Prediksi Tingkat Penjualan Pupuk Urea dengan Metode Monte Carlo

  • Rahmatia Wulan Dari
    Universitas Putra Indonesia YPTK Padang


Keywords: Prediction, Urea Fertilizer, Stock Control, Shallot, Monte Carlo Method

Abstract

The development of science and information technology over time is very rapid in today's era, one of which is the agricultural sector. In the agricultural sector, there are many things that utilize technology, such as shallot cultivation. The need for shallots is very high, so many farmers plant shallots. To produce shallots of good quality and have a high selling price, farmers provide nutrition for the shallots they plant. The nutrient that onions really need is urea fertilizer. The fluctuating need for fertilizer for each farmer results in the availability of fertilizer in Kiosks often experiencing shortages. This has an impact on the scarcity of the availability of urea fertilizer. So this research was carried out to predict the level of sales of urea fertilizer in maintaining the need for fertilizer for shallot plants at Kiosk Pak De. Fertilizer availability aims to prepare stocks to avoid scarcity at a later time. The method used in this study is the Monte Carlo Method. This method is a method that can predict based on repeated random sampling. This method can also be used in various aspects of imputation systems and prediction of missing data. The data used in this study are sales data for urea fertilizer from 2020 to 2021. Sales data for 2020 are used to predict sales for 2021 and sales data for 2021 are used to predict sales for 2022. The results obtained from this study are the prediction rate for in 2020 with an accuracy rate of 92% and an accuracy in 2021 of 92.25%. From these results it can be concluded that this method can help Kios Pak De in maintaining scarcity in the sale of urea fertilizer

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Published
2022-12-20
Section
Articles
How to Cite
Dari, R. W. (2022). Prediksi Tingkat Penjualan Pupuk Urea dengan Metode Monte Carlo. Jurnal Informasi Dan Teknologi, 4(4), 271-275. https://doi.org/10.37034/jidt.v4i4.251