Kidney failure diagnosis based on case-based reasoning (CBR) method and statistical analysis

Anggrawan, Anthony; Hidjah, Khasnur; Jihadil, Qudsi S.

doi:10.1109/iac.2016.7905733

Cited by 6 publications

(4 citation statements)

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“…Anthony Anggrawan, Khasnur Hidjah, and Jihadil Qudsi S. (2017) implemented an application system to detect kidney failure [20]. The previous research and this article have similarities in realizing a computer application system using the PHP programming language and MySQL database.…”

Section: Introductionmentioning

confidence: 94%

Scholarship Recipients Recommendation System Using AHP and Moora Methods

2022

IJIES

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Providing scholarships to students is an important action in helping students succeed in their studies. The scholarship recipients are students who meet the specified criteria. However, it is not easy to decide which scholarship recipients are genuinely eligible to receive scholarships, especially if the selection process for prospective scholarship recipients is done manually. Many prospective scholarship recipients must be selected, and more than one criterion is required. That is why it is not surprising that awarding scholarships to selected candidates takes a long time and the accuracy of the results is dubious. It means there needs to be a system that can assist in choosing prospective students who meet the criteria for the best requirements as scholarship recipients. Therefore, the purpose of this research is to build an application system that can provide recommendations for eligible candidates for scholarship recipients based on consideration of the criteria possessed by prospective scholarship recipients. This research method is an experimental study using a combination of the Analytical Hierarchy Process (AHP) and the Multi-Objective Optimization Method by Ratio Analysis (Moora) method to rank scholarship recipients. The study results indicate that using an application system integrated into the database in recommending prospective scholarship recipients according to the desired conditions is more accurate using a combination of AHP and Moora methods (up to 94.07%) than using only one Moora method (which is only 89.62%). This means that the selection of scholarship recipients according to the desired qualifications using the AHP method for weighting and the Moora method for ranking is a combination of methods that have relatively more reliable accuracy.

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Section: Introductionmentioning

confidence: 94%

Scholarship Recipients Recommendation System Using AHP and Moora Methods

2022

IJIES

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“… Anthony Anggrawan, Khasnur Hidjah, and Jihadil Qudsi S. (2017) implement intelligent application programs to detect kidney failure [19]. The previous research and the research in this article have similarities in developing web application programs with the PHP programming language and MySQL database.…”

Section: Introductionmentioning

confidence: 94%

Machine Learning for Diagnosing Drug Users and Types of Drugs Used

Anggrawan¹,

Satria²,

Nuraini³

et al. 2021

IJACSA

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Drug use is very detrimental to the physical and psychological health of users. Drug abuse also causes addiction and is a global epidemic. Therefore it is not surprising that scientific research related to drugs has attracted attention for research. However, many factors become obstacles in the medical services of the drug user, including cost, flexibility, and a slow process. Meanwhile, electronic systems can speed up handling time, improve work efficiency, save costs and reduce inspection errors. It means that a breakthrough is needed in developing a platform that can identify drug users. Therefore, this research aims to build machine learning with expertise like an expert who can diagnose drug users and distinguish the types of drugs used by drug users. The expert system on machine learning was developed using the Forward Chaining and Certainty Factor methods. This study concludes that the expert system on machine learning developed can be used to diagnose drug users and distinguish the types of drugs used with an accuracy of up to 80%. The implications of the expert system on machine learning are an alternative method for narcotics officers and medical doctors in diagnosing drug users and the types of drugs used.

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“…Various similarities or distance measurements have been proposed and widely applied, such as the cosine similarity and Jaccard correlation coefficient. The similarity calculation between documents is measured using a simple matching coefficient [16] and the Vector Space Model method in determining the similarity percentage of each document [17]. Meanwhile, similarities are often conceived in terms of inequality or distance as well [18].…”

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confidence: 99%

Analysis of Document Clustering based on Cosine Similarity and K-Main Algorithms

Triwijoyo

Kartarina

2019

journalisi

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Clustering is a useful technique that organizes a large number of non-sequential text documents into a small number of clusters that are meaningful and coherent. Effective and efficient organization of documents is needed, making it easy for intuitive and informative tracking mechanisms. In this paper, we proposed clustering documents using cosine similarity and k-main. The experimental results show that based on the experimental results the accuracy of our method is 84.3%.

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Kidney failure diagnosis based on case-based reasoning (CBR) method and statistical analysis

Cited by 6 publications

References 0 publications

Scholarship Recipients Recommendation System Using AHP and Moora Methods

Scholarship Recipients Recommendation System Using AHP and Moora Methods

Machine Learning for Diagnosing Drug Users and Types of Drugs Used

Analysis of Document Clustering based on Cosine Similarity and K-Main Algorithms

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