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APPLICATION OF AHP TO DETERMINE CRITICAL SUCCESS FACTOR FOR OUTSOURCING AUDIO PROJECT BASED SERVICE: A CASE STUDY OF PT. SHEFAI INDONESIA Muhammad Faishal; Dina Dellyana
International Journal of Economic, Business, Accounting, Agriculture Management and Sharia Administration (IJEBAS) Vol. 5 No. 1 (2025): February
Publisher : CV. Radja Publika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54443/ijebas.v5i1.2482

Abstract

This Research provides business process model for an organization that attempts to improve outsourcing strategy in the audio services sector. This research uses the case study approach by applying the Analytical Hierarchy Process (AHP) as a means to define critical success factors in outsourcing project-based audio services at PT. Shefai Indonesia. The research identifies the following as the seven most important criteria that are likely to determine the success of outsourcing: Adequate Communication Channels, Effective Feedback, Skilled Engineers, Skilled Voice Actor Pool, Skilled Project Manager, Turnaround Time Delivery, and Information Security. The study further combines internal (SWOT) and external (PESTEL) analyses to design a complete outsourcing workflow and business structure. To solve the problem, the business process incorporates five key stages, which are supported with CSFs at at critical points to enhance efficiency, vendor collaboration, and service quality
I MAMMOGRAPHY ACCEPTANCE WITH INSIGHTS FROM PATIENT AND HEALTHCARE PROFESSIONAL USING UTAUT Aulia Dyah Hutami Kawigraha; Dina Dellyana
International Journal of Economic, Business, Accounting, Agriculture Management and Sharia Administration (IJEBAS) Vol. 5 No. 2 (2025): April
Publisher : CV. Radja Publika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54443/ijebas.v5i2.2601

Abstract

Breast cancer currently positioned as the leading cause of cancer-related mortality among women in Indonesia, highlighting the urgent need for early detection and accurate diagnosis. AI-assisted mammography is one of a potential solution to detect the cancer early and reduce radiologist workload. However, the adoption of AI mammography remains limited, due to skepticism among healthcare professionals, and a lack of patient awareness. This study aims to evaluate the acceptance of AI mammography using the Unified Theory of Acceptance and Use of Technology (UTAUT) framework, by incorporating insights from both healthcare professionals and female patients aged 30 and above. A mixed-method approach was employed, quantitative surveys from 480 women and interviews 8 healthcare professionals. The results indicate that Performance Expectancy, Effort Expectancy, Social Influence, and Facilitating Conditions significantly impact Behavioral Intention to adopt AI mammography. However, the relationship between Behavioral Intention and actual Use Behavior did not meet reliability and validity thresholds, suggesting that adoption is still in its early phase. Key barriers identified include limited AI exposure, infrastructure disparities, regulatory constraints, and concerns over job displacement among radiologists.