eprintid: 9189
rev_number: 10
eprint_status: archive
userid: 2098
dir: disk0/00/00/91/89
datestamp: 2024-09-12 06:42:33
lastmod: 2024-09-12 06:42:33
status_changed: 2024-09-12 06:42:33
type: article
metadata_visibility: show
contact_email: repository@staff.ukdw.ac.id
creators_name: , Joko Purwadi
creators_name: , Rosa Delima
creators_name: , Argo Wibowo
creators_name: , Angelina Rumuy
creators_id: 0515047001
creators_id: 0228107401
creators_id: 0516118902
creators_id: 71190506
title: COMPARISON OF THE APPLICATION OF WEIGHTED COSINE SIMILARITY AND MINKOWSKI DISTANCE SIMILARITY METHODS IN STROKE DIAGNOSTIC SYSTEMS
ispublished: pub
subjects: QA76
subjects: R1
divisions: fak_tein
full_text_status: public
keywords: Expert system; stroke; case-based reasoning; Minkowski Distance; jaccard coefficient; weighted cosine; threshold; accuracy; diagnosis
abstract: Stroke is a critical medical condition requiring prompt intervention due to its multifaceted symptoms and causes influenced by various factors, including psychological aspects and the patient's lifestyle or daily habits that impact risk factors. The recovery process involves consistent medical care and lifestyle adjustments tailored to the individual case. Expert Systems, a scientific field focused on studying and developing diagnostic systems, can employ the Case-based Reasoning method to identify the type of stroke based on similarities with prior patient cases, considering specific causes and symptoms. This study utilizes the Weighted Cosine, Jaccard Coefficient, and Minkowski Distance methods to assess the similarity of stroke cases. The evaluation is based on input data such as patient causes or symptoms and risk factors from medical records. The analysis of case similarity and solutions involves applying the Weighted Cosine, Jaccard Coefficient, and Minkowski Distance methods, with a defined threshold value. The highest similarity values from previous patient cases are selected for each method. The test outcomes suggest that employing the Minkowski Distance method with a threshold value of 75 and an r value of three or four yields the highest levels of accuracy, recall, and precision. The Minkowski Distance achieves an accuracy and recall rate of more than 88 percent with 100 percent precision.
date: 2023
publication: (IJACSA) International Journal of Advanced Computer Science and Applications
volume: 14
number: 12
publisher: (IJACSA) International Journal of Advanced Computer Science and Applications
pagerange: 394-400
refereed: TRUE
issn: 2156-5570
official_url: https://thesai.org/Publications/ViewIssue?volume=14&issue=12&code=IJACSA
citation:   Joko Purwadi and Rosa Delima and Argo Wibowo and Angelina Rumuy  (2023) COMPARISON OF THE APPLICATION OF WEIGHTED COSINE SIMILARITY AND MINKOWSKI DISTANCE SIMILARITY METHODS IN STROKE DIAGNOSTIC SYSTEMS.  (IJACSA) International Journal of Advanced Computer Science and Applications, 14 (12).  pp. 394-400.  ISSN 2156-5570     
document_url: https://katalog.ukdw.ac.id/9189/1/Comparison%20of%20the%20Application%20of%20Weighted%20Cosine.pdf