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All Journal Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) International Journal Software Engineering and Computer Science (IJSECS) Jurnal Sistim Informasi dan Teknologi Seumike : Society Progress Journal
Handry Eldo
Universitas Muhammadiyah mahakarya Aceh
Humanities Chemical Engineering, Chemistry & Bioengineering Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Engineering Environmental Science Health Professions Nursing Social Sciences

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The Influence of Electronic Service Quality and Electronic Recovery on Online Re-Purchase Intention: Role of E-Loyalty as Intervening Variable Erwin Dhaniswara; Suluh Sri Wahyuningsih; Handry Eldo; Asri Ady Bakri; Agus Junaidi
Jurnal Sistim Informasi dan Teknologi 2023, Vol. 5, No. 3
Publisher : SEULANGA SYSTEM PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60083/jsisfotek.v5i3.271

Abstract

This study intends to examine how online service quality and online recovery affect online loyalty and how they affect consumers' willingness to repurchase online. In this study, a non-probability sampling strategy with a purposeful sampling procedure was applied. A sample of 100 respondents who had purchased products from the marketplace were given questionnaires in order to obtain the data. The data in this study are analyzed using the Partial Least Square (PLS) method. The findings of this study demonstrate that online repurchase intention and electronic service quality have an impact on online loyalty. This study also discovered that electronic service quality has an impact on online repurchase intention via electronic loyalty. Through electronic loyalty, electronic recovery also has an impact on online repurchase intention.
Integrating Zero Trust Architecture with Blockchain Technology to Maintain Data Security in the Cloud T. Irfan Fajri; Handry Eldo; Cut Susan Octiva; Dikky Suryadi; Muhammad Lukman Hakim
International Journal Software Engineering and Computer Science (IJSECS) Vol. 5 No. 3 (2025): DECEMBER 2025
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v5i3.5481

Abstract

Data security concerns have increasingly become a challenge to cloud computing services due to rising incidents of cyberattacks, identity theft, and data manipulation. The perimeter-based security model is ineffective because of vulnerabilities in authentication and access control, thus necessitating an adaptive layered approach. This paper presents attempts to merge Zero Trust Architecture (ZTA) with Blockchain technology as one possible way to ensure confidentiality, integrity, and availability of data in cloud environments. Research methodology comprises a detailed review of related literature, system architecture analysis, and simulation of the conceptual merger using encryption protocols and smart contracts. Results revealed that ZTA significantly reduces the opportunities for unauthorized access through multi-layered verification and least privilege principles while Blockchain provides a decentralized transparent immutable method for recording transactions on data. The hybrid will enhance security substantially against breaches from external attackers and insiders with an already established verifiable audit trail. This paper concludes that such a merger could create a stronger model—one that is more measurable—and sustainable for securing today's cloud infrastructure.
Integrasi Big Data dan AI untuk Pengambilan Keputusan dalam Smart City T. Irfan Fajri; Novi Rahayu; Handry Eldo; Giatika Chrisnawati; Rizkia Shaulita
Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) Vol 9 No 2 (2025): APRIL-JUNE 2025
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.v9i2.3860

Abstract

This research explores the integration of Big Data technology and Artificial Intelligence (AI) in decision-making in the context of Smart City. With the massive growth of data from various sources such as IoT, sensors, and information systems, Big Data is becoming an important foundation for in-depth analysis. Meanwhile, AI provides the ability to process data in real-time, identify patterns, and generate accurate recommendations. This research aims to analyze how the combination of these two technologies can improve efficiency, sustainability, and quality of life in cities. The methods used include literature review and case analysis in several smart cities. The results show that the integration of Big Data and AI can support faster, more precise, and data-driven decision-making, thus encouraging the creation of a smarter and more responsive city.
Integration of Edge Computing and Wireless Sensors for Energy Efficiency Monitoring in Solar Panels Cut Susan Octiva; T. Irfan Fajri; Handry Eldo; Ayuliana Ayuliana; Nur Amalia Hasma
International Journal Software Engineering and Computer Science (IJSECS) Vol. 6 No. 1 (2026): APRIL 2026
Publisher : Lembaga Otonom Lembaga Informasi dan Riset Indonesia (KITA INFO dan RISET) - Lembaga KITA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v6i1.6797

Abstract

Increased demand for renewable energy has driven the development of efficient monitoring systems to optimize solar panel performance. This study aims to implement and evaluate the integration of edge computing technology with wireless sensor networks (WSN) in real-time solar panel energy efficiency monitoring systems. This approach is designed to overcome the limitations of conventional monitoring systems that still rely on centralized computing and exhibit high latency in data collection. The research method includes designing an edge computing-based system architecture, installing wireless sensors to measure key parameters (voltage, current, light intensity, and temperature), and applying energy efficiency algorithms at the edge to process data locally. The data is then sent to the cloud for in-depth analysis and visualization of system performance. Testing was conducted by comparing data transmission efficiency, response time, and measurement accuracy between edge-based and conventional systems. The results of the study show that the integration of edge computing and wireless sensors can increase monitoring efficiency by up to 28.4%, reduce system latency by 35.7%, and increase data accuracy by 12.6% compared to conventional systems that are entirely cloud-based. In addition, bandwidth consumption is significantly reduced because the computing process is done on the edge.
Sentiment and Public Emotion Classification of Viral Content Using Transformer-Based Model Ferdi Antonio; Handry Eldo; Arrazy Elba Ridha; Iwan Adhicandra; Cut Susan Octiva
International Journal Software Engineering and Computer Science (IJSECS) Vol. 6 No. 1 (2026): APRIL 2026
Publisher : Lembaga Otonom Lembaga Informasi dan Riset Indonesia (KITA INFO dan RISET) - Lembaga KITA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v6i1.6969

Abstract

The proliferation of social media platforms has generated an unprecedented volume of viral content, each drawing varied public responses expressed through sentiment and emotion. Mapping those responses — not merely counting them — is what separates surface-level monitoring from a genuine understanding of public perception. This study classified sentiment (positive, negative, neutral) and emotion (anger, joy, sadness, and fear) toward viral content using a fine-tuned Transformer-based model. Data were collected from social media via web scraping, then subjected to standard text preprocessing: case folding, tokenization, stopword removal, and stemming. The cleaned dataset was subsequently annotated with sentiment and emotion labels. BERT (Bidirectional Encoder Representations from Transformers) served as the base architecture, fine-tuned for multi-label classification. Evaluation relied on an 80:20 train-test split, with performance measured through accuracy, precision, recall, and F1-score. Across all sentiment and emotion categories, the model returned consistently high scores and handled ambiguous, context-dependent text more reliably than conventional machine learning baselines. The Transformer-based approach proved well-suited for sentiment and emotion analysis on social media data, with clear potential for deployment in public opinion monitoring systems.
Platform Kolaborasi Virtual Meningkatkan Interaksi antara Guru dan Siswa di Era Digital Handry Eldo
Seumike : Society Progress Journal Vol. 1 No. 1 (2025): SEUMIKE
Publisher : Bansigom Na Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Perkembangan teknologi digital telah membawa perubahan signifikan dalam dunia pendidikan, terutama dalam cara interaksi antara guru dan siswa. Platform kolaborasi virtual menjadi salah satu solusi untuk meningkatkan komunikasi dan keterlibatan siswa dalam proses pembelajaran. Artikel ini bertujuan untuk mengeksplorasi peran platform kolaborasi virtual dalam memperkuat hubungan antara guru dan siswa di era digital. Penelitian ini mengkaji berbagai platform yang digunakan dalam pendidikan, seperti Google Classroom, Microsoft Teams, dan Zoom, serta dampaknya terhadap interaksi dan keterlibatan siswa. Hasil penelitian menunjukkan bahwa penggunaan platform kolaborasi virtual meningkatkan aksesibilitas materi pembelajaran, mempermudah komunikasi dua arah antara guru dan siswa, serta mempercepat umpan balik dalam proses belajar-mengajar. Selain itu, platform ini juga memfasilitasi pengembangan keterampilan digital siswa yang diperlukan di abad 21. Meskipun demikian, tantangan terkait dengan akses internet dan kesiapan teknologi di kalangan siswa dan guru masih menjadi hambatan utama dalam implementasi yang lebih luas. Artikel ini menyarankan perlunya pelatihan dan pengembangan infrastruktur untuk mendukung efektivitas penggunaan platform kolaborasi virtual dalam meningkatkan interaksi dan kualitas pembelajaran.
Co-Authors Agus Junaidi Antonio, Ferdi Arrazy Elba Ridha Asri Ady Bakri Ayuliana Ayuliana Cut Susan Octiva Dhaniswara, Erwin Dikky Suryadi Giatika Chrisnawati Iwan Adhicandra Muhammad Lukman Hakim Mutasar Novi Rahayu Nur Amalia Hasma Rizkia Shaulita Siswahyudianto Suluh Sri Wahyuningsih