KLASTERISASI HASIL PANEN SARANG WALET MENGGUNAKAN METODE K-MEANS CLUSTERING
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Institusion
Institut Teknologi Perusahaan Listrik Negara
Author
PUTRA, WINGGAR WAHARI
Indrianto, Indrianto
Djamain, Yasni
Indrianto, Indrianto
Djamain, Yasni
Subject
Teknik Informatika
Datestamp
2022-09-20 03:53:48
Abstract :
Clustering of the quality level of swallow's nests will be used to assist swallow breeders in producing swallow nests that are maximum in terms of quality. With this system, breeders can determine the quality of swiftlet nests more efficiently and without the help of a consultant. In this study, the author applies a method that is suitable for this case, namely the K-Means Clustering Method. The data used is an RGB (Red Green Blue) image in the image. In this system, the quality of swallow's nests is divided into 3 (three) parts, namely class 1 for the best quality swallow's nest with a color image that tends to be white, class 2 for a good quality/enough swallow's nest with a color image that tends to be yellow, and class 3 for swallow's nest of poor quality with a color image close to brown. And based on the results of testing the level of accuracy and precision produced by the system using 20 samples, it shows that the results for testing using the Confusion Matrix get test results of 76.9% for accuracy and 77.4% for precision.
Clustering of the quality level of swallow's nests will be used to assist swallow breeders in producing swallow nests that are maximum in terms of quality. With this system, breeders can determine the quality of swiftlet nests more efficiently and without the help of a consultant. In this study, the author applies a method that is suitable for this case, namely the K-Means Clustering Method. The data used is an RGB (Red Green Blue) image in the image. In this system, the quality of swallow's nests is divided into 3 (three) parts, namely class 1 for the best quality swallow's nest with a color image that tends to be white, class 2 for a good quality/enough swallow's nest with a color image that tends to be yellow, and class 3 for swallow's nest of poor quality with a color image close to brown. And based on the results of testing the level of accuracy and precision produced by the system using 20 samples, it shows that the results for testing using the Confusion Matrix get test results of 76.9% for accuracy and 77.4% for precision.
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