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dc.contributor.advisorArisandi, Dedy
dc.contributor.advisorRahmat, Romi Fadillah
dc.contributor.authorSiboro, Bora Sejati
dc.date.accessioned2024-02-07T03:34:21Z
dc.date.available2024-02-07T03:34:21Z
dc.date.issued2023
dc.identifier.urihttps://repositori.usu.ac.id/handle/123456789/91013
dc.description.abstractToday‘s trend on online shopping through various e-commerce applications has had a positive impact on the develompent of business in Expedition Services in Indonesia. The existence of various brands of goods delivery services allows people to have options in choosing any brand based on the preferences and needs of their own. As a form of brand competition amidst the increasingly specific needs and demands of society, companies need not merely brand awareness but also a good brand reputation. Assessment of a brand‘s reputation can be carried out based on user reviews through various platforms, especially social media Twitter, which is oftenly used by the public as a medium for Ekspresing opinion. This researchs was developed to obtain sentiment conclusions about an expedition service in Indonesia, namely SiCepat Ekspres, which is assessed based on various aspects, namely responsiveness, cost, goods condition, delivery, and time precision. The system was built using the Random Forest Classifier approach, where the data was tested based on the iteration of the Decision Tree method (tree_number). The results obtained through this sentiment analysis system are negative for the time precision aspect, while for other aspects mentioned before are in neutral. The average accuracy for the overall sentiment analysis results obtained is 90.8%.en_US
dc.language.isoiden_US
dc.publisherUniversitas Sumatera Utaraen_US
dc.subjectRandom Forest Classifieren_US
dc.subjectExpeditionen_US
dc.subjectSentimenten_US
dc.subjectABSAen_US
dc.subjectSDGsen_US
dc.titleAspect-Based Sentiment Analysis Mengenai Tingkat Kepuasan Pelanggan terhadap Ekspedisi Pengiriman Barang Menggunakan Random Foresten_US
dc.typeThesisen_US
dc.identifier.nimNIM161402020
dc.identifier.nidnNIDN0031087905
dc.identifier.nidnNIDN0003038601
dc.identifier.kodeprodiKODEPRODI59201#Teknologi Informasi
dc.description.pages74 Halamanen_US
dc.description.typeSkripsi Sarjanaen_US


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