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All Journal Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer
M. Ali Fauzi
Fakultas Ilmu Komputer, Universitas Brawijaya
Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering

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Prediksi Rating Pada Review Produk Kecantikan Menggunakan Metode Semantic Orientation Calculator dan Regresi Linier Bastian Dolly Sapuhtra; M. Ali Fauzi; Bayu Rahayudi
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 5 (2019): Mei 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Crowded producers of beauty product produce good and varied products. This has attracted consumers to use these beauty products. More and more consumers are using these beauty products, making producers try various innovations on their products. Innovation can be obtained from many comments, advices, or reviews made by consumers on variety of products. Benefits of product reviews for consumers are also useful to obtain information before buy a product. Many results of the review are not accompanied by rating. This makes it difficult for producers to classify reviews into certain sentiments. In this research aims to classify review into certain sentiments automatically into rating. In this research built a system using Semantic Orientation Calculator and Linear Regression methods. Breaking sentences in a review into n-gram (bigram and trigram) and one sentence aims to improve the results of predictions. Results of testing on this system are 23%, 71%, 67% on accuracy of bigram, 24%, 71%, 67% on accuracy of trigram, and lowest 24%, 67%, 64% on accuracy of one sentence with tolerance 0, tolerance 1, and sentiment reviews. The best result of testing on breaking sentence using n-gram (bigram and trigram) was good enough to solve problem in this research.
Seleksi Fitur Information Gain untuk Klasifikasi Informasi Tempat Tinggal di Kota Malang Berdasarkan Tweet Menggunakan Metode Naive Bayes dan Pembobotan TF-IDF-CF Ahmad Efriza Irsad; Yuita Arum Sari; M. Ali Fauzi
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 5 (2019): Mei 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (733.995 KB)

Abstract

Malang city is a city that has a significant increase in population, which is around 50 thousands people in just period of 5 years. One of the reasons is because Malang city is a city of education, the reasons its called city of education is because in this City there are a lot of public university and private university that are quite popular, such as Universitas Brawijaya (UB), Universitas Islam Malang (Unisma), etc. This resulted many migrants from outside the area of Malang city study in Malang city. There are some things that might be the reasons why migrants choose Malang city, such as the Malang city have one of the best quality university in Indonesia. When becoming a migrant, the most needed thing is certainly a place to live in a long term, because of that the migrants need information on where to live in the form of boarding house or rent house to live in, we can get this kind of information trough social media like Twitter, but on Twitter there is still no category for this kind of information. By seeing this problem, we can use Classification technique to classified the information in the form of living quarters in the city of Malang. In this study Naive Bayes method is used as the classification method, and Information gain as the feature selection method. Before entering the classification process the weighting is done first using TF-IDF-CF method. This study uses 150 training data and 60 testing data. The highest accuracy value in this study are 71,66% using 33% of feature, using TF-IDF-ICF weighthing and, without using number feature.
Co-Authors Ahmad Efriza Irsad Bastian Dolly Sapuhtra Bayu Rahayudi Yuita Arum Sari