TY - GEN
T1 - Implementation of Time Series Forecasting Using Single Moving Average Model-A Case Study in Printing Industry
AU - Gandesrukma, Nadia Cahyani
AU - Sanjaya, Beryl Putra
AU - Damayanti, Alfina
AU - Nurcahyo, Rahmat
N1 - Publisher Copyright:
© IEOM Society International.
PY - 2021
Y1 - 2021
N2 - The first step in optimizing the overall planning process is to develop a reliable forecasting process. In this paper we discuss the implementation of forecasting in the printing industry, forecasting the timing of demands is one of the critical issues. Time series is a collection of observations made at regular time intervals and its analysis refers to problems in correlations among successive observations. A Simple Moving Average model is a time series constructed by taking averages of several sequential values of another time series. To support the research, data collection from the firm is needed. In order to find the best model, the research will be supported by graphic visualization, analysis, and the accuracy of the Single Moving Average model for demand forecasting with data obtained from the firm over the course of 1-2 years. The demand products are provided by CV. Mitrakom Bintang Kemilau firm. In this paper we calculated 3 different data, two of the three are based on the types of product which have the most sales percentage within 2 years of production, shelf talker and wobbler, the other is total products produced by the firm. Based on the three types of data we gathered two years in advance, we found evidence that forecasting data using the Single Moving Averages model results in 30%-50% errors using the error standard of Mean Absolute Percentage Error (MAPE) supported by Mean Absolute Deviation (MAD) and Mean Squared Error (MSE).
AB - The first step in optimizing the overall planning process is to develop a reliable forecasting process. In this paper we discuss the implementation of forecasting in the printing industry, forecasting the timing of demands is one of the critical issues. Time series is a collection of observations made at regular time intervals and its analysis refers to problems in correlations among successive observations. A Simple Moving Average model is a time series constructed by taking averages of several sequential values of another time series. To support the research, data collection from the firm is needed. In order to find the best model, the research will be supported by graphic visualization, analysis, and the accuracy of the Single Moving Average model for demand forecasting with data obtained from the firm over the course of 1-2 years. The demand products are provided by CV. Mitrakom Bintang Kemilau firm. In this paper we calculated 3 different data, two of the three are based on the types of product which have the most sales percentage within 2 years of production, shelf talker and wobbler, the other is total products produced by the firm. Based on the three types of data we gathered two years in advance, we found evidence that forecasting data using the Single Moving Averages model results in 30%-50% errors using the error standard of Mean Absolute Percentage Error (MAPE) supported by Mean Absolute Deviation (MAD) and Mean Squared Error (MSE).
KW - Accuracy
KW - Forecasting
KW - MAPE
KW - Printing industry
KW - Single moving average
UR - http://www.scopus.com/inward/record.url?scp=85125889723&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:85125889723
SN - 9781792361289
T3 - Proceedings of the International Conference on Industrial Engineering and Operations Management
SP - 313
EP - 323
BT - Proceedings - 2021 IEOM India Conference
A2 - Babu, Shekar
A2 - Shetty, Devdas
A2 - Vasu, V.
A2 - Sharma, R.R.K.
A2 - Ali, Ahad
PB - IEOM Society
T2 - 1st Indian International Conference on Industrial Engineering and Operations Management, IEOM 2021
Y2 - 16 August 2021 through 18 August 2021
ER -