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BIOSURVEILLANCE UNTUK DETEKSI PENYEBARAN PENYAKIT DI INDONESIA BERDASARKAN TWEETS MENGGUNAKAN ALGORITMA NAÏVE BAYES

Oktavianto, Lazqar Markus (2018) BIOSURVEILLANCE UNTUK DETEKSI PENYEBARAN PENYAKIT DI INDONESIA BERDASARKAN TWEETS MENGGUNAKAN ALGORITMA NAÏVE BAYES. Bachelors Degree (S1) thesis, University of Muhammadiyah Malang.

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Abstract

Biosurveillance is the information process, integration, and communication of information that is very likely to relate to humans, animals, or plant health. This study uses a method that can classify what is appropriate with the target class that has been determined. The classification process is based on the extraction of synthetic features. The results of the extraction then use the Naïve Bayes algorithm. The purpose of this study is to tweets data, then it will be visualized in the location map. The Naïve Bayes algorithm was chosen because it has a better level of accuracy than other algorithms. Based on the scenarios that have been done, the accuracy results that result in the tweet data process using the extraction of synthetic features on the test data (test data) of 91.5%. The accuracy results obtained from Named Entity Recognition (NER) to find the location is 96%. The results of testing the system, the average accuracy value is the best. Hopefully the system can be used to develop other supporting features and algorithms.

Item Type: Thesis (Bachelors Degree (S1))
Student ID: 201310370311189
Keywords: Biosurveillance, Naïve Bayes, NER
Subjects: Z Bibliography. Library Science. Information Resources > ZA Information resources
Divisions: Faculty of Engineering > Department of Informatics (55201)
Depositing User: Sulistyaningsih Sulistyaningsih
Date Deposited: 26 Dec 2018 07:56
Last Modified: 26 Dec 2018 07:56
URI : http://eprints.umm.ac.id/id/eprint/42595

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