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Journal : JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING

Aspect-Based Sentiment Analysis On FLIP Application Reviews (Play Store) Using Support Vector Machine (SVM) Algorithm Nurul Hidayati; Faqih Hamami; Riska Yanu Fa’rifah
JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Vol. 7 No. 1 (2023): Issues July 2023
Publisher : Universitas Medan Area

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31289/jite.v7i1.9768

Abstract

The development of fintech has driven the rapid growth of e-wallets like Flip, offering a convenient solution for interbank transfers without administrative fees. User reviews on the Play Store serve as crucial feedback for understanding the user experience. This research utilizes aspect-based sentiment analysis (ABSA) in combination with the SVM method to detect opinions, perceptions, and reviews pertaining to Flip's speed, security, and cost aspects. The objective is to provide valuable insights to both users and companies regarding their experiences with Flip in conducting financial transactions. The study employs a dataset comprising 13,500 preprocessed and cleansed data points, followed by TF-IDF vectorization. The data is divided into training and testing sets, utilizing techniques such as the train-test split and K-Fold Cross Validation to assess model performance. GridSearch analysis reveals that specific parameter combinations, notably C=1.0 and test_size=0.1, yield high accuracy across all aspects, with the linear kernel displaying the highest overall accuracy. Model evaluation is conducted using the confusion matrix and classification report, presenting accuracy, precision, recall, and F1-scores for each aspect. Notably, the Support Vector Machine model performs well, particularly in the speed, security, and cost aspects, where the cost aspect demonstrates exceptionally strong results. In summary, this study employs ABSA to analyze Flip application reviews, with the Support Vector Machine model showcasing impressive performance across various aspects, providing valuable insights for users and companies engaging with Flip's financial transaction services.Keywords: aspect-based sentiment analysis, support vector machine, reviews, Flip
Co-Authors Agus Maolana Hidayat Ahmad, Mokhtarrudin Al amudi, Farhan Hasan Aldi Akbar Ambarita, Ruth Sesilya Anis Farihan Mat Raffei Arrahmani, Farras Hilmy Aziz, Abdurrahman Azzam Imaduddin, Muhammad Budi Rustandi Kartawinata Dahlan, Iqbal Ahmad Deandra, Valen Deden Witarsyah Dimas Raihan Zein Dina Meliana Saragi Fa'rifah, Riska Yanu Fabrianti Kusumasari, Tien Fadhil Hidayat Faishal Mufied Al Anshary Febrianti, Ferda Ayu Dwi Putri Ferda Ayu Dwi Putri Febrianti Ferda Ernawan Fetty Fitriyanti Lubis Firzania, Heidea Yulia Fitri Bimantoro Hadwirianto, Muhammad Raihan Helmayanti, Sheva Aditya Hidayati, Ilma Nur I Gede Pasek Suta Wijaya Iqbal Santosa Irfan Darmawan Ismail, Mohd Arfian Jauhari, M.Habib Joel Rayapoh Damanik Kardila, Yuni Kurniawan, Muhammad Rayhan Kuswandi, Brillian Adhiyaksa Lubis, Rizki Aulia Akbar Mangsor, Miza Mardika, Jody Mat Raffei, Anis Farihan Maulana, Fakhri Hassan Muhammad Bryan Gutomo Putra Muhammad Fahmi Hidayat, Muhammad Fahmi Muhammad Fauzan Nasrullah Muhammad Hafizh Murahartawaty Murahartawaty Nasrullah, Muhammad Fauzan Nicolaus Advendea Prakoso Indaryono Novanza, Alvin Renaldy Nuraliza, Hilda Nurul Hidayati Nuryatno, Edi Oktariani Nurul Pratiwi Orvalamarva Pratiwi, Oktaria Nurul Puruhita, Maretha Fitrie Puspitasari, Aprilia Mega Rachmadita Andreswari Raffei, Anis Farihan Mat Rahmah, Najma Syarifa Rahmat Fauzi Ramdani, Dwi Fickri Insan Ramli, Muhammad Ayyub Razali, Raja Razana Raja Rd. Rohmat Saedudin Salsabila Riswanti, Khairunnisa Satya Nugraha, Gibran Sheva Aditya Helmayanti Silmy Sephia Nurashila Sinung Suakanto Suhono Harso Supangkat Sujak, Aznul Fazrin bin Abu Syfani Alya Fauziyyah Tatang Mulyana Tien Fabrianti Kusumasari Vina Fadillah Widyadhari, Dinda Putri Yanu Fa'Rifah, Riska Yudo Husodo, Ario Yulizar, Iqbal Zahid, Azham