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All Journal Pangripta Jurnal Ilmiah Kajian Perencanaan Pembangunan Jurnal Pengembangan Teknologi Informasi dan Komunikasi (JUPTIK)
Meilani, Cindy
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Humanities Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Engineering Library & Information Science Social Sciences

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Klasifikasi Jenis Tanaman Obat Herbal Berdasarkan Ciri Daun Menggunakan K-NN Meilani, Cindy; Ambarwati, Rizki; Saputri, Devita; Fujianto
Jurnal Pengembangan Teknologi Informasi dan Komunikasi (JUPTIK) Vol. 3 No. 2 (2025): JURNAL PENGEMBANGAN TEKNOLOGI INFORMASI DAN KOMUNIAKSI (JUPTIK)
Publisher : Prodi Teknologi Informasi Universitas Muhammadiyah Muara Bungo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52060/juptik.v3i2.3028

Abstract

Indonesia has a variety of abundant plants, including medicinal plants. However, many people still do not know about the types of herbal medicinal plants that exist. The process of identifying types of herbal medicinal plants generally relies on the knowledge of botanists with manual methods, which rely on morphological characteristics and vision. With advances in technology, leaf image recognition can be done using computer vision methods. This study aims to identify types of herbal medicinal plants based on leaf image patterns using the K-Nearest Neighbors (K-NN) method. The identification process begins with taking leaf images, then feature extraction is carried out to distinguish plant types. The results of the study show that the K-NN method can provide a fairly good level of accuracy in identifying types of medicinal plants. This system is expected to help the public recognize medicinal plants more effectively and expand knowledge about the benefits of herbal plants. Thus, the application of leaf image recognition technology can be a solution in conserving knowledge about medicinal plants in Indonesia.
Klasifikasi Jenis Tanaman Obat Herbal Berdasarkan Ciri Daun Menggunakan K-NN Meilani, Cindy; Ambarwati, Rizki; Saputri, Devita; Fujianto
Jurnal Pengembangan Teknologi Informasi dan Komunikasi (JUPTIK) Vol. 3 No. 2 (2025): JURNAL PENGEMBANGAN TEKNOLOGI INFORMASI DAN KOMUNIAKSI (JUPTIK)
Publisher : Universitas Muhammadiyah Muara Bungo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52060/juptik.v3i2.3028

Abstract

Indonesia has a variety of abundant plants, including medicinal plants. However, many people still do not know about the types of herbal medicinal plants that exist. The process of identifying types of herbal medicinal plants generally relies on the knowledge of botanists with manual methods, which rely on morphological characteristics and vision. With advances in technology, leaf image recognition can be done using computer vision methods. This study aims to identify types of herbal medicinal plants based on leaf image patterns using the K-Nearest Neighbors (K-NN) method. The identification process begins with taking leaf images, then feature extraction is carried out to distinguish plant types. The results of the study show that the K-NN method can provide a fairly good level of accuracy in identifying types of medicinal plants. This system is expected to help the public recognize medicinal plants more effectively and expand knowledge about the benefits of herbal plants. Thus, the application of leaf image recognition technology can be a solution in conserving knowledge about medicinal plants in Indonesia.
Media Arts, Creative Economy Transformation, and Collaborative Urban Governance in Emerging Creative Cities: Evidence from Malang, Indonesia Albaba, M Ziaelfikar; Aini, Asfa Agustina Nusba; Iswari, Hanif Rani; Ainun, Siti Nur; Meilani, Cindy
PANGRIPTA Vol. 9 No. 1 (2026): Pangripta Jurnal Ilmiah Kajian Perencanaan Pembangunan
Publisher : Badan Perencanaan Pembangunan Kota Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58411/mtn1cs77

Abstract

The growing importance of creative economies has positioned Media Arts as a strategic driver of urban transformation, digital innovation, and sustainable competitiveness. However, existing creative city scholarship remains heavily concentrated on metropolitan cities in developed countries, while medium-sized cities in emerging economies, particularly in Southeast Asia, remain underexplored. This study examines the transformation of Malang City, Indonesia, into the first UNESCO Creative City of Media Arts in Southeast Asia by analyzing the integration of creative economy strategies, collaborative governance mechanisms, and Media Arts-based urban development. Using a qualitative descriptive case study approach, this research draws upon UNESCO dossiers, regional planning documents, policy reports, creative economy statistics, and relevant academic literature. The findings reveal that Malang’s transformation was supported by the synergistic interaction between cultural heritage, educational ecosystems, digital innovation, and collaborative governance institutionalized through the Culture–Talent–Technology (CTT) framework and the Hexahelix governance model. The study further demonstrates that Media Arts ecosystems contributed not only to economic growth and employment generation but also to cultural revitalization, urban branding, tourism development, and social inclusion. The findings contribute theoretically by extending creative city and collaborative governance literature through the proposed Media Arts-Based Urban Transformation Model for medium-sized cities in emerging economies. Practically, the study provides strategic insights for cities seeking to develop sustainable and globally competitive creative ecosystems through culturally grounded, innovation-oriented, and collaborative urban development strategies.
Co-Authors Aini, Asfa Agustina Nusba Ainun, Siti Nur Albaba, M Ziaelfikar Ambarwati, Rizki Fujianto Hanif Rani Iswari Saputri, Devita