PENENTUAN JENIS MALARIA DENGAN MENGGUNAKAN METODE FORWARD CHAINING DAN NAIVE BAYES BERBASIS MOBILE

IRFANI MAHARANI, 1317051033 (2017) PENENTUAN JENIS MALARIA DENGAN MENGGUNAKAN METODE FORWARD CHAINING DAN NAIVE BAYES BERBASIS MOBILE. FAKULTAS MATEMATIKA DAN ILMU PENGETAHUAN ALAM, UNIVERSITAS LAMPUNG.

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Abstrak

ABSTRAK Penelitian ini dilakukan untuk membuat suatu sistem pakar yang mampu mengidentifikasi jenis malaria berdasarkan pengetahuan yang diberikan langsung dari pakar/ahlinya. Penelitian ini menggunakan metode perhitungan Naive Bayes dalam menghitung tingkat kepakaran dan dibuat pada mobile device platform Android. Data penelitian ini terdiri dari data gejala dan data jenis malaria, serta data aturan. Pada penelitian ini data jenis malaria dibatasi yaitu berjumlah 4 jenis penyakit dengan 25 jenis gejala dan 4 jenis aturan. Metode inferensi yang digunakan yaitu forward chaining Kata Kunci : Sistem Pakar, Naive Bayes, Forward Chaining, Jenis Malaria, Skala Likert, Android. ABSTRACT This research is aimed to establish an expert system that may identify the type of malaria based on knowledge that is given by the expert. This study uses Naïve Bayes calculation in measuring the level of expertise which is generated in Android mobile device platform. The data of this research consist of symptoms data, types of malarias data, and data rules. The type of malaria in this study are limited for 4 types only with 25 types of symptoms and 4 types of rules. The inference method in this study uses forward chaining method by searching the rules based on the answers that given by users. The answers of users then are processed by rules and computed by using Naïve Bayes calculation. The searching process is continued until getting a conclusion of malaria type probability in percentage. The results showed: Key Words : Expert System, Naive Bayes, Forward Chaining, Type of Malaria, Likert Scale, Android.

Tipe Karya Ilmiah: Skripsi
Subyek: Q Science (General)
Q Science (General) > QA Mathematics > QA76 Computer software
Program Studi: Fakultas MIPA > Prodi Ilmu Komputer
Depositing User: 74627479 . Digilib
Date Deposited: 31 Jul 2017 01:46
Last Modified: 31 Jul 2017 01:46
URI: http://digilib.unila.ac.id/id/eprint/27628

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