Bulletin of Social Informatics Theory and Application ISSN 2614-0047

Vol. 6, No. 2, December 2022, pp. 102-110 102

https:doi.org/10.31763/businta.v6i2.553

Social network analysis of the development of the halal industry

in Indonesia

Muhamad Subhi Apriantoro a,1,*, Adelia Eka Nuraini a,2, Hudaifah b,3

a Faculty of Islamic Religion, Universitas Muhammadiyah Surakarta, Sukoharjo, 57169, Indonesia
b Faculty of Computing & Mathematics Industrial, King Fahd University of Petroleum & Minerals, 3126, Kingdom Saudi Arabia
1 msa617@ums.ac.id ; 2 i000190007@student.ums.ac.id; 3 g201806140@kfupm.edu.sa

* corresponding author

1. Introduction

Halal Industry refers to processing goods and services using methods and tools that comply with
sharia [1]. Currently, halal products and enterprises are a religious problem in the Muslim community
and a way of life [2]. Indonesia, which has a larger Muslim population than other nations, has not
developed its halal business effectively [3]. The Indonesian market is quite promising. The halal
industry is currently a global trend. In this scenario, it is evident that the potential for the halal business
increases from year to year [4].

The existence of the halal industry cannot be separated from the existence of a structured
movement through social media [5]. Conversations about the halal industry influence public opinion
in determining lifestyle decisions with the halal industry or others [6].

The development of information technology is the development of a system that is very concerned
with the ease of internet access and speed because there are now numerous digital sources circulating
on the internet [7]. It can track aspects of daily life that are inextricably linked to digital technology.
With the following terms, social media has become necessary for the public, dramatically altering the
social landscape and how participation is understood. The application of accurate and proportionate
information technology to software (platforms) and software (operating systems) continues to offer
numerous benefits to the community [8].

All scientific disciplines anticipate the effectiveness and efficiency of an information system's
performance due to its practical advantages. In addition, the recent rapid development of digital issues
has strengthened the public's understanding of its role. The data is then used for various channels of
participation that are classified as reading the public opinion that develops within a society.

A R T I C L E I N F O A B S T R A C T

Article history

Received October 16, 2022

Revised November 18, 2022

Accepted November 30,2022

This study looks at the public sentiment of Twitter users regarding the halal
industry. Data was taken using Drone Emprit Academic, an extensive data
method that captures and analyzes conversations on social media, especially on
Twitter, developed by Media Kernels Indonesia, which is also installed on the
Information System Agency of the Islamic University of Indonesia. The research
method uses a social network analysis approach to analyze data on social media
conversations. The data was obtained after observing for 30 days from trending
Twitter topics. The data is processed by the Social Network Analysis (SNA)
system, which can be interpreted as describing the interactions and
relationships that always occur between one individual and another in an
organization or work environment and the company. We found that the halal
industry in Indonesia is growing more rapidly with the existence of social
networks. A large number of conversations among Twitter users in Indonesia
shows this.

This is an open access article under the CC–BY-SA license.

Keywords

Social networking

Twitter

Social media

Machine learning

Sentiment analysis

https://doi.org/10.31763/businta.v6i2.55
mailto:msa617@ums.ac.id
http://creativecommons.org/licenses/by-sa/4.0/
http://creativecommons.org/licenses/by-sa/4.0/

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Consequently, a tool is required to detect in detail the analysis conducted by netizens in software
application conversations [9]. In this study, we will present the functions of the Drone Emprit
Academic (DEA) application developed by the Islamic University of Indonesia in light of current
trends among internet users. This study will describe the usage of keywords in the Halal Industry in
Indonesia, which has become a topic of conversation among netizens on social media, particularly on
Twitter. Drone Emprit provides vast data to discover actual social. According to the study, Drone
Emprit Academic is an extensive data system that records and analyzes social media, particularly
Twitter chats [10].

Using the streaming technology, Drone Emprit already uses a Twitter-integrated API (Applications
Programming Interface) service to capture talks in near-real time. Twitter displays trending
percentages, retweets, and graphs, with retweet status and conversations taking precedence [11], [12].
The data as a reference can only be read/viewed for the many types and social phenomena that occur.
This study has limited the capability of the Drone Emprit Academic application to scan public debates
on social media using the phrases Halal Industry [13].

In this DEA application, researchers will perform a study using a Social Network Analysis method
frequently employed by academics and researchers, including professors, teachers, researchers, and
students [14]. Examining the network patterns in which organizations, ideas, and people interact in
various ways, SNA has various network features that give relationships that aid in the development of
information management [15].

2. Method

In this study, descriptive qualitative methodology is employed [16]. A case study is the qualitative
research method employed in this study. In this context, a case study is a qualitative research method
purposely designed to generate and discover novel processes or behaviors as a research object that is
not well recognized [17]–[19]. The Drone Emprit Academic application has been the subject of
research in reading citizen conversations in social media with the Twitter application for the last 30
(thirty) days, beginning on 3 (three) August and ending on 1 (one) September. In contrast, the data
analyzed in this study were collected from 3 (three) August to September 1. The research presented
here takes the form of citizen conversations around the Halal Industry in Indonesia. Social Network
Analysis (SNA) from the Drone Emprit Academic (DEA) of the Islamic University of Indonesia was
utilized to collect data on their talks using data collection techniques [20].

The tracking process of conversations by netizens goes through several stages: One, it can analyze
the entire cluster of netizen conversations that are adjusted to the keywords Halal Industry. Second,
conversations with netizens are very determined in the period. Third, we quickly analyze keywords
through Social Network Analysis (SNA) and then describe them based on influencers, buzzers, and
followers. Fourth, we can select conversations based on the number of retweets, mentions, user
accounts, and hashtags used. Fifth, it can determine the percentage of the bot (robot) accounts in the
conversation. Sixth, identify the most shared sites. Finally, determine which regions the netizens who
participated in the conversation came from [21]. The algorithm of the data flow can be seen in Fig. 1.

Fig. 1. Algorithm of the data flow

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Apriantoro et.al (Social network analysis of the development of the halal industry in Indonesia)

3. Results and Discussion

Drone Emprit Academic discovered 5,585 active Twitter social media users discussing the Halal
Industry. We discussed the Halal Industry on Twitter between August 3 and September 1, 2022. The
data comes exclusively from social media platforms, not news websites. This finding indicates that
internet users are highly enthusiastic about the topic. The following discussion will outline the specific
analysis of the various chats.

3.1. Mention Analysis

Twitter users continue to engage in heated discussions about the Halal Industry in August 2022.
With 787 tweets on August 17, 2022, the topic of the Halal Industry reached its highest point in
August. There was no conversation from August 18-22. The conversation about the Halal Industry
resumed on August 23 and peaked on August 25, 2022, with 451 tweets. After two days, the
conversation topic began declining on the 27th, when only 127 tweets were posted about it. This Halal
Industry discussion will experience daily ups and downs until September 1, 2022. Fig. 2 shows the
trends of total mentions by media type.

Fig. 2. Trends of total mentions by media types

Fig. 3 shows that Drone Emprit Academic discovers daily Twitter activity about the Halal Industry.
From Monday to Wednesday, the Halal Industry is frequently discussed and has increased in
frequency on Wednesday. Monday, as many as 584 Twitter users discuss this subject. As a result, as
many as 1,656 Twitter users discussed this subject at its highest point on Wednesday. From Thursday
to Saturday, the number of Twitter users discussing this topic decreased from 810 to 477. Finally, as
many as 837 Twitter users discussed this topic on Sunday.

Fig. 3. Mentions by day

We compile an analysis of Twitter users' hourly Halal Industry-related conversation mentions.
Similar to midnight or midnight, 113 Twitter users were discussing this topic. However, only 48
Twitter users talked about the halal industry at three o'clock, but by nine o'clock, that number had
risen to 483. In addition, the conversation is declining, possibly because everyone is engaged in
activities such as work, school, or college during working hours. Fig. 4 shows mentions by the hour.

584
738

1,656

810

483 477

837

200

400

600

800

1000

1200

1400

1600

1800

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Fig. 4. Mention by hour

We analyze engagement types. Fig. 5 shows Twitter users' total mentions, replies, and retweets.
As a result, from August 3 to September 1, 2022, the number of tagged or tagged someone's account
in conversations or comments on halal Industry topics reached 973 accounts (17.42%). Responses
given to other people's Tweets reached 746 accounts (13.36%), and (retweets) reposted a tweet of up
to 3,866 accounts (69.22%). The total number of mentions, replies, and retweets on the Halal Industry
on Twitter is 5,585 active Twitter accounts. At the same time, the level of interaction on this topic is
4.74.

Fig. 5. Total daily rt, reply, and mentions

The exposure captured by the Emprit Academic Drone application analyzes Twitter followers and
posts from followers on topics discussing the Halal Industry. Starting from Twitter followers 0-3
posted (tweets) of 296 (5.30%), Twitter followers from 4-25 posted (tweets) 450 (8.06%), Twitter
followers from 26-50 posted (tweets) 297 (5.32%), Twitter followers 51-100 tweets 410 (7.34%),
from 101-500 Twitter followers his posts (Tweets) 1,672 or (29.94%), Twitter followers from 501-
1000 his posted (tweets Hence, the sum of all of the postings (tweets) made by all of the followers is
5,585, which is equal to 100%. Fig. 6 shows the total exposure.

Fig. 6. shows the total exposure

113
55 61 48 53

111

210

319
379

483
453

388

276
312 292 283 277

358

251
212

179
156 161 153

100

200

300

400

500

600

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23

200

400

600

800

8. Aug 15. Aug 22. Aug 29. Aug

mention reply rt

500

1000

1500

2000

0-3 4_25 26-50 51-100 101-500 501-1000 1001-10K 10K-100K 100K-500K 500K-1M 1M-up

Number of Followers

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3.2. Sentiment Analysis

We analyzed sentiment from August 3 to September 1, 2022, resulting in harmful, positive, and
neutral comments. Many netizens participated in mentioning the topic of the Halal Industry. There
were also unfavorable remarks or answers from netizens, with as many as 1,895 or 34% of mentions.
Most netizen responses were positive, with 3,460 or 62% of mentions. Meanwhile, those who
responded neutrally were 230 or (4%) mentions. In total, 5,585 netizens participated in the Halal
Industry topic. Fig. 7 to Fig. 8 shows the total mentions and share of voice by sentiment.

Fig. 7. total mentions by sentiments

Fig. 8. share of voice by sentiment

As shown below, we analyze sentiment by day and comments that lead to pros and cons.
On Monday, there were 584 mentions. Blue commented positively on 301 netizens, and in
red, 267 negative comments. Next was Tuesday, where netizens commented more positively,
as many as 503, negative 154, and neutral 81. The highest peak of netizens commenting on
Wednesday was 1,656 mentions, 695 positive comments, 863 negative, and only 98 neutral.
From Thursday onwards, positive comments are always the most on the following day, like
Thursday, and there are 677 positive and negative comments, only 118: Friday positive 322
and negative 152. On Saturday, there were 400 positive, 74 negative comments. On Sunday,
562 commented positive and 267 negative comments. Fig. 9 shows sentiment by day.

Fig. 9. Sentiment by day

In the middle of the night, at 00:00 or 12 pm, netizens gave 80 positive comments and only 28
negatives. At 04:00, positive comments dropped to 33 and negative ones only 17 comments. At the
peak of commenting at 09:00, there were 239 negative comments, 231 positive and neutral comments,

1895

3460

230

500

1000

1500

2000

2500

3000

3500

4000

Negative Positive Netral

301
503

695 677

322 400
562

267

154

863

118

152 74

26781

200

400

600

800

1000

1200

1400

1600

1800

Monday Tuesday Wednesday Thursday Friday Saturday Sunday

Positve Negative Neutral

34%

62%

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and 13 comments. In addition, netizens' comments have experienced ups and downs, and many still
comment positively about the Halal Industry because in Indonesia, the majority of Muslims, so many
Muslim netizens know halal and haram for them. Fig. 10 shows sentiment by the hour.

Fig. 10. Sentiment by hour

3.3. Influential Source

In Table 1, we analyzed the most shared sites on the topic of the Halal Industry. Here are the top
five sites; first, the site shopee shared 39 times with the I.P. number 143.92.85.2 with SimilarWeb
traffic. Second, the site bisanews.id share up to 7 times with the I.P. number 153.92.10.148 with
SimilarWeb traffic. Third, republika.co.id site shares six times the I.P. number 18.138.109.77 with
SimilarWeb traffic. Fourth, the site tribunnews.com six times with the I.P. number 13.33.88.94
SimilarWeb traffic. Fifth, the site keuangannews.id share up to 4 times with the I.P. number
192.124.249.183 SimillarWeb traffic.

Table.1 Most shared sites

No Sites Number of Shares I.P. Traffic

1 shopee 39 143.92.85.2 SimilarWeb

2 bisanews.id 7 153.92.10.148 SimilarWeb

3 www.republika.co.id 6 18.138.109.77 SimilarWeb

4 www.tribunnews.com 6 13.33.88.94 SimilarWeb

5 keuangannews.id 4 192.124.249.183 SimilarWeb

The first hashtag, "BangkitBersamaET" has 722 tweets, and the second hashtag, "ShopeeID" has
157 tweets. The third down green, "GaspolkinerjapositifBSI" with 103 tweets, and the bottom fourth,
"racuninskincare" with 77 tweets. The fifth bottom color is "collagendrink" 77 tweets, from top to
bottom until the smallest box. Table 4.8 shows a positive comment from one Twitter user on the
hashtag "BangkitBersamaET". Fig. 11 shows the top hashtags in the halal industry.

Fig. 11. Top hashtags

80
29 38 31 33 56

109
158185

231247214210244221200186
249

76
135118105108 97

28
22 20 15 17

156
185

239196
155

56
58

51 75 76

57
47 44 40 50

4
4

5
9

13
10

12
10 20

8 15

20
14 7 13 6

100

200

300

400

500

600

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23

Positive Negative Neutral

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Twitter accounts greatly influence the halal industry conversation on food and tourism accounts.
Fig. 12 shows the top influencers, including @yozariam, @H_Bakkaniy, @MalaysianFoods,
@pmbrutiketmurah, and @MNW_MNW_MN. In other words, the account is lighter to attract the
participation of netizens to provide comments with the theme of the Halal Industry, which has various
discussions ranging from Muslim clothing to halal food.

Fig. 12. Top influencers

In the conversation, it is known that the bot account shows 998 authors (73.60%) with a bot score
of 0-1. That is why in the conversation that discusses the halal industry, it is natural that it is sourced
from netizens, not because of robot accounts. Table 2 shows the results of the bot analysis.

Table.2 Bot score

Bot Score Authors Authors

(%)

Posts Posts (%) Retweeted Mentions Replies

0 - 1 998 73.60 % 1,178 72.94 % 895 169 114

1 - 2 218 16.08 % 254 15.73 % 196 35 23

2 - 3 83 6.12 % 104 6.44 % 74 21 9

3 - 4 40 2.95 % 44 2.72 % 28 10 6

4 - 5 17 1.25 % 35 2.17 % 5 25 5

3.4. Demography Analysis

Of the 4,166 active accounts, it was found that millennials aged 19-29 were very highly engaged
in this Halal Industry-themed conversation or 50.51%, 49.94% of posts were tweeted, 644 tweets were
called 94 times and reposted (replies) 77 times. While 31.38% of 18-year-olds use Twitter and are
involved in this theme, there are 505 posts tweeted, 399 tweets mentioned 57 times and reposted
(replies), and as many as 49. The identified authors were 1,380 or 33.13%. Table 3 shows
demographics by age.

Table.3 Demography by age

Age

Group

Authors Authors

(%)

Posts Posts

(%)

Retweeted Mentions Replies

18 433 31.38 % 505 30.94 % 399 57 49

19-29 697 50.51% 815 49.94 % 644 94 77

30-39 116 8.41 % 140 8.58 % 95 28 17

40 134 9.41 % 172 10.54 % 77 78 17

We found the types of users in this Halal Industry topic Twitter application. There 90.29% of
authors with non-org user types, while 9.71% with organizational user types. Table 4 shows
demographics by user type.

Table.4 Demography of user type

User

Type

Authors Authors (%) Posts Posts (%) Retweeted Mentions Replies

Non-org 1.246 90.29% 1.380 84.56% 1.120 120 140

Is-org 134 9.71% 252 15.44% 95 137 20

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Table 5 shows that 63.26% of men and 36.74% of women were in this Halal Industry topic
conversation, with men posting 65.44% and women 34.56%. It resulted in 766 tweet retweets, 184
mentions, and 118 reposts for the male gender. Meanwhile, women retweeted 449 tweets, referred to
them 73 times, and reposted 42 times.

Table.5 Demography br gender

Gender Authors Authors

(%)

Posts Posts (%) Retweeted Mentions Replies

Male 873 63.26% 1,068 65.44% 766 184 118

Female 507 36.74%% 564 34.56% 449 73 42

Based on this demographic data, it is known that the generation aged 19-29 with non-affiliated
status in organizations and the male gender is the largest producer of tweets about the halal industry
in Indonesia.

4. Conclusion

A total of 5,585 Twitter social users discussed the topic of the Halal Industry. The peak of the
discussion was on August 17, 2022. Before that date, the conversation on this topic experienced daily
ups and downs. Wednesday's mentions were the highest at 1,656 Twitter users. One day there are 24
hours, while at 09.00, the topic is discussed by as many as 483 Twitter. The Top Hashtag is found on
the #BangkitSemangatET account, which has 722 tweets. The top influencer on Twitter accounts, the
most influential related to Halal Industry conversations, is @yozariam 729 engagements. In the
Sentiment analysis, netizens responded positively rather than negatively, with 3,460 positive mentions
from 5,585. Analysis of emotions, anger, and trust are dominant on this topic. The netizens' location
in this topic's distribution in Indonesia is relatively even, not in Eastern Indonesia. This conversation
is less desirable. Millennials aged 19-29 are interested in the Halal Industry, while older people are
only slightly interested. SNA (Social Network Analysis) looks at @yozariam accounts and
@H_Bakkaniy many negative cluster influences, while @MalaysianFoods and @pmbrytiketmurah
have positive clusters.

This study has the limitation of only using Twitter as the primary data for analysis. In the
subsequent study, researchers can use data sources from other social media covering not only one
country.

References

[1] N. Ahmad and S. M. Shariff, “Supply Chain Management: Sertu Cleansing for Halal Logisitics

Integrity,” in Procedia Economics and Finance, Jan. 2016, vol. 37, pp. 418–425, doi: 10.1016/S2212-

5671(16)30146-0.

[2] A. N. Millatina, F. Hakimi, R. A. Budiantoro, and M. R. Arifandi, “The Impact of Halal Label in Halal

Food Buying Decisions,” J. Islam. Econ. Laws, vol. 5, no. 1, pp. 159–176, Mar. 2022, doi:

10.23917/jisel.v5i1.17139.

[3] H. M. H. Habibie and D. R. Donna, “Factors that Influence the Intention to Purchase Halal Food

Products (Case Study of Universitas Gadjah Mada Students),” Benefit J. Manaj. dan Bisnis, vol. 5 No

1, pp. 83–95, Jul. 2020. [Online]. Available at: https://journals.ums.ac.id/index.php/benefit/article/ .

[4] R. Siregar and A. Alam, “Halal Label On Food Products By Mui (Indonesian Ulama Council) And

Students Purchasing Decision Of Faculty Of Business And Economic Universitas Muhammadiyah

Surakarta,” J. Islam. Econ. Laws, vol. 1, no. 1, pp. 1–30, Jul. 2018, doi: 10.23917/jisel.v1i1.6163.

[5] S. B. Istiyanto, M. B. Priyantono, M. A. F. Rifai, K. Wahyuningsih, D. Fansyiari, and L. G. O.

Ramdhani, “Social media learning on Indonesian university students,” Bull. Soc. Informatics Theory

Appl., vol. 5, no. 1 SE-Articles, pp. 58–62, Oct. 2021.[Online]. Available at:

https://pubs.ascee.org/index.php/businta/article/view/433.

https://doi.org/10.1016/S2212-5671(16)30146-0
https://doi.org/10.1016/S2212-5671(16)30146-0
https://doi.org/10.23917/jisel.v5i1.17139
https://journals.ums.ac.id/index.php/benefit/article/view/10653
https://doi.org/10.23917/jisel.v1i1.6163
https://pubs.ascee.org/index.php/businta/article/view/433

110 Bulletin of Social Informatics Theory and Application ISSN 2614-0047
Vol. 6, No. 2, December 2022, pp. 102-110

Apriantoro et.al (Social network analysis of the development of the halal industry in Indonesia)

[6] M. A. Arrazy, M. T. A. Ndaru, N. M. Sari, M. D. Ariyanti, and A. Ghosh, “The impact of social media

use on suicide-related behavior,” Bull. Soc. Informatics Theory Appl., vol. 5, no. 1 SE-Articles, pp. 7–

13, Oct. 2021. [Online]. Available at: https://pubs.ascee.org/index.php/businta/article/view/398.

[7] M. Irfan, Z. Chen, T. S. Adebayo, and M. A. S. Al-Faryan, “Socio-economic and technological drivers

of sustainability and resources management: Demonstrating the role of information and

communications technology and financial development using advanced wavelet coherence approach,”

Resour. Policy, vol. 79, p. 103038, Dec. 2022, doi: 10.1016/j.resourpol.2022.103038.

[8] N. J. Kholit and M. Nastain, “Mapping of data communication networks on social media,” Inject

(Interdisciplinary J. Commun., vol. 5, no. 2, pp. 143–162, Jan. 2021, doi: 10.18326/inject.v5i2.143-

162.

[9] M. Collonnaz et al., “Social network analysis to study health behaviours in adolescents: A systematic

review of methods,” Soc. Sci. Med., vol. 315, p. 115519, Dec. 2022, doi:

10.1016/j.socscimed.2022.115519.

[10] H. Gusfa and F. E. D. Kadjuand, “Political Agonism for Indonesian Cyberpolitic: Critical Cyberculture

to Political Campaign of 2019 Indonesian Presidential Election in Twitter,” Nyimak J. Commun., vol.

4, no. 2, p. 211, Sep. 2020, doi: 10.31000/nyimak.v4i2.2685.

[11] Z. Gilani, R. Farahbakhsh, G. Tyson, and J. Crowcroft, “A Large-scale Behavioural Analysis of Bots

and Humans on Twitter,” ACM Trans. Web, vol. 13, no. 1, pp. 1–23, Feb. 2019, doi: 10.1145/3298789.

[12] K. Anam, L. M Kolopaking, and R. A Kinseng, “The Effectiveness of Social Media Usage within

Social Movement to Reject the Reclamation of the Jakarta Bay, Indonesia,” Sodality J. Sosiol.

Pedesaan, vol. 8, no. 1, pp. 64–81, Apr. 2020, doi: 10.22500/8202028955.

[13] S. H. Sahir, R. S. Ayu Ramadhana, M. F. Romadhon Marpaung, S. R. Munthe, and R. Watrianthos,

“Online learning sentiment analysis during the covid-19 Indonesia pandemic using twitter data,” IOP

Conf. Ser. Mater. Sci. Eng., vol. 1156, no. 1, p. 012011, Jun. 2021, doi: 10.1088/1757-

899X/1156/1/012011.

[14] A. R. Rahmanti, D. N. A. Ningrum, L. Lazuardi, H.-C. Yang, and Y.-C. Li, “Social Media Data

Analytics for Outbreak Risk Communication: Public Attention on the ‘New Normal’ During the

COVID-19 Pandemic in Indonesia,” Comput. Methods Programs Biomed., vol. 205, p. 106083, Jun.

2021, doi: 10.1016/j.cmpb.2021.106083.

[15] M. A. Laagu and A. Setyo Arifin, “Analysis the Issue of Increasing National Health Insurance (BPJS

Kesehatan) Rates through Community Perspectives on Social Media: A Case Study of Drone Emprit,”

in 2020 International Conference on Smart Technology and Applications (ICoSTA), Feb. 2020, pp. 1–

7, doi: 10.1109/ICoSTA48221.2020.1570615599.

[16] V. A. Handini and A. Dunan, “Buzzer as the Driving Force for Buzz Marketing on Twitter in the 2019

Indonesian Presidential Election,” Int. J. Sci. Technol. Manag., vol. 2, no. 2, pp. 479–491, Feb. 2021,

doi: 10.46729/ijstm.v2i2.172.

[17] R. S. Juairiah and H. Ubaya, “Visualization of Twitter Geo-location for Equalization Analysis of Smart

Cities in Indonesia,” in 2020 International Conference on Informatics, Multimedia, Cyber and

Information System (ICIMCIS), Nov. 2020, pp. 278–283, doi: 10.1109/ICIMCIS51567.2020.9354293.

[18] Y. Hanafi et al., “The new identity of Indonesian Islamic boarding schools in the ‘new normal’: the

education leadership response to COVID-19,” Heliyon, vol. 7, no. 3, p. e06549, Mar. 2021, doi:

10.1016/j.heliyon.2021.e06549.

[19] L. Hakim, “COVID-19 and the Moment to Evaluate Tourism Euphoria, Indonesia,” J. Indones. Tour.

Dev. Stud., vol. 8, no. 2, pp. 119–123, Apr. 2020, doi: 10.21776/ub.jitode.2020.008.02.09.

[20] I. Fahmi, “Drone Emprit Academic: Software for social media monitoring and analytics,” Drone

Emprit Acad., 2018.

[21] I. Fahmi, “Drone Emprit: Konsep dan Teknologi,” IT Camp Big Data Data Mining, Jakarta, 2017.

https://pubs.ascee.org/index.php/businta/article/view/398
https://doi.org/10.1016/j.resourpol.2022.103038
https://doi.org/10.18326/inject.v5i2.143-162
https://doi.org/10.18326/inject.v5i2.143-162
https://doi.org/10.1016/j.socscimed.2022.115519
https://doi.org/10.31000/nyimak.v4i2.2685
https://doi.org/10.1145/3298789
https://doi.org/10.22500/8202028955
https://doi.org/10.1088/1757-899X/1156/1/012011
https://doi.org/10.1088/1757-899X/1156/1/012011
https://doi.org/10.1016/j.cmpb.2021.106083
https://doi.org/10.1109/ICoSTA48221.2020.1570615599
https://doi.org/10.46729/ijstm.v2i2.172
https://doi.org/10.1109/ICIMCIS51567.2020.9354293
https://doi.org/10.1016/j.heliyon.2021.e06549
https://doi.org/10.21776/ub.jitode.2020.008.02.09