Forecasting Sea Cucumber Catches Using the ARIMA Method

Jehanus, Maria Oktaviani and Wulandari, Lusi Mei Cahya and Bellanov, Agrienta (2025) Forecasting Sea Cucumber Catches Using the ARIMA Method. Social Science and Humanities Journal (SSHJ), 9 (1). pp. 6440-6450. ISSN 2456-2653

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Abstract

Sea cucumbers are marine resources that have a significant ecological role and important economic value. UD. Matahari Jalan Sukolilo Baru II, Bulak District, Surabaya is an MSME that processes sea cucumber catches and sells them to various distributors, including trading abroad. The catch of sea cucumbers obtained by fishermen in uncertain quantities, every subsequent period. Therefore, the results of sea cucumber fishing are known to be influenced by several factors, one of which is climatic factors such as temperature, humidity and tides. The research was conducted to predict the uncertain catch of sea cucumbers with the ARIMA method to obtain effective modeling and equations. Forecasting can help determine the right period by using one of the methods that correspond to the sequence of time. The ARIMA method is an approach used in time series analysis to model and forecast data arranged in a specific order. Predict the catch of sea cucumbers by looking at the smallest error, and the catch of sea cucumbers after forecasting in the next period. The result of the selection of the best ARIMA model from the humidity variable is (1,1,1) more significant and effective for sea cucumber fishing in the short term (1.2 days) in the rainy season, with the smallest error of 271.11. The forecast results in April 2024 for the 107 period are 268.42 kg, the forecast data is close to the actual data in the previous period. Keywords: Forecasting; ARIMA; Sea Cucumber.

Item Type:	Article
Uncontrolled Keywords:	Forecasting, ARIMA, Sea Cucumber
Subjects:	H Social Sciences > HD Industries. Land use. Labor > HD28 Management. Industrial Management L Education > L Education (General)
Divisions:	Fakultas Teknik > Prodi Teknik Industri
Depositing User:	Agrienta Bellanov
Date Deposited:	03 Sep 2025 06:36
Last Modified:	03 Sep 2025 06:37
URI:	http://repositori.ukdc.ac.id/id/eprint/2417

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