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All Journal KOMIK (Konferensi Nasional Teknologi Informasi dan Komputer)
Simatupang, Meylita Putri
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Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering

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ANALISA TESTIMONIAL DENGAN MENGGUNAKAN ALGORITMA TEXT MINING DAN TERM FREQUENCY- INVERSE DOCUMENT FREQUENCE (TF-IDF) PADA TOKO ALLMEEART Simatupang, Meylita Putri; Utomo, Dito Putro
KOMIK (Konferensi Nasional Teknologi Informasi dan Komputer) Vol 3, No 1 (2019): Smart Device, Mobile Computing, and Big Data Analysis
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/komik.v3i1.1697

Abstract

E-commerce or often referred to as an online shop is the latest trend of the community in carrying out shopping activities, first before the rise of e-commerce companies like today the community to meet their needs still rely on distros around the customer lives, or to a shopping place but now it has switch to shoop online. The advantages offered by online shoop are the relatively low prices, no need to shop locations, and guarantee goods, it has an impact on retail shops that are increasingly lonely. Testimonials are one of the techniques carried out to convince customers to shop at e-commerce they have, testimonials are the responses of buyers for their experience of shopping in an e-commerce application starting from the payment process until the goods are received, the more positive experiences conveyed in the testimonials, the customer who have not shopped on an e-commerce application will be more convinced to shop. Testimonials on an e-commerce application are not always positive, there are times when testimonials are delivered by negative buyers. The customer's problem is the unavailability of percentages or information on the number of buyers with positive and negative shopping experiences because in general testimonials are only delivered in the form of a list.Keywords:  Testimonial Analysis, Text Mining Algorithm, Term Frequency-Inverse Document Frequency (TF-IDF)
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