APPLICATION OF THE MINKOWSKI DISTANCE SIMILARITY METHOD IN CASE-BASED REASONING FOR STROKE DIAGNOSIS

Angelina Rumuy and Rosa Delima and Kuncoro Probo Saputra and Joko Purwadi (2023) APPLICATION OF THE MINKOWSKI DISTANCE SIMILARITY METHOD IN CASE-BASED REASONING FOR STROKE DIAGNOSIS. JUITA : Jurnal Informatika, 11 (2). pp. 323-332. ISSN 2579-8901

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Official URL: https://doi.org/10.30595/juita.v11i2.18582

Abstract

A Stroke is a cerebrovascular disease characterized by impaired brain function due to damage or death of brain tissue caused by reduced or blocked blood and oxygen flow to the brain. Expert systems can be used as learning aids for medical students to diagnose stroke. Medical records of stroke cases can be reused as a reference for diagnosing stroke when there are new cases, known as the case-based reasoning (CBR) method. This study implements the Minkowski distance similarity method in CBR to calculate the similarity value between cases, where each similar case has the same solution. This study uses the Minkowski distance similarity method in CBR to obtain the most optimal value of r and the most appropriate threshold value in the expert system for stroke diagnosis. The diagnosis process is carried out by inputting the patient's condition, symptoms, and risk factors. Then the system will calculate the similarity value and take the case with the highest similarity value as the solution, providing that the similarity value must be greater than or equal to the threshold value. Based on system testing, the best accuracy value was achieved by applying a threshold value of 75 with an r value of 3 or 4, with an accuracy rate of 88,89%, a recall value of 88%, and a precision of 100%.

Item Type:	Article
Uncontrolled Keywords:	Case-Based Reasoning, Stroke Diagnosis, Minkowski Distance similarity
Subjects:	Q Ilmu Pengetahuan > Matematika > Perangkat Lunak (Software) Komputer
Divisions:	Fakultas Teknologi Informasi
Depositing User:	Beatrix Stefany
Date Deposited:	12 Sep 2024 06:37
Last Modified:	12 Sep 2024 06:37
URI:	http://katalog.ukdw.ac.id/id/eprint/9184

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