Dasa Aprisandi (1)*, Galih Nur Wijaya (2)
(1) Program Studi Teknik Sipil, Institut Sains Dan Teknologi Nasional, Jakarta, INDONESIA
*Corresponding author: dasa@istn.ac.id
Penelitian ini berhasil mengembangkan sistem cerdas guna mengatasi masalah pelaporan dan estimasi biaya perbaikan aset kampus yang selama ini dilakukan secara manual sehingga menghambat efisiensi transparansi dan kecepatan respon
pemeliharaan. Sistem yang dikembangkan memanfaatkan Google Form sebagai pelaporan bagi pengguna dan Microsoft Excel sebagai dashboard analisis. Melalui penerapan metode design based research terciptalah suatu alur kerja terintegrasi yang mampu menghasilkan estimasi biaya perbaikan secara otomatis berdasarkan standar analisa harga satuan pekerjaan yang berlaku. Hasil penelitian ini memberikan kontribusi praktis berupa sebuah solusi biaya rendah yang meningkatkan efisiensi transparansi dan kecepatan dalam menangani kerusakan aset. Selain itu penelitian ini juga memberikan kontribusi metodologis melalui sebuah blueprint teknologi serta identifikasi tantangan implementasi yang dapat dijadikan panduan bagi perguruan tinggi lain dalam mengembangkan sistem serupa.
REFERENSI
Afolabi, Adedeji, et al. E-Maintenance Framework for Strategic Asset Management in Tertiary Institutions BT –
Computational Science and Its Applications – ICCSA 2019. Edited by Sanjay Misra et al., Springer International
Publishing, 2019, pp. 266–77.
Chung, Suwan, et al. “Smart Facility Management System Based on Open BIM and Augmented Reality
Technology.” Applied Sciences, vol. 11, no. 21, 2021, https://doi.org/10.3390/app112110283.
Fialho, Beatriz C., et al. “Development of a BIM and IoT-Based Smart Lighting Maintenance System Prototype for
Universities’ FM Sector.” Buildings, vol. 12, no. 2, 2022, https://doi.org/10.3390/buildings12020099.
Li, Weiguang. “Design of Smart Campus Management System Based on Internet of Things Technology.” J. Intell.
Fuzzy Syst., vol. 40, 2021, pp. 3159–68, https://doi.org/10.3233/jifs-189354.
Nurhasan, Usman, et al. “Implementasi Aplikasi E-Reporting Infrastructure (ERI) Sebagai Media Monitoring Pengaduan Kerusakan Fasilitas Kampus.” PETIR, 2021, https://doi.org/10.33322/petir.v15i1.1532.
Pan, Xiao, and T. Y. Yang. “Postdisaster Image-Based Damage Detection and Repair Cost Estimation of Reinforced
Concrete Buildings Using Dual Convolutional Neural Networks.” Computer-Aided Civil and Infrastructure
Engineering, vol. 35, no. 5, May 2020, pp. 495–510, https://doi.org/https://doi.org/10.1111/mice.12549.
Perez, Husein, et al. “Deep Learning for Detecting Building Defects Using Convolutional Neural Networks.”
Sensors, vol. 19, no. 16, 2019, https://doi.org/10.3390/s19163556.
Rodriguez, Francisca S., et al. “Performance Differences between Instructions on Paper vs Digital Glasses for a
Simple Assembly Task.” Applied Ergonomics, vol. 94, 2021, p. 103423,
https://doi.org/https://doi.org/10.1016/j.apergo.2021.103423.
Roy, Arunabha M., and Jayabrata Bhaduri. “DenseSPH-YOLOv5: An Automated Damage Detection Model Based
on DenseNet and Swin-Transformer Prediction Head-Enabled YOLOv5 with Attention Mechanism.” Advanced
Engineering Informatics, vol. 56, 2023, p. 102007, https://doi.org/https://doi.org/10.1016/j.aei.2023.102007.
Sandhya, S., et al. “Adoption of Google Forms for Enhancing Collaborative Stakeholder Engagement in Higher
Education.” Journal of Engineering Education Transformations, 2020,
https://doi.org/10.16920/jeet/2020/v33i0/150161.
Xie, Xiang, et al. “Digital Twin Enabled Asset Anomaly Detection for Building Facility Management.” IFAC-
PapersOnLine, vol. 53, no. 3, 2020, pp. 380–85, https://doi.org/https://doi.org/10.1016/j.ifacol.2020.11.061.
Yin, Mengtian, et al. “Exploring the Value of Digital Twins for Information Management in Highway Asset
Maintenance.” Developments in the Built Environment, 2025, https://doi.org/10.1016/j.dibe.2025.100614.
Zhang, Xiaoying, et al. “Using Virtual Reality Technology to Visualize Management of College Assets in the Internet
of Things Environment.” IEEE Access, vol. 8, 2020, pp. 157089–102,
https://doi.org/10.1109/ACCESS.2020.3019836.