Vol. 3 No. 2 (2024): December 2024

This research examines the implementation of internet networks using Tenda N301 router in Pidie Regency as a connectivity solution for areas with infrastructure limitations. The research methodology employs a qualitative approach with descriptive analysis conducted at three strategic locations: Peutoe Village Office, SDN 1 Sigli, and Sigli Public Health Center during the period from July to December 2019. Implementation was carried out through stages of site survey, device installation and configuration, network performance measurement, load testing, and 30-day monitoring to evaluate system reliability and performance. Research results demonstrate satisfactory technical performance with average download speed of 28.8 Mbps, upload speed of 11.6 Mbps, latency of 15.2 ms, and packet loss of 0.2%. Effective coverage area reaches an average of 1,978 m² with capability to handle 18-20 concurrent users. User satisfaction level reaches a score of 4.2 out of 5.0 with 99.1% uptime during the monitoring period. Security implementation using WPA2-PSK, guest network, and MAC address filtering provides adequate protection for public institutional environments. Economic analysis shows positive return on investment within 8-12 months with low total cost of ownership. This research proves that entry-level routers such as Tenda N301 can be an effective and efficient solution for improving internet connectivity in remote areas, despite having limitations in user capacity and coverage area. The implementation model developed can serve as a template for similar deployments in other areas with similar geographical and socio-economic characteristics.

This research aims to develop a web-based decision-making system to identify strategic locations for salon businesses in Banda Aceh using the Simple Additive Weighting (SAW) method. The primary issue is the critical need to select an optimal location to minimize business risks, enhance competitiveness, and maximize profits in the service sector, particularly salons, influenced by factors such as accessibility, proximity to crowded areas, competitor presence, female population aged 15–50 years, upper-middle-class population, and rental costs. The methodology includes direct field observations, in-depth interviews with salon owners, and data analysis using SAW based on six key criteria. The system features a user-friendly interface with a main menu and submenus, including data alternatives, criteria, analysis, graphs, reports, and user management, to streamline data input, processing, and visualization. Data were collected through in-person and online questionnaires, processed using PHP and MySQL-based software. The results indicate that Syiah Kuala (Darussalam) achieves the highest score of 0.83, making it the optimal location, presented through ranking tables and bar graphs for clear visualization. The system significantly improves decision-making efficiency and effectiveness by providing accurate location recommendations, assisting both existing and prospective salon entrepreneurs in selecting strategic locations that ensure long-term business success in Banda Aceh.

The recruitment process for contract employees in government institutions often encounters obstacles due to its reliance on manual procedures, which are prone to errors, time-consuming, and influenced by subjectivity. This study develops a web-based Decision Support System to support the selection process at the Aceh Islamic Sharia Office by applying the Simple Additive Weighting (SAW) method. The research employed the waterfall approach, which included requirements analysis, system design, implementation, and testing. The system was developed using PHP and MySQL as its core technologies. The results indicate that the SAW method provides more objective and measurable rankings of applicants compared to manual procedures. The system also generates transparent reports, accelerates the selection process, and reduces human error. Therefore, the application of SAW is proven to be effective in supporting a fairer and more efficient recruitment process within government institutions.

This study aims to implement a thin client network based on dumb terminal using NComputing vSpace Type L130 in the academic room of SMAN 1 Bandar Baru to enhance resource efficiency and computer system performance. The research was motivated by the high power consumption and maintenance complexity of conventional desktop systems in the school’s computer laboratory. The methodology includes definition, design, and verification stages, with testing focused on four parameters: CPU usage, memory consumption, network throughput, and power consumption. The implementation utilized a Lenovo X3650 M5 server running Microsoft Hyper-V Server 2012 R2 and five NComputing L300 units, connected via a 100 Mbps Ethernet network using the User Extension Protocol (UXP). Test results showed an average CPU usage of 35%, memory usage of 9 GB out of 16 GB, throughput of 85 Mbps, and power consumption of 5 watts per unit, achieving up to 97% energy savings compared to conventional desktops. The system supports administrative and web-based applications stably, reduces maintenance costs, and enables centralized management. This research offers an energy-efficient and scalable solution that can be replicated in other educational institutions with similar constraints.

This study aims to develop a web-based decision support system using the Multi-Objective Optimization on the Basis of Ratio Analysis (MOORA) method to determine the best rice quality in Pidie Regency, assisting farmers in selecting high-quality rice for consumption or seeds. Primary data were collected through interviews and observations with farmers and agricultural experts, identifying five evaluation criteria: grain size, moisture content, color, aroma, and protein content. The system was built using PHP, HTML/CSS, JavaScript, and MySQL, with the MOORA process involving decision matrix creation, normalization, criteria weighting, and alternative ranking. Testing revealed a system accuracy of 87.5% and user satisfaction of 4.2 out of 5, with Rice A achieving the highest rank (optimization value of 0.892). The system offers a practical solution with a user-friendly interface, reducing subjectivity in rice quality assessment, though limited to 10 alternatives and excluding market price factors. This research contributes to Pidie’s farmers by enhancing decision-making efficiency and paving the way for web-based agricultural technology development.