RAINFALL FORECASTING USING THE HOLT-WINTERS EXPONENTIAL SMOOTHING METHOD

Authors

  • I Komang Arya Ganda Wiguna Fakultas Teknologi Dan Informatika , Institut Bisnis Dan Teknologi Indonesia
  • Ni Luh Putu Ayu Cintia Utami Fakultas Teknologi Dan Informatika , Institut Bisnis Dan Teknologi Indonesia
  • Wayan Gede Suka Parwita Fakultas Teknologi Dan Informatika , Institut Bisnis Dan Teknologi Indonesia
  • I Putu Agus Eka Darma Udayana Fakultas Teknologi Dan Informatika , Institut Bisnis Dan Teknologi Indonesia
  • I Gede Iwan Sudipa Fakultas Teknologi Dan Informatika , Institut Bisnis Dan Teknologi Indonesia

Keywords:

Rainfall Forecasting, Holt-Winters Exponential Smoothing Method, MAPE Testing

Abstract

Abiansemal District is dominated by agricultural land, with Subak Blahkiuh being one of the agricultural lands in the district. Agriculture is extremely weather-dependent, particularly during the monsoon season. Therefore, precipitation forecasting is necessary for determining a favorable sowing season. Researchers use the Holt-Winters Exponential Smoothing method with data from 2012 to 2022 for forecasting. Holt-Winters Exponential Smoothing employs two forecasting models. The results of the calculations indicate that the additive model has alpha equal to 0.653467, beta equal to 0.0036348, and gamma equal to 0.1182400. While the multiplicative model has alpha values of 0.8889286, 0.0001 and 0.0246825 for beta and gamma, respectively. For accurate forecasting, it is necessary to examine the error data, specifically the MAE and MAPE. The multiplicative model yielded an MAE of 158.87 and a MAPE of 55.18%, whereas the additive model yielded an MAE of 186.59 and a MAPE of 70.18%. The MAPE values of the additive model and multiplicative model are greater than 50 percent, indicating that the additive and multiplicative models provide inaccurate forecasts. Between the additive model and the multiplicative model, the Holt-Winters Exponential Smoothing method favors the multiplicative model for future precipitation forecasting.

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References

A. B. Wijaya, C. Dewi, and B. Rahayudi, “Peramalan Curah Hujan Menggunakan Metode High Order Fuzzy Time Series Multi Factors,” J. Pengemb. Teknol. Inf. dan Ilmu Komput., vol. 2, no. 3, pp. 930–939, 2018.

M. F. Amrulloh and D. Agustina, “Rancang Bangun Sensor Kelembaban Tanah Untuk Sistem Irigasi Tanaman Kaktus Berbasis Android,” J. Krisnadana, vol. 2, no. 2, pp. 354–361, 2023.

M. L. Radhitya and G. I. Sudipa, “PENDEKATAN Z-SCORE DAN FUZZY DALAM PENGUJIAN AKURASI PERAMALAN CURAH HUJAN,” SINTECH (Science Inf. Technol. J., vol. 3, no. 2, pp. 149–156, 2020.

E. Q. Ajr and F. Dwirani, “Menentukan Stasiun Hujan Dan Curah Hujan Dengan Metode Polygon Thiessen Daerah Kabupaten Lebak,” Agustus, vol. 2, no. 2, pp. 139–146, 2019.

I. G. I. Sudipa, R. Riana, I. N. T. A. Putra, C. P. Yanti, and M. D. W. Aristana, “Trend Forecasting of the Top 3 Indonesian Bank Stocks Using the ARIMA Method,” Sink. J. dan Penelit. Tek. Inform., vol. 8, no. 3, pp. 1883–1893, 2023.

I. M. D. P. Asana, I. K. A. G. Wiguna, K. J. Atmaja, and I. P. A. Sanjaya, “FP-Growth Implementation in Frequent Itemset Mining for Consumer Shopping Pattern Analysis Application,” J. Mantik, vol. 4, no. 3, pp. 2063–2070, 2020.

W. G. S. Parwita and N. K. N. P. Dewi, “METODE AUTOREGRESSIVE INTEGRATE MOVING AVERAGE DALAM PERAMALAN INDEKS HARGA KONSUMEN KOTA DENPASAR,” Smart EDU Bul. Educ., vol. 1, no. 4, pp. 158–170, 2022.

A. R. Anam, “Edudikara : Jurnal Pendidikan dan Pembelajaran Analisis Pemetaan Agroklimat dengan Menggunakan Metode Klasifikasi Iklim Oldeman di Daerah Kabupaten Tegal,” vol. 7, no. September, pp. 154–165, 2022.

D. A. Wibisono, D. Anggraeni, and A. F. Hadi, “Perbaikan Model Seasonal Arima Dengan Metode Ensemble Kalman Filter Pada Hasil Prediksi Curah Hujan,” Maj. Ilm. Mat. dan Stat., vol. 19, no. 1, p. 9, 2019, doi: 10.19184/mims.v19i1.17262.

I. L. Nindian Puspa Dewi, “Implementasi Holt-Winters Exponential Smoothing untuk Peramalan Harga Bahan Pangan di Kabupaten Pamekasan,” Digit. Zo. J. Teknol. Inf. dan Komun., vol. 11, no. 2, pp. 223–236, 2020, doi: 10.31849/digitalzone.v11i2.4797.

A. Aryati, I. Purnamasari, and Y. N. Nasution, “Peramalan dengan Menggunakan Metode Holt-Winters Exponential Smoothing (Studi Kasus: Jumlah Wisatawan Mancanegara yang Berkunjung Ke Indonesia) Forecasting using the method of Holt-Winters Exponential Smoothing (Case Study: Number of Foreign Tourists Visi,” J. EKSPONENSIAL, vol. 11, no. 1, pp. 99–106, 2020.

E. F. Putra, Y. Asdi, and M. Maiyastri, “PERAMALAN DENGAN METODE PEMULUSAN EKSPONENSIAL HOLT-WINTER DAN SARIMA (Studi Kasus: Jumlah Produksi Ikan (Ton) di Kota Sibolga Tahun 2000-2017),” J. Mat. UNAND, vol. 8, no. 1, p. 75, 2019, doi: 10.25077/jmu.8.1.75-83.2019.

W. Xu et al., “Prediction of congenital heart disease for newborns: comparative analysis of Holt-Winters exponential smoothing and autoregressive integrated moving average models,” BMC Med. Res. Methodol., vol. 22, no. 1, p. 257, 2022.

W. Jiang, X. Wu, Y. Gong, W. Yu, and X. Zhong, “Holt–Winters smoothing enhanced by fruit fly optimization algorithm to forecast monthly electricity consumption,” Energy, vol. 193, p. 116779, 2020.

Y. J. Siregar, R. Hartono, A. E. Hardana, P. S. Agribisnis, U. Brawijaya, and E. Smoothing, “Peramalan harga cabai rawit di kota malang dengan metode holt-winters exponential smoothing,” vol. 6, pp. 99–110, 2021.

N. P. R. Apriyanti, I. K. G. D. Putra, and I. M. S. Putra, “Peramalan Jumlah Kecelakaan Lalu Lintas Menggunakan Metode Support Vector Regression,” J. Ilm. Merpati (Menara Penelit. Akad. Teknol. Informasi), vol. 8, no. 2, p. 72, 2020, doi: 10.24843/jim.2020.v08.i02.p01.

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Published

2023-03-29

How to Cite

Wiguna, I. K. A. G., Utami, N. L. P. A. C., Parwita, W. G. S., Udayana, I. P. A. E. D., & Sudipa, I. G. I. (2023). RAINFALL FORECASTING USING THE HOLT-WINTERS EXPONENTIAL SMOOTHING METHOD. Jurnal Info Sains : Informatika Dan Sains, 13(01), 15–23. Retrieved from https://ejournal.seaninstitute.or.id/index.php/InfoSains/article/view/2656