Pratama, Dananjaya Endi
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Connectivity Revolution: Fiber Optic Network Mapping for Modern Jember Darmawan, Muhammad Riza; Fadhil, Martiana Kholila; Rizkiyah R., Candra Putri; Pratama, Dananjaya Endi; Triputradi, Moh. Erdianto
Jurnal Arus Elektro Indonesia Vol. 10 No. 3 (2024)
Publisher : Fakultas Teknik, Universitas Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19184/jaei.v10i3.53349

Abstract

Jember Regency is a popular marine tourism destination with five beaches, each experiencing an increase in the number of visitors each year in Jember Regency. Although these beaches are favorites and increase visitors annually, they require better infrastructure to support tourism activities. The research evaluated the network design using several parameters: power link budget, rise time, Signal to Noise Ratio (SNR), and Bit Error Rate (BER). The result of this study shows that the 39 network paths meet the BER calculation standard of 10-12 and the SNR standard of 21.5 dB.
A Study on Reducing Measurement Fluctuations in Iron-Electrode Salinity Sensor Using Moving Average and Kalman Filters Pratama, Dananjaya Endi; Habibulloh, Muhammad Aldino; Darmawan, Muhammad Riza; Ramadhani, Candra Putri Rizkiyah; Triputradi, Mohammad Erdianto; Fadhil, Martiana Kholila
Journal of Applied Electrical Engineering Vol. 9 No. 1 (2025): JAEE, June 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaee.v9i1.9539

Abstract

Indonesia is recognized as one of the leading shrimp-producing countries globally, with most farms operating on a small scale using traditional methods. This creates a strong demand for low-cost technologies to support aquaculture. One critical component in shrimp farming is water quality monitoring, where salinity is a key parameter affecting shrimp health and growth. Affordable salinity sensors using iron electrodes are increasingly considered. However, they often produce unstable and fluctuating readings, compromising monitoring reliability. This study addresses the issue by applying digital filters to enhance the stability of salinity sensor data. Two filtering methods, Moving Average and Kalman filters were evaluated using salinity ADC data from previous research. The analysis focused on comparing their effectiveness in stabilizing measurements. Results show that the Moving Average filter outperformed the Kalman filter, providing lower standard deviation values (87,09, 65,69, 63,67) and variance values (7,5807E+03, 4,3150E+03, 4,0542E+03), confirming its suitability for improving low-cost salinity sensor performance.