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All Journal Jurnal Pepadun
Kurnia Muludi
Jurusan Ilmu Komputer, Fakultas Matematika dan Ilmu Pengetahuan Alam, Universitas Lampung
Computer Science & IT

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IMPLEMENTASI SUPPORT VECTOR MACHINE (SVM) DALAM MEMPREDIKSI JUMLAH PENYAKIT DEMAM BERDARAH (STUDI KASUS PENYEBARAN DEMAM BERDARAH DI SINGAPURA) Danu Sasmita; Favorisen Rosyking Lumbanraja; Kurnia Muludi; Astria Hijriani
Jurnal Pepadun Vol. 3 No. 2 (2022): August
Publisher : Department of Computer Science, Faculty of Mathematics and Natural Sciences, University of Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/pepadun.v3i2.123

Abstract

Dengue Hemorrhagic Fever (DHF) is an infectious disease caused by dengue virus infection and is transmitted through the bite of female mosquito species Aedes aegypti and Aedes albopictus. Environmental factors are one of the causes of the high prevalence of dengue fever, including the layout of buildings, water reservoirs, indentations in the soil, temperature and other things that can help the Aedes mosquito life cycle take place. The purpose of this study is to predict the spread of dengue disease using the SVM (Support Vector Machine) method with rainfall data in Singapore from 2014 to 2018, weather data and pain data, comparing this study with previous research by Adeline Ong in 2014 entitled " Predicting Dengue Cases in Singapore”, as well as knowing the results of predicting the distribution of DHF using the SVM method in the form of variance values (R2) with linear, gaussian and polynomial kernels. The results of the experiment found that the lowest error value was shown by the linear kernel with an error rate of 35.15%, with a variance value of 64.85%.
Analisis Sentimen Opini Masyarakat Terhadap Pelayanan BPJS Kesehatan Provinsi Lampung Berbasis Twitter Admi Syarif; Arafia Isnayu Akaf; Rizky Prabowo; Kurnia Muludi
Jurnal Pepadun Vol. 3 No. 3 (2022): December
Publisher : Department of Computer Science, Faculty of Mathematics and Natural Sciences, University of Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/pepadun.v3i3.136

Abstract

Nowadays, the internet has increased the amount of information stored and accessed through the web at a very fast speed. The internet can be a place to express opinions on health topics, politics, companies, and others. Many social media are used by the people of Lampung in expressing opinions and seeking information. Twitter is one of the communication media that is in great demand by the public. There are various kinds of topics discussed by Twitter users, one of the topics that are currently being discussed is the Lampung Health Social Security Administration Agency (BPJS). Health is also a very important thing and is still a conversation that is often discussed anywhere and anytime. BPJS Health helps the community in overcoming a declining economy, with BPJS Health, the community does not have to pay for medical expenses. Therefore, the service from BPJS Kesehatan Lampung will be carried out by sentiment analysis so that it can be known whether the public opinion about BPJS Kesehatan Lampung is positive or negative. This study uses the Naïve Bayes algorithm. This sentiment uses a dataset from Twitter which uses several keywords regarding BPJS Kesehatan Lampung. Based on the research results, it is known that the Naïve Bayes algorithm has an accuracy value of 89,33%.
Co-Authors Admi Syarif Arafia Isnayu Akaf Astria Hijriani Danu Sasmita Favorisen R. Lumbanraja Prabowo, Rizky