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: | https://repositori.ukdc.ac.id/id/eprint/2417 |
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