin, Elektro dan Ilmu Komput., vol. 7, no. 2, p. 537, 2016, doi: 10.24176/simet.v7i2.765.
I. Muzayyanah and W. Mahmudy, “Penentuan Persediaan Bahan Baku Dan Membantu Target Marketing Industri Dengan Metode Fuzzy Inference System Tsukamoto,” J. Doro, vol. 4, no. 2014, pp. 4–7, 2014, [Online]. Available: http://wayanfm.lecture.ub.ac.id/files/2015/06/JurnalSkripsi-2013-2014-009-Iklila-Muzayyanah.pdf.
M. Sholihin, N. Fuad, and N. Khamiliyah, “Sistem Pendukung Keputusan Penentuan Warga Penerima Jamkesmas Dengan Metode Fuzzy Tsukamoto,” J. Tek., vol. 5, no. 2 SPK, pp. 501–506, 2013.
Indah Akmar Nasution, “Sistem Pendukung Keputusan Penentuan Pemilihan Laptop Dengan Menerapkan Fuzzy Tahani,” Pelita Inform. Budi Darma, no. 0911378, pp. 93–96, 20AD, [Online]. Available: www.stmik-budidarma.ac.id.
M. Irfan, L. P. Ayuningtias, and J. Jumadi, “Analisa Perbandingan Logic Fuzzy Metode Tsukamoto, Sugeno, Dan Mamdani ( Studi Kasus : Prediksi Jumlah Pendaftar Mahasiswa Baru Fakultas Sains Dan Teknologi Uin Sunan Gunung Djati Bandung),” J. Tek. Inform., vol. 10, no. 1, pp. 9–16, 2018, doi: 10.15408/jti.v10i1.6810.
S. Hartanto, “Implementasi Fuzzy Rule Based System untuk Klasifikasi Buah Mangga,” Techsi, vol. 9, no. 2, pp. 103–122, 2017, [Online]. Available: https://doi.org/10.29103/techsi.v9i2.217.
K. Hamdi, B. Sunaryo, A. Arianto, Yuhefizar, and I. Gunawan, “Sistem Pelacakan Lokasi Petugas Survei RTLH Menggunakan GPS Android dan WebGIS,” J. RESTI (Rekayasa Sist. dan Teknol. Informasi), vol. 3, no. 3, pp. 552–559, 2019, doi: 10.29207/resti.v3i3.1355.
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