WHAT DO INDONESIAN NETIZENS THINK ABOUT THE EMONEY? : A SENTIMENT ANALYSIS WITH MACHINE LEARNING

This study aims to identify the most popular topics and words in conversations in cyberspace with the issue of E-Money. In addition, the research aims to find out how netizens feel about E-Money with the help of Machine Learning. This study uses a quantitative method with a sentiment analysis approach using the Machine Learning program, namely Orange Data Mining. The data used are tweets originating from Twitter that were crawled from April 5, 2023, to April 12, 2023. Researchers used the keywords E-Money," "Electronic Money," and "Electronic Money" to get a total of 800 tweets. The results showed that the words "Money," "Deposit," and "Tools" are the three words that appear most frequently in discussions of E-Money on Twitter, which is a registration procedure for using E-Money for the first time. In addition, E-Money is widely discussed in tweets in the form of Quizzes or giveaways, so in these tweets, E-money is used as a medium for transferring funds. Overall, the sentiment shown by netizens on Twitter is positive, with emotions dominated by feelings of joy and surprise towards E-Money. On the other hand, a tiny number still shows negatively, especially when experiencing technical problems when using E-Money, so concerns arise about the security of their money and personal data. Then the results of this study can be used by E-Money issuers as evaluation material to continue improving the security system so that E-Money users feel safe and satisfied and will continue to use E-Money for an extended period.

[1]  R. Ratnasari,et al.  CELEBRITY ENDORSERS VS EXPERT ENDORSERS: WHO CAN AFFECT CONSUMER PURCHASE INTENTION FOR HALAL FASHION PRODUCT? , 2022, Jurnal Ekonomi dan Bisnis Islam (Journal of Islamic Economics and Business).

[2]  Michaela A. Balzarova,et al.  Perceptions of Blockchain Readiness for Fairtrade Programmes , 2022, SSRN Electronic Journal.

[3]  Emmanuel Mogaji,et al.  The dark side of mobile money: Perspectives from an emerging economy , 2022, Technological Forecasting and Social Change.

[4]  Manimay Ghosh.  Empirical study on consumers’ reluctance to mobile payments in a developing economy , 2022, Journal of Science and Technology Policy Management.

[5]  F. Ishengoma,et al.  Sustenance of the digital transformations induced by the COVID-19 pandemic response: lessons from Tanzanian public sector , 2022, Global Knowledge, Memory and Communication.

[6]  Yogesh Kumar Dwivedi,et al.  Consumer adoption of mobile payment services during COVID-19: extending meta-UTAUT with perceived severity and self-efficacy , 2022, International Journal of Bank Marketing.

[7]  A. Alshaher,et al.  User trends of electronic payment systems adoption in developing countries: an empirical analysis , 2021, Journal of Science and Technology Policy Management.

[8]  Daniel Collyn,et al.  Determinant Analysis of Tebing Tinggi Low Public Interest on Using Electronic Money , 2021 .

[9]  Sumeer Gul,et al.  Public perception of COVID-19 vaccines from the digital footprints left on Twitter: analyzing positive, neutral and negative sentiments of Twitterati , 2021, Libr. Hi Tech.

[10]  S. Sunarsih,et al.  Understanding Muslim’s switching from cash to m-payments: based on push-pull-mooring framework , 2021, Journal of Islamic Marketing.

[11]  Himanshu Joshi,et al.  Importance-performance map analysis to enhance the performance of attitude towards mobile wallet adoption among Indian consumer segments , 2021, Aslib J. Inf. Manag..

[12]  B. Ślusarczyk,et al.  Impact of the COVID-19 Pandemic on Online Consumer Purchasing Behavior , 2021, J. Theor. Appl. Electron. Commer. Res..

[13]  Tenace Kwaku Setor,et al.  Do digital payment transactions reduce corruption? Evidence from developing countries , 2021, Telematics Informatics.

[14]  J. Sarkis,et al.  COVID-19 pandemic digitization lessons for sustainable development of micro-and small- enterprises , 2021, Sustainable Production and Consumption.

[15]  Hoda Mansour.  How successful countries are in promoting digital transactions during COVID-19 , 2021, Journal of Economic Studies.

[16]  R. Villano,et al.  Mobile Money Adoption and Response to Idiosyncratic Shocks: Empirics from Five Selected Countries in Sub-Saharan Africa , 2021, SSRN Electronic Journal.

[17]  Shrawan Kumar Trivedi,et al.  Twitter sentiment analysis of app based online food delivery companies , 2021 .

[18]  O. Güney,et al.  How COVID-19 affects individuals' food consumption behaviour: a consumer survey on attitudes and habits in Turkey , 2021 .

[19]  Sotiris Ioannidis,et al.  A survey of Twitter research: Data model, graph structure, sentiment analysis and attacks , 2021, Expert Syst. Appl..

[20]  Felix Fridom Mailoa.  Analisis sentimen data twitter menggunakan metode text mining tentang masalah obesitas di indonesia , 2020, Journal of Information Systems for Public Health.

[21]  S. Oktavilia,et al.  Analysis The Use of Electronic Money in Indonesia , 2020 .

[22]  Syed Tanzeel Rabani,et al.  Identifying propaganda from online social networks during COVID-19 using machine learning techniques , 2020, International journal of information technology : an official journal of Bharati Vidyapeeth's Institute of Computer Applications and Management.

[23]  Nripendra P. Rana,et al.  Understanding consumer adoption of mobile payment in India: Extending Meta-UTAUT model with personal innovativeness, anxiety, trust, and grievance redressal , 2020, Int. J. Inf. Manag..

[24]  Wassan A.A. Al-Khowaiter,et al.  Digital payment and banking adoption research in Gulf countries: A systematic literature review , 2020, Int. J. Inf. Manag..

[25]  Hendy Mustiko Aji,et al.  The effects of subjective norm and knowledge about riba on intention to use e-money in Indonesia , 2020 .

[26]  Zoran Kalinic,et al.  The moderating effects of gender on customer satisfaction and continuance intention in mobile commerce: a UTAUT-based perspective , 2020, Technol. Anal. Strateg. Manag..

[27]  Gerrit Rooks,et al.  Learning mobile money in social networks: Comparing a rural and urban region in Uganda , 2020, Comput. Hum. Behav..

[28]  H. Purohit,et al.  Emergence and Growth of Mobile Money in Modern India: A Study on the Effect of Mobile Money , 2020, 2020 Advances in Science and Engineering Technology International Conferences (ASET).

[29]  N. Falah,et al.  E-Money Challenge in Disruption Era: Uncovering the Dilemma Issues from Consumers’ Perspective , 2019 .

[30]  Rokhmat Subagiyo.  ERA FINTECH: PELUANG DAN TANTANGAN BAGI EKONOMI SYARIAH , 2019, el-Jizya : Jurnal Ekonomi Islam.

[31]  Cheng-Min Chao,et al.  Factors Determining the Behavioral Intention to Use Mobile Learning: An Application and Extension of the UTAUT Model , 2019, Front. Psychol..

[32]  Peter Andras,et al.  User perception of Bitcoin usability and security across novice users , 2019, Int. J. Hum. Comput. Stud..

[33]  M. Lokanan,et al.  Anti-money laundering and counter-terrorist financing threats posed by mobile money , 2019, Journal of Money Laundering Control.

[34]  Alain Yee-Loong Chong,et al.  Multi-class Twitter sentiment classification with emojis , 2018, Ind. Manag. Data Syst..

[35]  Fibria Indriati,et al.  THE INFLUENCE OF UTAUT FACTORS ON E-RETENTION WITH E-SATISFACTION AS MEDIATING VARIABLE IN E-LEARNING , 2018, Hasanuddin Economics and Business Review.

[36]  Brijesh Sivathanu.  Adoption of digital payment systems in the era of demonetization in India , 2018, Journal of Science and Technology Policy Management.

[37]  Santi Indra Astuti,et al.  PETA GERAKAN LITERASI DIGITAL DI INDONESIA: STUDI TENTANG PELAKU, RAGAM KEGIATAN, KELOMPOK SASARAN DAN MITRA YANG DILAKUKAN OLEH JAPELIDI , 2017 .

[38]  Hway-Boon Ong,et al.  Cashless payment and economic growth , 2016 .

[39]  Rodney Graeme Duffett,et al.  Facebook advertising's influence on intention-to-purchase and purchase amongst Millennials , 2015, Internet Res..

[40]  Harminder Singh,et al.  Understanding the effect of e-learning on individual performance: The role of digital literacy , 2015, Comput. Educ..

[41]  Lani Miliani,et al.  Adoption Behavior of E-Money Usage , 2013 .

[42]  Lu’liyatul Mutmainah,et al.  You`ve Over the Line! Muslim Consumers are Resistant to Opposite Brand Values , 2023 .

[43]  D. Draheim,et al.  Secure and Efficient Implementation of Electronic Money , 2022, FDSE.

[44]  J. Purba,et al.  Collaboration of digital payment usage decision in COVID-19 pandemic situation: Evidence from Indonesia , 2021, International Journal of Data and Network Science.

[45]  R. Rahmawati,et al.  ANALISIS PENGARUH E-MONEY TERHADAP PERPUTARAN UANG DI INDONESIA , 2020 .

[46]  Claude Sicotte,et al.  Modeling factors explaining the acceptance, actual use and satisfaction of nurses using an Electronic Patient Record in acute care settings: An extension of the UTAUT , 2015, Int. J. Medical Informatics.

[47]  Darwanto Darwanto,et al.  The Role of Technology Acceptance Model Theory and the Relationship with Hifz Mal in the Phenomences of Using E-Money in the Milenial Era , 2022, Al-Kharaj : Jurnal Ekonomi, Keuangan & Bisnis Syariah.