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All Journal The Indonesian Journal of Computer Science
Cuatanto, Ricardo
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Computer Science & IT Electrical & Electronics Engineering Engineering

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Comparative Analysis Between Naïve Bayes Algorithm and Decision Tree Loss Rate from Fire Disaster Data in DKI Jakarta Province Cuatanto, Ricardo; Sutomo, Rudi
The Indonesian Journal of Computer Science Vol. 12 No. 4 (2023): The Indonesian Journal of Computer Science (IJCS)
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v12i4.3347

Abstract

In urban locations like DKI Jakarta Province, fire poses a severe concern. Understanding the trends and variables that affect fire risk requires analysis of fire incidence data. To assess fire data in the DKI Jakarta Province, the method uses the Decision Tree and Nave Bayes algorithms. The Decision Tree identifies the primary causes of fires, whereas Naive Bayes forecasts fire risk using weather and historical data. These two algorithms' combined outputs offer a thorough understanding of the features and causes of a fire. By educating authorities and the public on how to manage this risk, this research helps to improve fire mitigation techniques. The safety and readiness for fire disasters in this area should increase. The accuracy of the two predictions made by the Naive Bayes algorithm is 75%. In contrast, the accuracy of the Decision Tree algorithm is 78%, leading to the conclusion that the Decision Tree approach is more helpful in categorizing the severity of fire disaster losses.
Measurement of IT Governance Capabilities Using COBIT 2019 in the Indonesian Business Sector Cuatanto, Ricardo; Sutomo, Rudi
The Indonesian Journal of Computer Science Vol. 12 No. 5 (2023): The Indonesian Journal of Computer Science (IJCS)
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v12i5.3412

Abstract

The Indonesian business sector uses information technology to support private, business, and governmental decision-making. However, there are problems with IT implementation, such as a weak Business Continuity Plan, a lack of change testing procedures, and insufficient project review activities. Utilising the COBIT performance model based on COBIT 2019, this study seeks to evaluate the IT governance of the Indonesian business sector. The chosen domains are BAI05 (Managed Organizational Change), BAI06 (Managed IT Changes), and BAI07 (Managed IT Change Acceptance and Transitioning). According to the results, BAI05 scored level 2 (90.6%), BAI06 scored level 2 (80.3%), and BAI07 scored level 2 (87%) respectively. Level 3 (78%) is where BAI07 falls short and needs to be improved. Following a set timeline, recommendations will be implemented once they have been approved by SM Innovation & Digital Transformation and Manager Innovation & IT Project Management in the Indonesian Business Sector.
Co-Authors Sutomo, Rudi