Pendekatan Principal Component Analysis untuk Peningkatan Efektivitas Pemeliharaan Jalan Kabupaten - Pratama, Bagus Gilang; SARI, SELY NOVITA; Yuliani, Oni (Institut Teknologi Nasional Yogyakarta, 2024)
Road maintenance is a crucial aspect of maintaining the quality and sustainability of transportation infrastructure, especially at the district level, as well-maintained roads support the smooth distribution and economic mobility. However, with the increasing number of road sections and limited budget, determining maintenance priorities becomes a challenge. This study aims to analyze the application of Principal Component Analysis (PCA) in improving the efficiency and accuracy of road maintenance priority determination at the district level. Using data from 141 road sections, variables such as road conditions, traffic volume, pavement width, and heavy vehicle count were analyzed using the PCA method. In conclusion, PCA is effective in simplifying the decision-making process regarding road maintenance by focusing on significant variables, thereby increasing the efficiency of resource management and the accuracy of maintenance priority determination. The data normalized using Min-Max Scaler was reduced to 9 principal variables that explained more than 90% of the variance from the original data.