Penerapan Principal Component Analysis (PCA) terhadap Data Indikator Kesehatan di Sumatera Utara Tahun 2020

Abstract

Health Indicators are variables used to determine a condition of changes in the health sector. There are many indicators that describe health characteristics, thus making the authors conduct this research with the aim of reducing these indicators to become more dominant in North Sumatra in 2020. The types of indicators taken consist of 15 variables based on 33 districts/cities in North Sumatra, reducing the indicators was carried out using the principal component analysis (PCA) method. Based on the results of the study, the factor analysis stage consisted of testing variables using the KMO Bartlett's Test of Sphericity method as well as measuring MSA (Measure of Sampling Adequacy), factoring processes, and rotation processes. After testing the variables, the KMO and MSA values were obtained > 0.5, which means that the variable is feasible for further testing. After that, factor analysis was carried out, there were 4 factors formed with the value of each factor (7.314), (1.747), (1.379), (1.102). From the results of the final test, there were 14 variables left that could be grouped into 4 new factors, namely Population Health Services, Health Conditions and Services, Health Facilities and Health Conditions, and Community Behavior for Healthy Living.