Forecasting Indonesia’s Wholesale Price Index (WPI) Using the Holt's Exponential Smoothing Method

Isma Muthahharah; Sitti Masyitah Meliyana; Zakiyah Mar’ah

doi:10.35877/454RI.qems3937

Isma Muthahharah Universitas Negeri Makassar (ID)
Sitti Masyitah Meliyana Universitas Negeri Makassar (ID)
Zakiyah Mar’ah Universitas Negeri Makassar (ID)

https://doi.org/10.35877/454RI.qems3937

Keywords: Holt’s Exponential Smoothing, Forecasting, Wholesale Price Index, MAPE.

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Abstract

The Index of Wholesale Price (WPI) is a key benchmark in analyzing price movements at the wholesale level as it can affect the economic stability of a country. This research purpose to forecast the movement of WPI in Indonesia using Holt's Exponential Smoothing technique, which is effective in analyzing time series data that show trend patterns. This research utilizes secondary data obtained from the BPS for the period 2020-2024. The analysis is carried out by determining the optimal value of α and β parameters using trial and error techniques. Furthermore, the forecasting process is carried out using the best parameters that have been obtained. Based on the analysis results, the combination of parameters α = 0.9 and β = 0.8 provides a Mean Absolute Percentage Error (MAPE) value of 0.22%, which indicates a very good level of forecasting accuracy. WPI forecasting for the year 2025 shows a consistent upward pattern, reflecting a consistent increase in WPI previous historical trends. The results of this study can be a reference in making price and wholesale trade policies by the government and related parties in the economic sector.

References

Amalia, I. R., Widiharih, T., & Tarno. (2024). Holt Winters Exponential Smoothing Untuk Meramalkan Produk Domestik Bruto Di Indonesia. Jurnal Gaussian, 13(1), 219–229. https://doi.org/10.14710/j.gauss.13.1.219-229
Andini, P. D. A., Wahyuningsih, S., & Siringoringo, M. (2024). Aplikasi Metode Double Exponential Smoothing Holt Dengan Optimasi Golden Section Untuk Peramalan Nilai Ekspor Provinsi Kalimantan Timur. Jurnal Eksponensial, 15(1), 20–28. https://doi.org/10.30872/eksponensial.v15i1.1278
Aziza, J. N. (2022). Perbandingan Metode Moving Average, Single Exponential Smoothing, dan Double Exponential Smoothing Pada Peramalan Permintaan Tabung Gas LPG PT Petrogas Prima Services. Jurnal Teknologi dan Manajemen Industri Terapan, 1(I), 35–41. https://doi.org/10.55826/tmit.v1ii.8
Farafisha, S. N. (2022). Perbandingan Peramalan Double Exponential Smoothing Holt dan Double Exponential Smoothing Dengan Parameter Damped. Universitas Islam Indonesia.
Khoiri, H. A. (2023). Analisis Deret Waktu Univariat (C. P. Hendrastati (ed.)). UNIPMA Press. https://kwu.unipma.ac.id/buku/1823/analisis-deret-waktu-univariat-teori-dan-pengolahan-data
Manullang, S., & Mansyur, A. (2023). Peramalan Penjualan Beras Di Perum Bulog Sub Divre Medan Menggunakan Metode Double Exponential Smoothing. Jurnal Riset Rumpun Matematika Dan Ilmu Pengetahuan Alam (JURMIPA), 2(1), 26–36. https://doi.org/10.55606/jurrimipa.v2i1.618
Melani, V. D., Miftahuddin, & Subianto, M. (2022). Seleksi Model ARFIMA-GPH Dan Intervensi Multi Input Pada Indeks Harga Perdagangan Besar Indonesia. Jurnal Gaussian, 11(2), 163–172.
Nabillah, I., & Ranggadara, I. (2020). Mean Absolute Percentage Error untuk Evaluasi Hasil Prediksi Komoditas Laut. Journal of Information System, 5(2), 250–255. https://doi.org/10.33633/joins.v5i2.3900
Razi, Z., Mirunnisa, Maryanti, & Nurhayati. (2024). Peramalan Nilai Tukar Petani Provinsi Aceh : Ditinjau Dengan Metode Double Exponential Smoothing Dan Holt Winter. Lebesgue: Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistika, 5(2), 974–982. https://doi.org/10.46306/lb. v5i2
Suksemawan, I. M. P. E., Sumarjaya, I. W., & Srinadi, I. G. A. M. (2024). Peramalan Indeks Harga Perdagangan Besar Kelompok Komoditas Pertanian Menggunakan Metode Singular Spectrum Analysis. E-Jurnal Matematika, 13(2), 115–120. https://doi.org/10.24843/MTK.2024.v13.i02.p450
Vimala, J., & Nugroho, A. (2022). Forecasting Penjualan Obat Menggunakan Metode Single, Double, dan Triple Exponential Smoothing (Studi Kasus: Apotek Mandiri Medika). Jurnal Penerapan Teknologi Informasi dan Komunikasi, 1(2), 90–99.
Wahyu, F., & Hendrik, B. (2023). Perbandingan Algoritma Time Series Dan Fuzzy Inference System Dalam Analisis Data Deret Waktu. Jurnal Penelitian Teknologi Informasi Dan Sains (JPTIS), 1(3), 16–24. https://doi.org/10.54066/jptis.v1i3.711
Wardalisah. (2024). Peramalan Harga Saham Menggunakan Metode Light Gradient Boosting Machine dengan Optuna Hyperparameter Optimization (Studi Kasus: Saham PT. Vale Indonesia Tbk.). Universitas Hasanuddin.
Winanti, G. L., Ispriyanti, D., & Sugito. (2023). Pemodelan Indeks Harga Perdagangan Besar (WPI) Sektor Ekspor Menggunakan ARFIMA-GARCH. Jurnal Gaussian, 12(1), 52–60. https://doi.org/10.14710/j.gauss.12.1.52-60
Yulianti, N. A., Cahyawati, D., & Susanti, E. (2023). Penggunaan Metode Double Exponential Smoothing Tipe Holt pada Peramalan Kasus Covid-19 di Provinsi Sumatera Selatan. Jurnal Statistika, 23(1), 19–28.