Article Per Year (5 Year)
p-Index From 2020 - 2025
2.319
P-Index
This Author published in this journals
All Journal International Journal of Advances in Intelligent Informatics Jurnal Pengabdian UntukMu NegeRI Journal of Information Technology and Computer Science (JOINTECS) JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI Sebatik Jurnal Teknik Informatika UNIKA Santo Thomas Jurnal Inovasi Kebijakan IKRA-ITH ABDIMAS MEANS (Media Informasi Analisa dan Sistem) Patria : Jurnal Pengabdian Kepada Masyarakat Journal of Applied Data Sciences Jurnal Penelitian Inovatif Jurnal Teknik Informatika Unika Santo Thomas (JTIUST) Jurnal Pengabdian Pada Masyarakat Indonesia (JPPMI) Safari : Jurnal Pengabdian Masyarakat Indonesia J-DEPACE (Journal of Dedication to Papua Community) Jurnal Pengabdian Masyarakat Jurnal Pendidikan MIPA
Natalia Magdalena Rafu Mamulak
Universitas Katolik Widya Mandira
Religion Arts Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Health Professions Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Public Health Social Sciences Other

Published : 20 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search
Journal : Journal of Applied Data Sciences

 1 
Determining Important Features for Dengue Diagnosis using Feature Selection Methods Bria, Yulianti Paula; Nani, Paskalis Andrianus; Siki, Yovinia Carmeneja Hoar; Mamulak, Natalia Magdalena Rafu; Meolbatak, Emiliana Metan; Guntur, Robertus Dole
Journal of Applied Data Sciences Vol 6, No 1: JANUARY 2025
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v6i1.445

Abstract

This research aims to determine the important features including symptoms and risk factors for dengue diagnosis. This study’s dataset was obtained from medical records collected from two hospitals in Indonesia from patients with dengue and nondengue diseases. Four feature selection methods including feature importance, recursive feature elimination, correlation matrix and KBest were leveraged to determine significant features. Feature importance employed a tree-based classifier to derive the importance scores of the features. Recursive feature elimination employed a machine learning classifier to choose the most important features from the given dataset. Correlation matrix was employed to select the best features because it has the ability to use the correlation between each feature with the target. Univariate feature selection – Kbest has the ability to choose the best features based on univariate statistical tests. Important features were also gathered from fifteen Indonesian medical doctors to confirm the results. We used six machine learning techniques for dengue prediction. The random forest classifier yields the highest accuracy for the best combination of features with the accuracy of 0.93 (LR: 0.90 (0.04), KNN: 0.89 (0.04), XGBoost: 0.91 (0.03), RF: 0.93 (0.04), NB: 0.88 (0.09), SVM: 0.89 (0.04)) and precision of 0.90 (LR: 0.86 (0.22), KNN: 0.67 (0.14), XGBoost: 0.77 (0.13), RF: 0.90 (0.13), NB: 0.66 (0.20), SVM: 0.66 (0.18)). This study shows the significant features for dengue diagnosis including fever, fever duration, headache, muscle and joint pain, nausea, vomiting, abdominal pain, shivering, malaise, loss of appetite, shortness of breath, rash, bleeding nose, bitter mouth, temperature and age. This knowledge is pivotal to educate society to seek medical advice when dengue symptoms appear to avoid severe conditions. Arthralgia/joint pain and myalgia/muscle pain are the most significant features for the dengue prediction. This knowledge is important for medical doctors as a starting point for clinical dengue diagnosis.
Co-Authors Abineno, Richard Sanni Abineno, Richard Sanni Abineno, Richard Sanni Adri Gabriel Sooai Alfry Aristo Jansen Sinlae Alicia Herlin Mondolang Corazon Olivia Sianturi David Amfotis Donatus Joseph Manehat Dosinaeng, Wilridus Beda Nuba Emerensiana Ngaga Emerensiana Ngaga Emiliana Metan Meolbatak Frengky Tedy Guterres, Ilda Ignatius Pricher Agung Nirwanto Samane Irmina Veronika Uskono Karolina Yunita Solle Kristoforus Djawa Djong Maur, Yohanes E.H. Meolbatak, Emiliana Metan Meryani Lakapu Nahak, Paskalis F. Neang P. Atamani Paskalis Andrianus Nani Patrisius Batarius Paulina Aliandu Redy A. Lelan Robertus Dole Guntur RR. Ella Evrita Hestiandari Samuel I. Leton Shine Crossifixio Sianturi Siki, Yovinia C. H. Sisilia Daeng Bakka Mau Talo, Martinus Coreia Tangi, Hironimus Tinenti, Yanti Rosinda Yohanes Ovaritus Jagom Yosefina R. Tey Seran Yovinia Carmeneja Hoar Siki Yulianti Paula Bria Zenonisya G. Batara