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Journal : Matrik : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer

User Interface and Exprience Gamification-Based E-Learning with Design Science Research Methodology Viva Arifin; Velia Handayani; Luh Kesuma Wardhani; Hendra Bayu Suseno; Siti Ummi Masruroh
MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Vol 22 No 1 (2022)
Publisher : LPPM Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/matrik.v22i1.2427

Abstract

In 2020, the Islamic Elementary Teacher Working Group (KKG MI) held an E-Learning Training for Islamic Elementary School Teachers in DKI Jakarta about one of the gamification applications, Quizizz. According to observation, many teachers are still perplexed when utilizing the Quizizz program. This is due to the application’s design and different functionalities, which still appear complicated to some teachers who aren’t used to using it. The existing gamification application is also considered not to meet the learning needs at Islamic elementary schools in Jakarta. This study intends to analyze and design User Interface (UI) and User Experience (UX) designs for gamification-based e-learning applications as solutions to the problems found. Data collection begins with an observation and also a literature study, questionnaires, and interviews. For the design, Design Science Research Methodology (DSRM) is used, which consists of six stages: Problem Identification & Motivation, Define the Objective for a Solution, Design & Development, Demonstration, Evaluation and Communication. The results of the evaluation of the gamification-based e-learning design designed with the User Experience Questionnaire (UEQ) and Task Success show that the e-learning design is considered attractive and users can interact with e-learning effectively and easily.
Convolutional Neural Network for Colorization of Black and White Photos Siti Ummi Masruroh; Andrew Fiade; Muhammad Ikhsan Tanggok; Rizka Amalia Putri; Luigi Ajeng Pratiwi
MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Vol 22 No 2 (2023)
Publisher : LPPM Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/matrik.v22i2.2652

Abstract

People today are very fond of capturing moments by taking pictures. Various photo functions are used to document all forms of information that you want to store. In photos with digital images that have black and white, the information obtained is less than optimal, so an image processing process is needed to get color photos. Based on this, the author wants to change photos from black and white to color photos. The method used in this research is Convolutional Neural Network (CNN). This study uses Atlas 200 DK hardware and Ascend 310 processor. The data used in this study are 32 black and white photos in .jpg format as training data and perform 6 experimental scenarios with different numbers of black and white photos in each experiment. The total black and white photos used to experiment were 81 photos. The results obtained are models that successfully perform processing in the form of color photos with the appropriate color results in predicting the possible color of the object in each pixel in the photo. Based on this research, the trend of artificial intelligence can be implemented in changing the color of photos according to color predictions.
Accuracy of K-Nearest Neighbors Algorithm Classification For Archiving Research Publications Muhamad Nur Gunawan; Titi Farhanah; Siti Ummi Masruroh; Ahmad Mukhlis Jundulloh; Nafdik Zaydan Raushanfikar; Rona Nisa Sofia Amriza
MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Vol 23 No 3 (2024)
Publisher : LPPM Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/matrik.v23i3.3915

Abstract

The Archives and Research Publication Information System plays an important role in managing academic research and scientific publications efficiently. With the increasing volume of research and publications carried out each year by university researchers, the Research Archives and Publications Information System is essential for organizing and processing these materials. However, managing large amounts of data poses challenges, including the need to accurately classify a researcher's field of study. To overcome these challenges, this research focuses on implementing the K-Nearest Neighbors classification algorithm in the Archives and Research Publications Information System application. This research aims to improve the accuracy of classification systems and facilitate better decision-making in the management of academic research. This research method is systematic involving data acquisition, pre-processing, algorithm implementation, and evaluation. The results of this research show that integrating Chi-Square feature selection significantly improves K-Nearest Neighbors performance, achieving 86% precision, 84.3% recall, 89.2% F1 Score, and 93.3% accuracy. This research contributes to increasing the efficiency of the Archives and Research Publication Information System in managing research and academic publications.