Priambodo, B; Rahayu, S; Hazidar, AH; Naf'An, E; Masril, M; Handriani, I; Pratama Putra, Z; ... Jumaryadi, Y; + view all Priambodo, B; Rahayu, S; Hazidar, AH; Naf'An, E; Masril, M; Handriani, I; Pratama Putra, Z; Kudr Nseaf, A; Setiawan, D; Jumaryadi, Y; - view fewer (2019) Predicting GDP of Indonesia Using K-Nearest Neighbour Regression. In: Journal of Physics: Conference Series. (pp. pp. 1-7). IOP Science

Preview

Text Priambodo_2019_J._Phys.__Conf._Ser._1339_012040.pdf - Published Version Download (557kB) | Preview

Abstract

The impact of the global recession in 1998 that originated from the recession in the US will affect the projected economies in Asia, including Indonesia, both direct and indirect nature. In this study, we predicted Indonesia's GDP in the event of the economic crisis that hit Indonesia starting in 1998. Instead of using the famous prediction algorithm as a neural network and linear regression. K-Nearest Neighbour is selected because it is easy and fast to use in the small dataset. We use a dataset from 1980-2002, consisting of rice prices, premium prices, GDP of Japanese country, American GDP, currency exchange rates, Indonesian government consumption, and the value of Indonesia's oil exports. For evaluation, we compare k-NN regression prediction result with prediction result using back propagation neural network and multiple linear regression algorithm. Result show, k-NN regression is able to predict Indonesia's GDP using small dataset better than the neural network, and multiple linear regression method.

Download activity - last month

Export as CSVJSONXML

Download activity - last 12 months

Export as JSONXMLCSV

Downloads by country - last 12 months

Export as CSVJSONXML

Archive Staff Only

View Item