A socio-economic analysis of the role of medical drones in the era of the COVID-19 pandemic

Coronavirus is a large family of viruses that cause illness ranging from mild to severe symptoms. The high and fast transmission rate causes all activities in various fields, including the health and economic sector, to be carried out with caution. Different technologies are also developed to support health workers' performance and financial circumstances, including drones in multiple aspects of medical needs ranging from delivering drugs and medical devices to carrying out vital sign checks. This study uses a qualitative descriptive. Data was obtained utilizing observation and literature study. Medical drones have a strategic role in fighting the COVID-19 pandemic, starting from the enforcement of social distancing programs, COVID-19 transport specimens to disinfection facilities in large areas. Medical drones are the latest technology in the medical field that helps medical performance improve healthcare service quality. The use of drones in the health sector needs to be further developed. © 2022 Institute of Society Transformation. All rights reserved.

Website design analysis for the management and promotion of micro, small, and medium-sized enterprises (MSMEs) in the Covid-19 pandemic period

Micro, Small, and Medium-sized Enterprises (MSMEs) have an essential and strategic role in national economic development. During the Covid-19 pandemic, MSMEs experienced a negative impact by decreasing the sales turnover of products sold. This is due to the Social Distancing and Large-Scale Social Restrictions policies implemented by the government to prevent the spread and transmission of Covid-19. As a result, MSMEs product sales transactions that have been carried out offline cannot be done, so that the sales of MSMEs products have decreased. The decline in product sales turnover is a challenge for MSMEs during the Covid-19 pandemic. The slump in sales turnover experienced by MSMEs is a common challenge because MSMEs is one of the sectors that can drive national economic growth. One solution to overcome these challenges is to use online media such as websites. This study has analysed website design that can be implemented into an MSMES marketplace website as a medium for managing and promoting MSMEs products. There are several steps taken. Namely, data collection and website needs analysis. The data collection stage was carried out using the method of literature study, observation, and interviews. Meanwhile, the needs analysis stage consists of two stages: The data processing and data analysis stages. The system design stages are then carried out by designing the Unified Modeling Language (UML) system. The resulting UML designs include use cases, activity diagrams, sequence diagrams, and class diagrams. The UML design results that have been done can be implemented into a website for management, promotion, and online sales transactions of MSMEs products for MSMEs. © 2023 Author(s).

Evaluation of the Universitas Jenderal Soedirman e-learning website (Eldiru) using the WebQual 4.0 method

The Covid-19 pandemic has repercussions in a variety of areas, including health, the economics, and education. The most noticeable impact in the education sector is the implementation of the learning process. Before the Covid-19 epidemic was carried out in the real world, it became an online learning experience. This is to stop the Covid-19 virus from spreading. Jenderal Soedirman University (UNSOED), one of the educational institutions, has forced lecturers and students to conduct online learning since early March 2020 to avoid the spread of the Covid-19 virus. Eldiru, a UNSOED e-learning website, is used for the learning. This study assesses the website's quality. The quality of an E-Learning website might have an impact on the online learning process. The WebQual 4.0 approach is used to assess Eldiru's quality in this study. WebQual 4.0 employs four instruments: usability, information quality, service interaction, and user satisfaction. The research was conducted by conducting a survey of lecturers and students with a total of 50 respondents. The results showed that the variables usability, information quality, service interaction, and user satisfaction have a dominant influence on online learning. © 2023 Author(s).

MODIFICATION OF K-MEANS AND K-MODE ALGORITHMS TO ENHANCE THE PERFORMANCE OF CLUSTERING STUDENT LEARNING STYLES IN THE LEARNING MANAGEMENT SYSTEM

During the Corona Virus Disease (COVID-19) pandemic, many access to learning used the e-learning system through the Learning Management System (LMS) platform. One of the weaknesses of the learning process through e-learning is that it cannot detect student learning styles based on actual behavior patterns during online learning. Most of the methods used to study automatic detection techniques use classification methods. One of the weaknesses of the classification method is the determination of class labels, so a learning style detection model was developed using the concept of clustering before classification to produce class labels with a high level of validation. This study focuses on increasing the validity of the clustering method by comparing the performance of the modified K-Means and K-Mode algorithms. The proposed modification of the two algorithms is carried out at the initial centroid determination stage. The performance of the two modified algorithms was carried out by measuring the validation values of the Davies-Bouldin Index (DBI) and Silhouette Index (SI) using log file data from 88 students taking computer programming courses. The validation results of the DBI and SI values indicate that the proposed model has better performance when implemented in the K-Mode algorithm than the K-Means algorithm. © 2023 ICIC International.

ANALYSIS OF COMMUNITY ACTIVITY RESTRICTION POLICY (PPKM) DURING THE COVID-19 PANDEMIC

The purpose of this study was to determine community activities during the implementation of the activity restriction policy (Indonesian: Pemberlakuan Pembatasan Kegiatan Masyarakat, PPKM) during the COVID-19 pandemic in Medan city. The type of research method is a quantitative descriptive study using a survey design. The instrument used in this research is a questionnaire. The sampling technique was using accidental sampling so that the number of samples obtained was 790 people. The findings of this study are that the characteristics and economic activities of the people of Medan city during the implementation of PPKM are in the essential sector of as many as 423 respondents (53.6%). Quantitatively, this figure is high because it is above 50% when compared to the non-essential sector, which is less than 367 respondents (47.4%). PPKM officers need to ensure that employees who do not work in the office are for non-essential sector companies that run work from home (WFH) to avoid the spread of COVID-19. The selection of appropriate policies and public obedience to government policies related to activity restrictions can break the chain of the spread of COVID-19 in Medan city. © 2022 The Authors.

The application of instrumentation system on a contactless robotic triage assistant to detect early transmission on a COVID-19 suspect

This article discusses the instrumentation system of airlangga robotic triage assistant version 1 (ARTA-1), a robot used as a contact-free triage assistant for Coronavirus disease (COVID-19) suspects. The triage process consists of automatic vital signs check-up as well as the suspect’s anamnesis that in turns will determine whether the suspect will get a specific care or not. Measurements of a suspect’s vital conditions, i.e. temperature, height, and weight, are carried out with sensors integrated with the Arduino boards, while a touch-free, hand gesture questions and answers is carried out to complete anamnesis process. A portable document format (PDF) format of the triage report, which recommends what to do to the suspect, will then be automatically generated and emailed to a designated medical staff. © 2021 Institute of Advanced Engineering and Science. All rights reserved.

Role of parents in improving children's fine motor skills at home during the COVID-19 pandemic

This study discusses the role of parents in improving children's fine motor skills at home during the COVID-19 pandemic. fine motor is a motor activity that involves the activity of small or smooth muscles. This movement requires eye and hand coordination and good motion control that enables it to perform accuracy and precision in motion. The purpose of this study is the role of parents in stimulating fine motor skills during the COVID-19 pandemic, and what are fine motor activities that can be done with children while at home. This research uses a literature study method. The results of this study explain what role parents do in improving children's fine motor skills at home and describe the fine motor activities that can be carried out during the COVID-19 pandemic. The author hopes that the results of this study can provide benefits and inspiration, especially for parents of toddlers and for readers in general. © 2020 ACM.

Predicting the Number of COVID-19 Sufferers in Malang City Using the Backpropagation Neural Network with the Fletcher-Reeves Method

COVID-19 is a type of an infectious disease that is caused by the new coronavirus. The spread of COVID-19 needs to be suppressed because COVID-19 can cause death, especially for sufferers with congenital diseases and a weak immune system. COVID-19 spreads through direct contact, wherein the infected individual spreads the COVID-19 virus through cough, sneeze, or close contacts. Predicting the number of COVID-19 sufferers becomes an important task in the effort to curb the spread of COVID-19. Artificial neural network (ANN) is the prediction method that delivers effective results in doing this job. Backpropagation, a type of ANN algorithm, offers predictive problem solving with good performance. However, its performance depends on the optimization method applied during the training process. In general, the optimization method in ANN is the gradient descent method, which is known to have a slow convergence rate. Meanwhile, the Fletcher-Reeves method has a faster convergence rate than the gradient descent method. Based on this hypothesis, this paper proposes a prediction model for the number of COVID-19 sufferers in Malang using the Backpropagation neural network with the Fletcher-Reeves method. The experimental results show that the Backpropagation neural network with the Fletcher-Reeves method has a better performance than the Backpropagation neural network with the gradient descent method. This is shown by the Means Square Error (MSE) resulting from the proposed method which is smaller than the MSE resulting from the Backpropagation neural network with the gradient descent method. © 2021 Syaiful Anam et al.

Time Series Analysis for Understanding Local Policy Impact of COVID-19 Cases in East Java

Daily new cases of COVID-19 as a series of data points ordered in time is one representation of time series data. Our works expect to understand the data characteristics that is related to existing government policies. This paper aims to highlight the impact report and analyses of some COVID-19 policies in East Java province districts. The study is focused on the policy execution before and during the new normal situation of COVID-19 using time series data of new cases as possible and easily observable results. Aside from time series analysis, some visual analysis is performed as well. The experiments focused on some questions related to the policy effectiveness: finding patterns of daily new cases to instigate the need for other local policies and understanding any precedence on occurred cases for nearby districts. Although the second question is not confirmable, the first question verifies more tightened social distancing is still necessary for the new normal. © 2020 IEEE.

Smart Development of Big Data App for Determining the Modelling of Covid-19 Medicinal Compounds Using Deep AI Core Engine System

Smart Big Data App Using Deep Artificial Intelligence (AI) Core Engine System focuses on solving problems related to the difficulty in building a prototyping model computer simulation like in silico as a model initiation of the complex Covid-19 medicinal compound involving Big Data ecosystems such as Hadoop and Spark. The difficulty is for example, currently, it is still very arduous to measure the rate of mixture of a compound when combined with many other compounds, which can consider the trade-off in minimizing the negative effects but optimizing the positive effects. In addition, the computation time becomes very long when using a system that is not in the Big Data ecosystem since this is proportional to the large number of compounds that vary widely and also the number of different situations of Covid-19 patients with other congenital diseases (comorbid) or without congenital disease;thus, it can be considered to be included in a condition that requires a very complex computational process which is very difficult to model using a conventional mathematical approach because the calculations are certainly very complex when compared to approaches using meta-heuristics algorithms such as Particle Swarm Optimization (PSO) which is much easier but requires a very large particle population space and iterative process to achieve global convergence. As a consequence, it requires fast computation processes based on distributed computing such as using the Big Data ecosystem. From the review of these problems, the system was created based on the Computational Intelligence;hence, the end-users, especially the developers, can build an application easier in spite of the complex computations, one of the which is in the meta-heuristic technique to minimize the negative effects and optimize the positive effects of the medicinal compounds by including a lot of data to get a better modeling. Therefore, the prototyping modeling project can be quick and robust, and achieve high performance measurements. © Published under licence by IOP Publishing Ltd.