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Journal : Mathematical Journal of Modelling and Forecasting

Analysis of Raw Material Inventory Control using the ABC Analysis Method and EOQ Method in the Fajar Onion Crackers Business Ledy Vanesa; Helma, Helma
Mathematical Journal of Modelling and Forecasting Vol. 1 No. 1 (2023): June 2023
Publisher : Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/mjmf.v1i1.7

Abstract

Inventory control is one aspect that affect the company's smooth operation. In this study, the Activity Based Costing (ABC) analysis method and the Economic Order Quantity (EOQ) method are applied to control raw material inventory. The Bawang Fajar cracker business is one of the SMEs whose raw material inventory control has yet to use the ABC analysis method and the EOQ method. This research is applied research. Based on the results of this study, it was found that the grouping of raw material inventories according to ABC analysis was divided into three groups, namely group A; wheat flour and cooking oil, group B; eggs, and group C; onion and garlic. The TIC value based on the EOQ method is Rp. 1,749,102.00, while the TIC value based on the method used by the company is Rp. 3,582,200.00. So that the EOQ method is more effective than the method used by the company in the Fajar Bawang Crackers Business.
Geographically Weighted Regression Analysis on Cases of Malnutrition Under Five in the West Sumatra Sandriani, Fifi; Helma, Helma
Mathematical Journal of Modelling and Forecasting Vol. 1 No. 1 (2023): June 2023
Publisher : Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/mjmf.v1i1.8

Abstract

Malnutrition is a condition experienced by toddlers due to low nutrition or nutritional needs that have not been met. Effort to improve health status by improving the nutritional status of toddlers. The purpose of this research is clarify the Geographically Weighted Regression model is the best model when compared to the multiple linear regression model. The data used was obtained data from the West Sumatra Provincial Helath Office for 2020. The dependent variable used is the percentage of cases of malnutrition and there are several independent variables, namely the percentage of children under five who were given vitamin A, the percentage of babies who were exclusively breastfeed, and babies born with low birth weight. The results showed that the gwr model can explain the diversity of cases of malnutrition of children under five by 99% with a total squared error of 0.002 compared with multiple linear regression model which is able to explain the diversity of cases of malnutrition among children under five by 43% with a total squared errors of 0.585. It is concluded that the gwr model is the best model.