PREDICTION OF ROAD SECTION LENGTH WITH LIGHT DAMAGE AND ANALYSIS OF INFLUENCING FACTORS: A CASE STUDY IN JAWA TENGAH USING LINEAR REGRESSION - Sulistyowati; Puji Lestari, Dyah Aryati; Mahardika, Vera (JUTSU : Jurnal Teknik Sipil Unpand, 2025)
Road maintenance planning can be optimized by identifying the road’s performance in the next period. Bina Marga Jawa Tengah, who is responsible for roads and bridges performance in the province of Jawa Tengah releases data containing every road section’s condition status along with the length of each section, Annual Average Daily Traffic volume with the volume of each type of vehicle that passed on every road section. The data also contains every section type of pavement along with the length of each type of pavement on every road section. Using this secondary data, this research aimed to predict the length of 83 road sections that fell into the category of Light Damage from 2019 to 2024, the predictions are for 2025 and 2026. The projections are 53.04 KM and 47.88 KM for 2025 and 2026, respectively. The investigation of the most influencing factor in the ‘Light Damage’ road category could not perform very well as we lack the schedule and type of maintenance data. The lack of such data yielded a very low R2 (mostly less than 0.3) as the lack of such data made the existing data irrelevant.