Research Article
Application of the Naïve Bayes Algorithm and Simple Exponential Smoothing for Food Commodity Prices Forecasting
@INPROCEEDINGS{10.4108/eai.2-5-2019.2284613, author={Muhammad Lutfi and Hidayatul Muttaqien and Aulia Apriliani and Hazriani Zainuddin and Yuyun Yuyun}, title={Application of the Na\~{n}ve Bayes Algorithm and Simple Exponential Smoothing for Food Commodity Prices Forecasting}, proceedings={1st International Conference on Science and Technology, ICOST 2019, 2-3 May, Makassar, Indonesia}, publisher={EAI}, proceedings_a={ICOST}, year={2019}, month={6}, keywords={forecasting commodity price}, doi={10.4108/eai.2-5-2019.2284613} }- Muhammad Lutfi
Hidayatul Muttaqien
Aulia Apriliani
Hazriani Zainuddin
Yuyun Yuyun
Year: 2019
Application of the Naïve Bayes Algorithm and Simple Exponential Smoothing for Food Commodity Prices Forecasting
ICOST
EAI
DOI: 10.4108/eai.2-5-2019.2284613
Abstract
Inconstancy of the market prices can affect society's purchasing power. One effort to anticipate the price uncertainty is by conducting commodity price forecasting. In the concept of forecasting, the commodity prices can be predicted by studying sales data in the previous period. This study aims to implement a decision support system in predicting food commodity prices trend. In data collection, the authors used list of food commodities provided by Industry and Trade Service of Gowa Regency. For data analysis, we use Naive Bayes algorithm to predict the food commodity prices in the future and Simple Exponential Smoothing to find out the price trend in a certain period. As a result, both methods can predict commodity prices and market tendency in a given time completely.