Comparison of Spatial Socioeconomic and Health Clustering Population in Chiang Mai Province

• Main Authors: Wasana Phiwkhom, Phisanu Chiawkhun, Ekkarat Boonchieng, Waraporn Boonchieng, Nawapon Nakharutai
• Format: Conference Proceeding
• Published: 2020
• Subjects: Computer Science; Decision Sciences; Engineering; Physics and Astronomy
• Online Access: https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85091821341&origin=inward; http://cmuir.cmu.ac.th/jspui/handle/6653943832/70429
• Institution: Chiang Mai University

© 2020 IEEE. In this research, we compared Spatial Socioeconomic and Health Clustering Population in Chiang Mai Province. The data used in this study is socioeconomic data, health problems from the Center of Excellence in Community Health Information, Chiang Mai University. The sample size used in this study is 50,460 people living in Chiang Mai. A random Sampling Method was used to select sample from semi-city, suburbs and rural group. The variables are age, income, latitude, and longitude and health problems from patient medical records. Adaptive Density-Based Spatial Clustering of Applications with Noise (A-DBSCAN) and Improvement of formulas parameters calculation Density-Based Spatial Clustering of Applications with Noise (I-DBSCAN) were used to analyze the data. We compared the efficiency and the relationship between areas and health of the population in Chiang Mai Province. The results showed that the A-DBSCAN method is better than the I-DBSCAN method. The majority of the population in Chiang Mai is suffering from chronic diseases, and income levels are correlated with illness at the level of significance 0.05 (p-value < 0.05).