Article Per Year (5 Year)
p-Index From 2021 - 2026
0.408
P-Index
This Author published in this journals
All Journal Syntax: Journal of Software Engineering, Computer Science and Information Technology Jurnal Pengabdian
Nicholas Edison
Unknown Affiliation
Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities Astronomy Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Immunology & microbiology Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Neuroscience Nursing Physics Public Health Social Sciences Transportation Veterinary Other

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
Kegiatan Pelatihan dan Pengabdian kepada Masyarakat dalam Pemahaman Penggunaan Tools AI untuk Membuat Konten Christy, Christy; Jennifer Jocelyn; Jennifer Velensia Santoti; Nicholas Edison; Ricko Andreas Kartono; Hartati, Ery
Jurnal Pengabdian Vol. 4 No. 1 (2025): Januari-Juni
Publisher : Bengkulu Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58222/jp.v4i1.1283

Abstract

This training activity aims to improve the understanding of students of SMP Xaverius Maria Palembang regarding the use of artificial intelligence (AI) tools to create digital content, such as graphic design, video, and music. The hands-on practice-based training method is used to provide students with real experience in using AI applications, such as ChatGPT, Microsoft Designer, Luma AI, and Udio AI. The results of the training show that students not only understand the basic concepts of AI, but are also able to produce more innovative and creative content. Evaluation through interactive quizzes shows an increase in student understanding, although there are some challenges in understanding certain technical terms. This training has succeeded in encouraging students to become active and ethical digital creators, supporting their digital literacy to face the era of increasingly developing technology.
KEYWORD EXTRACTION KOMENTAR TERHADAP KONFLIK INDIA-PAKISTAN PADA PLATFORM YOUTUBE MENGGUNAKAN TF-IDF DAN COSINE SIMILARITY Nicholas Edison; Kristian Fernando; Hafiz Irsyad; Abdul Rahman
Syntax : Journal of Software Engineering, Computer Science and Information Technology Vol 6, No 2 (2025): Desember 2025
Publisher : Universitas Dharmawangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46576/syntax.v6i2.6638

Abstract

Konflik antara India dan Pakistan merupakan isu geopolitik yang sering menjadi perhatian global dan menimbulkan diskusi luas di media sosial, termasuk platform YouTube. Penelitian ini bertujuan untuk mengekstraksi kata kunci dari komentar-komentar pengguna YouTube mengenai topik konflik India-Pakistan, serta menganalisis kemiripan makna seluruh komentar antar video menggunakan metode TF-IDF dan Cosine Similarity. Data diperoleh dari kolom komentar tiga video YouTube yang relevan dan diproses melalui tahapan pra-pemrosesan teks, perhitungan bobot kata menggunakan TF-IDF, serta pengukuran similaritas menggunakan Cosine Similarity. Hasil ekstraksi kata kunci menggunakan TF-IDF menunjukkan terdapat 20 kata kunci dengan frekuensi tertinggi, dengan 3 kata kunci tertinggi adalah “india”, “pakistan” dan “perang”. Hasil perhitungan Cosine Similarity menunjukkan bahwa tingkat kemiripan antar komentar video berkisar antara 0,544 hingga 0,695, dimana nilai similarity tertinggi terdapat pada perbandingan Video 1 dan Video 3 (0,695), Video 1 dan Video 2 (0,653), sementara Video 2 dan Video 3 (0,544). Hasil ini menunjukkan bahwa kombinasi metode ini efektif dalam mengidentifikasi topik dominan serta hubungan semantik antar komentar. Visualisasi kata kunci dengan WordCloud juga memperjelas representasi opini publik yang berkembang. Penelitian ini memberikan kontribusi dalam pemetaan diskursus digital secara kuantitatif dan efisien.
Co-Authors Abdul Rahman Christy, Christy Hafiz Irsyad Hartati, Ery Jennifer Jocelyn Jennifer Velensia Santoti Kristian Fernando Ricko Andreas Kartono