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All Journal Jurnal Teknologi dan Manajemen Industri Terapan Prosiding Seminar Nasional Teknologi Informasi dan Bisnis Jurnal Pengabdian Masyarakat Tekno
Ramadhan, Chandra
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Mechanical Engineering Physics

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Inovasi Editing Video CapCut Desktop di Media Creative Solutions (MCS) Ramadan, M. Zidan; Ramadhan, Chandra; Abdullah, Fahmi
Jurnal Pengabdian kepada Masyarakat TEKNO (JAM-TEKNO) Vol 6 No 1 (2025): Juni 2025
Publisher : Ikatan Ahli Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/jamtekno.v6i1.6573

Abstract

In today's digital era, video editing skills have become essential for professionals in the creative industry to enhance the competitiveness of digital content. This Community Service Program (PKM) aims to improve video editing skills using CapCut Desktop among staff and managers at Media Creative Solutions (MCS), Bandung. The program was conducted through an interactive training method that combined theory, demonstrations, and project-based simulations. The results showed significant improvements in participants' abilities to independently edit videos more professionally, as well as a better understanding of CapCut Desktop features. In conclusion, the practice-based training proved effective in enhancing participants' digital competencies, and it is recommended that similar training be conducted regularly to maintain and further develop their skills.
Analisis Perbandingan Model CNN dan IndoBERT Dalam Sentimen Berita Politik Indonesia Ramadhan, Chandra; Atina, Vihi; Permatasari, Hanifah
Prosiding Seminar Nasional Teknologi Informasi dan Bisnis Prosiding Seminar Nasional Teknologi Informasi dan Bisnis (SENATIB) 2025
Publisher : Fakultas Ilmu Komputer Universitas Duta Bangsa Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47701/v1r9ka69

Abstract

Penelitian ini membandingkan kinerja dua model deep learning, Convolutional Neural Network (CNN) dan IndoBERT, dalam mengklasifikasikan sentimen berita politik berbahasa Indonesia. Data berasal dari portal berita online dengan topik politik seperti kebijakan publik, kinerja menteri, dan konflik legislatif. Label sentimen ditentukan dengan pendekatan berbasis leksikon (positif, negatif, netral). Proses pemodelan meliputi prapemrosesan teks dan pelatihan model CNN menggunakan embedding layer serta Conv1D, sementara IndoBERT menggunakan arsitektur transformer yang telah dilatih sebelumnya. Evaluasi menggunakan akurasi, presisi, recall, dan f1-score menunjukkan IndoBERT unggul dengan akurasi 92,93%, terutama pada klasifikasi kelas netral. CNN memiliki akurasi 89,13%, namun kesulitan dalam mengklasifikasikan sentimen netral. Hasil ini menunjukkan keunggulan IndoBERT dalam klasifikasi sentimen berita politik dan potensi model berbasis transformer dalam pemrosesan bahasa alami Indonesia (Indonesian Natural Language Processing).
Design Optimization of CNC Router 2413 for the Interior Design Industry Using Reverse Engineering and DFMA Ramadhan, Chandra; Dewa Kusuma Wijaya; Rudi Tjahyono
Jurnal Teknologi dan Manajemen Industri Terapan Vol. 4 No. 3 (2025): Jurnal Teknologi dan Manajemen Industri Terapan
Publisher : Yayasan Inovasi Kemajuan Intelektual

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55826/jtmit.v4i3.1148

Abstract

The wood industry faces prolonged production times due to the use of conventional tools and the declining number of artisans. This study aims to design the CNC 2413 machine to meet the production needs of the interior design industry by improving efficiency, precision, and adaptability. The design process applies the Reverse Engineering approach combined with Design for Manufacturing and Assembly (DFMA). The key technical aspects include torque calculation, Center of Gravity (CoG) analysis, and assembly mapping. The results indicate that a 3-axis CNC router is sufficient for cutting and engraving tasks, requiring a minimum torque of 0.4116 N·m (Y-axis), 0.3528 N·m (X-axis), and 0.0156 N·m (Z-axis), with a spindle torque of 0.159 N·m. The Nema 24 stepper motor and Bosch GKF router were selected as they meet the specified requirements. The CoG analysis produced X = 56.9–63.0 cm, Y = 100.9–127.3 cm, and Z = 3.884 cm, demonstrating structural stability and resistance to vibration. This design is considered feasible and reliable for long-term use. In addition, the study offers practical significance in terms of potential production cost savings through lower power consumption compared to conventional machines and the opportunity to enhance the production capacity of small and medium enterprises (SMEs) in the interior design sector. This research provides a practical reference for developing CNC routers using locally sourced components, aligned with the technical and economic needs of the interior design industry.
Co-Authors Atina, Vihi Dewa Kusuma Wijaya Fahmi Abdullah, Fahmi Permatasari, Hanifah Ramadan, M. Zidan Rudi Tjahyono