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All Journal INTECOMS: Journal of Information Technology and Computer Science Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) eScience Humanity Journal
Guna, Bucky Wibawa Karya
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Arts Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Languange, Linguistic, Communication & Media Social Sciences

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The Impact of Social Media Communication on Youth Identity Formation: A Cross-Cultural Analysis Nugraha, Aat Ruchiat; Sjoraida, Diah Fatma; Rembe, Elismayanti; Guna, Bucky Wibawa Karya; Sani, Asrul; Suhardi, Suhardi; Fitria, Arie
eScience Humanity Journal Vol 4 No 2 (2024): eScience Humanity Journal Volume 4 Number 2 May 2024
Publisher : Asosiasi Ide Bahasa Kepri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37296/esci.v4i2.177

Abstract

This study aims to analyze the impact of social media communication on the formation of adolescent identity from a cross-cultural perspective. Using cross-cultural analysis methods, this study investigates how adolescents from different countries and cultures interact with social media and how those interactions affect the formation of their identities. The results of the study show that social media plays an important role as an important space for adolescents to uncover, express, and negotiate their cultural identity. Social media platforms provide access to a wide range of cultural expressions, allowing for the blending and transformation of traditional and modern cultural elements. However, research also shows that the influence of social media can lead to cultural homogenization and the potential loss of unique local cultural identities. In addition, the study also found that social media use can influence teens by offering a sense of community and membership, as well as facilitating connections with like-minded friends globally.
Analisis Sentimen Film Dirty Vote Menggunakan BERT (Bidirectional Encoder Representations from Transformers) Sjoraida, Diah Fatma; Guna, Bucky Wibawa Karya; Yudhakusuma, Dudi
Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) Vol 8 No 2 (2024): APRIL-JUNE 2024
Publisher : Lembaga Otonom Lembaga Informasi dan Riset Indonesia (KITA INFO dan RISET)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jtik.v8i2.1580

Abstract

This research aims to conduct sentiment analysis on reviews of the film "Dirty Vote" from various sources, such as social media, film review websites, and online forums, using a fine-tuned BERT model. This approach includes review data collection, data pre-processing, BERT model refinement, and model performance evaluation. The research results show that the BERT model achieves a high level of performance with accuracy, precision, recall, and F1-score exceeding the threshold of 0.8 on the validation dataset. Sentiment analysis from various sources revealed variations in public opinion toward the film “Dirty Vote,” with significant differences in sentiment expressed via social media such as Twitter and Facebook compared to reviews from dedicated websites or online forums. In addition, discussion analysis of sentiment findings revealed people's preferences for certain aspects of films, such as visual effects and music. Sentiment analysis findings revealed that visual effects and music received the highest ratings from the public, while the cast and director received lower ratings. This information can be used by filmmakers to improve unsatisfactory aspects in subsequent film production.
The Impact Machine Learning Algorithms : Study Meta-Analysis Sani, Asrul; Oktavio, Adrie; Metasari, Rean; Santosa, Tomi Apra; sjoraida, Diah Fatma; Rembe, Elismayanti; Amri, Miftachul; Guna, Bucky Wibawa Karya
INTECOMS: Journal of Information Technology and Computer Science Vol 7 No 4 (2024): INTECOMS: Journal of Information Technology and Computer Science
Publisher : Institut Penelitian Matematika, Komputer, Keperawatan, Pendidikan dan Ekonomi (IPM2KPE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31539/intecoms.v7i4.10860

Abstract

Machine Learning (ML) algorithms have revolutionized various fields, including science, technology, and business. This study conducted a meta-analysis to review the impact of ML algorithms on various domains. This research is a type of meta-analysis research. The data sources in this study come from 12 national and international journals published in 2022-2024. Data collection techniques through direct observation through journal databases. The inclusion criteria in this meta-analysis are research obtained from google scholar; ScienceDirect and ERIC, Research must be related to machine learning algorithms, research has complete data to calculate the effect size value. Data analysis in this study was conducted by statistical analysis with JSAP 0.16.3 application. The results of the study concluded that ML lgoritma has a significant impact on various fields including the discovery of new knowledge, process efficiency and accuracy in prediction with an effect size value of 0.793; p < 0.001. These findings show that ML algorithms have great potential to improve performance and efficiency in various fields.
Nonverbal Communication, Interpersonal Relationships, Gestures, Postures, Proxemics. Sjoraida, Diah Fatma; Nugraha, Aat Ruchiat; Guna, Bucky Wibawa Karya; Ali, Makhrus; Arifin, Andi Harmoko; Nomleni, Anton PW; Hendrik, Hendrik; Pasaribu, Daniel
eScience Humanity Journal Vol 4 No 2 (2024): eScience Humanity Journal Volume 4 Number 2 May 2024
Publisher : Asosiasi Ide Bahasa Kepri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37296/esci.v4i2.179

Abstract

This study aims to explore the role of nonverbal communication in interpersonal relationships, with a focus on gestures, postures, and proxemics (physical distance between individuals). Nonverbal communication, which includes body movements, body language, as well as the use of personal space, has a significant impact on the understanding and dynamics of relationships between individuals. The study uses observation and in-depth interview methods to identify patterns of nonverbal communication in daily interactions. The results showed that gestures, postures, and proxemics can affect the way people respond to and understand each other, thereby strengthening or weakening interpersonal relationships. This research contributes to a deeper understanding of the importance of nonverbal elements in building effective and harmonious communication in various social contexts.
Co-Authors Aat Ruchiat Nugraha Adrie Oktavio Ali, Makhrus Amri, Miftachul Andi Harmoko Arifin Asrul Sani Diah Fatma Sjoraida Fitria, Arie Hendrik Hendrik Metasari, Rean Nomleni, Anton PW Pasaribu, Daniel Rembe, Elismayanti Santosa, Tomi Apra Suhardi Suhardi Yudhakusuma, Dudi