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Ahmad Azhari
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Mobile and Forensics
Published by Universitas Ahmad Dahlan
ISSN : 26566257     EISSN : 27146685     DOI : https://doi.org/10.12928/mf
Core Subject : Science, Engineering,
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Library & Information Science Neuroscience
Mobile and Forensics (MF) adalah Jurnal Nasional berbasis online dan open access untuk penelitian terapan pada bidang Mobile Technology dan Digital Forensics. Jurnal ini mengundang seluruh ilmuan dan peneliti dari seluruh dunia untuk bertukar dan menyebarluaskan topik-topik teoritis dan praktik yang berorientasi pada kemajuan teknologi mobile dan digital forensics.
Arjuna Subject : Teknik (semua kategori) - Teknologi Media
Articles 8 Documents
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Search results for , issue "Vol. 6 No. 2 (2024)" : 8 Documents clear
Image Forensics Using Error Level Analysis and Block Matching Methods Sudianto, Iis; Anwar, Nuril
Mobile and Forensics Vol. 6 No. 2 (2024)
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/mf.v6i2.5719

Abstract

The development of image editing tools today makes everyone able to manipulate images easily so that many images are doubtful of their authenticity. The current image can be used as evidence in a legal case in court. The authenticity of the image is a topic that many have tried to solve various studies. This study discusses the authenticity of the image using the Error Level Analysis (ELA) method to determine the authenticity of the image, especially in the JPEG image. Block Matching is used in the process of dividing an image into several square or block parts. The ELA method has been successfully implemented with 95% image compression resulting in MSE and PSNR values ​​in distinguishing the edited image. The average MSE is 23.8 dB and the average PSNR is 34.47 dB. Block Matching results as a whole show that the pixel value for x values ​​that reach 30 there are 9 images, x values ​​that reach 24 there are 9 images, x values ​​that reach 23 there are 1 image, and for x values ​​that reach 19 there is 1 image. The result of pixel (y) of all images exceeds the value of 12 which in pixel (y) undergoes many changes marked by the presence of white spots.
Identification of Plasmodium Vivax in Blood Smear Images Using Otsu Thresholding Algorithm Huda, Nurul; Aulia, Latifathul; Pandini, Maulany Citra
Mobile and Forensics Vol. 6 No. 2 (2024)
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/mf.v6i1.11261

Abstract

In this research, we explore the efficacy of Convolutional Neural Networks (CNN) and Support Vector Machines (SVM) in identifying Plasmodium vivax from blood smear images. We utilized a dataset comprising images of Plasmodium vivax and non-infected cells, applying CNN for deep feature extraction and SVM with otsu’s thresholding for segmentation. The dataset was preprocessed and augmented to enhance model performance. The CNN architecture, consisting of multiple convolutional and dense layers, achieved an accuracy of 98.46% on the validation set. For comparison, features extracted using Otsu’s Thresholding were fed into an SVM classifier, yielding an accuracy of 82%. Confusion matrix was generated to evaluate the classification performance of both models. The CNN model demonstrated superior accuracy and robustness in classification tasks compared to the SVM model. This research shows how deep learning frameworks can be used to analyse medical images and how important it is to have methods for extracting and choosing features to make machine learning models work better.
Rediscover Story Of Muhammadiyah Through 3D Game By Applying Game Development Life Cycle Hafizh, Achmad Nur; Azhari, Ahmad
Mobile and Forensics Vol. 6 No. 2 (2024)
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/mf.v6i2.11388

Abstract

Though specifically in Indonesia, Muhammadiyah is already well known but there are still some who do not know their history. This makes people that do not know about Muhammadiyah and the history behind it to make unfounded assumptions about the Islamic refined organization. The purpose is to make an educational game based on Muhammadiyah Museum to further increase the wisdom of players about Muhammadiyah’s history and also to remember and know the history behind each artifact is visualized in form of a game to increase the player’s knowledge. The game development for players will be developed using the Game Development Life Cycle (GDLC) methodology and mostly the modelling technique that will be used is mesh modelling technique in Blender. Each step of this methodology is fitting for the game development and the step might be skipped or swapped according to the needs of research. There are 2 black box tests conducted, the first black box test that has 15 functions result is 47% in accordance with several bugs found which was fixed in the second black box test that resulted 87% in accordance, 13% not in accordance because of the feature was not yet implemented but listed in the main menu. The second test conducted which results and practicality of this educational game using the System Usability Scale (SUS) which consists of 10 instrument statements were scored 85.3 which means that this educational game was declared excellent and acceptable.
Design Job Vacancy Website Using The Laravel Framework Fauzi, Moch Farid; Yudian Pradipta, Govin; Setiyawan, Deny; Ichsan, Muhammad Nur; Reyhandhipa, Dzaki Ahsana
Mobile and Forensics Vol. 6 No. 2 (2024)
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/mf.v6i2.5644

Abstract

Job vacancies are the most sought after during the current COVID-19 pandemic—the number of layoffs by companies experiencing problems in their business. Many people become unemployed, and income levels decrease while their needs must still be met. This has an impact on the number of people looking for job vacancies. Often found job seekers and job seekers seeking information still through mass media, banners, posters, billboards, and word of mouth. This search and recruitment model will not be efficient and will not be right on target. The solution offered to overcome these problems is to create a website for job vacancies, recruitment, and job applications. The research method used is Rapid Application Development (RAD) to find out the website creation process carried out in a short and influential period. The research flow is looking for references, determining project needs by making UI design and database design, making prototypes, testing, refining, developing features, feedback questionnaires, and project implementation. This research resulted in a job vacancy website called "AntiNggur". This website is expected to facilitate the dissemination of information on job vacancies, the job search process, and the process of recruiting new workers that are more effective and more targeted.
National Institute of Standard Technology Approach for Steganography Detection on WhatsApp Audio Files Muhammad, Abdul Haris; Mandar, Gamaria
Mobile and Forensics Vol. 6 No. 2 (2024)
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/mf.v6i2.11287

Abstract

Audio steganography in instant messaging applications such as WhatsApp poses new challenges in the field of digital security, especially due to the ability to hide data in frequently used formats. This research examines the effectiveness of steganography detection on WhatsApp audio files by applying a method developed by the National Institute of Standards and Technology (NIST). This approach was chosen due to its reputation in security testing standards, but its use in the context of audio steganography on instant messaging platforms has not been widely explored. The novelty of this research lies in the adaptation of the NIST method specifically for audio steganography analysis in WhatsApp, which includes testing against various compression and end-to-end encryption scenarios. The main findings of this research show that the NIST method successfully improves the accuracy of hidden message detection compared to conventional steganalysis techniques, especially under the condition of compressed audio files. In addition, this research also found that the integration of the NIST method enables more effective detection of steganographic data in encrypted audio files. These results confirm that the NIST method can be successfully adapted for instant messaging applications such as WhatsApp, making a significant contribution in the improvement of digital security. This research not only identifies weaknesses in existing steganography techniques, but also introduces a new framework for more accurate and efficient detection in encrypted environments.
Design and Build a Flutter-Based PKKMB Application with a QR Code Feature at Narotama University Putra, Fredy Pradana; Winardi, Slamet
Mobile and Forensics Vol. 6 No. 2 (2024)
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/mf.v6i2.11300

Abstract

Introduction to Campus Life for New Students (PKKMB) at Narotama University is a mandatory activity for new S1 students to get to know the academic and non-academic aspects as a condition for submitting a thesis proposal exam. The success of PKKMB is measured by the completion of tasks by participants, but manual recording for attendance, task grades, and compliance violations is prone to errors and fraud. This study uses a qualitative method that includes views, opinions, experiences, and open-ended questions to obtain the perspective of the respondents. Interviews with the chairman of the committee and participants of PKKMB 2023 were conducted to determine application features through the stages of requirements, design, implementation, testing, and maintenance. After determining the features of the application, the next step is to collect data through observation, interviews, and documentation, which are then analyzed through the stages of examination, classification, and drawing conclusions. The implementation of the PKKMB application includes splash screen pages, logins, participant homepages, participant assignments, graduation announcements, participant personal data, committee homepage, committee attendance, committee duties, and committee violations. The application was tested using the System Usability Scale with 30 respondents, resulting in a final score of 82.5 for the committee and 83 for the participants, which shows that the system is easy to use. The app is designed with Flutter, QR Code features, Laravel, and interface design from Figma.
Hybrid ABC–K Means for Optimal Cluster Number Determination in Unlabeled Data Rosyid, Harunur; bin Lakulu, Muhammad Modi; bt. Mailok , Ramlah
Mobile and Forensics Vol. 6 No. 2 (2024)
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/mf.v6i2.11529

Abstract

This study presents the ABC K Means GenData algorithm, an enhancement over traditional K Means clustering that integrates the Artificial Bee Colony (ABC) optimization approach. The ABC K Means GenData algorithm addresses the issue of local optima commonly encountered in standard K Means algorithms, offering improved exploration and exploitation strategies. By utilizing the dynamic roles of employed, onlooker, and scout bees, this approach effectively navigates the clustering space for categorical data. Performance evaluations across several datasets demonstrate the algorithm's superiority. For the Zoo dataset, ABC K Means GenData achieved high Accuracy (0.8399), Precision (0.8089), and Recall (0.7286), with consistent performance compared to K Means and Fuzzy K Means. Similar results were observed for the Breast Cancer dataset, where it matched the Accuracy and Precision of K Means and surpassed Fuzzy K Means in Precision and Recall. In the Soybean dataset, the algorithm also performed excellently, showing top scores in Accuracy, Precision, Recall, and Rand Index (RI), outperforming both K Means and Fuzzy K Means.. The comprehensive results indicate that ABC K Means GenData excels in clustering categorical data, providing robust and reliable performance. Future research will explore its application to mixed data types and social media datasets, aiming to further optimize clustering techniques. .
Digital Financial Transformation in Indonesia: Non-Cash Usage Via Modified UTAUT2 With Trust Ardy Nuswantoro, Setio; Muhammad Ulfi; Sahwari, Sahwari; Linda, Linda; Damayanti, Amara
Mobile and Forensics Vol. 6 No. 2 (2024)
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/mf.v6i2.11709

Abstract

Digital payments are transforming the financial landscape in Indonesia, offering fast and efficient services that meet the growing demand for cashless transactions. This study analyzes the factors influencing digital payment adoption using the UTAUT2 model, with the addition of Trust as a critical factor. Cluster analysis was also conducted using the k-prototype algorithm to see their characteristics and perceptions about digital payments. A survey was conducted from June to August 2024, gathering 451 responses from users of digital payment services. The data were analyzed using structural equation modeling to test 13 hypotheses. Of these, 10 hypotheses were accepted, indicating that Effort Expectancy, Performance Expectancy, Social Influence, Facilitating Conditions, Hedonic Motivation, Habit, and Trust significantly influence Behavioral Intention. Social Influence and Facilitating Conditions also directly impacted trust, which further strengthened users' intention to adopt digital payments. However, Price Value did not significantly affect Behavioral Intention, and Habit was not a strong predictor of continued use behavior. Trust emerged as a key factor in driving user engagement and long-term adoption. The study highlights that while convenience and social influence are crucial, trust in digital payment services is essential for sustaining user adoption. Cluster analysis divides respondents into four clusters, where the first, second, and third clusters are from young people with different perceptions about digital payment and the fourth cluster is from mature people who are mostly working as teachers or lecturers. These findings offer valuable insights into promoting digital payment usage and supporting Indonesia’s shift towards a digital economy.

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