Pengklasifikasian Tingkat Kesejahteraan Keluarga Di Desa Citamiang Dengan Penerapan Logika Fuzzy Model Tahani

  • Yoga Permana Universitas Muhammadiyah Sukabumi
  • Lelah Lelah Universitas Muhammadiyah Sukabumi

Abstract

Indonesia is a country with a substantial population population, in the year 2020 the population of Indonesia reaches 269.6 million. Each of them certainly has a family. Family welfare not only affects the success of its family, but also affects the success of the government, no exception of village governance. Therefore, information about the family welfare level is necessary to review the efforts that the Government has made if it is successful or not. To determine the level of family welfare there are several indicators such as income, occupation, age and dependents. In order to classify the family welfare process can be more efficient, it can be processed through programs that apply Fuzzy logic with Tahani model. The purpose of the study was intended to classify the welfare of the family based on population data owned by the village government. Based on the research results obtained by Fuzzy logic with Tahani model can be used to process population data in accordance with the level of family welfare indicators by providing output in the form of classifications of families including incapacitated families, underprivileged families and privileged families. The output of the program was also tested with the fuzzyTECH application to measure the success of Fuzzy logic on the built program.

Keywords: Fuzzy logic, Tahani Model, Classification, Family, Village

References

Viva Budy Kusnandar, “Inilah Proyeksi Jumlah Penduduk Indonesia 2020,” katadata.co.id, 2020. [Daring]. Tersedia pada: https://databoks.katadata.co.id/datapublish/2020/01/02/inilah-proyeksi-jumlah-penduduk-indonesia-2020#:~:text=Berdasarkan hasil Survei Penduduk Antar,hanya 134%2C27 juta jiwa. [Diakses: 01-Jun-2020].

Humas, “Tahun 2020 Bkkbn Bersama K/L Terkait Serentak Mengadakan Pendataan Keluarga Di Indonesia,” Bkkbn, 2019. [Daring]. Tersedia pada: https://www.bkkbn.go.id/detailpost/tahun-2020-bkkbn-bersama-k-l-terkait-serentak-mengadakan-pendataan-keluarga-di-indonesia. [Diakses: 01-Jun-2020].

A. P. Astari dan R. Komarudin, “Sistem Pendukung Keputusan Pemilihan Karyawan Terbaik Dengan Metode Fuzzy Tahani,” PIKSEL Penelit. Ilmu Komput. Sist. Embed. Log., vol. 6, no. 2, hal. 169–178, 2018.

S. Hartanto, “Implementasi Fuzzy Rule Based System,” Techsi, vol. 9, no. 2, hal. 103–117, 2017.

E. Ismaredah, “Implementasi Fuzzy Database Model Tahani untuk Pembelian Rumah Perumnas,” Semin. Nas. Teknol. Informasi, Komun. dan Ind., vol. 9, hal. 436–447, 2017.

M. Rusli, Dasar Perancangan Kendali Logika Fuzzy. UB Press, 2017.

G. K. Gandhiadi, L. Putu, dan I. Harini, “Aplikasi Fuzzy Model Tahani Dalam Penentuan Pemilihan Spesifikasi Tablet PC,” vol. 8, no. 2, hal. 88–94, 2019.

M. H. Setiawan, G. K. Gandhiadi, dan L. P. I. Harini, “Penerapan Metode Logika Fuzzy Model Tahani Dalam Pemilihan Hardware Komputer,” E-Jurnal Mat., vol. 6, no. 4, hal. 248, 2017.

A. B. Purnomo, W. Henny, dan Daryanto, “Klasifikasi Kelas Berdasarkan Prestasi Siswa Menggunakan Metode Fuzzy Logic,” Universitas Muhammadiyah Jember, 2018.

Y. Rohani, “Penentuan Fire Strength Pada Fuzzy Menggunakan Microsoft Excel , Studi Kasus : Keputusan Memilih Sepeda Motor,” J. Teknol. Inf. dan Komun., vol. 7, no. 1, hal. 1–7, 2016.

F. AlAwadhi, M. A. Yousef, dan A. Al-Kandari, “Accident Detection Traffic Light System with Dynamic Fuzzy Logic Control Using FuzzyTech Program and iTraffic Simulation,” Int. J. Perceptive Cogn. Comput., vol. 1, no. 1, hal. 11–17, 2015.

Published
2020-07-20
How to Cite
[1]
Y. Permana and L. Lelah, “Pengklasifikasian Tingkat Kesejahteraan Keluarga Di Desa Citamiang Dengan Penerapan Logika Fuzzy Model Tahani”, rabit, vol. 5, no. 2, pp. 97-107, Jul. 2020.
Section
Articles
PDF (Bahasa Indonesia)
Abstract views: 767
downloads: 530