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All Journal Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer
Reyvaldo Aditya Pradana
Fakultas Ilmu Komputer, Universitas Brawijaya
Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering

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Klasifikasi Mutu Susu Sapi menggunakan Metode Modified K-Nearest Neighbor (MKNN) Reyvaldo Aditya Pradana; Imam Cholissodin; Nurul Hidayat
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 6 No 3 (2022): Mei 2022
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Milk is a very complex food ingredient, because milk has many ingredients needed by the human body. It is necessary to control the quality of cow's milk in order to produce high quality dairy products. With the development of food technology for cow's milk products, UPT Laboratory of Animal Health Malang by creating an application system that can classify the quality of cow's milk. This cow's milk quality application system uses input in the form of chemical composition where this composition is taken with the Julie C2 Milkscope tool. The chemical composition of milk consists of fat, lean dry matter, viscosity, lactose and protein. There are various methods used. This study uses the Modified K-Nearest Neighbor method and the dataset used is 269 cow's milk quality data with 5 parameters and 2 yield classes. Based on several studies, the Modified K-Nearest Neighbor method can be used in the classification process and obtain a fairly high level of accuracy. Based on the test results, the average test accuracy value of K value is 91.1%, then the average value of the accuracy of testing the effect of the amount of training data is 88.4%, and the average value of balanced and unbalanced class testing accuracy is 86.12%. It can be concluded that the Modified K-Nearest Neighbor method can be implemented and tested into the cow's milk quality classification system.
Co-Authors Imam Cholissodin Nurul Hidayat