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* Corresponding Author
Indonesian Twitter User Sentiment towards PeduliLindungi App in Strengthening Smart Living during COVID-19
https://doi.org/10.22146/ikat.v6i2.89824 Rendy Kurniawan(1), Rini Rachmawati(2*)
(1) Gadjah Mada University
(2) Gadjah Mada University
(*) Corresponding Author
Abstract
The COVID-19 pandemic has changed lifestyles in counties and cities in just a few months by putting technology at the forefront of fighting the pandemic. Handling COVID-19 can show technological disparities and inequalities between different cities, given the COVID-19 condition that continues to plague various towns and districts in Indonesia. One of the steps to handle it, namely providing national-scale public services with a COVID-19 tracker application called PeduliLindungi. Using the PeduliLindungi app in each city and Regency is a form of Smart City implementation in Indonesia, especially in the Smart Living dimension. PeduliLindungi is a must-have app for residents who move or enter public facilities to create a safe and healthy city during the COVID-19 pandemic. Given the WFH trend, Twitter has become an abundant data source to collect public opinion regarding PeduliLindungi applications needed to improve service quality. This study aims to analyze Twitter users’ sentiments towards the PeduliLindungi app usage in the context of strengthening smart living. Sentiment analysis was performed in this study using the VADER Sentiment towards tweets dataset collected over two different periods. The results show that the Indonesian government effectively uses Twitter to answer questions and share COVID-19 and PeduliLindungi-related information with the public. Negative sentiment was expressed more towards the PeduliLindungi app than positive sentiment due to public unrest over data security and constraints encountered in using the PeduliLindungi app.
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Allam, Z.; Jones, D. S. On the Coronavirus (COVID-19) Outbreak and the Smart City Network: Universal Data Sharing Standards Coupled with Artificial Intelligence (AI) to Benefit Urban Health Monitoring and Management. Healthcare 2020, 8 (1), 46. [CrossRef] Attaran, H.; Kheibari, N.; Bahrepour, D. Toward Integrated Smart City: A New Model for Implementation and Design Challenges. GeoJournal 2022. [CrossRef]. Branchi, P.; Fernández-Valdivielso, C.; Matias, I. Analysis Matrix for Smart Cities. Future Internet 2014, 6 (1), 61–75. [CrossRef] CNBC Indonesia. Available online: https://www.cnbcindonesia.com/tech/20210903114615-37-273446/sertifikat-vaksin-jokowi-bocor-netizen-apalagi-data-kita (accessed on 22 September 2021) Das, D.; Zhang, J. J. Pandemic in a Smart City: Singapore’s COVID-19 Management through Technology & Society. Urban Geography 2021, 42 (3), 408–416. [CrossRef]. Djalante, R.; Lassa, J.; Setiamarga, D.; Sudjatma, A.; Indrawan, M.; Haryanto, B.; Mahfud, C.; Sinapoy, M. S.; Djalante, S.; Rafliana, I.; Gunawan, L. A.; Surtiari, G. A. K.; Warsilah, H. Review and Analysis of Current Responses to COVID-19 in Indonesia: Period of January to March 2020. Progress in Disaster Science 2020, 6, 100091. [CrossRef]. Gërguri-Rashiti, S.; Abazi-Alili, H.; Dika, Z. The Use of ICT in the Decision Making Process: The Case of Macedonian Entre-preneurial Businesses. In Entrepreneurship in the Balkans; Ramadani, V., Schneider, R. C., Eds.; Springer Berlin Heidelberg: Berlin, Heidelberg, 2013; pp 339–366. [CrossRef]. Giffinger, R.; Gudrun, H. Smart Cities Ranking: An Effective Instrument for the Positioning of the Cities? ACE: Architecture, City and Environment 2010, 4 (12), 7–26. [CrossRef]. Hermawan, L.; Bellaniar Ismiati, M. Pembelajaran Text Preprocessing Berbasis Simulator Untuk Mata Kuliah Information Retrieval. JT 2020, 17 (2), 188. [CrossRef]. Hutto, C.; Gilbert, E. VADER: A Parsimonious Rule-Based Model for Sentiment Analysis of Social Media Text. ICWSM 2014, 8, 216-225. Indurkhya, N.; Damerau, F. J. Handbook of Natural Language Processing; Chapman & Hall/CRC: Boca Raton, FL, 2010. Ji, X.; Chun, S. A.; Geller, J. Knowledge-Based Tweet Classification for Disease Sentiment Monitoring. In Sentiment Analysis and Ontology Engineering; Pedrycz, W., Chen, S.-M., Eds.; Springer International Publishing: Cham, 2016; Vol. 639, pp 425–454. [CrossRef]. Kaur, A., & Gumber, N. Sentimental Analysis on Application Reviews on Educational Apps. International Journal of Engineering and Technical Research (IJETR) 2014, 2, 16-19. Kementerian Kesehatan Republik Indonesia. Available online: https://sehatnegeriku.kemkes.go.id/baca/rilis-media/20210704/0738021/pemerintah-integrasikan-data-kesehatan-dengan-aplikasi-pedulilindungi-untuk-mencegah-pemalsuan-hasil-tes-covid-19-sebagai-syarat-perjalanan/ (accessed on 20 September 2021). Kim, K.-S.; Sin, S.-C. J.; Yoo-Lee, E. Y. Undergraduates’ Use of Social Media as Information Sources. CRL 2014, 75 (4), 442–457. [CrossRef] Kunzmann, K. R. Smart Cities After Covid-19: Ten Narratives. disP - The Planning Review 2020, 56 (2), 20–31. [CrossRef]. Kurniawati; Khadapi, M.; Riana, D.; Arfian, A.; Rahmawati, E.; Heriyanto. Public Acceptance Of Pedulilindungi Application In The Acceleration Of Corona Virus (Covid-19) Handling. J. Phys.: Conf. Ser. 2020, 1641 (1), 012026. [CrossRef]. Kylili, A.; Afxentiou, N.; Georgiou, L.; Panteli, C.; Morsink-Georgalli, P.-Z.; Panayidou, A.; Papouis, C.; Fokaides, P. A. The Role of Remote Working in Smart Cities: Lessons Learnt from COVID-19 Pandemic. Energy Sources, Part A: Recovery, Utilization, and Environmental Effects 2020, 1–16. [CrossRef]. PeduliLindungi. Available online: https://www.pedulilindungi.id/ (accessed on 20 September 2021). Puri, M.; Dau, Z.; Varde, A. S. COVID and Social Media: Analysis of COVID-19 and Social Media Trends for Smart Living and Healthcare. SIGWEB Newsl. 2021, No. Autumn, 1–20. [CrossRef] Rachmawati, R.; Choirunnisa, U.; Pambagyo, Z. A.; Syarafina, Y. A.; Ghiffari, R. A. Work from Home and the Use of ICT during the COVID-19 Pandemic in Indonesia and Its Impact on Cities in the Future. Sustainability 2021b, 13 (12), 6760. [CrossRef] Rachmawati, R. Pengembangan Perkotaan Dalam Era Teknologi Informasi Dan Komunikasi, Cetakan kedua.; Gadjah Mada University Press: Yogyakarta, 2018. Rachmawati, R. Pengembangan Smart Village Untuk Penguatan Smart City Dan Smart Regency. JSC 2018, 1 (2), 12–19. [CrossRef]. Rachmawati, R.; Sari, A. D.; Sukawan, H. A. R.; Widhyastana, I. M. A.; Ghiffari, R. A. The Use of ICT-Based Applications to Support the Implementation of Smart Cities during the COVID-19 Pandemic in Indonesia. Infrastructures 2021a, 6 (9), 119. [CrossRef]. Rachmawati, R. Toward Better City Management through Smart City Implementation. hgeo 2019, 13 (2). [CrossRef]. Raila, T. A.; Rosadi, S. D.; Permata, R. R. PERLINDUNGAN DATA PRIVASI DI INDONESIA DAN SINGAPURA TERKAIT PENERAPAN DIGITAL CONTACT TRACING SEBAGAI UPAYA PENCEGAHAN COVID-19 SERTA TANGGUNGJAWAB-NYA. khdk 2021, 2 (1), 1. [CrossRef]. Statista. Available online: https://www.statista.com/statistics/242606/number-of-active-twitter-users-in-selected-countries/ (accessed on 20 September 2021). The Conversation. Available online: https://theconversation.com/smart-cities-can-help-us-manage-post-covid-life-but-theyll-need-trust-as-well-as-tech-138725 (accessed on 22 September 2021). Varghese, C.; Pathak, D.; Varde, A. S. SeVa: A Food Donation App for Smart Living. In 2021 IEEE 11th Annual Computing and Communication Workshop and Conference (CCWC); IEEE: NV, USA, 2021; pp 0408–0413. [CrossRef]. Wearesocial. Available online: https://wearesocial.com/digital-2021/ (accessed on 20 September 2021). WHO. Coronavirus Disease 2019 (COVID-19) Situation Report – 68; 2021b. WHO. COVID-19 PHEIC Global research and Innovation forum: towards a research roadmap; 2021a.
DOI: https://doi.org/10.22146/ikat.v6i2.89824
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