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A Heuristic Network for Predicting the Percentage of Gross Domestic Product Distribution

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SAIN2018_gaffar2018_A heuristic network for predicting.pdf (493.0Kb)
Date
2019-03-25
Author
Gaffar, Emmilya Umma Aziza
Gani, Irwan
Haviluddin, Haviluddin
Gaffar, Achmad Fanany Onnlita
Alfred, Rayner
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Abstract
In a country, economic growth indicators are measured by GDP growth rates. In order to predict GDP growth then, economic situation and economic development strategy have always been used. In this study, GDP contribution at the current price by the industrial sector has been predicted by using heuristic network method. There were nine GDP growth variables including (1) Agriculture, Livestock, Forestry, Fishery, (2) Mining & Quarrying, (3) Manufacturing Industry, (4) Electricity, Gas, Water supply, (5) Construction, (6) Trade, Hotel, Restaurant, (7) Transport& Communication, (8) Finance, Real Estate & Business Services, and (9) Services in the period 2001-2016 have been analyzed. Experimental results show that the error rate forecasting in 2017 is less than 10%. The results show that intelligent computing method (heuristic network) can be an alternative method for predicting the contribution of GDP. This method predicts fairly quickly, significantly and produces an acceptable error prediction.
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http://repository.unmul.ac.id/handle/123456789/3903
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Repository Universitas Mulawarman copyright ©   LP3M Universitas Mulawarman
Jalan Kuaro Kotak Pos 1068
Telp. (0541) 741118
Fax. (0541) 747479 - 732870
Samarinda 75119, Kalimantan Timur, Indonesia
Contact Us | Send Feedback