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Local area network architecture design at Nurul Jalal Islamic Boarding School, North Jakarta Sitanggang, Andri Sahata; Syafariani, R. Fenny; Hasti, Novrini; Sari, Febilita Wulan; Pasya, Dhara
International Journal of Advances in Applied Sciences Vol 13, No 1: March 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijaas.v13.i1.pp123-133

Abstract

A computer network is a telecommunications network that allows computers to communicate with each other by exchanging data. At Nurul Jalal Islamic Boarding School, they have taken advantage of advances in computer network technology, but have not been fully connected properly. Therefore, in this research, a local area network (LAN) architecture that is connected to speedy internet will be built and developed. The design of this network architecture includes designing a connection to the internet speedy network and designing a computer lab architecture that is connected to the network at the Nurul Jalal Islamic Boarding School. This study aims to design the existing technology with the system and add technologies and systems that do not yet exist so that they can be integrated into a computer network connected to the speedy internet network. It is hoped that this research will help teachers and students of Nurul Jalal Islamic Boarding School in exploring information so that it can help effective and efficient learning.
Internet of Things (IoT) Integration for Real-Time Monitoring in Smart Cities T. Irfan Fajri; Novi Rahayu; Wasiran; Yusuf Unggul Budiman; Novrini Hasti
International Journal Software Engineering and Computer Science (IJSECS) Vol. 5 No. 1 (2025): APRIL 2025
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v5i1.3465

Abstract

The advancement of Internet of Things (IoT) technology has opened great opportunities for the implementation of real-time monitoring systems in supporting smart city management. This research aims to develop an IoT integration model that can monitor various urban aspects, such as traffic management, energy consumption, waste management, and air quality, in an efficient and integrated manner. The model is designed to collect, process, and analyze data from various IoT sensors scattered in urban areas, with a focus on delivering information in an integrated manner. urban areas, with a focus on delivering real-time information to the government and the public. The research methodology includes the development of development of an IoT-based system prototype that integrates hardware and hardware and software with the support of cloud computing architecture for data management. data management.
Analysis of Household Electricity Consumption Patterns Using K-Nearest Neighbor (KNN) Method Cut Susan Octiva; Sultan Hady; Dedy Irwan; T. Irfan Fajri; Novrini Hasti
International Journal Software Engineering and Computer Science (IJSECS) Vol. 5 No. 1 (2025): APRIL 2025
Publisher : Lembaga Komunitas Informasi Teknologi Aceh (KITA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/ijsecs.v5i1.3877

Abstract

The increasing demand for electricity in the household sector poses significant challenges to energy efficiency initiatives and environmental conservation efforts. Examining electricity usage patterns offers a pathway to uncover key determinants that influence consumption levels while formulating more effective strategies for energy management. This study attempts to evaluate electricity consumption patterns in the household sector using the K-Nearest Neighbor (KNN) algorithm. This approach is used to categorize consumption data based on attribute similarities among household units. The findings are expected to encourage more rational electricity usage practices, thereby reducing energy inefficiencies and strengthening efforts to conserve natural resources. Furthermore, the analysis aims to provide actionable insights for households to adopt sustainable habits and for policymakers to design targeted interventions that address peak demand periods and promote the use of energy-efficient technologies. By identifying specific behavioral and technological factors that contribute to high consumption, the results can serve as a basis for tailored programs aimed at minimizing waste and promoting long-term environmental management.