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SISTEM OTOMATISASI RENDERING VIDEO TEMPLATE AFTER EFFECTS BERBASIS WEB DENGAN EXTENDSCRIPT DAN FLASK Ragil Raditya Saputra; Zacky Innova; Epsilona Katiga Capricorna; Bambang Irawan; Ridwan Ramadhan; Muhammad Hafizh Rahman Hakim
TEKNIMEDIA: Teknologi Informasi dan Multimedia Vol. 6 No. 2 (2025): Desember 2025
Publisher : Badan Penelitian dan Pengabdian Masyarakat (BP2M) STMIK Syaikh Zainuddin NW Anjani

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46764/teknimedia.v6i2.299

Abstract

The process of creating animations or videos in Adobe After Effects typically requires repetitive and time-consuming manual interaction, making it less efficient in digital multimedia workflows. To address this challenge, this study designed a web-based rendering automation system by integrating ExtendScript, After Effects' internal scripting language, and the Flask framework as the backend. The HTML-based interface allows users to input parameters such as text, color, or formatting options, which are then processed by Flask and passed to After Effects via a local subprocess. Beyond integration, we also compared this automation system with manual methods. This system increased work efficiency by up to 67.78% compared to traditional manual methods and supported automated processing based on user input. This system provides a practical and affordable solution for users who want to accelerate the production of visual content from After Effects templates with customizations to text and color, without compromising the flexibility and quality of the final result. This technology integration demonstrates that automating the creative process can be done effectively, stably, and easily accessible via the web if further developed.
SISTEM OTOMATISASI RENDERING VIDEO TEMPLATE AFTER EFFECTS BERBASIS WEB DENGAN EXTENDSCRIPT DAN FLASK Ragil Raditya Saputra; Zacky Innova; Epsilona Katiga Capricorna; Bambang Irawan; Ridwan Ramadhan; Muhammad Hafizh Rahman Hakim
TEKNIMEDIA: Teknologi Informasi dan Multimedia Vol. 6 No. 2 (2025): Desember 2025
Publisher : Badan Penelitian dan Pengabdian Masyarakat (BP2M) STMIK Syaikh Zainuddin NW Anjani

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46764/teknimedia.v6i2.299

Abstract

The process of creating animations or videos in Adobe After Effects typically requires repetitive and time-consuming manual interaction, making it less efficient in digital multimedia workflows. To address this challenge, this study designed a web-based rendering automation system by integrating ExtendScript, After Effects' internal scripting language, and the Flask framework as the backend. The HTML-based interface allows users to input parameters such as text, color, or formatting options, which are then processed by Flask and passed to After Effects via a local subprocess. Beyond integration, we also compared this automation system with manual methods. This system increased work efficiency by up to 67.78% compared to traditional manual methods and supported automated processing based on user input. This system provides a practical and affordable solution for users who want to accelerate the production of visual content from After Effects templates with customizations to text and color, without compromising the flexibility and quality of the final result. This technology integration demonstrates that automating the creative process can be done effectively, stably, and easily accessible via the web if further developed.
Analisis Komparatif K-Means dan Hierarchical Clustering Menggunakan Validasi Internal Clustering Shafwan Awaludin; Andri Agustian; Epsilona Katiga Capricorna; Muhammad Raihan Ilham; Nur Ananda Rumi; Vitri Tundjungsari
JUPITER (Jurnal Penelitian Ilmu dan Teknologi Komputer) Vol 18 No 1 (2026): Jurnal Penelitian Ilmu dan Teknologi Komputer (JUPITER)
Publisher : Teknik Komputer Politeknik Negeri Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5281/zenodo.18384228

Abstract

Clustering ialah salah satu pendekatan unsupervised learning yang bertujuan mengelompokkan informasi bersumber pada tingkatan kemiripan karakteristiknya tanpa memakai label kelas. Tata cara K- Means serta Hierarchical Clustering jadi algoritma yang kerap digunakan sebab konsepnya simpel dan gampang diimplementasikan. Riset ini bertujuan menyamakan kinerja tata cara K- Means serta Hierarchical Clustering memakai validasi internal cluster buat memperhitungkan mutu hasil pengelompokan. Dataset yang digunakan diperoleh dari salah satu web penyedia informasi terbuka berbasis website yang sediakan informasi numerik serta sudah banyak dimanfaatkan pada riset informasi mining. Proses riset dimulai dengan akuisisi informasi, preprocessing, pelaksanaan algoritma K- Means serta Hierarchical Clustering, dan penilaian hasil clustering memakai validasi internal berbentuk Silhouette Coefficient, Davies- Bouldin Index, serta Calinski- Harabasz Index. Hasil pengujian menampilkan kalau tiap- tiap tata cara mempunyai ciri yang berbeda pada pembuatan cluster. K- Means cenderung menciptakan cluster yang lebih kompak, sebaliknya Hierarchical Clustering membagikan visualisasi ikatan antar informasi yang lebih jelas lewat dendrogram. Nilai validasi internal menampilkan tata cara dengan mutu clustering terbaik tergantung pada struktur informasi yang digunakan. Riset ini diharapkan bisa jadi rujukan dalam pemilihan tata cara clustering yang cocok bersumber pada ciri informasi serta kebutuhan analisis.