CLASSIFICATION OF CUSTOMER COMPLAINTS ON INSTAGRAM COMMENTS USING NAÏVE BAYES ALGORITHM WITH N-GRAM FEATURE EXTENSION

  • Fachri Amsury Sekolah Tinggi Manajemen Informatika dan Komputer Nusa Mandiri
  • Nanang Ruhyana Sekolah Tinggi Manajemen Informatika dan Komputer Nusa Mandiri
  • Irwansyah Saputra Sekolah Tinggi Manajemen Informatika dan Komputer Nusa Mandiri
  • Daning Nur Sulistyowati Sekolah Tinggi Manajemen Informatika dan Komputer Nusa Mandiri
Keywords: SMOTE Technique, N-Gram, Classification, Comments Instagram, Complaints, Naïve Bayes

Abstract

Customer complaints about the company can be used as a form of self-evaluation and performance that has been carried out by the company, based on customer complaints the company can find out the weaknesses that exist in the company and fix them. The forms of submitting customer complaints are very diverse, currently not only by telephone, but customers also submit suggestions or complaints, customers can submit suggestions or complaints via electronic mail or e-mail or forums in cyberspace that are indeed created by product-producing companies to accommodate various complaints, suggestions, and direct criticism from consumers, especially social media that are free to express opinions on the delivery services used. Instagram is a social media that is more inclined towards images and on the other hand, has captions and comments text, a study is needed for the problem of customer complaints from shipping service users on an Instagram account of a delivery service company. Based on this background, a solution is needed in solving problems for text mining classification using Naïve Bayes with SMOTE techniques and N-Gram feature extraction with the usual process for text mining so that it can produce Naïve Bayes and SMOTE accuracy with an accuracy of 88.54%, before implementation. N-Gram and the accuracy rate increased by 1.44% after the N-Gram Term was applied to 89.98% by using a dataset of 776 Instagram comment text records that had to preprocess text.

References

Amsury, F., Ruhyana, N., Saputra, I., & Sulistyowati, D. N. (2020). Laporan Akhir Penelitian Mandiri: Klasifikasi Keluhan Pelanggan Pada Komentar Instagram Menggunakan Algortima Naïve Bayes Dengan Ekstarksi Fitur N-Gram. Jakarta.

APJII. (2019). Buletin APJII Edisi-40 - Mei 2019: Survei APJII yang Ditunggu-tunggu,Penetrasi Internet Indonesia 2018. Retrieved from apjii.or.id website: https://apjii.or.id/content/read/104/418/BULETIN-APJII-EDISI-40---Mei-2019

Dellia, P., & Tjahyanto, A. (2017). Tax Complaints Classification on Twitter Using Text Mining. IPTEK Journal of Science, 2(1), 11–15. https://doi.org/10.12962/j23378530.v2i1.a2254

Dewi, R. N. (2018). Model Text Mining Untuk Identifikasi Keluhan Pelanggan Produk Perusahaan Perangkat Lunak (Universitas Islam Indonesia). Universitas Islam Indonesia. Retrieved from https://dspace.uii.ac.id/bitstream/handle/123456789/10239/Tesis Rona Neysa Dewi 12917229.pdf?sequence=2&isAllowed=y

Hartini, S. (2016). Efektifitas Endorsment pada Media Sosial Instagram pada Produk Skin Care. Bina Insani ICT Journal, 3(1), 43–50. Retrieved from http://www.ejournal-binainsani.ac.id/index.php/BIICT/article/view/794

Indriyani, S., & Mardiana, S. (2016). Pengaruh Penanganan Keluhan (Complaint Handling) Terhadap Kepercayaan Dan Komitmen Mahasiswa Pada Perguruan Tinggi Swasta Di Bandar Lampung. Jurnal Bisnis Darmajaya, 2(1), 1–13. Retrieved from https://journal.darmajaya.ac.id/index.php/JurnalBisnis/article/view/615

Indriyani, Susi. (2014). FAKTOR EMPATI DALAM PENANGANAN KELUHAN TERHADAP KEPERCAYAAN DAN KOMITMEN MAHASISWA DI STIE MITRA LAMPUNG. Seminar Bisnis & Teknologi 2014 IBI Darmajaya, 1–15. Bandar Lampung: Institut Informatika Dan Bisnis Darmajaya. Retrieved from https://jurnal.darmajaya.ac.id/index.php/sembistek/article/view/199

Laksana, J., & Purwarianti, A. (2015). Indonesian Twitter text authority classification for government in Bandung. Proceedings - 2014 International Conference on Advanced Informatics: Concept, Theory and Application, ICAICTA 2014, 129–134. https://doi.org/10.1109/ICAICTA.2014.7005928

Mayasari, I. Y., & Indriyani, R. (2016). Analisis Strategi Bersaing pada PT.Citra Surya Pacific. AGORA, 4(2), 188–196. Retrieved from http://publication.petra.ac.id/index.php/manajemen-bisnis/article/view/4803

Putri, R. L. (2016). Peningkatan Kualitas Produk Melalui Penerapan Prosedur dan Sistem Produksi : Studi Pada UD Wijaya Kusuma Kota Blitar. Jurnal Wahana Riset Akuntansi, 4(2), 813–828. Retrieved from http://ejournal.unp.ac.id/index.php/wra/article/view/7223/

Ruhyana, N., & Rosiyadi, D. (2019). Klasifikasi Komentar Instagram Untuk Identifikasi Keluhan Pelanggan Jasa Pengiriman Barang Dengan Teknik Smote. Faktor Exacta, 12(4), 280–290. https://doi.org/10.30998/faktorexacta.v12i4.4981

Sabirin, & Setiawati, C. I. (2017). The driving factors of instagram utilization for marketing efforts in promoting student owned online store. Proceedings - 2016 International Seminar on Application of Technology for Information and Communication, ISEMANTIC 2016, 64–69. https://doi.org/10.1109/ISEMANTIC.2016.7873811

Setiawan, R. A., & Setyohadi, D. B. (2017). Analisis Komunikasi Sosial Media Twitter sebagai Saluran Layanan Pelanggan Provider Internet dan Seluler di Indonesia. Journal of Information Systems Engineering and Business Intelligence, 3(1), 16.

https://doi.org/10.20473/jisebi.3.1.16-25

Sieber, J. E. (2008). Data Mining: Knowledge Discovery for Human Research Ethics. Journal of Empirical Research on Human Research Ethics, 3(3), 1–2. https://doi.org/10.1525/jer.2008.3.3.1

Widagdo, P. B. (2016). Perkembangan Electronic Commerce ( E- Commerce ) di Indonesia. Yogjakarta.

Published
2020-09-15
How to Cite
Amsury, F., Ruhyana, N., Saputra, I., & Sulistyowati, D. (2020). CLASSIFICATION OF CUSTOMER COMPLAINTS ON INSTAGRAM COMMENTS USING NAÏVE BAYES ALGORITHM WITH N-GRAM FEATURE EXTENSION. Jurnal Techno Nusa Mandiri, 17(2), 109-116. https://doi.org/10.33480/techno.v17i2.1632