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All Journal Bulletin of Electrical Engineering and Informatics Journal of Information Systems and Informatics Jurnal Nasional Teknik Elektro dan Teknologi Informasi
Prihanto Ngesti Basuki
Universitas Kristen Satya Wacana
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Energy Engineering

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Analysis of Information Technology Governance Using the COBIT 5 Framework (Case Study: E-Legal Drafting Legal Section of the Regional Secretariat of Salatiga City) Caecilia Ika Pramita Ady; Prihanto Ngesti Basuki; Augie David Manuputty
Journal of Information System and Informatics Vol 1 No 2 (2019): Journal of Information Systems and Informatics
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33557/journalisi.v1i2.17

Abstract

Information Technology (IT) governance is used to manage and optimize IT resources in supporting organizational goals. The Legal Section of the Regional Secretariat of Salatiga City as part of a government organization has built E-Legal Drafting information system to develop the functions of making regional legal products as well as the realization of e-government development in the legal field. The COBIT framework supports IT governance by providing work support to regulate IT alignment with the organization's business objectives. The results of this study are expected to show an overview of the implementation of IT governance in E-Legal Drafting information system from APO domain within the COBIT 5 framework, show the current system information level of capability and performance that is obtained from the measurement of capability levels, and also providing evaluation and recomendation based on the results of the gap analysis to help obtain the quality of information systems expected by the Legal Section of the Regional Secretariat of Salatiga City.
Analisis Kinerja Sistem Informasi pada PT. Bank Central Asia Menggunakan IT Balanced Scorecard Achmad Fikri Syarif Mail; Prihanto Ngesti Basuki; Agustinus Fritz Wijaya
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 7 No 1: Februari 2018
Publisher : Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (852.621 KB)

Abstract

PT. Bank Central Asia (BCA) is the biggest private bank in Indonesia. It always offers various banking solutions which address customers’ financial needs. Through various high quality and targeted products and services, BCA financial solution supports personal financial planning and customers’ business development. KlikBCA Individual (KBI) is one of the services that BCA offers to enable customers have practical, safe, and easy banking transaction. Therefore, a thorough measurement of Information System (IS)/Information Technology (IT) application performance from several aspects toward this innovation is needed. It measures how good the service is for both company and customers. The methodology used in this research is IT Balanced Scorecard. The result shows that the highest perspective is the company contribution as much as 19.33%, followed by the future perspective as much as 19%, the user orientation perspective as much as 18.8%, and the last is operationalization perspective as much as 14.58%. The final result is 71.71%, which indicates that it has reached a good level.
Improving genomic classification via Pearson-based SNP selection: a comparison of k-NN, SVM, and random forest Prihanto Ngesti Basuki; Sri Yulianto Joko Prasetyo; Adi Setiawan
Bulletin of Electrical Engineering and Informatics Vol 15, No 1: February 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v15i1.9087

Abstract

Accurate genomic classification is vital for precision health and population studies, yet high-dimensional single-nucleotide polymorphism (SNP) data (pn) amplify noise, redundancy, and overfitting. This study evaluates a simple, model-independent Pearson-based selection that ranks SNPs by feature–label correlation, and assesses k-nearest neighbors (k-NN), linear support vector machine (SVM), and random forest (RF) under leakage-free stratified Monte Carlo cross-validation (MCCV). Performance increases monotonically with |r|: the strongest tiers reach ?99–100% accuracy; SVM leads in mid tiers (RF second), while k-NN is competitive mainly at the extremes. A matched-dimensionality PCA-120 baseline (TRAIN-only) attains parity for SVM/RF and trails slightly for k-NN at the 10% test size. With 120-SNP panels, prediction medians are ?0.30 ms (SVM), 1.81–1.83 ms (k-NN), and 34–35 ms (RF), supporting CPU-only deployment. A consensus panel combining correlation evidence with principal component analysis (PCA) selection frequency yields interpretable Top-20/Top-120 subsets and |r|-based operating thresholds. Overall, Pearson-based selection provides a transparent, reproducible baseline for small-sample SNP classification, offering accuracy competitive with PCA at lower computational complexity and straightforward extensions to broader cohorts and multi-omics integration.
Co-Authors Achmad Fikri Syarif Mail Adi Setiawan Agustinus Fritz Wijaya Augie David Manuputty Caecilia Ika Pramita Ady Sri Yulianto Joko Prasetyo