A · 概述
COUNTDOWN TO POLLING DAY

沙巴 PRN 2026

1 August 2026 · 73 DUN Seats · Majority 37

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~1,784,843 registered voters · Dissolved 5 June 2026

Net Δ (Before → 预测)
PRN 状态
00 Days
:
00 小时
:
00 Mins
:
00 Secs

🏛 Before vs 预测 Gabungan

Kiri = komposisi semasa / pra-bubar. Kanan = unjuran (purata senario berwajaran) bukan salinan data semasa.

SEBELUM / BEFORE (pre-dissolution)

73
总计 Seats
37
所需多数席位
1,784,843
Registered Voters
7
Battleground Seats

UNJURAN GABUNGAN (scenario-weighted)

🎯 PATH TO MAJORITY

Seats short of state majority and swing seats needed (approx.)

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🧩 OTHER / East 马来西亚 parties (raw)

B · Map & Fight

🗺 DUN SEAT MAP 73 CONSTITUENCIES

73

🧩 STATE CONTROL MAP

Projected bloc control by DUN seat click a tile for details

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⚔ MAJORITY WAR ROOM 37 SEATS TO GOVERN

C · 实时 Pulse

🔴 实时 RESULTS CENTER

STANDBY

实时 DUN seat declarations on polling day · 演示: ?demo=实时

加载中...

📡 新闻 SENTIMENT RADAR

📰 ELECTION 新闻 FEED

实时 RSS

马来语 Mail · Bernama · BM sentiment scoring

D · Methods

🎯 NEURALOPS PROJECTIONS 方法 1: 场景

模型: 40% PRN2023 + 25% GE15 + 20% sentiment + 10% demographics + 5% campaign

🎲 MONTE CARLO SIMULATION 方法 2：蒙特卡洛

50,000 trial runs across 73 seats · majority probability distribution

运行中 simulation...

🧪 GPT REGRESSION SIMULATION LAB 方法 3: GPT 回归

GPT labelled

Multiple regression-style stress tests across turnout, youth, rural, sentiment and transfer variables

🎛 SIMULATION CONTROLS

Adjust 实时 assumptions, then Monte Carlo and GPT regression will recalculate.

货币对 stress under uniform seat shock
−5% 基础 +5%
E · 综合

📊 SIMULATION REMARKS 共识

综合所有预测方法与媒体情绪得出的精细分析

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📜 ELECTION HISTORY