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Journal : IJIIS: International Journal of Informatics and Information Systems

The Naive Bayes Algorithm in Predicting the Spread of the Omicron Variant of Covid-19 in Indonesia: Implementation and Analysis Jeffri Prayitno Bangkit Saputra; Racidon P Bernarte
International Journal of Informatics and Information Systems Vol 5, No 2: March 2022
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/ijiis.v5i2.131

Abstract

Indonesia was struck by an epidemic of the corona virus in the start of March 2020, according to official reports (covid). Indonesia continues to see a rise in the number of cases of covid-19 spreading on a daily basis. The general people are urged to engage in social distancing in order to disrupt the development of COVID-19, which has spread across Indonesia's numerous areas. For this reason, this research was undertaken as a preemptive step against the Covid-19 pandemic by estimating the extent of the Omicron variety of Covid-19's spread around the world, with a particular emphasis on Indonesia. The research methodologies employed in this study were problem analysis and literature review, as well as data gathering and execution. The Naive Bayes technique is thought to be capable of estimating the degree of COVID-19 dissemination in Indonesia. The results of the Naive Bayes method classification study revealed that 16 data from 33 data tested for Covid-19 cases per province were correctly classified with an accuracy of 46.4252 percent, while 16 data from 33 data tested for Covid-19 cases per province were misclassified with an accuracy of 46.4252 percent.
The Impact of Servicescape Perception on Perceived E-Commerce Value and Client Loyalty Jeffri Prayitno Bangkit Saputra
International Journal of Informatics and Information Systems Vol 4, No 3: December 2021
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/ijiis.v4i3.118

Abstract

While previous research on e-servicescapes has focused on the ordinary Internet user, several studies show that heavy Internet users are the target audience. To maximize firm profitability, it is vital to understand the nature of heavy user consumption; hence, this study examines the primary components of e-servicescapes and their relationship to buy intent using moderated data from heavy and light Internet users. Three hundred and forty-two genuine internet users with online purchasing experience answered an online questionnaire, and discrepancies were determined using structural equation modeling. For ordinary users, aesthetic appeal and interaction are significant factors in purchase intention; for heavy users, interactivity is the most important attribute, followed by aesthetic appeal, layout, and functionality; and for light users, aesthetic appeal is the sole consideration. Additionally, our data show that financial stability does not help heavy, regular, or light users. We demonstrate how heavy and light Internet users evaluate e-servicescapes to signal quality attributes and contribute to their cognitive responses and purchase intentions based on their consumption traits by integrating purchase intentions with e-service quality and segmentation theory in e-servicescapes. It is advised that online merchants identify heavy and light users, rethink their current e-servicescapes, and apply more tailored marketing methods to attract and retain heavy and light users, as well as increase their purchase intent. While this study concentrated on the most salient characteristics of heavy users, more research is required to explicate additional critical mediators. This poll makes no mention of the three kinds of websites or product qualities. Finally, demographic and psychological variables such as gender and personal characteristics may act as significant mediators in the link between the e-servicescape and purchase intention, but their relevance requires more research.