Analisis Faktor Utama Penentu Harga Rumah di Surakarta Menggunakan Principal Component Analysis

Abstract

Residence is often referred to as one of the primary needs. Therefore, it is important to formulate a well-planned series of actions to ensure that every family has a dwelling of their own. In this planning process, an analysis of the factors determining house prices is necessary to serve as a basis for finding suitabel housing. The objective of this research is to conduct a Principal Component Analysis (PCA) on the main factors determining house prices using the dataset from Surakarta. The identified factors that contribute to house prices include the number of bedrooms, the number of bathrooms, the size of the house, the distance from the house to the city center, and the distance from the house to the nearest hospital. The analysis is performed using the PCA library in Python, resulting in two main factors with a variance above 90%. The first component represents accessibility factors, specifically the distance from the house to the city center and the distance from the house to the nearest hospital. On the other hand, the second component represents spatial and accommodation factors, including the number of bedrooms, the number of bathrooms, and the size of the house.