A Analisis Tingkat Kepuasan Konsumen Pada Pelayanan PT. AXZ Furniture Di Media Internet Menggunakan Metode VADER dan ARM

Ida Ayu Laksmi; I Made Candiasa; Putu Hendra Suputra

doi:10.30865/jurikom.v12i6.9322

Authors

Ida Ayu Laksmi Universitas Pendidikan Ganesha, Singaraja
I Made Candiasa Universitas Pendidikan Ganesha, Singaraja
Putu Hendra Suputra Universitas Pendidikan Ganesha, Singaraja

DOI:

https://doi.org/10.30865/jurikom.v12i6.9322

Keywords:

Vader, Association Rule, Confusion Matrix, positif, negatif, netral, Furniture

Abstract

Bali Art Furniture is one of the companies in Bali that exports furniture and home decoration products. During its operation, this company utilises various internet media platform services such as websites, Facebook Marketplace, Instagram, WhatsApp Business, Pinterest, and Google to communicate online with consumers. As the company has grown over time, it has recruited many employees to increase its capacity to provide services. The company has never conducted a systematic evaluation of customer service satisfaction, either internally or externally. Based on this phenomenon, a customer satisfaction analysis was conducted using customer comment data. Customer service satisfaction was evaluated using the VADER and ARM methods as a basis for comparing the effectiveness of these methods. Based on the analysis of the two methods, the VADER method produced an accuracy of 34%, while the ARM method produced an accuracy of 64%. The evaluation results using the confusion matrix of the VADER model showed that positive comments were more recognisable by the system than negative and neutral comments, as seen from the positive recall value of 0.90, which was greater than the negative and neutral recall values. Meanwhile, the evaluation results using the ARM method showed that neutral comments were more recognisable by the system than positive and negative comments, as seen from the neutral recall value of 0.88, which was greater than the positive and negative recall values. Thus, the highest accuracy results in the ARM model became the guideline in making recommendation results.

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