Classification Of Country Status In 2022 Based On Social Indicators With Ordinal Logistic Regression

This research examines the classification of country status in 2022 by applying ordinal logistic regression on various social indicators including education, health and economic. The urgency of the research is to know the country determine factors with specific factors in the form of research variables that can be useful for policy makers, unlike the existing classification which is only divided based on GDP per capita or HDI score only. By dividing 3 country status classes, namely not developed, developing and developed countries using the world bank classification baseline, the accuracy results were obtained at 72,5% but there were several variables that were not significant. After re-modelling, the accuracy was found increased to 76.4% with the odds ratio results for the minimum wage variable being 42,32 in the high class compared to the middle class and 11,66 for the middle class compared to the lower class, which means that the higher the minimum wage tends to be classify countries as developed countries. Another variable that has significance level is the birth rate with an odds ratio of 0,71 in the high and middle classes and 0.89 in the middle and lower classes comparison, which shows that this variable has a negative effect because the odds ratio is <1, which means that the higher the birth rate tends to make the country will be classified as a non-developed country

Reduksi Faktor-Faktor yang Mempengaruhi Kualitas Air Hujan dengan Metode Analisis Komponen Utama

The increase in air pollution that occurs due to industrial and economic activities will affect the rainwater content. The vital function of one of the sources of clean, namely rainwater, makes the urgency of research on indications of a decrease in rainwater quality by analyzing the substances contained. The parameters used for the determination of rainwater quality are the degree of acidity, conductivity, calcium, magnesium, sodium, potassium, ammonium, sulfate ions, nitrate ions, chloride ions, total hardness, and acidity. The data source used is data from the Central Statistics Agency (BPS) entitled "Indonesian Environmental Statistics 2022". By using the main component analysis method to reduce the variables of rainwater quality influence factors in 35 city/station samples in Indonesia, results were obtained, namely rainwater quality influence factors that can be formed into three main components with each containing 10 variables consisting of acidity, conductivity, magnesium, sodium, potassium, chloride ions, sulfate ions, nitrate ions, total hardness, and acidity capable of explaining 73.695% of the total variance