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Pembagian Beban Trafik pada Cluster Server Kusumawardani, Mila; Suharto, Nugroho; Zakaria, Muhammad Nanak
Jurnal EECCIS (Electrics, Electronics, Communications, Controls, Informatics, Systems) Vol. 16 No. 1 (2022)
Publisher : Faculty of Engineering, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/jeeccis.v16i1.619

Abstract

Permasalahan yang ada pada server adalah banyaknya user yang mengakses dalam waktu bersamaan. Untuk mengatasinya dapat digunakan konsep cluster server. Metode yang digunakan dalam artikel ini adalah membangun 3 cluster server web  dan 1 load balancer dari 4 buah Nanopi2 serta  mengimplementasikan algoritma round robin dalam pengaturan kerjanya. Hasil yang diperoleh adalah bahwa terjadi pembagian beban trafik yang berimbang di antara 3 server dengan rata-rata pada saat server menerima request dari client adalah 33.57%, 32.64%, dan 33.8%, serta rata-rata pada saat server memberikan response adalah 33.47%, 34.14%, dan 35.35%
Internet of things-based fuzzy controller for automatic irrigation and NPK nutrient monitoring of grapes Sarosa, Moechammad; Wirayoga, Septriandi; Kusumawardani, Mila; Firmanda Al Riza, Dimas; Mulyani Azis, Yunia
Bulletin of Electrical Engineering and Informatics Vol 14, No 6: December 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v14i6.9715

Abstract

Grape cultivation has gained increasing attention due to its short growing period and the high market value of its sweet, refreshing fruits. However, achieving optimal growth requires precise environmental and nutrient management, which can be challenging under conventional farming practices. This research aims to develop an automatic watering system that integrates soil moisture and nutrient monitoring to optimize grape cultivation. The system utilizes Nitrogen Phosphorus Potassium (NPK) sensors, soil moisture sensors, and a camera for growth observation, all connected through the internet of things (IoT) for remote monitoring via Android devices. A fuzzy logic controller is implemented to regulate watering duration based on environmental conditions such as temperature and humidity. Experimental results show that the system effectively adjusts watering duration to approximately six seconds when the temperature is between 25–32 °C and humidity is around 60%. The DS18B20 temperature sensor achieved an average error rate of only 0.12%, while the humidity sensor demonstrated 0.2% error, indicating high accuracy levels of 99.8%. Despite minor limitations related to internet stability and sensor calibration, the system demonstrates strong potential for commercial-scale smart farming applications, promoting resource-efficient and data-driven grape cultivation.