Klasifikasi Tingkat Dehidrasi Berdasarkan Kondisi Urine, Denyut Jantung dan Laju Pernapasan
DOI:
https://doi.org/10.25126/jtiik.2021824379Abstrak
Dehidrasi merupakan suatu kondisi ketika tubuh kekurangan cairan. Secara umum terdapat tiga tingkatan dehidrasi, yaitu dehidrasi ringan, sedang dan berat. Tingkatan dehidrasi berat sangat berbahaya bagi penderitanya, bahkan dapat mengakibatkan kematian. Untuk mencegah terjadinya tingkatan dehidrasi yang berbahaya, maka diperlukan pendeteksian secara dini agar penderita dehidrasi segera mendapatkan penanganan yang cepat dan tepat. Terdapat beberapa parameter yang dapat digunakan untuk mendeteksi dehidrasi, diantaranya warna dan kadar ammonia pada urine, denyut jantung dan laju pernapasan. Pada penelitian ini, dirancang sebuah sistem klasifikasi tingkatan dehidrasi berdasarkan empat parameter tersebut dengan menggunakan metode klasifikasi k-nearest neighbor. Sistem yang dirancang mampu memberikan kemudahan untuk melakukan pemeriksaan secara mandiri dan mendapatkan hasil klasifikasi tingkat dehidrasi secara real-time. Dataset yang digunakan dalam penelitian ini berjumlah 75 data yang didapatkan dari pasien diare yang menjalani perawatan di Rumah Sakit. Data tersebut sudah memiliki tingkatan dehidrasi berdasarkan diagnosis dari dokter. Dari hasil pengujian yang telah dilakukan, metode k-nearest neighbor memiliki tingkat akurasi terbaik pada penggunaan nilai k=5 dan k=7 dengan nilai akurasi sebesar 96%.
Abstract
Dehydration is a condition when the body lacks of fluids, caused by the amount of fluid released by the body is greater than the fluids that enters the body. Dehydration is divided into three levels, mild, moderate and severe. Severe dehydration is very dangerous and can even lead to death in patients. To prevent dangerous levels of dehydration, early detection is needed to provide fast and precise treatment to patients. There are several parameters that can be used to detect dehydration, such as color and ammonia levels in urine, heart rate and respiratory rate. This paper designed a system to classify dehydration levels based on these four parameters using k-nearest neighbor classification method. The system is designed to be easy to use independently and provides real-time classification results. There are 75 datasets used in this paper, obtained from diarrhea patients in a hospital in Malang. Each data already has a label in the form of dehydration level based on the doctor’s diagnosis. From the test result, k-nearest neighbor has the best classification accuracy at k=5 and k=7 with the accuracy of 96%.
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