Applied Exponential Smoothing Holt-Winter Method for Predict Rainfall in Mataram City

Dewi Darma Pertiwi(1*)

(1) Department of Statistics, Universitas Muhammadiyah Semarang, Semarang
(*) Corresponding Author


Weather conditions in the city of Mataram tend to be erratic and difficult to predict, such as the condition of rainfall data in 2018 which changes over a certain period of time so that the weather is difficult to predict accurately. In this study, we propose the Exponential Smoothing Holt-Winter method to forecast rainfall in the city of Mataram, so that it can be a decision support for various interested sectors. This method has been tested using secondary data from the Mataram City Central Bureau of Statistics for the period January 2014 to 2018 and evaluated using Mean Absolute Deviation (MAD), Mean Squared Error (MSE) and Mean Absolute Percentage Error (MAPE). The results of this study indicate that using the Exponential Smoothing Holt-Winter method yields better results, each of which is MAPE 142.3, MAD 95.6 and MSD value 24988.7 and the data smoothing value is obtained for the smallest combination value of α 0.2, β 0.1, and γ 0.1. It can be concluded that the proposed method can provide better information and can be used to predict rainfall in Mataram City for the next 12 periods.


Exponential Smoothing; Holt-Winter; Mataram; Rainfall

Full Text:



Chen, Zhenhua, and Yuxuan Wang. 2019. “Impacts of Severe Weather Events on High-Speed Rail and Aviation Delays.” Transportation Research Part D: Transport and Environment 69 (April): 168–83.

Dhamodharavadhani, S., and R. Rathipriya. 2019. “Region-Wise Rainfall Prediction Using MapReduce-Based Exponential Smoothing Techniques.” In Advances in Intelligent Systems and Computing, 229–39.

Dunstan, Piers K., Bradley R. Moore, Johann D. Bell, Neil J. Holbrook, Eric C.J. Oliver, James Risbey, Scott D. Foster, Quentin Hanich, Alistair J. Hobday, and Nathan J. Bennett. 2018. “How Can Climate Predictions Improve Sustainability of Coastal Fisheries in Pacific Small-Island Developing States?” Marine Policy 88 (February): 295–302.

Golding, Nicola, Chris Hewitt, Peiqun Zhang, Min Liu, Jun Zhang, and Philip Bett. 2019. “Co-Development of a Seasonal Rainfall Forecast Service: Supporting Flood Risk Management for the Yangtze River Basin.” Climate Risk Management 23: 43–49.

Hartomo, Kristoko Dwi, Subanar, and Edi Winarko. 2015. “Winters Exponential Smoothing and Z-Score, Algorithms for Prediction of Rainfall.” Journal of Theoretical and Applied Information Technology 73 (1).

Hyndman, Rob J., Anne B. Koehler, J. Keith Ord, and Ralph Snyder. 2010. “Forecasting with Exponential Smoothing: The State Space Approach.” International Journal of Forecasting 26 (1): 204–5.

Metcalfe, Andrew V., and Paul S.P. Cowpertwait. 2009. Introductory Time Series with R. Introductory Time Series with R. New York, NY: Springer New York.

Noviandi, and Ahmad Ilham. 2020. “Optimization Fuzzy Inference System Based Particle Swarm Optimization for Onset Prediction of the Rainy Season.” Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control 5 (1): 61–70.

Pascawati, Nur Alvira, Tri Baskoro Tunggul Satoto, Tri Wibawa, Roger Frutos, and Sylvie Maguin. 2019. “Dampak Potensial Perubahan Iklim Terhadap Dinamika Penularan Penyakit DBD Di Kota Mataram.” BALABA: JURNAL LITBANG PENGENDALIAN PENYAKIT BERSUMBER BINATANG BANJARNEGARA 15 (49–60).

Wichitarapongsakun, Patana, Charoon Sarin, Pantip Klomjek, and Sombat Chuenchooklin. 2016. “Rainfall Prediction and Meteorological Drought Analysis in the Sakae Krang River Basin of Thailand.” Agriculture and Natural Resources 50 (6): 490–98.

Zhu, Mengxun, Hans J. De Boeck, Hang Xu, Zuosinan Chen, Jiang Lv, and Zhiqiang Zhang. 2020. “Seasonal Variations in the Response of Soil Respiration to Rainfall Events in a Riparian Poplar Plantation.” Science of The Total Environment 747 (December): 141222.

Article Metrics

Abstract view : 116 times
PDF - 11 times



  • There are currently no refbacks.

Editorial Office of Journal of Intelligent Computing and Health Informatics (JICHI)

Department of Informatics
Faculty of Engineering Building 1nd Floor, Universitas Muhammadiyah Semarang
Jl. Kasipah No. 12, Jastingaleh, Kec. Candisari, Kota Semarang, Prov. Jawa Tengah, Indonesia 50254 |
Facebook: (in progress)
Twitter: (in progress)

(024) 8445768
+6288215427973 (Whatsapp/SMS)
Web Analytics Made Easy - StatCounter
View My Stats

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