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All Journal Bulletin of Electrical Engineering and Informatics JOIV : International Journal on Informatics Visualization
Jusoh, Yusmadi Yah
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Computer Science & IT Electrical & Electronics Engineering

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Sustainability dimensions in enhancing the energy and resource efficiency of big data systems D/O Arunachalam, Aishwharya Raani; Jusoh, Yusmadi Yah; Abdullah, Rusli; Umarova, Zhanat; Akhmetova, Sabira; Iztayev, Zhalgasbek; Zhumatayev, Nurlybek
Bulletin of Electrical Engineering and Informatics Vol 13, No 6: December 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v13i6.8052

Abstract

Big data systems are essential for many businesses to grow, leveraging the vast amounts of data they generate and access. However, big data systems are plagued by significant sustainability challenges. Thus, this study aims to identify metrics that can measure the sustainability of big data systems. This research conducted a comprehensive literature review to identify five key sustainability dimensions: technical, environmental, economic, social, and individual. Then, a set of 29 metrics corresponding to these dimensions was developed. To ensure the relevance and applicability of these metrics, an expert validation session was carried out with five experts in the big data field. The validation process confirmed the appropriateness of our proposed metrics and modification take place. The findings of this study present 30 metrics upon experts’ validation that could enhance the sustainability of big data systems, offering meaningful insights for researchers and practitioners aiming to enhance resource and energy efficiency in this domain.
Validating a Quality Model through Expert Review for Green Information Systems Muhammad, Shireen; Jusoh, Yusmadi Yah; Haizan Nor, Rozi Nor; Jussupbekova, Gulzat Tyrysbekovna; Baidibekova, Aidin Orisbayevna
JOIV : International Journal on Informatics Visualization Vol 8, No 4 (2024)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.8.4.3648

Abstract

Software developers use a quality model as a guide to help them determine the quality factors of a software product they are designing. This study aims to validate a quality model for green information systems, or green IS, towards achieving eco-sustainability. Thus, this study aims to identify quality factors for green IS that will contribute to eco-sustainability. This study's methodology included two rounds of expert evaluation with four experts. Two strategies were deployed in each round to discover the quality factors. In the first round, the strategy was to take existing software quality factors and interpret them in the context of eco-sustainability. In the second round, existing eco-sustainability goals were adopted and clustered into categories; in this study’s context, quality factors were aligned with the eco-sustainability goals. An initial model consisting of 35 quality factors was synthesized from a green IS design framework, sustainable software, and social media literature. The experts presented and assessed the model in the first round. Thus, 18 quality factors have been selected for the next second-round review. Five quality factors— accuracy, completeness, accessibility, customization, and collaboration emerged from the second-round review. Each quality factor was aligned to the eco-sustainability sub-goals of eco-efficiency, eco-equity, and eco-effectiveness, which resulted in the development of a proposed model. The experts concluded that the revised model could be employed in a data collection survey since it closely resembles the green IS quality model for eco-sustainability.
Chatbot Adoption Model in Determining Student Career Path Development: Pilot Study Ahmed, Mohamed Hassan; Abdullah, Rusli; Jusoh, Yusmadi Yah; Azmi Murad, Masrah Azrifah
JOIV : International Journal on Informatics Visualization Vol 9, No 1 (2025)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.9.1.3798

Abstract

A career decision is incredibly essential in one's life. It shapes one's future role in society, influences professional development, and can lead to success and fulfillment. Making a sound and consistent career decision based on skills and interests is critical for personal and professional development. Since generative AI is an emerging and revolutionizing technology industry in the market, which is very good in generating contents, providing consultancies and answering questions in humanly fashion, integrating AI chatbots into the career planning process can help students to get more accurate and personalized advice for their future career. This pilot study emphasized the student’s adoption of chatbot technology for career selecting processes utilizing the extended Unified Theory of Acceptance and Use of Technology (UTAUT2) model with four additional constructs which influence the student’s career selection, namely: Perceived Student’s External Factors (PEF), Perceived Student’s Interest (PSN), Perceived Career Opportunities (PCO) and Perceived Self-Efficacy (PSF). An online survey was conducted, and 37 responses were received and analyzed. The measurement model produced a promising result, and the discriminant validity, construct reliability and validity of the model were confirmed with a Cronbach’s alpha (α) above 0.70 threshold and AVE over 0.5 cut-off for most of the constructs including the four above mentioned latent variables. However, the Price Value (PPV) and Facilitating Conditions (PFC) UTAUT2 constructs produced alpha () of 0.680 and 0.611 respectively which is still adequate since their AVE is above the 0.5 threshold. Consequently, their interpretation and conclusions should be approached with caution.
Factors Influencing Information Quality of Information Systems: A Systematic Literature Review Aziz, Azwan Abd; Haizan Nor, Rozi Nor; Jusoh, Yusmadi Yah; Wan Ab. Rahman, Wan Nurhayati; Mohd. Ali, Norhayati
JOIV : International Journal on Informatics Visualization Vol 8, No 3-2 (2024): IT for Global Goals: Building a Sustainable Tomorrow
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.8.3-2.3483

Abstract

In today's digital era, information quality in information systems is essential for organizational effectiveness and decision-making. This systematic literature review aims to assess and synthesize factors influencing information quality across various systems, focusing on key dimensions such as reliability, accessibility, usability, accuracy, completeness, and timeliness. The existing literature is fragmented, lacking an integrated theory that comprehensively addresses the significance of information quality. Thus, a systematic review was conducted following the PRISMA framework to address this gap and provide evidence-based recommendations for research and practice. Studies were identified, screened, and selected from Scopus and Web of Science. After an initial search using specific keywords, a total of 1,548 articles were found that contained specified terms or strings in various combinations. Of these, 31 studies were chosen for full review based on predefined inclusion and exclusion criteria. The analysis was organized into three primary themes: i) Core Information Quality Factors, ii) Synergizing Information Quality with System and Service Quality, and iii) Impact of Information Quality on User Satisfaction and Organizational Outcomes. The results emphasize the significant role of high information quality in enhancing user satisfaction and operational efficiency. Different industries prioritize various quality dimensions according to their specific needs. Therefore, this review elucidates the imperative function of good quality information in reinforcing information systems' proper functioning, calling for empirical studies to develop holistic frameworks that incorporate multiple dimensions and impact analysis across different domains.
Co-Authors Abdullah, Rusli Ahmed, Mohamed Hassan Akhmetova, Sabira Aziz, Azwan Abd Baidibekova, Aidin Orisbayevna D/O Arunachalam, Aishwharya Raani Iztayev, Zhalgasbek Jussupbekova, Gulzat Tyrysbekovna Masrah Azrifah Azmi Murad, Masrah Azrifah Mohd. Ali, Norhayati Muhammad, Shireen Rozi Nor Haizan Nor, Rozi Nor Umarova, Zhanat Wan Ab. Rahman, Wan Nurhayati Zhumatayev, Nurlybek