Article Per Year (5 Year)
p-Index From 2021 - 2026
0.23
P-Index
This Author published in this journals
All Journal Proceeding of the Electrical Engineering Computer Science and Informatics JOT
Dewi Khairani
Syarif Hidayatullah State Islamic University
Computer Science & IT Electrical & Electronics Engineering

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
Analysis of Statement Branch and Loop Coverage in Software Testing with Genetic Algorithm Rizal Broer Bahaweres; Khoirunnisya Zawawi; Dewi Khairani; Nashrul Hakiem
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 4: EECSI 2017
Publisher : IAES Indonesia Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (615.883 KB) | DOI: 10.11591/eecsi.v4.1049

Abstract

Software testing is one important aspect of the software development process. About 50% of the time and cost in the software development process used for software testing process. There are two methods of software testing, black-box testing and white-box testing. This research using white-box testing. Software testing can be done manually or automatically. Based on research conducted, genetic algorithm has been widely implemented in software testing, such as test data generator. The purpose of this study is to apply a genetic algorithm in software testing and comparing the results with manual testing, automated, and automated with genetic algorithm. The test parameters are coverage measurements (statement, branch and loop coverage) and the time of testing. The conclusion of this study is automated testing with genetic algorithm requires fewer time and test cases to achieve coverage of 100%
Human Centered Artificial Intelligence Through GDPR Compliant Data Science Workflow Implementation Nuke Puji Lestari Santoso; Dewi Khairani; Siti Ummi Masruroh; Agung Rizky; Aman Jaiswal
Journal of Orange Technology Vol. 3 No. 1 (2026): October
Publisher : Sinar Mentari Sundara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.68012/jot.v3i1.96

Abstract

The rapid advancement of Artificial Intelligence (AI) and data science technologies has transformed organizational decision-making across healthcare, finance, and digital services. Despite these advancements, the increasing use of personal data has intensified concerns regarding privacy, transparency, ac countability, and public trust. Building trustworthy Human-Centered AI requires data science workflows that integrate regulatory compliance, ethical principles, and responsible governance throughout the AI lifecycle. This study aims to examine how GDPR-compliant data science workflow implementation supports the development of trustworthy Human-Centered AI through a qualitative and practice-oriented research approach. The study synthesizes evidence from recent literature, industry case studies, expert perspectives, and governance oriented analytical frameworks to identify effective strategies for integrating privacy by design, data minimization, transparency, accountability, and privacy-preserving techniques, including anonymization, pseudonymization, and differential privacy, into data science workflows. The findings indicate that successful implementation depends not only on technical safeguards but also on strong organizational governance, continuous compliance monitoring, and cross-functional collaboration among legal, technical, and managerial stakeholders. Furthermore, the integration of explainable and governance-aware machine learning models improves transparency, strengthens stakeholder trust, and supports responsible human-centered AI without significantly reducing analytical performance. This study proposes a structured GDPR-compliant data science workflow framework that enables organizations to balance analytical effectiveness, regulatory compliance, and human-centered principles while fostering trustworthy, transparent, and sustainable Artificial Intelligence for real-world digital innovation.
Co-Authors Agung Rizky Aman Jaiswal Khoirunnisya Zawawi Nashrul Hakiem Nuke Puji Lestari Santoso Rizal Broer Bahaweres Siti Ummi Masruroh