This study aims to evaluate the soil fertility index using the Nutrient Index (NI) and Principal Component Analysis (PCA) across different land uses in Mojogedang Subdistrict, Karanganyar Regency, Indonesia. Soil samples were collected using purposive sampling from 14 land map units (LMUs) and analysed in the laboratory for selected soil chemical properties. The laboratory data were processed using the Nutrient Index and Soil Fertility Index methods, with the Minimum Data Set (MDS) derived from correlation analysis and Principal Component Analysis (PCA), followed by scoring to determine the scoring index (Si). According to land-use type, the classification of soil fertility index using two methods yielded different classes in both land uses. The Nutrient Index method showed that the mixed garden had higher soil fertility than the moorland, whereas the values are medium (1.75) and low (1.62), respectively. Meanwhile, the PCA method classified both mixed garden and moorland as medium, with values of 0.54 and 0.51, respectively. However, the soil fertility index for each land map unit differed across land uses. A T-test showed significant differences (p = 0.000) between the two methods. The determining factors in the Nutrient Index method are total N and available P, with land use as the main source of variation (p = 0.002), while in the PCA method are soil pH, organic carbon, available P, cation exchange capacity (CEC) with soil type (p = 0.001) and land use (p = 0.003) as the main sources of variation. The study concludes that the PCA method provides a more comprehensive representation of soil fertility conditions by using a broader set of soil indicators. In contrast, the Nutrient Index method is simpler and easier to apply as it utilizes fewer soil parameters. Understanding the different types of land uses and soil characteristics is crucial for enhancing soil fertility and ensuring sustainable agricultural practices.