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All Journal Jurnal Bisnis Tani Jurnal Ilmiah Manajemen Kesatuan Jurnal Agrinika : Jurnal Agroteknologi dan Agribisnis International Journal of Eco-Innovation in Science and Engineering (IJEISE) Jurnal Ilmiah SOSIO AGRIBIS AGRIEKSTENSIA Jurnal Riset Multidisiplin : Agrisosco Prosiding Seminar Nasional Kusuma Jurnal Ilmiah Manajemen Agribisnis Sinergi Aksi Nyata Cendekia
Akbar Hariputra
Departement Of Agribussines, Faculty Of Agriculture, Universitas Pembangunan Nasional Veteran Jawa Timur, Surabaya 60294, Indonesia
Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mechanical Engineering Social Sciences Veterinary Other

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Penerapan Experiential Learning untuk Meningkatkan Kompetensi dan Refleksi Mahasiswa pada Pelatihan Mining Data Makro Intan Mega Maharani; Dita Rosyita; Aulia Nurul Hikmah; Putra Astaman; Aditya Arief Rachmadhan; Akbar Hariputra; Dita Atasa; Annisa Vira Widayanti
Sinergi Aksi Nyata Cendekia Vol 1, No 1 (2025): Agustus
Publisher : Lembaga Penelitian, Pengembangan, Pemberdayaan Potensi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.6131/sancaka.v1i1.173

Abstract

Penelitian ini bertujuan untuk menganalisis efektivitas pelatihan data mining makro berbasis experiential learning dalam meningkatkan kompetensi konseptual, kemandirian, dan refleksi mahasiswa untuk menutup kesenjangan antara tuntutan Outcome-Based Education (OBE) dan kesiapan mahasiswa. Kegiatan ini merupakan bagian dari program pengabdian kepada masyarakat yang dirancang dengan pendekatan student-centered learning (SCL). Data diperoleh melalui pre-test, post-test, dan kuesioner reflektif. Analisis menggunakan tiga indikator utama: Normalized-Gain (N-Gain), Reflective Learning (RL), dan Experiential Learning Mapping (ELM). Hasil menunjukkan peningkatan signifikan pada pemahaman konseptual (N-Gain = 1,00), sedangkan nilai RLII sebesar 3,29 mengindikasikan refleksi moderat. Temuan ini menegaskan bahwa experiential learning efektif dalam memperkuat kompetensi kognitif, tetapi optimalisasi fase reflektif diperlukan agar pembelajaran menjadi transformasional dan berkelanjutan.
Utilizing ChatGPT as a Large Language Model for Qualitative Decision Tree Modeling: A Proof-of-Concept for Strengthening Food Security in Indonesia Rachmadhan, Aditya Arief; Wijayati, Prasmita Dian; Widayanti, Annisa Vira; Hariputra, Akbar; Dewanti, Rizki Puspita
Jurnal Riset Multidisiplin Agrisosco Vol 4, No 1 (2026): Vol 4 No 1 April 2026
Publisher : Lembaga Penelitian, Pengembangan, Pemberdayaan Potensi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61316/jrma.v4i1.229

Abstract

This study explores the use of Artificial Intelligence, specifically ChatGPT as a large language model, in constructing a qualitative decision tree to support food security analysis in Indonesia. Framed within the FAO’s four-pillar approach—availability, access, utilization, and stability—the research adopts a methodological proof-of-concept design and does not rely on primary or secondary empirical datasets. Instead, the analysis is based on AI-generated reasoning derived from structured prompts, which are systematically organized into a conceptual decision tree framework. Validation is conducted through interpretative comparison with established theoretical frameworks and national policy documents, rather than empirical testing or expert elicitation. The resulting model provides a structured representation of strategic pathways and potential policy options, highlighting the advantages of AI-assisted modeling in terms of speed, scalability, and integrative synthesis of knowledge. However, the model remains qualitative and exploratory, with limitations related to contextual specificity, potential bias, and the absence of real-time data. The findings suggest that AI can function as a complementary analytical tool for structuring policy-relevant insights, although its application requires careful validation and should not be interpreted as evidence of policy effectiveness.
Teknologi dalam Rantai Pasok Agribisnis: Analisis Bibliometrik tentang Perannya dalam Meningkatkan Ketahanan Pangan Annisa Vira Widayanti; Raka Selaksa Charisma Muchammad; Akbar Hariputra; Aditya Arief Rachmadhan
Agriekstensia : Jurnal Penelitian Terapan Bidang Pertanian Vol. 24 No. 1 (2025): AGRIEKSTENSIA: Jurnal Penelitian Terapan Bidang Pertanian
Publisher : Politeknik Pembangunan Pertanian Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34145/agriekstensia.v24i1.3738

Abstract

Climate change, global disruptions, and unequal food distribution have made food security a critical and urgent global issue. In response, digital technologies offer strategic opportunities to enhance the efficiency, transparency, and resilience of agribusiness supply chains. However, existing research remains fragmented, often lacking thematic integration and a global perspective on how digital innovations contribute to food security. This study aims to systematically map the global research landscape through a bibliometric analysis of 100 Scopus-indexed articles published between 2019 and 2025, focusing on the intersection of digital technology, agribusiness, and food security. Using VOSviewer, five major thematic clusters are identified: blockchain and traceability, digital supply chain platforms, artificial intelligence, sustainability transformation, and data-driven agribusiness. The findings show that technologies such as blockchain, IoT, and AI play a vital role in supporting food system availability, accessibility, and stability. Emerging topics such as circular economy and digital inclusion reflect a shift toward more sustainable and equitable digital food systems. This study not only synthesizes existing academic discourse but also provides strategic insights for future research, policy design, and inclusive technological adoption—particularly in developing regions. As such, it serves as an essential foundation for designing systemic, inclusive, and sustainable digital transformation in agrifood systems to address the urgent challenge of global food security.
Co-Authors Aditya Arief Rachmadhan Aditya Arief Rachmadhan Annisa Vira Widayanti Asri, Dian Aulia Nurul Hikmah Dewanti, Rizki Puspita Dita Atasa Dita Rosyita Dwi Laila Maulida Endang Siswati Hary Sastryawanto Intan Mega Maharani Lainatussifa Manihuruk, Ekamonika Prasmita Dian Wijayati Putra Astaman Qalsum, Ummy Rachmadhan, Aditya Arief Raka Selaksa Charisma Muchammad Ramadhani, Mirza Sari, Putri Nurmalita Sastryawanto, Hary Siswati, Endang Wanto, Hary Yennyka Leilasariyanti