PREDIKSI PERTUMBUHAN PRODUK DOMESTIK REGIONAL BRUTO (PDRB) MENGGUNAKAN ADAFTIVE NEURO FUZZY INFERENCE SYSTEM (ANFIS) (Studi Kasus : PDRB Provinsi Bali) - , Made Agung Raharja ([Yogyakarta] : Universitas Gadjah Mada, 2012)
Gross Domestic Regional Product (GDRP) is the total value of final goods and services produced by all business units on a regional/area within a certain time period. Adaptive Neuro-fuzzy inference system (ANFIS) is the merger mechanism described fuzzy inference system in neural network architectures. In this study conducted by the ANFIS prediction of GDRP growth that has the main goal is to make the design and construction of a model that can predict the growth of the Gross Domestic Regional Product (GDRP) in the Province of Bali on a regular basis. GDRP growth is the importance of values as one tool that is used as a measuring tool that can describe the success rate of development in an area. GRDP growth prediction using ANFIS method with 5 (five) in the form of the input parameters of the regional economic indicators closely linked to GRDP growth. Five indicators are: government consumption, investment, exports, inflation and tourist visits and the number of data pairs used were as many as 34 annual periods from 1976 to 2010 period. System data used are vague inference Takagi Sugeno Kang (TSK) Order One, and learning methods used are hybrid method combining the Least Squares Estimator (LSE) used in advanced stages and algorithms Error Backpropagation (EBP) is used in reverse phase. The results generate GDRP growth forecast for the smallest training error 1.35E-07 with the type of membership function Triangle (Triangular). Validation test used the F test and obtained F calculated is smaller than the F table. So there is proximity between the results of ANFIS model predictions with actual data (model is valid). The simulation results predicted GDRP growth for the period 2011 GDRP growth value of 5.7614%.