Opinion Mining On E-Commerce Data Using Sentiment Analysis And K-Meloid Clustering
|1st Untung Rahardja||
2nd Taqwa Hariguna
|3rd Wiga Maulana Baihaqi|
|Universitas Raharja||STMIK Amikom Purwokerto||STMIK Amikom Purwokerto|
|Dept. Information System||Dept. Information System||Dept. Information System|
|Tangerang, Indonesia||Puwokerto, Indonesia||Puwokerto, Indonesia|
|[email protected]||[email protected]||[email protected]|
Prof. Dr. Ir. Untung Rahardja, M.T.I., MM sambutan sebagai tuan rumah.
lanjut dengan presentasi jurnal ilmiah
This study aimed to analyze sentiment opinions to find out the opinions of users on an-commerce Web. The method used was through analyzing text reviews obtained from customers on e-commerce website. The algorithm used was k-medoid clustering.
Nowadays, the development of web technology is increases rapidly. the internet becomes a very important source of information for many people. This progress has resulted in an increase in the use of e-commerce. Many people tend to make goods purchases transactions online. In this context, reviews from previous buyers greatly influence the decisions that will be made by be buyer. In general, the experience felt by previous customers tends to be shared in the comments column on the website, the feelings or emotions will be revealed to the product the buy. From the results of customer reviews can greatly help new buyers to choose the products they want. This is caused by the opinions of others people are important things that can influence their decisions the from computation,
sentiments, emotions in the from of text.
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