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Emerging Information Science and Technology
Published by Universitas Muhammadiyah Yogyakarta
ISSN : 27226042     EISSN : 27226050     DOI : https://doi.org/10.18196/eist
Core Subject : Science,
Computer Science & IT
Emerging Information Science and Technology is a double-blind peer-reviewed journal which publishes high quality and state-of-the-art research articles in the area of information science and technology. The articles in this journal cover from theoretical, technical, empirical, and practical research. It is also an interdisciplinary journal that interested in both works from the boundaries of subdisciplines in Information Science and Technology and from the boundaries between Information Science and Technology with other disciplines. EIST is an Open Access Journal to advance sharing science and technology. People have rights to read, download, copy, distribute, print and use with proper acknowledgment and citation. There is no publication fees for authors.
Arjuna Subject : Teknik (semua kategori) - Teknik (Lain-Lain)
Articles 77 Documents
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Mobile Surveillance System using Unmanned Aerial Vehicle for Aerial Imagery Haq, Muhamad Amirul
Emerging Information Science and Technology Vol. 5 No. 2 (2024): November
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/eist.v5i2.24837

Abstract

Crowd counting plays a vital role in public safety, particularly during riot scenarios where understanding crowd dynamics is crucial for effective decision-making and risk mitigation. Accurate crowd estimation in such environments enables authorities to monitor the situation in real time, allocate resources efficiently, and prevent potential escalations. However, counting individuals in a riot scenario presents unique challenges due to the chaotic nature of the scene, varying crowd densities, and obstructions caused by movement and environmental factors. Traditional methods struggle to provide reliable results in these conditions, necessitating advanced solutions. This study explores the implementation of CSRNet (Congested Scene Recognition Network), a state-of-the-art deep learning model, to address crowd counting in challenging environments characterized as "images in the wild." CSRNet’s ability to leverage dilated convolutions allows it to effectively capture contextual information and handle high crowd densities without sacrificing spatial resolution. We evaluate the model’s performance on diverse datasets, including aerial imagery and real-world riot scenarios, focusing on its adaptability to dynamic, unstructured environments. The results demonstrate the potential of CSRNet to provide accurate crowd density estimates under adverse conditions, offering critical insights for public safety applications. By addressing the technical challenges of implementing CSRNet in these contexts, this study contributes to the advancement of deep learning-based crowd counting, emphasizing its significance in real-world scenarios such as riots and other high-stakes events. Future work aims to further enhance the model's robustness and applicability to diverse operational settings.
Application for Recording Marriage Events at KUA: Design and Implementation Using Visual Studio 2012 and MySQL Siska, Sri Tria; Suhery, Lilik; Hariyadi, Hariyadi; Ananda, Suci Rizki
Emerging Information Science and Technology Vol. 5 No. 2 (2024): November
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/eist.v5i2.24846

Abstract

 In the management of data recording marriage events at the KUA (the Office of Religious Affairs) is still manual and has not utilized information technology to the fullest. The process of inputting, managing and storing data on recording marriage events only utilizes Microsoft Office applications and there is even some data that is written manually so that the process of presenting reports for recording marriage events is still relatively slow and inefficient, there are often errors and loss of data which results in the KUA having to search for data again. To overcome this problem, an application design is carried out that can speed up the process of recording marriage events at the KUA. Design and Implementation was using Visual Studio 2012 and MySQL as a database processing place. The application designed to support the process of recording marriage events more effectively and efficiently. 
Performance of Long Range-Frequency Hopping Spread Spectrum (LR-FHSS) For LoRaWAN Satellite Communication Adi, Puput; Stekelorom , Kevin
Emerging Information Science and Technology Vol. 6 No. 1 (2025)
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/eist.v6i1.26431

Abstract

Some factors that need to be developed in the LoRaWAN satellite communication system are using LR-FHSS (Long Range-Frequency Hoppong Spread Spectrum) to increase resistance to frequency interference and jamming, with the technique of using a small bandwidth per channel and operating on the same spectrum. With LR-FHSS devices on Earth can communicate with satellites that have relatively many movements. LR-FHSS uses 137 kHz bandwidth which is divided per channel around 488 Hz, with coding rates of 1/3 and 2/3 and separately modulated headers and payloads, and hop distance is a range of 3-50 kHz. LR-FHSS implementation is for monitoring hard-to-reach areas such as oceans, mountains, deserts, and others, as well as logistics tracking and asset management. LR-FHSS LoRaWAN uses RP2-1.0.1 which is the LoRa Alliance standardization for satellite communication. This research shows the Frequency Hopping Pattern for each device, the graph shows that there are 3 devices, devices 1, 2, and 3, which are spread over the free frequency channel between 0.0 and 17.5 with time slots 0 to 90. CR 1 with Frequency Hopping produces the fastest Time-on-air (ms) of 2 ms, and CR 2/3 with Frequency Hopping 3 ms, this is the best setting to produce the fastest ToA.
Implementation of Finite State Automata to Optimize the Waste Collection Process in the Greenify Application Setyawan, Ryan Ari; Christianto, Devri Budi; Bening, Ridho Gilang
Emerging Information Science and Technology Vol. 6 No. 1 (2025)
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/eist.v6i1.27032

Abstract

Efficient waste management is a major challenge in urban life. One promising solution is the use of Finite State Automata (FSA) to optimize the waste containment process within the Greenify application. This study aims to explore the application of FSA in designing the logical flow for waste management, which includes identifying waste types, collection locations, and pick-up schedules. The methodology employed is a theoretical approach that implements the FSA model to regulate statuses and transitions between different steps in the waste management process. The results demonstrate that FSA can improve operational efficiency, reduce management errors, and enhance the user experience. The application of FSA in Greenify facilitates a more structured and automated waste management system, while also improving the accuracy of scheduling and waste collection. This conclusion highlights the significant potential of FSA as a technological solution for environmentally friendly waste management, with the goal of optimizing the performance of the Greenify application and advancing urban waste management practices.
Implementation Of Transfer Learning In Cat Breed Detection Using Web-Based Convolutional Neural Network (CNN) Fitrianto, Furqon; Rouza, Erni; Basorudin
Emerging Information Science and Technology Vol. 6 No. 1 (2025)
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/eist.v6i1.27104

Abstract

Cats are one of the most popular pets because of their friendly and adorable nature. Along with the increasing cat population in Indonesia and the variety of breeds, cat breed identification is a challenge in itself, especially for cat lovers to the animal conservation community. This research aims to develop an image-based cat breed classification system using transfer learning method with MobileNetV2 Convolutional Neural Network (CNN) model. This model was chosen because of its ability to produce high accuracy with good computational efficiency, making it suitable for use on devices with limited resources. The dataset used consists of 13,000 training images and 3,250 testing images of 13 cat breeds. The model training process was carried out up to 50 epochs with the addition of fine-tuning for 10 epochs, after previously terminating the process at the 60th epoch, resulting in a validation accuracy of 98.67%. Model performance testing also showed high average results of evaluation metrics, namely precision of 91.38%, recall of 91.39%, and F1-score of 91.33%. Based on these results, it can be concluded that the application of MobileNetV2 transfer learning is able to classify cat breeds accurately and efficiently. The website made makes it easy for users to recognize cat breeds by simply uploading images, making it very useful for the general public, professionals, and cat enthusiasts.
Web-Based E-Office System Design Using Yii2 Framework Siswanto, Hery; Shofiyatun, Siti
Emerging Information Science and Technology Vol. 6 No. 1 (2025)
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/eist.v6i1.27155

Abstract

Universitas Muhammadiyah PKU Surakarta in its efforts to improve the efficiency and effectiveness of office administration management faces challenges in document management and workflows that are still running conventionally. Manual processes often take longer, are prone to errors, and require large physical storage space. To overcome these problems, this study aims to design and build a web-based E-Office system by utilizing the Yii2 framework. The method used in this study is SDLC and the system design used includes the needs analysis stage, system design using the Unified Modeling Language (UML) consisting of use case diagrams, activity diagrams, and class diagrams, and system implementation using the Yii2 framework with the PHP programming language and MySQL database. Implementation using Devops. The Yii2 framework was chosen because of its robust structure, complete security features, SSO login with Google, and its ability to accelerate the application development process. The E-Office system developed will include various essential features such as incoming and outgoing mail management, electronic mail disposition, SPPS management, and document status tracking features. It is expected that with the implementation of this system, Muhammadiyah University of PKU Surakarta can realize a more modern, paperless, transparent, accountable office administration system, and is able to increase productivity and quality of service for all academicians. This system is also expected to facilitate the decision-making process of leaders through fast and accurate access to information.
Innovative Learning Strategy Using H5P to Create Engaging Learning Modules for Students Kurnianti, Apriliya; Isnanda, Reza Giga; Farkhani, Jodi Nur; Qodri, Krisna Nuresa
Emerging Information Science and Technology Vol. 6 No. 1 (2025)
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/eist.v6i1.27169

Abstract

Technology in education plays a crucial role in delivering effective learning, especially for students in Indonesian schools abroad. This study aims to develop and evaluate an interactive learning website based on WordPress and H5P, with a focus on Indonesian culture, particularly traditional dance. The website was developed locally using XAMPP and integrated with interactive videos, quizzes, and simulations. Evaluation results indicate that most students felt a greater connection to Indonesian culture, and the learning process became more engaging. This strategy has proven to enhance student engagement and strengthen national identity in multicultural environments
Performance Benchmark in Febrile Mass Screening Detection Sofiah, Siti; Hawari, Kamarul; Khatun, Sabira
Emerging Information Science and Technology Vol. 1 No. 1: February 2020
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/eist.114

Abstract

Recently, detecting and tracking people using infrared sensors in public surveillance has been given attention by many researchers since the global outbreak of severe acute respiratory syndrome, and machine vision is bound to play an important role. In machine vision, sliding window approach has appeared as most promising approach. Since Papageorgious et al who proposed the first sliding window detetectors until Dalal et al who have come out with a large gains detector based on histogram adoption, the ideas of sliding in human detections continue to serve as a root for modern detectors. While there is increasing research in thermal spectrum, very little research focus on the effectiveness of state of art detectors in febrile mass screening application. The exposed area of head-to-shoulder is an important body part for region of interest detection priorly before the temperature of febrile person is measured by the thermal camera. In addition, some of the thermal datasets used in previous research are more fit to surveillance or safety applications where the targets are mostly far-scales. One of the challenges in detecting the pedestrian in thermal images is the nature and quality of image in infrared spectrum as well as the real crowd situation in public area that cause occlusion. Therefore in this paper, we are interested to evaluate the top three detectors’ performance on thermal images taken during fever screening in Kuala Lumpur International Airport. We also analyze the best approach to be adopted in the detection using a new context of training and evaluation.
The Development of 3D Survival Simulation Game for Identifying Safe Food and Water in Borneo Forest Kurniawan, Yuda Fatah; Isnanda, Reza Giga; Asroni, Asroni
Emerging Information Science and Technology Vol. 1 No. 1: February 2020
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/eist.111

Abstract

For adventures who like to explore the forest with diverse type of flora, such as Borneo forest, being lost and have limited supply of food and water become one of the biggest threats for survival. Therefore, it is important to know how to identify food and water that is safe for consumption. Unfortunately, the learning media for survival skills are still heavy on verbal approach, so there is a need for a more practical and visual learning media. To overcome the problem, this research was aimed to develop a survival simulation game that teach the player how to identify safe food and water in Borneo forest. The game was developed in six steps based on Luther’s steps of authoring multimedia. At the end of the development process, the feasibility of the game as learning media is tested using pre-test and post-test method. Statistical analysis using paired t-test showed that the post-test result (M=77.33, SD=5.37) was significantly higher than the pre-test result (M=56.67, SD=8.24) ); t(29)=18.49, p < 0.001. This indicates that the game is feasible in teaching the knowledge to the player. In the future, this game can be an alternative and practical solution for teaching survival skill.
Classification of Mangosteen Surface Quality Using Principal Component Analysis Riyadi, Slamet; Ayu Ratiwi, Amelia Mutiara; Damarjati, Cahya; Hariadi, Tony K.; Prabasari, Indira; Utama, Nafi Ananda
Emerging Information Science and Technology Vol. 1 No. 1: February 2020
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/eist.115

Abstract

Mangosteen (Garcinia mangostana L) is one of the primary contributor for Indonesia export. For export commodity, the fruit should comply the quality requirement including its surface. Presently, the surface is evaluated by human visual to classify between defect and non- defect surface. This conventional method is less accurate and takes time, especially in high volume harvest. In order to overcome this problem, this research proposed images processing based classification method using principal component analysis (PCA). The method involved pre-processing task, PCA decomposition, and statistical features extraction and classification task using linear discriminant analysis. The method has been tested on 120 images by applying 4-fold cross validation method and achieve classification accuracy of 96.67%, 90.00%, 90.00% and 100.00% for fold-1, fold-2, fold-3 and fold-4, respectively. In conclusion, the proposed method succeeded to classify between defect and non-defect mangosteen surface with 94.16% accuracy.

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