Claim Missing Document
Check
Articles

Found 5 Documents
Search

Covid-19: Implementation e-voting Blockchain Concept Mustofa Kamil; Ankur Singh Bist; Untung Rahardja; Nuke Puji Lestari Santoso; Muhammad Iqbal
International Journal of Artificial Intelligence Research Vol 5, No 1 (2021): June 2021
Publisher : STMIK Dharma Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (568.049 KB) | DOI: 10.29099/ijair.v5i1.173

Abstract

The current situation of the Covid-19 pandemic is currently increasing public concern about the community. The government has especially recommended Stay at Home and the implementation of PSBB in various regions. One of the concerns is when the election of regional leaders to the general chairman. Even though there is already a safeguard regulation, this is not considered safe in the current Covid-19 pandemic. The solution in this research is the use of a blockchain-based E-voting system to help tackle election unrest during Covid-19. Where e-voting with blockchain technology can be carried out anywhere through the device without the need to be present in the voting booth, reducing data fraud, accurate and decentralized voting results that can be accessed by the public in real-time. The use of cryptographic protocols is applied for data transfer between system components as well as valid system security. This research method uses SUS trial analysis in a significant system of the Covid-19 pandemic situation. The implication that the SUS Score analysis shows 90 shows an acceptable E-voting system, meaning that the community can accept it because it brings positive and significant impacts such as effectiveness and efficiency.
The Impact Of Online System on Health During Covid 19: A Comprehensive Study Bhupesh Rawat; Ankur Singh Bist; Untung Rahardja; Chandra Lukita; Dwi Apriliasari
ADI Journal on Recent Innovation Vol. 3 No. 2 (2022): March
Publisher : ADI Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34306/ajri.v3i2.654

Abstract

COVID-19 creates an unprecedented situation before humanity. Covid-19 has changed lives in all aspects, from education, industry and social life. However, the existence of Covid-19 has greatly impacted the field of education, where the applicable learning methods usually need to make drastic changes to decide the spread of Covid-19. The education sector is turning to online education because it is not possible to call students in schools and colleges. Technology online education is proving itself to be a cure for catastrophe and filling gaps. There are major challenges regarding student health due to the high use of mobile, tablet and computer screens. There are problems regarding student health in the application of technology online learning, in this paper we make a detailed study of the same problem with the ultimate goal of research to find out the preventive measures. In this paper, we use the literature study method to explore negative cases in terms of obtaining negative reasoning due to excessive screen use during the COVID-19 scenario
Quantum Computing and AI: Impacts & Possibilities Bhupesh Rawat; Nidhi Mehra; Ankur Singh Bist; Muhamad Yusup; Yulia Putri Ayu Sanjaya
ADI Journal on Recent Innovation Vol. 3 No. 2 (2022): March
Publisher : ADI Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34306/ajri.v3i2.656

Abstract

Quantum computing is one of the emerging technologies. Different communities and research organizations are working to bring quantum computing applications into reality. Artificial Intelligence is another emerging area and getting stable with time. This paper, the main objective is to find out the impact of quantum computing research growth for AI applications. Thus, the method used in this study uses computational methods. so that this research can be concluded regarding the growing impact of quantum computing research for a given AI application. This paper also presents the impact and possibilities of quantum computing in the field of artificial intelligence.
Analysis Of Deep Learning Techniques For Chest X-Ray Classification In Context Of Covid-19 Vertika Agarwal; M. C. Lohani; Ankur Singh Bist; Eka Purnama Harahap; Alfiah Khoirunisa
ADI Journal on Recent Innovation Vol. 3 No. 2 (2022): March
Publisher : ADI Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34306/ajri.v3i2.659

Abstract

Coronaviruses (COV) are a large family of viruses that cause illness ranging from common cold to more severe disease such as MIDDLE EAST RESPIRATORY SYNDROME (MERS-COV) and SEVERE ACUTE RESPIRATORY SYNDROME (SARS-COV). Common signs of infection include respiratory symptoms, Fever, Cough, Shortness of breath and breathing difficulties. In severe cases, infection can cause pneumonia, severe acute respiratory syndrome, kidney failure and even death.3-Tier strategy is employed by government to combat this virus i.e., Track, Test and Treat. So, there is a need to increase the testing speed but the main stumbling block is the time RT-PCR takes which is around 2-3 days. In this situation, the recent research using Radiology imaging (such as Xray) techniques can be proven helpful to detect Covid 19. Latest deep learning techniques applied to Xray scans which rapidly detects the disease and thus reducing the time for testing. Moreover, it is accurate as compare to RT-PCR test where nose and mouth swabs are taken by lab technician which is prone to error.In this survey paper, ten different DL Techniques are surveyed which performs Xray classification with different accuracy. Different combination of Datasets are employed by these algorithms to improve the performance of their proposed model.Our paper evaluates the performance of each algorithm based on two parameters -Accuracy and Sensitivity.
An Exhaustive Analysis of Stress on Faculty Members Engaged in Higher Education Ankur Singh Bist; Bhupesh Rawat; Untung Rahardja; Qurotul Aini; Anggy Giri Prawiyogi
IAIC Transactions on Sustainable Digital Innovation (ITSDI) Vol 3 No 2 (2022): April
Publisher : Pandawan Sejahtera Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34306/itsdi.v3i2.533

Abstract

Higher education is the face of innovation for any country. The quality and dedication of professors help to maintain quality in this process. With time, parameters were raised to check the quality of professor attributes. In this paper, we discuss all possible parameters taken by universities to evaluate faculty performance. Gradually it grew overhead pressure on professors and impacted the teaching-learning process. Our paper focused on stress parameters with possible solutions for the same issue. The process consists of several parameters to evaluate an employee's performance, such as no publications in conferences and journals, no patents filed, additional responsibilities performed, other qualifications achieved, result in the analysis of courses taught, etc. Still, it also puts a lot of pressure on both of them because they have to balance all this extra work and teaching. This paper focuses on different faculty assessment parameters and their impact on the faculty teaching-learning process. We also propose possible solutions on how this stress can be alleviated, and the existing strategy can be simplified.