Analytics Dashboard — Sistem Manajemen Statistik Seluler

Date Range

Year

Month

Start Date

End Date

City

Owner Market Share

Indonesia (Global)

Pemilik	Sites	Share

Operator Teratas

Berdasarkan jumlah sel

Operator	Wilayah	Sel	RSRP	RSRQ

Pengukuran UE

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Sel Logis

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Situs Fisik

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Rata-rata RSRP

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Tren Pengukuran

7 hari terakhir

Tren Kualitas Sinyal

7 hari terakhir

Distribusi Kualitas Sinyal

Rentang Kualitas RSRP

Total Pengukuran

—

Rata-rata RSRP

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Rata-rata RSRQ

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Peringatan

Theoretical Coverage (POI)

Estimasi RSRP berbasis model (memperhitungkan kontur) untuk lokasi kritis

Kota

Total POI

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Sangat Baik (≥-80)

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Baik (-81 to -100)

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Cukup+Buruk (<-100)

—

Kota	Total POI	Rata-rata RSRP	Distribusi Cakupan	Skor

Kecamatan	Total POI	Rata-rata RSRP	Distribusi Cakupan	Skor

Cakupan Terbaik (15 Teratas)

Kelurahan	POI	Rata-rata RSRP

Perlu Peningkatan (15 Teratas)

Kelurahan	POI	Rata-rata RSRP

Jenis POI	Jumlah	Rata-rata RSRP	Min	Maks	Distribusi

POI kritis yang perlu perhatian - Lokasi ini memiliki cakupan sinyal terlemah dan harus diprioritaskan untuk perbaikan jaringan.

Nama POI	Jenis	Lokasi	RSRP	Status	Menara Pelayan

Agregasi RSRP UE Real-time

Pengukuran crowdsourcing dari Drive Test

Kota

Total Measurements

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Sangat Baik (≥-80)

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Baik (-81 to -100)

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Cukup+Buruk (<-100)

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Kota	Pengukuran	Rata-rata RSRP	Distribusi Cakupan	Skor

Kecamatan	Pengukuran	Rata-rata RSRP	Distribusi Cakupan	Skor

Cakupan Terbaik (15 Teratas)

Kelurahan	Pengukuran	Rata-rata RSRP

Perlu Peningkatan (15 Teratas)

Kelurahan	Pengukuran	Rata-rata RSRP

Coverage Comparison

Theoretical Coverage (POI) vs Drive Test (Real UE)

Kota

Kota	Teoretis (POI)		Real-time (UE)		Perbedaan (Real - Model)
Kota	Jumlah	Rata-rata RSRP	Pengukuran	Rata-rata RSRP	Perbedaan (Real - Model)

Kecamatan	Teoretis (POI)		Real-time (UE)		Perbedaan (Real - Model)
Kecamatan	Jumlah	Rata-rata RSRP	Pengukuran	Rata-rata RSRP	Perbedaan (Real - Model)

Menampilkan 20 kelurahan dengan selisih terbesar antara model teoretis dan pengukuran real-time

Kelurahan	Kecamatan	Teoretis (POI)		Real-time (UE)		Perbedaan (Real - Model)
Kelurahan	Kecamatan	Jumlah	Rata-rata RSRP	Pengukuran	Rata-rata RSRP	Perbedaan (Real - Model)

Poor Signal & Blankspot

Area dengan cakupan lemah atau tidak ada berdasarkan pengukuran RSRP UE

Kota

Kota	Total Pengukuran	Rata-rata RSRP	Sinyal Buruk (< -100 dBm)	Sangat Buruk (< -115 dBm)	Distribusi

District	Total Measurements	Avg RSRP	Poor Signal (< -100 dBm)	Very Poor (< -115 dBm)	Distribution

Menampilkan area dengan kualitas sinyal terburuk (urut rata-rata RSRP terendah)

Kelurahan	Kecamatan	Total Pengukuran	Rata-rata RSRP	Blankspot (-150 dBm)	Sinyal Buruk (< -115 dBm)	Status

📊 4G LTE Quality Insights

Penilaian Kualitas Jaringan Kelola Dashboard

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Nilai Kualitas Keseluruhan

Insight Utama

Rekomendasi

Penilaian ini berbasis pengukuran drive test dan menjadi referensi perencanaan jaringan serta pengambilan keputusan.

Theoretical Foundation & Analysis Methodology

This Cellular Statistic Management System performs comprehensive network coverage analysis based on rigorous propagation modeling standards and theoretical frameworks established by international telecommunications bodies. The analytical framework comprises:

Scientific Basis

Cost-Hata Propagation Model: Industry-standard empirical path loss model validated across cellular frequency bands (800–2600 MHz), incorporating terrain morphology and clutter categorization per ITU recommendations.
ITU-R Recommendations: Propagation models (P.1546-5, P.1812-4) providing deterministic and statistical coverage prediction methodologies aligned with 3GPP standardized site-planning procedures.
3GPP Technical Specifications: Coverage and capacity planning tools (3GPP TS 36.942 for LTE, 3GPP TS 38.901 for 5NR) defining link budget calculations, cell-edge thresholds, and inter-cell interference coordination.
Measurement-Based Validation: Drive-test data correlation (RSRP, RSRQ, SINR measurements) against theoretical predictions to calibrate models and identify planning-reality misalignments.

Analytical Limitations & Inherent Uncertainties

Despite rigorous modeling standards, predictive coverage values are subject to significant deviations from actual in-field conditions. This variance stems from complex multifactorial radio-propagation phenomena:

Primary Deviation Sources

Terrain & Morphology: High-resolution digital elevation models may not capture micro-topography, urban canyon effects, or transient obstacles (construction, vegetation growth). Clutter databases require continuous updates.
Environmental Factors: Weather-dependent attenuation (rain-induced absorption at higher frequencies), seasonal foliage density variations, and dynamic urban landscape changes introduce non-deterministic path losses.
User Equipment (UE) Variability: Device-specific antenna patterns, tuning efficiency, modem implementation variations, and user handling practices (grip/shielding) cause 3–8 dB measurement variance independent of network performance.
Propagation Anomalies: Atmospheric ducting, diffraction complexities in dense urban areas, multipath fading patterns, and interference from adjacent operators create localized prediction errors ±15 dB in worst-case scenarios.
Temporal Dynamics: Network congestion, cell load fluctuations, handover overhead, and inter-cell interference variations produce time-dependent performance degradation not captured in quasi-static models.
Data Quality & Sampling Bias: Drive-test route selection may not uniformly sample geographic regions; sparse measurements in rural areas introduce statistical uncertainty; measurement timing coincides with specific traffic profiles.

Recommended Application Framework

This system's outputs are analytical decision-support tools, not absolute performance predictors. Responsible deployment practices mandate:

Validation Through Measurement: Systematic drive-test campaigns in target deployment areas (minimum 3–5 km per sub-district) to establish baseline coverage signatures and validate theoretical predictions within ±5 dB confidence intervals.
Multi-Stakeholder Collaboration: Cross-functional engagement involving RF Planning engineers, Field Operations teams, Regulatory Affairs specialists, and Real Estate divisions to harmonize network planning with infrastructure constraints and regulatory mandates.
Iterative Refinement: Deploy network interventions (new sites, parameter optimization, spectrum refarming) and conduct post-implementation measurement audits to quantify actual improvement and recalibrate predictive models.
Scenario Analysis: Utilize Monte Carlo simulations and sensitivity analyses to quantify confidence intervals around central predictions, establishing acceptable risk thresholds for business-critical deployments.
Regulatory Compliance: Ensure all planning outputs satisfy national frequency allocation policies, environmental impact assessments, and operator licensing obligations before implementation approval.
Documentation & Traceability: Maintain audit trails recording model versions, input datasets, propagation parameters, and assumption changes to enable transparent reproducibility and accountability.

Disclaimer: This system is provided for strategic planning support only. Operators remain solely responsible for independent validation, regulatory compliance, and performance accountability. The developers disclaim liability for inaccuracies, omissions, or consequential losses arising from reliance on system outputs without independent verification.