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All Journal Jurnal Informatika dan Rekayasa Elektronik
Supardianto Supadianto
Universitas Islam Indonesia
Computer Science & IT

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IMPLEMENTASI SPARQL DENGAN FRAMEWORK JENA FUSEKI UNTUK MELAKUKAN PENCARIAN PENGETAHUAN PADA MODEL ONTOLOGI JALUR KLINIS TATA LAKSANA PERAWATAN PENYAKIT KATARAK Lalu Mutawalli; Indi Febriana Suhriani; Supardianto Supardianto
Jurnal Informatika dan Rekayasa Elektronik Vol. 1 No. 2 (2018): JIRE Nopember 2018
Publisher : LPPM STMIK Lombok

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36595/jire.v1i2.66

Abstract

Abstract The prevalence of cataracts in Indonesia is very high, this can affect the quality of life, productivity and social aspects will cause the nation's economy to be in a low-level position. Cataract problems certainly need to be considered more, however, on the other hand, the lack of experts (doctors) is an obstacle especially outside the city. Uneven distribution of experts will complicate the conditions for solving problems. With these conditions, a semantic-based information technology approach is needed regarding the treatment of patients with cataracts. Semantic information can provide knowledge to non-physician health workers, this will certainly facilitate the process of prevention and prevention of cataracts. In this research, knowledge is modeled using the ontology concept. We have built an ontology model that can be used as a guide to the management of cataract disease. To extract the built-in ontology model, simple protocol and RDF Language (SPARQL) are used as query languages. Apache Jena Fuseki is used to simplify the process of evaluating knowledge.
FUZZY EXPERT SYSTEM UNTUK MEMBANTU DIAGNOSIS AWAL SINDROMA METABOLIK Supardianto Supadianto; Sri Kusumadewi; Linda Rosita
Jurnal Informatika dan Rekayasa Elektronik Vol. 4 No. 1 (2021): JIRE April 2021
Publisher : LPPM STMIK Lombok

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36595/jire.v4i1.313

Abstract

Metabolic syndrome is a condition that occurs in a person simultaneously, such as an increase in blood pressure, high blood sugar levels, excess fat around the waist, and an unusual increase in cholesterol levels. This condition makes the risk for sufferers experiencing heart disease, stroke, and diabetes mellitus very high. Metabolic syndrome is a non-contagious disease. A person who has metabolic syndrome is usually difficult to detect, because experts are needed to analyze it. Fuzzy Expert System (Fuzzy Expert System) is part of artificial intelligence using fuzzy logic. where the system tries to adopt human knowledge to computers so that computers can solve problems as usually done by experts. Where later the results of the system developed in the study can at least help experts (doctors) in providing conclusions on the risk of disease suffered by patients through the analysis of metabolic syndrome. This system will involve experts such as doctors and patients, where the doctor makes a diagnosis of the patient's metabolic syndrome analysis results, and the patient is used to seeing the diagnosis of the risk of the disease being suffered.
Co-Authors Indi Febriana Suhriani Lalu Mutawalli Linda Rosita Sri Kusumadewi