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Rozi, Achmad
Universitas Primagraha, Serang, Banten, Indonesia
Religion Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Environmental Science Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Social Sciences Other

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Peran Pelatihan dan Pengembangan dalam Meningkatkan Kualitas Sumber Daya Manusia Andara, Adissya Maya; Rozi, Achmad
Jurnal Tadbir Peradaban Vol. 5 No. 1 (2025): Jurnal Tadbir Peradaban
Publisher : Prodi Manajemen STIE Hidayatullah Depok

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55182/jtp.v5i1.560

Abstract

Pelatihan dan pengembangan merupakan aspek krusial dalam meningkatkan kualitas sumber daya manusia (SDM) di suatu organisasi. Penelitian ini bertujuan untuk mengeksplorasi peran pelatihan dan pengembangan dalam meningkatkan kualitas SDM melalui pendekatan kualitatif. Fokus utama dari penelitian ini adalah untuk memahami bagaimana pelatihan dapat meningkatkan kompetensi dan motivasi karyawan serta mempengaruhi kinerja mereka dalam jangka panjang. Dalam penelitian ini, data dikumpulkan melalui wawancara mendalam dengan sejumlah karyawan dan manajer di beberapa perusahaan yang berbeda. Hasil penelitian menunjukkan bahwa pelatihan yang efektif dapat meningkatkan keterampilan teknis dan non-teknis karyawan, memperkuat kemampuan kepemimpinan, serta memperbaiki hubungan antar karyawan dalam suatu tim. Selain itu, pengembangan melalui program pelatihan juga berkontribusi pada peningkatan motivasi dan loyalitas karyawan terhadap organisasi. Temuan ini menegaskan pentingnya strategi pelatihan yang berkelanjutan dan terstruktur untuk memastikan pengembangan SDM yang optimal. Dengan demikian, perusahaan yang fokus pada pengembangan SDM dapat mencapai peningkatan kinerja yang signifikan dan berkelanjutan. Penelitian ini memberikan wawasan penting bagi pengambil kebijakan dan manajer sumber daya manusia dalam merancang program pelatihan yang lebih efektif dan sesuai dengan kebutuhan perusahaan serta karyawan.
Implementasi Sistem Penilaian Kinerja Berbasis Kompetensi dalam Organisasi Modern Sandra, Mela; Rozi, Achmad
Jurnal Tadbir Peradaban Vol. 4 No. 3 (2024): Jurnal Tadbir Peradaban
Publisher : Prodi Manajemen STIE Hidayatullah Depok

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55182/jtp.v4i3.562

Abstract

Penilaian kinerja berbasis kompetensi telah menjadi salah satu elemen penting dalam manajemen sumber daya manusia di organisasi modern. Artikel ini membahas implementasi sistem penilaian kinerja berbasis kompetensi yang diterapkan di berbagai organisasi modern untuk meningkatkan efisiensi dan efektivitas kerja karyawan. Penilaian kinerja berbasis kompetensi mengacu pada pengukuran kemampuan karyawan dalam menjalankan tugas sesuai dengan kompetensi yang diharapkan oleh organisasi, bukan hanya berdasarkan hasil kerja semata. Penerapan sistem ini diharapkan dapat meningkatkan pemahaman tentang kinerja individual dan kolektif dalam organisasi serta mendorong pengembangan profesionalisme. Penelitian ini mengidentifikasi tantangan yang dihadapi dalam implementasi sistem tersebut, seperti resistensi dari karyawan dan manajer, serta perlunya pelatihan untuk memastikan pemahaman yang tepat tentang kompetensi yang diukur. Selain itu, penelitian ini juga membahas manfaat yang dapat diperoleh oleh organisasi dalam meningkatkan kualitas kinerja dan mencapai tujuan strategis jangka panjang. Dengan pendekatan yang lebih objektif dan terstruktur, sistem penilaian berbasis kompetensi memberikan dasar yang lebih kuat dalam pengambilan keputusan terkait pengembangan karir, promosi, dan pelatihan. Secara keseluruhan, implementasi sistem ini diharapkan dapat meningkatkan kinerja organisasi secara keseluruhan melalui pemahaman yang lebih baik terhadap kebutuhan kompetensi dan pencapaian tujuan yang lebih jelas.
Utilizing Generative AI Models in Architectural Design An Innovative Approach Palupi Meilani, Yohana F. Cahya; Rohim, Rohim; Rozi, Achmad; Sunarjo, Richard Andre; Moyo, Kgomotso
Technomedia Journal Vol 10 No 2 (2025): October
Publisher : Pandawan Incorporation, Alphabet Incubator Universitas Raharja

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/wg15r798

Abstract

In the context of modern architectural design that demands innovation, speed, and efficiency, the emergence of generative artificial intelligence (AI) introduces a new paradigm in the creative process. This technology enables architects to explore design ideas more rapidly and extensively through diffusion-based algorithms capable of producing complex architectural visuals in a short amount of time. This study aims to empirically evaluate the effectiveness and efficiency of generative AI models, particularly Stable Diffusion v2.1, in supporting the stages of ideation, sketching, and architectural modeling. The research employs both qualitative and quantitative approaches through a comparative experiment between manual design and AI-assisted design. Measurements were conducted using four main parameters: production time, visual complexity, rendering sharpness, and the number of design iterations. The results indicate that the generative AI model can accelerate production time by up to 35% greater efficiency compared to the manual method. Furthermore, the Visual Complexity Score (VCS) reached 8.5/10 for AI-generated designs and 6.2/10 for manual ones, with an increase in rendering resolution up to 450 PPI. However, limitations were observed in semantic interpretation and the model’s dependence on well-crafted prompts. This study concludes that the integration of generative AI in architectural design not only enhances the efficiency and effectiveness of the design process but also expands the creative potential of architects. The research contributes to the development of sustainable digital architecture and supports the achievement of SDG 9 (Industry, Innovation, and Infrastructure) and SDG 11 (Sustainable Cities and Communities). 
KEPUASAN KERJA SEBAGAI MODERASI ETIKA KERJA DAN BUDAYA ORGANISASI TERHADAP KINERJA KARYAWAN Sunarni, Sunarni; Br. Ginting, Helmina; Asbullah, M.; Sucipto, Bambang; Rozi, Achmad
JURNAL ILMIAH EDUNOMIKA Vol. 8 No. 1 (2024): EDUNOMIKA
Publisher : ITB AAS Indonesia Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29040/jie.v8i1.11091

Abstract

Kinerja karyawan merupakan hasil kerja yang dicapai seseorang ketika menyelesaikan tugas yang dilimpahkan kepadanya dan bergantung pada keterampilan, pengalaman, keseriusan, dan waktu. Penelitian ini bertujuan untuk mengetahui pengaruh etika kerja dan budaya organisasi terhadap kinerja karyawan dengan kepuasan kerja sebagai moderasi. Analisis saat ini menggunakan pendekatan kuantitatif. Metodologi pengumpulan data yang digunakan melibatkan pengiriman kuesioner yang telah menerima sekitar 160 tanggapan responden. Dalam penelitian ini, partisipan yang paling umum adalah pekerja di kantor yang tersebar di Indonesia, dan metode analisisnya menggunakan software Smart PLS. Hasil penelitian menunjukan bahwa etika kerja dan budaya organisasi berpengaruh terhadap kinerja karyawan, dan kepuasan kerja sebagai moderasi mampu memoderasi etika kerja dan budaya organisasi terhadap kinerja karyawan. Kata Kunci: Kinerja Karyawan, Etika Kerja, Budaya Organisasi, Kepuasan Kerja
Life Cycle Assessment of Silicon Photovoltaics and Their Environmental Impacts Aziz, Lukmanul Hakim; Callula, Brigitta; Rozi, Achmad; Madani, Muchlisina
International Transactions on Artificial Intelligence Vol. 4 No. 1 (2025): November
Publisher : Pandawan Sejahtera Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/italic.v4i1.941

Abstract

The rapid expansion of silicon based Photovoltaic (PV) technologies continues to drive the global shift toward sustainable energy systems. However, the environmental implications across the full life cycle of PV modules particularly those associated with upstream silicon purification routes remain insufficiently examined. This study provides a comprehensive assessment of the environmental and process level impacts of Metallurgical Grade Silicon (MGS) and Upgraded Metallurgical Grade Silicon (UMGS), covering extraction, manufacturing, operation, and end of life stages. A process oriented Life Cycle Assessment (LCA) is conducted to analyze variations in carbon intensity, hazardous material use, and energy demand, complemented by comparative evaluations of monocrystalline and polycrystalline module production pathways. To enhance analytical precision, this study incorporates an AI-assisted predictive modeling framework using supervised machine learning to estimate Global Warming Potential (GWP) and identify key factors influencing emission variability. The AI-enhanced model reveals that electricity mix and purification route exert the strongest influence on GWP, and scenario simulations demonstrate that UMGS based processes can reduce upstream emissions by up to 89% under favorable energy conditions. Additionally, the study highlights future challenges related to increasing PV waste volumes between 2025 and 2030 and the need for improved recycling infrastructures. Overall, the integration of AI-based prediction with conventional LCA offers a more dynamic and adaptive evaluation of PV sustainability performance. The findings underscore the importance of renewable powered manufacturing, early adoption of low-energy purification technologies, and policy support to achieve long-term environmental and socio-economic benefits.
Impact of HR Management on AI Implementation and Data Protection in Indonesian Manufacturing Achmad Rozi; Junengsih Junengsih; Surya Alam; Avinash Pawar; Wahid Sumarjo; Denok Sunarsi
International Journal of Cyber ​​and IT Service Management (IJCITSM) Vol. 6 No. 1 (2026): April
Publisher : International Institute for Advanced Science & Technology (IIAST)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34306/ijcitsm.v6i1.226

Abstract

This study aims to analyze the influence of Human Resource Management (HRM) strategies on the implementation of Artificial Intelligence (AI) in industrial forecasting and data protection within the cybersecurity era in Indonesian manufacturing companies. A quantitative approach was used with a survey method to collect data from 96 employees of manufacturing companies in Indonesia, determined by the Lemeshow formula. The findings show that HRM strategy has a positive and significant effect on industrial forecasting, with a t-statistic of 48.639 > 1.984 and a P-value of 0.000 < 0.05. Furthermore, HRM strategy significantly affects data protection, with a t-statistic of 27.927 > 1.984 and a P-value of 0.000 < 0.05. Industrial forecasting positively influences AI implementation, with a t-statistic of 27.927 > 1.984 and a P-value of 0.000 < 0.05, while data protection also positively affects AI implementation, supported by a t-statistic of 2.457 > 1.984 and a P-value of 0.014 < 0.05. Additionally, HRM strategy significantly influences AI implementation, with a t-statistic of 6.020 > 1.984 and a P-value of 0.000 < 0.05. Finally, HRM strategy positively impacts AI implementation through data protection, indicated by a t-statistic of 2.421 > 1.984 and a P-value of 0.016 < 0.05. In conclusion, this study highlights the importance of HRM strategies in enhancing AI implementation and cybersecurity in Indonesian manufacturing companies, underscoring the need for integrating HR strategies with AI and data protection systems to optimize operational efficiency and safeguard against cyber threats.
Co-Authors Agus Salim Alam, Surya Andara, Adissya Maya Asbullah, M. Avinash Pawar Ayu Puspitasari, Ayu Azhar Affandi Aziz, Lukmanul Hakim Br. Ginting, Helmina Callula, Brigitta Denok Sunarsi Denok Sunarsi Didit Haryadi Dodi Ilham Erlangga, Heri Evita Yuliatul Wahidah Firdaus, Abdurrahman Haerofiatna Hariyaty Ab Wahid HERMAWATI, RAHMI Iqbal Maulana Ivana, Melda Junengsih Junengsih M. Said Saggaf Madani, Muchlisina Mela Sandra Moh. Toriqul Chaer Moyo, Kgomotso Nurjaya Nurjaya Pahmi, Achmad Palupi Meilani, Yohana F. Cahya Rufi'i Setyowati, Ani Siti Rohaya Siti Rohaya Sucipto, Bambang Sunarjo, Richard Andre Sunarni Sunarni Sunarsi, Denok Supriatno, Eko Surya Alam Suryani, N Lilis Suwanto Suwanto Wahid Sumarjo Wahyudi Wahyudi