PREDIKSI PENJUALAN OBAT PADA PEDAGANG BESAR FARMASI MENGGUNAKAN METODE PERBANDINGAN EKSPONENSIAL (MPE)

Fransiskus Masan; Sumarlin; Heni

doi:10.46880/mtk.v12i2.6217

Authors

Fransiskus Masan Universitas Uyelindo
Sumarlin Universitas Uyelindo
Heni Universitas Uyelindo

DOI:

https://doi.org/10.46880/mtk.v12i2.6217

Keywords:

Drug Sales Prediction, Entropy Method, Exponential Comparison Method (MPE), Inventory Management, Mean Absolute Percentage Error (MAPE)

Abstract

Mathio Jaya Pharma is a pharmaceutical distribution company that plays an important role in maintaining drug inventory to meet customer demand. Inappropriate inventory management can lead to overstocking, which increases the risk of product expiration, or stock shortages that may disrupt customer service. This study aims to predict drug sales as a basis for inventory procurement planning for the following period. The methods used in this study are the Entropy Method to determine objective criterion weights based on data variation and the Exponential Comparison Method to generate drug sales predictions. The data used consist of drug sales records from January 1 to December 31, 2025, with inventory, price, and total sales as the evaluation criteria. The weights obtained from the Entropy Method are used as input for the MPE calculation to produce sales predictions for the next period. The results indicate that the system is capable of generating drug sales predictions and providing inventory status information categorized as safe or critical. Based on the prediction results, Paracetamol, Dexa, and Caviplex are classified as safe because the available stock is sufficient to meet future demand, while Amoxicillin is categorized as critical and requires additional procurement. Accuracy testing using the Mean Absolute Percentage Error (MAPE) produced values of 74.51% for Paracetamol, 58.33% for Caviplex, 47.51% for Dexa, and 33.33% for Amoxicillin. The findings indicate that the combination of the Entropy Method and the Exponential Comparison Method can assist the company in predicting future drug sales and support more effective and efficient decision-making in inventory management.

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