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All Journal Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) Jurnal INFOTEL
Zainal, Zulfan
Unknown Affiliation
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering

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Aplikasi Reservasi Maintenance Kendaraan Berbasis SMS Gateway Zulfan, Zulfan; Munawir, Munawir
Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) Vol 3, No 1 (2019): JTIK
Publisher : KITA Institut

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (443.691 KB) | DOI: 10.35870/jtik.v3i1.84

Abstract

Private or public vehicles as a means of transportation are now increasingly being used. This develops along with a large number of residents in their daily activities. With so many vehicles the need for vehicle maintenance centers is also growing. At present, the vehicle maintenance center is not proportional to the number of vehicles. This problem is seen by many vehicle users who are waiting to take care of their vehicles and some of them have to make reservations. Reservations made are still conventional in nature that is still making reservations at the vehicle maintenance center. Therefore, the purpose of this paper is to explain the making of the SMS Gateway vehicle reservation application. The method used is the Software Development Life Cycle (SDLC) using PHP, MySQL, and Gammu programming. This research produces an application that can make customers make vehicle maintenance reservations remotely using SMS media. And customers can receive information about vehicles that have been completed through maintenance via SMS sent via the application server.Keywords:Reservation, Vehicle, Information System, SMS gateway
Mobile Application Development for Facial Classification of Autistic Children Based on MobileNet-V3 Ramadhan, Irsyan; Melinda, Melinda; Yunidar, Yunidar; Acula, Donata D; Miftahujjannah, Rizka; Rusdiana, Siti; Zainal, Zulfan
JURNAL INFOTEL Vol 17 No 3 (2025): August
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/infotel.v17i3.1363

Abstract

Early detection of autism spectrum disorder (ASD) is crucial to support timely interventions that can improve children’s cognitive and social development. However, conventional approaches still rely on subjective observations and parental reports. This study proposes the development of a Flutter-based mobile application for face classification of autistic and non-autistic children using the MobileNetV3-Small architecture. The dataset contains 600 original facial images of children aged 4 to 14 years (300 autistic and 300 non-autistic), which were expanded to 1,860 images through augmentation techniques such as Gaussian noise addition, flipping, and contrast adjustment. The model was trained using transfer learning and optimized with the SGD optimizer and sigmoid activation function. During training, the model achieved a training accuracy of 95.27% and a validation accuracy of 97.92%, indicating effective learning with minimal overfitting. Evaluation on the test data showed perfect performance, with accuracy, precision, recall, and F1-score all reaching 100%. The model was then converted to TensorFlow Lite format to allow on-device inference on mobile platforms. The app enables users to upload photos via camera or gallery and instantly receive classification results, which are also saved to Firebase for history tracking. Testing showed a fast response time (1–2 seconds) and a smooth, user-friendly experience. These results highlight the potential of the system as a lightweight, efficient, and accessible facial image-based ASD screening tool, particularly in regions with limited access to specialized healthcare. Future work should include validation using larger and more diverse datasets across different demographics to ensure model robustness, fairness, and generalizability in real-world environments.
Co-Authors Acula, Donata D Melinda Melinda Miftahujjannah, Rizka Munawir Munawir Ramadhan, Irsyan Siti Rusdiana Yunidar