Implementasi Metode Moving Average Sebagai Prediksi Penjualan Perlengkapan Pertanian Pada CV. Aneka Tani

Abstract

CV. Aneka Tani is a shop that sells various agricultural equipment. The problems in CV. Aneka Tani are the process of recording transactions that are still done manually with a sales book and there is no sales prediction system. It causes waste of paper, human error in transactions, and bad stock management. The purpose of this research is to predict sales of agricultural equipment, applying the Moving Average algorithm to CV. Aneka Tani’s data to generate sales prediction models, and analyze predictive models. The research method used is the CRISP-DM (Cross Industry Standard Process for Data Mining) which consists of business understanding, data understanding, data preparation, modeling, evaluation, and implementation. The process of collecting data is done by conducting interviews with business owners. There were 6 products used in Moving Average method. The stable product is Dafat with MAD value is 0,9 and MSE value is 1,2. The non stabel product is Phonska with MAD value is 13,6 and MSE value is 245,7.