Instagram Sentiment Analysis with Naive Bayes and KNN: Exploring Customer Satisfaction of Digital Payment Services in Indonesia

Hanif Sudira; Alifiannisa Lawami Diar; Yova Ruldeviyani

doi:10.1109/IWBIS.2019.8935700

Instagram Sentiment Analysis with Naive Bayes and KNN: Exploring Customer Satisfaction of Digital Payment Services in Indonesia

Hanif Sudira, Alifiannisa Lawami Diar, Yova Ruldeviyani

Department of Computer Science

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

18 Citations (Scopus)

Abstract

Internet penetration and trends of social media have generated a load of data and many researchers have done sentiment analysis to know user's customer satisfaction of a particular brand through textual data form. This research was conducted to determine the customer satisfaction of digital payment services (Go-Pay, Ovo, and LinkAja) in Indonesia, analyzed from the result of Instagram sentiment analysis, in which the textual data form used is the Instagram comment. The research model was built with sentiment analysis classification algorithm: Naïve Bayes and K-Nearest Neighbors (KNN), and customer satisfaction theory. The result of this research with 3800 training data and 200 test data by using 20 k-fold cross validation shows that GO-PAY has all kinds of customers who satisfied, not satisfied and both. As for OVO and LinkAja have a more neutral sentiment. The most accurate classification algorithm implemented in this research is the KNN classifier algorithm, up to 90%. The final sentiment analysis result of this research contributed to the current state of customer satisfaction towards Go-Pay, Ovo, and LinkAja as a digital payment service provider in Indonesia and maybe an input to the relevant stakeholder.

Original language	English
Title of host publication	2019 International Workshop on Big Data and Information Security, IWBIS 2019
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	21-26
Number of pages	6
ISBN (Electronic)	9781728153476
DOIs	https://doi.org/10.1109/IWBIS.2019.8935700
Publication status	Published - Oct 2019
Event	2019 International Workshop on Big Data and Information Security, IWBIS 2019 - Bali, Indonesia Duration: 11 Oct 2019 → …

Publication series

Name	2019 International Workshop on Big Data and Information Security, IWBIS 2019

Conference

Conference	2019 International Workshop on Big Data and Information Security, IWBIS 2019
Country/Territory	Indonesia
City	Bali
Period	11/10/19 → …

Keywords

Customer Satisfaction
Digital Payment
Instagram
K-Nearest Neighbors
Naïve Bayes
Sentiment Analysis

Access to Document

10.1109/IWBIS.2019.8935700

Cite this

Sudira, H., Diar, A. L., & Ruldeviyani, Y. (2019). Instagram Sentiment Analysis with Naive Bayes and KNN: Exploring Customer Satisfaction of Digital Payment Services in Indonesia. In 2019 International Workshop on Big Data and Information Security, IWBIS 2019 (pp. 21-26). Article 8935700 (2019 International Workshop on Big Data and Information Security, IWBIS 2019). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IWBIS.2019.8935700

Sudira, Hanif ; Diar, Alifiannisa Lawami ; Ruldeviyani, Yova. / Instagram Sentiment Analysis with Naive Bayes and KNN : Exploring Customer Satisfaction of Digital Payment Services in Indonesia. 2019 International Workshop on Big Data and Information Security, IWBIS 2019. Institute of Electrical and Electronics Engineers Inc., 2019. pp. 21-26 (2019 International Workshop on Big Data and Information Security, IWBIS 2019).

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title = "Instagram Sentiment Analysis with Naive Bayes and KNN: Exploring Customer Satisfaction of Digital Payment Services in Indonesia",

abstract = "Internet penetration and trends of social media have generated a load of data and many researchers have done sentiment analysis to know user's customer satisfaction of a particular brand through textual data form. This research was conducted to determine the customer satisfaction of digital payment services (Go-Pay, Ovo, and LinkAja) in Indonesia, analyzed from the result of Instagram sentiment analysis, in which the textual data form used is the Instagram comment. The research model was built with sentiment analysis classification algorithm: Na{\"i}ve Bayes and K-Nearest Neighbors (KNN), and customer satisfaction theory. The result of this research with 3800 training data and 200 test data by using 20 k-fold cross validation shows that GO-PAY has all kinds of customers who satisfied, not satisfied and both. As for OVO and LinkAja have a more neutral sentiment. The most accurate classification algorithm implemented in this research is the KNN classifier algorithm, up to 90%. The final sentiment analysis result of this research contributed to the current state of customer satisfaction towards Go-Pay, Ovo, and LinkAja as a digital payment service provider in Indonesia and maybe an input to the relevant stakeholder.",

keywords = "Customer Satisfaction, Digital Payment, Instagram, K-Nearest Neighbors, Na{\"i}ve Bayes, Sentiment Analysis",

author = "Hanif Sudira and Diar, {Alifiannisa Lawami} and Yova Ruldeviyani",

year = "2019",

month = oct,

doi = "10.1109/IWBIS.2019.8935700",

language = "English",

series = "2019 International Workshop on Big Data and Information Security, IWBIS 2019",

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Sudira, H, Diar, AL & Ruldeviyani, Y 2019, Instagram Sentiment Analysis with Naive Bayes and KNN: Exploring Customer Satisfaction of Digital Payment Services in Indonesia. in 2019 International Workshop on Big Data and Information Security, IWBIS 2019., 8935700, 2019 International Workshop on Big Data and Information Security, IWBIS 2019, Institute of Electrical and Electronics Engineers Inc., pp. 21-26, 2019 International Workshop on Big Data and Information Security, IWBIS 2019, Bali, Indonesia, 11/10/19. https://doi.org/10.1109/IWBIS.2019.8935700

Instagram Sentiment Analysis with Naive Bayes and KNN: Exploring Customer Satisfaction of Digital Payment Services in Indonesia. / Sudira, Hanif; Diar, Alifiannisa Lawami; Ruldeviyani, Yova.
2019 International Workshop on Big Data and Information Security, IWBIS 2019. Institute of Electrical and Electronics Engineers Inc., 2019. p. 21-26 8935700 (2019 International Workshop on Big Data and Information Security, IWBIS 2019).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AB - Internet penetration and trends of social media have generated a load of data and many researchers have done sentiment analysis to know user's customer satisfaction of a particular brand through textual data form. This research was conducted to determine the customer satisfaction of digital payment services (Go-Pay, Ovo, and LinkAja) in Indonesia, analyzed from the result of Instagram sentiment analysis, in which the textual data form used is the Instagram comment. The research model was built with sentiment analysis classification algorithm: Naïve Bayes and K-Nearest Neighbors (KNN), and customer satisfaction theory. The result of this research with 3800 training data and 200 test data by using 20 k-fold cross validation shows that GO-PAY has all kinds of customers who satisfied, not satisfied and both. As for OVO and LinkAja have a more neutral sentiment. The most accurate classification algorithm implemented in this research is the KNN classifier algorithm, up to 90%. The final sentiment analysis result of this research contributed to the current state of customer satisfaction towards Go-Pay, Ovo, and LinkAja as a digital payment service provider in Indonesia and maybe an input to the relevant stakeholder.

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PB - Institute of Electrical and Electronics Engineers Inc.

Y2 - 11 October 2019

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Sudira H, Diar AL, Ruldeviyani Y. Instagram Sentiment Analysis with Naive Bayes and KNN: Exploring Customer Satisfaction of Digital Payment Services in Indonesia. In 2019 International Workshop on Big Data and Information Security, IWBIS 2019. Institute of Electrical and Electronics Engineers Inc. 2019. p. 21-26. 8935700. (2019 International Workshop on Big Data and Information Security, IWBIS 2019). doi: 10.1109/IWBIS.2019.8935700

Instagram Sentiment Analysis with Naive Bayes and KNN: Exploring Customer Satisfaction of Digital Payment Services in Indonesia

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