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1.
12th International Conference on Virtual Campus, JICV 2022 ; 2022.
Article in English | Scopus | ID: covidwho-2161458

ABSTRACT

Indonesia implemented the online learning system during COVID-19. These changes were associated with the country's vast and archipelago-shaped area. Therefore, this research aimed to examine online learning publication trend during the pandemic using bibliometric analysis. The results showed that 2021 had the most publications on online learning during the pandemic, with 259. The frequently used keywords included online learning (n = 95), COVID-19 (n = 71), and e-learning (n = 70). Santoso HB had the most publications with 14 documents, while Junus K and Sulisworo D had 7. Jakarta State University had the most publications, including 8 documents, 8 citations, and 23 link strengths. Ahmad Dahlan University had 6 documents, 9 citations, and 1 link strength. Indonesia and Malaysia had the most collaborations with 29 publications. Future research can be developed using motivational learning and the post-COVID-19 school system as keywords. Furthermore, this research provided a thematic trend visualization map for future research to develop educational concepts and policies on online learning, specifically in archipelagic countries such Indonesia. © 2022 IEEE.

2.
12th International Conference on Virtual Campus, JICV 2022 ; 2022.
Article in English | Scopus | ID: covidwho-2161457

ABSTRACT

This article aims to describe student responses when implementing SFH and provide an outline of six recommendations for the implementation of online learning during COVID-19, with the expectancy that learning under any conditions will continue to run benevolently. This study had a total of 693 participants with 416 (60%) women and 277 (40%) men, with a vulnerable age 17-24 years. In total, 34 universities across Indonesia participated in this study. This study uses online surveys as a method of collecting qualitative research. In this situation, the state, to respond to instruction on integrating online learning during the epidemic in universities, was given recommendations. In order to make conclusions easily understood by researchers and readers, data is organized into categories and described as units. During COVID-19, the Ministry of Education and Culture prepares educational regulations that are socialized via digital media. Online learning rose by 10.3% between COVID-19 and prior. WhatsApp is utilized 38.2% and Google Classroom 34.92%. This article also discusses some student feedback and complaints. The education office and school have strong communication. However, it is vital to adopt national rules connected to online learning that do not burden schools, students, teachers, or parents. Aside from that, the government should work with local and international online education software developers. Ensuring that education continues to run ideally in Indonesia, despite its limitations and issues, by developing a standard operating process for online learning evaluation. © 2022 IEEE.

3.
Emerging Science Journal ; 5(Special issue):157-181, 2021.
Article in English | Scopus | ID: covidwho-1594359

ABSTRACT

Inhalation therapy is one of the most popular treatments for many pulmonary conditions. The proposed Covid-19 aromatherapy robot is a type of Unmanned Ground Vehicle (UGV) mobile robot that delivers therapeutic vaporized essential oils or drugs needed to prevent or treat Covid-19 infections. It uses four omnidirectional wheels with a controlled speed to possibly move in all directions according to its trajectory. All motors for straight, left, or right directions need to be controlled, or the robot will be off-target. The paper presents omnidirectional four-wheeled robot trajectory tracking control based on PID and odometry. The odometry was used to obtain the robot's position and orientation, creating the global map. PID-based controls are used for three purposes: motor speed control, heading control, and position control. The omnidirectional robot had successfully controlled the movement of its four wheels at low speed on the trajectory tracking with a performance criterion value of 0.1 for the IAEH, 4.0 for MAEH, 0.01 for RMSEH, 0.00 for RMSEXY, and 0.06 for REBS. According to the experiment results, the robot's linear velocity error rate is 2%, with an average test value of 1.3 percent. The robot heading effective error value on all trajectories is 0.6%. The robot's direction can be monitored and be maintained at the planned trajectory. © 2021 by the authors.

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