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Laporan Kemajuan Hibah Penelitian DPPM tahun 2025.
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rusv NVONlNnh•V10YIO. Urgensi Penelitian. Kesenjangan Legalitas.
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Tujuan Penelitian. Merancang Strategi Digitalisasi.
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Metodologi Penelitian. Pendekatan R&D. Research and Development dengan mixed methods menggabungkan kuantitatif dan kualitatif untuk solusi aplikatif..
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Received: Octotwr IS, 2021. Revised: December 20, 2021. International Journal of Intelligent Engineering & Systems http O'www.inass.org' A Data-Driven Model for Accelerating Home Industry Food Production License (PIRI) Certification through SME Assistance Programs Using K-Means Clustering Analysis Panji Novantaral* Yayan Suryana: Moh. Ali Fikri3 Ragel Trisudarmo* Department of Information Systems, Faculty of Computer Science. Kuningan University, Indonesia •Department ofEnglish Education, Faculty of Teacher Training and Education, Universitas Kuningan, Indonesia 'Politeknik Negeri Indramayu. West Java, Indones ia • Corresponding author's Email: [email protected] Abstract: The objective of this research is to develop a data-driven model to accelerate the certification of the Home Industry product License (PIRT) for SME actors in Kuningan Regency through a stnlctured mentoring program. This study uses a K-Means cluster analysis approach by utilizing quantitative SME data from 37 districts in Kuningan Regency, covering variables of production, legality, business scale, and geographical distribution. Spatial analysis was conducted to identify distribution patterns and regional mentoring needs. The results of the study show the formation of five main SME clusters, namely: (l) micro SMEs require strengthening of basic legality, (2) transitional SMEs with partial PIRT certification, (3) established SMEs with high production and full cenification, (4) seasonal SMEs with distribution challenges and limited legality, and (5) leading SMEs ready for expansion with additional celtifieation_ These findings indicate that a data-driven approach can accelerate the PIRT certification process through targeted mentoring strategies, while at the same time providing a methodological contribution in the form of integrating spatial analysis with K-Means clustering for mapping SME needs. Keywords: UMKM; PIRT Cenification; K-Means Clustering; Spatial Analysis; Kuningan Regency, Data-Driven 1. Introduction The growth of Small and Medium Enterprises (S.MES) in the household food sector plays a strategic role in supporting food security and strengthening the local economy in Indonesia, Food-related SMEs not only create jobs and enhance the competitiveness of the domestic economy but also contribute to preserving traditional culinary heritage that has the potential to become a leading commodity Nevertheless, the majority of SMEs face obstacles in meeting regulatory requirements and food safety certification, particularly the Home Industry Food business capacities are factors that often slow down the issuance of P-IRT certificates [31, Efforts to accelerate certification through mentoring programs have been carried out by the government and stakeholders. However, the approach [7], [8] Conventional approaches remain generic and are less capable of accommodating the heterogeneity of SME conditions, whether in terms Of production capacity, sanitation, or administrative readmess [10], [l l]. In line with the advancement of data analytics, the K- Means clustering method offers a systematic aooroach to erouome SMEs based on their orofiles.
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Kesesuaian dengan Usulan Penelitian. Metodologi Terlaksana.
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Hasil Survei Baseline: Temuan Kritis. ooo PIRT Digttnl tnnpe PKI- LJF.u yeno Utgtng esta unfux.
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IAAI Food business registrion Ycwr end to' be' tan) ine hid cur in. ery business and goom d Your ation @ Re9SttaI bushes C.oloreed colnati•m Your your herket bindrind hurvest Our ro•er snes cefcd afed cunv.re. mt wou your , Food roe o Vah Heck at hon you 'r cf Fern un.
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Dashboard 3.239% 55.796. Platform Digital PIRT: Fitur Utama.
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SERAPAN ANGGARAN BIAYA. Peran Mitra Kerja Sama:. Dinas Kesehatan Kabupaten Kuningan menjadi mitra kunci. Kontribusi berupa In-Kind: penyediaan data historis, akses sistem internal, dan dukungan fasilitas untuk FGD dan pelatihan..
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Potensi Keberlanjutan Hasil Penelitian. Tahun 2 (2026).
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Level TKT dan Indikator Keberhasilan. Level TKT Saat Ini.
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Rencana Tahapan Selanjutnya: Bulan 9-12. 01. Finalisasi Sistem (Bulan 9-10).
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Terima kasih.