Diagnosa Penyakit Kanker Prostat menggunakan Metode Certainty Factor

The rapid development of information technology affects the way people access information, including in the health sector. Prostate cancer, as one of the most significant types of cancer in men, is often detected late due to lack of information and limited costs. To overcome this problem, a system is needed that is able to diagnose prostate cancer quickly, precisely, and accurately. This study aims to develop a web-based expert system using the Certainty Factor (CF) method to diagnose prostate cancer based on the symptoms that appear. The CF method was chosen because of its ability to determine the level of confidence in the facts or rules used in the diagnosis. This study uses data on symptoms and types of prostate cancer. The results of the study can help the public in recognizing prostate cancer symptoms early, with a high level of accuracy in diagnosis. This study is expected to make it easier for patients to make an early diagnosis and accelerate the treatment of prostate cancer.

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Publication Details

Journal
Mars Jurnal Teknik Mesin Industri Elektro Dan Ilmu Komputer
Published
2024-08-16
DOI
https://doi.org/10.61132/mars.v2i5.341
Primary Topic
Data Mining and Machine Learning Applications
Type
article
Field-Weighted Citation Impact
0.00
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article

Diagnosa Penyakit Kanker Prostat menggunakan Metode Certainty Factor

Victor Maruli Pakpahan, Achmad Fauzi, Nezha Febriyan
Mars Jurnal Teknik Mesin Industri Elektro Dan Ilmu Komputer
Data Mining and Machine Learning Applications
article

Diagnosa Penyakit Kanker Prostat menggunakan Metode Certainty Factor

Victor Maruli Pakpahan, Achmad Fauzi, Nezha Febriyan
article en

Abstract

The rapid development of information technology affects the way people access information, including in the health sector. Prostate cancer, as one of the most significant types of cancer in men, is often detected late due to lack of information and limited costs. To overcome this problem, a system is needed that is able to diagnose prostate cancer quickly, precisely, and accurately. This study aims to develop a web-based expert system using the Certainty Factor (CF) method to diagnose prostate cancer based on the symptoms that appear. The CF method was chosen because of its ability to determine the level of confidence in the facts or rules used in the diagnosis. This study uses data on symptoms and types of prostate cancer. The results of the study can help the public in recognizing prostate cancer symptoms early, with a high level of accuracy in diagnosis. This study is expected to make it easier for patients to make an early diagnosis and accelerate the treatment of prostate cancer.

Mars Jurnal Teknik Mesin Industri Elektro Dan Ilmu KomputerVol. 2(5)
Kootenay Association for Science & Technology (CA)
Openalex Percentile: Top 68%
Data Mining and Machine Learning Applications
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