Penerapan Metode Least Square Untuk Memprediksi Harga Pangan Di Kota Gorontalo - lahabu, sintiya; Sudirman S; Harun, Rofiq (Teknik Informatika Fakultas Ilmu Komputer Universitas Ichsan Gorontalo, 2023)
Abstract ; This study aims to predict food prices in Gorontalo city. Food is a basic human need. Garlic (Allium sativum) is a type of food and is one of the commodities to be developed because it has become a community need as a spice almost in every dish. The increase in onion prices is highly dependent on the harvest and planting seasons. It is also affected by weather and pest attacks. In addition, price increases are also related to marketing activities. If compared to consumer areas, onion prices in producer areas are lower. The main problem is the difficulty of predicting food prices, especially garlic which can change at any time due to the unstable availability in the market. It is influenced by several factors such as weather and pest attacks. This study wants to create a system with data mining techniques that will be used to predict food prices in Gorontalo city based on previous food price data and using the Least Square method and finding the level of error using the Mean Absolute Percentage Error (MAPE). The result of the level of accuracy for food prices is 80.59%. The results of this accuracy can be categorized that the application made is feasible to be used in predicting food prices in Gorontalo city. Keywords: Least Square, food price prediction, MAPE