Article Per Year (5 Year)
p-Index From 2020 - 2025
0
P-Index
This Author published in this journals
All Journal Bulletin of Electrical Engineering and Informatics Bulletin of Electrical Engineering and Informatics Bulletin of Electrical Engineering and Informatics Indonesian Journal of Electrical Engineering and Computer Science
Nilam Nur Amir Sjarif
Universiti Teknologi Malaysia
Computer Science & IT Electrical & Electronics Engineering Engineering

Published : 4 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 4 Documents
Search

 1 
Mobile Business Intelligence Acceptance Model for Organisational Decision Making Lim Yee Fang; Nurulhuda Firdaus Mohd Azmi; Yazriwati Yahya; Haslina Sarkan; Nilam Nur Amir Sjarif; Suriayati Chuprat
Bulletin of Electrical Engineering and Informatics Vol 7, No 4: December 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (286.339 KB) | DOI: 10.11591/eei.v7i4.1356

Abstract

Mobile Business Intelligence (BI) is the ability to access BI-related data such as key performance indicators (KPIs), business metric and dashboard through mobile device. Mobile BI addresses the use-case of remote or mobile workers that need on-demand access to business-critical data. User acceptance on mobile BI is an essential in order to identify which factors influence the user acceptance of mobile BI application. Research on mobile BI acceptance model on organizational decision-making is limited due to the novelty of mobile BI as newly emerged innovation. In order to answer gap of the adoption of mobile BI in organizational decision-making, this paper reviews the existing works on mobile BI Acceptance Model for organizational decision-making. Two user acceptance models which are Technology Acceptance Model and Technology Acceptance Model for Mobile Services will be review. Realizing the essential of strategic organizational decision-making in determining success of organizations, the potential of mobile BI in decision-making need to be explore. Since mobile BI still in its infancy, there is a need to study user acceptance and usage behavior on mobile BI in organizational decision-making. There is still opportunity for further investigate the impact of mobile BI on organizational decision-making.
Mobile Business Intelligence Acceptance Model for Organisational Decision Making Lim Yee Fang; Nurulhuda Firdaus Mohd Azmi; Yazriwati Yahya; Haslina Sarkan; Nilam Nur Amir Sjarif; Suriayati Chuprat
Bulletin of Electrical Engineering and Informatics Vol 7, No 4: December 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (286.339 KB) | DOI: 10.11591/eei.v7i4.1356

Abstract

Mobile Business Intelligence (BI) is the ability to access BI-related data such as key performance indicators (KPIs), business metric and dashboard through mobile device. Mobile BI addresses the use-case of remote or mobile workers that need on-demand access to business-critical data. User acceptance on mobile BI is an essential in order to identify which factors influence the user acceptance of mobile BI application. Research on mobile BI acceptance model on organizational decision-making is limited due to the novelty of mobile BI as newly emerged innovation. In order to answer gap of the adoption of mobile BI in organizational decision-making, this paper reviews the existing works on mobile BI Acceptance Model for organizational decision-making. Two user acceptance models which are Technology Acceptance Model and Technology Acceptance Model for Mobile Services will be review. Realizing the essential of strategic organizational decision-making in determining success of organizations, the potential of mobile BI in decision-making need to be explore. Since mobile BI still in its infancy, there is a need to study user acceptance and usage behavior on mobile BI in organizational decision-making. There is still opportunity for further investigate the impact of mobile BI on organizational decision-making.
Mobile Business Intelligence Acceptance Model for Organisational Decision Making Lim Yee Fang; Nurulhuda Firdaus Mohd Azmi; Yazriwati Yahya; Haslina Sarkan; Nilam Nur Amir Sjarif; Suriayati Chuprat
Bulletin of Electrical Engineering and Informatics Vol 7, No 4: December 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (286.339 KB) | DOI: 10.11591/eei.v7i4.1356

Abstract

Mobile Business Intelligence (BI) is the ability to access BI-related data such as key performance indicators (KPIs), business metric and dashboard through mobile device. Mobile BI addresses the use-case of remote or mobile workers that need on-demand access to business-critical data. User acceptance on mobile BI is an essential in order to identify which factors influence the user acceptance of mobile BI application. Research on mobile BI acceptance model on organizational decision-making is limited due to the novelty of mobile BI as newly emerged innovation. In order to answer gap of the adoption of mobile BI in organizational decision-making, this paper reviews the existing works on mobile BI Acceptance Model for organizational decision-making. Two user acceptance models which are Technology Acceptance Model and Technology Acceptance Model for Mobile Services will be review. Realizing the essential of strategic organizational decision-making in determining success of organizations, the potential of mobile BI in decision-making need to be explore. Since mobile BI still in its infancy, there is a need to study user acceptance and usage behavior on mobile BI in organizational decision-making. There is still opportunity for further investigate the impact of mobile BI on organizational decision-making.
Metrics and Benchmarks for Empirical and Comprehension Focused Visualization Research in the Sales Domain Loo Yew Jie; Doris Hooi-Ten Wong; Zarina Mat Zain; Nilam Nur Amir Sjarif; Roslina Ibrahim; Nurazean Maarop
Indonesian Journal of Electrical Engineering and Computer Science Vol 12, No 3: December 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v12.i3.pp1340-1348

Abstract

Data visualization is an effort which aims to communicate data effectively and clearly to the audience through graphicalrepresentation. Data visualization efforts must be coordinated with an understanding into the Cognitive Learning Theory (CLT). In the sales domain, sales data visualization are made possible with the available Business Intelligence (BI) tools such as Microsoft Power BI, Tableau, Plotly, and others. These tools allow seamless interaction for the top management as well as the sales force with regard to the data. Sales data visualization comes with an array of advantages such as self-service analysis by business users, rapidly adapt to changing business conditions, and enable continuous on-demand reporting among others. The advantages of sales data visualization also comes with the challenges such as difficulty in identifying visual noise, high rate of image change, and high performance requirements. In an effort to reduce cognitive activity that does not enhance learning, sales visualization dashboard must be designed in a way that is neithertoo simplistic nor too complex to ensure that the Intrinsic Cognitive Load (ICL), Extrinsic Cognitive Load (ECL), and Germane Cognitive Load (GCL) are in sync with the audience. With the combination of sales data visualization and CLT, understanding complex sales details quickly is made possible by not only the top management of the organization, but also the sales force of the organization.
Co-Authors Doris Hooi-Ten Wong Haslina Sarkan Lim Yee Fang Loo Yew Jie Nurazean Maarop Nurulhuda Firdaus Mohd Azmi Roslina Ibrahim Suriayati Chuprat Yazriwati Yahya Zarina Mat Zain