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Implementation of an Integrated Information System for Construction Services Development to Support Infrastructure Projects at the Public Works Department of Tarakan City Hadriansa, H; Prayogi, Denis; Fadlan, Muhammad; Fandariansyah, F
IJISTECH (International Journal of Information System and Technology) Vol 8, No 5 (2025): The February edition
Publisher : Sekolah Tinggi Ilmu Komputer (STIKOM) Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/ijistech.v8i5.373

Abstract

Efficient infrastructure development requires effective management, particularly in developing construction services. The Public Works (PU) Department of Tarakan City faces challenges in overseeing and guiding construction service providers to ensure smooth execution and project quality. This study aims to design and implement an integrated information system using the Scrum method, which supports construction service development, project progress monitoring, contractor data management, and budget supervision. Scrum was chosen to enhance flexibility and collaboration among development teams by allowing the system to be built iteratively and incrementally. The system is designed to improve transparency, efficiency, and accuracy in managing construction projects. The implementation results show that applying the Scrum method in developing the integrated information system has successfully accelerated the verification process, reduced administrative errors, and improved budget control. Additionally, the system has increased project management efficiency, expedited decision-making, and facilitated monitoring and evaluation processes. This study recommends further development and expansion of the system to support more effective construction service development in the future
Face Recognition Using Machine Learning Algorithm Based on Raspberry Pi 4b Sunardi, Sunardi; Fadlil, Abdul; Prayogi, Denis
International Journal of Artificial Intelligence Research Vol 6, No 1 (2022): June 2022
Publisher : Universitas Dharma Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (502.574 KB) | DOI: 10.29099/ijair.v7i1.321

Abstract

Machine learning is one of artificial intelligence that is used to solve various problems, one of which is classification. Classification can separate a set of objects based on certain characteristics. This study discusses the classification of objects in the form of facial images with the aim of the system being able to recognize a person's face to access a room for security reasons. The application of machine learning using the support vector machine algorithm with the support vector classifier technique is implemented on a raspberry pi-based security device.  The results of training using this algorithm produce a model with 99% accuracy in 0.10 seconds based on testing data of 525 face images. The model evaluation got 99% precision, 99% recall, and 99% f1-score. Testing the model made from the training process using the raspberry pi model 4b is can recognize facial images in real-time.  If the security device detects someone at the door and then recognizes the face image then room access will be granted and an alarm is activated indicating the door is open.