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All Journal Zonasi: Jurnal Sistem Informasi Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer) J-COSCIS : Journal of Computer Science Community Service Fleksibel: Jurnal Pengabdian Kepada Masyarakat The Indonesian Journal of Computer Science
Fajrizal
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Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering Environmental Science Languange, Linguistic, Communication & Media Library & Information Science Social Sciences Transportation

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Journal : The Indonesian Journal of Computer Science

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Feature Selection in Naïve Bayes for Predicting ICU Needs of COVID-19 Patients Taslim, Taslim Malano; fajrizal; Handayani, Susi; Toresa, Dafwen
The Indonesian Journal of Computer Science Vol. 12 No. 3 (2023): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v12i3.3211

Abstract

COVID-19 is a global pandemic that requires a coordinated global response in all healthcare and national healthcare systems. Identifying patients at high risk of contracting the COVID-19 virus is crucial to increasing awareness before patients become further infected by the virus, which can cause severe respiratory illnesses requiring specialized care in intensive care units (ICUs). This study aims to predict the need for ICUs in patients infected with the COVID-19 virus. The predicted ICU requirements serve as a reference for hospitals to meet the ICU needs of COVID-19 patients. The prediction of ICU requirements for COVID-19 patients is performed using the Naïve Bayes algorithm, and particle swarm optimization (PSO) used to obtain the best accuracy values from Naïve Bayes. In the initial testing, Naïve Bayes without feature selection resulted in an accuracy rate of 74.75%. Testing Naïve Bayes+PSO by increasing the number of PSO generations shows that as the number of generations in PSO increases, the accuracy rate also increases. Testing Naïve Bayes+PSO with 3000 generations and a population size of 20 shows an increase in the accuracy rate to 80.95%. Testing Naïve Bayes+PSO by increasing the population size to 40 with 1000 generations for each population size shows an increase in the accuracy rate to 80.70%.
Optimasi Nilai K Pada Algoritma k-Means untuk Klasterisasi Data Pasien Covid-19 Moh. Fatkuroji; Fajrizal; Taslim; Eka Sabna; Kursiah Warti Ningsih
The Indonesian Journal of Computer Science Vol. 11 No. 2 (2022): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v11i2.3088

Abstract

With the spread of Covid-19 to various countries, it is difficult for Governments and Health Agencies in the world to handle Covid-19 cases to date. The prevention carried out by the Government and Health Agencies in the world is carried out by giving vaccines to the public. However, in some places it is not implemented in accordance with PMK Number 84 of 2020 which prioritizes providing vaccines to the elderly. With the current density of the population in Indonesia, the administration of vaccines does not see who is prioritized first. The application of the k-means algorithm is carried out to cluster patients affected by Covid-19 on the Covid-19 case data obtained from kaggle.com in the form of patient data from January 1, 2020 to May 31, 2020 as many as 139119 cases. The results of clustering data on cases affected by Covid-19 with k=3 yielded a WCSS value of 6801292.2. Calculations of the K-Means Algorithm using the Google Collaboratory Tools resulted in clusters with the cases of patients affected by Covid-19 in Cluster-0 as many as 58.237 cases, in Cluster-1 as many as 53.932 cases, and in Cluster-2 as many as 26.950 cases.  
Co-Authors Afriansyah Ahmad Zamsuri, Ahmad Anam, M Khairul Chatarina Umbul Wahyuni Fana Wiza, Fana Hardianto, Roki Lucky Lhaura Van FC, Lucky Lhaura Mhd. Arief Hasan, Mhd. Arief Moh. Fatkuroji Muhamad Sadar Musfawati Ningsih, Kursiah Warti Sabna, Eka Susi Handayani Susi Handayani Syahril Syahtriatna Djusar Taslim Taslim, Taslim Malano Toresa, Dafwen Walhidayat Yeni, Refliza Yeza Febriani Yogi Ersan Fadrial Yogi Yunefri, Yogi