SISTEM PAKAR BERBASIS WEB UNTUK MENDIAGNOSA PENYAKIT EPILEPSI DAN PENANGANANNYA MENGGUNAKAN THEOREMA BAYES

MELLYANA CAHYA NINGRUM , NIM. 08651002 (2013) SISTEM PAKAR BERBASIS WEB UNTUK MENDIAGNOSA PENYAKIT EPILEPSI DAN PENANGANANNYA MENGGUNAKAN THEOREMA BAYES. Skripsi thesis, UIN SUNAN KALIJAGA.

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Abstract

Todays, computer technology has widely used in various domain with no exception in medical world. Expert system is one of the computer technology branch which try to adopt the human mind to the computer system so that it can mimics the human expert in a way of solve some particular problems. The main objectives of expert system development is to substitute the human knowledge on the computer system in order to assist the ordinary/non-expert people for solving a particular problem. We use ESDLC (Expert System Development Life Cycle) as a development method for this research. ESDLC consist of several steps such as identifying and analyzing problems, acquisition and representation of knowledge (knowledge representation), prototype development, verification, validation and testing, implementation and integration. Then, we use PHP and MySQL for the program implementation and also, we use a forward chaining as inference method. Our application require symptoms suffered by the patien as an input. Afterward, our system will generate the possible disease suffered by the patient and it's explanation. Based on the problems definition and method development above, we can conclude that this system can assist the doctor especially who dealing with nerve epilepsy. The expert system based-on bayes theorem can be used as a supporting tool for diagnosing epilepsy based on the type syndrome. Hopefully, our system can help people to get information about epilepsy faster and easier. Our system implement bayes theorem and rule-based probability that can support the developed expert system to generate the solution based on the input received. Key words: Expert System, Epilepsy, Symptoms, Forward Chaining, Bayes Theorem, PHP, MySQL

Item Type: Thesis (Skripsi)
Subjects: Tehnik Informatika
Divisions: Fakultas Sains dan Teknologi > Teknik Informatika (S1)
Depositing User / Editor: Miftahul Ulum [IT Staff]
Date Deposited: 19 Apr 2013 15:54
Last Modified: 11 Mar 2016 08:52
URI: http://digilib.uin-suka.ac.id/id/eprint/7267

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