Aplikasi Pedulilindungi Mitigasi Bencana Covid-19 Di Indonesia

Abstract

In addition to adequate information about the potential for the Covid-19 disaster that has hit the world, especially Indonesia, mistakes in communicating information can cause uncertainty that worsens the situation. This study aims to analyze the disaster analysis model in the protected care application created by the government as a form of disaster mitigation in this country. This study uses a qualitative descriptive method. The object of the research is the disaster communication model in the Pedulilindung application launched by KOMINFO. The subjects of this research are parties involved in making the idea of a protected application, namely the head of the Public Relations Bureau of KOMINFO Mr. Ferdinandu Setu and also the users of the application. Methods of data collection using in-depth interviews and observations. as a result, KOMINFO conducts disaster response with a disaster communication model which includes, among others, information, communication, coordination, disaster mitigation and the media. media involvement ensures messages and information conveyed are accurate, fast and precise, targeting the use of social media in Indonesia to the fifth largest in the world, but the result is that many Indonesians are reluctant to use the application because it is not effective.

Klasifikasi Sentimen Ulasan Pengguna Aplikasi PeduliLindungi di Google Play Menggunakan Algoritma Support Vector Machine dengan Seleksi Fitur Chi-Square

“…Oleh sebab itu, pemerintah Indonesia menciptakan sebuah aplikasi bernama PeduliLindungi. Aplikasi ini diharapkan mampu melindungi masyarakat Indonesia dengan saling berbagi lokasi saat bepergian agar contact tracing dengan orang yang terinfeksi virus dapat terus dilakukan sehingga dapat memperlambat dan menurunkan penyebaran virus corona [11]. Namun masih terdapat beberapa ulasan negatif dalam aplikasi tersebut diantaranya kesalahan informasi lokasi, aplikasi yang terlalu banyak menghabiskan daya, log-out otomatis sehingga pengguna harus memasukkan kode OTP berulang kali dan membutuhkan kecepatan internet tinggi.…”

“…Data Cleaning merupakan proses membersihkan karakter atau kata yang kurang memiliki pengaruh dalam proses text mining. Karakter yang dihapus atau dihilangkan berupa punctuation atau tanda baca, simbol-simbol, emoticon, link, karakter, angka dan lain-lain [11].…”

The Implementation Of The Care-Protect (Pedulilindungi) Application: The Economic Impact And Constraints Faced

“…From the data that has been collected, little information is obtained regarding the economic impact caused by the implementation of the PeduliLindungi application. However, in general, a screening process for people who will use public facilities is expected to reduce the potential for Covid-19 transmission in public spaces (Putri & Hamzah, 2021). On the other hand, the screening process for people who access public facilities through the PeduliLindungi application can also provide other benefits such as creating community economic productivity in public areas, such as in shopping centers while still implementing health protocols, so that it is expected to be able to create benefits that have a dual effect on the community and various aspects of community life.…”

Analisis Prilaku Pengguna Aplikasi Peduli Lindungi mengunakan Framework Technology Acceptance Model (TAM)

“…Salah satu upaya yang dilakukan pemerintah saat ini yaitu gencar melakukan vaksinasi massal dan melakukan tindakan pencegahan virus dengan meluncurkan aplikasi Peduli Lindungi yang dapat diakses oleh masyarakat dari perangkat seluler pribadi.Aplikasi ini juga dimanfaatkan untuk melakukan pendaftaran vaksinasi, scan QR untuk Check-In/Out dan dokumen perjalanan (Sefrika, 2021). Sejalan dengan pernyataan (Putri & Hamzah, 2021), penanggulangan bencana memerlukan pendekatan soft power, yaitu meningkatkan kewaspadaan masyarakat dan memberikan informasi yang akurat tentang bencana.…”