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All Journal Journal of Artificial Intelligence and Engineering Applications (JAIEA)
Dolli Sari Sinaga
STIKOM Tunas Bangsa
Automotive Engineering Computer Science & IT Control & Systems Engineering

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PREDICTION OF PRODUCT SALES RESULTS USING ADAPTIVE NEURO FUZZY INFERENCE SYSTEM (ANFIS) Dolli Sari Sinaga; Agus Perdana Windarto; Rizki Alfadillah Nasution; Irfan Sudahri Damanik
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 1 No. 2 (2022): February 2022
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1579.262 KB) | DOI: 10.53842/jaiea.v1i2.73

Abstract

This study aims to optimize profits and minimize losses from product sales at X Market has achieved in the future. The data used in this study were obtained directly from X Market Trade by observing and interviewing. X Market Tradingis one of the industries that produces and sells food products to be marketed in the region and outside the region. The data to be processed is the result of the sale of food products at X Market uses the adaptive neuro fuzzy inference system (ANFIS) method which is a combination of Fuzzy Logic and Artificial Neural Networks. The data used is monthly sales data from 2018 to 2020 as many as 36 data. From a total of 36 data, it will be divided into 2 types of training and test data distribution, namely 90:10 with a total of 60 epochs and a learning rate range of 0.1 – 0.9. From the research results obtained the highest accuracy of 88.55% on 90% training data and 10% test data with a learning rate of 0.6. It was concluded that the ANFIS method could be implemented in predicting the sales of tofu. By doing this research is expected to provide input to X Market in optimizing profits and minimizing losses from product sales in the future.
Co-Authors Agus Perdana Windarto Irfan Sudahri Damani, Irfan Sudahri Nasution, Rizki Alfadillah