Pengembangan Model Prediksi Penjualan Ice Cream UMKM Jogja Menggunakan Metode Autoregressive

Authors

  • Muhammad Rais Ramadhani Universitas Duta Bangsa, Indonesia
  • Nurmalitasari Universitas Duta Bangsa, Indonesia
  • Nurchim Universitas Duta Bangsa, Indonesia

DOI:

https://doi.org/10.31316/jderivat.v10i2.6289

Abstract

There are Micro Small Medium Enterprises (MSMEs) Jogja is included in the new category because of its launch in early 2023, but it already has a total turnover of hundreds of millions. This MSME focuses on enlisted Ice Cream sales with dozens of Ice Cream menu variants. The unstable level of sales originating from trends or seasons becomes a separate enemy for business actors. This study aims to carry out the permanent sales of MSME Jogja using the autoregressive method. The steps taken are (1) data collection, (2) Calculation of ACF and PACF, (3) data processing, and (4) calculation of error values. The data used in the current study is the 8 -8-month sales transaction data. The results showed that the autoregressive method can predict the sale of MSME Jogja with a low error value of MAE = 0.18 and RMSE = 0.14. With this, Ice Cream sales predictions using the Autoregressive Method can be accepted, which results in sales predictions in the following month, May 2024, as many as 1,118 products were sold. Suggestions for further researchers to research each existing menu variant.

Keywords: Prediction, Sales, Ice Cream, Autoregressive

References

Anggraeni, D. T. (2020). Peramalan Harga Saham Menggunakan Metode Autoregressive Dan Web Scrapping Pada Indeks Saham Lq45 Dengan Python. Rabit : Jurnal Teknologi Dan Sistem Informasi Univrab, 5(2), 137–144. https://doi.org/10.36341/rabit.v5i2.1401

Ciptady, K., Harahap, M., Jonvin, J., Ndruru, Y., & Ibadurrahman, I. (2022). Prediksi Kualitas Kopi Dengan Algoritma Random Forest Melalui Pendekatan Data Science. Data Sciences Indonesia (DSI), 2(1). https://doi.org/10.47709/dsi.v2i1.1708

Ensafi, Y., Amin, S. H., Zhang, G., & Shah, B. (2022). Time-series forecasting of seasonal items sales using machine learning – A comparative analysis. International Journal of Information Management Data Insights, 2(1), 100058. https://doi.org/10.1016/j.jjimei.2022.100058

Eriva, C. Y., Arfiani, M., Ramadhan, R., Fauziah, S. R., & Paramita, S. (2022). Jurnal Ilmiah Akuntansi Peradaban. Jurnal Ilmiah Akuntansi Peradaban, VIII(2), 157–169.

Hani’ah, M., & Kurniawan, Y. (2023). Optimasi Parameter Holt–Winters Exponential Smoothing Menggunakan Multivariabel Golden Section Untuk Prediksi Penjualan Mobil Indonesia. G-Tech: Jurnal Teknologi Terapan, 7(2), 596–609. https://doi.org/10.33379/gtech.v7i2.2386

Hartanto, B., Fitriasih, S. H., & Tomo, S. (2022). Sistem Informasi Prediksi Jumlah Pendaftar Calon Siswa Baru Di SMK Muhammadiyah 2 Sukoharjo Menggunakan Metode Autoregressive. Jurnal SITECH : Sistem Informasi Dan Teknologi, 4(2), 147–154. https://doi.org/10.24176/sitech.v4i2.6795

Hassyddiqy, H., & Hasdiana, H. (2023). Analisis Peramalan (Forecasting) Penjualan Dengan Metode ARIMA (Autoregressive Integrated Moving Average) Pada Huebee Indonesia. Data Sciences Indonesia (DSI), 2(2), 92–100. https://doi.org/10.47709/dsi.v2i2.2022

Hawaldar, I. T., Ullal, M. S., Sarea, A., Mathukutti, R. T., & Joseph, N. (2022). The Study on Digital Marketing Influences on Sales for B2B Start-Ups in South Asia. Journal of Open Innovation: Technology, Market, and Complexity, 8(1), 23. https://doi.org/10.3390/joitmc8010023

Karima, Y., Putri, Z. E. B., & Purwanto, E. (2023). Penerapan Digital Marketing di UMKM Kripik Pisang Nickii Etjo Sukoharjo dalam Meningkatkan Omset Penjualan. Seminar Nasional & Call for Paper HUBISINTEK , 1–8. https://datareportal.com/reports/digital-2022-indonesia

Mardiyono, A., Purwanto, E., & Nurmalitasari, N. (2022). Sistem Informasi Prediksi Penerimaan Siswa Baru Menggunakan Metode Autoregressive Di SMP Negeri 3 Purwantoro. Bianglala Informatika, 10(1), 7–11. https://doi.org/10.31294/bi.v10i1.11850

Prasetiya, D., Pohan, M. E., Abdillah, M. A., & ... (2023). Analisis Metode Peramalan Penjualan Guna Menentukan Jumlah Persediaan (Suryana’s Ice Cream). Jurnal Pendidikan Tambusai, 7(3), 28692–28696. https://doi.org/10.31004/jptam.v7i3.11561

Pristiwanto. (2022). Autoregressive Integrated Moving Average (Arima) Dalam Memprediksi Jumlah Penjualan Frame. Jurnal Multimedia Dan Teknologi Informasi (Jatilima), 2(1), 36–45. https://doi.org/10.54209/jatilima.v2i1.142

Sinaga, S. A. (2023). Implementasi Metode Arima (Autoregressive Moving Average) Untuk Prediksi Penjualan Mobil. Journal Global Technology Computer, 2(3), 102–109. https://doi.org/10.47065/jogtc.v2i3.4013

Singagerda, F. S., Rahmawati, L., & Sabri, A. Z. S. A. (2024). Linking supply chain management practices with supply chain performance and food and beverage: Evidence from SMEs’ competitive advantage. Uncertain Supply Chain Management, 12(2), 829–840. https://doi.org/10.5267/j.uscm.2024.1.004

Subhani, M. I., Ezhak, E., Osman, A., & Prachyangprecha, S. (2022). Volatilities in Market Shares through Financial Fundamentals for Global Automobile Industry. Transportation Research Procedia, 63, 2409–2420. https://doi.org/10.1016/j.trpro.2022.06.277

Tan, E., & Astuti, I. (2020). Metode Autoregressive Integrated Moving Average untuk Meramalkan Penjualan. EKOMABIS: Jurnal Ekonomi Manajemen Bisnis, 1(02), 149–158. https://doi.org/10.37366/ekomabis.v1i02.43

Tian, K., Jiang, Y., Yuan, Z., Peng, B., & Wang, L. (2024). Visual Autoregressive Modeling: Scalable Image Generation via Next-Scale Prediction. 1–19. http://arxiv.org/abs/2404.02905

Vankadara, L. C., Faller, P. M., Hardt, M., Minorics, L., Ghoshdastidar, D., & Janzing, D. (2022). Causal Forecasting: Generalization Bounds for Autoregressive Models. Proceedings of Machine Learning Research, 180, 2002–2012.

Vulandari, R. T., & Parwitasari, T. A. (2018). Perbandingan Model AR(1), ARMA (1,1), dan ARIMA (1,1,1) pada Prediksi Tinggi Muka Air Sungai Bengawan Solo pada Pos Pemantauan Jurug. MUST: Journal of Mathematics Education, Science and Technology, 3(1), 46. https://doi.org/10.30651/must.v3i1.1620

Wahyu S, S., Nurchim, N., & Susanto, R. (2022). Penerapan Data Mining Dengan Algoritma Apriori pada Penjualan di New Java Steak. DutaCom, 15(2), 99–104. https://doi.org/10.47701/dutacom.v15i2.2011

Wulandary, S. (2020). Vector Autoregressive Integrated (VARI) Method for Forecasting the Number of Internasional Visitor in Batam and Jakarta. Jurnal Matematika, Statistika Dan Komputasi, 17(1), 94–108. https://doi.org/10.20956/jmsk.v17i1.10536

Downloads

Published

2024-07-09

Issue

Vol. 11 No. 2 (2024): Jurnal Derivat (Agustus 2024)

Section

Articles

Citation Check

License

Copyright (c) 2024 Muhammad Rais Ramadhani, Nurmalitasari, Nurchim

Creative Commons License

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Authors who publish with this journal agree to the following terms:

  1. Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution-ShareAlike 4.0 International License that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this journal.
  2. Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this journal.
  3. Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).