MODEL PERAMALAN PENJUALAN MENGGUNAKAN PENDEKATAN WEIGHTED MOVING AVERAGE PADA UMKM KOPI

Authors

  • Cantika Putri Lylla Universitas Tiga Serangkai, Indonesia
  • Retno Tri Vulandari Universitas Tiga Serangkai, Indonesia
  • Andriani Kusumaningrum Universitas Tiga Serangkai, Indonesia

DOI:

https://doi.org/10.30646/tikomsin.v14i1.1077

Keywords:

Sales Forecasting, Weighted Moving Average, Coffee Sales, Forecasting Model

Abstract

Sales forecasting plays a critical role in supporting effective inventory management, particularly for small and medium enterprises (SMEs) in the coffee sector, where demand exhibits fluctuating patterns over time. Inaccurate demand estimation may lead to stock shortages, resulting in lost sales opportunities, or overstocking, which increases holding costs and product waste. Therefore, a reliable and accurate forecasting model is required to support optimal inventory planning and operational efficiency. This study aims to develop and implement a sales forecasting model using the Weighted Moving Average (WMA) method and to evaluate its predictive accuracy. The WMA method, as a time series approach, assigns different weights to historical data, emphasizing more recent observations to better capture short-term trends. Historical coffee sales data were utilized as the basis for model development. Forecast accuracy was evaluated using the Mean Absolute Percentage Error (MAPE). The results indicate that the WMA model provides a high level of accuracy, with a forecast value of approximately 22,914 units for the subsequent period and a MAPE value of 0.29% using weight parameters of 0.7, 0.2, and 0.1. This level of accuracy is categorized as very high, demonstrating that the proposed model is effective and reliable for supporting inventory decision-making and improving operational performance in SMEs.

References

A. Giawa, S. Kakisina, A. Telaumbanua, dan H. Gulo, “Analisis peramalan penjualan produk telur untuk menentukan persediaan pada CV. Monalisa Mitra Makmur Kota Gunungsitoli,†Jurnal Publikasi Manajemen Informatika, vol. 5, no. 2, 2026, doi: 10.55606/jupumi.v5i2.6638.

Y. S. Sura, A. P. Sasmito, dan J. D. Irawan, “Peramalan kebutuhan stok produk puzzle berdasarkan data penjualan di PT. XYZ menggunakan metode double moving average,†Jurnal SKANIKA, vol. 8, no. 1, Jan. 2025, doi: 10.36080/skanika.v8i1.3317

N. Fazirah, E. E. Wisnuna, M. Muslihah, A. Zakaria, dan A. B. Susetyo, “Pemodelan dan peramalan harga kopi robusta menggunakan autoregressive integrated moving average (ARIMA) dengan EViews,†Jurnal Inovasi Ekonomi Syariah dan Akuntansi, vol. 3, no. 1, Jan. 2026, doi: 10.61132/jiesa.v3i1.1968.

S. Rifadli dan R. Sari, “Implementasi metode weighted moving average (WMA) pada prediksi penjualan gas elpiji berbasis website,†Jurnal Desain dan Analisis Teknologi, vol. 3, no. 2, Jul. 2024, doi: 10.58520/jddat.v3i2.47.

D. L. Suryani, K. F. M., dan Munif, “Penerapan algoritma weighted moving average untuk peramalan penjualan LPG bersubsidi di Pangkalan Ranba Lamongan,†Jurnal Pendidikan dan Teknologi Indonesia (JPTI), vol. 5, no. 8, pp. 2416–2432, Aug. 2025, doi: 10.52436/1.jpti.972.

F. Dzulfikar, S. Widyastuti, dan M. Erwanto, “Metode weighted moving average untuk peramalan penjualan toko material Fans Jaya,†Journal of Computation Science and Artificial Intelligence (JCSAI), vol. 2, no. 2, 2025, doi: 10.58468/d7perw74.

A. Apriliani, H. Zainuddin, A. Agussalim, dan Z. Hasanuddin, “Peramalan tren penjualan menu restoran menggunakan metode single moving average,†Jurnal Teknologi Informasi dan Ilmu Komputer, vol. 7, no. 6, Dec. 2020, doi: 10.25126/jtiik.2020722732.

D. Junianto, P. Suseno, dan Y. R. Mahariani, “Perbandingan metode peramalan berdasarkan tingkat akurasi untuk memprediksi produksi bawang merah di Kabupaten Nganjuk,†JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika), vol. 10, no. 2, pp. 1734–1742, Jun. 2025, doi: 10.29100/jipi.v10i2.7738.

S. Sylvia, “Implementasi dan Analisa Metode Peramalan Exponential Smoothing dan Weighted Moving Average untuk Permintaan Produk,†Journal of Industrial Engineering and Management Research, vol. 3, no. 4, pp. 45–53, 2022, doi: 10.7777/jiemar.v3i4.401.

W. Hariadi and Sulantari, “Forecasting Tingkat Inflasi Year-on-Year Indonesia dengan Metode Weighted Moving Average,†Unisda Journal of Mathematics and Computer Science, vol. 8, no. 2, pp. 120–128, 2022, doi: 10.52166/ujmc.v8i2.3576.

I. G. B. Aprilyanta, A. Lestari, and S. Christina, “Perbandingan Implementasi Metode Weighted Moving Average dan Single Exponential Smoothing pada Persediaan Obat,†Jurnal Saintekom: Sains, Teknologi, Komputer, dan Manajemen, vol. 12, no. 2, pp. 88–95, September 2022, doi: 10.33020/saintekom.v12i2.317.

M. H. Riandi, N. T. Wiyani, and D. Arigawati, “Prediksi Penjualan melalui Metode Weighted Moving Average (WMA) pada UMKM Nasi Bakar,†Jurnal Riset Entrepreneurship, vol. 7, no. 2, pp. 85–92, Agustus 2024, doi: 10.30587/jre.v7i2.8459.

D. Andrean and L. Hakim, “Aplikasi Forecasting Menggunakan Metode Least Square dan Weighted Moving Average untuk Penjualan Minyak Goreng,†Jurnal Algoritma, Logika dan Komputasi, vol. 5, no. 2, pp. 101–108, 2023, doi: 10.30813/j-alu.v5i2.3555.

M. A. Karim, U. Yudatama, dan A. Primadewi, “Peramalan stok penjualan Sahabi frozen food dengan weighted moving average,†Journal of Computer System and Informatics (JoSYC), vol. 5, no. 4, August. 2024, doi: 10.47065/josyc.v5i4.5824.

V. Indriani dan W. Hadikurniawati, “Implementasi metode weighted moving average (WMA) untuk prediksi stok daging dalam sistem berbasis web,†Jurnal Informatika Sains dan Teknologi, vol. 10, no. 1, Apr. 2025, doi: 10.24252/instek.v10i1.53695.

Downloads

Published

2026-04-27

Issue

Vol. 14 No. 1 (2026): Jurnal Tikomsin, Vol 14, No.1, April 2026

Section

Articles

Citation Check

License

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

  • Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
  • 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 acknowledgement of its initial publication in this journal.
  • 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).

 

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