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This Author published in this journals
All Journal JREC (Journal of Electrical and Electronics) Journal of Students‘ Research in Computer Science (JSRCS)
Malikus Sumadyo
Universitas Islam 45 Bekasi
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering

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Evaluasi Penggunaan Website Kampus Menggunakan Metode Usability Testing dan System Usability Scale Inna Ekawati; Malikus Sumadyo; Retno Nugroho Whidhiasih
JREC (Journal of Electrical and Electronics) Vol. 11 No. 2 (2023): JREC (Journal of Electrical and Electronics)
Publisher : Program Studi Teknik Elektro Fakultas Teknik Universitas Islam 45 Bekasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33558/jrec.v11i2.7957

Abstract

The campus website is the face of an institution that can be accessed online by everyone because the website is a central information service. When individuals such as potential students, the wider public, and those within the institution itself require information about the campus, they will primarily turn to the website as their main source. However, not all campus websites have a perfect role as information and service centers. The quality of a campus website can be seen from the perception and feedback of its users. Therefore, an assessment of online media usage, especially websites, is essential at all times to understand user perceptions of the ongoing website development. This research is intended to evaluate the usability of the website of Islamic University 45 Bekasi to obtain the best recommendations for improvement. In addition to the evaluation, this research also compares two methods of website usability evaluation. The methods to be used are usability testing and the System Usability Scale. Both methods are conducted simultaneously to obtain qualitative and quantitative data. This research yields recommendations for areas that need improvement or enhancement and also provides a comparison of the two methods used as references for usability evaluation. The research results reveal that with the first method, there is a significantly higher number of positive perceptions than negative ones, although there are many suggestions for improvement. On the other hand, when using the second method, the campus website exhibits the second least favorable usability score among a total of eleven levels.
Deteksi Emosi Menggunakan Convolutional Neural Network Berdasarkan Ekspresi Wajah Inna Ekawati; Fadilla Nidya Riyanto Putra; Malikus Sumadyo; Retno Nugroho Whidhiasih
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.
Konversi ke Microservices Untuk Peningkatan Layanan Perpustakaan Malikus Sumadyo; Rahmadya Trias Handayanto; Ramdhani Setiawan
Journal of Students‘ Research in Computer Science Vol. 5 No. 2 (2024): November 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/vr275f23

Abstract

Most web-based applications are applications that provide services to users. The services themselves often change according to policies that are usually based on user satisfaction information. Unfortunately, existing applications are mostly based on open-source which is mostly monolithic. If there is an addition of a new service, it requires development from the beginning again. Especially when there is an imbalance between one service and another where one service requires large resources while other services do not require too many resources such as processors, network speed, or database size. This study tries to propose a system change in the library based on PHP-MySQL to be based on microservices.
Co-Authors Fadilla Nidya Riyanto Putra Inna Ekawati Inna Ekawati Rahmadya Trias Handayanto Ramdhani Setiawan Retno Nugroho Whidhiasih Retno Nugroho Whidhiasih