SALES FORECASTING FOR MIXUE ICE CREAM PRODUCTS USING THE TREND MOMENT METHOD
Abstract viewed = 369 times
PDF (Bahasa Indonesia) downloaded = 422 times
Abstract
Sales of consumen products often experience fluctuations each period, so proper sales planning is required to ensure that the company’s operational activities run smoothly. The problem that arises is the absence of a forecasting model that is easy to use but capable of producing accurate results. This study aims to develop a sales forecasting model using the Trend Moment method. This method is chosen because it is simple and can be used to identify the direction of trends based on previous sales data. This study utilizes monthly sales data collected over a one-year period. The Trend Moment method in this study successfully achieved a MAPE value of 1.8% and an accuracy rate of 98.2%. These values indicate that the model is sufficiently accurate in forecasting sales. The results of this model can assist the company in planning production, managing distribution, and controlling inventory. This study is also beneficial as a basis for developing simple forecasting models for similar products in the future.
Downloads
Download data is not yet available.
References
Adam Suhaidi Batubara, A. S. B., Dafitri, H., & Faisal, I. (2022). Analysis of Linear Regression and Trend Moment Methods in Predicting Sales Using Mape. Jurnal Sistem Informasi Dan Ilmu Komputer Prima(JUSIKOM PRIMA), 6(1), 75–81. https://doi.org/10.34012/jurnalsisteminformasidanilmukomputer.v6i1.2919
Adeputra, J., & Pratiwi, H. (2025). Optimization of Spareparts Stock Data Management at PT . Astra Motor Kaltim 2 using the Trend Moment Method. 8(158), 326–332.
Ali, A. A. A., Fayad, A. A. S., Alomair, A., & Al Naim, A. S. (2024). The Role of Digital Supply Chain on Inventory Management Effectiveness within Engineering Companies in Jordan. Sustainability, 16(18), 8031. https://www.mdpi.com/2071-1050/16/18/8031
Alzeyani, E. M. M., & Szabó, C. (2024). Comparative Evaluation of Model Accuracy for Predicting Selected Attributes in Agile Project Management. Mathematics, 12(16). https://doi.org/10.3390/math12162529
Bartsch, F., Zeugner-Roth, K. P., & Katsikeas, C. S. (2022). Consumer authenticity seeking: conceptualization, measurement, and contingent effects. Journal of the Academy of Marketing Science, 50(2), 296–323. https://doi.org/10.1007/s11747-021-00813-y
Cruso, J. (2024). Digital Transformation : Redefining Business in the Digital Age Abstract. 2015, 2015–2017. https://doi.org/10.36648/1550-7521.22.70.445
Fauzan, A., Rahayu, D. G., Handayani, A., Tahyudin, I., Saputra, D. I. S., & Purwadi, P. (2023). Sales Forecasting Analysis Using Trend Moment Method: A Study Case of a Fast Moving Consumer Goods Company in Indonesia. Journal of Information Technology and Cyber Security, 1(1), 1–8. https://doi.org/10.30996/jitcs.7572
Fildes, R., Kolassa, S., & Ma, S. (2022). Post-script—Retail forecasting: Research and practice. International Journal of Forecasting, 38(4), 1319–1324. https://doi.org/10.1016/j.ijforecast.2021.09.012
Firmansyah, R., Puspitorini, S., Pariyadi, P., & Syah, T. (2021). Sales and Stock Purchase Prediction System Using Trend Moment Method and FIS Tsukamoto. Arcitech: Journal of Computer Science and Artificial Intelligence, 1(1), 15. https://doi.org/10.29240/arcitech.v1i1.3057
Fitri Safira, S., Rohman, F., & Aisjah, S. (2024). The Effect of Country of Origin and Price on Purchase Intention Mediated by Trust : A Study on Mixue Global Franchising Consumers in Malang City. IRJEMS International Research Journal of Economics and Management Studies, 3(4), 325–332. https://doi.org/10.56472/25835238/IRJEMS-V3I4P142
Iriyanti, M. P., Kurniawati, A., & Widiastuti, W. (2022). Sales Stock Forecasting System Using Trend Moment Method (Study Case: Warcam Store). Jurnal Teknik Informatika (Jutif), 3(5), 1131–1140. https://doi.org/10.20884/1.jutif.2022.3.5.161
Khandhar, M. A. (2025). Sales Forecast and Inventory Management Using ML. International Journal for Research in Applied Science and Engineering Technology, 13(1), 1982–1988. https://doi.org/10.22214/ijraset.2025.66732
Mweshi, G. K., & Muhyila, M. (2024). Determining a Statistical Analysis for the Quantitative Study in Research. Advances in Social Sciences Research Journal, 11(7), 187–231. https://doi.org/10.14738/assrj.117.17018
Nikulchev, E., & Chervyakov, A. (2023). Development of Trading Strategies Using Time Series Based on Robust Interval Forecasts. Computation, 11(5). https://doi.org/10.3390/computation11050099
O’Hare, J., Dekoninck, E., Mombeshora, M., Martens, P., Becattini, N., & Boujut, J. F. (2020). Defining requirements for an Augmented Reality system to overcome the challenges of creating and using design representations in co-design sessions. CoDesign, 16(2), 111–134. https://doi.org/10.1080/15710882.2018.1546319
Permatahati, I., & Muqorobin, M. (2022). Computer Sales Forecasting System Application Using Web-Based Single Moving Average Method. International Journal of Computer and Information System (IJCIS), 3(2), 56–63. https://doi.org/10.29040/ijcis.v3i2.68
Sewu, P. L. S., Tresnawati, & Rachelia, C. (2024). Legal Analysis of the Success of Mixue Franchise Schemes in Singapore, South Korea, and Japan Linked to the Success of Mixue Franchise Schemes in Indonesia and Vietnam. European Journal of Law and Political Science, 3(2), 18–27. https://doi.org/10.24018/ejpolitics.2024.3.2.126
Shrikhande, P. (2024). Sales Forecasting Methods : A Comparative Study with Excel-Based Analysis. 1–11. https://doi.org/10.55041/IJSREM38171
Tarsini, I., & Anggraeni, R. (2024). Explore flowchart and pseudocode concepts in algorithms and programming. Indonesian Journal of Multidisciplinary Science, 3(5). https://doi.org/10.55324/ijoms.v3i5.807
Titis Sri Wulan, Putri Wahyu Novika, Elmi Nurvianti, & Feby Arma Putra. (2024). Impact of ERP System Implementation on Operational and Financial Efficiency in Manufacturing Industry. Journal of Economic Education and Entrepreneurship Studies, 5(3), 491–501. https://doi.org/10.62794/je3s.v5i3.4328
Wahedi, H. J., Heltoft, M., Christophersen, G. J., Severinsen, T., Saha, S., & Nielsen, I. E. (2023). Forecasting and Inventory Planning: An Empirical Investigation of Classical and Machine Learning Approaches for Svanehøj’s Future Software Consolidation. Applied Sciences (Switzerland), 13(15), 1–21. https://doi.org/10.3390/app13158581
Yulisetiarini, D., Nurhayati, Tamara, A., & Subagio, A. (2023). The Effect of Brand Image And Trust on Loyalty Through Customer Satisfaction as an Intervening Variable at KFC in Jember. Journal of Innovations in Business and Industry, 03(02), 111–116.
Zhou, Y., Shen, X., & Yu, Y. (2023). Inventory control strategy: based on demand forecast error. Modern Supply Chain Research and Applications, 5(2), 74–101. https://doi.org/10.1108/mscra-02-2023-0009
Adeputra, J., & Pratiwi, H. (2025). Optimization of Spareparts Stock Data Management at PT . Astra Motor Kaltim 2 using the Trend Moment Method. 8(158), 326–332.
Ali, A. A. A., Fayad, A. A. S., Alomair, A., & Al Naim, A. S. (2024). The Role of Digital Supply Chain on Inventory Management Effectiveness within Engineering Companies in Jordan. Sustainability, 16(18), 8031. https://www.mdpi.com/2071-1050/16/18/8031
Alzeyani, E. M. M., & Szabó, C. (2024). Comparative Evaluation of Model Accuracy for Predicting Selected Attributes in Agile Project Management. Mathematics, 12(16). https://doi.org/10.3390/math12162529
Bartsch, F., Zeugner-Roth, K. P., & Katsikeas, C. S. (2022). Consumer authenticity seeking: conceptualization, measurement, and contingent effects. Journal of the Academy of Marketing Science, 50(2), 296–323. https://doi.org/10.1007/s11747-021-00813-y
Cruso, J. (2024). Digital Transformation : Redefining Business in the Digital Age Abstract. 2015, 2015–2017. https://doi.org/10.36648/1550-7521.22.70.445
Fauzan, A., Rahayu, D. G., Handayani, A., Tahyudin, I., Saputra, D. I. S., & Purwadi, P. (2023). Sales Forecasting Analysis Using Trend Moment Method: A Study Case of a Fast Moving Consumer Goods Company in Indonesia. Journal of Information Technology and Cyber Security, 1(1), 1–8. https://doi.org/10.30996/jitcs.7572
Fildes, R., Kolassa, S., & Ma, S. (2022). Post-script—Retail forecasting: Research and practice. International Journal of Forecasting, 38(4), 1319–1324. https://doi.org/10.1016/j.ijforecast.2021.09.012
Firmansyah, R., Puspitorini, S., Pariyadi, P., & Syah, T. (2021). Sales and Stock Purchase Prediction System Using Trend Moment Method and FIS Tsukamoto. Arcitech: Journal of Computer Science and Artificial Intelligence, 1(1), 15. https://doi.org/10.29240/arcitech.v1i1.3057
Fitri Safira, S., Rohman, F., & Aisjah, S. (2024). The Effect of Country of Origin and Price on Purchase Intention Mediated by Trust : A Study on Mixue Global Franchising Consumers in Malang City. IRJEMS International Research Journal of Economics and Management Studies, 3(4), 325–332. https://doi.org/10.56472/25835238/IRJEMS-V3I4P142
Iriyanti, M. P., Kurniawati, A., & Widiastuti, W. (2022). Sales Stock Forecasting System Using Trend Moment Method (Study Case: Warcam Store). Jurnal Teknik Informatika (Jutif), 3(5), 1131–1140. https://doi.org/10.20884/1.jutif.2022.3.5.161
Khandhar, M. A. (2025). Sales Forecast and Inventory Management Using ML. International Journal for Research in Applied Science and Engineering Technology, 13(1), 1982–1988. https://doi.org/10.22214/ijraset.2025.66732
Mweshi, G. K., & Muhyila, M. (2024). Determining a Statistical Analysis for the Quantitative Study in Research. Advances in Social Sciences Research Journal, 11(7), 187–231. https://doi.org/10.14738/assrj.117.17018
Nikulchev, E., & Chervyakov, A. (2023). Development of Trading Strategies Using Time Series Based on Robust Interval Forecasts. Computation, 11(5). https://doi.org/10.3390/computation11050099
O’Hare, J., Dekoninck, E., Mombeshora, M., Martens, P., Becattini, N., & Boujut, J. F. (2020). Defining requirements for an Augmented Reality system to overcome the challenges of creating and using design representations in co-design sessions. CoDesign, 16(2), 111–134. https://doi.org/10.1080/15710882.2018.1546319
Permatahati, I., & Muqorobin, M. (2022). Computer Sales Forecasting System Application Using Web-Based Single Moving Average Method. International Journal of Computer and Information System (IJCIS), 3(2), 56–63. https://doi.org/10.29040/ijcis.v3i2.68
Sewu, P. L. S., Tresnawati, & Rachelia, C. (2024). Legal Analysis of the Success of Mixue Franchise Schemes in Singapore, South Korea, and Japan Linked to the Success of Mixue Franchise Schemes in Indonesia and Vietnam. European Journal of Law and Political Science, 3(2), 18–27. https://doi.org/10.24018/ejpolitics.2024.3.2.126
Shrikhande, P. (2024). Sales Forecasting Methods : A Comparative Study with Excel-Based Analysis. 1–11. https://doi.org/10.55041/IJSREM38171
Tarsini, I., & Anggraeni, R. (2024). Explore flowchart and pseudocode concepts in algorithms and programming. Indonesian Journal of Multidisciplinary Science, 3(5). https://doi.org/10.55324/ijoms.v3i5.807
Titis Sri Wulan, Putri Wahyu Novika, Elmi Nurvianti, & Feby Arma Putra. (2024). Impact of ERP System Implementation on Operational and Financial Efficiency in Manufacturing Industry. Journal of Economic Education and Entrepreneurship Studies, 5(3), 491–501. https://doi.org/10.62794/je3s.v5i3.4328
Wahedi, H. J., Heltoft, M., Christophersen, G. J., Severinsen, T., Saha, S., & Nielsen, I. E. (2023). Forecasting and Inventory Planning: An Empirical Investigation of Classical and Machine Learning Approaches for Svanehøj’s Future Software Consolidation. Applied Sciences (Switzerland), 13(15), 1–21. https://doi.org/10.3390/app13158581
Yulisetiarini, D., Nurhayati, Tamara, A., & Subagio, A. (2023). The Effect of Brand Image And Trust on Loyalty Through Customer Satisfaction as an Intervening Variable at KFC in Jember. Journal of Innovations in Business and Industry, 03(02), 111–116.
Zhou, Y., Shen, X., & Yu, Y. (2023). Inventory control strategy: based on demand forecast error. Modern Supply Chain Research and Applications, 5(2), 74–101. https://doi.org/10.1108/mscra-02-2023-0009
Published
2025-07-17
How to Cite
TAMBUNAN, Fitra Dorica; ANITA, Anita; CHRISTIN, Julia.
SALES FORECASTING FOR MIXUE ICE CREAM PRODUCTS USING THE TREND MOMENT METHOD.
JOISIE (Journal Of Information Systems And Informatics Engineering), [S.l.], v. 9, n. 2, p. 306-314, july 2025.
ISSN 2527-3116.
Available at: <https://ejournal.pelitaindonesia.ac.id/ojs32/index.php/JOISIE/article/view/5086>. Date accessed: 07 nov. 2025.
doi: https://doi.org/10.35145/joisie.v9i2.5086.
Issue
Section
Articles
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
