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Journal : Indonesian Journal of Computing, Engineering, and Design

Web Conference Internet Traffic Analysis during Study-from-Home Period: Case in Sampoerna University Muhammad Agni Catur Bhakti; Wandy Wandy
Indonesian Journal of Computing, Engineering, and Design (IJoCED) Vol. 2 No. 2 (2020): IJoCED
Publisher : Faculty of Engineering and Technology, Sampoerna University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35806/ijoced.v2i2.116

Abstract

Web conference feature embedded in Learning Management System (LMS) has been implemented in Sampoerna University (SU) to support mandatory Teaching-and-Learning from home activities during early stage of Covid-19 spreading period in Jakarta. The use of technologies and Internet connection to support these academic activities became very essential. The objec-tive of this research is to analyze internet speed and quota con-sumptions to meet the web conference requirements. Lecturers and students need sufficient Internet quota, stable Internet connection with proper speed, either using wired or wireless connection, in prepaid or postpaid subscriptions for smooth online learning. This research was an exploratory and quantitative research with surveys using non-probability with identified voluntary response sampling. The results showed that web conferences using BigBlueButton for audio-call, text-based chat, and rarely updated presenter shared-screen consumed only 3.11% of average students’ Internet connection speed, while the quota consumptions for 3 Credit Points Course session were 129.15 MB (Megabyte) per session, and for 4 Credit Points Course session were 140.2 MB per session. It was concluded that students are supposed to experience no or less delay during web conferences, and still have plenty of Internet bandwidth that can be utilized to support Study-from-Home activities.
An FMCW Radar-Based Intelligent System for Non-Contact Detection and Monitoring of Pneumonia Symptoms Purnomo, Ariana Tulus; Frandito, Raffy; Limantoro, Edrick Hensel; Djajasoepena, Rafie; Bhakti, Muhammad Agni Catur; Lin, Ding Bing
Indonesian Journal of Computing, Engineering, and Design (IJoCED) Vol. 6 No. 1 (2024): IJoCED
Publisher : Faculty of Engineering and Technology, Sampoerna University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35806/ijoced.v6i1.395

Abstract

Pneumonia is one of the most common contagious respiratory diseases, and one of its symptoms is shortness of breath. This symptom underscores the need for non-contact monitoring methods, which our paper addresses by proposing a strategy that uses Frequency-Modulated Continuous Wave (FMCW) radar to extract breathing waveforms and then classifies them with an eXtreme Gradient Boosting (XGBoost) model. The model performs well on our dataset, using stratified k-fold cross-validation and Mel-Frequency Cepstral Coefficients (MFCC) feature extraction. This intelligent system can correctly identify deep and deep-quick breathing patterns with 98% and 87.5% recall scores, respectively. Integrating FMCW and XGBoost offers a promising solution for early detection and real-time monitoring of pneumonia