PENERAPAN METODE FUZZY INFERENCE SYSTEM (FIS) SUGENO DALAM MENENTUKAN NILAI INFLASI (STUDI KASUS PADA DATA INFLASI MEDAN)

Authors

  • Olga Laura Mahlona Universitas Negeri Medan
  • Said . Iskandar Universitas NegerI Medan

DOI:

https://doi.org/10.24114/jmk.v6i3.22215

Keywords:

Inflasi, Logika Fuzzy, Sugeno.

Abstract

Pada penelitian ini, diterapkan metode logika fuzzy dengan sistem inferensi fuzzy Sugeno untuk memperhitungkan nilai inflasi berdasarkan variabel-variabel yang terdapat pada Indeks Harga Konsumen (IHK). Tujuan penelitian ini adalah untuk mengetahui hasil perhitungan nilai inflasi dengan menggunakan sistem inferensi fuzzy Sugeno dan ketepatan hasil perhi- tungan dengan menggunakan sistem inferensi fuzzy Sugeno. Pada himpunan fuzzy rendah menggunakan data terendah dan himpunan fuzzy tinggi menggunakan data tertinggi dari setiap variabel. Dalam penelitian ini menggunakan fungsi keanggotaan representasi linear naik dan representasi linear turun . Model logika fuzzy Sugeno pada penelitian ini menggunakan output (konsekuen) berupa konstanta (model Sugeno orde nol). Secara umum bentuk model Sugeno orde nol adalah:   IF (x1isA1)â—¦ (x2isA2)â—¦...â—¦ (xiisAi) THEN z is k. Penegasan atau defuzzifikasi diperoleh dengan menggunakan metode rata-rata terpusat (Weight Average). Dari hasil penelitian diperoleh MSE dengan nilai yang kecil yakni sebesar 0.00000922673 dan MAPE sebesar 1.00819%.Kata kunci: Inflasi, Logika Fuzzy, Sugeno.  ABSTRACT In this study, applied fuzzy logic method with Sugeno fuzzy inference system to calculate the inflation value based on variables contained in the Consumer Price Index (CPI). The purpose of this study was to determine the results of the calculation of inflation values using the Sugeno fuzzy inference system and the accuracy of the results of the calculation by using the Sugeno fuzzy inference system. The low fuzzy set uses the lowest data and the high fuzzy set uses the highest data from each variable. In this study using a function of linear representation representation increases and linear representation decreases. Sugeno fuzzy logic model in this study uses output (consequently) in the form of a constant (the zero order Sugeno model). In general, the zero-order Sugeno model is: IF (x1isA1) â—¦ (x2isA2) â—¦ ... â—¦ (xisAi) THEN z is k. Defuzzification is obtained using the weighted average method. From the research results obtained MSE with a small value of 0.00000922673 and MAPE of 1.00819%.

Author Biographies

Olga Laura Mahlona, Universitas Negeri Medan

Jurusan Matematika

Said . Iskandar, Universitas NegerI Medan

Jurusan Matematika

References

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Setiadji., (2009): Himpunan dan Logika Samar, Graha Ilmu, Yogyakarta.

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Published

2020-12-05

Issue

Vol. 6 No. 3 (2020): Karismatika

Section

Articles

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Copyright (c) 2020 KARISMATIKA: Kumpulan Artikel Ilmiah, Informatika, Statistik, Matematika dan Aplikasi

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