DIAGNOSA PENYAKIT PERNAFASAN DENGAN CERTAINTY FACTOR DAN PARTICLE SWARM OPTIMIZATION

PURWANTI, RANI INDAH and Rini, Dian Palupi and Miraswan, Kanda Januar (2020) DIAGNOSA PENYAKIT PERNAFASAN DENGAN CERTAINTY FACTOR DAN PARTICLE SWARM OPTIMIZATION. Undergraduate thesis, Sriwijaya University.

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Abstract

Respiration is an important organ for every individual and and often is not detected early with a layman so that requires an expert. One of artificial intelligence is an expert system. This expert system itself is the knowledge of the experts implemented into the system. Expert systems can help in solving a problem. The problem that is the case in this study is respiratory disease. Through this expert system sufferers can bridge themselves with experts. The knowledge used in this study was processed with Certainty Factor. However, because this method has expert values that are considered subjective, this study will overcome these shortcomings by searching for expert value optimization using Particle Swarm Optimization (PSO). Where the PSO method will produce expert value with the best optimization in the search process. This study compares the results of disease diagnosis in Certainty Factor with subjective expert values with the Certainty Factor method whose expert value is sought using the PSO method. From this study, the highest accuracy is obtained at 80% when using the CF-PSO method

Item Type: Thesis (Undergraduate)
Uncontrolled Keywords: sistem pakar, nilai pakar, penyakit pernafasan
Subjects: T Technology > T Technology (General) > T1-995 Technology (General)
T Technology > TJ Mechanical engineering and machinery > TJ1125-1345 Machine shops and machine shop practice > TJ1180 Machining, Ceramic materials--Machining-Strength of materials-Machine tools-Design and construction > TJ1180.I34 Machining-Machine tools-Numerical control-Computer integrated manufacturing systems-Artificial intelligence
Divisions: 09-Faculty of Computer Science > 55201-Informatics (S1)
Depositing User: Rani Indah Purwanti
Date Deposited: 29 Jun 2020 04:55
Last Modified: 29 Jun 2020 04:55
URI: http://repository.unsri.ac.id/id/eprint/30880

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