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All Journal Jurnal Telematika Journal of Students‘ Research in Computer Science (JSRCS) Journal of Computer Science Contributions (Jucosco)
Ekawati, Inna
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering

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Analisis Sentimen Masyarakat Terhadap Kebijakan Pemerintah Selama Pandemi Covid-19 Menggunakan Algoritma Naïve Bayes Emeraldi, Muhammad Aqil; Ekawati, Inna; Sumadyo, Malikus
Journal of Students‘ Research in Computer Science Vol. 3 No. 1 (2022): Mei 2022
Publisher : Program Studi Informatika Fakultas Ilmu Komputer Universitas Bhayangkara Jakarta Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31599/ycx3jc57

Abstract

The increase in data is very large, one of the sources comes from social media, especially Twitter which talks a lot about Covid-19 . The news through Twitter media regarding the impact of the Covid-19 virus is widely discussed because it causes unrest for the public which has led to the issuance of various government policies with the aim of preventing the spread of Covid-19 . Related to this, it is necessary to conduct a sentiment analysis of the text contained in the Twitter media. In this study, a sentiment analysis process was carried out related to public sentiment towards government policies during the Covid-19 pandemic in Indonesia on Twitter social media using the Naive Bayes Classifier method where the data used was classified into 2 sentiment values, namely positive and negative sentiment. The data used are 300 positive tweets data and 300 negative tweets data, where 80% of the total data is used as training data and 20% data is used as test data. Based on the test results, the data with a total of 120 tweets obtained the results of measuring the recall value of 93.33%, precision 93.33%, F-Score 93.33% and an average accuracy of 93.33%.
Deteksi Emosi Menggunakan Convolutional Neural Network Berdasarkan Ekspresi Wajah Ekawati, Inna; Putra, Fadilla Nidya Riyanto; Sumadyo , Malikus; Whidhiasih, Retno Nugroho
Journal of Students‘ Research in Computer Science Vol. 5 No. 1 (2024): Mei 2024
Publisher : Program Studi Informatika Fakultas Ilmu Komputer Universitas Bhayangkara Jakarta Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31599/h0kayy31

Abstract

Facial expression recognition is an effective method for identifying someone's emotional expression. Emotional expressions can be recognized from changes in facial expressions, wrinkles on the forehead, blinking of the eyes, or changes in facial skin color. Facial expressions that a person generally has, such as neutral, angry, happy expressions. The problem that often occurs is the subjective assessment of a person's expression. This research examines how artificial intelligence can recognize facial expressions. The facial recognition process in the research uses a Convolutional Neural Network (CNN), which is a deep learning method capable of carrying out an independent learning process for object recognition, object extraction and classification and can be applied to high resolution images that have a nonparametric distribution model. The two main stages in CNN are feature learning and classification. The results of facial expression recognition can be used to detect a person's emotions. This research uses the FER2013 dataset which contains images of happy, sad, angry, afraid, surprised, disgusted and neutral emotions. The data set in the research received tests that had been carried out, namely the percentage of accuracy level in the model was 76%. It is hoped that the classification of emotions resulting from this research can contribute to the development of artificial intelligence technology and as a tool in various fields such as psychology, education and others. For further research, it can be developed further by adding other architectures such as VGG19, MobileNet, and ResNet-50 so that the resulting CNN model is more optimal.
Pelacakan Geometri Segitiga dan Lingkaran di Kawasan Tepi untuk Segmentasi Objek Sucipto, Putra Wisnu Agung; Firasanti, Annisa; Bakri, Muhammad Amin; Ekawati, Inna; Yaqin, Khusnul
Jurnal Telematika Vol. 19 No. 2 (2024)
Publisher : Yayasan Petra Harapan Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61769/telematika.v19i2.717

Abstract

Segmentation of yellow fish egg spheres in digital images often fails due to the difficulty of determining the boundaries between adjacent or overlapping objects. This research proposes a geometry tracking-based segmentation method to solve the problem. This method uses triangulation of three important edge points around the object to determine the initial segment landmarks. Then, it uses their formation to form a complete circle of candidate segments. The set of pixels enveloped by this circle will be examined for shape and colour to be recognised as segments of an object or not. The method was tested on a fish egg image dataset containing more than 5,473 yellow-orange coloured fish egg spheres in 11 digital images. These egg sphere images vary in size, shape, brightness, contrast, density, shadow, noise, light reflection, and blur. Based on the experimental results, the method was able to correctly segment 4,370 egg spheres with 242 false segments and 1,103 undetected spheres. The performance metrics of this method are precision 94.7%, recall 79.8%, IoU 76.5%, and dice coefficient 86.7%.
Pelatihan Pemanfaatan Software Pendukung Dalam Pembuatan Artikel Ilmiah Terpublikasi Bagi Guru-Guru SMA Herlawati, Herlawati; Atika, Prima Dina; Hendharsetiawan, Andy Achmad; Handayanto, Rahmadya Trias; Sumadyo, Malikus; Whidhiasih, Retno Nugroho; Ekawati, Inna; Irwan, Dadan; Haryono, Haryono
Journal Of Computer Science Contributions (JUCOSCO) Vol. 3 No. 2 (2023): Juli 2023
Publisher : Lembaga Penelitian, Pengabdian kepada Masyarakat dan Publikasi Universitas Bhayangkara Jakarta Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31599/sgfq4k95

Abstract

Supportive software for scientific article creation is an application that assists in writing scientific articlesefficiently and effectively. This software features reference management, note-taking, text review, andformatting according to academic standards. The training to be provided will focus on creating scientificarticles using supportive software to enhance the competence of teachers in publishing their scientific articles.By understanding how to create scientific articles, high school teachers can improve their academic abilities,serve as positive examples for students, provide resources, and contribute to research and educationaldevelopment. This can help improve the quality of education and produce competent and skilled students. Theproposed solution is to organize training on the utilization of supportive software in scientific article creation.This training will provide understanding and skills in using software such as Mendeley and ChatGPT. Mendeleyis a reference management software that assists in collecting, managing, and storing references for scientificarticles. Additionally, Mendeley helps organize references according to various writing styles such as APA,MLA, Chicago, Vancouver, and IEEE. ChatGPT, on the other hand, is a natural language model that helpsgenerate structured and meaningful texts. In the context of scientific article creation, ChatGPT can assist informulating and organizing ideas or concepts, as well as providing suggestions or feedback for scientificwriting. Both of these software options can be chosen based on the needs and preferences of the writer. Theresults of this training, based on a survey using an online mentimeter, showed that it was very useful and theparticipants wanted to continue this training.
Co-Authors Agung Sucipto, Putra Wisnu Dadan Irwan Emeraldi, Muhammad Aqil Firasanti, Annisa Haryono Haryono Hendharsetiawan, Andy Achmad Herlawati Herlawati KHUSNUL YAQIN Malikus Sumadyo Muhammad Amin Bakri Prima Dina Atika Putra, Fadilla Nidya Riyanto Rahmadya Trias Handayanto Retno Nugroho Whidhiasih Sumadyo , Malikus