Kosasih Kosasih
Universitas Sangga Buana YPKP, Bandung, Indonesia

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The Effect of Competence and Public Service Optimization on the Implementation Performance of the Quick Wins Program Satria Nasution; Kosasih Kosasih; Vip Paramarta; Sobarna Kartamihardja
Indonesian Interdisciplinary Journal of Sharia Economics (IIJSE) Vol 8 No 3 (2025): Sharia Economics
Publisher : Universitas KH. Abdul Chalim Mojokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31538/iijse.v8i3.7857

Abstract

Dalam era globalisasi dan perkembangan teknologi yang pesat, kompetensi Sumber Daya Manusia (SDM) menjadi faktor kunci dalam menentukan keberhasilan organisasi, termasuk dalam sektor publik, sehingga peneliti tertarik untuk melakukan penelitian. Penelitian ini bertujuan untuk mendapat bukti empirik tentang pengaruh kompetensi, optimalisasi pelayanan publik dan implementasi kinerja Quick Wins (Survey Pada Sub Direktorat Tugas Umum Direktorat Samapta Polda Jabar di Jl. Soekarno – Hatta No.748, Cimenerang, Kec. Gedebage, Kota Bandung, Jawa Barat 40613). Metode penelitian ini yang digunakan adalah analisis deskriptif verifikatif dan analisis regresi linier berganda. Pengumpulan data menggunakan kuesioner yang di sebarkan kepada seluruh karyawan dengan teknik proportional random sampling. Jumlah responden yang terkumpul sebanyak 100 orang yang mewakili personil Sub Direktorat Tugas Umum Direktorat Samapta Polda Jabar di Jl. Soekarno-Hatta No.748, Cimenerang, Kec. Gedebage, Kota Bandung, Jawa Barat 40613 yang di pilih secara acak. Hasil penelitian deskriptif menjukkan bahwa kompetensi, optimalisasi pelayanan publik dan implementasi kinerja pada umumnya tergolong baik. Hasil analisis verikatif baik secara parsial dan simultan terbukti bahwa kompetensi dan optimalisasi pelayanan berpengaruh positif dan signifikan terhadap implementasi kinerja, maka peneliti sarankan agar dipertahankan dan ditingkatkan lagi.
Artificial Intelligence in Hospital Human Resource Management: A Systematic Review and Bibliometric Analysis Kosasih Kosasih; Marisa Yesika; Fana Afizza Lustina; Efi Rusdiana; Ardio Rizky Tansil, Tan
Advances in Human Resource Management Research Vol. 4 No. 2 (2026): February - May
Publisher : Yayasan Pendidikan Bukhari Dwi Muslim

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60079/ahrmr.v4i2.776

Abstract

Purpose: This study examines research trends on the application of Artificial Intelligence (AI) in hospital human resource management (HRM) and explores its implications for employee performance and career development. Research Method: A Systematic Literature Review (SLR) and bibliometric analysis were conducted on 30 articles published between 2020 and 2025. Relevant studies were identified through a structured keyword search and screened using the PRISMA protocol. VOSviewer was employed to map research trends, thematic clusters, and keyword relationships. Results and Discussion: Our major research clusters were identified as: AI and employee performance; AI in recruitment and talent management; career development and employee engagement; and digital transformation with data analytics. Publications increased substantially after 2023, reflecting growing interest in AI-driven HRM. The literature indicates a shift from operational efficiency and automation toward strategic workforce management, data-driven decision-making, talent optimization, and sustainable career development. AI is increasingly recognized as a tool for enhancing organizational adaptability and human capital effectiveness in hospitals. Implications: Healthcare organizations should integrate AI with workforce capabilities and organizational readiness to improve employee performance and support sustainable career development. Originality: This study provides a comprehensive synthesis of AI research in hospital HRM by combining PRISMA-based review procedures with bibliometric analysis.
Implementation of the JKN Tiered Referral System: A PRISMA-Based Systematic Literature Review and Bibliometric Analysis of Healthcare Management Challenges Kosasih Kosasih; Alif Yosi Samrotul Qolbi; Annisa Dwi Ramdania Pamungkas; Muthia Isratnasari; Leoni Ester Manukiley
Advances in Human Resource Management Research Vol. 4 No. 2 (2026): February - May
Publisher : Yayasan Pendidikan Bukhari Dwi Muslim

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60079/ahrmr.v4i2.783

Abstract

Purpose: This study examines the implementation of the tiered referral system under Indonesia’s Jaminan Kesehatan Nasional (JKN) program and analyzes the dilemma between service quality and cost control from healthcare management and public policy perspectives. Research Method: This study employed a Systematic Literature Review (SLR) using the PRISMA framework, complemented by bibliometric analysis with VOSviewer. Data were drawn from national and international scientific publications published between 2020 and 2025 concerning tiered referrals, healthcare service quality, and cost efficiency under JKN. Results and Discussion: The findings show that multidimensional challenges, including limited healthcare resources, inadequate infrastructure, low patient compliance, and weak coordination across healthcare levels, hinder implementation. Bibliometric mapping indicates growing research interest and a thematic shift from service quality and cost efficiency toward patient behavior, healthcare accessibility, digital health transformation, and integrated care. The analysis confirms a persistent trade-off between improving service quality and controlling healthcare expenditure, driven by structural and managerial constraints. Implications: The study highlights the need for integrated management strategies that balance quality improvement and cost containment. Strengthening primary care, referral coordination, patient compliance, and digital health adoption is essential for JKN sustainability. Originality: This study integrates PRISMA-based SLR and bibliometric analysis to provide a comprehensive assessment of Indonesia’s JKN tiered referral system.