The current global food challenge necessitates the need to increase agricultural production. Farmers' innovative mindset is unavoidable for successful and sustainable agriculture. Precision agriculture, through novel technology like big data, is an effective solution that can exponentially increase agricultural productivity and quality. Innovativeness among food growers is a significant determinant for adopting new technologies. For this reason, the Exploratory Factor Analysis (EFA) technique was used in this research to construct a reliable and valid instrument that measures innovativeness. Data was collected from small-scale farmers in Terengganu, Malaysia. The questionnaire was developed on a scale of one to ten. With the help of IBM SPSS Statistics version 25.0, the EFA was carried out using the principal component extraction method with Varimax Rotation. The study assessed Bartlett's Test of Sphericity and Kaiser-Meyer-Olkin (KMO) to determine the adequacy of the sample. Bartlett's test revealed a significant result (0.000), and the KMO value was excellent (0.726). The findings of the EFA revealed two components and eight items with Cronbach's Alpha values of more than 0.7, all of which were found to be significant. As a result, the results demonstrated the instrument's accuracy and dependability. This research contributes to developing items that assess innovativeness in the context of small farming in Malaysia.