<resource xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns="http://datacite.org/schema/kernel-4" xsi:schemaLocation="http://datacite.org/schema/kernel-4 http://schema.datacite.org/meta/kernel-4.1/metadata.xsd"><identifier identifierType="DOI">10.34820/FK2/OQYEQX</identifier><creators><creator><creatorName>IRADIANTY, ALDILLA</creatorName><affiliation>Telkom University</affiliation></creator></creators><titles><title>Analysis of Financial Literacy Level from Shoopeepay and OVO E-Wallet user using LDA-Based Topic Modelling</title></titles><publisher>Telkom University Dataverse</publisher><publicationYear>2022</publicationYear><subjects><subject>Business and Management</subject><subject>e-wallet, user generated content, topic modelling, latent dirichlet allocation, financial literacy</subject></subjects><contributors><contributor contributorType="ContactPerson"><contributorName nameType="Organizational">IRADIANTY, ALDILLA</contributorName><affiliation>Telkom University</affiliation></contributor></contributors><dates><date dateType="Submitted">2022-04-27</date><date dateType="Updated">2022-04-27</date></dates><resourceType resourceTypeGeneral="Dataset"/><sizes><size>1803560</size></sizes><formats><format>application/x-rar-compressed</format></formats><version>1.0</version><rightsList><rights rightsURI="info:eu-repo/semantics/openAccess"/><rights rightsURI="https://creativecommons.org/publicdomain/zero/1.0/">CC0 Waiver</rights></rightsList><descriptions><description descriptionType="Abstract">Konten dalam social media dimanfaatkan untuk mengetahui tingkat literasi keuangan pengguna Shopeepay dan OVO, dengan metode text mining yaitu topic modeling dengan pendekatan latent dirichlet allocation (LDA)</description></descriptions><geoLocations/></resource>