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IJID (International Journal on Informatics for Development)
Published by Universitas Islam Negeri Sunan Kalijaga Yogyakarta
ISSN : 22527834     EISSN : 25497448     DOI : -
Core Subject : Science,
Computer Science & IT
One important point in the accreditation of higher education study programs is the availability of a journal that holds the results of research of many investigators. Since the year 2012, Informatics Department has English language. Journal called IJID International Journal on Informatics for Development. IJID Issues accommodate a variety of issues, the latest from the world of science and technology. One of the requirements of a quality journal if the journal is said to focus on one area of science and sustainability of IJID. We accept the scientific literature from the readers. And hopefully these journals can be useful for the development of IT in the world. Informatics Department Faculty of Science and Technology State Islamic University Sunan Kalijaga.
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Articles 4 Documents
 1 
Search results for , issue "Vol. 12 No. 2 (2023): IJID December" : 4 Documents clear
Optimisation of Residual Network Using Data Augmentation and Ensemble Deep Learning for Butterfly Image Classification Diniati Ruaika; Shofwatul Uyun
IJID (International Journal on Informatics for Development) Vol. 12 No. 2 (2023): IJID December
Publisher : Faculty of Science and Technology, UIN Sunan Kalijaga Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14421/ijid.2023.4038

Abstract

Image classification is a fundamental task in vision recognition that aims to understand and categorize an image under a specific label. Image classification needs to produce a quick, economical, and reliable result. Convolutional Neural Networks (CNN) have proven effective for image analysis. However, problems arise due to factors such as the model’s quality, unbalanced training data, overfitting, and layers’ complexity. ResNet50 is a transfer learning-based convolutional neural network model frequently used in many areas, including Lepidopterology. Studies have shown that ResNet50 performs with lower accuracy than other models for classifying butterflies. Therefore, this study aims to optimise the accuracy of ResNet50 using an augmentation approach and ensemble deep learning for butterfly image classification. This study used a public dataset of butterflies from Kaggle. The dataset contains 75 different butterfly species, 9.285 training images, 375 testing images, and 375 validation images. A sequence of transformation functions was applied. The ensemble deep learning was constructed by incorporating ResNet50 with CNN. To measure ResNet50 optimisation, the experimental results of the original dataset and the proposed methods were compared and analysed using evaluation metrics. The research revealed that the proposed method provided better performance with an accuracy of 95%.
Design and Development of an Edugame Arabic for Learning Media Yudha Riwanto; Inggrid Yanuar Risca Pratiwi; Asri Wulan Septiana; Fauzia Anis Sekar Ningrum; Ajie Kusuma Wardhana
IJID (International Journal on Informatics for Development) Vol. 12 No. 2 (2023): IJID December
Publisher : Faculty of Science and Technology, UIN Sunan Kalijaga Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14421/ijid.2023.4297

Abstract

Learning media provides significant advantages to students by improving their learning experience through the use of multimedia applications, resulting in a more engaging and fascinating learning environment while reducing the monotony associated with traditional manual learning techniques. Digital learning material, provides a platform for interesting learning activities, encouraging a delightful and cost-effective learning experience. The impact of learning media is especially noticeable in the subject of the Arabic language. Arabic is traditionally regarded as a difficult language, and many students dislike this language course. However, the Edugame Arabic was created to overcome this issue. Using the GDLC process, which includes phases of initialization, pre-production, production, testing, and publishing. This game-learning application was evaluated through a testing phase that included groups of school students who were actively involved in Arabic language lessons. Edugame Arabic has successfully been installed and runs smoothly on various Android smartphones. Moreover, the game's offline capability allows users to continue their learning without an internet connection. The questionnaire responds, with users strongly agreeing that the app has an appealing design, an intriguing game premise, good material delivery, and considerable aid in learning Arabic. Furthermore, users generally acknowledged that the Edugame is simple to use and helps with vocabulary learning.
Anomaly-Based Intrusion Detection System for the Internet of Medical Things Franklin, Eichie; Pranggono, Bernardi
IJID (International Journal on Informatics for Development) Vol. 12 No. 2 (2023): IJID December
Publisher : Faculty of Science and Technology, UIN Sunan Kalijaga Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14421/ijid.2023.4308

Abstract

The use of the Internet of Things (IoT) in the health sector, known as the Internet of Medical Things (IoMT), allows for personalized and convenient (e)-health services for patients. However, there are concerns about security and privacy as unethical hackers can compromise these network systems with malware. We proposed using hyperparameter-optimized Machine and Deep Learning models to address these concerns to build more robust security solutions. We used a representative Anomaly Intrusion Detection System (AIDS) dataset to train six state-of-the-art Machine Learning (ML) and Deep Learning (DL) architectures, with the Synthetic Minority Oversampling Technique (SMOTE) algorithm used to handle class imbalance in the training dataset. Our hyperparameter optimization using the Random search algorithm accurately classified normal cases for all six models, with Random Forest (RF) and K-Nearest Neighbors (KNN) performing the best in accuracy. The attention-based Convolutional Neural Network and Long Short-Term Memory (CNN-LSTM) model was the second-best performer, while the hybrid CNN-LSTM model performed the worst. However, there was no single best model in classifying all attack labels, as each model performed differently in terms of different metrics.
IT Infrastructure Assessment using the COBIT 2019 Framework Rifa'i, Aulia Faqih; Sumarsono; Muhammad Fauzan Al Baihaqi; Yazid Azfa Yasa
IJID (International Journal on Informatics for Development) Vol. 12 No. 2 (2023): IJID December
Publisher : Faculty of Science and Technology, UIN Sunan Kalijaga Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14421/ijid.2023.5152

Abstract

The Admission Office is responsible for student enrollment, and since 2013, the admission process at UIN Sunan Kalijaga has been supported by information technology. To assess the current state of the IT infrastructure in this university, the COBIT 2019 Framework was used. This study identifies five key domains in need of improvement: APO12 (manage risk), which focuses on managing IT-related risks within an organization, BAI10 (manage configuration), to ensure that IT services are delivered efficiently and effectively, DSS02 (manage service requests & incidents), involves the process of providing quick and efficient responses to user requests and handling various incidents, DSS03 (manage problems), to provide timely and effective support to consumers, ensuring their issues are addressed, their needs are met, and DSS04 (manage continuity), to ensure that the organization can respond effectively to incidents and disruptions, minimizing downtime and maintaining business continuity. The results showed that the capability levels for these domains in UIN Sunan Kalijaga were at Level 1, while the target was Level 4, leading to a capability gap of 3. The gap indicates that considerable effort is required to improve and achieve the desired level of maturity, and this research proposes some recommendations to improve the IT infrastructure.

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