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All Journal Jurnal Sistem Cerdas AQILA : Acceleration, Quantum, Information Technology and Algorithm Journal
Rukmana, Putri Utami
Unknown Affiliation
Automotive Engineering Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Electrical & Electronics Engineering

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Perbandingan Analisis Sentimen Aplikasi Traveloka dan Tiket.com pada Twitter dengan Metode Support Vector Machine Rukmana, Putri Utami; Pratiwi, Oktariani Nurul; Fakhrurroja, Hanif
Jurnal Sistem Cerdas Vol. 6 No. 3 (2023)
Publisher : APIC

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37396/jsc.v6i3.350

Abstract

The emergence of the COVID-19 pandemic in Indonesia resulted in an economic crisis, including in the world of tourism, which caused a decline in the national economy. With the existence of Online Travel Agencies (OTA) such as Traveloka and Tiket.com, it is hoped that they can help improve the tourism sector for the Indonesian economy. As a popular OTA and to see the opinion of the Indonesian people, it can be seen from public opinion in the form of tweets on the Twitter application. The tweets data will be taken and sentiment analysis will be carried out on the OTA Traveloka and Tiket.com applications which will be classified into certain classes based on opinions and modeling will be carried out using the Support Vector Machine (SVM) algorithm method. This research aims to determine the level of accuracy of the SVM algorithm and find out how sentiment analysis compares between Traveloka and Tiket.com. In the sentiment analysis comparison, in terms of price, Traveloka is superior and in terms of service, Tiket.com is superior. After modeling by comparing splitting data and handling imbalanced data using Synthetic Minority Oversampling Technique (SMOTE), the best SVM accuracy results for the Tiket.com price dataset were 68%, for Traveloka prices it was 97%, for Tiket.com services it was 92%, and for Traveloka services it is 89%.
Weaving Digital Relationships: A Social CRM Case Study of Local Beauty Brands Ana, Asri; Utami Rukmana, Putri; Lubis, Muharman
Acceleration, Quantum, Information Technology and Algorithm Journal Vol. 2 No. 2 (2025): VOLUME 2, NO 2: DECEMBER 2025
Publisher : Yayasan Asmin Intelektual Berkah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62123/aqila.v2i2.70

Abstract

The Customer Relationship Management paradigm evolved from transaction-based tod collaboration-oriented approach through Social CRM (SCRM) due to digital transformation. Descriptive qualitative research investigates the CRM approaches executed by BLP Beauty and MOP Beauty using digital ethnography and observational methods. The research extends its observation activities to digital platforms including social media platforms and e-commerce platforms and customer review platforms. The analysis proves BLP Beauty uses a standardized omnichannel strategy that adopts community engagement and performs hashtag-based social monitoring and collaborative customer engagement including two additional customer impact channels through Key Opinion Leaders (KOLs) and influencers. BLP Beauty operates with an open and extensive market segmentation whereas MOP Beauty adopts an elite branding strategy with premium positioning. CRM strategies work best when they match the brand image together with key traits of the customer base. The study establishes how vital it is to unite technology and community elements with emotional value creation for developing sustainable customer relations during the current digital era.
Co-Authors Ana, Asri Fakhrurroja, Hanif Muharman Lubis Oktariani Nurul Pratiwi