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All Journal Syntax: Journal of Software Engineering, Computer Science and Information Technology PUBLIDIMAS CSRID Jurnal Komputer Indonesia (JU-KOMI)
Akbar, Muhammad Barkah
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Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mechanical Engineering

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Journal : PUBLIDIMAS

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Pelatihan Pembelajaran Rancang Bangun Aplikasi Metode Segmentasi Dengan Thresholding Rosnelly, Rika; Wahyuni, Linda; Hardianto, Hardianto; Akbar, Muhammad Barkah; Daifiria; Subhan, Zhafira Nur
Publikasi Pengabdian Masyarakat Vol 4 No 1 (2024): PUBLIDIMAS Vol. 4 No. 1 MEI 2024
Publisher : LPPM Universitas Potensi Utama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22303/publidimas.v4i1.345

Abstract

Image processing technology has attracted human attention to be studied so that it has become a science that can be accepted and understood in everyday life. An image is a representation, likeness, or imitation of an object. The output of a data recording system can be a photo, an optical signal such as a photo, an analog signal such as an image on a TV monitor, or a digital signal that can be stored directly on storage media. One of the processes in image processing (image preprocessing). One image segmentation technique is thresholding, which uses differences in brightness or darkness to distinguish objects from the background. Thresholding is based on groupings in the histogram according to certain backgrounds or objects that can be extracted by separating the groups of the histogram. Otsu thresholding is used in a variety of applications ranging from medical imaging to low-level computer vision. The Otsu method takes an approach, namely discriminant analysis, namely determining a variable that can divide foreground and background objects. This training provides excellent benefits for students in understanding objects for applying thresholding segmentation.
Pemanfaatan Artificial Intelligence (AI) untuk Ide Penciptaan Karya Seni Berbahan Serbuk Kayu di CV. Rendy Hendicraft Soeheri, Soeheri; Setiawan, Adil; Nasution, M. Irfan Aldy; Akbar, Muhammad Barkah
Publikasi Pengabdian Masyarakat Vol 4 No 2 (2024): PUBLIDIMAS Vol. 4 No. 2 NOVEMBER 2024
Publisher : LPPM Universitas Potensi Utama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22303/publidimas.v4i2.408

Abstract

The utilization of Artificial Intelligence (AI) in the creative industry has opened new opportunities to enhance innovation and efficiency. This study aims to explore the use of AI as a tool to generate creative ideas for wood powder-based art at CV. Rendy Hendicraft. The methodology includes experiments with generative AI tools such as Flux AI, DALL-E and MidJourney to produce initial designs, followed by a selection and adaptation process by local artists. The results demonstrate that AI can generate diverse innovative design patterns, including traditional carvings, geometric abstracts, and modern-traditional hybrid elements, which are then transformed into wood powder artworks. The collaboration between AI and humans accelerates the conceptualization phase and broadens creative perspectives. However, adapting AI-generated designs to the wood powder medium requires modifications to accommodate material characteristics, such as texture and structural durability. The impacts of this initiative include increased productivity for CV. Rendy Hendicraft, product diversification, and strengthened competitiveness in the craft market. This study concludes that integrating AI into the creative process does not replace human roles but acts as an innovation catalyst supporting the sustainability of local-based creative industries.
Co-Authors Aulia, Lili Budi Triandi Daifiria Mochammad Imron Awalludin Muhammad Zarlis Nasution, M. Irfan Aldy Rika Rosnelly, Rika Setiawan, Adil Soeheri, Soeheri Subhan, Zhafira Nur Vania, Dea Ersa Wahyuni, Linda Zulkifli Nasution