Article Per Year (5 Year)
p-Index From 2021 - 2026
1.431
P-Index
This Author published in this journals
All Journal IJBE (Integrated Journal of Business and Economics) Jurnal Investasi Budapest International Research and Critics Institute-Journal (BIRCI-Journal): Humanities and Social Sciences Jurnal Pengabdian Pelitabangsa JRAP (Jurnal Riset Akuntansi dan Perpajakan) Jurnal Lentera Pengabdian Dedikasi : Jurnal Pengabdian Lentera
Pujiharta, Pujiharta
Unknown Affiliation
Religion Arts Humanities Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Energy Environmental Science Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Public Health Social Sciences Other

Published : 8 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
Comparative Analysis of Arima Model and Exponential Smoothing in Predicting Inventory in Automotive Companies Pujiharta, Pujiharta; Darma, Yuki Dwi; Wiyanti, Novita Riska; Gunawan, Ahmad
Budapest International Research and Critics Institute (BIRCI-Journal): Humanities and Social Sciences Vol 5, No 1 (2022): Budapest International Research and Critics Institute February
Publisher : Budapest International Research and Critics University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33258/birci.v5i1.3707

Abstract

Forecasting is an activity to predict future events by using and considering data from the past. Forecasting is an important tool in effective and efficient planning. So that demand forecasting can be predicted and the amount of inventory can be determined in order to anticipate the number of varied and fluctuating demand. In order to obtain good forecast results, a forecasting method is used that can predict seasonal data. This study aims to determine the best forecasting model using ARIMA and exponential smoothing methods and to compare the forecasting results with the two methods in order to obtain the best method. Data on the number of requests for cars PT. Suzuki Indomobil Motor 2017 – 2019 is data that contains seasonal patterns so that ARIMA and Holt-Winters exponential smoothing can be used. Data obtained by means of documentation with secondary data collection and literature study. The results show that PT Suzuki Indomobil Motor is more appropriate to use the Holt-Winters Additive exponential smoothing method because the resulting error rate is smaller.
Co-Authors Ahmad Gunawan Darma, Yuki Dwi Dasril, Yuki Dwi Darma Dharma, Yuki Dwi Hanafia, Fifi Hartati, Nani Hutauruk, Basar M. Indriani, Meika Indriati, Petiana Parulian, Parulian Soejarminto, Yos Supriyanto Supriyanto Tan, Emmelia Utami, Asri Wiyanti, Novita Riska