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All Journal Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Community Empowerment
Yuita Arum Sari
Fakultas Ilmu Komputer , Universitas Brawijaya
Arts Humanities Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering Public Health Social Sciences

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Analisis Sentimen Review Produk Kecantikan menggunakan Metode Naive Bayes Binti Najibah Agus Ratri; Yuita Arum Sari; Indriati Indriati
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 5 No 12 (2021): Desember 2021
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

People are interested in buying and selling using e-commerce. In the place of buying and selling many products, one of which is beauty products. Many beauty products offer various advantages, with many products not being separated from reviews that assess a particular product regarding quality, advantages, disadvantages, and others. A review from a customer who has used the product can be used as a recommendation to choose the best product and as a determinant of product quality. Determination of product quality can be seen from various comments or reviews from customers to see whether the product is a best seller product or a less desirable product. Therefore, beauty product review data classification is carried out by labelling positive, negative, and neutral reviews. In this test using the Naive Bayes method with TF and TF Log weighting, TF weighting has a better accuracy value than TF Log weighting. TF weighting has an accuracy of 55% while TF Log weighting only has an accuracy of 52%. Meanwhile, to label the review using a kappa measure, in this test the kappa measure on each rater has the same value, namely 0.8.
Pengenalan Citra Makanan Kue Tradisional menggunakan Ekstraksi Fitur HSV Color Moment dan Local Binary Pattern dengan K-Nearest Neighbour Gagas Budi Waluyo; Yuita Arum Sari; Bayu Rahayudi
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 5 No 12 (2021): Desember 2021
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Traditional cakes or market snacks are traditional foods that we need to preserve, these traditional cakes are very rarely found today, because many people do not know about these traditional cakes and are very rarely found in this modern era. Actually this traditional cake is a delicious food and there are many various types and certainly not too many preservatives in it. But over time traditional cakes have been shifted by modern food and a lot of food is imported into the country, therefore it is time to preserve it so that it does not become extinct and posterity can find out. So a system is needed to recognize traditional cakes using technology as it is today n this study, to recognize traditional cakes using Hue Saturation Value (HSV) color feature extraction and Local Binary Pattern (LBP) texture features and classified using the K-Nearest Neighbor (KNN) method. The color feature used is the color moment which produces three values, namely the mean, standard deviation, and skewness. While the LBP texture feature will produce a grayscale value as much as the number of neighbors used. After that, the obtained feature extraction is classified using K-Nearest Neighbor. The test results show that if you only use the HSV color feature method, you get an accuracy value of 75%. If only using the LBP texture feature method, the accuracy value is 72.5%. Meanwhile, if the two feature extraction methods are combined, the accuracy value is 75%.
Analisis Sentimen Masyarakat Indonesia terhadap Covid-19 pada Media Sosial Twitter menggunakan Metode Naive Bayes Tuahta Ramadhani; Yuita Arum Sari; Edy Santoso
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 5 No 12 (2021): Desember 2021
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Twitter is often used by users to write or discuss issues and various topics that are currently happening. Twitter, which has many active users, is able to create a Twitter trending topic, where people are able to freely share information as well as the latest opinions on issues that are being discussed internationally. Not only as a liaison for socializing and interacting, Twitter can be used as a means of giving hope and showing about many things that are happening also in the community, such as in the case of the Covid-19 pandemic in Indonesia. With the emergence of the Covid-19 pandemic, it has caused various opinions from citizens, especially on Twitter social media users, especially the Indonesian people. Information about the views of residents is conveyed very quickly. there are those who defend and disagree regarding the information regarding the emergence of the Covid-19 pandemic. Everyone has their own thoughts and opinions, therefore this sentiment analysis can be applied to find out people's opinions on events that occur. In addition, in this study, sentiment analysis can be used to determine the level of accuracy based on data comments or opinions contained on Twitter social media. This study uses a classification strategy based on the Naive Bayes algorithm to classify text into three classes, namely positive, negative, and neutral. The use of this algorithm is also because it is a simple method. The difference between this study and previous research is the object of research which focuses on tweet comments related to Covid-19. From this study, it can be concluded that the results of the sentiment analysis system using the Naive Bayes method for Covid-19 data on Twitter and the level of accuracy with the Confusion Matrix are 87%.
Pengelompokan Ulasan Produk HP pada Marketplace Tokopedia menggunakan Metode Semi Supervised K-Means Rizky Ardiawan; Yuita Arum Sari; Bayu Rahayudi
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 6 No 1 (2022): Januari 2022
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

The internet has grown rapidly in accordance with the changing times. It also changes shopping behavior that was originally face to face now can be done online. Cell phones or smartphones are the most sought after items today. To buy these items online, there are many marketplaces available in Indonesia, such as Tokopedia. A product review is rated as the main factor for consumers to buy goods. To perform analysis on reviews, a method is needed that can classify and group reviews into existing categories. By combining the two understandings between Supervised and unsupervised, one can create a grouping method based on training data consisting of labeled data. The method that is suitable for this case is the Semi Supervised K-Means method. From the results of this study, it was found that in 4 different experiments, the evaluation of the cluster value using Silhouette was 0.013647 which was the largest value using the Semi Supervised K-Means method. Which is very small, namely 3 clusters. However, the results of clustering the clusters produced in the same method proved to be better than the K-Means method in general with the review data according to the original label.
Pengembangan Sistem Informasi Verifikasi Keaslian Hasil Test Swab di Dunia Penerbangan (Studi Kasus: Kantor Kesehatan Pelabuhan Kelas 1 Soekarno-Hatta) Nur Aisyah Asriani; Fajar Pradana; Yuita Arum Sari
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 6 No 2 (2022): Februari 2022
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

The Soekarno-Hatta Airport Class I Aviation Health Office (AHO) is a government institution tasked with validating COVID-19 negative test result (CNTR) documents, which is one of the prerequisites for boarding a flight. At one point, there have been forgeries made to such documents, which passed the manual and offline validation process done by AHO. To solve this problem, the writer try to devise an Information System for Verification of Swab Test Result Authenticity, which performs the validation automatically and online, so that flying can be safer from the risk of COVID-19 spread. The system was built by using the prototype development method, which consists of several stages, including data collection, requirements analysis, prototype building, prototype evaluation, system design, system implementation and system testing. Based on iterations done, there were 13 requirements identified from 2 actors, COVID-19 testing labs, AHO and system admin. Implementation was done using the javascript programming framework ReactJS and NodeJS. System testing was divided into four stages which consist of unit testing with 3 samples, integration testing to produce valid results, validation testing to obtain valid results from test cases, and non-functional testing in the form of usability testing using the System Usability Scale (SUS) method that obtained a point of 73,46 from 15 respondents.
Co-Authors Achmad Arwan Achmad Dinda Basofi Sudirman Ade Kurniawan Adella Ayu Paramitha Adi Mashabbi Maksun Adinugroho, Sigit Agus Wahyu Widodo Ahmad Efriza Irsad Ahmad Fauzi Ahsani Akbar Imani Yudhaputra Akhmad Muzanni Safi'i Akhmad Rohim Akmilatul Maghfiroh Alip Setiawan Amalia Safitri Hidayati Amelia Kosasih Andina Dyanti Putri Anggita Mahardika Ani Enggarwati Arrizal Amin Barbara Sonya Hutagaol Bayu Rahayudi Berlian Bidari Ratna Sari B Binti Najibah Agus Ratri Budi Darma Setiawan Cahya Chaqiqi Candra Dewi Chindy Putri Beauty Dea Valentina Delischa Novia Sabilla Destin Eva Dila Purnama Sari Devinta Setyaningtyas Atmaja Dhimas Anjar Prabowo Dian Eka Ratnawati Dika Perdana Sinaga Dyva Agna Fauzan Edy Santoso Eka Dewi Lukmana Sari Eka Novita Shandra Fachrul Rozy Saputra Rangkuti Fadhil Yusuf Rahadika Fajar Pradana Fakhruddin Farid Irfani Faraz Dhia Alkadri Farid Rahmat Hartono Fatwa Reza Rizqika Febriana Ranta Lidya Fida Dwi Febriani Fira Sukmanisa Fitra Abdurrachman Bachtiar Fitria Indriani Frisma Yessy Nabella Gabriel Mulyawan Gagas Budi Waluyo Galuh Fadillah Grandis Gregorius Ivan Sebastian Hafid Satrio Priambodo Hamim Fathul Aziz Haris Bahtiar Asidik Ian Lord Perdana Ibnu Rasyid Wijayanto Imam Cholissodin Imam Cholissodin Inas Istiqlaliyyah Indriati Indriati Irma Pujadayanti Ivan Ivan Juniman Arief Karunia Ayuningsih Kenza Dwi Anggita Kresentia Verena Septiana Toy Kukuh Wiliam Mahardika Lita Handayani Tampubolon M. Ali Fauzi M. Ali Fauzi Mala Nurhidayati Marji Marji Moch Alyur Ridho Moch. Ali Fauzi Mohammad Rizky Hidayatullah Muh. Arif Rahman Muhammad Abdan Mulia Muhammad Bima Zehansyah Muhammad Faiz Al-Hadiid Muhammad Rizky Setiawan Muhammad Sanzabi Libianto Muhammad Tanzil Furqon Muhammad Zaini Rahman Nadhif Sanggara Fathullah Noerhayati Djumaah Manis Nova Amynarto Novan Dimas Pratama Novanto Yudistira Nugroho Dwi Saksono Nur Aisyah Asriani Ofi Eka Novyanti Panji Gemilang Panji Prasuci Saputra Pretty Natalia Hutapea Putra Pandu Adika Putra Pandu Adikara Putri Harnis Raditya Rinandyaswara Randy Cahya Wihandika Randy Ramadhan Rasif Nidaan Khofia Ahmadah Ratih Kartika Dewi Ratna Tri Utami Refi Fadholi Renaza Afidianti Nandini Rendi Cahya Wihandika Restu Amara Rezza Pratama Rhevitta Widyaning Palupi Rifki Akbar Siregar Rizky Ardiawan Rizky Maulana Iqbal Rosintan Fatwa Safira Dyah Karina San Sayidul Akdam Augusta Sarah Najla Adha Sarah Yuli Evangelista Simarmata Sigit Adi Nugroho Sigit Adinugroho Sinta Kusuma Wardani Sulaiman Triarjo Supraptoa Supraptoa Sutrisno Sutrisno Tibyani Tibyani Tri Rahayuni Tuahta Ramadhani Utaminingrum, Fitri Vriza Wahyu Saputra Wahyuni Lubis Willy Karunia Sandy Yosua Dwi Amerta