User Sentiment Analysis in the Fintech OVO Review Based on the Lexicon Method

Widiantoro, Albertus Dwiyoga; Wibowo, Adi; Harnadi, Bernardinus

doi:10.1109/icic54025.2021.9632909

Cited by 7 publications

(12 citation statements)

References 16 publications

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“…In this phase, various libraries, including Google Colab, nltk, pandas, spacy, and the Indonesian Sastrawi library were utilized for preprocessing. The Indonesian Sastrawi library particularly aided in converting the Indonesian language's word affix into its basic form [46].…”

Section: Preprocessingmentioning

confidence: 99%

A Hybrid Sampling Approach for Improving the Classification of Imbalanced Data Using ROS and NCL Methods

2023

IJIES

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This research presents a novel hybrid sampling technique, implemented at the data level, to effectively address imbalanced and noisy data in classification processes. The proposed technique expertly combines two established methods, namely, the random over sampling (ROS) and neighbourhood cleaning rule (NCL) approaches, to tackle imbalance and noise issues, respectively. The study carried out an empirical evaluation of the proposed approach using crowdsourced text data that primarily emphasized the triple bottom line (TBL) dimension of a smart social, economic, and environmental city. The study used the long short-term memory (LSTM), convolutional neural networks (CNN), and CNN-LSTM classification models to validate the efficacy of the proposed hybrid sampling technique and compare its performance with other existing approaches, including ROS oversampling, NCL undersampling, synthetic minority over sampling & tomek links (SMOTE-Tomek), and synthetic minority oversampling and edited nearest neighbours (SMOTE-ENN) hybrid sampling. The results are impressive, with the ROS-NCL hybrid sampling technique achieving high accuracy rates across all three classification models, at 97.71%, 98.01%, and 98.11%, respectively. This approach provides a robust and effective solution for handling impure data and holds great promise in identifying complex data patterns in real-world classification problems.

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Section: Preprocessingmentioning

confidence: 99%

A Hybrid Sampling Approach for Improving the Classification of Imbalanced Data Using ROS and NCL Methods

2023

IJIES

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“…The data that is cleaned or cleaned will become a dataset that can be used properly because it is already structured. Data processing is done so that raw data becomes data ready for analysis [13]. Data processing was carried out using the Microsoft Excel application and stored in the comma separated value (.csv) data format.…”

Section: Scrubmentioning

confidence: 99%

Data Visualization Of House Of Worship Distribution In The IKN Nusantara Region Using Python

Adi Jaya,

Fauzi,

Suryana

et al. 2023

JIM

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Nusantara, Indonesia's new capital, has a land area 256,142 ha and a marine area 68,189 ha. Transmigrant residents in the North Penajam Paser Regency region has increased as a result. The difficulty of finding a place of worship in the closest location because they are unfamiliar with their location or the nearby roadways. We can utilize data visualization to show the distribution of places of worship in order to solve this issue. Analysis was done on several types of houses of worship, including mosques, churches, and musholla. Python is the programming language, and the libraries used are NumPy, Pandas, Matplotlib, Seaborn, RegEx, and Folium. Muslims for the majority of places of worship in IKN Nusantara (91.26%), musholla making up 57.92% of the total and mosques making up 33.33% and 8.74% are owned by Christians. Sukaraja Village, Semoi Dua Village, Argo Mulyo Village, and Tengin Baru Village have the highest concentration. Keywords: Data Visualization, House of Worship, IKN Nusantara, Python

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“…Fintech, short for financial technology, refers to the use of technology to provide financial services. The term encompasses a wide range of innovations, from mobile banking apps and peer-to-peer lending platforms to blockchain and artificial intelligence-powered investment tools [11]. The rise of fintech has disrupted the traditional financial services industry, offering consumers more choice, convenience and control over their financial affairs.…”

Section: Literature Review Fintechmentioning

confidence: 99%

Sentiment Analysis of User Preference for Old Vs New Fintech Technology Using SVM and NB Algorithms

Nurdin,

Alexandri,

Sumadinata

et al. 2023

Management Systems in Production Engineering

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The aim of this study is to use sentiment analysis to compare the efficiency of old and new fintech technologies by collecting data from various sources and analyzing it using the SVM and NB algorithms. The study seeks to identify opinions or feelings from text in order to provide a clear picture of public opinion and the direction of the debate regarding old and new fintech technologies. The results of the study show that the SVM algorithm has an average accuracy of 87.32% and the NB algorithm has an average accuracy of 81.56% in testing the sample data in a comparison of old and new fintech technology on the internet. The study tested data in a comparison of two specific arguments, namely the debate about which technology is more efficient in old and new fintech on the internet. Despite many unresolved arguments, the study successfully proved that new fintech is more preferred than old fintech, with 71% positive sentiment directed towards new fintech. However, the dataset also found that 62% negative sentiment is directed towards new fintech, indicating that although new fintech is more preferred, there are still some issues that need to be addressed. One reason for negative sentiment towards new fintech may be the continued concerns about security and privacy of user data. Furthermore, other factors that may cause negative sentiment towards new fintech include a lack of understanding about how the technology works.

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User Sentiment Analysis in the Fintech OVO Review Based on the Lexicon Method

Abstract: User reviews are important in the new approach to fintech services. To learn this information, a simple sentiment analysis can make the right observations to support the ... View more Metadata

Cited by 7 publications

References 16 publications

A Hybrid Sampling Approach for Improving the Classification of Imbalanced Data Using ROS and NCL Methods

A Hybrid Sampling Approach for Improving the Classification of Imbalanced Data Using ROS and NCL Methods

Data Visualization Of House Of Worship Distribution In The IKN Nusantara Region Using Python

Sentiment Analysis of User Preference for Old Vs New Fintech Technology Using SVM and NB Algorithms

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