Utilizing Machine Learning to Determine User Interface Elements in Agricultural Mobile Location-Based Services

Abstract The evolution of mobile location-based technology revolutionizes user experiences, providing personalized services and seamless navigation. This transformation influences how individuals interact with information and surroundings, enhancing daily life’s connectivity and convenience. However, creating interactive mobile location-based user interfaces (UI) for diverse users, especially in lower-middle-income countries, poses a significant challenge. Overcoming barriers to technology adoption within this diverse user group necessitates strategic planning to prevent exacerbating the digital divide. It is imperative to comprehend farmers’ preferences and requirements, especially in the context of user interface design. This study aims to determine preferred UI elements using machine learning based on respondents’ demographic characteristics. This investigation examines the user interface preferences of chili farmers in reporting pest and disease incidents through the implementation of a machine learning algorithm. Data was acquired through surveys and field experiments involving specified user interface elements for reporting chili crop issues in Batu Pahat and Johor Bahru. The findings of this study were analyzed using the Random Forest (RF) and Support Vector Machine (SVM) algorithms, and it shows that the image icon and radio button were the respondents’ preferences in stating the name of the disease. Based on the overall accuracy and kappa values, Random Forest is the more effective model for making predictions in this study. The findings support the transition of Malaysian farmers towards becoming intelligent farmers when designing the UI based on the demographic characteristics of farmers, aligning with the objectives of the Shared Prosperity Vision 2030 and endorsing the National Agrofood Policy 2021-2030 (NAP2.0). Additionally, this initiative aligns with the Food and Agriculture Organization of the United Nations (FAO) efforts to digitize farmers, including smallholders.