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All Journal Jurnal Teknologi Informasi dan Multimedia JOURNAL OF INFORMATION SYSTEM MANAGEMENT (JOISM) Jurnal Pengabdian kepada Masyarakat Nusantara SINTA Journal (Science, Technology, and Agricultural)
Pirmansah, Imam Ainudin
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Agriculture, Biological Sciences & Forestry Astronomy Biochemistry, Genetics & Molecular Biology Chemistry Computer Science & IT Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Environmental Science Physics Social Sciences Veterinary

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ANALISA STRATEGIS DALAM PROSES GENERATE IMAGE-TO-VIDEO PADA PLATFORM AI GENERATIF UNTUK OPTIMALISASI KUALITAS VIDEO Pirmansah, Imam Ainudin; Satria, Dhimas Adi; Musthofa, Rifai Ahmad
Journal of Information System Management (JOISM) Vol. 7 No. 1 (2025): Juni
Publisher : Universitas Amikom Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24076/joism.2025v7i1.2131

Abstract

Perkembangan pesat kecerdasan buatan generatif (AI) telah mentransformasi proses pembuatan konten digital, khususnya dalam menghasilkan video dari gambar statis. Meskipun telah hadir berbagai platform AI image-to-video seperti Kling, Runway, Pixverse, dan Hailuo, hingga kini belum ada benchmarking komprehensif dan sistematis terkait kinerja serta kualitas output dari platform-platform tersebut. Penelitian ini menyajikan analisis komparatif terhadap keempat platform guna mengoptimalkan kualitas video untuk kebutuhan kreatif maupun profesional. Pendekatan kuantitatif dan kualitatif digunakan melalui pengukuran waktu proses, resolusi, frame rate, Peak Signal-to-Noise Ratio (PSNR), Structural Similarity Index Measure (SSIM), serta penilaian berbasis skala Likert oleh panelis ahli. Hasil eksperimen menunjukkan bahwa Runway secara konsisten menghasilkan kualitas visual dan sinematografi terbaik, Kling unggul dalam stabilitas karakter dan efisiensi biaya, Hailuo menonjol pada detail tekstur, sementara Pixverse menawarkan workflow tercepat. Temuan ini memberikan panduan praktis bagi pengguna, pengembang, dan pelaku industri dalam memilih dan mengoptimalkan platform AI image-to-video.
Pemanfaatan Teknologi Generatif Artificial Intelligence sebagai Media Promosi bagi Guru dan Staf Publikasi di Sekolah Dasar Satria, Dhimas Adi; Sidauruk, Acihmah; Sutarni, Sutarni; Pirmansah, Imam Ainudin
Jurnal Pengabdian kepada Masyarakat Nusantara Vol. 6 No. 3 (2025): Edisi Juli - September
Publisher : Lembaga Dongan Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55338/jpkmn.v6i3.6211

Abstract

Perkembangan Kecerdasan Buatan (Artificial Intelligence/AI) telah menyentuh berbagai aspek kehidupan manusia, termasuk dunia pendidikan. Salah satu bentuk inovasi AI yang memiliki potensi besar adalah Generatif Artificial Intelligence (Gen-AI), sebuah teknologi yang mampu menghasilkan konten multimedia seperti teks, gambar, video, dan audio berdasarkan data yang dilatihkan. Teknologi ini dapat dimanfaatkan oleh guru, siswa, dan staf sekolah untuk mendukung proses pembelajaran, promosi sekolah, serta dokumentasi kegiatan akademik. Namun, masih banyak tenaga pendidik dan staf di tingkat sekolah dasar yang belum memahami cara memanfaatkan Gen-AI secara optimal. Kegiatan pengabdian masyarakat ini bertujuan untuk memperkenalkan berbagai platform Gen-AI kepada guru dan staf sekolah dasar di Kota Yogyakarta, sekaligus memberikan pelatihan praktis dalam penggunaannya untuk menciptakan konten pendidikan dan promosi berbasis AI. Metode pelaksanaan terdiri dari tiga tahap utama: (1) analisis kebutuhan melalui survei dan wawancara untuk mengidentifikasi tantangan dan peluang penerapan Gen-AI di sekolah, (2) pendampingan langsung dalam penggunaan tools Gen-AI serta (3) pembuatan produk konten seperti video promosi sekolah dan dokumentasi kegiatan yang dapat digunakan untuk menyambut tahun ajaran baru. Hasil kegiatan menunjukkan bahwa Gen-AI dapat meningkatkan efisiensi dan kreativitas dalam pembuatan materi pembelajaran maupun promosi sekolah. Meskipun demikian, diperlukan pendampingan berkelanjutan untuk memastikan pemanfaatan teknologi ini tetap sesuai dengan kebutuhan pendidikan dan etika digital. Melalui pengabdian ini, diharapkan guru dan staf sekolah dapat lebih percaya diri dalam mengadopsi teknologi Gen-AI sebagai alat pendukung inovasi di lingkungan sekolah.
Optimizing the Representation of Facial Muscle Anatomy in 3D Animation Expressions Pirmansah, Imam Ainudin; Rahman, Ahmad Zaid; Satria, Dhimas Adi
SINTA Journal (Science, Technology, and Agricultural) Vol. 5 No. 1 (2024)
Publisher : Perkumpulan Dosen Muda (PDM) Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37638/sinta.5.1.73-82

Abstract

This research aims to optimize the representation of facial muscle anatomy in 3D animated expressions by using a hybrid approach that combines blendshape and joint-based rigging techniques as well as an advanced control system. Blendshape is used to capture fine details and nuances of facial expressions, while joint-based rigging provides additional flexibility for broader, more dynamic movements. The implemented control system allows precise and interactive manipulation of various facial expressions, resulting in more realistic and natural facial deformations. The research methodology includes the development of a facial model with accurate anatomical details, followed by the implementation of a hybrid rig that combines blendshape and joint-based rigging. The control system is built using a node connector technique, which allows granular regulation of facial expression and deformation parameters. Validation was carried out through extensive testing with various facial expressions to assess the accuracy and realism of the resulting animation. The research results show that this hybrid approach significantly increases the accuracy and realism of facial expressions in 3D animation compared to conventional methods. The control system developed also proved effective in providing flexibility and ease of use for animators. Thus, this research offers an important contribution to improving the quality and efficiency of 3D animation production, as well as opening up opportunities for further development in facial rigging and animation techniques.
Implementasi Generatif Artificial Intelligence pada Tahap Pembuatan Animasi menggunakan Metode MDLC Satria, Dhimas Adi; Pirmansah, Imam Ainudin; Musthofa, Rifai Ahmad
Jurnal Teknologi Informasi dan Multimedia Vol. 7 No. 4 (2025): November
Publisher : Sekawan Institut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35746/jtim.v7i4.746

Abstract

The rapid advancement of artificial intelligence (AI) in recent years has unlocked new opportunities across various fields, including creative industries such as animation. This study focuses on the application and use of generative AI, particularly text-to-image, text-to-video, and image-to-video models, in the process of creating animated scenes. This technology enables the generation of complex and imaginative visual content based solely on narrative descriptions (prompts) provided by users. By automating the production of images or videos, generative AI not only accelerates the production process and significantly reduces costs but also opens doors to exploring more diverse and innovative visual styles. This research analyzes several cutting-edge generative AI technologies, while evaluating their advantages and challenges in producing animated content. The AI-based animation development process is examined using the Multimedia Development Life Cycle (MDLC) framework, which consists of six key stages: Concept, Design, Material Collection, Development, Testing, and Distribution. The findings suggest that generative AI holds great potential for enhancing animators' efficiency, particularly in pre-production stages such as storyboarding, concept art creation, and rough animation. However, while AI can automate many technical aspects, human intervention remains essential to ensure visual consistency, artistic quality, and narrative coherence. Key challenges include dependence on dataset quality, risks of visual style plagiarism, and the need for manual refinement to align outputs with creative visions. Thus, the integration of generative AI in animation production should be viewed as an assistive tool rather than a complete replacement for human creativity. This study provides insights into how AI technology can be optimally utilized in the animation industry while preserving artistic value and originality.
Co-Authors Acihmah Sidauruk Musthofa, Rifai Ahmad Rahman, Ahmad Zaid Satria, Dhimas Adi Sutarni, Sutarni