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All Journal Kharisma Tech RAGAM: Journal of Statistics and Its Application
Ramadha Meisa Putra, Naufalarizqa
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Humanities Computer Science & IT Economics, Econometrics & Finance Engineering Mathematics Public Health

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PEMODELAN KUALITAS UDARA JAKARTA BERBASIS DATA MINING DENGAN ALGORITMA RANDOM FOREST, KNN, DAN NAIVE BAYES Ramadha Meisa Putra, Naufalarizqa
RAGAM: Journal of Statistics & Its Application Vol 5, No 1 (2026): RAGAM: Journal of Statistics & Its Application
Publisher : Universitas Lambung Mangkurat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20527/ragam.v5i1.18196

Abstract

Air quality prediction plays an important role in supporting public health monitoring in highly urbanized regions such as DKI Jakarta. This study aims to predict the Air Pollutant Standard Index (ISPU) category using three supervised learning algorithms, namely Random Forest, k Nearest Neighbors (kNN), and Naive Bayes, based on five pollutant parameters: PM10, SO2, CO, O3, and NO2. The dataset used in this study consists of validated daily air‑quality records that have undergone preprocessing steps including handling missing values and applying min max normalization. Model evaluation is conducted using the Test and Score feature in the Orange Data Mining software, which provides a visual programming environment for machine learning analysis. The results show that Random Forest achieves the highest performance with an accuracy of 97 percent, followed by kNN with 94 percent and Naive Bayes with 88 percent. Feature ranking using the Chi Square test indicates that PM10 is the most dominant factor influencing ISPU category with a value of 870.174, followed by O3 and NO2. These findings highlight that ensemble-based models are well suited for multiclass air quality classification and confirm that particulate matter remains a key determinant of air quality conditions in Jakarta.
EVALUASI TATA KELOLA TEKNOLOGI INFORMASI BERDASARKAN DOMAIN EDM COBIT 2019 PADA BANK XYZ Ramadha Meisa Putra, Naufalarizqa
KHARISMA Tech Vol 21 No 1 (2026): KHARISMATech Journal
Publisher : STMIK KHARISMA Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55645/kharismatech.v21i1.693

Abstract

Information technology (IT) governance plays an essential role in ensuring that the use of IT aligns with business objectives, delivers optimal value, and effectively manages risks, particularly in the banking sector. This study aims to evaluate the implementation of IT governance in the Evaluate, Direct, and Monitor (EDM) domain based on the COBIT 2019 framework at Bank XYZ. The research adopts a case study approach with an evaluative method through an assessment of the capability levels of processes EDM01 to EDM05. Data were collected through the review of IT policies and procedures, IT strategic planning documents, internal control reports, and discussions with relevant stakeholders during the observation period. The results indicate that all processes within the EDM domain have achieved capability level 4 (Managed). This finding suggests that IT governance at the top management level of Bank XYZ has been implemented in a structured, measurable, and quantitatively monitored manner. However, opportunities for further improvement remain, particularly in strengthening follow-up actions derived from IT benefits evaluation and ensuring consistent governance performance measurement across EDM processes. This study is expected to provide practical insights for enhancing strategic IT governance and to support future research on the application of the COBIT 2019 EDM domain in the banking industry.
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