METODE SSA PADA DATA PRODUKSI PERIKANAN TANGKAP DI PROVINSI JAWA BARAT

  • Fadhilah Fitri Program Studi Magister Statistika Terapan, Universitas Padjadjaran
  • Nurul Fiskia Gamayanti Program Studi Magister Statistika Terapan, Universitas Padjadjaran
  • Gumgum Gunawan Program Studi Magister Statistika Terapan, Universitas Padjadjaran

Abstract

Indonesia is an archipelagic country where 2/3 of its territory isĀ  ocean. The vastness of Indonesia's oceans is expected to produce abundant sea products that can meet the needs of Indonesian consumers, especially fish. Adequacy of the amount of fish consumption can be assessed through the number of fish catch. Based on data at the Ministry of Marine Affairs and Fisheries in 2015, West Java has a low growth of fish consumption, 6.05% in 2010-2014. Therefore, it is necessary to forecast the results of fish catch for several years ahead so it can be known whether the provision of fish consumption will be fulfilled or not. One method that can be used is Singular Spectrum Analysis (SSA). The SSA method is a flexible method because it uses a nonparametric approach. That is, in its application, this method does not require the model specification of time series data, as well as parametric assumptions. Forecasting accuracy of a method is said to be good if it has a MAPE value less than 20%. MAPE of SSA method forecast is 6.19% so that SSA method is suitable for forecasting of capture fishery production in West Java Province. The forecast for fishery production in West Java Province in 2015 for the first, second, third, and fourth quarter were 53,978.49 Ton, 54,406.91 Ton, 50,889.11 Ton, and 56,896.96 Ton, respectively.

Published
2017-12-29
How to Cite
FITRI, Fadhilah; GAMAYANTI, Nurul Fiskia; GUNAWAN, Gumgum. METODE SSA PADA DATA PRODUKSI PERIKANAN TANGKAP DI PROVINSI JAWA BARAT. Jurnal Ilmiah Matematika dan Pendidikan Matematika, [S.l.], v. 9, n. 2, p. 95-110, dec. 2017. ISSN 2550-0422. Available at: <http://jos.unsoed.ac.id/index.php/jmp/article/view/2870>. Date accessed: 08 feb. 2023. doi: https://doi.org/10.20884/1.jmp.2017.9.2.2870.

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