Implementasi Metode Weighted Moving Average (WMA) Pada Prediksi Harga Bahan Pokok

Authors

  • Fina Ustadatin Program Studi Teknik Informatika, Universitas PGRI Ronggolawe
  • Asfan Muqtadir Program Studi Teknik Informatika, Universitas PGRI Ronggolawe
  • Amaludin Arifia Program Studi Teknik Informatika, Universitas PGRI Ronggolawe

DOI:

https://doi.org/10.34010/komputika.v12i2.10304

Abstract

Staples are goods or commodities that are needed routinely in everyday life. Staples have an important role in meeting food needs. Availability, price, and accessibility of basic commodities can affect people's welfare. Prices of basic commodities tend to experience price volatility. This makes people uneasy and will affect the level of purchase of each staple. The purpose of this research is to predict the price of staple goods in the Tuban district market, East Java. The method used in this study is the Weighted Moving Average (WMA), to predict the price of materials using data on prices of staple foods that existed previously. This method is used in order to obtain accurate forecasting results. The Weighted Moving Average method is suitable for predicting the price of basic commodities, because it is able to provide predictions using existing data, namely previous data and can future prices. The results of this study are that the highest MAPE value is 0.3 for the staple ingredient premium rice, and the lowest MAPE value is 5.3 for the staple ingredient red chili.

Keywords – Basic commodities; Forecasting; Weighted Moving Average.

References

M. Rizaldi Satyaputra, F. Richard Kodong, O. Samuel Simanjuntak, and J. Teknik Informatika, “Seminar Nasional Informatika 2018 (semnasIF 2018) UPN ‘Veteran’ Yogyakarta,” 2018.

M. Arsyad, dan Maryam Saud, P. Studi Agroteknologi, F. Pertanian, and U. Pohuwato, “Evaluasi Tingkat Kualitas Dan Mutu Beras Hasil Penggilingan Padi di Kecamatan Duhiadaa Kabupaten Pohuwato Quality And Rice Quality Level Evaluation Of Rice Milling In Duhiadaa District, Pohuwato District,” 2020.

L. Hasanah, “Analisis Faktor-Faktor Pengaruh Terjadinya Impor Beras di Indonesia Setelah Swasembada Pangan,” Growth: Jurnal Ilmiah Ekonomi Pembangunan, vol. 1, no. 2, p. p, 2022.

A. Faktor-Faktor et al., “Agriecobis (Journal of Agricultural Socioeconomics and Business) Artikel Penelitian,” vol. 3, no. 2, pp. 79–86, 2020, doi: 10.22219/agriecobis.

Y. Harry Bahar et al., “Pengaruh Trimming Dan Pengempaan Terhadap Kualitas Dan Simpan Cabai Rwait Merah (Capsicum frutescens L.) Dalam Bentuk Cabai Kering Dan Cabai Bubuk Effect of Trimming and Pressing Treatments on Cayenne Pepper (Capsicum frutescens L) Quality and Shelf Life of Dried Chilli and Chilli Powder,” 2022.

B. E. W. Asrul, S. Zuhriyah, and S. H. Makassar, “Sistem Informasi Peramalan Harga Pangan Dengan Menggunakan Metode Naïve Bayes Di Kota Makassar,” 2018.

S. N. Rahmadhani, L. Logiandani, R. Z. Ramadhan, R. N. Sofia Amriza, and M. Y. Fathoni, “Analisis Forecasting Penjualan Gula Merah di Jatilawang Menggunakan Metode Weighted Moving Average,” Jurnal Sisfokom (Sistem Informasi dan Komputer), vol. 11, no. 3, pp. 381–386, Dec. 2022, doi: 10.32736/sisfokom.v11i3.1433.

S. Fatmaria Tantri, N. Eltivia, and N. I. Riwajanti, “The Forecasting Analysis of Profit on Astra Companies List on Indonesia Stock Exchange (IDX),” Journal of Applied Business, Taxation and Economics Research, vol. 2, no. 3, pp. 247–257, Feb. 2023, doi: 10.54408/jabter.v2i3.156.

N. Khoerudin, S. P. Ramadhani, M. Hasian, V. Sinaga, and D. M. Kusumawardani, “Analisis Rantai Pasok Penjualan Sepatu Sekolah Masa Pandemi Covid-19 dengan Metode Weighted Moving Average,” Jurnal Riset Komputer), vol. 10, no. 1, pp. 2407–389, 2023, doi: 10.30865/jurikom.v10i1.5456.

S. M. Robial, “Perbandingan Model Statistik Pada Analisis Metode Peramalan Time Series (Studi Kasus: PT. Telekomunikasi Indonesia, Tbk Kandatel Sukabumi),” Jurnal Ilmiah SANTIKA, vol. 8, no. 2, 2018.

I. Solikin and S. Hardini, “Aplikasi Forecasting Stok Barang Menggunakan Metode Weighted Moving Average (WMA) pada Metrojaya Komputer,” Jurnal Informatika: Jurnal Pengembangan IT, vol. 4, no. 2, pp. 100–105, May 2019, doi: 10.30591/jpit.v4i2.1373.

J. Mayani Syahputri Hasibuan, R. Tama Andri Agus, P. Studi Sistem Informasi, and S. Royal Kisaran, “Forecasting Of Yamaha Motorcycle Sales Using The Weighted Moving Average (WMA) Web-Based,” Jurnal Teknik Informatika (JUTIF), vol. 3, no. 2, 2022, doi: 10.20884/1.jutif.2022.3.2.216.

D. Julika Sari, H. Saputra, A. Nasution, S. Informasi, and S. Tinggi Manajemen Informatika dan Komputer Royal Kisaran, “The Use Of The Method Predicts The Inventory Of Tofu Raw Materials Case Study Industry Tahu Iyus,” Jurnal Teknik Informatika (JUTIF), vol. 3, no. 2, pp. 429–436, 2022, doi: 10.20884/1.jutif.2022.3.2.224.

A. Kumila, B. Sholihah, E. Evizia, N. Safitri, and S. Fitri, “Perbandingan Metode Moving Average dan Metode Naïve Dalam Peramalan Data Kemiskinan,” JTAM | Jurnal Teori dan Aplikasi Matematika, vol. 3, no. 1, p. 65, Apr. 2019, doi: 10.31764/jtam.v3i1.764.

I. Setiawan, “Rancang Bangun Aolikasi Peramalan Persediaan Stok Barang Menggunakan Metode Weigted Moving Average (WMA) Pada Toko Barang xyz,” 2021.

S. Ramayani, M. Iqbal, P. Studi Sistem Informasi, and S. Tinggi Manajemen Informatika dan Komputer Royal Kisaran, “Forecasting Of Fertilizer Inventory in UD. Menara Tani With Weighted Moving Average (WMA) And double Exponential Smoothing (DES) Method,” vol. 3, no. 3, pp. 487–494, 2022, doi: 10.20884/1.jutif.2022.3.3.171.

Downloads

Published

2023-09-21

How to Cite

[1]
“Implementasi Metode Weighted Moving Average (WMA) Pada Prediksi Harga Bahan Pokok”, Komputika, vol. 12, no. 2, pp. 83–90, Sep. 2023, doi: 10.34010/komputika.v12i2.10304.