Penerapan Fuzzy Logic Controller dalam Meningkatkan Efisiensi Energi Listrik pada Pengoperasian Air Conditioner berbasis IoT

Authors

  • Dahlan Universitas Muhammadiyah Bima Author https://orcid.org/0009-0003-1225-6548
  • Rahmat Dani S Universitas Megarezky Makassar Author
  • Muhammad Amirul Mu’min Universitas Muhammadiyah Bima Author
  • Irma Eryanti Putri Universitas Muhammadiyah Bima Author

DOI:

https://doi.org/10.63866/jpst.v2i1.114

Keywords:

Air Conditioner, Internet of Things, Fuzzy Logic Controller, Efisiensi Energi

Abstract

Konsumsi energi listrik yang tinggi pada sistem penyejuk udara (Air Conditioner/AC) masih menjadi tantangan utama dalam manajemen energi bangunan. Penelitian ini mengusulkan pengembangan sistem kendali AC berbasis Internet of Things (IoT) yang terintegrasi dengan Fuzzy Logic Controller (FLC) sebagai pendekatan adaptif untuk meningkatkan efisiensi energi. Penelitian ini terletak pada integrasi FLC yang diimplementasikan secara langsung pada mikrokontroler IoT dengan mekanisme pemantauan dan pencatatan data operasional secara real-time, sehingga evaluasi kinerja sistem berbasis data aktual penggunaan energi. Sistem menggunakan sensor suhu sebagai input utama yang diproses melalui aturan fuzzy untuk menghasilkan keputusan kendali yang menyesuaikan kondisi lingkungan secara dinamis. Pengujian dilakukan pada lingkungan ruangan tertutup dalam periode operasional dengan membandingkan konsumsi energi antara sistem kendali konvensional dan sistem yang diusulkan. Hasil eksperimen menunjukkan bahwa penerapan FLC berbasis IoT mampu menurunkan konsumsi energi listrik hingga 28,8% tanpa mengurangi tingkat kenyamanan termal ruangan. Temuan ini menegaskan potensi pendekatan yang diusulkan sebagai solusi efektif untuk pengembangan sistem HVAC cerdas, serta dapat dikembangkan lebih lanjut dengan penambahan variabel lingkungan dan skala pengujian yang lebih luas. khususnya pada implementasi rumah pintar dan bangunan berenergi efisien.

Downloads

Download data is not yet available.

References

[1] I. E. Agency, Energy Efficiency 2023. Paris: IEA, 2023.

[2] ASHRAE, ASHRAE Handbook—HVAC Systems and Equipment. Atlanta: ASHRAE, 2020.

[3] K. K. dan Informatika, Pedoman Implementasi Internet of Things di Indonesia. Jakarta: Kominfo, 2023.

[4] J.-H. Han, C.-S. Choi, W.-K. Park, I.-W. Lee, and S.-H. Kim, “Smart home energy management system including renewable energy based on ZigBee and PLC,” IEEE Transactions on Consumer Electronics, vol. 60, no. 2, pp. 198–202, 2014.

[5] Z. Alamin, Khaeruddin, and Dahlan, “Sistem Penerangan Jalan Cerdas Berbasis Energi Surya dan IoT dengan Komunikasi LoRa,” Jurnal Pengembangan Sains dan Teknologi, vol. 1, no. 2, pp. 69–79, Jun. 2025, doi: 10.63866/jpst.v1i2.78.

[6] D. Dahlan, Y. Yuyun, and S. Sahibu, “Electronic Equipment Power Usage Control and Monitoring System in the Home Internet Of Things (IOT) Based,” Journal of System and Computer Engineering (JSCE), vol. 6, no. 1, pp. 90–100, Jan. 2025, doi: 10.61628/jsce.v6i1.1613.

[7] S. E. Board, “Advancing machine learning strategies for power and energy management systems,” Sensors, vol. 25, no. 4, p. 2101, 2025.

[8] Y. M. Banad, “Artificial intelligence and machine learning for smart grids,” Energy Reports, vol. 11, pp. 1123–1140, 2025.

[9] V. C. Gungor, “Smart grid technologies: Communication technologies and standards,” IEEE Trans Industr Inform, vol. 7, no. 4, pp. 529–539, 2013.

[10] Y. Chen, P. Xu, J. Gu, F. Schmidt, and W. Li, “Measures to improve energy demand flexibility in buildings for demand response,” Energy Build, vol. 43, no. 10, pp. 2625–2634, 2011.

[11] T. J. Ross, Fuzzy Logic with Engineering Applications. Wiley, 2010.

[12] A. I. Dounis and C. Caraiscos, “Advanced control systems engineering for energy and comfort management in a building environment—A review,” Renewable and Sustainable Energy Reviews, vol. 13, no. 6–7, pp. 1246–1261, 2009.

[13] X. Li, J. Wen, and J. Hu, “Energy-efficient HVAC control using deep reinforcement learning,” Energy Build, vol. 172, pp. 415–427, 2018.

[14] R. Yang and L. Wang, “Development of multi-agent system for building energy and comfort management,” Energy Build, vol. 56, pp. 1–7, 2013.

[15] J. Kim and J. E. Braun, “Reduced-order building modeling for real-time control,” ASHRAE Trans, vol. 118, no. 1, pp. 473–485, 2012.

[16] P. Ferreira and A. Ruano, “Energy management in HVAC systems using fuzzy logic,” Energy Build, vol. 89, pp. 192–202, 2015.

[17] M. W. Ahmad, M. Mourshed, and Y. Rezgui, “Trees vs Neurons: Comparison between random forest and ANN for high-resolution prediction of building energy consumption,” Energy Build, vol. 147, pp. 77–89, 2016.

[18] H.-X. Zhao and F. Magoulès, “A review on the prediction of building energy consumption,” Renewable and Sustainable Energy Reviews, vol. 16, no. 6, pp. 3586–3592, 2012.

[19] D. Kolokotsa, “The role of smart grids in the building sector,” Energy Build, vol. 116, pp. 703–708, 2016.

[20] P. Palensky and D. Dietrich, “Demand side management: Demand response, intelligent energy systems, and smart loads,” IEEE Trans Industr Inform, vol. 7, no. 3, pp. 381–388, 2011.

[21] S. Wang and Z. Ma, “Supervisory and optimal control of building HVAC systems: A review,” HVAC&R Res, vol. 14, no. 1, pp. 3–32, 2008.

[22] P. H. Shaikh, N. B. M. Nor, P. Nallagownden, I. Elamvazuthi, and T. Ibrahim, “A review on optimized control systems for building energy and comfort management of smart sustainable buildings,” Renewable and Sustainable Energy Reviews, vol. 34, pp. 409–429, 2014.

[23] T. Wei, Q. Zhu, and F. R. Yu, “Proactive demand participation of smart buildings in smart grid,” IEEE Trans Smart Grid, vol. 7, no. 3, pp. 1411–1422, 2016.

[24] L. A. Zadeh, “Fuzzy sets,” Information and Control, vol. 8, no. 3, pp. 338–353, 1965.

Downloads

Published

2026-01-22

How to Cite

[1]
Dahlan, Rahmat Dani S, Muhammad Amirul Mu’min, and Irma Eryanti Putri, “Penerapan Fuzzy Logic Controller dalam Meningkatkan Efisiensi Energi Listrik pada Pengoperasian Air Conditioner berbasis IoT”, J. Pengemb. Sains Teknol., vol. 2, no. 1, pp. 22–32, Jan. 2026, doi: 10.63866/jpst.v2i1.114.