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Journal : Applied Technology and Computing Science Journal

Dual Load balancing menggunakan Algoritma Round-robin pada Cloud Computing Awang Andhyka; Fawaidul Badri
TEKNOLOGI DITERAPKAN DAN JURNAL SAINS KOMPUTER Vol 2 No 2 (2019): December
Publisher : Universitas Nahdlatul Ulama Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33086/atcsj.v2i2.1373

Abstract

Downtime pada cloud computing seringkali memiliki dampak langsung penggunanya. Situs besar dapat kehilangan jutaan dana atau lebih dalam pendapatan setiap menit situs mereka tidak tersedia. Dengan menggunakan server load untuk balancing yang dimungkinkan untuk memberikan keandalan yang lebih baik karena algoritma load pada balancing digunakan untuk meminimkan kesalahan serta memungkinkan kemungkinan pada peningkatan dan pemeliharaan server tanpa mengganggu layanan yang ditawarkan. Jika server macet dan perlu dimatikan karena pemeliharaan, itu hanya akan menyebabkan penurunan kinerja, sementara layanan masih tersedia di server yang masih aktif. Penyedia layanan perlu menyesuaikan dengan perjanjian tingkat pada sebuah layanan yang menggambarkan batasan untuk layanan yang diberikan, seperti waktu respons, waktu aktif, bandwidth, dll. Karena padatnya komunikasi lintas jaringan dapat berubah dengan cepat sehingga sangat penting bagi penyedia layanan untuk dapat beradaptasi dengan perubahan yang mungkin terjadi karena untuk meningkatkan lalu lintas terhadap server. Load balancing menyediakan kemungkinan untuk menyesuaikan jaringan dengan permintaan yang banyak dan meningkat pada lalu lintas berdasarkan dinamika cloud computing.
Design and Build a Web App-Based Conference Registration System Using the Waterfall Model Fawaidul Badri; Ridwan Maulana; Khusnul Khotimah; Rizqi Putri Nourma Budiarti; Awang Andhyka
TEKNOLOGI DITERAPKAN DAN JURNAL SAINS KOMPUTER Vol 4 No 2 (2021): December
Publisher : Unusa Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33086/atcsj.v4i2.2820

Abstract

During the pandemic, many events are held online. conference registration (webinars, seminars, workshops) which basically will cause its complexity for admins if there are excess registrants or over participants from achieving the registration quota target. In addition, the admin must monitor regularly to ensure that there are no excess registrants that result in inefficient. The method used in the development of this application is the waterfall method. The purpose of this research is to build a web-based conference registration system that can make it easier for admins/organizers to manage the registration process. The results of this study the system can display the results of the recap from the admin so that the user can see the quota from the conference registration organized by the committee as well as testing of users from several tests to produce an application system that runs well.
Sentiment Analysis of Digital Ethics in YouTube Islamic Preaching Videos Using Support Vector Machine Rahmah, Arizka Sabilah; Andhyka, Awang; Nugroho, Rizky Aditya
TEKNOLOGI DITERAPKAN DAN JURNAL SAINS KOMPUTER Vol 8 No 2 (2025): December
Publisher : Universitas Nahdlatul Ulama Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33086/atcsj.v8i2.8422

Abstract

The rapid expansion of Islamic preaching in the digital sphere, particularly through YouTube, calls for a deeper understanding of communication ethics as reflected in user responses. This study analyzes the sentiments expressed in comments on Islamic preaching videos to identify patterns of digital ethics within online communities. The research employs a Support Vector Machine (SVM) classification model with TF-IDF feature representation. Data were collected from YouTube comments and processed through several preprocessing stages, including text cleaning, case normalization, tokenization, stopword removal, and stemming, before being manually labeled into three sentiment categories: positive, negative, and neutral. Testing on 22 data samples shows that the SVM model achieved an accuracy of 77.27%, with the highest performance observed in the neutral category. Misclassification in the positive and negative categories was mainly influenced by data imbalance and linguistic variations commonly found in religious discourse. These findings indicate that SVM combined with TF-IDF is reasonably effective for sentiment analysis in the context of digital Islamic preaching; however, improvements in data balance and the incorporation of contextual features are necessary to enhance classification performance. Overall, this study provides an initial insight into audience response patterns toward digital Islamic preaching and contributes to the development of digital ethics research in Islamic communication studies.