Article Per Year (5 Year)
p-Index From 2021 - 2026
3.611
P-Index
This Author published in this journals
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

Published : 105 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 105 Documents
Search

 7   8   9   10   11 
Pemerolehan Informasi pada Alkitab Berbahasa Indonesia Menggunakan Metode BM25 dan Query Expansion Word2Vec Pretty Natalia Hutapea; Putra Pandu Adikara; Yuita Arum Sari
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 5 No 5 (2021): Mei 2021
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

The Indonesian state officially recognizes six religions, namely Islam, Protestantism, Catholicism, Hinduism, Buddhism, and Confucianism. In Protestantism, the Bible is used as its holy book. In carrying out their worship, Protestants must have a close relationship with God through reading and studying the Bible. A Bible book contains a lot of information, so a system is needed to access and manage that information quickly and accurately. The information retrieval system can be used to get results relevant to user needs through query input. Queries entered by the user sometimes do not return relevant results due to errors in the query, so a query expansion technique that is capable of expanding or modifying the query is required. The modeling used for query expansion is Word2Vec, while to obtain relevant document results, the document is ranked using the Best Match 25 (BM25) method. Tests conducted in this study compared the document output when using query expansion and without using query expansion. The test results of this study get the highest results when not using the query expansion with the Precision @ 10 and MAP values ​​of 0.86 and 0.93.
Analisis Sentimen Kebijakan New Normal Dengan Menggunakan Automated Lexicon Senti-N-Gram Rifki Akbar Siregar; Yuita Arum Sari; Indriati Indriati
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 5 No 13 (2021): Publikasi Khusus Tahun 2021
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Untuk dipublikasikan ke JTIIK
Penerapan Model Residual ConvNet dengan Augmentasi Citra untuk Klasifikasi Ekspresi Wajah Manusia Fadhil Yusuf Rahadika; Novanto Yudistira; Yuita Arum Sari
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 5 No 13 (2021): Publikasi Khusus Tahun 2021
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

During the COVID-19 pandemic, many offline activities are turned into online activities via video meetings to prevent the spread of the COVID-19 virus. In the online video meeting, some micro-interactions are missing when compared to direct social interactions. The use of machines to assist facial expression recognition in online video meetings is expected to increase understanding of the interactions among users. Many studies have shown that CNN-based neural networks are quite effective and accurate in image classification. In this study, some open facial expression datasets were used to train CNN-based neural networks with a total number of training data of 342,497 images. This study gets the best results using ResNet-50 architecture with Mish activation function and Accuracy Booster Plus block. This architecture is trained using the Ranger and Gradient Centralization optimization method for 60000 steps with a batch size of 256. The best results from the training result in accuracy of AffectNet validation data of 0.5972, FERPlus validation data of 0.8636, FERPlus test data of 0.8488, and RAF-DB test data of 0.8879. From this study, the proposed method outperformed plain ResNet in all test scenarios without transfer learning, and there is a potential for better performance with the pre-training model.
Ekstraksi Fitur Color Moments Ciel*A*B*, Hsv, Dan Local Binary Pattern Untuk Klasifikasi Citra Kue Tradisional Delischa Novia Sabilla; Yuita Arum Sari; Agus Wahyu Widodo
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 5 No 13 (2021): Publikasi Khusus Tahun 2021
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Untuk dipublikasikan di SIET
Pembentukan Daftar Stopword Goffman Transition Point dengan Pembobotan Emoji pada Analisis Sentimen di Twitter Rizky Maulana Iqbal; Yuita Arum Sari; Edy Santoso
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 5 No 13 (2021): Publikasi Khusus Tahun 2021
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Untuk dipublikasikan di Jurnal Teknologi Informasi dan Ilmu Komputer (JTIIK)
Pengembangan Sistem Konsultasi Gizi dan Konsumsi Harian berbasis Web Moch Alyur Ridho; Fajar Pradana; Yuita Arum Sari
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 5 No 8 (2021): Agustus 2021
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

The adequacy of nutritional needs in the human body is very important in supporting its survival. Lack of nutritional needs can lead to reduced immunity to disease infections. The nutritional needs needed to meet each individual's daily calories vary greatly, it is usually supported by differences in gender and age, weight and height, the latter is a daily body activity. The difficulty of the community in determining the number of daily calories needed, the many factors that influence in the fulfillment of nutritional needs can be easily solved by the development of the system to be carried out. In addition, the user will be facilitated by the presence of several reminder features that will record the calories of food entered in his body by identifying images of food consumed by the user, and users can also consult with nutritionists available on the system to conduct further discussions. The development method conducted in this study uses waterfall method by applying Object Oriented Programming (OOP) based programming and using HTML and PHP programming languages, while to implement data structures using relational database mechanisms namely is MySQL. In this study, 3 samples were used to test the unit and produce a system that was made to run well, in addition to validation testing using 14 test cases and showing 14 functions run well.
Seleksi Fitur Alternative Accuracy2 pada Analisis Sentimen Mengenai Kebijakan Pembatasan Sosial Berskala Besar dengan K-Nearest Neighbor Restu Amara; Yuita Arum Sari; Putra Pandu Adikara
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 5 No 8 (2021): Agustus 2021
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Pembatasan Sosial Berskala Besar or PSBB is one of Indonesian Goverment new policies to surpress the spread of COVID-19 pandemic. This policy generates lots of public opinion about pros and cons, and it became the most discussed topic in social media such as Twitter. From this public opinion, we can get the information about the act of PSBB wich can be classify as it either positive opinion or negative opinion. Sentiment analysis is used to extract information from data text, to get to know whats the point behind every opinion. Excessive data size has become the main problem about text classification, there's a step called feature selection, this step is used to eliminate the unnecessery words in data. In this research, we aim to know the effect of Alternative Accuracy2 feature selection that used with classification method like K-Nearest Neighbor (KNN) on classification result. We used data text with total about 300 public opinion and used K-Fold K-Fold Cross Validation as validation process. The average evaluation results of 5-fold for the use of the Allternative Accuracy2 feature selection, which is equal to 0,7367 for the accuracy value with 0,7667 for precision, 0,7277 for recall, and the f-measure is 0,7453 with a k value in KNN k = 47, while K-Nearest Neighbor without using feature selection resulted in 0,7167 for accuracy, 0,7467 for precision, 0,7049 for recall, and 0,7249 for f-measure. Based on these results, it can be concluded that the use of Alternative Accuracy2 feature selection can increase the evaluation value because the resulting features can clarify the characteristics of each document.
Seleksi Fitur Gain Ratio pada Analisis Sentimen Kebijakan Pemerintah Mengenai Pembelajaran Jarak Jauh dengan K-Nearest Neighbor Galuh Fadillah Grandis; Yuita Arum Sari; Indriati Indriati
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 5 No 8 (2021): Agustus 2021
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

The Ministry of Education and Culture (Kemendikbud) released Circular Number 15 of 2020 concerning Guidelines for Implementing Learning from Home in an Emergency for the Spread of COVID-19, which is known as Distance Learning (PJJ). This Circular was issued during the Covid-19 emergency to protect students' rights to receive educational services while simultaneously preventing the spread of Covid-19. Following the publication of this policy, numerous types of responses or opinions from the general public began to be expressed on social media, especially Twitter. This can take the shape of a good or negative opinion, thus a sentiment analysis is required to determine whether this policy has gotten a lot of favorable or negative feedback. Sentiment analysis is a method for determining the sentiments that present in each viewpoint. The K-Nearest Neighbor (KNN) classification approach is used for sentiment analysis, and it seeks to find the outcomes or values of the closest documents. In addition, the increase ratio will be used to remove irrelevant terms via feature selection. As a result, the gain ratio with the highest f-measure value, namely 0.74 at k = 11 with testing on the second fold and k = 90 with testing on the first fold, is used. In comparison to using the information gain, the outcome of employing the gain ratio for each fold has a steady f-measure value.
Pembentukan Daftar Stopword menggunakan Term Based Random Sampling pada Analisis Sentimen dengan metode Naive Bayes (Studi Kasus: Kuliah Daring di Masa Pandemi) Raditya Rinandyaswara; Yuita Arum Sari; Muhammad Tanzil Furqon
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 5 No 13 (2021): Publikasi Khusus Tahun 2021
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Untuk dipublikasikan di Jurnal Teknologi Informasi dan Ilmu Komputer (JTIIK)
Estimasi Sisa Makanan Otomatis pada Kotak Makan menggunakan Segmentasi Citra berbasis Clustering dengan Algoritme K-Means Haris Bahtiar Asidik; Yuita Arum Sari; Agus Wahyu Widodo
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 5 No 9 (2021): September 2021
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Food is a source of energy for living things, consuming food in standardized portions can help meet nutritional needs, but on the other hand, it will have a negative impact on the body. Foodservice in the hospital is a support system in accelerating the patient's healing process, the patient's leftover food reflects the patient's low acceptance of food which can increase the risk of malnutrition. Currently, the global volume of food waste is estimated at 1.6 billion tonnes with food waste carbon estimated at 3.3 billion tonnes of CO2 equivalent to greenhouse gases per year. It takes a tool to find out how much food a person has consumed. With the development of technology, the process of calculating the weight of food waste can be done through the image of the food before it is eaten and the image of the food after it is eaten. The food image in the lunch box is segmented to obtain food segments in the image through the clustering method using the K-means algorithm based on the blue color level in the image. The results of the Intersection over Union (IoU) segmentation accuracy on images with a white background reached 98.9%. Based on the segmentation results obtained, the weight of leftover food was predicted using the Elementary Leftover Food Estimation (EFLE) method. By using the Root Mean Square Error (RMSE), the experimental results reach the smallest error of 1.12. This indicates that the proposed method is capable to project the weight of the food residue.
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