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Implementation of Fuzzy Logic Method and Certainty Factor for Diagnosis Expert System of Chronic Kidney Disease

Journal of Advances in Information Systems and Technology · Vol. 2 No. 1 (2020) · hlm. 61–68

DOI
10.15294/jaist.v2i1.44369
ISSN
2715-999X, 2714-9714
Terbit
2020-04-30
Penerbit
Department of Computer Science, Faculty of Mathematics and Natural Sciences, Universitas Negeri Semarang
Bahasa
eng
Lisensi
creativecommons.org/licenses/by-sa/4.0

Abstrak

Problem analysis from the development of technology that was originally conducted manually, it can now conduct systematically using computerization. An expert system can solve one problem analysis in diagnosing a disease like chronic kidney disease. Fuzzy logic and certainty factor are expert system methods that are often used. The data used in this research was Chronic Kidney Disease, which was obtained from the UCI dataset. The system was developed using the Laravel PHP framework programming language and MySQL database. The system's development used the waterfall method, which was analyzing user needs to the system, conducting design of the system, coding, and testing the system if it achieves what was expected. The combination of fuzzy logic and certainty factor methods worked with several stages, namely fuzzification (CFuser), rule base formation for CF, calculating CFexpert, Calculating CF values, the combination of CF values, Finding CFmaximum. The accuracy level of the system generated from 400 data was obtained 92.25% accuracy for the fuzzy logic method, 97.25% accuracy for the certainty factor, 99% accuracy method for the combination of fuzzy logic and certainty factor methods. While the kappa value for the fuzzy logic method, certainty factor, and the combination of the two methods were respectively 0.84, 0.94, 0.98.

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  • State University of Semarang
  • International Islamic University Malaysia
  • Universitas PGRI Palembang
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Rekan penulisOrganisasiArtikel bersama
Endang SugihartiState University of Semarang5
Amin SuyitnoState University of Semarang5
Rochmad RochmadInternational Islamic University Malaysia3
Alamsyah AlamsyahState University of Semarang3
Much Aziz MuslimState University of Semarang3
Novanka Agnes SekartajiState University of Semarang2
Irfan Fajar MuttaqinState University of Semarang2
Ramadhan Ridho ArrohmanState University of Semarang2
Dwijanto DwijantoState University of Semarang2
Putriaji HendikawatiState University of Semarang2
Hanif Ilmi MardlootillahAfiliasi tidak diketahui2
Anggyi Trisnawan PutraState University of Semarang2
Athoillah AthoillahState University of Semarang2
Muhammad Kahvi Khakam SyahState University of Semarang1
Fernando Dinar SetiawanState University of Semarang1
Rafif Musyaffa IndartoAfiliasi tidak diketahui1
Muhammad Danil AminuddinAfiliasi tidak diketahui1
Fairuz Trideas HilmyAfiliasi tidak diketahui1
Ahmad Imam MutaqinState University of Semarang1
Budi PrasetiyoState University of Semarang1
Jumanto JumantoState University of Semarang1
Rofik RofikState University of Semarang1
Arif WidiyatmokoState University of Semarang1
Stephani Diah PamelasariState University of Semarang1
Arka YanitamaState University of Semarang1
Melissa Salma DarmawanState University of Semarang1
Aji SaputraUniversitas PGRI Palembang1
Desy Fitria AstutianingtyasAfiliasi tidak diketahui1
Gerard Sean DwayneAfiliasi tidak diketahui1
Aisyah Nathania AramintaAfiliasi tidak diketahui1
Inoru Nian AlfitaAfiliasi tidak diketahui1
Ahmad Zidhan IlmanaAfiliasi tidak diketahui1
Nathania AdristinaAfiliasi tidak diketahui1
Syafa Nabilah SyahputraState University of Semarang1
Kholiq BudimanAfiliasi tidak diketahui1
Anggyi Trisnawan PutraAfiliasi tidak diketahui1
zaenal abidinAfiliasi tidak diketahui1

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Sumber metadata: OAI-PMH (metadata jurnal) https://journal.unnes.ac.id/sju/index.php/jaist/oai, pertama di-harvest 6 Nov 2026, terakhir terlihat 8 Nov 2026.
Metadata asli (oai_dc) 
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	<dc:title xml:lang="en-US">Implementation of Fuzzy Logic Method and Certainty Factor for Diagnosis Expert System of Chronic Kidney Disease</dc:title>
	<dc:creator>Agusta, Anggil</dc:creator>
	<dc:creator>Arini, Florentina Yuni</dc:creator>
	<dc:creator>Arifudin, Riza</dc:creator>
	<dc:description xml:lang="en-US">Problem analysis from the development of technology that was originally conducted manually, it can now conduct systematically using computerization. An expert system can solve one problem analysis in diagnosing a disease like chronic kidney disease. Fuzzy logic and certainty factor are expert system methods that are often used. The data used in this research was Chronic Kidney Disease, which was obtained from the UCI dataset. The system was developed using the Laravel PHP framework programming language and MySQL database. The system's development used the waterfall method, which was analyzing user needs to the system, conducting design of the system, coding, and testing the system if it achieves what was expected. The combination of fuzzy logic and certainty factor methods worked with several stages, namely fuzzification (CFuser), rule base formation for CF, calculating CFexpert, Calculating CF values, the combination of CF values, Finding CFmaximum. The accuracy level of the system generated from 400 data was obtained 92.25% accuracy for the fuzzy logic method, 97.25% accuracy for the certainty factor, 99% accuracy method for the combination of fuzzy logic and certainty factor methods. While the kappa value for the fuzzy logic method, certainty factor, and the combination of the two methods were respectively 0.84, 0.94, 0.98.</dc:description>
	<dc:publisher xml:lang="en-US">Department of Computer Science, Faculty of Mathematics and Natural Sciences, Universitas Negeri Semarang</dc:publisher>
	<dc:date>2020-04-30</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
	<dc:type>info:eu-repo/semantics/publishedVersion</dc:type>
	<dc:type xml:lang="en-US">Peer-reviewed Article</dc:type>
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	<dc:identifier>https://journal.unnes.ac.id/sju/jaist/article/view/44369</dc:identifier>
	<dc:identifier>10.15294/jaist.v2i1.44369</dc:identifier>
	<dc:source xml:lang="en-US">Journal of Advances in Information Systems and Technology; Vol 2 No 1 (2020): April; 61-68</dc:source>
	<dc:source>2715-999X</dc:source>
	<dc:source>2714-9714</dc:source>
	<dc:source>10.15294/jaist.v2i1</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://journal.unnes.ac.id/sju/jaist/article/view/44369/18059</dc:relation>
	<dc:rights xml:lang="en-US">Copyright (c) 2020 Journal of Advances in Information Systems and Technology</dc:rights>
	<dc:rights xml:lang="en-US">http://creativecommons.org/licenses/by-sa/4.0</dc:rights>
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