Article Per Year (5 Year)
p-Index From 2021 - 2026
0.408
P-Index
This Author published in this journals
All Journal Scientific Journal of Engineering Research Scientific Journal of Computer Science
Tangaro, Diana May Glaiza G.
Unknown Affiliation
Computer Science & IT Engineering

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

Found 2 Documents
Search

 1 
Comparative Analysis of Hierarchical Token Bucket and Per Connection Queue Methods in Video Conferences Kariyamin; Alyandi, La Ode; A'an, Deyti Lusty; Suarti, Wa Ode Reni; Yapono, Putri; Tangaro, Diana May Glaiza G.; Talirongan, Florence Jean B.
Scientific Journal of Engineering Research Vol. 1 No. 2 (2025): June
Publisher : PT. Teknologi Futuristik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64539/sjer.v1i2.2025.13

Abstract

Video conferencing is a set of interactive telecommunication technologies that allow two or more parties in different locations to interact using audio and video simultaneously. In video conferencing tools, bandwidth management is needed to maintain the quality of data transmitted through bandwidth. The Hierarchical Token Bucket (HTB) method is a method that uses a hierarchical structure and priorities for the client so that the distribution of bandwidth can be adjusted. In contrast, the Per Connection Queue (PCQ) method is a method that applies bandwidth sharing so that the allocation of bandwidth can be done more evenly to all clients. The parameters used to determine the quality of service in both methods are throughput, packet loss, delay, and jitter. The test results showed that in the Zoom application, the HTB method had an average TIPHON Standard Index of 3.5, while the PCQ method was 3.75. However, in the TrueConf application, the HTB method has a TIPHON standard index of 3.75, while the PCQ method has a TIPHON standard index of 3.5. In the TrueConf application, the HTB method is superior, while in the Zoom application, the PCQ method is superior.
Identification of Dominant Topics in Public Discussions on IKN using Latent Dirichlet Allocation (LDA) and BERTopic Ningrum, Ariska Fitriyana; Talirongan, Florence Jean B.; Tangaro, Diana May Glaiza G.
Scientific Journal of Computer Science Vol. 1 No. 1 (2025): June
Publisher : PT. Teknologi Futuristik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64539/sjcs.v1i1.2025.19

Abstract

This study aims to analyze public opinion related to the relocation of Indonesia's National Capital City (IKN) through topic modeling on Twitter data. The two main approaches used are Latent Dirichlet Allocation (LDA) based on Bag of Words and BERTopic based on Transformer language model. LDA was chosen for its ability to identify topic distribution in large text collections, while BERTopic was used to overcome the limitations of LDA in capturing semantic meaning in short and informal texts such as tweets. The analysis was conducted on a collection of tweets discussing the relocation of IKN, with the aim of uncovering the main themes and public perceptions. The result of LDA showed three main topics in the public discussion, namely (1) political debate and nationalism related to the relocation, (2) policy implementation and project execution, and (3) economic justification and challenges facing Jakarta. Mean-while, BERTopic identified topics with more contextual representations, including aspects of investment, economic impact construction progress, and public perception. Dominant topics include urban relocation, investment in IKN, and socio-economic impacts. The novelty of study lies in the comparison of two topic modeling approaches in the context of social media sentiment analysis related to major public policy issues. These findings not only enrich the understanding of the narratives that develop in society, but also provide important insights for policy makers in responding to public opinion more appropriately and contextually.
Co-Authors A'an, Deyti Lusty Alyandi, La Ode Ariska Fitriyana Ningrum Kariyamin Suarti, Wa Ode Reni Talirongan, Florence Jean B. Yapono, Putri