Repository Universitas Pakuan

Detail Karya Ilmiah Dosen

Eneng Tita Tosida, Erniyati, Krisna

Judul : Sentiment Analysis Using the Support Vector Machine For Community Compliance Representation in The Covid-19 Pandemic Period

Abstrak :
The increase in positive cases of Covid-19 in Indonesia is still relatively high. The main factor affecting the high number of positive cases of Covid-19 in Indonesia is the decreasing level of citizen compliance. This study aims to build a model of citizen compliance representation through a sentiment analysis approach using social media. The method used to build this model is done with a text mining approach, using the sentiment analysis by Support Vector Machine (SVM) algorithm. This model was built using the term Large-Scale Social Restrictions (LSSR) as a
key phrase. This key phrase is interpreted through four main types of activities, namely work from home (WFH), studying at home, transportation, and physical distancing. We used data from twitter and news period April-August 2020. This representative model of citizen compliance during the Covid-19 pandemic is able to show a visualization of the condition of citizens' compliance levels grouped by city and province. The citizen compliance representation model shows an accuracy rate of 98% for WFH activities, 93% for learning activities at home, 88% for
transportation activities and 90% for physical distancing activities. This model can be an initial reference for identifying the level of compliance of citizens with regard to government policies related to programs for handling Covid-19 cases in Indonesia.

Keywords: Citizen compliance, Covid-19, Representative model, Support Vector Machine, Sentiment analysis

Tahun : 2021 Media Publikasi : Prosiding

Kategori : Prosiding No/Vol/Tahun : 3 / 11 / 2021

ISSN/ISBN : 2169-8767/978-1-7923-6124-1

PTN/S : Universitas Pakuan Program Studi : ILMU KOMPUTER

Bibliography :
Apasari P.J. Twitter Sentiment Analysis Using the Lexicon-Based Method and Support Vector Machine. Telkom University. Bandung. (Analisis Sentimen Twitter Menggunakan Metode Lexicon-Based dan Support Vector Machine). Universitas Telkom. Bandung, 2017.

Carteni A, Di Francesco L, Martino M. How Mobilit Habits Influenced the Spread of the COVID-19 Pandemic : Result from the Italian Case Study. Science of The Total Environment, Vol. 741, Nov 1, 2020, 140489. https://doi.org/10.1016/j.scitotenv.2020.140489, 2020.

Flynn, M., & Francis, L. Text Mining Handbrook. In Casuality Actuarial Society E-Forum, 2010.

Gullo, F. From pattern in data to knowledge discovery: what data mining can do. Physics Procedia, 62, pp. 12-18, 2015.

Han, J. & Kamber, M. Data Mining Concepts and Techniques Second Edition. Morgan Kauffman, San Francisco, 2012.

Huang, Chia-Hui, Keng-CHieh, Yang, dan Kao, Han-Ying. Analyzing Big Data With The Hybrid Interval Regression Methods. The Scientific World Journal, 2014.

Kharde, V., & Sonawane, P. Sentiment Analysis of Twitter Data: A Survey Of Techniques. arXiv preprint arXiv, Vol. 139, 0957-8887, 2016.

Liu, B. Sentiment Analysis and Opinion Mining. Synthesis lectures on human language technologies, 5(1), 1-167. 2012.

Monarizqa, N., Nugroho, L. E., & Hantono, B. S. Application of Sentiment Analysis on Indonesian-Language Twitter as a Rating Officer. (Penerapan Analisis Sentimen Pada Twitter Berbahasa Indonesia Sebagai Pemberi Rating). Jurnal Penelitian Teknik Elektro dan Teknologi Informasi, 1, 151–155, 2014.

Nugroho, K. S. Confusion Matrix for Model Evaluation in Supervised Learning.Confusion Matrix. (Evaluasi Model pada Supervised Learning). https://medium.com/@ksnugroho/confusion-matrix-untuk-evaluasi-model-padaunsupervised-machine-learning-bc4b1ae9ae3f, 2019.

Permana, R. H. The 2020 Homecoming Prohibition Applies to LSSR Areas, Here's the List. Retrieved from DetikNews: Larangan Mudik 2020 Berlaku Untuk Daerah LSSR, DetikNews: https://news.detik.com/berita/d- 4989468/larangan-mudik-2020-berlaku-untuk-daerah-LSSR-ini-daftarnya/4 (Accessed Mei 16th 2020), 2020.

Saini, S. Sentiment Analysis on Twitter Data using R. International Conference on Automation, Computational and Technology Management (ICACTM) 68–72, 2019.

Suryahadi, A. The Impact of COVID-19 Outbreak on Poverty: An Estimation for Indonesia. SMERU. Working Paper. The SMERU Research Institute : Jakarta, 2020.

Tosida, E.T., Permana, A., Karlitasari, L., Ardiansyah, D., Andria, F., Bon A.T. Digital Tourism Education Collaboration for Strengthening Micro Business and Post Covid-19 Sustainable Eduacation Models : Proceedings of the International Conference on Industrial Engineering and Operations Management, Detroid Michigan, USA, August 10-14, 2020. pp. 2399-2408, ISSN: 2169-8767.
http://www.ieomsociety.org/detroit2020/papers/489.pdf, 2020a.

Tosida, E.T., Muhaimin, A., Hidayat, M., Ardiansyah, D., Andria, F., Bon A.T. Strengthening the Competitiveness of Micro-Businesses Based on Local Wisdom Through Digital Tourism Education Collaboration : Proceedings of the International Conference on Industrial Engineering and Operations Management, Detroid Michigan, USA, August 10-14, 2020. pp. 2439-2446, ISSN : 2169-8767,
http://www.ieomsociety.org/detroit2020/papers/494.pdf , 2020b.

Tosida, E. T., Ardiansyah, D., Walujo, A. D. Kujang And Batik Bogor Educational Games To Grow Millennial Generation Enthusiasm For Local Wisdom Through Digital Media. International Journal of Business, Economics, and Social Development. https://doi.org/10.46336/ijbesd.v1i2.35, 2020c

Tosida, E. T., Ardiansyah, D., Walujo, A. D., & Sofyandi, A. System Design of Augmented Reality Technology to Strengthen Sustainable Imaging of Kujang Products Based on Local Culture. International Journal of Recent Technology and Engineering, 8(4), 5940–5949. https://doi.org/10.35940/ijrte.d9016.118419, 2019.

URL : http://www.ieomsociety.org/singapore2021/papers/753.pdf

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Detail Karya Ilmiah Dosen

Eneng Tita Tosida, Erniyati, Krisna

Judul	:	Sentiment Analysis Using the Support Vector Machine For Community Compliance Representation in The Covid-19 Pandemic Period
Abstrak	:	The increase in positive cases of Covid-19 in Indonesia is still relatively high. The main factor affecting the high number of positive cases of Covid-19 in Indonesia is the decreasing level of citizen compliance. This study aims to build a model of citizen compliance representation through a sentiment analysis approach using social media. The method used to build this model is done with a text mining approach, using the sentiment analysis by Support Vector Machine (SVM) algorithm. This model was built using the term Large-Scale Social Restrictions (LSSR) as a key phrase. This key phrase is interpreted through four main types of activities, namely work from home (WFH), studying at home, transportation, and physical distancing. We used data from twitter and news period April-August 2020. This representative model of citizen compliance during the Covid-19 pandemic is able to show a visualization of the condition of citizens' compliance levels grouped by city and province. The citizen compliance representation model shows an accuracy rate of 98% for WFH activities, 93% for learning activities at home, 88% for transportation activities and 90% for physical distancing activities. This model can be an initial reference for identifying the level of compliance of citizens with regard to government policies related to programs for handling Covid-19 cases in Indonesia. Keywords: Citizen compliance, Covid-19, Representative model, Support Vector Machine, Sentiment analysis
Tahun	:	2021	Media Publikasi	:	Prosiding
Kategori	:	Prosiding	No/Vol/Tahun	:	3 / 11 / 2021
ISSN/ISBN	:	2169-8767/978-1-7923-6124-1
PTN/S	:	Universitas Pakuan	Program Studi	:	ILMU KOMPUTER
Bibliography	:	Apasari P.J. Twitter Sentiment Analysis Using the Lexicon-Based Method and Support Vector Machine. Telkom University. Bandung. (Analisis Sentimen Twitter Menggunakan Metode Lexicon-Based dan Support Vector Machine). Universitas Telkom. Bandung, 2017. Carteni A, Di Francesco L, Martino M. How Mobilit Habits Influenced the Spread of the COVID-19 Pandemic : Result from the Italian Case Study. Science of The Total Environment, Vol. 741, Nov 1, 2020, 140489. https://doi.org/10.1016/j.scitotenv.2020.140489, 2020. Flynn, M., & Francis, L. Text Mining Handbrook. In Casuality Actuarial Society E-Forum, 2010. Gullo, F. From pattern in data to knowledge discovery: what data mining can do. Physics Procedia, 62, pp. 12-18, 2015. Han, J. & Kamber, M. Data Mining Concepts and Techniques Second Edition. Morgan Kauffman, San Francisco, 2012. Huang, Chia-Hui, Keng-CHieh, Yang, dan Kao, Han-Ying. Analyzing Big Data With The Hybrid Interval Regression Methods. The Scientific World Journal, 2014. Kharde, V., & Sonawane, P. Sentiment Analysis of Twitter Data: A Survey Of Techniques. arXiv preprint arXiv, Vol. 139, 0957-8887, 2016. Liu, B. Sentiment Analysis and Opinion Mining. Synthesis lectures on human language technologies, 5(1), 1-167. 2012. Monarizqa, N., Nugroho, L. E., & Hantono, B. S. Application of Sentiment Analysis on Indonesian-Language Twitter as a Rating Officer. (Penerapan Analisis Sentimen Pada Twitter Berbahasa Indonesia Sebagai Pemberi Rating). Jurnal Penelitian Teknik Elektro dan Teknologi Informasi, 1, 151–155, 2014. Nugroho, K. S. Confusion Matrix for Model Evaluation in Supervised Learning.Confusion Matrix. (Evaluasi Model pada Supervised Learning). https://medium.com/@ksnugroho/confusion-matrix-untuk-evaluasi-model-padaunsupervised-machine-learning-bc4b1ae9ae3f, 2019. Permana, R. H. The 2020 Homecoming Prohibition Applies to LSSR Areas, Here's the List. Retrieved from DetikNews: Larangan Mudik 2020 Berlaku Untuk Daerah LSSR, DetikNews: https://news.detik.com/berita/d- 4989468/larangan-mudik-2020-berlaku-untuk-daerah-LSSR-ini-daftarnya/4 (Accessed Mei 16th 2020), 2020. Saini, S. Sentiment Analysis on Twitter Data using R. International Conference on Automation, Computational and Technology Management (ICACTM) 68–72, 2019. Suryahadi, A. The Impact of COVID-19 Outbreak on Poverty: An Estimation for Indonesia. SMERU. Working Paper. The SMERU Research Institute : Jakarta, 2020. Tosida, E.T., Permana, A., Karlitasari, L., Ardiansyah, D., Andria, F., Bon A.T. Digital Tourism Education Collaboration for Strengthening Micro Business and Post Covid-19 Sustainable Eduacation Models : Proceedings of the International Conference on Industrial Engineering and Operations Management, Detroid Michigan, USA, August 10-14, 2020. pp. 2399-2408, ISSN: 2169-8767. http://www.ieomsociety.org/detroit2020/papers/489.pdf, 2020a. Tosida, E.T., Muhaimin, A., Hidayat, M., Ardiansyah, D., Andria, F., Bon A.T. Strengthening the Competitiveness of Micro-Businesses Based on Local Wisdom Through Digital Tourism Education Collaboration : Proceedings of the International Conference on Industrial Engineering and Operations Management, Detroid Michigan, USA, August 10-14, 2020. pp. 2439-2446, ISSN : 2169-8767, http://www.ieomsociety.org/detroit2020/papers/494.pdf , 2020b. Tosida, E. T., Ardiansyah, D., Walujo, A. D. Kujang And Batik Bogor Educational Games To Grow Millennial Generation Enthusiasm For Local Wisdom Through Digital Media. International Journal of Business, Economics, and Social Development. https://doi.org/10.46336/ijbesd.v1i2.35, 2020c Tosida, E. T., Ardiansyah, D., Walujo, A. D., & Sofyandi, A. System Design of Augmented Reality Technology to Strengthen Sustainable Imaging of Kujang Products Based on Local Culture. International Journal of Recent Technology and Engineering, 8(4), 5940–5949. https://doi.org/10.35940/ijrte.d9016.118419, 2019.
URL	:	http://www.ieomsociety.org/singapore2021/papers/753.pdf