Article Per Year (5 Year)
p-Index From 2021 - 2026
0.61
P-Index
This Author published in this journals
All Journal JSITP IT-Explore: Jurnal Penerapan Teknologi Informasi dan Komunikasi Journal Of Informatics And Busisnes
Novaldi, Alexander
Unknown Affiliation
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance

Published : 3 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 3 Documents
Search

 1 
Perancangan Data Warehouse Menggunakan Model Star Schema untuk Analisis Penjualan Retail Berbasis PostgreSQL Wijaya, Andri; Novaldi, Alexander
Journal Of Informatics And Busisnes Vol. 3 No. 3 (2025): Oktober - Desember
Publisher : CV. ITTC INDONESIA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47233/jibs.v3i3.3759

Abstract

The retail industry faces significant challenges in managing massive transaction data volumes. Reliance on operational systems (OLTP) often hinders complex historical data analysis. This study aims to design and implement a Data Warehouse using the Star Schema approach to support efficient retail sales analysis. Utilizing the Sample Superstore dataset, the development follows Kimball’s methodology with technical ETL implementation on PostgreSQL. The research produced a Star Schema architecture consisting of one fact table and five dimension tables. Validation testing confirmed complete data integrity during migration. The results demonstrate the system's capability to present rapid multidimensional insights, including positive annual sales trends and profitability disparities across product categories. This implementation proves that PostgreSQL effectively serves as a robust infrastructure for business intelligence, providing a solid foundation for strategic management decision-making.
Klasifikasi resiko Diabetes Mengunakan Algoritma Decision Tree Stefanus Charles Selvianto; Novaldi, Alexander; Wijaya, Andri
Jurnal Sistem Informasi dan Teknologi Peradaban Vol. 6 No. 2 (2025): jurnal Sistem Informasi dan Teknologi Peradaban
Publisher : Prodi Sistem Informasi Universitas Peradaban

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58436/jsitp.v6i2.2485

Abstract

Abstrak Peningkatan kasus Diabetes Mellitus menuntut adanya metode deteksi dini yang efektif untuk mencegah komplikasi serius pada penderita. Penelitian ini bertujuan mengklasifikasikan risiko diabetes menggunakan algoritma Decision Tree yang mampu menghasilkan aturan keputusan yang mudah diinterpretasikan oleh tenaga medis. Penelitian memanfaatkan dataset Pima Indians Diabetes dari repositori UCI Machine Learning yang diolah menggunakan perangkat lunak RapidMiner. Melalui tahapan preprocessing dan pembagian data latih serta uji dengan rasio 80:20, model dievaluasi menggunakan Confusion Matrix dan kurva ROC. Hasil pengujian menunjukkan model mencapai akurasi 70.13%, presisi 70.00%, recall 25.93%, dan nilai AUC sebesar 0.736 (fair performance). Meskipun nilai recall rendah mengindikasikan keterbatasan sensitivitas, tingginya nilai presisi menunjukkan model sangat andal dalam meminimalkan kesalahan diagnosis positif palsu. Secara spesifik, model menemukan aturan klinis bahwa kadar glukosa di atas 127.5 mg/dL merupakan indikator risiko tinggi, diikuti oleh Body Mass Index (BMI) dan usia sebagai faktor determinan sekunder pada pasien dengan gula darah normal. Penelitian ini menyimpulkan bahwa metode Decision Tree efektif digunakan sebagai sistem pendukung keputusan medis berbasis aturan (rule-based decision support) untuk identifikasi profil risiko pasien.
Analisis manajemen resiko teknologi informasi pada rumah sakit menggunakan framework Cobit 5.0 domain APO12 Novaldi, Alexander; M Raka Nurhabibi; S Charles Selvianto; Sri Andayani
IT Explore: Jurnal Penerapan Teknologi Informasi dan Komunikasi Vol 5 No 1 (2026): IT-Explore Februari 2026
Publisher : Fakultas Teknologi Informasi, Universitas Kristen Satya Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24246/itexplore.v5i1.2026.pp11-25

Abstract

ABSTRACT The implementation of Information Technology at XYZ Hospital serves as a key driver in enhancing the efficiency of healthcare services, but it also raises the organization’s vulnerability to significant operational risks. The primary risks identified involve inaccurate data resulting from human mistakes, breakdowns in system interoperability, and the deterioration of hardware infrastructure that may interfere with patient care. This research seeks to assess the governance of IT risk management and determine the organization’s capability level using the COBIT 5.0 framework, focusing on the APO12 (Manage Risk) domain. The study employs qualitative methods, gathering information through interviews and direct observations, and then conducts a gap analysis to compare the current state (As-Is) with the desired future state (To-Be). Findings show that the organization’s capability is currently at Level 2 (Managed Process) with a score of 1.87, which is still below the intended maturity level of 3 (Established Process) at 2.94. These results indicate that risk management activities are still largely reactive and rely on intuition, with no standardized procedures embedded within the institution. Ultimately, the study suggests formalizing a Risk Register, standardizing mitigation procedures through established SOPs, and developing a Disaster Recovery Plan to strengthen risk governance into a more systematic, preventive, and resilient framework.
Co-Authors Andri Wijaya M Raka Nurhabibi S Charles Selvianto Sri Andayani Stefanus Charles Selvianto