Prediction of the Sea Level from the PUMMA System Using SARIMA

  • Irfan Asfy Fakhry Anto National Research and Innovation Agency
  • Oka Mahendra National Research and Innovation Agency
  • Purnomo Husnul Khotimah National Research and Innovation Agency
  • Semeidi Husrin National Research and Innovation Agency
Keywords: Sea Level, Prediction, PUMMA, Sea Level Prediction, Seasonal Moving Average


The rising sea levels can threaten millions of people residing along the coast or lowlands. The risk can be mitigated by the sea-level prediction done by collecting information on the likelihood of rising sea levels. The Ministry of Marine Affairs and Fisheries of Indonesia has developed Perangkat Ukur Murah untuk Muka Air Laut (Inexpensive Device for Sea Level Measurement, PUMMA) to measure sea levels. PUMMA is located in remote monitoring stations based on Indonesian maritime area. The PUMMA system currently lacks a prediction feature. This objective of this study is to model the sea-level prediction using the dataset for one year, from July 2021 until July 2022. The seasonal autoregressive integrated moving average (SARIMA) method was used because SARIMA proved to be a flexible and versatile method for a dataset having noncomplex nature and seasonal patterns. This study has developed several models of the SARIMA. The model performance was evaluated using the mean absolute percentage error (MAPE), R-squared, mean square error (MSE), and root mean square error (RMSE) metrics. The SARIMA(1, 1, 0)(1, 1, 1)12 model achieved the lowest prediction error with an R-squared of 0.508, MSE of 0.0479, and RMSE of 0.069. Based on the performance, SARIMA(1, 1, 0)(1, 1, 1)12 model is feasible for predicting sea levels using the PUMMA dataset.


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How to Cite
Irfan Asfy Fakhry Anto, Oka Mahendra, Purnomo Husnul Khotimah, & Semeidi Husrin. (2023). Prediction of the Sea Level from the PUMMA System Using SARIMA . Jurnal Nasional Teknik Elektro Dan Teknologi Informasi, 12(3), 205-211.