Analyzing and visualizing data dengue hotspot location

In this paper, we will explore the Dengue Hotspot Location training data set that publicly available at data.gov.my. The data set consists of 10,116 cases reported according to respective district in Malaysia for 5 years, starting from 2011 until 2015. The dataset contain 7 columns which are: Tahun,...

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Main Authors:	Zainal Abidin, Nadzurah, Ismail, Amelia Ritahani
Format:	Conference or Workshop Item
Language:	English English
Published:	Universiti Malaya 2018
Subjects:	QA75 Electronic computers. Computer science
Online Access:	http://irep.iium.edu.my/65783/ http://irep.iium.edu.my/65783/2/Data%20Science%20Research%20Symposium%202018.pdf http://irep.iium.edu.my/65783/1/Analyzing%20and%20Visualizing%20Data%20-%20Finalized.pdf

id	iium-65783
recordtype	eprints
spelling	iium-657832018-09-04T06:52:01Z http://irep.iium.edu.my/65783/ Analyzing and visualizing data dengue hotspot location Zainal Abidin, Nadzurah Ismail, Amelia Ritahani QA75 Electronic computers. Computer science In this paper, we will explore the Dengue Hotspot Location training data set that publicly available at data.gov.my. The data set consists of 10,116 cases reported according to respective district in Malaysia for 5 years, starting from 2011 until 2015. The dataset contain 7 columns which are: Tahun, Minggu, Negeri, Daerah/Zon, Lokaliti, Jumlah Kes Terkumpul, and Tempoh Wabak Berlaku (Hari). The purpose of this study is to measure strength of the correlation between all variables in dataset Dengue Hotspot Location. This paper also focused primarily on the selection of suitable variables from a large data set and imputation of missing values. Many statistical models has proven to be fail with missing values. Besides, many researchers had proposed various ways to handle missing values. However, in this paper we demonstrate our approach for analyzing data with one of the machine learning classifier, Naïve Bayes. The choices were made from the highest accuracy among four machine learning classifiers experimented in the previous paper (Abidin, Ritahani, & Emran, 2018). Universiti Malaya 2018-07-12 Conference or Workshop Item NonPeerReviewed application/pdf en http://irep.iium.edu.my/65783/2/Data%20Science%20Research%20Symposium%202018.pdf application/pdf en http://irep.iium.edu.my/65783/1/Analyzing%20and%20Visualizing%20Data%20-%20Finalized.pdf Zainal Abidin, Nadzurah and Ismail, Amelia Ritahani (2018) Analyzing and visualizing data dengue hotspot location. In: Data Science Research Symposium 2018, University Malaya.
repository_type	Digital Repository
institution_category	Local University
institution	International Islamic University Malaysia
building	IIUM Repository
collection	Online Access
language	English English
topic	QA75 Electronic computers. Computer science
spellingShingle	QA75 Electronic computers. Computer science Zainal Abidin, Nadzurah Ismail, Amelia Ritahani Analyzing and visualizing data dengue hotspot location
description	In this paper, we will explore the Dengue Hotspot Location training data set that publicly available at data.gov.my. The data set consists of 10,116 cases reported according to respective district in Malaysia for 5 years, starting from 2011 until 2015. The dataset contain 7 columns which are: Tahun, Minggu, Negeri, Daerah/Zon, Lokaliti, Jumlah Kes Terkumpul, and Tempoh Wabak Berlaku (Hari). The purpose of this study is to measure strength of the correlation between all variables in dataset Dengue Hotspot Location. This paper also focused primarily on the selection of suitable variables from a large data set and imputation of missing values. Many statistical models has proven to be fail with missing values. Besides, many researchers had proposed various ways to handle missing values. However, in this paper we demonstrate our approach for analyzing data with one of the machine learning classifier, Naïve Bayes. The choices were made from the highest accuracy among four machine learning classifiers experimented in the previous paper (Abidin, Ritahani, & Emran, 2018).
format	Conference or Workshop Item
author	Zainal Abidin, Nadzurah Ismail, Amelia Ritahani
author_facet	Zainal Abidin, Nadzurah Ismail, Amelia Ritahani
author_sort	Zainal Abidin, Nadzurah
title	Analyzing and visualizing data dengue hotspot location
title_short	Analyzing and visualizing data dengue hotspot location
title_full	Analyzing and visualizing data dengue hotspot location
title_fullStr	Analyzing and visualizing data dengue hotspot location
title_full_unstemmed	Analyzing and visualizing data dengue hotspot location
title_sort	analyzing and visualizing data dengue hotspot location
publisher	Universiti Malaya
publishDate	2018
url	http://irep.iium.edu.my/65783/ http://irep.iium.edu.my/65783/2/Data%20Science%20Research%20Symposium%202018.pdf http://irep.iium.edu.my/65783/1/Analyzing%20and%20Visualizing%20Data%20-%20Finalized.pdf
first_indexed	2023-09-18T21:33:19Z
last_indexed	2023-09-18T21:33:19Z
_version_	1777412656055975936

Analyzing and visualizing data dengue hotspot location

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