APLIKASI PERAMALAN PENJUALAN OBAT BERBASIS METODE SINGLE EXPONENTIAL SMOOTHING (STUDI KASUS: APOTEK BUNGSU KENDARI)
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Institusion
Institut Teknologi Perusahaan Listrik Negara
Author
SAINUDDIN, SHAFIRA AULIA RAMADANI
Aziza, Rosida Nur
Ningrum, Rahma Farah
Aziza, Rosida Nur
Ningrum, Rahma Farah
Subject
Teknik Informatika
Datestamp
2023-05-31 07:50:38
Abstract :
Forecasting is an obligatory activity that is used to predicting future demand. In the Bungsu pharmaceutical company there are 20-50 sales transactions that must be recorded on a daily basis. As a results, to construct a drug data sales forecasting system in a pharmaceutical, pharmacists have complexities estimating the amount to order of each type in the following month. As a result, to construct a drug data sales forecasting system in a pharmacy, the researcher conducted an ongoing system analysis process. The Single Exponential Smoothing method is considered the most suitable for forecasting drug sales data since it is a forecasting method on moving averages by providing weights which are unchallenging to analyze. Forecasting analysis is done by looking for the best alpha (?) value so as to produce an accurate forecast. The use of data from the last 10 months as a reference data for recording the past for forecasting experiments for the following month. Experiments with different alphas produced the most accurate value, namely ?=0.1 with the smallest error rate, namely the smallest MSE=358, 041 and MAPE=22%.
Forecasting is an obligatory activity that is used to predicting future demand. In the Bungsu pharmaceutical company there are 20-50 sales transactions that must be recorded on a daily basis. As a results, to construct a drug data sales forecasting system in a pharmaceutical, pharmacists have complexities estimating the amount to order of each type in the following month. As a result, to construct a drug data sales forecasting system in a pharmacy, the researcher conducted an ongoing system analysis process. The Single Exponential Smoothing method is considered the most suitable for forecasting drug sales data since it is a forecasting method on moving averages by providing weights which are unchallenging to analyze. Forecasting analysis is done by looking for the best alpha (?) value so as to produce an accurate forecast. The use of data from the last 10 months as a reference data for recording the past for forecasting experiments for the following month. Experiments with different alphas produced the most accurate value, namely ?=0.1 with the smallest error rate, namely the smallest MSE=358, 041 and MAPE=22%.
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