ABSTRACT
SMPN 174 Jakarta is a junior high school in East Jakarta that has 719 students and 22 classrooms, including being one of the schools with government programs in the form of assistance such as Smart Jakarta Card, Smart Indonesia Program, and School Operational Assistance. To meet educational needs and distribute to students who are entitled to assistance. Currently, the selection process for student beneficiaries at SMPN 174 Jakarta is still done manually, so there is a risk of making decisions that are not on target and require a longer time. Therefore, a decision support system was made to select students who receive assistance. The development of the decision support system used in this research is the Multi-Objective Optimization Method on the Basic of Ratio (MOORA). The tests include black-box testing and comparison testing of calculation results with manual calculations. The Decision Support System for Selection of Student Recipients for the Impact of COVID-19 has been successfully created, and the results of selecting recipients of this assistance are obtained based on the calculation of the highest optimization value. The verifier has approved them with a percentage of 66.7% strongly agreeing and 33.3% agreeing. © 2022 IEEE.
ABSTRACT
The 2010's has seen a dramatic increase in potential small launch vehicle contenders, defined as rockets capable of carrying at most 1000 kg to Low Earth Orbit. Spurred on by government programs such as the European Horizon 2020 or the American DARPA Launch Challenge, and the rapid proliferation of CubeSats and nanosatellites, more than 100 different commercial, semi-commercial, and government entities worldwide are now working on new entrants of this class. To date the most successful small launcher, the Northrop Grumman Pegasus has launched 45 times, but its flight rate has dropped to less than one a year. At the same time launch opportunities on ESPA rings, secondary slots on larger launchers, and CubeSat missions as cargo to the International Space Station have proliferated. Despite this seemingly bleak market environment, new entrants have emerged looking for a new magic formula. Others are new commercial entries from unexpected markets such as China. All are inspired by the success of SpaceX and the desire to capitalize on the perceived demand caused by the mega constellations. This paper presents an overview of the small satellite launch systems under development today. Capabilities, stated performance goals, cost, and funding sources are compared where available. This paper is a yearly update of a paper originally presented at the 2015 Conference on Small Satellites [1] and subsequently at the 2016 International Astronautical Congresses [2]. We also review the growing number of entrants that have dropped out since we first started this report. Despite the COVID- 19 pandemic, the authors discovered fifteen new systems under development and one system became operational in the past 12 months. Two other systems attempted their first flight in 2021 but were unsuccessful. The author welcomes any comments, feedback, or corrections. Copyright 2021 by Northrop Grumman Corporation. Published by the IAF, with permission and released to the IAF to publish in all forms.
ABSTRACT
One of the Indonesian government's programs in dealing with Covid19 problems is the Social Safety Net program which is given to the community, especially Covid19 assistance which is given every month to the community. Based on the assistance provided by the government, many people expressed their opinions through Twitter social media. This study aims to analyze the sentiment on Twitter tweets regarding the Social Safety Net Program from March to December 2020. The data collected is 4061 tweets data. The data is classified into two classes, namely positive and negative. The classification algorithm used is Gated Recurrent Unit (GRU). Hyperparameter testing is carried out in order to produce an optimal model. In the optimal GRU hyperparameter, when there are 10 GRU units, the activation function is sigmoid, the optimizer used is Adam, the batch size is 128, with 10 epochs of iteration and 0.2 dropout size. The GRU model produces an f1score of 92.09%, a precision of 90.34%, and a recall of 93.90%. © 2021 IEEE.
ABSTRACT
The COVID-19 public health emergency caused widespread economic shutdown and unemployment. The resulting surge in Unemployment Insurance claims threatened to overwhelm the legacy systems state workforce agencies rely on to collect, process, and pay claims. In Rhode Island, we developed a scalable cloud solution to collect Pandemic Unemployment Assistance claims as part of a new program created under the Coronavirus Aid, Relief and Economic Security Act to extend unemployment benefits to independent contractors and gig-economy workers not covered by traditional Unemployment Insurance. Our new system was developed, tested, and deployed within 10 days following the passage of the Coronavirus Aid, Relief and Economic Security Act, making Rhode Island the first state in the nation to collect, validate, and pay Pandemic Unemployment Assistance claims. A cloud-enhanced interactive voice response system was deployed a week later to handle the corresponding surge in weekly certifications for continuing unemployment benefits. Cloud solutions can augment legacy systems by offloading processes that are more efficiently handled in modern scalable systems, reserving the limited resources of legacy systems for what they were originally designed. This agile use of combined technologies allowed Rhode Island to deliver timely Pandemic Unemployment Assistance benefits with an estimated cost savings of $502,000 (representing a 411% return on investment). © 2020 Owner/Author.