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INDONESIA
PROCEEDING IC-ITECHS 2014
Published by Sekolah Tinggi Informatika dan Komputer Indonesia Malang
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Core Subject : Science, Education,
Computer Science & IT Education
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Articles 235 Documents
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Improve Healthcare Accessibility via a Mobile App for Health Facility Search Utilizing Location-Based Services Zulkarnain, Adnan; Gibran, Devid
IC-ITECHS Vol 5 No 1 (2024): IC-ITECHS
Publisher : LPPM STIKI Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32664/ic-itechs.v5i1.1512

Abstract

Access to health facilities is an important aspect of individual well-being but many communities, especially in remote areas, face difficulties in finding and accessing health services. Location-Based Services (LBS) technology in mobile applications offers a solution to this problem. This research aims to develop and test an LBS-based mobile application to improve the accessibility of health facilities. Using applied design, applications are developed for Android platforms. The sample consisted of 100 respondents in areas with limited access to health facilities, divided into experimental and control groups. Data is collected through application usage logs and questionnaires, analyzed using appropriate statistical techniques to evaluate accessibility and user satisfaction. The results show that the LBS application significantly increases the accessibility of health facilities. The experimental group found and accessed health facilities 30% faster than the control group. As many as 85% of experimental group respondents were satisfied with the ease of use and speed of application access. The LBS application is effective in increasing the accessibility of health services by providing real-time information about nearby health facilities. This research has practical implications for app developers, healthcare providers, and policymakers.
The Digital Learning Revolution: AI-Powered Adaptive Learning in PGSD Lectures Hertati, Elvani
IC-ITECHS Vol 5 No 1 (2024): IC-ITECHS
Publisher : LPPM STIKI Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32664/ic-itechs.v5i1.1532

Abstract

The development of digital technology has significantly impacted education, including PGSD (Primary School Teacher Education) lectures. AI-powered adaptive learning offers vast potential to revolutionize digital learning in PGSD, particularly in the course on Digital Learning. This study aims to explore the use of AI-powered adaptive learning in the context of fifth-semester PGSD students enrolled in Digital Learning courses for elementary schools. This research employs a qualitative approach with a case study method. Data were collected through observations, in-depth interviews with lecturers and students, and document analysis. Data were analyzed thematically to identify the benefits, challenges, and effective strategies for implementing AI-powered adaptive learning. The findings reveal that AI-powered adaptive learning has significant potential to enhance the effectiveness of digital learning in PGSD lectures. This system can provide personalized learning tailored to the needs and abilities of each student. It also boosts learning motivation, fosters independence, and optimizes study time. However, the study also highlights several challenges, such as resource availability, technology access, and lecturers' readiness to implement this system. This research recommends that universities consider integrating AI-powered adaptive learning as an integral part of digital learning in PGSD lectures. It also serves as a reference for developing strategies and policies that support the effective and sustainable implementation of AI-powered adaptive learning in higher education.
A Literature Review: Examining Visual Design and Multimedia Elements Role in Fighting Misinformation and Strengthening Media Trust Arbi, Hafiz; Juhana, Agus
IC-ITECHS Vol 5 No 1 (2024): IC-ITECHS
Publisher : LPPM STIKI Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32664/ic-itechs.v5i1.1534

Abstract

The development of digital media has presented new challenges in maintaining the credibility of information, especially amidst the increasing prevalence of misinformation and hoaxes that spread rapidly through social platforms. This study aims to explore how visual design and multimedia elements can contribute to building audience trust in media and encouraging engagement in disseminating credible information. Using the Systematic Literature Review (SLR) method, the research follows a selection procedure based on PRISMA 2020 guidelines to ensure the validity and quality of the included studies. From 20 articles that meet the inclusion criteria, the key findings indicate that consistent and aesthetically pleasing visual design, particularly those capable of touching the emotional aspects of the audience, plays a crucial role in enhancing media credibility and brand loyalty. Additionally, interactive multimedia approaches, such as dynamic infographics and narrative-based short videos, not only capture audience interest but also strengthen their intention to share credible information. This study concludes that the application of strong visual elements and emotion-based multimedia strategies can help counter misinformation by strengthening media brand equity. Recommendations for future research include developing interactive designs that can educate audiences in identifying credible information and collaborating with media professionals to ensure broader impact. These findings provide practical guidance for media in integrating visual design as an effective tool to build trust and enhance information literacy in the digital age.
A Train Driving Simulator to Enhance Railway Technology Student’s Learning Experience Using Prototype Method and OpenBVE Domato, Mea Ann E. Domato Ann E.; Gutierrez, Gabriel T.; Canas, Maxine Honey A; Salinas, Cyril Rose R.; Sison, Venerando A.; Bunag, Sherlie D.; Delizo, Carlo Jay G.; Aunario, Connie C.; Andador, Jennifer D.; Garcia, Julius G.
IC-ITECHS Vol 5 No 1 (2024): IC-ITECHS
Publisher : LPPM STIKI Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32664/ic-itechs.v5i1.1540

Abstract

A Train Driving Simulator is a software application that tries to replicate the experience of operating a train. This unique equipment minimizes the expense of using actual rolling stock to teach future railway staff. The research aims to create a Train Driving Simulator with OpenBVE for Railway Technology students. The research focused on making a simulator that simulates the feeling of driving a train, which involved detailed physics modeling and control of the train. The simulator was built to be user-friendly and accessible, with features such as the 3D representation of the LRT Line 1 route and its compact, portable architecture. The simulator was built from commercial off-shelf parts and tested for usefulness, safety, and durability. The simulator's performance was tested using the TUP evaluation metrics. The research aimed to enhance the learning experience of students undergoing railway technology by providing on-site training in operating a train. The simulator will likely provide students and instructors with maximum benefit in courses like Railway Signaling, Rolling Stocks, and Railway Facilities
An Automated Rack Storage System for Railway Devices and Equipment Using QR Code and Cloud Database Technology Sarong, Charm Angel R.; Ignacio, Aaliyah Mikaela A.; Guzarin, Chrizel R.; Valdueza, Rhen Jester; Delizo, Carlo Jay G.; Bunag, Sherlie D.; Aunario, Connie C.; Martin, Weellrr D.; Garcia, Julius G.
IC-ITECHS Vol 5 No 1 (2024): IC-ITECHS
Publisher : LPPM STIKI Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32664/ic-itechs.v5i1.1541

Abstract

This research project aims to develop an automated storage rack system for railway devices and equipment using QR codes and cloud-based database technology. The automated rack system can precisely store railway devices and equipment using the cloud-based QRC/QR Code database. It explores the drawbacks of conventional storage management methods in the railway industry, like lack of order, inefficiency, and security issues. Using QR codes to track and monitor all tools, equipment, and components, the proposed system includes a cloud-based database providing real-time inventory visibility and data analysis capabilities. Additionally, the system features CCTV surveillance for added security level and mobile phone integration to ensure that only you, as the end user, get access. Based on the study's findings, automated storage rack systems promise significant improvements in efficiency, security, and operational effectiveness for railway maintenance.
A Modular Track and Signaling Simulation Trainer for Railway Technology Program Dumalag, Alexi Maxine A.; Jatulan, Mark Joseph A.; Marmol, Marlon P.; Taneo, Abegail A.; Sison, Ghazali Illuminada R.; Garcia, Julius G.; Bunag, Sherlie D.; Ballesteros, Mariezol V.; Delizo, Carlo Jay G.
IC-ITECHS Vol 5 No 1 (2024): IC-ITECHS
Publisher : LPPM STIKI Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32664/ic-itechs.v5i1.1542

Abstract

The modular railway track and signaling simulation trainer research project was developed to provide an enjoyable and educational tool to train railway students and professionals upon recognizing the need for effective training in traffic and signaling safety-critical areas. It provides a miniature model that accurately replicates railway switch points and signaling systems with modules depicting track layouts and signaling conditions created using Programmable Logic Controller (PLC) and Human-Machine Interface (HMI). The prototype's accurate and efficient miniature railway model showed that the simulation trainer was very effective. The survey demonstrated that railway students and professionals were satisfied with the trainer's performance and various use and educational potential for students. This simulation trainer design successfully changes railway training programs because it offers a relatively safe and exciting environment that allows learners to get practical experience and understanding of railway operations. The modular design of the trainer will facilitate future expansion and customization, making it adaptable to railway training needs and technology. The simulation trainer should include level crossings, track circuits, and train detection systems for further investigation. This would provide an improvement in the comprehensiveness and flexibility of the trainer, therefore helping with providing skilled railway workers.
Empowering ESL Learning: Motivation in Acquiring English as a Second Language Dela Rosa, Reyn Alyana Legaspi; Santos, Crissel Kylle; Yaya, Kristan
IC-ITECHS Vol 5 No 1 (2024): IC-ITECHS
Publisher : LPPM STIKI Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32664/ic-itechs.v5i1.1551

Abstract

ABSTRACT: This study investigates the role of motivation in enhancing English as a Second Language (ESL) acquisition among Grade 7 students. It employs a qualitative-descriptive method as it analyzes the complex dynamics of motivation in the context of English as a Second Language (ESL) learning, providing a nuanced grasp of the motivational elements that influence ESL learners' language acquisition journeys. The study investigates the varied nature of motivation using interviews and thematic analysis, with the goal of uncovering ESL learners' subjective experiences, challenges, and attitudes. Grasping the complexities of motivation within the ESL context is dominant, as it can influence students' engagement and language proficiency. Results of the study have shown that English as a Second Language Learning (ESL) is one of the common factors that affects students learning in a classroom setting. Motivation also plays a significant role in determining students’ academic performance and overall accomplishment in acquiring proficiency in English as a Second Language (ESL). The study assessed the motivational factors among Grade 7 students, focusing on Integrative Orientation with a composite mean of (5.14) and Instrumental Orientation with a composite mean (5.07) respectively. Problems encountered were evaluated through Survey Questionnaires (composite mean: 3.65) and Interviews. Integrative Orientation significantly influences English as a Second Language motivation, while difficulties in English language usage emerge as primary issues. Grade 7 students, undergoing a transitional academic phase, face challenges in adjusting to learning. Recommendations of the researchers focus on academic importance that will help enhance and increase learning motivation of the students in English as a Second Language.
An Enhancement of Eigenface Algorithm Applied for Identifying Spoofing Attacks in Facial Recognition Casison, Ron Hale; Upaga, Chloe Gwyneth; Guialil, Jamillah; Cortez, Dan Michael
IC-ITECHS Vol 5 No 1 (2024): IC-ITECHS
Publisher : LPPM STIKI Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32664/ic-itechs.v5i1.1553

Abstract

Facial recognition is a biometric authentication technology that identifies individuals using their facial features in images and videos. The rise of spoofing attacks poses significant risks, especially for facial recognition, as malicious actors are impersonating individuals by misusing their identities. The accuracy of facial recognition can be impacted by factors like face occlusions, image low-resolution, and the distance of the user's face from the camera, leading to potential misidentification. This research enhanced the Eigenface Algorithm applied to identify spoofing attacks in facial recognition. The algorithm extracts facial features and transforms them into eigenvectors for improved accuracy. Previous studies showed limitations in face detection at varying distances, prompting the incorporation of a distance-based scale in the enhanced algorithm, targeting a range of 30 cm to 60 cm from the camera. In this study, the researchers implemented OpenCV2 and stored the trained dataset in a YAML file. The dataset was generated by capturing multiple images with varying environments and distances, which were then preprocessed to resize and convert them to grayscale. Results showed a confidence level of 93.83% for the enhanced algorithm, a significant improvement from 57.38% with the existing one, and a faster average recognition time of 0.0141 seconds compared to 0.0216 seconds, demonstrating a 36.45% increase in confidence and a speed improvement of 0.0075 seconds. The distance-based scaling improves the efficiency of the Eigenface Algorithm by preventing recognition attempts at unsuitable distances, thus enhancing usability in practical applications.
Enhancing ResNet with Ghost Weight Normalization For Improved Retina Disease Classification Baihaqi, Galih Restu; Shalsadilla, Shafatyra Reditha; Argaputri, Maulida Khairunisa
IC-ITECHS Vol 5 No 1 (2024): IC-ITECHS
Publisher : LPPM STIKI Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32664/ic-itechs.v5i1.1554

Abstract

Retinal disease is a dangerous disease. If left untreated, it can cause blurred vision and even cause permanent blindness. Recently, deep learning approaches are widely used to classify medical diseases. A widely used model to classify medical diseases is ResNet. To train the ResNet model, the data used is data obtained from Kaggle with the name Retinal OCT Images (Optical Coherence Tomography) consisting of 4 classes namely choroidal neovascularization (CNV), DRUSEN, diabetic macular edema (DME), and Normal with a total of 83,600 data. The ResNet base model showed accuracy and f1-score of 92%. Modifying the ResNet Base model with the addition of Ghost Weight Normalization (GWN) which aims to provide more weight normalization opportunities shows an increase in accuracy and f1-score to 94%. GWN can also increase the accuracy of CNN Base from 77% to 81%. This improvement shows that GWN can improve the accuracy of Deep learning models with its weight normalization variation technique. Although the training load and training time when using GWN can increase, the accuracy and f1-score of the ResNet model with GWN of 94% can make the chance of misclassification of retinal diseases smaller.
Development of Cloud Messaging-Based Mobile Learning Application to Improve Interaction in the Learning Process at STIKI (ebelajar case study) Perdana, Derajat Aalim
IC-ITECHS Vol 5 No 1 (2024): IC-ITECHS
Publisher : LPPM STIKI Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32664/ic-itechs.v5i1.1555

Abstract

In the digital era, the use of technology in the learning process is crucial to improve the effectiveness and efficiency of education. This study aims to develop a cloud messaging-based mobile learning application to improve interaction between students and lecturers at STIKI. This application is developed using the Dart programming language with the Flutter framework and utilizes cloud messaging technology to enable fast and effective communication in the form of announcements, discussions, and task notifications. The research method used is the research and development (R&D) method with the Agile software development model. The development stages include needs analysis, design, implementation, and application testing and evaluation. The results of the study show that this mobile learning application can increase the frequency and quality of interaction in the learning process. This increase is measured through user satisfaction surveys and analysis of application usage data. With this application, it is expected to provide a positive contribution in increasing student involvement in the teaching and learning process, as well as making it easier for lecturers to deliver materials and information related to lectures. This study also presents recommendations for further development so that the application can continue to be adjusted to user needs and technological developments.

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