Classification of Heart Disease Diagnosis using the Random Forest Algorithm

Akbar Hidayatullah Harahap (Teknik Informatika, UIN Sunan Gunung Djati Bandung)
Ihsan Muttaqin Bin Abdul Malik (Teknik Informatika, UIN Sunan Gunung Djati Bandung)
Muhammad Irfan Nur Imam (Teknik Informatika, UIN Sunan Gunung Djati Bandung)
Muhammad Thariq Sabiq Bilhaq (Teknik Informatika, UIN Sunan Gunung Djati Bandung)
Aisyah Amini Nur (Teknik Informatika, UIN Sunan Gunung Djati Bandung)
Siti Lufia Dwi Agustini (Teknik Informatika, UIN Sunan Gunung Djati Bandung)

Gunung Djati Conference Series
Vol. 3 (2021): Mini Seminar Kelas Data Mining 2020

The heart is an important part of the human body organs. But it does not rule out this heart problem and causes several symptoms, causing deadly heart disease. Therefore, many studies are used to obtain fast, precise and accurate heart disease diagnosis data. One of them is the classification of heart disease diagnoses using the Random Forest algorithm. This random forest algorithm method uses several unified decision trees. So that accurate results can be obtained regarding the diagnosis of this heart disease. The accuracy obtained from the experimental results using the Python programming language is 85.3%.