Didik Wibowo, Michelle Novia, Rarasati Nan Rumaksi, Steffany Indra Gunawan


The Coronavirus (COVID-19) outbreak has spread across the globe at such a high speed that the number of infections and deaths of people is increasing swiftly each day. Therefore, it is very important to find positive cases early for medication and control the spread of the disease. Some techniques have been tried to detect COVID-19 in several injuries, but they have limited efficiency. Here, we present application of Naïve Bayes Classifier algorithm to COVID-19 diagnosis. The algorithm only requires two probabilities in order to be executed, which are: prior probability and conditional probability. Experimental results have proven the effectiveness of NBC which could achieve a detection accuracy of more than 90%.

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Ali ZH, Ali HA (2020) QoS provisioning framework for service-oriented internet of things (IoT). Clust Comput 23:575–591

Dada E, Bassi J, Chiroma H, Abdulhamid S et al (2019) Machine learning for email spam filtering: review, approaches and open research problems. Heliyon 5(6):1–23

Hewage P, Trovati M, Pereira E, Behera A (2020) Deep learning– based effective fne–grained weather forecasting model. Pattern Anal Appl. https://doi.org/10.1007/s10044-020-00898-1

Huang C, Wang Y, Li X, Ren L et al (2020) Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China. Lancet 395(10233):497–506

Kang H, Xia L, Yan F, Wan Z et al (2020) Diagnosis of coronavirus disease 2019 (covid-19) with structured latent multi-view representation learning. IEEE Trans Med Imaging 39(8):2606–2614

Kaur G, Oberoi A (2020) Novel approach for brain tumor detection based on Naïve Bayes classification. In: Sharma N, Chakrabarti A, Balas V (eds) Data management, analytics and innovation. Advances in intelligent systems and computing (1042). Springer, Singapore, pp 451–462. https://doi.org/10.1007/978-981-32-9949-8_31

Khotimah B, Miswanto M, Suprajitno H (2020) Optimization of feature selection using genetic algorithm in Naïve Bayes classification for incomplete data. Int J Intell Eng Syst 13(1):334–343

Mansour, N. A., Saleh, A. I., Badawy, M., & Ali, H. A. (2021, January 15). Accurate detection of Covid‑19 patients based on Feature Correlated Naïve Bayes (FCNB) classification strategy (N. A. Mansour, Ed.). Accurate detection of Covid‑19 patients based on Feature Correlated Naïve Bayes (FCNB) classification strategy, 10(Ambient Intelligence and Humanized Computing), 33.

Rabie AH, Saleh AI, Abo-Al-Ez K (2015) A new strategy of load forecasting technique for smart grids. IJMTER 2(12):332–341

Rabie AH, Ali SH, Ali HA, Saleh AI (2019a) A fog based load forecasting strategy for smart grids using big electrical data. Clust Comput 22(1):241–270

Shaban W, Rabie AH, Saleh AI, Abo-Elsoud M (2020) A new COVID19 Patients Detection Strategy (CPDS) based on hybrid feature selection and enhanced KNN classifier. Knowl-Based Syst 205:1–8

Widianto Mochammad Haldi (23 December 2019) Algoritma Naive Bayes. Retrieved at 3 July 2021 from https://binus.ac.id/bandung/2019/12/algoritma-naive-bayes/

Zu Z, Jiang M, Xu P, Chen W et al (2020) Coronavirus disease 2019 (COVID-19): a perspective from China. Radiology 296(2):15–25


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