PROYEKSI STOKASTIK PRODUKSI KEDELAI DI INDONESIA

Authors

  • Yurlia Pitasari
  • Agus Hudoyo
  • Achdiansyah Soelaiman

DOI:

https://doi.org/10.23960/jiia.v6i3.3018
Abstract View: 539

Abstract

Soybean is one of vegetable protein sources. It is so important that the government targets self-sufficiency on this commodity.  Its target is 3.00 million tons in 2019, i.e. more than three times of the production in 2015. A production target is better stochastically forecasted that its result is an interval at a certain probability level.  There were some studies that forecasted productions of soybean.  However, their results were not as the intervals. Therefore, the objective of this research is for stochastically forecasting the soybean production.  Its data are time series data obtained from the FAO and the Indonesian Statistics Central Bureau. Data were analyzed by using econometrics.  The result of forecasting is the soybean production will be 0.99 million tons in 2019 with the 95% confidence interval between 0.94 and 1.05 million tons.

Key words: Soybean, production, forecast

Downloads

Download data is not yet available.

Downloads

Published

2019-03-20

How to Cite

Pitasari, Y., Hudoyo, A., & Soelaiman, A. (2019). PROYEKSI STOKASTIK PRODUKSI KEDELAI DI INDONESIA. Jurnal Ilmu Ilmu Agribisnis: Journal of Agribusiness Science, 6(3), 229–235. https://doi.org/10.23960/jiia.v6i3.3018

Issue

Vol. 6 No. 3 (2018)

Section

Articles

License

Authors who publish with this journal agree to the following terms:

Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.

Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.

Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).