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Kabupaten Musi Rawas Utara

City in Sumatera Selatan, Indonesia

Overview

Kabupaten Musi Rawas Utara is a tranquil regency in South Sumatra, Indonesia, renowned for its lush rural scenery, traditional markets, and serene river landscapes. It provides a glimpse into authentic Sumatran life, away from major tourist routes.

Geographic Context

Jurisdiction
Indonesia
Province
Sumatera Selatan
Population
—
Time Zone
Asia/Jakarta
Coordinates
-2.49°, 103.29°

Key Metrics

Safety Score · estimate
60
Female Safety
45
LGBTQ+ Safety
30
Traffic Safety
40
Food Safety
55
Monthly Cost · estimate
$317
Local Cost
$205
Local Income
$150
Cashless
35
English
25
Temperature
26.1°C
Summer Avg
25.9°C
Winter Avg
25.9°C
Record High
34.2°C
Record Low
18.3°C
Humidity
87%
Precipitation
2376 mm
City Vibrancy
—
Coworking
0
Cafes
0
Nightlife
0
Parks
0
Transport
0
Walk Score
0
Footways
—
Airport
MJY
Distance
41 km

Data sources

Source-backed data

World Air Quality Index - Latest available city-level air quality station measurement. Record updated 2025-12-05.
OpenStreetMap - Nearby amenities counted from OpenStreetMap-derived city extracts. Record updated 2025-12-09.
OpenStreetMap transport extract - Walkability, footway density, and airport access metrics derived from mapped transport features. Record updated 2025-12-06.

Estimates and unverified origins

Oyster List climate data - Climate origins are unverified. Available methods include historical APIs and AI estimates; stored rows do not identify the original dataset, reference period, or model for each value. Treat these summaries as estimates until independently verified. Record updated 2026-03-22.
Oyster List city price estimates - Price origins are unverified. Available generation methods include AI estimates; stored records do not identify a survey, observation period, or model for each price. Record updated 2026-01-14.
Oyster List AI-assisted estimates - Safety, lifestyle, income, and practical scores include model-assisted estimates. Stored records do not identify supporting observations for each score. Model-reported confidence: 60/100; this is not a measured accuracy score. Model: derived+gpt-4.1. Record updated 2026-03-26.

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