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All Journal Journal of Computer Science and Research GEMBIRA (Pengabdian Kepada Masyarakat)
Yoga Fitriana
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PENINGKATAN STRATEGI PEMASARAN CERIA TOUR AND TRAVEL BATAM Fendi Hidayat; Yoga Fitriana; Sultan Septian
Jurnal Gembira: Pengabdian Kepada Masyarakat Vol 1 No 05 (2023): OKTOBER 2023
Publisher : Media Inovasi Pendidikan dan Publikasi

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Abstract

Munculnya jasa tour dan travel pada saat ini membuat masyarakat lebih mudah dalam mendapatkan jasa – jasa di tour and travel , Kebutuhan jasa juga di ikuti dengan kebutuhan terhadap kualitas pelayanan, guna memberikan layanan yang berkualitas dibutuhkan komunikasi yang tepat terhadap para pelanggannya. Penelitian ini bertujuan untuk mengetahui strategi – strategi apa saja yang dilakukan Customer Relations dalam meningkatkan kepuasan pelanggannya. Metode yang digunakan dalam penelitian ini adalah deskriptif kualitatif. Penelitian ini dilakukan di tour and travel terdekat. Teknik pengumpulan data yang digunakan adalah wawancara, observasi dan studi pustaka. Hasil penelitian ini menunjukkan bahwa strategi komunikasi interpersonal yang digunakan pada Tour dan Travel dalam meningkatkan kepuasan adalah dengan Customer Relations eksternal dan Customer Relations internal dalam menangani konsumen baik di dalam maupun luar.
Sentiment and Customer Loyalty Analysis of Shopee Using Machine Learning Algorithms Yoga Fitriana
Journal of Computer Science and Research (JoCoSiR) Vol. 2 No. 3 (2024): July: Artificial Intelligence
Publisher : Asosiasi Perguruan Tinggi Informatika dan Ilmu Komputer (APTIKOM) Provinsi Sumatera Utara

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The exponential growth of e-commerce platforms has transformed consumer shopping behavior globally, including in Indonesia. Shopee, as one of the dominant online marketplaces, continuously attracts millions of active users through competitive pricing strategies, promotional events, and digital convenience. However, understanding user satisfaction and loyalty remains a challenge in such dynamic environments. This research aims to analyze user sentiment and customer loyalty toward Shopee by integrating computational sentiment analysis techniques with behavioral survey assessment. A total of 3,000 Shopee user reviews were collected through web scraping, then processed using text mining methods and classified into positive and negative categories using two machine learning algorithms: Support Vector Machine (SVM) and Naïve Bayes Classifier (NBC). Additionally, a structured loyalty survey was distributed to 30 respondents to evaluate behavioral loyalty indicators such as repeat purchase, advocacy, and emotional attachment. The SVM algorithm demonstrated superior performance with an accuracy rate of 98%, surpassing the Naïve Bayes Classifier’s 85% accuracy. The loyalty survey indicated a strong positive correlation between sentiment polarity and customer retention, revealing that satisfied users exhibit consistent repurchase intentions and brand advocacy. These findings emphasize the significance of integrating computational analytics and behavioral measurement in e-commerce performance evaluation. The results also provide managerial insights for enhancing digital service quality, consumer engagement, and long-term competitiveness in Indonesia’s online retail market
Co-Authors Fendi Hidayat Sultan Septian