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Evaluating Public Service Innovation Using Digital Transformation, Transparency, and Citizen Satisfaction Across Government Administrative Institutions Ady Setiawan; Muchayatin Muchayatin; Fajar Surahman; Faizah Julina
Mandalika Journal of Business and Management Studies Vol 4 No 2 (2026): Mandalika Journal of Business and Management Studies
Publisher : Mandalika Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59613/mjbms.v4i2.510

Abstract

Public service innovation has become a strategic priority for governments seeking to improve service quality, strengthen accountability, and enhance citizen-oriented governance. This study aims to evaluate public service innovation across government administrative institutions through three key dimensions: digital transformation, transparency, and citizen satisfaction. The research employed a qualitative approach using library research, drawing upon relevant literature on public sector innovation, digital government, transparency, accountability, and citizen satisfaction. The analysis was conducted through qualitative content analysis and thematic synthesis of selected scholarly sources. The findings indicate that digital transformation plays a crucial role in improving service efficiency, accessibility, and responsiveness, while transparency strengthens accountability, public trust, and institutional legitimacy. Furthermore, citizen satisfaction emerges as a key indicator for assessing the effectiveness of public service innovation and the extent to which public services meet citizens’ expectations. Based on the literature synthesis, the study proposes an integrated conceptual framework that positions digital transformation, transparency, and citizen satisfaction as the primary dimensions for evaluating public service innovation. The study contributes to the public administration literature by offering a holistic perspective that integrates technological and governance dimensions in the assessment of innovation performance within government institutions. Future research is encouraged to empirically validate the proposed framework across different administrative contexts.
Systematic Literature Review: Peran Machine Learning dalam Manajemen Sumber Daya Manusia Agus Purbo Widodo; Ady Setiawan
OPTIMAL Jurnal Ekonomi dan Manajemen Vol. 5 No. 4 (2025): Desember OPTIMAL: Jurnal Ekonomi dan Manajemen
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/optimal.v5i4.8089

Abstract

The Industrial Revolution 4.0 has driven the integration of technology across various sectors, including the application of machine learning (ML) in Human Resource Management (HRM). This technology offers significant potential for improving the efficiency and effectiveness of HR management. This study, conducted using a systematic literature review (SLR), aims to examine the potential, driving and inhibiting factors, and impact of machine learning implementation in HRM. The results show that the application of ML in HRM offers significant benefits, including accelerating and improving the accuracy of the recruitment process, predicting employee turnover rates, providing appropriate training recommendations for employees, and evaluating and personalizing HR performance. Machine learning also plays a role in supporting more informed strategic decision-making. Factors driving ML implementation include the need for accurate decision-making, processing large amounts of data, and higher operational efficiency. However, several challenges hinder its implementation, such as data privacy and security concerns, potential bias in algorithms, high implementation costs, and corporate cultural resistance to change. Despite these challenges, the positive impact of machine learning implementation is significant, particularly in transforming the role of HRD to become more strategic, increasing efficiency and accuracy, and accelerating the completion of administrative work. However, the application of this technology also carries risks, such as data privacy breaches, discrimination due to algorithmic bias, and resistance within corporate cultures that hinder the adoption of new technologies. Therefore, while machine learning offers significant potential, its implementation in HR must be undertaken cautiously, with proper risk management to maximize its benefits and minimize potential negative impacts.
Peranan Kepala Sekolah dalam Meningkatkan Kinerja Sumber Daya Manusia di SMAN 1 Bululawang Kabupaten Malang Iwan Agus Famuji; Rukin Rukin; Ady Setiawan
Jurnal Ilmu Manajemen, Ekonomi dan Kewirausahaan Vol. 5 No. 2 (2025): Juli : Jurnal Ilmu Manajemen, Ekonomi dan Kewirausahaan
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/jimek.v5i2.6128

Abstract

This study examines the influence of school leadership on improving the quality of human resources within educational institutions by implementing character- and environment-focused programs, specifically the Adiwiyata School initiative. Employing a qualitative methodology, data were gathered through interviews, observations, and document analysis across several schools participating in the program. The results reveal that transformational leadership plays a critical role in motivating teachers and staff to enhance their professional skills and adopt innovative teaching approaches rooted in environmental stewardship and national character values. Additionally, active collaboration between schools and local communities emerges as a key factor contributing to the program’s effectiveness. The Adiwiyata School program not only fosters heightened environmental consciousness but also cultivates a school culture dedicated to developing student character. The study concludes that effective leadership in human resource management and school governance is essential for fostering sustainable, positive transformation, particularly within the evolving educational landscape influenced by digital advancements and pandemic challenges. These findings provide valuable insights for formulating adaptive and sustainable policies and management strategies in education.