This Author published in this journals
All Journal Mediagro
Suryaningrum, Rahma Sabilah
Unknown Affiliation

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

Penentuan Metode Kuantitatif Terbaik Dalam Peramalan Penjualan Selada Hidroponik Di Setya Agrofarm Ganestyani, Indah Arum; Suryaningrum, Rahma Sabilah
Mediagro: Jurnal Ilmu-ilmu Pertanian Vol 22 No 1 (2026): MEDIAGRO
Publisher : Universitas Wahid Hasyim

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31942/mediagro.v22i1.15135

Abstract

Setya Agrofarm is a business engaged in agriculture, especially hydroponic vegetables with commoodities being lettuce, a business that has only been operating for two years. The research location is located in Blimbing Village, Boja District, Kendal Regency. Setya Agrofarm in hydroponic lettuce cultivation using the NFT (Nutrient Film Technique) system. One of the problems faced in the agricultural business is the uncertainty in vegetables sales, causing conditions of shortage or excess supply, which occurs several times, therefore the importance of forecasting. This uncertainty is caused by several factors including price, weather, and market competition. The respondent sampling techniques uses Nonprobability sampling, namely snowball sampling. This technique was chosen because the data came from the first source which was incomplete and then required information from other sources. The number of forecasting methods, Setya Agrofarm requires an appropriate forecasting method to deal with supply uncertainty and sales trends, the purpose of this study is to determine the best quantitative forecasting method including Naïve, Moving Average, and the single exponentiant smoothing method based on he results of the smaller MAPE (Mean Absolute Percentage Error). The results of the study showed that the most accurate method was to forecast sales using the Moving Average method with a MAPE value of 27.53% at length, this method can be used as a reference for Setya Agrofarm in Forecasting the next one-year period.