Classification of Crude Palm Oil Quality Eligibility Using Support Vector Machine Algorithm

In this research, a quality classification of Crude Palm Oil (CPO) produced by PT. PP London Sumatra Indonesia Tbk. In this research, the parameters for CPO quality are the levels of VM (Water), DIRT (Dirt), FFA (Free Fatty Acid). Use of the Support Vector Machine (SVM) algorithm to classify the suitability of Crude Palm Oil quality using machine learning methods as CPO quality parameter data for training. Using the SVM algorithm as a classification method has the advantage of handling complex and high-dimensional data, so it can be a new contribution in analyzing the feasibility of CPO quality. The aim of this research is to apply the Support Vector Machine algorithm in classifying CPO quality and apply the use of the Support Vector Machine algorithm with Google Colab Python Notebooks in determining the quality of palm oil (CPO). The research method used in this research is a descriptive method with qualitative analysis, data obtained through data collection is then interpreted in accordance with the research objectives that have been formulated and obtained through interviews. Based on the results of testing the CPO quality classification application using the Support Vector Machine algorithm with Google Colab Python Notebooks tools, it can be concluded that the application can carry out CPO quality classification with a dataset of 3 measurement results in 2020, 2021 and 2022 totaling 1,095 records. The test results carried out a training dataset of 70% or 730 training data and 365 testing data with an accuracy value of 84.15%.