Comparison of algorithm Support Vector Machine and C4.5 for identification of pests and diseases in chili plants

Abstract

Data from the Central Bureau of Statistics of the population working in the agricultural sector continued to decline from 39.22 million in 2013 to 38.97 million in 2014, the number dropped back to 37.75 million in 2015. According to the MIT G-Lab Team (global entrepreneurship program) concludes five factors that make it difficult to raise agricultural productivity to compete in the domestic market, namely the low education of farmers in dealing with pests, the difficulty of access to finance for rural areas, lack of skills, lack of access to information and lack of application of agricultural technology. Chili plants are plants that are very susceptible to pests so BPS noted a decrease in chili production reaching 25%. Information about chili pests is collected so that it becomes a database that can be used to identify disease pests using the data mining method. The use of data mining algorithms is expected to help in the identification of pests and diseases in chili plants. In this study comparing the performance classification techniques of Support Vector Machine (SVM) and C4.5 algorithms. The attributes used consist of Leaves, Stems, and Fruits. By using each training data and testing data as many as 30 data. The results of the study were conducted, based on the accuracy of SVM, which was 82.33% and C4.5 89.29 %%. The final result of this study was that the accuracy of the C4.5 method was better.

Performance Analysis of the Hybrid Voting Method on the Classification of the Number of Cases of Dengue Fever

“…In another similar study, DHF in Indonesia was predicted using the Decision Tree with an accuracy of 76% [5]. Another study used a comparison of the Support Vector Machine and C4.5 algorithms for the identification of pests and diseases in chili plants, with an accuracy of 82.33% and 89.25%, respectively [6]. Another study using k-Nearest Neighbor for heart disease obtained an accuracy of 81,31% [7].…”

Factores Determinantes para Aumentar la Productividad y Disminuir los Costos de los Agricultores Limeños

“…El sector agropecuario en el Perú es uno de los sectores primarios cuyas actividades productivas generan gran impacto sobre el Producto Bruto Interno del país, además de generar 1 de cada 4 empleos a nivel nacional, cifra que se ha mantenido a lo largo de la última década, siendo que en 2007 pasó de emplear al 28.3% de la Población Económicamente Activa y en 2018 el 23.5% de la misma [1] (Intituto Peruano de la Economía, 2019). Dados los puntos presentados destacamos la importancia del sector agropecuario y su influencia en la economía peruana.…”

Analysis of sales levels of pharmaceutical products by using data mining algorithm C45

“…In managing product availability, several inventory management techniques can be used, one of which is data mining with the c45 algorithm, k means and others [18]. The c45 method can be used for various prediction processes and is compared with the Support Vector Machine algorithm for identification of pests and diseases in plants [19]. The c45 algorithm can also be used to diagnose covid 19 surveillance classifications which include PDP, ODP, and OTG [20].…”