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All Journal Jurnal Sains dan Teknologi Jurnal Simetris Jurnal Buana Informatika Jurnal Teknologi Register: Jurnal Ilmiah Teknologi Sistem Informasi EMITTER International Journal of Engineering Technology JOIN (Jurnal Online Informatika) Jurnal ELTIKOM : Jurnal Teknik Elektro, Teknologi Informasi dan Komputer INTEGER: Journal of Information Technology Informatika Pertanian Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control SINTECH (Science and Information Technology) Journal Prosiding Seminar Nasional Sains dan Teknologi Terapan Jurnal ULTIMATICS Journal of Information Technology and Computer Engineering Jurnal EDUTECH Undiksha JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) JISKa (Jurnal Informatika Sunan Kalijaga) Jurnal Mnemonic Journal of Soft Computing Exploration Journal La Edusci JUSTIN (Jurnal Sistem dan Teknologi Informasi) Jurnal Pemberdayaan Masyarakat JGHTT Indonesian Journal of Learning and Instructional Innovation
Febri Liantoni, Febri
Universitas Sebelas Maret
Aerospace Engineering Agriculture, Biological Sciences & Forestry Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Mathematics Mechanical Engineering Social Sciences Other

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TikTok as Microlearning: Unveiling Vocational Students’ Experiences in Learning Computer Systems Larasati, Sukma; Budianto, Aris; Liantoni, Febri; Ulfa, Saida
Jurnal Pemberdayaan Masyarakat Vol 5, No 1 (2026)
Publisher : Yayasan Keluarga Guru Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46843/jpm.v5i1.574

Abstract

This study aims to explore the learning experiences of vocational high school students in using TikTok as a microlearning medium for computer systems. The study aims to identify the factors that support or inhibit this process. The study used a qualitative descriptive approach. Data were collected through questionnaires and in-depth interviews with 10th-grade students at a vocational high school in Surakarta. Data analysis was conducted thematically based on three aspects: Cognitive Strategies, Efforts, and Metacognitive Strategies. The results indicate that using TikTok in learning provides a positive learning experience. This positive outcome is due to TikTok's concise, visual, and easily accessible content. Students can learn independently through short videos, create summaries, engage in peer discussions, and manage their study time. Inhibiting factors also include distractions from non-educational content and the videos' limited depth of information. In conclusion, TikTok has the potential to be an effective microlearning platform for vocational high school students, particularly for learning computer systems. The implications of this study's findings fill a gap in the literature, particularly regarding TikTok-based microlearning for productive subjects in vocational education.
Comparison of Adaptive Ant Colony Optimization for Image Edge Detection of Leaves Bone Structure Liantoni, Febri; Perwira, Rifki Indra; Bataona, Daniel Silli
EMITTER International Journal of Engineering Technology Vol 6 No 2 (2018)
Publisher : Politeknik Elektronika Negeri Surabaya (PENS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (455.566 KB) | DOI: 10.24003/emitter.v6i2.306

Abstract

Leaf bone structure has a characteristic that can be used as a reference in digital image processing. One form of digital image processing is image edge detection. Edge detection is the process of extracting edge information from an image. In this research, Adaptive Ant Colony Optimization algorithm is proposed for edge image detection of leaf bone structure. The Adaptive Ant Colony Optimization method is a modification of Ant Colony Optimization, in which the initial an ant dissemination process is no longer random, but it is done by a pixel placement process that allows for an edge based on the value of the image gradient. As a comparison also performed edge detection using Robert and Sobel method. Based on the experiments performed, Adaptive Ant Colony Optimization algorithm is capable of producing more detailed image edge detection and has thicker borders than others. Keywords: edge detection, ant colony optimization, robert, sobel
Co-Authors Abin Suarsa Acihmah Sidauruk Agus Efendi Agus Santoso Ananda, Rizky Putu Anas, Rizky Chairul Andini, Ratih Friska Dwi Annisa, Fitri Nur Anwar, Rizak Al Hasbi Aris Budianto, Aris Astuti, Asri B.M.A.S. Anaconda Bangkara Bambang Yuwono Bataona, Daniel Silli Bataona, Daniel Silli Bernadhed, Bernadhed Chaizara, Rezza Fariszal Hisyam Chastine Fatichah Cucuk Wawan Budiyanto Dwi Maryono Hasyim, Jaka Wardana Hendro Nugroho, Hendro Hidayatulah Himawan Hidayatulloh, A. Nururrochman Larasati, Sukma Luky Agus Hermanto, Luky Agus Majid, Desva Fitranda Maruf, Irma Rachmawati Maryanti Mulia Sulistiyono Myrtha, Risalina Nanik Suciati Nugroho, Hendro Nurcahya Pradana Taufik Prakisya Palupi, Dian Exsi Prabaswara, Muhammad Arden Prakisya , Nurcahya Pradana Taufik Prakisya, Nurcahya Pradana Taufik Pratama, Kalistus Haris Purnama, Bayu Rizkhy Candra Puspanda Hatta Putri, Nanditya Vianti Qurin, Milani Tanya Rahmawati, Weny M. Ramadhan, Firdaus Ditio Ramadhan, Raqael Fisabillah Rifki Indra Perwira Rosetya, Septiyawan Rosihan Ari Yuana, Rosihan Ari Rustanto, Diki Wahyudi Saida Ulfa Salsabila, Zahra Khalila Santoso, Agus Adi Saputro, Muhammad Naufal Adi Setiyani, Susanti Simanjuntak, Ondihon Siswoyo, Risya Ines Putri Sukmagautama, Coana Sukmaningrum, Agy Hafidzah Wahyudi, Yusuf Rois Weny Mistarika Rahmawati Yusfia Hafid Aristyagama