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PERANCANGAN INFRASTRUKTUR DAN IMPLEMENTASI WEB SERVER UNTUK WEBSITE SEKOLAH SEBAGAI MEDIA INFORMASI DAN KOMUNIKASI DI SMP PJHI BALIKPAPAN Ihsan Ihsan; Dwi Lesmideyarti; Qory Hidayati; Tri Retno Nugroho
Jurnal Teknologi Terpadu Vol 11, No 1 (2023): JTT (Jurnal Teknologi Terpadu)
Publisher : Pusat Penelitian dan Pengabdian Kepada Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32487/jtt.v11i1.1598

Abstract

This research activity in collaboration with partners is carried out with the background of wanting to implement relevant science to solve problems that occur in the community. The world of education, from elementary school to university levels, is required to be able to adapt to rapidly developing technological advances, especially in the field of information. Various ways are carried out by an agency to address the global issue of the 4.0 revolution, where information systems are needed, especially junior high schools that do not yet have a web server as a cloud-based database storage medium and school website facilities as a medium of information to the public. Various information can be provided through the school's website, including school profiles, learning activities, teacher and student achievements and New Student Admissions (PPDB). In this research activity, the implementing team designed a web server and school website using the UML (Unified Modeling Language) and PHP (PHP Hypertext Preprocessor) programming language. The problems faced by partners are the location of the school which is less strategic and the number of applicants is getting smaller every year in the Batakan area of East Balikpapan, does not have informative media for various aspects of interest, the existence of an online PPDB policy from the Education Office to suppress the increase in cases of covid19, limited human resources in the internet and information systems, as well as school quality assurance, namely accreditation. To overcome these problems, SMP PJHI Balikpapan must have its own web server and website. The benefits of online PPDB activities can be carried out so that parents do not need to go to school during registration, and can facilitate the achievement of school accreditation, so as to increase the credibility of the school. The research activities carried out by the team consisted of establishing communication with partners, designing and implementing school servers and websites, providing training on the use of websites, implementing websites in schools.
Kendali Lampu Lalu Lintas dengan Deteksi Kendaraan Menggunakan Metode Blob Detection Qory Hidayati
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 6 No 2: Mei 2017
Publisher : Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1199.446 KB)

Abstract

Traffic jam is a major traffic problem often found in big cities of Indonesia. It is because the number of vehicles increases annually. Therefore, a simulation to detect the number of vehicles in every lane of traffic is needed to monitor the traffic. Traffic control is also required in order to reduce traffic jam. This paper develops a vehicle detection and counting system using image processing. Detection is carried out using image segmentation which is processed by object filtering and blob extraction. Morphological operators are employed for blob extraction. Testing is conducted using a video obtained from the ATCS Bandung. The video is taken at the Laswi - A. Yani intersection Bandung. Software prototypes are created in C++, using Windows Forms Application as a programming library for Windows and Open CV for image processing module. The result shows that blob detection method can give good results if there is no intersection between blobs of each car. The performance is poor when this method is used for heavy traffic conditions, where the cars are close to each other. The performance level of sensitivity is 91.67%, precision is 61.11%, specificity is 80.55%, f-Measure is 73.33%, and accuracy is 83.33%. The accuracy for vehicles detection on sunny condition is 82.11% and reduced by 76.50% on rainy condition. This method works better in quiet condition, with accuracy of 83.07%, and is reduced by 67.70% in crowded condition. The average processing time is 0.042 seconds when using video, and 0.033 seconds using real camera.