PENERAPAN ALGORITMA K-MEANS CLUSTERING PADA APLIKASI MENENTUKAN BERAT BADAN IDEAL - Yusuf Ramadhan Nasution; Muhammad Eka (Algoritma: Jurnal Ilmu Komputer dan Informatika, 2018)
One application of computer technology in the medical world is to determine the ideal body weight (BMI) of a patient by comparing the body weight, height, and size of the patient's own skeleton, so doctors can determine the diet menu that is most suitable for such patients. This becomes very important, especially in the field of medicine, such as the field of beauty, athletes, or other fields that require ideal body shapes such as models, artists and so forth. This ideal body weighting system is done by the ratio of height to body weight, and the size of the patient's frame. While the K-Means Clustering algorithm is an algorithm that can classify data based on benchmark values given and calculate the data group. This system can be used to determine ideal body weight by applying BMI values as X coefficients and the patient frame size values as the Y coefficients and cluster central points are set first. However, this system still needs further development because there is no change facility to clustering data category, grouping process is shown in the form of animation, and the need of clustering category in store in one structured database. Keywords: Ideal Weight, K-Means Clustering Algorithm