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All Journal Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) Jurnal Darma Agung
Dinata, Ericha Septya
Unknown Affiliation
Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Social Sciences

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APLIKASI WEBSITE UNTUK PERANCANGAN INFRASTRUKTUR JARINGAN SISTEM KOMUNIKASI SERAT OPTIK: FITUR KALKULASI LINK POWER BUDGET Dinata, Ericha Septya; Hambali, Akhmad; Iqbal, Muhammad
JURNAL DARMA AGUNG Vol 31 No 5 (2023): OKTOBER
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat Universitas Darma Agung (LPPM_UDA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46930/ojsuda.v31i5.3761

Abstract

Latar Belakang – Aplikasi website kalkulasi Link Power Budget (LPB) pada perancangan sistem komunikasi serat optik sangat dibutuhkan. Hal ini dikarenakan pembangunan sistem komunikasi serat optik terus dilakukan. Tujuan – Fitur LPB dirancang untuk membantu teknisi mengetahui daya yang akan dipancarkan oleh pemancar agar dapat diterima dengan baik oleh penerima. Pada kalkulasi LPB terdapat gambar untuk memudahkan teknisi memahami komponen penyusun infrastruktur serat optik mulai dari transmitter (tx) sampai pada receiver (rx). Fitur kalkulasi LPB bertujuan untuk mendapatkan nilai dari dua persamaan matematis yaitu total redaman (α_Total) dan sensitivitas daya (Pr). Metode - Kalkulasi LPB pada website didesain dengan navigasi yang intuitif, tata letak yang jelas, dan tampilan yang responsif sehingga pengguna akan mudah mengoperasikannya. Hasil Penelitian - Berdasarkan hasil pengujian perhitungan manual dan aplikasi website nilai redaman total sisi uplink sebesar sebesar 25,97497 dB dan downlink sebesar 25,53497. Hasil simulasi daya terima pada perhitungan manual maupun website didapatkan hasil yang sama yaitu sebesar -21 dBm. Kesimpulan – Nilai akurasi terhadap fitur LPB dapat disimpulkan bahwa LPB memiliki akurasi 100% dari 100%. Berdasarkan hasil perhitungan akurasi tersebut, maka fitur kalkulasi LPB merupakan fitur kalkulasi yang akurat dan layak digunakan untuk perancangan infrastruktur jaringan sistem komunikasi optik khususnya pada LPB.
Adaptive Cooling System Control in Data Center with Reinforcement Learning Dinata, Ericha Septya; Hertiana, Sofia Naning; Sugesti, Erna Sri
Jurnal Ilmiah Teknik Elektro Komputer dan Informatika Vol. 11 No. 1 (2025): March
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jiteki.v11i1.30671

Abstract

Data center cooling system is consuming large amounts of power, which requires effective control to reduce operational costs and deliver optimal server performance. The high power consumption occurs because traditional cooling methods struggle to adapt dynamically to workloads, causing wasteful power consumption. Therefore, this study aimed to explore the use of machine learning methods to improve energy efficiency for data center cooling system. For the experiment, an RL (Reinforcement Learning) model was designed to adjust cooling parameters with dynamic environmental changes. The method focused on optimizing energy efficiency while maintaining stable temperature and humidity control. By applying RL-based control method to PAC system, this study contributed original results that validated the effectiveness of RL-simulated data center environments. Specifically, the stages included developing system model, creating simulations using the PAC control system, and training an RL model with environmental conditions. Data were collected from simulations and analyzed to test the model performance, and the outcomes were presented using a real-time monitoring interface with Flask. The results showed that the RL model achieved an average reward of 4.76 (between -5 and 5), a convergence rate 13.2, a sampling efficiency 10.15, and a stability score 2.6. The model effectively reduced temperature and increased humidity during stressed data center operations. When compared with a fixed cooling system, RL showed superior adaptability to workload variations and reduced unnecessary energy consumption. However, scalability to real data center remained an issue, which required more than simulation validation. In conclusion, the RL-based method optimized efficiency of cooling system, showing the potential to improve energy savings and operational resilience in data center environments.
Co-Authors Akhmad Hambali Erna Sri Sugesti Sofia Naning Hertiana Winnugroho Wiratman, Manfaluthy Hakim, Tiara Aninditha, Aru W. Sudoyo, Joedo Prihartono