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Tech-E
Published by Universitas Buddhi Dharma
ISSN : -     EISSN : -     DOI : -
Core Subject : Science,
Computer Science & IT
Jurnal Tech-E dikembangkan dengan tujuan menampung karya ilmiah Dosen dan Mahasiswa, baik hasil tulisan ilmiah maupun penelitian yang berupa hasil studi kepustakaan.
Arjuna Subject : -
Articles 132 Documents
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Inclusive Design Elements in a Digital Storytelling Prototype for Dyslexic Children: A Thematic Analysis Hassan Syauqi Ridzuan; Maizatul Hayati Mohamad Yatim; Nor Zuhaidah Mohamed Zain
Tech-E Vol. 10 No. 1 (2026): TECH-E (Technology Electronic)
Publisher : Fakultas Sains dan Teknologi-Universitas Buddhi Dharma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31253/te.v10i1.4642

Abstract

This study explores expert perspectives on the essential elements of a digital storytelling (DST) prototype designed to support early literacy among children with dyslexia. It aims to inform DST designers and educators in developing relevant content and potential design and implementation strategies for inclusive literacy learning. A qualitative design was employed using the Delphi method, involving iterative semi-structured interviews with seven subject-matter experts from special education, instructional technology, and multimedia fields. Data were analyzed using Braun and Clarke’s six-phase thematic analysis framework to generate themes systematically and ensure interpretive rigour. The findings revealed six interrelated themes emphasizing learner engagement, accessibility, pedagogical structure, content relevance, multimedia design, and teacher support. These themes indicate that experts indicated that future DST prototypes should combine clear instructional sequencing, dyslexia-friendly interface features, meaningful story content, and practical guidance for educators. The study highlights the need to integrate pedagogical, technological, and contextual considerations to enhance literacy development and engagement among dyslexic children. Overall, the study offers an empirically grounded framework for future DST development and promotes sustainable, equitable literacy interventions within inclusive educational settings.
Implementation of the K-Means Clustering Algorithm for Network Traffic Analysis on Debian 12 Daniel Silaban; Gracia Simatupang; Fasrad Juang Harefa; Lotar Mateus Sinaga
Tech-E Vol. 10 No. 1 (2026): TECH-E (Technology Electronic)
Publisher : Fakultas Sains dan Teknologi-Universitas Buddhi Dharma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31253/te.v10i1.4796

Abstract

Network traffic analysis is a crucial aspect of maintaining server performance and security. This study aims to implement the K-Means clustering algorithm to group network traffic characteristics on a server running the Debian 12 Bookworm operating system. Raw data was collected in real time using the tcpdump utility on the enp0s3 network interface by capturing 3,000 data packets (packet capture/PCAP). The raw data was then extracted using tshark into CSV format based on the Packet Size and Frequency features as input parameters for data mining. Clustering was evaluated for K values ranging from 2 to 10 using inertia, the Silhouette Score, and the Davies–Bouldin Index. K=3 was retained to represent macro-level segmentation, while K=5 was examined to provide a more detailed traffic representation based on the combined consideration of cluster validity and interpretability. For K=3, the mean packet sizes ranged from 121.00 to 1,241.85 bytes, while for K=5 they ranged from 118.75 to 1,303.81 bytes. The findings demonstrate the feasibility of K-Means as an initial approach for descriptive network-traffic segmentation. However, the study did not directly evaluate anomaly-detection accuracy or cybersecurity effectiveness. The findings demonstrate the feasibility of K-Means as an initial approach for descriptively segmenting Debian 12 network traffic based on packet size and packet frequency.

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