Training Mine Data Analytics & Digital Transformation

Training Mine Data Analytics & Digital Transformation adalah program pelatihan pertambangan yang membahas pemanfaatan data analytics, Internet of Things (IoT), automation, Artificial Intelligence (AI), Machine Learning, dashboard analytics, dan teknologi digital untuk meningkatkan produktivitas, efisiensi, reliability, serta keselamatan operasi pertambangan.

Industri pertambangan menghasilkan data dalam jumlah besar dari aktivitas exploration, mine planning, drilling, production, hauling, processing, heavy equipment maintenance, environmental monitoring, hingga supply chain dan logistics. Data tersebut dapat diolah menjadi informasi dan insight yang mendukung pengambilan keputusan secara lebih cepat dan berbasis data.

Melalui training ini, peserta akan memahami konsep Digital Mining, Industry 4.0, Smart Mining Operations, Mine Data Analytics, Predictive Maintenance, Fleet Management System, Digital Twin, serta penggunaan tools seperti Power BI, Python, Excel Analytics dan IoT Dashboard.

Mengapa Mine Data Analytics & Digital Transformation Penting?

Transformasi digital membantu perusahaan pertambangan mengintegrasikan data dari berbagai aktivitas operasional sehingga manajemen dapat memperoleh gambaran kinerja tambang secara lebih cepat, terukur dan komprehensif.

Dengan penerapan mining data analytics, perusahaan dapat menganalisis produktivitas alat, cycle time, fuel consumption, equipment utilization, downtime, maintenance performance, haul road performance, production achievement, serta berbagai indikator operasional lainnya.

Pemanfaatan IoT, AI, Machine Learning, predictive analytics, real-time monitoring dan dashboard juga dapat membantu perusahaan beralih dari pendekatan reaktif menuju pengelolaan operasi yang lebih prediktif dan berbasis data.

Manfaat Training Mine Data Analytics & Digital Transformation

Setelah mengikuti training ini, peserta diharapkan mampu:

• Memahami konsep digital transformation di industri pertambangan.
• Memahami konsep Digital Mining dan Smart Mining Operations.
• Mengidentifikasi potensi data di seluruh rantai operasi mine-to-mill.
• Memahami Mine Data Ecosystem.
• Memahami proses data acquisition, data quality dan data integration.
• Mengintegrasikan data ERP, SCADA, FMS dan IoT.
• Memahami descriptive, diagnostic, predictive dan prescriptive analytics.
• Menggunakan data analytics untuk mendukung optimasi operasi tambang.
• Menganalisis produktivitas dan utilisasi heavy equipment.
• Menganalisis haul cycle dan hauling performance.
• Menggunakan data untuk meningkatkan fuel efficiency.
• Memahami predictive maintenance untuk peralatan pertambangan.
• Memahami Fleet Management System.
• Memahami pemanfaatan IoT dan real-time monitoring.
• Memahami konsep Digital Twin dalam operasi pertambangan.
• Mengembangkan dashboard KPI pertambangan.
• Memahami pemanfaatan Power BI, Python dan Excel Analytics.
• Menyusun digital mining roadmap.
• Mendukung pengambilan keputusan berbasis data.

Materi Training Mine Data Analytics & Digital Transformation

Hari 1 – Fundamentals of Mine Data Analytics

1. Introduction to Digital Mining & Industry 4.0

• Konsep Digital Transformation
• Digital Mining
• Mining Industry 4.0
• Smart Mining Operations
• Data-driven mining
• Connected mining operations
• Automation dalam pertambangan
• Perkembangan teknologi digital di industri pertambangan
• Digital maturity dalam organisasi pertambangan

2. Mine Data Ecosystem

• Konsep Mine Data Ecosystem
• Exploration data
• Geological data
• Mine planning data
• Production data
• Heavy equipment data
• Maintenance data
• Environmental data
• Financial data
• Supply chain & logistics data
• Health & safety data

3. Data Acquisition & Data Quality

• Data acquisition
• Manual vs automated data collection
• Sensor data
• Equipment telemetry
• IoT data
• Data accuracy
• Data completeness
• Data consistency
• Data validation
• Data cleansing
• Data quality management

4. Mining Data Management & Integration

• Mining database
• Data architecture
• Data integration
• Enterprise Resource Planning (ERP)
• SCADA
• Fleet Management System (FMS)
• Internet of Things (IoT)
• Maintenance database
• Cloud data platform
• Data warehouse
• Single source of truth

5. Fundamentals of Data Analytics for Mining

• Data analytics fundamentals
• Descriptive Analytics
• Diagnostic Analytics
• Predictive Analytics
• Prescriptive Analytics
• Mining operational analytics
• Trend analysis
• Variance analysis
• Correlation analysis
• Data-driven decision making

6. Mining KPI & Performance Analytics

• Production KPI
• Equipment KPI
• Maintenance KPI
• Safety KPI
• Environmental KPI
• Production achievement
• Equipment availability
• Equipment utilization
• Productivity
• Downtime
• Cycle time
• Fuel consumption
• Cost per ton

7. Hauling & Fleet Data Analytics

• Haul cycle analysis
• Loading time
• Hauling time
• Queuing time
• Dumping time
• Truck productivity
• Fleet utilization
• Fleet availability
• Equipment idle time
• Haul road performance
• Fleet optimization

8. Data Analytics for Fuel Efficiency

• Fuel consumption analysis
• Fuel efficiency KPI
• Fuel consumption per equipment
• Fuel consumption per ton
• Idle fuel consumption
• Operator behaviour analysis
• Haul road influence
• Payload influence
• Fuel efficiency improvement

9. Data Visualization & Mining Dashboard

• Principles of data visualization
• Mining dashboard
• Operational dashboard
• Production dashboard
• Maintenance dashboard
• Fleet dashboard
• Environmental dashboard
• KPI visualization
• Real-time dashboard
• Management dashboard

10. Analytics Tools for Mining

• Microsoft Excel Analytics
• Microsoft Power BI
• Python for Data Analytics
• IoT Dashboard
• Database tools
• Data visualization tools
• Analytics workflow
• Reporting automation

Hari 2 – Smart Mining & Digital Transformation

11. Internet of Things (IoT) in Mining

• Konsep Internet of Things
• Connected equipment
• Smart sensor
• Equipment telemetry
• Remote monitoring
• Real-time data acquisition
• Equipment health monitoring
• Environmental monitoring
• IoT architecture
• IoT dashboard

12. Artificial Intelligence & Machine Learning in Mining

• Artificial Intelligence fundamentals
• Machine Learning fundamentals
• Mining AI applications
• Classification
• Regression
• Prediction
• Anomaly detection
• Equipment failure prediction
• Production forecasting
• Operational optimization

13. Predictive Maintenance Analytics

• Preventive vs Predictive Maintenance
• Condition-Based Maintenance
• Equipment health data
• Failure history
• Maintenance history
• Vibration data
• Temperature data
• Oil analysis data
• Failure prediction
• Remaining Useful Life
• Maintenance optimization

14. Fleet Management System (FMS)

• Konsep Fleet Management System
• Fleet monitoring
• Truck dispatch
• Equipment tracking
• Payload monitoring
• Cycle time monitoring
• Equipment utilization
• Fleet productivity
• Dispatch optimization
• Real-time fleet analytics

15. Digital Twin for Mining Operations

• Konsep Digital Twin
• Physical asset & digital model
• Real-time operational data
• Equipment Digital Twin
• Mine Digital Twin
• Simulation
• Scenario analysis
• Operational optimization
• Predictive monitoring

16. Drone Mapping & Remote Sensing

• Drone technology in mining
• Aerial mapping
• Remote sensing
• Stockpile measurement
• Mine progress monitoring
• Survey data
• Digital terrain model
• Operational monitoring
• Integration with mine analytics

17. Real-Time Monitoring & Control

• Real-time mining operations
• Operational monitoring
• Equipment monitoring
• Production monitoring
• Safety monitoring
• Environmental monitoring
• Automated alerts
• Exception reporting
• Control room dashboard
• Decision support system

18. Mine-to-Mill Data Analytics

• Mine-to-mill concept
• Drilling data
• Blasting data
• Fragmentation data
• Loading & hauling data
• Crusher performance
• Processing plant data
• Throughput analysis
• Recovery analysis
• Integrated operational optimization

19. Digital Mining Roadmap

• Digital maturity assessment
• Identifikasi business problem
• Digital opportunity identification
• Technology selection
• Data readiness assessment
• People & competency readiness
• Digital governance
• Implementation priorities
• Quick wins
• Digital transformation roadmap
• Change management

20. Case Study – Mine Data Analytics & Digital Transformation

• Optimasi haul road menggunakan data analytics
• Fuel efficiency analytics
• Heavy equipment productivity analysis
• Predictive maintenance case study
• Fleet Management System case study
• Dashboard analytics
• IoT monitoring
• Digital mining implementation
• Identifikasi digital improvement opportunity
• Penyusunan Digital Mining Action Plan

Metode Training

Training Mine Data Analytics & Digital Transformation menggunakan pendekatan pembelajaran yang menggabungkan konsep, diskusi, data analysis, dashboard, case study, dan penyusunan digital transformation roadmap.

• Presentasi dan pembahasan konsep
• Diskusi interaktif
• Mining data analysis
• KPI analysis
• Dashboard analytics
• Fleet performance analysis
• Predictive maintenance discussion
• Case study pertambangan
• Problem solving
• Digital Mining Action Plan

Target Peserta Training

• Mining Engineer
• Mine Operation Engineer
• Mine Planning Engineer
• Production Engineer
• Maintenance Engineer
• Reliability Engineer
• Data Analyst
• Business Intelligence Analyst
• IT / Digital Transformation Team
• Fleet Management Personnel
• Technical Services
• Mine Supervisor & Superintendent
• Operation Manager
• Maintenance Manager
• Digital Transformation Manager
• Data Management Team
• Profesional yang terlibat dalam digitalisasi operasi pertambangan

Pembicara / Fasilitator

Tim Trainer Johnson Indonesia

Trainer berpengalaman dan fokus pada bidang mining operations, data analytics, business intelligence, digital transformation, Industry 4.0, IoT, automation, maintenance analytics, dan teknologi pertambangan.

Jadwal Training Mine Data Analytics & Digital Transformation

Jadwal Training

• 26–27 Januari 2027
• 11–12 Februari 2027
• 25–26 Maret 2027
• 22–23 April 2027
• 06–07 Mei 2027
• 10–11 Juni 2027
• 20–21 Juli 2027
• 10–11 Agustus 2027
• 14–15 September 2027
• 07–08 Oktober 2026
• 09–10 November 2026
• 14–15 Desember 2026

Jam Pelaksanaan Training

09.00–16.00 WIB

Durasi Public Offline Training adalah 2 hari.

Metode Pelaksanaan Training

Public Offline Training

• Pelaksanaan secara tatap muka.
• Lokasi di salah satu hotel bintang 4 di area setempat.
• Minimal 5 peserta untuk Fix Running.
• Durasi 2 hari.
• Waktu training pukul 09.00–16.00 WIB.

In-House Training

Program dapat diselenggarakan secara khusus melalui In-House Training Mine Data Analytics & Digital Transformation. Materi, dataset, tools, studi kasus, jadwal dan durasi dapat disesuaikan dengan kebutuhan perusahaan.

Fee Investasi Training Mine Data Analytics & Digital Transformation

Offline Training Jakarta

Rp 5.950.000,- / peserta / 2 hari

• Pelaksanaan secara tatap muka di hotel.
• Waktu training pukul 09.00–16.00 WIB.
• Termasuk fasilitas training.

Online Training

Rp 5.500.000,- / peserta / 2 hari

• Pelaksanaan live secara online.
• Menggunakan Zoom Meeting.
• Waktu training pukul 09.00–16.00 WIB.

Private Training Jakarta

Rp 8.000.000,- / peserta / 2 hari

• PASTI RUNNING.
• Pelaksanaan secara private.
• Lokasi di Johnson Indonesia Training Center.

Offline Training Luar Jakarta

• Rp 12.000.000,- / peserta – PASTI RUNNING
• Rp 8.500.000,- / peserta untuk pengiriman 1–5 peserta.
• Rp 8.000.000,- / peserta untuk pengiriman lebih dari 5 peserta.

Fasilitas Training

• Training Material
• Seminar Kit
• Certificate
• Lunch
• Snack / Coffee Break
• Souvenir

In-House Training Mine Data Analytics & Digital Transformation

Johnson Indonesia menyediakan program In-House Training Mine Data Analytics & Digital Transformation yang dapat dikustomisasi berdasarkan kondisi dan kebutuhan digitalisasi perusahaan pertambangan.

Materi dapat difokuskan pada data aktual perusahaan seperti production data, fleet data, heavy equipment data, maintenance data, fuel consumption, cycle time, downtime, equipment utilization, environmental data, maupun KPI operasional lainnya.

Program juga dapat disesuaikan menggunakan tools seperti Microsoft Power BI, Microsoft Excel, Python, IoT Dashboard, Fleet Management System atau platform analytics yang digunakan perusahaan.

Biaya In-House Training disesuaikan dengan jumlah peserta, lokasi, durasi, tools, dataset, ruang lingkup materi dan kebutuhan perusahaan.

Training Mining & Digital Transformation Terkait

• Training Mining Automation
  
• Training Heavy Equipment Maintenance & Reliability Improvement
  
• Training Risk-Based Inspection (RBI) & Asset Integrity in Mining
  
• Training Mine Planning, Design & Scheduling
  
• Training Mineral Processing & Beneficiation Technology
  
• Training Project Management for Mining Operations
  
• Mining Training Series Johnson Indonesia
  

Keunggulan Training Johnson Indonesia

• Training Provider Since 2002.
• Trainer berpengalaman dan fokus pada bidangnya.
• Materi dapat disesuaikan dengan kebutuhan perusahaan.
• Tersedia Public Training, Online Training, Private Training dan In-House Training.
• Pembelajaran menggabungkan konsep, data analytics, dashboard, discussion dan case study.
• Materi dapat disesuaikan menggunakan data dan KPI operasional perusahaan.
• Program mendukung pengembangan kompetensi menuju Smart Mining Operations.

Informasi & Pendaftaran Training

Johnson Indonesia – Training Center
Training Provider Since 2002

Telp: (021) 5417516
HP / WhatsApp: 0858 8690 3082 (Komariah – Fast Response)
HP / WhatsApp: 0815 972 5020
PIC: Nur / Komariah / Nisa / Dinda / Fanni

Untuk informasi jadwal terbaru, proposal, Public Training, Private Training maupun In-House Training Mine Data Analytics & Digital Transformation, silakan menghubungi Johnson Indonesia.

Daftarkan peserta perusahaan Anda untuk meningkatkan kompetensi Mine Data Analytics, Digital Mining, Smart Mining dan Digital Transformation bersama Johnson Indonesia.