Proceedings of the 4th Asia Pacific Management Research Conference (APMRC 2022)

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Analyzing the Suitability of Time Series and Associative Forecasting Methods for Cotton Bud Product

Authors
Siti Cahya Santini1, *, Devilia Sari1, Lidya Nur Assifa2
1International Business Administration Department, Telkom University, Bandung, Indonesia
2Faculty of Earth Science and Technology, Bandung Institute of Technology, Bandung, Indonesia
*Corresponding author. Email: ceiysitisansan@gmail.com
Corresponding Author
Siti Cahya Santini
Available Online 12 December 2022.
DOI
10.2991/978-94-6463-076-3_19How to use a DOI?
Keywords
Forecasting; Forecasting Error; Moving Range Chart; Polynomial Regression
Abstract

At PT DBAS, the main problem is the problem of BABY-GRADE-A supply/demand. If a production shortage occurs, the company loses sales leading to overwork and costs. Likewise, suppose there is overproduction, even though the product is durable with a more extended expiration date. In that case, warehousing problems may arise, such as limited warehouses, higher inventory costs, damaged products, and environmental issues. Thus, this study is conducted to discover a suitable forecasting method for BABY-GRADE-A to forecast its future demand and sales figures of BABY-GRADE-A in 2021. This research uses a quantitative descriptive method by comparing the measurement of sales data errors in the time series and polynomial regression methods. To conclude, the most suitable forecasting method for BABY-GRADE-A is Polynomial Regression. MSE and MAPE resulting from the technique are 6,103.18 and 9.07%, respectively. Then, the forecast demand in 2021 is predicted to be 11,426 cartons. Significantly, several aspects should be considered by the company and future researchers, such as market change, marketing strategy, inventory management, and other operations activities.

Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the 4th Asia Pacific Management Research Conference (APMRC 2022)
Series
Advances in Economics, Business and Management Research
Publication Date
12 December 2022
ISBN
978-94-6463-076-3
ISSN
2352-5428
DOI
10.2991/978-94-6463-076-3_19How to use a DOI?
Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Siti Cahya Santini
AU  - Devilia Sari
AU  - Lidya Nur Assifa
PY  - 2022
DA  - 2022/12/12
TI  - Analyzing the Suitability of Time Series and Associative Forecasting Methods for Cotton Bud Product
BT  - Proceedings of the 4th Asia Pacific Management Research Conference (APMRC 2022)
PB  - Atlantis Press
SP  - 259
EP  - 268
SN  - 2352-5428
UR  - https://doi.org/10.2991/978-94-6463-076-3_19
DO  - 10.2991/978-94-6463-076-3_19
ID  - Santini2022
ER  -