Penerapan metode text mining dengan k-means clustering untuk mengetahui sentimen dan topik populer studi kasus: tiga online marketplace di Indonesia

Fransisko, Andy (2021) Penerapan metode text mining dengan k-means clustering untuk mengetahui sentimen dan topik populer studi kasus: tiga online marketplace di Indonesia. Bachelor thesis, Universitas Pelita Harapan.

[img] Text (Title)
Title.pdf
Restricted to Repository staff only
Available under License Creative Commons Attribution Non-commercial Share Alike.

Download (1MB)
[img]
Preview
Text (Abstract)
Abstract.pdf
Available under License Creative Commons Attribution Non-commercial Share Alike.

Download (339kB) | Preview
[img]
Preview
Text (ToC)
ToC.pdf
Available under License Creative Commons Attribution Non-commercial Share Alike.

Download (1MB) | Preview
[img] Text (Chapter1)
Chapter1.pdf
Restricted to Registered users only
Available under License Creative Commons Attribution Non-commercial Share Alike.

Download (1MB)
[img] Text (Chapter2)
Chapter2.pdf
Restricted to Registered users only
Available under License Creative Commons Attribution Non-commercial Share Alike.

Download (1MB)
[img] Text (Chapter3)
Chapter3.pdf
Restricted to Registered users only
Available under License Creative Commons Attribution Non-commercial Share Alike.

Download (1MB)
[img] Text (Chapter4)
Chapter4.pdf
Restricted to Registered users only
Available under License Creative Commons Attribution Non-commercial Share Alike.

Download (9MB)
[img] Text (Chapter5)
Chapter5.pdf
Restricted to Registered users only
Available under License Creative Commons Attribution Non-commercial Share Alike.

Download (307kB)
[img]
Preview
Text (Bibliography)
Bibliography.pdf
Available under License Creative Commons Attribution Non-commercial Share Alike.

Download (513kB) | Preview
[img] Text (Appendices)
Appendices.pdf
Restricted to Repository staff only
Available under License Creative Commons Attribution Non-commercial Share Alike.

Download (4MB)

Abstract

Pengguna Internet dan media sosial yang banyak dan terus bertambah memicu munculnya peluang bisnis baru di Indonesia. Salah satu indikasinya adalah munculnya sejumlah perusahaan marketplace di Indonesia. Kehadiran online marketplace tersebut membuat masyarakat mempunyai pilihan atas online marketplace sesuai preferensinya. Salah satu faktor yang menjadi dasar pemilihan tersebut adalah dengan membaca komentar atau review dari konsumen atas marketplace yang diunggah di media sosial. Penelitian ini menggunakan metode text mining dengan algoritma k-means clustering untuk mengetahui sentimen dan topik yang paling banyak dibahas oleh konsumen online marketplace di Indonesia. Data yang dibutuhkan untuk diolah oleh algoritma k-means tersebut berupa komentar atau review dari tiga online marketplace (Tokopedia, Shopee dan Bukalapak) yang ada di twitter. Banyak data untuk tiap marketplace dimaksud adalah 1500 data tweets. Hasil dari penelitian menunjukkan bahwa ketiga online marketplace tersebut berasosiasi dengan topik yang berbeda-beda walaupun berada di dalam satu industri yang sama. Kebanyakan konsumen membahas topik mengenai program yang diadakan oleh online marketplace tersebut. Topik utama untuk Tokopedia adalah “belanja” dan “terimakasih”; sedangkan untuk Shopee adalah “pilih” dan “jongho” serta untuk Bukalapak adalah “prakerja”. Hasil analisis sentimen menunjukkan bahwa sentimen ketiga online marketplace tersebut secara dominan netral. / The number of internet and social media users, which continues to increase at a very fast rate, has resulted in the emergence of new business opportunities in Indonesia. One indication is the emergence of marketplace companies in Indonesia. The presence of this online marketplace makes people have choices of online marketplaces according to their preferences. One of the factors that became the basis for this election was reading comments or reviews from consumers on the marketplace posted on social media. This research was conducted using text mining method with k-means clustering algorithm to find out the sentiments and topics that are widely discussed by online marketplace consumers in Indonesia. Required data was processed by the k-means algorithm in the form of comments or reviews from three online marketplaces (Tokopedia, Shopee and Bukalapak) on Twitter. The amount of data for each marketplace referred to is 1500 data tweets. The results showed that the three online markets were related to different topics, even though they are in the same industry. Most consumers discuss topics about the programs held by their respective online marketplaces. The main topics related to Tokopedia are “belanja” (“shopping”) and “terima kasih” (“thank you”); while for Shopee “pilih” (“choose”) and “jongho”, and for Bukalapak “pra-kerja” (“pre-employment”). The sentiment analysis conducted shows that the sentiment of the three online markets is dominant neutral.

Item Type: Thesis (Bachelor)
Creators:
CreatorsNIMEmail
Fransisko, AndyNIM01081170001andyfransisko1@gmail.com
Contributors:
ContributionContributorsNIDN/NIDKEmail
Thesis advisorWidjaja, Andree EmmanuelNIDN0313098505andree.widjaja@uph.edu
Uncontrolled Keywords: text mining; kmeans; online marketplace; review; media sosial
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: University Subject > Current > Faculty/School - UPH Karawaci > School of Information Science and Technology > Information Systems
Current > Faculty/School - UPH Karawaci > School of Information Science and Technology > Information Systems
Depositing User: Users 9303 not found.
Date Deposited: 01 Mar 2021 10:32
Last Modified: 01 Mar 2021 10:32
URI: http://repository.uph.edu/id/eprint/24491

Actions (login required)

View Item View Item