Meta-Analisis: Tingkat Akurasi Peramalan Menggunakan Metode Neuro-Fuzzy

Baiq Windi Diska Putri, Syaharuddin Syaharuddin, Kiki Riska Ayu Kurniawati

Abstract


Forecasting is one of the most important elements in decision making. One of the methods used in forecasting is the Neuro-Fuzzy Method, which is a component with different frequencies or an analytical tool commonly used to present data. The purpose of this meta-analysis is to reanalyze the results of research related to forecasting using the neuro-fuzzy method. The data is collected through indexing databases such as Google Scholar. The filtered data is the result of research that contains the value of the amount of data (N), correlation test (r) and classification. Then analyzed using meta-analysis through effect size and standard error to see the summary effect size. The results of data analysis using JASP software show that the Estimate value at the level of forecasting accuracy using the neuro-fuzzy method is 0.974. Which belongs to the high category, there is a classification section called modification and non-modification. The estimate value of the modification is 0.945 and the p-Rank-test value is 0.563, while for non-modification the estimate value is 0.988 and the p-Rank-test value is 0.649, so it is in the high category.


Keywords


Forecasting, Neuro-fuzzy method, Meta-analysis.

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References


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