Mendeteksi penyakit jantung menggunakan machine learning dengan algoritma logistic regression

Kenichi, Kenichi and Tanjaya, Henry (2020) Mendeteksi penyakit jantung menggunakan machine learning dengan algoritma logistic regression. Bachelor thesis, Universitas Pelita Harapan.

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Abstract

Penyakit Jantung atau disebut juga penyakit kardiovaskular merupakan salah salah satu penyakit berbahaya yang dapat menyebabkan kematian. Seiring berkembangnya teknologi dan peningkatan popularitas teknologi machine learning, teknologi machine learning tersebut dapat digunakan untuk membantu mendeteksi penyakit jantung dengan menggunakan data pasien. Terdapat berbagai jenis metode yang dapat digunakan untuk mendiagnosa apakah seseorang terkena penyakit jantung atau tidak. Penelitian ini mengimplementasikan penggunaan algoritma yaitu logistic regression, dimana algoritma tersebut memakai fungsi logistik untuk menghasilkan binary atau nol dan satu sebagai penentuan klasifikasi. Setelah eksperimen dilakukan dengan algoritma logistik regresi memberikan hasil yang memiliki keunggulan yang berbeda beda terhadap metode lainnya berdasarkan model analisa confusius matrix. / Heart Disease or also called cardiovascular disease is one of the dangerous diseases that can cause death. As technology develops and the popularity of machine learning technology increases, machine learning technology can be used to help detect heart disease using patient data. There are various methods that can be used to diagnose whether a person has heart disease. This research implements the use of an algorithm called logistic regression, where the algorithm uses logistic functions to produce binary or zero and one as a classification determination. After the experiment is carried out with a logistic regression algorithm the results have different advantages over other methods based on the confucius matrix analysis model.

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