Understanding citizen feedback of Jakarta government super app: Leveraging deep learning models

Muhammad Cendekia Airlangga; Andi Sulasikin; Yudhistira Nugraha; Nur Laily Romadhotul Husna; Muhamad Erza Aminanto; Fajar Kurniawan; Juan Intan Kanggrawan

doi:10.1109/ISC257844.2023.10293572

Understanding citizen feedback of Jakarta government super app: Leveraging deep learning models

Muhammad Cendekia Airlangga, Andi Sulasikin, Yudhistira Nugraha, Nur Laily Romadhotul Husna, Muhamad Erza Aminanto, Fajar Kurniawan, Juan Intan Kanggrawan

Cyber Security Indonesia

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

1 Citation (Scopus)

Abstract

Jakarta Kini (JAKI) is a mobile application created by Jakarta Government to facilitate the Jakarta residents towards public services. Sentiment analysis of users' reviews should be done to provide an understanding of the essence of the issues which JAKI's users face. In this paper, word cloud analysis and a comparison of several deep learning methods were done to do the sentiment analysis of JAKI's reviews. Word cloud analysis indicates the satisfaction of the users as well as the need for several improvements that should be made by the JAKI developers. Furthermore, several deep learning techniques were employed such as LSTM, BiLSTM, GRU, BiGRU, and IndoBERT since their performance is better than conventional machine learning. Results show that the IndoBERT model outperforms another model. This shows that IndoBERT can effectively be used for this Indonesian sentiment analysis task and can be used as a reference method for analyzing Indonesian reviews in JAKI and other mobile apps in Google Play Store and Apple App Store.

Original language	English
Title of host publication	Proceedings of 2023 IEEE International Smart Cities Conference, ISC2 2023
Editors	Mihnea Costoiu, George Cristian Lazaroiu
Place of Publication	Piscataway NJ USA
Publisher	IEEE, Institute of Electrical and Electronics Engineers
Number of pages	6
ISBN (Electronic)	9798350397758, 9798350397741
ISBN (Print)	9798350397765
DOIs	https://doi.org/10.1109/ISC257844.2023.10293572
Publication status	Published - 2023
Event	IEEE International Smart Cities Conference 2023 - Bucharest, Romania Duration: 24 Sept 2023 → 27 Sept 2023 Conference number: 9th https://ieeexplore.ieee.org/xpl/conhome/10293179/proceeding (Proceedings) https://attend.ieee.org/isc2-2023/ (Website)

Conference

Conference	IEEE International Smart Cities Conference 2023
Abbreviated title	ISC2 2023
Country/Territory	Romania
City	Bucharest
Period	24/09/23 → 27/09/23
Internet address	https://ieeexplore.ieee.org/xpl/conhome/10293179/proceeding (Proceedings) https://attend.ieee.org/isc2-2023/ (Website)

Keywords

Deep learning
JAKI
Reviews
Sentiment Analysis
Word Cloud

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1109/ISC257844.2023.10293572

Cite this

Airlangga, M. C., Sulasikin, A., Nugraha, Y., Husna, N. L. R., Aminanto, M. E., Kurniawan, F., & Kanggrawan, J. I. (2023). Understanding citizen feedback of Jakarta government super app: Leveraging deep learning models. In M. Costoiu, & G. Cristian Lazaroiu (Eds.), Proceedings of 2023 IEEE International Smart Cities Conference, ISC2 2023 IEEE, Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/ISC257844.2023.10293572

Airlangga, Muhammad Cendekia ; Sulasikin, Andi ; Nugraha, Yudhistira et al. / Understanding citizen feedback of Jakarta government super app : Leveraging deep learning models. Proceedings of 2023 IEEE International Smart Cities Conference, ISC2 2023. editor / Mihnea Costoiu ; George Cristian Lazaroiu. Piscataway NJ USA : IEEE, Institute of Electrical and Electronics Engineers, 2023.

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title = "Understanding citizen feedback of Jakarta government super app: Leveraging deep learning models",

abstract = "Jakarta Kini (JAKI) is a mobile application created by Jakarta Government to facilitate the Jakarta residents towards public services. Sentiment analysis of users' reviews should be done to provide an understanding of the essence of the issues which JAKI's users face. In this paper, word cloud analysis and a comparison of several deep learning methods were done to do the sentiment analysis of JAKI's reviews. Word cloud analysis indicates the satisfaction of the users as well as the need for several improvements that should be made by the JAKI developers. Furthermore, several deep learning techniques were employed such as LSTM, BiLSTM, GRU, BiGRU, and IndoBERT since their performance is better than conventional machine learning. Results show that the IndoBERT model outperforms another model. This shows that IndoBERT can effectively be used for this Indonesian sentiment analysis task and can be used as a reference method for analyzing Indonesian reviews in JAKI and other mobile apps in Google Play Store and Apple App Store.",

keywords = "Deep learning, JAKI, Reviews, Sentiment Analysis, Word Cloud",

author = "Airlangga, {Muhammad Cendekia} and Andi Sulasikin and Yudhistira Nugraha and Husna, {Nur Laily Romadhotul} and Aminanto, {Muhamad Erza} and Fajar Kurniawan and Kanggrawan, {Juan Intan}",

note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; IEEE International Smart Cities Conference 2023, ISC2 2023 ; Conference date: 24-09-2023 Through 27-09-2023",

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doi = "10.1109/ISC257844.2023.10293572",

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publisher = "IEEE, Institute of Electrical and Electronics Engineers",

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Airlangga, MC, Sulasikin, A, Nugraha, Y, Husna, NLR, Aminanto, ME, Kurniawan, F & Kanggrawan, JI 2023, Understanding citizen feedback of Jakarta government super app: Leveraging deep learning models. in M Costoiu & G Cristian Lazaroiu (eds), Proceedings of 2023 IEEE International Smart Cities Conference, ISC2 2023. IEEE, Institute of Electrical and Electronics Engineers, Piscataway NJ USA, IEEE International Smart Cities Conference 2023, Bucharest, Romania, 24/09/23. https://doi.org/10.1109/ISC257844.2023.10293572

Understanding citizen feedback of Jakarta government super app: Leveraging deep learning models. / Airlangga, Muhammad Cendekia; Sulasikin, Andi; Nugraha, Yudhistira et al.
Proceedings of 2023 IEEE International Smart Cities Conference, ISC2 2023. ed. / Mihnea Costoiu; George Cristian Lazaroiu. Piscataway NJ USA: IEEE, Institute of Electrical and Electronics Engineers, 2023.

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

TY - GEN

T1 - Understanding citizen feedback of Jakarta government super app

T2 - IEEE International Smart Cities Conference 2023

AU - Airlangga, Muhammad Cendekia

AU - Sulasikin, Andi

AU - Nugraha, Yudhistira

AU - Husna, Nur Laily Romadhotul

AU - Aminanto, Muhamad Erza

AU - Kurniawan, Fajar

AU - Kanggrawan, Juan Intan

N1 - Conference code: 9th

PY - 2023

Y1 - 2023

N2 - Jakarta Kini (JAKI) is a mobile application created by Jakarta Government to facilitate the Jakarta residents towards public services. Sentiment analysis of users' reviews should be done to provide an understanding of the essence of the issues which JAKI's users face. In this paper, word cloud analysis and a comparison of several deep learning methods were done to do the sentiment analysis of JAKI's reviews. Word cloud analysis indicates the satisfaction of the users as well as the need for several improvements that should be made by the JAKI developers. Furthermore, several deep learning techniques were employed such as LSTM, BiLSTM, GRU, BiGRU, and IndoBERT since their performance is better than conventional machine learning. Results show that the IndoBERT model outperforms another model. This shows that IndoBERT can effectively be used for this Indonesian sentiment analysis task and can be used as a reference method for analyzing Indonesian reviews in JAKI and other mobile apps in Google Play Store and Apple App Store.

AB - Jakarta Kini (JAKI) is a mobile application created by Jakarta Government to facilitate the Jakarta residents towards public services. Sentiment analysis of users' reviews should be done to provide an understanding of the essence of the issues which JAKI's users face. In this paper, word cloud analysis and a comparison of several deep learning methods were done to do the sentiment analysis of JAKI's reviews. Word cloud analysis indicates the satisfaction of the users as well as the need for several improvements that should be made by the JAKI developers. Furthermore, several deep learning techniques were employed such as LSTM, BiLSTM, GRU, BiGRU, and IndoBERT since their performance is better than conventional machine learning. Results show that the IndoBERT model outperforms another model. This shows that IndoBERT can effectively be used for this Indonesian sentiment analysis task and can be used as a reference method for analyzing Indonesian reviews in JAKI and other mobile apps in Google Play Store and Apple App Store.

KW - Deep learning

KW - JAKI

KW - Reviews

KW - Sentiment Analysis

KW - Word Cloud

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U2 - 10.1109/ISC257844.2023.10293572

DO - 10.1109/ISC257844.2023.10293572

M3 - Conference Paper

AN - SCOPUS:85178363626

SN - 9798350397765

BT - Proceedings of 2023 IEEE International Smart Cities Conference, ISC2 2023

A2 - Costoiu, Mihnea

A2 - Cristian Lazaroiu, George

PB - IEEE, Institute of Electrical and Electronics Engineers

CY - Piscataway NJ USA

Y2 - 24 September 2023 through 27 September 2023

ER -

Airlangga MC, Sulasikin A, Nugraha Y, Husna NLR, Aminanto ME, Kurniawan F et al. Understanding citizen feedback of Jakarta government super app: Leveraging deep learning models. In Costoiu M, Cristian Lazaroiu G, editors, Proceedings of 2023 IEEE International Smart Cities Conference, ISC2 2023. Piscataway NJ USA: IEEE, Institute of Electrical and Electronics Engineers. 2023 doi: 10.1109/ISC257844.2023.10293572

Understanding citizen feedback of Jakarta government super app: Leveraging deep learning models

Abstract

Conference

Keywords

UN SDGs

Access to Document

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