Expert System to Diagnose Eye Disease Due to Frequently Using Computer with Bayes Theorem Method

Laia, Taozara; Hasugian, Penda Sudarto

doi:10.35335/idss.v5i1.46

Cited by 5 publications

(4 citation statements)

References 4 publications

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“…Bayes' theorem uses statistics to determine trade-offs between various decisions, using the probabilities and values that go along with each option. A technique for overcoming the problem of data ambiguity into definite data (Laia & Hasugian, 2022).…”

Section: Bayes' Theorem and Weighted Product Conceptmentioning

confidence: 99%

Profession recommendation based on multiple intelligence for high school students

Setyadi,

Supriyanta,

Ruswanti

et al. 2024

10.5267/j.msl

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One of the problems students often face is the lack of understanding of their interests and talents which will cause confusion in making future study choices and career plans. Career selection is an expression of personality into the world of work followed by identification of certain occupational stereotypes. Eight intelligences according to dr. Howard Gardner is linguistic, logical, mathematical, visual spatial, musical, kinesthetic, interpersonal, intrapersonal, and naturalist. This research purpose is to develop a system that produces information and professional recommendations that are in accordance with multiple intelligences of prospective high school students using a combination of Bayes' theorem and weighted product (WP) method. User’s preference value is calculated using the Bayes Theorem method to give each multiple intelligence value which is a criterion. WP method calculation to find professions that match user preferences. Weight of each criterion needed in WP method is calculated by Rank Order Centroid method. WP calculation will produce a ranking of 3 professions according to the input from the user. From system testing results that compared to results from experts, an accuracy of 67.33% is obtained. Based on the accuracy value, it can be said that the accuracy level system is quite good.

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Section: Bayes' Theorem and Weighted Product Conceptmentioning

confidence: 99%

Profession recommendation based on multiple intelligence for high school students

Setyadi,

Supriyanta,

Ruswanti

et al. 2024

10.5267/j.msl

View full text Add to dashboard Cite

show abstract

“…Literatür incelendiğinde, dikkat çeken uygulamaların özellikle kanser teşhislerinde Masood vd., 2019;Ragab vd., 2022;Sahu vd., 2020;Salem vd., 2016;Tsougos vd., 2018;West vd., 2005;Zhou vd., 2015) ve kalp hastalıklarının erken tespitinde (Bashir vd., 2014;Çomak vd., 2007;Gharehbaghi vd., 2017;Lahsasna vd., 2012;Paul vd., 2018;Safdar vd., 2018;Yan vd., 2006) gerçekleştirildiğini görmek mümkündür. Bununla birlikte göz hastalıkları teşhisi için geliştirilen sistemler de dikkate çekicidir (Borkhade, & Raut, 2015;Laia, & Hasugian, 2022;Lindahl vd., 1999;Lopez vd., 2016;Saleh, & Eswaran, 2014;Xu vd., 2016). Hastalık teşhisi uygulamalarında en önemli avantaj kuşkusuz ki görüntü tabanlı veriler için elde edilmekte; Derin Öğrenme modellerinin kullanımıyla hassas ve başarılı teşhisler gerçekleştiren zeki karar destek sistemleri etkili bir biçimde geliştirilmektedir.…”

Section: Sağlikta Zeki̇ Karar Destek Si̇stemleri̇unclassified

İş Dünyasında Yapay Zekâ-İnsan Etkileşimi Kongresi: Bildiriler Kitabı

Üniversitesi¹

2022

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“…Based on previous studies, an interpolation method is needed to normalize patient values in terms of laboratory data performed by Raditya et al, (2020). It shows that using the certainty factor results in a higher level of accuracy, reaching 96%, compared to Dempster-Shafer, which achieves 94%.…”

Section: Introductionmentioning

confidence: 99%

Optimization of Expert System Based on Interpolation, Forward Chaining, and Certainty Factor for Diagnosing Abdominal Colic

Soetanto,

Painem,

Suryadewiansyah

2024

Journal of Computer Science

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Abdominal colic is a common condition that affects infants and it can be difficult to diagnose because it shares many symptoms with other conditions, such as gastric disease and appendicitis. Limitations of existing diagnostic methods include the unreliability of physical examinations and medical histories and the high cost and time-consuming nature of imaging tests. This research proposes an expert system based on interpolation, forward chaining, and certainty factors for diagnosing abdominal colic. This system has the potential to provide a more accurate and efficient way to diagnose abdominal colic, which could lead to better patient outcomes. This research proposes an expert system based on interpolation, forward chaining, and certainty factors for diagnosing abdominal colic. This system is implemented as a web application model. The forward chaining method is used to establish rules for the expert system. The rules are based on the symptoms and diseases that are included in the system's knowledge base. The interpolation method is used to normalize lab results and the certainty factor method is used to process medical history and physical examinations. This is necessary because medical history and physical examinations can be imprecise. The expert system was tested on a dataset of 100 cases and it was able to accurately diagnose 96 patients, achieving a 96% accuracy rate. This suggests that the expert system has the potential to provide a more accurate and efficient way to diagnose abdominal colic, which could lead to better patient outcomes.

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Expert System to Diagnose Eye Disease Due to Frequently Using Computer with Bayes Theorem Method

Cited by 5 publications

References 4 publications

Profession recommendation based on multiple intelligence for high school students

Profession recommendation based on multiple intelligence for high school students

İş Dünyasında Yapay Zekâ-İnsan Etkileşimi Kongresi: Bildiriler Kitabı

Optimization of Expert System Based on Interpolation, Forward Chaining, and Certainty Factor for Diagnosing Abdominal Colic

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