PERANCANGAN METODE PERAMALAN PERMINTAAN DAN PERBAIKAN KEBIJAKAN PRODUKSI DI PT SOLAS LANGGENG SEJAHTERA
PT Solas Langgeng Sejahtera is a company that operates in the pharmaceutical sector and produces various types of medicines, supplements, multivitamins, and cosmetics. Since the pandemic of Covid-19, product demand has become unstable. According to the company’s historical data, there was a 17% d...
Saved in:
Main Author: | |
---|---|
Format: | Final Project |
Language: | Indonesia |
Online Access: | https://digilib.itb.ac.id/gdl/view/71324 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Institut Teknologi Bandung |
Language: | Indonesia |
Summary: | PT Solas Langgeng Sejahtera is a company that operates in the pharmaceutical
sector and produces various types of medicines, supplements, multivitamins, and
cosmetics. Since the pandemic of Covid-19, product demand has become unstable.
According to the company’s historical data, there was a 17% decrease in demand
for ethical products in 2020, while demand increased by 12% in 2021. PT Solas
Langgeng Sejahtera is currently experiencing difficulties due to an increase in the
number of pending order each year. The number of pending orders increased by
249% in 2021. The company has not been able to predict demand, so the amount
of product fulfillments to customers is also often delayed due to stockouts.
Currently, the company uses a Simple Moving Average method with N=3 to predict
demand for all product, and the average error value is obtained at 110% using
Mean Absolute Percentage Error (MAPE) method.
This research will design a demand forecasting method by testing five types of
methods, including Simple Moving Average, Single Exponential Smoothing, Double
Exponential Smoothing, Linear Regression, dan Triple Exponential Smoothing.
This research will also design a production policy that is able to minimize total cost
by considering the ratio and minimum stock.
The result show that each product uses different forecasting methods according to
past demand patterns. Using different forecasting methods for each product can
reduce errors by 41,62%. Meanwhile, the production policy us being improved by
changing the minimum stock value using the average demand to reduce the number
of pending orders and total cost. The change in minimum stock resulted in an 8,87%
decrease in the number of pending orders and a 2,15% decrease total costs.
|
---|