ANALISIS DATA REVIEW KINERJA APLIKASI E-COMMERCE DENGAN PENDEKATAN MACHINE LEARNING

PRAMONO, ADE (2020) ANALISIS DATA REVIEW KINERJA APLIKASI E-COMMERCE DENGAN PENDEKATAN MACHINE LEARNING. S1 thesis, Universitas Mercu Buana Jakarta.

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Abstract

The development of information technology affects all areas of life,one of them is buying and selling in the form of e-commerce. The public can easily make transactions through internet media. There are many user reviews about the performance of applications in Google Play. Review information can help consumers choose applications and help companies monitor customer satisfaction in order to improve the quality of features and services. Reading the reviews as a whole manually does tend to be time consuming and may not necessarily get the right information. An analysis of e-commerce services is needed to find out how users respond to e-commerce application services. In this research an experiment was conducted to analyze the data of reputable e-commerce reviews in Indonesia, namely Tokedia, Bukalapak, and Shopee. In this study the application of the naive bayes classifier and support vector machine algorithm is examined in classifying review data based on positive or negative class categories. From the classification results then a visualization and text association of each review class is carried out to obtain the required information. Based on the test results it is known that the Naive Bayes classifier algorithm has better performance than support vector machines with an average accuracy of 90.72%, acceptance 91%, recall 91%, and f1-score 91%. Key words: e-commerce, analisis sentiment, machine learning, naïve bayes classifier, support vector machine Perkembangan teknologi informasi mempengaruhi seluruh bidang kehidupan, salah satunya kegiatan jual beli berupa e-commerce. Masyarakat dapat dengan mudah melakukan transaksi melalui media internet. Terdapat banyak ulasan pengguna mengenai kinerja aplikasi yang ada di google play. Informasi ulasan dapat membantu konsumen dalam memilih aplikasi dan membantu perusahan dalam memantau kepuasan pelanggan guna meningkatkan kualitas fitur dan layanan. Membaca ulasan secara keseluruhan dengan cara manual cenderung menghabiskan waktu serta belum tentu mendapatkan informasi yang sesuai. Diperlukan analisis terhadap layanan e-commerce untuk mengetahui bagaimana tanggapan pengguna terhadap layanan aplikasi e-commerce. Pada penelitian ini dilakukan eksperimen untuk analisis data ulasan e-commerce bereputasi baik di Indonesia, yaitu tokopedia, bukalapak, dan shopee. Dalam penelitian ini dikaji penerapan algoritma naive bayes classifier dan support vector machine dalam mengklasifikasi data ulasan berdasarkan kategori kelas positif atau kelas negatif. Dari hasil klasifikasi kemudian dilakukan visualisasi dan asosiasi teks setiap kelas ulasan guna mendapatkan informasi yang diperlukan. Berdasarkan hasil uji coba diketahui bahwa algoritma naive bayes classifier memiliki kinerja lebih baik dari pada support vector machine dengan rata-rata akurasi 90.72%, precision 91%, recall 91%, dan f1-score 91%. Kata kunci: e-commerce, analisis sentiment, machine learning, naïve bayes classifier, support vector machine

Item Type: Thesis (S1)
Call Number CD: JM/TI. 20 100
NIM/NIDN Creators: 41516010122
Uncontrolled Keywords: e-commerce, analisis sentiment, machine learning, naïve bayes classifier, support vector machine
Subjects: 000 Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum > 000. Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum > 005 Computer Programmming, Programs, Data/Pemprograman Komputer, Program, Data
000 Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum > 000. Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum > 005 Computer Programmming, Programs, Data/Pemprograman Komputer, Program, Data > 005.5 General Purpose Application Programs/Program Aplikasi dengan Kegunaan Khusus
600 Technology/Teknologi > 650 Management, Public Relations, Business and Auxiliary Service/Manajemen, Hubungan Masyarakat, Bisnis dan Ilmu yang Berkaitan > 658 General Management/Manajemen Umum > 658.01-658.09 [Management of Enterprises of Specific Sizes, Scopes, Forms; Data Processing]/[Pengelolaan Usaha dengan Ukuran, Lingkup, Bentuk Tertentu; Pengolahan Data]
600 Technology/Teknologi > 650 Management, Public Relations, Business and Auxiliary Service/Manajemen, Hubungan Masyarakat, Bisnis dan Ilmu yang Berkaitan > 658 General Management/Manajemen Umum > 658.01-658.09 [Management of Enterprises of Specific Sizes, Scopes, Forms; Data Processing]/[Pengelolaan Usaha dengan Ukuran, Lingkup, Bentuk Tertentu; Pengolahan Data] > 658.05 Data Processing Computer Applications/Pengolahan Data Aplikasi Komputer
Divisions: Fakultas Ilmu Komputer > Informatika
Depositing User: Dede Muksin Lubis
Date Deposited: 23 Sep 2022 02:16
Last Modified: 23 Sep 2022 02:16
URI: http://repository.mercubuana.ac.id/id/eprint/69425

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