Smart Plant: A Mobile Application for Plant Disease Detection

Abstract

Indonesia is one of the big producers of agricultural products in the world. Agriculture sector plays an important role in the national economic development structure. However, the proportion of young farmers (ages 20 to 30 years old) is only 8% of the farmer population (BPS, 2019). Majority proportion comes from old people with age interval from 50 to 60 years old. (Taufik Leoni, 2020). Based on our case study in Purwokerto, the problem that is often found by old age farmers is the reduced ability to see and recognize plant diseases. Furthermore, they also face the difficulty to follow the development of agricultural science so that some of their knowledge is outdated. That encourages us to make a mobile application to identify plant disease and connect them with scientists. Since the majority of farmers in Purwokerto plant tomatoes, we limit this research for tomato disease only. After studying some related previous research, we found most of them used a deep structure of Convolutional Neural Network (CNN) to reach a high accuracy. However, since our aim is to make daily use technology for old people, a high complexity model does not fit for this case. Therefore, we proposed our own CNN model with less complexity but got 89% accuracy. For future works, we plan to develop it for the other plants and hope it will help all farmers to do quality control, especially for the old age farmers.