Optimalisasi Energi Pada Lift Berdasarkan Gerak Vertikal pada Lift Menggunakan Hybrid Naive Bayes
DOI:
https://doi.org/10.32492/jeetech.v6i2.6203Keywords:
Optimalisasi Energi, Lift, Gerak Vertikal, Naive BayesAbstract
Penelitian ini bertujuan untuk mengoptimalkan penggunaan energi pada sistem lift berdasarkan
gerak vertikal menggunakan algoritma Hybrid Naive Bayes. Proses optimalisasi didasarkan pada
pengumpulan data dilakukan di Gedung B11 Fakultas Teknik Universitas Negeri Malang selama periode
waktu tertentu, dalam upaya mengurangi konsumsi energi pada gedung bertingkat, efisiensi energi lift
menjadi salah satu fokus utama. Dengan memanfaatkan data penggunaan lift yang meliputi pola pergerakan
vertikal, waktu operasional, serta beban muatan, penelitian ini melakukan klasifikasi dan prediksi efisiensi
energi. Algoritma Hybrid Naive Bayes dipilih karena kemampuannya dalam menangani ketidakpastian data
serta keandalannya dalam klasifikasi, terutama saat dikombinasikan dengan metode optimisasi lainnya. Hasil
prediksi efisiensi energi yang akurat juga memungkinkan manajemen gedung untuk menerapkan strategi
operasional yang lebih hemat energi dan ramah lingkungan. Dengan demikian, penelitian ini diharapkan
memberikan kontribusi signifikan dalam pengelolaan energi yang lebih efisien pada sistem lift di gedung
gedung tinggi.
References
A. Syaifudin, “Analisis Kelayakan Elevator Studi Kasus Hotel Grand Tjokro Dan Mataram City Yogyakarta,” Inersia, vol. X, no. 2, pp. 186–196, 2014.
K. Al-Kodmany, “Elevator Technology Improvements: A Snapshot,” Encyclopedia, vol. 3, no. 2, pp. 530–548, 2023, doi: 10.3390/encyclopedia3020038.
X. Zhang and M. U. Zubair, “Extending the useful life of elevators through appropriate maintenance strategies,” J. Build. Eng., vol. 51, no. October 2021, p. 104347, 2022, doi: 10.1016/j.jobe.2022.104347.
A. Fahriansyah, “Perencanaan Lift Penumpang Dengan Sistem Penggerak Tipe Traksi Kapasitas 600 Kg Untuk Keperluan Gedung Rumah Sakit Studi …,” 2021, [Online]. Available: http://eprints.uniska-bjm.ac.id/9140/%0Ahttp://eprints.uniska-bjm.ac.id/9140/1/ARTIKEL ALIYAN FAHRIANSYAH-dikonversi.pdf
A. Hamsi, I. A. Siregar, M. Sabri, Mahadi, and Tugiman, “Simulasi Perancangan Dan Pembuatan Shop Drawing Pada Pembangunan Lift Penumpang Kapasitas 20 Orang/1350 Kg,” Dinamis, vol. 6, no. 2, p. 11, 2018, doi: 10.32734/dinamis.v6i2.7102.
A. Sulistyo, “OPTIMASI PERHITUNGAN ULANG KEBUTUHAN LIFT PENUMPANG TYPE IRIS1-NV PA 20 (1350) C0105 PADA GEDUNG APARTEMEN 17 LANTAI,” no. 112, pp. 3–10.
R. H. Issa, H. Sarhan, and I. K. Al-abbas, “Optimization of Electric Passenger Elevator Available online www.jsaer.com Journal of Scientific and Engineering Research , 2021 , 8 ( 5 ): 43-55 Optimization of Electric Passenger Elevator,” no. June, 2021.
J. Zhang and Q. Zong, “Energy-saving scheduling optimization under up-peak traffic for group elevator system in building,” Energy Build., vol. 66, pp. 495–504, 2013, doi: 10.1016/j.enbuild.2013.07.069.
A. De Almeida, E. Dütschke, C. Patrao, S. Hirzel, and J. Fong, “Elevators and escalators: Energy performance and Strategies to promote energy efficiency,” no. April, 2010.
T. (2022). Glad, A., Kokkala, J., Ruokokoski, M., Sorsa, J., & Tukia, “Reducing Energy Consumption by an Optimization Algorithm,” The 2022 International Elevator & Escalator Symposium, Barcelona, Spain. [Online]. Available: https://elevatorworld.com/article/reducing-energy-consumption-by-an-optimization-algorithm-in-elevator-group-control/
A. F. Afifah, T. Herlintang, D. Ratna, and N. Hartono, “Analisa Kebutuhan Dan Manajemen Pemeliharaan Elevator Pada Gedung Perum Perhutani Unit I Jawa Tengah,” Wahana Tek. Sipil J. Pengemb. Tek. Sipil, vol. 22, no. 1, pp. 17–28, 2017.
A. C. H. J. Thebuwena, S. M. S. M. K. Samarakoon, and R. M. C. Ratnayake, “Optimization of energy consumption in vertical mobility systems of high-rise office buildings: A case study from a developing economy,” Energy Effic., vol. 17, no. 6, 2024, doi: 10.1007/s12053-024-10246-5.
T. M. Wut, “Elevator Energy-Efficient Projects in the Next Generation of High-Rise Green Buildings BT - Sustainable Energy and Green Finance for a Low-carbon Economy: Perspectives from the Greater Bay Area of China,” J. Fu and A. W. Ng, Eds., Cham: Springer International Publishing, 2020, pp. 245–258. doi: 10.1007/978-3-030-35411-4_13.
H. Sachs, H. Misuriello, and S. Kwatra, “Advancing elevator energy efficiency,” Rep. A1501, no. January, 2015, [Online]. Available: https://unepdtu.org/wp-content/uploads/sites/3/2016/03/a1501.pdf
J. H. Ang, Y. Yusup, S. A. Zaki, A. Salehabadi, and M. I. Ahmad, “Comprehensive Energy Consumption of Elevator Systems Based on Hybrid Approach of Measurement and Calculation in Low-and High-Rise Buildings of Tropical Climate towards Energy Efficiency,” Sustain., vol. 14, no. 8, pp. 1–21, 2022, doi: 10.3390/su14084779.
Y. Zhang, Z. Yan, F. Yuan, J. Yao, and B. Ding, “A novel reconstruction approach to elevator energy conservation based on a DC micro-grid in high-rise buildings,” Energies, vol. 12, no. 1, 2019, doi: 10.3390/en12010033.
P. A. Markos and A. J. Dentsoras, “An integrated mathematical method for traffic analysis of elevator systems,” Appl. Math. Model., vol. 105, pp. 50–80, 2022, doi: 10.1016/j.apm.2021.12.021.
Y. Wu and J. Yang, “Directional optimization of elevator scheduling algorithms in complex traffic patterns[Formula presented],” Appl. Soft Comput., vol. 158, no. April 2023, 2024, doi: 10.1016/j.asoc.2024.111567.
A. N. Z. Rashed et al., “Connected smart elevator systems for smart power and time saving,” Sci. Rep., vol. 14, no. 1, pp. 1–13, 2024, doi: 10.1038/s41598-024-69173-1.
K. M. Al-Aidaroos, A. Abu Bakar, and Z. Othman, “Naïve Bayes variants in classification learning,” Proc. - 2010 Int. Conf. Inf. Retr. Knowl. Manag. Explor. Invis. World, CAMP’10, pp. 276–281, 2010, doi: 10.1109/INFRKM.2010.5466902.
M. I. Ghozali, “IMPLEMENTASI METODE GAUSSIAN NAÏVE BAYES UNTUK MEMBANGUN MODEL PREDIKSI SERANGAN JANTUNG SKRIPSI Oleh: MUHAMMAD IMAM GHOZALI NIM. 200605110154 PROGRAM STUDI TEKNIK INFORMATIKA FAKULTAS SAINS DAN TEKNOLOGI UNIVERSITAS ISLAM NEGERI MAULANA MALIK IBRAHIM MAL,” Malang, 2024.
Heliyanti Susana, “Penerapan Model Klasifikasi Metode Naive Bayes Terhadap Penggunaan Akses Internet,” J. Ris. Sist. Inf. dan Teknol. Inf., vol. 4, no. 1, pp. 1–8, 2022, doi: 10.52005/jursistekni.v4i1.96.
S. C. Wang, R. Gao, and L. M. Wang, “Bayesian network classifiers based on Gaussian kernel density,” Expert Syst. Appl., vol. 51, pp. 207–217, 2016, doi: 10.1016/j.eswa.2015.12.031.
K. B. P. Y. Perkasa and F. Eka Purwiantono, “Sistem Rekomendasi Jurusan Menggunakan Algoritma Naïve Bayes Gaussian Berbasis Web,” J-Intech, vol. 11, no. 2, pp. 361–370, 2023, doi: 10.32664/j-intech.v11i2.1090.
Published
How to Cite
Issue
Section
Copyright (c) 2025 Adika Prana Ihsanuddin, Siti Sendari, Ilham Ari Elbaith Zaeni, M. Afnan Habibi, Danang Arengga Wibowo
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
