Performance analysis of data mining methods for sexually transmitted disease classification

Gusti E. Yuliastuti; Adyan N. Alfiyatin; Agung M. Rizki; A. Hamdianah; H. Taufiq; W. F. Mahmudy

doi:10.11591/ijece.v8i5.pp3933-3939

Performance analysis of data mining methods for sexually transmitted disease classification

Gusti E. Yuliastuti
, Adyan N. Alfiyatin
, Agung M. Rizki
, A. Hamdianah
, H. Taufiq
, W. F. Mahmudy^*

^*Corresponding author for this work

Faculty of Computer Science

Research output: Contribution to journal › Article › peer-review

9 Citations (Scopus)

Abstract

According to health reports of Malang city, many people are exposed to sexually transmitted diseases and most sufferers are not aware of the symptoms. Malang city being known as a city of education so that every year the population number increases, it is at risk of increasing the spread of sexually transmitted diseases virus. This problem is important to be solved to treat earlier sufferers sexually transmitted diseases virus in order to reduce the burden of patient spending. In this research, authors conduct data mining methods to classifying sexually transmitted diseases. From the experiment result shows that K-NN is the best method for solve this problem with 90% accuracy.

Original language	English
Pages (from-to)	3933-3939
Number of pages	7
Journal	International Journal of Electrical and Computer Engineering
Volume	8
Issue number	5
DOIs	https://doi.org/10.11591/ijece.v8i5.pp3933-3939
Publication status	Published - 2018

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 5 Gender Equality

Keywords

Classification task
Data mining
K-means
K-nearest neighbor
Naïve bayes
Sexually transmitted disease

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10.11591/ijece.v8i5.pp3933-3939

Cite this

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title = "Performance analysis of data mining methods for sexually transmitted disease classification",

abstract = "According to health reports of Malang city, many people are exposed to sexually transmitted diseases and most sufferers are not aware of the symptoms. Malang city being known as a city of education so that every year the population number increases, it is at risk of increasing the spread of sexually transmitted diseases virus. This problem is important to be solved to treat earlier sufferers sexually transmitted diseases virus in order to reduce the burden of patient spending. In this research, authors conduct data mining methods to classifying sexually transmitted diseases. From the experiment result shows that K-NN is the best method for solve this problem with 90\% accuracy.",

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AU - Yuliastuti, Gusti E.

AU - Alfiyatin, Adyan N.

AU - Rizki, Agung M.

AU - Hamdianah, A.

AU - Taufiq, H.

AU - Mahmudy, W. F.

PY - 2018

Y1 - 2018

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AB - According to health reports of Malang city, many people are exposed to sexually transmitted diseases and most sufferers are not aware of the symptoms. Malang city being known as a city of education so that every year the population number increases, it is at risk of increasing the spread of sexually transmitted diseases virus. This problem is important to be solved to treat earlier sufferers sexually transmitted diseases virus in order to reduce the burden of patient spending. In this research, authors conduct data mining methods to classifying sexually transmitted diseases. From the experiment result shows that K-NN is the best method for solve this problem with 90% accuracy.

KW - Classification task

KW - Data mining

KW - K-means

KW - K-nearest neighbor

KW - Naïve bayes

KW - Sexually transmitted disease

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DO - 10.11591/ijece.v8i5.pp3933-3939

M3 - Article

AN - SCOPUS:85053750797

SN - 2088-8708

VL - 8

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EP - 3939

JO - International Journal of Electrical and Computer Engineering

JF - International Journal of Electrical and Computer Engineering

IS - 5

ER -

Performance analysis of data mining methods for sexually transmitted disease classification

Abstract

UN SDGs

Keywords

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