PENERAPAN METODE K-MEANS UNTUK CLUSTERING HASIL PRODUKSI BERDASARKAN BERAT PRODUK - Putro, Herman Purwoko; Saputra, Memed; Najmuddin, Najmuddin (DESANTA (Indonesian of Interdisciplinary Journal), 2023)
In the industrial world, especially in manufacturing companies that convert raw materials into finished goods. Quality is the main thing that absolutely must be fulfilled in all products. There are several factors or parameters that can be used as a basic benchmark in determining the suitability of a product. As a manufacturing company engaged in the motor vehicle tire manufacturing industry, of course there are many parameters used to determine product suitability. One of them is the weight of the product. This research aims to group products based on their weight, namely Normal, Overweight and Underweight. The data grouping process is carried out using Data Mining rules by utilizing Clustering techniques. The Data Mining process is carried out using Knowledge Discovery in Database  steps. The method used to obtain process results is by using the K-Means algorithm. Data processed using Microsoft Excel and implemented using Rapid Miner V7.4 software. The data used in this research was obtained from the Curing department with a data sample of 4758 records. The results of this research are to find out the percentage value of each product weight condition, how many products meet the product eligibility requirements and vice versa. From this, it is hoped that a conclusion can be drawn about how the production process is generally performed.