Clay Tile, Support Vector Machine, Image Processing
Abstract
Quality control is a system that can assist a company in maintaining and maintaining product quality so that product defects do not occur. PT. XYZ is a company in the clay tile industry. Every month, PT. XYZ has products due to defects with an average of 2225 precarious. One of the problems that occurred at PT. XYZ is an inspection process that only uses sight. The use of sight can carry the risk of increased operating costs due to faulty examinations, failure to get business, and rework. With the development of technology, it can overcome this problem by finding artificial detectors using measurement methods, image preprocessing, and algorithms to detect defect. In this study using the Support Vector Machine (SVM) method in classifying defects. Taking pictures directly in this study using raspberry pi and making the algorithm system using pyhton software. This study uses a linear kernel in the SVM algorithm. The results in this study concluded that the highest accuracy rate was 88.6% using a linear kernel.
