Analisis Pengaruh Karakteristik Tanah Dasar terhadap Kerusakan Perkerasan Jalan, Studi Kasus Ruas Jalan Salusu-Lanang Kec. Lampasio, Kab. Tolitoli - Moh. Nasril; Ilmuddin Ilmuddin; Sudirman Latjemma; Ferdiansyah Ferdiansyah (LPPM Institut Pendidikan Nusantara Global, 2026)
Road pavement deterioration remains a significant issue on many road sections, including the Salusu–Lanang Road in Lampasio District, Tolitoli Regency. One of the factors suspected of contributing to pavement deterioration is the subgrade soil characteristics, including moisture content, plasticity index, and California Bearing Ratio (CBR). This study aimed to identify the characteristics of the subgrade soil, analyze the types of pavement distress, and examine the influence of subgrade soil characteristics on pavement deterioration. A quantitative research method with correlational and causal approaches was employed. Data were collected through field surveys and laboratory testing of soil samples obtained from three locations: STA 1+080, STA 1+560, and STA 2+669. The tested parameters included moisture content, Atterberg limits, specific gravity, Proctor compaction, and CBR values. Data were analyzed using SPSS through normality tests, Pearson correlation analysis, and multiple linear regression. The results indicate that the subgrade soil is classified as highly plastic clay (CH) according to the Unified Soil Classification System (USCS) and as A-7-6 according to the AASHTO classification system. The moisture content ranged from 36.05% to 40.43%, the plasticity index ranged from 22.29% to 24.37%, and the CBR values ranged from 3.50% to 4.00%, indicating poor bearing capacity. Statistical analysis revealed that the CBR value was the most dominant factor influencing pavement deterioration compared with moisture content and plasticity index. These findings provide valuable information for pavement design, evaluation, and maintenance based on subgrade soil characteristics. Future studies are recommended to incorporate additional variables, such as traffic volume, drainage conditions, and pavement layer thickness, to develop a more comprehensive analytical model.