ANALISIS SENTIMEN PELANGGAN KONSULTASI “TITIK TEMU” BERDASARKAN FEEDBACK PELANGGAN MENGGUNAKAN MACHINE LEARNING (BERT)

Meutia Quroti Ayun, . (0025) ANALISIS SENTIMEN PELANGGAN KONSULTASI “TITIK TEMU” BERDASARKAN FEEDBACK PELANGGAN MENGGUNAKAN MACHINE LEARNING (BERT). Skripsi thesis, Universitas Pembangunan Nasional Veteran Jakarta.

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Abstract

Digital transformation has shifted psychological and career consultation services to online platforms, such as TITIK TEMU. This study aims to evaluate customer satisfaction using sentiment analysis powered by the IndoBERT model. A total of 1,023 customer reviews from WhatsApp and surveys collected between 2021 and 2024 were analyzed through data cleaning, sentiment labeling into three categories, and model training using 5-fold cross-validation. The model achieved an accuracy of 89.6% in classifying sentiment. Wordcloud and comment similarity analysis were used to identify dominant keywords and customer perceptions. The findings provide valuable insights for improving service quality, particularly in communication and information clarity. Overall, IndoBERT proved effective in understanding customer sentiment toward digital consultation services on the TITIK TEMU platform. Keywords: Sentiment analysis, IndoBERT, customer satisfaction, online consultation, TITIK TEMU

Item Type: Thesis (Skripsi)
Additional Information: [No.Panggil: 2110512032] [Pembimbing: Bambang Saras Yulistiawan] [Penguji 1: Ika Nurlaili Isnainiyah] [Penguji 2: Theresia wati]
Uncontrolled Keywords: Sentiment analysis, IndoBERT, customer satisfaction, online consultation, TITIK TEMU
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Fakultas Ilmu Komputer > Program Studi Sistem Informasi (S1)
Depositing User: MEUTIA QUROTI AYUN
Date Deposited: 22 Aug 2025 07:39
Last Modified: 22 Aug 2025 07:39
URI: http://repository.upnvj.ac.id/id/eprint/37486

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