Analisis Tingkat Akurasi Metode Neuro Fuzzy dalam Prediksi Data IPM di NTB
Journal Title: JTAM (Jurnal Teori dan Aplikasi Matematika) - Year 2019, Vol 3, Issue 1
Abstract
This research was conducted to analyze the forecasting process in determining the best type used in the forecasting system. In this study the data used were the data of West Nusa Tenggara Province (HDI) HDI for the years 2008-2018 to predict the 2019 Human Development Index (HDI) data. This study uses Artificial Intelligence Neuro Fuzzy methods namely Fuzzy Mamdani and ANFIS Sugeno applied to Matlab . The types tested were Trimf, Trapmf, Gbellmf, Gaussmf, Gauss2mf, Sigmf, Dsigmf, Psigmf, and Primf. This type aims to see the level of accuracy based on the results of the error. The best forecasting results were obtained on the Gauss2mf type because it produced a prediction of 69.5 with an error of 0.95947 and MAD of 0.530.354, MSE of 1.570035, MAPE of 0.049273.
Authors and Affiliations
Aenul Muhajirah, Eka Safitri, Titin Mardiana, Hartina Hartina, Andi Setiawan
Keywords
Related Articles
- EP ID EP503677
- DOI 10.31764/jtam.v3i1.769
- Views 158
- Downloads 0
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