Pemodelan Regresi Logistik untuk Diagnosis Dini Infeksi Covid-19 di Indonesia

Nila Ayu Nur Roosyidah, Putu Krishnanda Supriyatna


Controlling the spread of the Covid-19 virus in Indonesia, the government continues to strive for a comprehensive 3T (Testing, Training, and Tracing) implementation. Massive testing is often constrained by several things, including cost and affordability of access. This study aims to create a model for early diagnosis of Covid-19 infection cases through several characteristic symptoms and experiences of close contact with positive patients. By using a binary logistic regression model, it was found that symptoms of anosmia, feverish symptoms, and close contact experience were significant in influencing Covid-19 infection. From the odds ratio value, it is known that anosmia is the most influential variable. Someone who has anosmia tends to be infected by 31 times compared to those who do not. Validation of the strength of the model in classifying is done by making predictions on the resulting model is good, because the measurement of each criterion of the strength of the model consists of accuracy, sensitivity, and specificity of the model both on the data testing each produces a value of 0.8 (close to 1). The area under the Receiver Operating Characteristic (ROC) curve for testing data is 0.8462, which means that the model already has good criteria for classifying.


Covid-19; Early Diagnose; Logistic Regression; Receiver Operating Characteristic

Full Text:



D. A. D. Nasution, E. Erlina, and I. Muda, “Dampak Pandemi COVID-19 terhadap Perekonomian Indonesia,” Jurnal Benefita, vol. 5, no. 2, pp. 212–224, jul 2020, doi:

Anonim, “Covid-19,” Satuan Tugas Penanganan COVID-19, 2020.

Komisi-IX, “Penurunan Harga Tes PCR Tak Selesaikan Masalah,” Dewan Perwakilan Rakyat Republik Indonesia, 2021.

M. Qjidaa, Y. Mechbal, A. Ben-fares, H. Amakdouf, M. Maaroufi, B. Alami, and H. Qjidaa, “Early detection of COVID19 by deep learning transfer Model for populations in isolated rural areas,” in 2020 International Conference on Intelligent Systems and Computer Vision (ISCV). IEEE, jun 2020, pp. 1–5, doi:

A. Agustang, I. A. Mutiara, and A. Asrifan, “Genealogi Stigma Sosial Terhadap Pasien Covid 19,” OSF Preprint, 2021, doi:

D. Junaedi, M. R. Arsyad, F. Salistia, and M. Romli, “Menguji Efektivitas Vaksinasi Covid-19 di Indonesia,” Reslaj : Religion Education Social Laa Roiba Journal, vol. 4, no. 1, pp. 120–143, aug 2021, doi:

S. Brief, “Smoking and COVID-19,” World Health Organization, 2020.

A. Sultana, R. Sharma, M. M. Hossain, S. Bhattacharya, and N. Purohit, “Burnout among healthcare providers during COVID-19: Challenges and evidence-based interventions,” Indian Journal of Medical Ethics, vol. 05, no. 04, pp. 308–311, nov 2020, doi: http: //

J. Elliott, M. Whitaker, B. Bodinier, O. Eales, S. Riley, H. Ward, G. Cooke, A. Darzi,

M. Chadeau-Hyam, and P. Elliott, “Predictive symptoms for COVID-19 in the community: REACT-1 study of over 1 million people,” PLOS Medicine, vol. 18, no. 9, p. e1003777, sep 2021, doi:

D. M. N. Aditya, “Anosmia pada COVID-19: Studi Neurobiologi,” KELUWIH: Jurnal Kesehatan dan Kedokteran, vol. 2, no. 1, pp. 50–55, dec 2020, doi: kesdok.V2i1.3098.

Anonim, “Symptoms of COVID-19,” Centers for Disease Control and Prevention, 2020.

——, “how is COVID-19 transmitted,” World Health Organization, 2020.

L. Edi Nugroho and Arkham Zahri Rakhman, “Mobilitas Manusia dan Tingkat Penyebaran Covid-19: Sebuah Analisis Kuantitatif,” Jurnal Nasional Teknik Elektro dan Teknologi Informasi, vol. 10, no. 2, pp. 124–130, may 2021, doi:

M. Tirz¨ıte, M. Bukovskis, G. Strazda, N. Jurka, and I. Taivans, “Detection of lung cancer with electronic nose and logistic regression analysis,” Journal of Breath Research, vol. 13, no. 1, p. 016006, nov 2018, doi:

R. Xiao, X. Cui, H. Qiao, X. Zheng, and Y. Zhang, “Early diagnosis model of Alzheimer’s Disease based on sparse logistic regression,” Multimedia Tools and Applications, vol. 80, no. 3, pp. 3969–3980, jan 2021, doi:

C.-Y. Song, J. Xu, J.-Q. He, and Y.-Q. Lu, “COVID-19 early warning score: a multi-parameter screening tool to identify highly suspected patients,” medRxiv, 2020.

A. Agresti, Categorical Data Analysis, 3rd ed. John Wiley & Sons Inc, 2018.

V. M. Patro and M. Ranjan Patra, “Augmenting Weighted Average with Confusion Matrix to Enhance Classification Accuracy,” Transactions on Machine Learning and Artificial Intelligence, vol. 2, no. 4, pp. 77–91, aug 2014, doi:

O. N. Oyelade and A. E. Ezugwu, “A case-based reasoning framework for early detection and diagnosis of novel coronavirus,” Informatics in Medicine Unlocked, vol. 20, p. 100395, 2020, doi:


Copyright (c) 2022 Nila Ayu Nur Roosyidah, Putu Krishnanda Supriyatna

Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

Jambura Journal of Mathematics has been indexed by

>>>More Indexing<<<

Creative Commons License

Jambura Journal of Mathematics (e-ISSN: 2656-1344) by Department of Mathematics Universitas Negeri Gorontalo is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. Powered by Public Knowledge Project OJS. 

Editorial Office

Department of Mathematics, Faculty of Mathematics and Natural Science, Universitas Negeri Gorontalo
Jl. Prof. Dr. Ing. B. J. Habibie, Moutong, Tilongkabila, Kabupaten Bone Bolango, Gorontalo, Indonesia