ANALISA METODE SUPPORT VECTOR MACHINE UNTUK PREDIKSI PENYAKIT HEPATITIS

PANGESTU, ARIF RAHMAN AJI (2024) ANALISA METODE SUPPORT VECTOR MACHINE UNTUK PREDIKSI PENYAKIT HEPATITIS. S1 thesis, Universitas Mercu Buana Jakarta.

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Abstract

The liver is the largest and most important organ in our body. We can't live without a heart. Liver disease is inflammation caused by infection with viruses, bacteria or toxic materials so that the liver cannot perform its functions properly and is not easy to find in the early stages of diagnosing liver disease [1]. Hepatitis is an inflammatory disease of the liver due to a viral infection that attacks and causes damage to the cells and functions of the liver. Hepatitis is a forerunner of liver cancer. Hepatitis can damage the function of the liver as a poison neutralizer and the digestive system of food in the body which breaks down food essences to then be distributed to all organs of the body which are very important for humans [2]. In this research, the support vector machine algorithm model, the K-Nearest Neighbor algorithm model to obtain rules for predicting hepatitis and provide a more accurate value than accuracy. Keywords : Hepatitis B, Support Vector Machine, K-Nearest Neighbor Hati adalah organ yang paling besar dan penting bagi tubuh kita. Kita tidak bisa hidup tanpa hati. Penyakit hati merupakan peradangan yang disebabkan oleh infeksi virus, bakteri atau bahan-bahan beracun sehingga hati tidak dapat melakukan fungsinya dengan baik serta tidak mudah ditemukan dalam tahap awal dalam mendiagnosis penyakit hati [1]. Penyakit hepatitis merupakan penyakit peradangan hati karena infeksi virus yang menyerang dan menyebabkan kerusakan pada sel-sel dan fungsi organ hati. Penyakit hepatitis merupakan penyakit cikal bakal dari kanker hati. Penyakit hepatitis dapat merusak fungsi organ hati sebagai penetral racun dan sistem pencernaan makanan dalam tubuh yang mengurai sari-sari makanan untuk kemudian disebarkan ke seluruh organ tubuh yang sangat penting bagi manusia [2]. Dalam penelitian yang dilakukan ini model algoritma support vector machine, model algoritma K-Nearest Neighbor untuk mendapatkan aturan untuk memprediksi penyakit Hepatitis dan memberikan nilai yang lebih akurat dari akurasi. Kata Kunci : Hepatitis B, Support Vector Machine, K-Nearest Neighbor

Item Type:	Thesis (S1)
Call Number CD:	FIK/INFO. 24 078
NIM/NIDN Creators:	41519010201
Uncontrolled Keywords:	Hepatitis B, Support Vector Machine, K-Nearest Neighbor
Subjects:	000 Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum > 000. Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum > 004 Data Processing, Computer Science/Pemrosesan Data, Ilmu Komputer, Teknik Informatika 100 Philosophy and Psychology/Filsafat dan Psikologi > 150 Psychology/Psikologi > 155 Differential and Developmental Psychology/Psikologi Diferensial dan Psikologi Perkembangan > 155.9 Environmental Psychology/Psikologi Lingkungan > 155.91 Influence of Physical Environment and Conditions/Pengaruh Lingkungan dan Kondisi Fisik > 155.916 Influence of Injuries, Diseases, Physical Disabilities, Disfigurements/Pengaruh Cedera, Penyakit, Cacat Fisik
Divisions:	Fakultas Ilmu Komputer > Informatika
Depositing User:	khalimah
Date Deposited:	02 Apr 2024 09:12
Last Modified:	02 Apr 2024 09:12
URI:	http://repository.mercubuana.ac.id/id/eprint/87869

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