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Journal : Jurnal ATMOSPHERE

PERENCANAAN MANAJEMEN RANTAI PASOK DAUN MURBEI JENIS MORRUS ALBA L. UNTUK PRODUKSI TEH HERBAL Ayudya Mahendaringratry
jurnal ATMOSPHERE Vol. 5 No. 1 (2024): ATMOSPHERE
Publisher : Teknik Kimia ITN Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36040/atmosphere.v5i1.11009

Abstract

PKK RT II RW VI, Tlogomas Village, Malang City, is an iconic area, namely the mulberry area, where every house in this area has at least 2 mulberry plants of the Morrus Alba L type. So far, members of PKK Rdaun mulberry kareT II RW VI, Merjosari Village, Malang strives to produce products made from mulberry, both fruit and leaves and stems/ratings. One product that is expected to become a mainstay is herbal tea made from mulberry leaves because the content in mulberry leaves is very good for human health. The main obstacle that arises when applying supply chain management (SCM) is the supply of raw materials which are usually obtained from local residents, with the production process being dried in the sun and roasted, resulting in small amounts of raw materials shrinking by 60%. The supply of raw materials needs to be increased through land improvement and mulberry plant seeds. If raw materials are available in abundance, marketing will be wide open for mulberry leaf herbal tea products.
ANALISIS METODE FORECASTING UNTUK MENINGKATKAN PENJUALAN BAKPIA LESTARI MALANG Aryafi, Javiery Khansa; Mahendaringratry, Ayudya
jurnal ATMOSPHERE Vol. 6 No. 1 (2025): ATMOSPHERE
Publisher : Teknik Kimia ITN Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36040/atmosphere.v6i1.14774

Abstract

This research aims to forecast the sales of bakpia products at UMKM Bakpia Lestari Malang to support production planning to be more optimal. The main problems faced are fluctuations in demand and limited production capacity caused by the implementation of a hybrid system, which is a combination of Make to Stock and Make to Order. A quantitative approach is used in this research by processing sales data for one year, and comparing five forecasting methods, namely Single Moving Averages, Weighted Moving Averages, Exponential Smoothing, Trend Projection, and Exponential Trend. The accuracy of each method is evaluated using Mean Absolute Deviation (MAD) and Mean Squared Error (MSE) indicators. The analysis results show that the Exponential Smoothing method with (α = 0.5) produces the lowest error rate, namely MAD of 55.56 and MSE of 10796.74. Therefore, this method is recommended as the best approach for forecasting sales in June 2025. These results are expected to be a reference for UMKM in managing the production process more efficiently and on target.