Analisis Akurasi UAV-LiDAR terhadap TLS pada Estimasi Volume Stockpile Batubara dan Pengembangan Dashboard Streamlit untuk Monitoring Rekonsiliasi Material Tambang

Purba, Michael Aragorn (2026) Analisis Akurasi UAV-LiDAR terhadap TLS pada Estimasi Volume Stockpile Batubara dan Pengembangan Dashboard Streamlit untuk Monitoring Rekonsiliasi Material Tambang. Other thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Akurasi estimasi volume stockpile batubara penting dalam rekonsiliasi material tambang karena menjadi dasar pengendalian stok, evaluasi produksi, dan analisis deviasi aliran material. Terrestrial Laser Scanner (TLS) memiliki ketelitian tinggi sebagai metode referensi, tetapi penggunaannya di area tambang aktif terkendala oleh banyaknya posisi pemindaian, waktu akuisisi lama, serta potensi occlusion pada geometri timbunan kompleks. Penelitian ini mengevaluasi Light Detection and Ranging berbasis Unmanned Aerial Vehicle (UAV-LiDAR) sebagai alternatif metode estimasi volume stockpile batubara terhadap TLS, serta mengembangkan dashboard Streamlit untuk monitoring rekonsiliasi material berbasis data survei operasional. Data UAV-LiDAR diakuisisi menggunakan DJI Matrice 350 RTK dengan sensor LiDAR Zenmuse L2, sedangkan data referensi TLS diperoleh menggunakan RIEGL VZ-2000i pada area Coal Processing Plant (CPP). Georeferensi dan uji akurasi geometrik menggunakan 10 Ground Control Point (GCP) dan 12 Independent Check Point (ICP). Estimasi volume dihitung dengan pendekatan cut and fill surface-to-surface terhadap base surface yang sama. Akurasi geometrik dievaluasi menggunakan CE90 dan LE90, sedangkan akurasi volumetrik dianalisis menggunakan Relative Error (RE) dan paired t-test. Dashboard Streamlit dikembangkan dari data survei operasional berformat Excel untuk menghitung deviasi volume, KPI, dan material flow. Hasil penelitian menunjukkan UAV-LiDAR mencapai CE90 0,111 m dan LE90 0,042 m, sehingga memenuhi ketelitian Kelas 1 skala 1:1.000. Nilai RE total pada tiga sesi sebesar -0,79%, -0,82%, dan -1,61%. Paired t-test menghasilkan p-value 0,812 pada level segmen dan 0,078 pada level stok, sehingga tidak terdapat perbedaan sistematis signifikan antara UAV-LiDAR dan TLS. Dashboard Streamlit mampu menghitung deviasi dan KPI, mengklasifikasikan status rekonsiliasi, serta menghasilkan laporan evaluasi operasional.
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The accuracy of coal stockpile volume estimation is important in mining material reconciliation because it serves as the basis for stock control, production evaluation, and material flow deviation analysis. Terrestrial Laser Scanner (TLS) provides high accuracy as a reference method; however, its use in active mining areas is constrained by multiple scan positions, long acquisition time, and potential occlusion in complex stockpile geometries. This study evaluates Unmanned Aerial Vehicle-based Light Detection and Ranging (UAV-LiDAR) as an alternative method for coal stockpile volume estimation against TLS, and develops a Streamlit dashboard for material reconciliation monitoring based on operational survey data.UAV-LiDAR data were acquired using a DJI Matrice 350 RTK equipped with a Zenmuse L2 LiDAR sensor, while TLS reference data were obtained using a RIEGL VZ-2000i in the Coal Processing Plant (CPP) area. Georeferencing and geometric accuracy assessment used 10 Ground Control Points (GCPs) and 12 Independent Check Points (ICPs). Volume estimation was calculated using a cut and fill surface-to-surface approach against the same base surface. Geometric accuracy was evaluated using CE90 and LE90, while volumetric accuracy was analyzed using Relative Error (RE) and a paired t-test. The Streamlit dashboard was developed from Excel-based operational survey data to calculate volume deviation, KPI, and material flow. The results show that UAV-LiDAR achieved a CE90 of 0.111 m and an LE90 of 0.042 m, meeting Class 1 accuracy requirements at a 1:1,000 scale. The total RE values across the three sessions were -0.79%, -0.82%, and -1.61%. The paired t-test produced p-values of 0.812 at the segment level and 0.078 at the stock level, indicating no significant systematic difference between UAV-LiDAR and TLS. The Streamlit dashboard can calculate deviations and KPIs, classify reconciliation status, and generate operational evaluation reports.

Item Type:	Thesis (Other)
Uncontrolled Keywords:	UAV-LiDAR, TLS, Volume Stockpile, Streamlit, Rekonsiliasi Material, UAV-LiDAR, TLS, Volume Stockpile, Streamlit, Rekonsiliasi Material
Subjects:	G Geography. Anthropology. Recreation > G Geography (General) > G70.5.I4 Remote sensing T Technology > TA Engineering (General). Civil engineering (General) > TA590 Topographical surveying T Technology > TN Mining engineering. Metallurgy
Divisions:	Faculty of Civil, Planning, and Geo Engineering (CIVPLAN) > Geomatics Engineering > 29202-(S1) Undergraduate Thesis
Depositing User:	Michael Aragorn Purba
Date Deposited:	20 Jul 2026 01:55
Last Modified:	20 Jul 2026 01:55
URI:	http://repository.its.ac.id/id/eprint/135440

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