Financial Technology: Digital Legal Challenges and Indonesia's Economic Prospects After Covid-19 Outbreak

Online loans are one of the financing business models organized using applications on the internet, the online loan business is currently developing so fast because it offers loans that can reach a sufficiently large amount with easy terms, procedures and transaction processes, all intended to improve people's economic conditions. However, its implementation still sparks many legal problems and presents challenges for digital law in Indonesia. This study aims to study the challenges faced by Indonesian digital law due to the growth of the online loan business and to explore how the prospects of the online loan (fintech) business in improving the economic conditions of the Indonesian people. This research used empirical juridical methods, a case, and a statutory approach. The results showed that the challenges faced by Indonesian law in anticipating the growth of online businesses tainted by various legal cases require a more comprehensive rule of law in the form of legislation, thereby supporting the growth of prospects of the online loan business in an effort to improve the economy of the people of the state. © 2022, University of Muhammadiyah Malang. All rights reserved.

Mask Detection Using Convolutional Neural Network

COVID-19 virus has hit Indonesia since early March 2020. One of the government's efforts to prevent the spread of COVID-19 is to do physical distancing to require people to wear masks when doing activities outside the home. One way to overcome this problem is by detecting mask users to be more obedient and obedient to the rules, then the identification process is carried out for mask users and those who do not use masks. The process is carried out using the Convolutional Neural Network method. CNN is known to be superior and does not require pre-processing so it saves more time. In terms of algorithmic competence, CNN is considered capable of carrying out the data detection process well. Of the 1376 datasets used, 30 epochs, accuracy = 0.988, recall = 0.990, precision = 0.987, and F1 = 0.988 with the required detection time for each image between 4 to 5 seconds. © 2022 IEEE.

Indonesian Twitter Sentiment Analysis Application on the Covid l9 Vaccine Using Naive Bayes Classifier

It's even one year since the COVID-19 pandemic hit Indonesia, to anticipate it, the government brought in a COVID-19 vaccine. Various types of COVID-19 vaccine have been introduced to Indonesia, including which ones will be considered the best according to the community through the Twitter platform. One of the venues that creates the most public sentiment is Twitter. It can be determined whether the public fully approves or rejects the existence of vaccination in Indonesia by analyzing public sentiment surrounding the COVID-19 vaccine. Data acquisition using a crawling procedure by connecting the Twitter API, pre-processing, sentiment categorization, and sentiment analysis outcomes are the stages of the sentiment analysis process to become a sentiment analysis application. The PHP and MySQL programming languages are used to create the database for the sentiment analysis application. After the application has been fully implemented, it can do sentiment analysis from each dictionary probability using the Naive Bayes Classifier approach. The study of the two keywords "vaksin covid"and "vaksin corona"yielded the following results. It has 93% positive sentiment results, 72% negative sentiment results, and 35% neutral sentiment outcomes, with an accuracy of 94.74% and 75.47% per keyword. Meanwhile, the Sinopharm vaccine, which has the most positive attitude with the terms "vaksin sinovac,""vaksin astrazeneca,""vaksin sinopharm,"and "vaksin nusantara,"has 84 percent tweets with a 74.23% accuracy rate. © 2021 IEEE.

Mapping Spread Virus COVID-19 in India Using K-Means Clustering

Covid have confirmed as pandemic global by the World Health Organization (WHO), because spread that very fast among humans. As a result of the Covid-19 virus, many infected patients died, including from all countries on the Asian continent. Like the case that occurred in one of the Asian countries, namely India, which is one of the countries that experienced a spike in Covid-19 cases, the transmission of thevirus Covid-19 in India penetrated more than 400,000 cases in 1 day. The number is the highest daily record set by India during the Covid-19 pandemic. However, it was found that the problem of the spread of Covid-19 tends to increase, this is the country with the second largest population in the world. The total number of Covid-19 cases in the country has reached 21 million or second only to the United States. The vastness of India's territory allows the need for grouping the parts by region in India. This grouping produces the center points for the spread of Covid-19 cases. The purpose of grouping Covid-19 cases based on clusters is to find out the weight/percentage value generated from each of these clusters using the K-Means Clustering method. This method is used to map the spread of the Covid-19 virus from various regions in India based on confirmed cases, dead, recovered and active/new clusters. The benefits obtained for the government in overcoming Covid-19 cases are to create strategies to prevent the spread of Covid-19 based on information from the results of regional clustering in India The results obtained from research conducted in 38 regions in India using 4 clusters resulted in Confirmed cases (C0) 199 items, Died (C1) 779 items, Recovered (C2) 21 items, and Active/new cluster (C3) 231 items with a totalcluster of 1230items. © 2021 IEEE.

Pendataan dan penyaluran bantuan langsung tunai dana Desa penanggulangan COVID-19 oleh pemerintah desa di Kecamatan Depati VII, Kabupaten Kerinci

The data collection and distribution of the Village Fund Direct Cash Assistance (BLT) by the Village Head is the implementation of the Central Government program in order to help ease the economic burden of the poor who are affected by the COVID-19 outbreak. The data collection and distribution of Village Funds is carried out through the respective Village Heads so that the assistance can be distributed smoothly and on target according to the goals that have been set including in the District of Depati VII Kerinci Regency. However, in its implementation data collection and distribution activities are in the spotlight because there are discrepancies with the expected goals. Therefore, this study aims to further discuss the implementation of data collection and distribution of the Village Fund BLT Fund in the District of Depati VII, Kerinci Regency and the problems encountered in it.