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All Journal Jurnal Ekonomi, Teknologi dan Bisnis Journal of Digital Marketing and Search Engine Optimization
Al Akromi, Elok Nur Affah
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Astronomy Computer Science & IT Economics, Econometrics & Finance Engineering Industrial & Manufacturing Engineering Mechanical Engineering

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The Influence of Digital Marketing on Brand Perception among Millennials and Gen Z Al Akromi, Elok Nur Affah
Journal of Digital Marketing and Search Engine Optimization Vol. 1 No. 1 (2024): Journal of Digital Marketing and Search Engine Optimization
Publisher : Politeknik Siber Cerdika Internasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59261/jseo.v1i1.4

Abstract

Digital marketing plays a pivotal role in shaping the perceptions of brands, particularly among Millennials and Gen Z, two generations deeply embedded in the digital landscape. As these younger generations increasingly use social media for information, entertainment, and purchasing decisions, brand perception has become inextricably linked to digital engagement. This study examines how digital marketing strategies, including influencer marketing, interactive content, and personalized advertising, influence the way these generations perceive and interact with brands. Through a review of literature and case studies, this paper identifies the key factors that affect brand perception, such as content authenticity, brand values, and the use of social media influencers. Additionally, the paper highlights how brands that effectively engage Millennials and Gen Z can improve brand loyalty, customer trust, and overall business performance. Findings suggest that brands that align their messaging with the values of these generations, such as sustainability and social responsibility, are more likely to foster positive brand perceptions. However, challenges such as content saturation, evolving social media algorithms, and the need for constant innovation remain. The study concludes by offering strategic recommendations for brands looking to enhance their digital marketing efforts and create lasting relationships with these influential consumer groups.
Training the Trainer: Measuring the Long-Term Effectiveness of AI Upskilling Programs for Indonesian Educators Al Akromi, Elok Nur Affah
Jurnal Ekonomi Teknologi dan Bisnis (JETBIS) Vol. 4 No. 12 (2025): Jurnal Ekonomi, Teknologi dan Bisnis
Publisher : Al-Makki Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57185/5975rm80

Abstract

Indonesia's national artificial intelligence (AI) education roadmap (2025–2045) positions teacher AI competency as foundational to its Golden Generation vision, yet the long-term effectiveness of AI upskilling programs for Indonesian educators remains empirically unexamined. This study aims to evaluate the extent to which AI-related competencies are retained over time, identify key factors influencing sustained AI integration among teachers, and compare the effectiveness of different upskilling programs across regional contexts. This longitudinal mixed-methods study measured the durability of AI competency gains among 347 in-service K–12 teachers across urban, peri-urban, and remote regional strata over four measurement waves: pre-intervention, immediate post-intervention, six-month follow-up, and twelve-month follow-up. Participants were drawn from two nationally deployed AI upskilling programs  Platform Merdeka Mengajar (PMM) and Microsoft Elevate   and assessed using a validated four-subscale questionnaire, semi-structured interviews, and structured classroom observation checklists. Results revealed a consistent "spike-and-decay" trajectory across all groups, with teachers retaining an average of only 63.5% of post-intervention competency gains at the twelve-month wave. Microsoft Elevate participants demonstrated significantly superior retention compared to PMM participants, and remote-stratum teachers experienced the steepest decay. Post-intervention AI self-efficacy, peer collaboration frequency, and perceived program relevance emerged as the strongest predictors of sustained behavioral integration. Qualitative findings identified infrastructure deficits, institutional isolation, curricular misalignment, and confidence erosion as primary disinvestment mechanisms. The study concludes that sustainable AI teacher competency requires a systems-level response encompassing mandatory post-training support, differentiated regional resourcing, and curriculum-embedded AI learning communities.
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