Ekplorasi Timeline : Waktu Respon Pesan Terbaik WhatSapp Group “Gurauan kita STMIK Amik”

  • Susandri susandri STMIK Amik Riau
  • Sarjon Defit Universitas Putra Indonesia YPTK Padang, Indonesia
  • Fristi Riandari STMIK Pelita Nusantara, Medan, Sumatera Utara, Indonesia
  • Bosker Sinaga STMIK Pelita Nusantara, Medan, Sumatera Utara, Indonesia
Keywords: Timiline, WhatSapp Group, Waktu respon terbaik, Sentimen, Emoji

Abstract

WhatsApp merupakan salah satu aplikasi pesan instan yang banyak di gunakan saat ini. WhatsApp memungkinkan pengguna membuat grup. Sering pesan pada grup tidak terbaca dan terabaikan oleh anggota grup. Perlu dilakukan analisa waktu yang tepat sebuah pesan direspon anggota grup dengan cepat sehingga informasi dapat disampaikan dengan baik pada semua anggota. Penelitian ini melakukan explorasi WhatSapp Group “Gurauan kita STMIK Amik” untuk menentukan waktu terbaik menyampaikan pesan dengan metode timeline serta menganalisis anggota yg berjumlah 32 orang, emoji dan sentimen. Pada Analisis sentimen dari 1095 total pesan, sentimen positif 35.53% dan sentimen negatif 64.47%. Respon emoji dari anggota sebanyak 46% menggunakan pesan emoji diatas 50% dan 34% anggota menggunakan emoji dibawah 50% sedangkan 18 % anggota tidak pernah menggunakan emoji. Dalam penelitian ini dari proses timeline dapat disimpulkan waktu terbaik untuk mengirimkan pesan pada hari selasa dan jum’at pada jam 10, 13 sampai 15 siang dan jam 20 pada malam hari.

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References

[1] M. M. Alsulami and A. Y. Al-Aama, “Exploring User’s Perception of Storage Management Features in Instant Messaging Applications: A Case on WhatsApp Messenger,” 2nd International Conference on Computer Applications and Information Security, 2019.
[2] T. K. Eds et al., “Beyond social chit chat? Analysing the social practice of a mobile messaging service on a higher education teacher development course,” International Journal of Educational Technology in Higher Education, vol. 3, no. 1, pp. 1–6, 2020.
[3] A. M.-F. and A. J. Emma Baulch, “Introduction: Ten year of Whatsapp: The role of chatapps in the formation and mobilizationof online publics,” First Monday, vol. 19, no. 1, pp. 1–7, 2020.
[4] G. Motteram, S. Dawson, and N. Al-Masri, “WhatsApp supported language teacher development: A case study in the Zataari refugee camp,” Education and Information Technologies, vol. 25 no. 6, pp 5731-5751, 2020.
[5] Ravishankara K, Dhanush, Vaisakh, and Srajan I S, “Whatsapp Chat Analyzer,” International Journal of Engineering Research & Technology, vol. 9, no. 5, pp. 897–900, 2020.
[6] A. Sinha, T. K. Midhush Manohar, S. Subramanian, and B. Das, “Text Segregation on Asynchronous Group Chat,” Procedia Computer Science. vol. 171, pp. 1371–1380, 2020.
[7] S. H. S. Nizam, N. H. Ab Rahman, and N. D. W. Cahyani, “Keyword Indexing And Searching Tool (KIST): A Tool to Assist the Forensics Analysis of WhatsApp Chat,” International Journal on Information and Communication Technology (IJoICT), vol. 6, no. 1, pp. 23-30, 2020.
[8] H. Shidek, N. Cahyani, and A. A. Wardana, “WhatsApp Chat Visualizer: A Visualization of WhatsApp Messenger’s Artifact Using the Timeline Method,” International Journal on Information and Communication Technology (IJoICT), vol. 6, no. 1, pp. 1-9, 2020.
[9] K. Manchikanti and B. Madhurika, “AirLine Tweets Sentiment Analysis using RNN and LSTM Techniques,” International Journal of Advanced Trends in Computer Science and Engineering, vol. 9, no. 5, pp. 8197–8201, 2020.
[10] N. Olizko, “Semiotic And Synergetic Methods Of Text Analysis,” 10th International Conference “Word, Utterance, Text: Cognitive, Pragmatic and Cultural Aspects”, pp. 1056–1063, 2020.
[11] L. Dogruel and A. Schnauber-Stockmann, “What determines instant messaging communication? Examining the impact of person- and situation-level factors on IM responsiveness,” Mobile Media & Communication, vol. 9, no.2, pp. 210-228. 2020.
[12] M. Thomas and C. A. Latha, “Sentimental analysis of transliterated text in Malayalam using recurrent neural networks,” Journal of Ambient Intelligence and Humanized Computing, vol. 11 no. 7, 2020.
[13] S. Rathor, “Use of Hadoop for Sentiment Analysis on Twitter’s Big Data,” Smart Innovations in Communication and Computational Sciences, Advances in Intelligent Systems and Computing 1168, pp. 47–53, 2020
[14] R. Xia and Z. Ding, “Emotion-cause pair extraction: A new task to emotion analysis in texts,” ACL 2019 - 57th Annual Meeting of the Association for Computational Linguistics, Proceedings of the Conference, pp. 1003–1012, 2020.
[15] K. König, “HM and EHM as discourse markers in German WhatsApp chats,” Discourse, Context Media, vol. 39, no.1, pp. 100457, 2021
[16] I. Bulut, M. Erdogan, B. Gonulal, R. Bas, and O. Kilic, “Using Short Texts and Emojis to Predict the Gender of a Texter in Turkish,” UBMK 2019 - Proceedings, 4th International Conference on Computer Science and Engineering, pp. 435–438, 2019.
[17] J. Völker and C. Mannheim, “Tuned in on senders’ self-revelation: Emojis and emotional intelligence influence interpretation of WhatsApp messages,” Computers in Human Behavior Reports, vol. 3, no. 1, pp. 100062, 2021.
[18] H. Taha Assaggaf, “A Discursive and Pragmatic Analysis of WhatsApp Text-based Status Notifications,” Arab World English Journal, vol. 10, no. 4, pp. 101–111, 2019.
[19] F. Al Rashdi, “Functions of emojis in WhatsApp interaction among Omanis,” Discourse, Context Media, vol. 26, no. 6, pp. 117–126, 2018.
[20] A. Sampietro, "Emoji and rapport management in Spanish WhatsApp chats," Journal of Pragmatics vol. 143. no. 5 , pp. 109-120, 2019.
Published
2021-05-31
How to Cite
susandri, S., Defit, S., Riandari, F., & Sinaga, B. (2021). Ekplorasi Timeline : Waktu Respon Pesan Terbaik WhatSapp Group “Gurauan kita STMIK Amik”. MATRIK : Jurnal Manajemen, Teknik Informatika Dan Rekayasa Komputer, 20(2), 317-324. https://doi.org/https://doi.org/10.30812/matrik.v20i2.1149
Section
Articles