Penerapan Machine Learning Untuk Menentukan Tingkat Kepuasan Tamu Hotel Dymens Menggunakan Metode Vader

  • Agung Ramadhanu Sistem Informasi,Universitas Putra Indonesia”YPTK”,Padang
  • Muhammad Raihan Zaky Fakultas Ilmu Komputer, Universitas Putra Indonesia “YPTK” Padang
  • Mokti Isra Fakultas Ilmu Komputer, Universitas Putra Indonesia “YPTK” Padang
  • Neni Sri Wahyuni Nengsih Fakultas Ilmu Komputer, Universitas Putra Indonesia “YPTK” Padang
  • Sularno Sularno Sistem Informasi, Universitas Dharma Andalas
  • Muhammad Razi A Universitas Jambi
Keywords: Machine Learning (ML), Valance Aware Dictonary and Sentimental Reasoner (VADER) Methods

Abstract

In Indonesia there are several social media that provide reviews and experiences related to an inn, including Tripadvisor.com, Traveloka, Tiket.com, and many more. Over time, machine learning can replace and improve human abilities in various fields, Machine Learning has been extensively researched and used to solve various problems. Among them is to find out how the assessment and views of hotel guests regarding the services and policies set. With reviews from customers or hotel guests, we can find out how the quality of the product or service is implemented, so that an evaluation can be carried out to increase customer satisfaction. Sentiment analysis, or opinion evaluation is an active area of ​​study in the field of natural language processing that analyzes opinions, sentiments, evaluations, attitudes, and emotions through improving the processing of subjectivity in texts. Sentiment analysis is useful for a wide variety of issues of interest to human-computer interaction practices and researchers, as well as people from fields such as: sociology, marketing and advertising, psychology, eco-economics, and political science. The process of sentiment analysis is often done to find out positive, neutral or negative opinion from the public regarding a certain matter. The Valence Aware Dictionary and Sentiment Reasoner (VADER) method is a sentiment analysis method that can identify a person's emotions based on words. So that the VADER Method can be used to identify hotel guest reviews and hotel management can make decisions based on the results of these assessments or reviews

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References

Ahmad Farki, Imam Baihaqi, dan Berto Mulia Wibawa. (2016). Pengaruh Online Customer Review dan Rating Terhadap Kepercayaan dan Minat Pembelian pada Online Marketplace di Indonesia. Jumal Teknis lnstitut Teknologi Surabaya, 5 (2): 2301-9271

Sunarya, A., Santoso, S., & Sentanu, W. (2015). Sistem Pakar Untuk Mendiagnosa Gangguan Jaringan Lan. CCIT Journal, 8(2), 1–11.

Goldberg, D.E., Holland, J.H. Genetic Algorithms and Machine Learning. Machine Learning 3, 95–99 (1988). https://doi.org/10.1023/A:1022602019183

Nayak, A., & Dutta, K. (2017). Impacts of machine learning and artificial intelligence on mankind. 2017 International Conference on Intelligent Computing and Control (I2C2), 1–3. https://doi.org/10.1109/I2C2.2017.83219 08

Hutto, C., & Gilbert, E. (2014, May). Vader: A parsimonious rule-based model for sentiment analysis of social media text. In Proceedings of the international AAAI conference on web and social media (Vol. 8, No. 1, pp. 216-225).

Adiyanto, R. (n.d.). Mengenal Web Dinamis dan Statis Serta Perbedaanya Pendahuluan.

Destiningrum, M., & Adrian, Q. J. (2017). SISTEM INFORMASI PENJADWALAN DOKTER BERBASSIS WEB DENGAN MENGGUNAKAN FRAMEWORK

CODEIGNITER ( STUDI KASUS : RUMAH SAKIT YUKUM MEDICAL CENTRE). 11(2), 30–37.

Effendi, & Rina Noviana. (2021). Perancangan Web Sistem Analisis Sentimen Media Sosial Twitter Dengan Metode Valence Aware Dictionary And Sentimen Reasoner (Vader) Menggunakan PHP & MysSQL pada Pemerintah Kota Bekasi. Jurnal Ilmiah Komputasi, 20(1). https://doi.org/10.32409/jikstik.20.1.369

Farmasi, P. S. (2016). Sistem Informasi Pengolahan Data Penanggulangan Bencana (BPBD) Kabupaten Padang Pariaman. 4(4).

Fitri Ayu and Nia Permatasari. (2018). perancangan sistem informasi pengolahan data PKL pada divisi humas PT pegadaian. Jurnal Infra Tech, 2(2), 12–26.

Hasbiyalloh, M., & Jakaria, D. A. (2018). Aplikasi Penjualan Barang Perlengkapan Hand Phone di Zildan Cell Singaparna Kabupaten Tasikmalaya. Jumantaka, 1(1), 61–70.

Putra, P., Toresa, D., Fadrial, Y., Sari, P., Muzawi, R., Sularno, S., & Sahrun, N. (2022). Sistem Pendukung Keputusan Penentuan Penerima BLT Menggunakan Metode SAW. Jurnal Teknologi Dan Sistem Informasi Bisnis, 4(2), 285-293. https://doi.org/10.47233/jteksis.v4i1.457

Published
2023-07-16
How to Cite
Ramadhanu, A., Zaky, M. R., Isra, M., Nengsih, N. S. W., Sularno, S., & A, M. R. (2023). Penerapan Machine Learning Untuk Menentukan Tingkat Kepuasan Tamu Hotel Dymens Menggunakan Metode Vader. Jurnal Teknologi Dan Sistem Informasi Bisnis, 5(3), 337-343. https://doi.org/10.47233/jteksis.v5i3.866
Section
Articles