Fuzzy-Klassen Model for Development Disparities Analysis based on Gross Regional Domestic Product Sector of a Region

TL;DR

This paper introduces a fuzzy-Klassen model utilizing fuzzy logic and Klassen typology to analyze regional development disparities based on GRDP sectors, providing a more nuanced assessment than traditional methods.

Contribution

The study develops a novel fuzzy-Klassen model combining fuzzy logic and Klassen typology for improved regional development imbalance analysis.

Findings

Fuzzy-Klassen model reveals sector inequalities in Cilegon City.

Model shows significant differences from traditional Klassen analysis.

Fuzzy approach identifies sectors with exponential growth.

Abstract

Analysis of regional development imbalances quadrant has a very important meaning in order to see the extent of achievement of the development of certain areas as well as the difference. Factors that could be used as a tool to measure the inequality of development is to look at the average growth and development contribution of each sector of Gross Regional Domestic Product (GRDP) based on the analyzed region and the reference region. This study discusses the development of a model to determine the regional development imbalances using fuzzy approach system, and the rules of typology Klassen. The model is then called fuzzy-Klassen. Implications Product Mamdani fuzzy system is used in the model as an inference engine to generate output after defuzzyfication process. Application of MATLAB is used as a tool of analysis in this study. The test a result of Kota Cilegon is shows that there are significant differences between traditional Klassen typology analyses with the results of the model developed. Fuzzy model-Klassen shows GRDP sector inequality Cilegon City is dominated by Quadrant I (K4), where status is the sector forward and grows exponentially. While the traditional Klassen typology, half of GRDP sector is dominated by Quadrant IV (K4) with a sector that is lagging relative status.