Dinasti International Journal of Management Science
Vol. 2 No. 3 (2021): Dinasti International Journal of Management Science (January - February 2021)

INVENTORY MANAGEMENT ANALYSIS BY OPTIMIZING THE FORCASTING METHODS (CASE STUDY AT PT XYZ INDONESIA)

Eddy Nugroho, Rosalendro (Unknown)
Resodiharjo, Maryana (Unknown)



Article Info

Publish Date
23 Jan 2021

Abstract

This research aims to analyze inventory management by optimizing the forecasting method at PT XYZ Indonesia. The research approach that used was descriptive research with the aim of explaining and describing the object of research by qualitative and quantitative data. Qualitative data defined a description from the activities of a company which was carried out by managing inventory. Quantitative data in form of sales data, inventory data, quantity data of the arrival of goods in the company. The research was conducted in the Storage System department using data for 30 months from January 2014 to June 2016. From the ABC analysis data conducted by the company, A category was taken as many as 10 items (stock keeping units). The results of research using the three types of forecasting methods, it is known that on the article level the smallest MAD value was for D product with linear regression forecasting method. The smallest MAPE value was for C product with simple moving average forecasting method. On the level of aggregate products, the smallest MAD and MAPE values were exponential smoothing forecasting, thus the exponential smoothing forecasting method is a method to predicts the smallest and most accurate aggregate for product deviation.

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Journal Info

Abbrev

DIJMS

Publisher

Subject

Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Industrial & Manufacturing Engineering Other

Description

This research was carried out on Build Operate Transfer investment in Business cooperation model to metering system development project by examinated those criterias by technology preparedness level (TKT) evaluation method, Innovation preparedness level and political, social economic, technology, ...