Sistem Pakar Mendiagnosa Penyakit Pada Tumor Otak Menggunakan Metode Case Based Reasoning (CBR)

This research aims to develop an expert system that can diagnose diseases related to brain tumors using the Case Based Reasoning (CBR) method. The CBR method works by comparing new cases with previous cases that have been stored in the database to provide appropriate diagnoses and treatment recommendations. This system is designed to assist medical personnel in analyzing patient symptoms, thus speeding up the process of identifying the type of brain tumor. In addition, the system is also equipped with a knowledge base obtained from real cases that have been validated by medical experts. Test results show that the diagnostic accuracy of this system reaches a fairly high level, especially in detecting frequently encountered types of brain tumors. Thus, this system has the potential to be an effective tool in the medical diagnosis process, especially in patients who show symptoms of brain tumors.

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Publication Details

Journal
Modem
Published
2024-09-19
DOI
https://doi.org/10.62951/modem.v2i4.253
Primary Topic
Edcuational Technology Systems
Type
article
Field-Weighted Citation Impact
0.00
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article

Sistem Pakar Mendiagnosa Penyakit Pada Tumor Otak Menggunakan Metode Case Based Reasoning (CBR)

Yani Maulita, Mhd Arif Permata, Victor Maruli Pakpahan
Modem
Edcuational Technology Systems
article

Sistem Pakar Mendiagnosa Penyakit Pada Tumor Otak Menggunakan Metode Case Based Reasoning (CBR)

Yani Maulita, Mhd Arif Permata, Victor Maruli Pakpahan
article en

Abstract

This research aims to develop an expert system that can diagnose diseases related to brain tumors using the Case Based Reasoning (CBR) method. The CBR method works by comparing new cases with previous cases that have been stored in the database to provide appropriate diagnoses and treatment recommendations. This system is designed to assist medical personnel in analyzing patient symptoms, thus speeding up the process of identifying the type of brain tumor. In addition, the system is also equipped with a knowledge base obtained from real cases that have been validated by medical experts. Test results show that the diagnostic accuracy of this system reaches a fairly high level, especially in detecting frequently encountered types of brain tumors. Thus, this system has the potential to be an effective tool in the medical diagnosis process, especially in patients who show symptoms of brain tumors.

ModemVol. 2(4)
Kootenay Association for Science & Technology (CA)
Good health and well-being
Openalex Percentile: Top 81%
Edcuational Technology Systems
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