Pra-Pemprosesan Data

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"A professional female architect in a modest, stylish outfit (fully clothed), reviewing blueprints at a construction site in Kuala Lumpur. Background includes a modern skyscraper under construction and bustling city life. Safe for work, appropriate content, perfect anatomy, natural proportions, professional, family-friendly, high resolution, realistic rendering."

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Rahsia Kuasai Data Siri Masa: Langkah Pra-Pemprosesan yang Anda Patut Tahu!

2025-07-25

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Dalam dunia analisis data, kita seringkali berhadapan dengan data deret waktu yang kompleks. Bayangkan, data penjualan harian kedai kopi kegemaran ...

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A professional data analyst, fully clothed in a modest baju kurung, analyzing a colorful data visualization (bar chart showing sales trends) on a large monitor in a bright, modern office in Kuala Lumpur. Safe for work, appropriate content, perfect anatomy, natural proportions, professional setting, well-formed hands, proper finger count.

Analisis Data Siri Masa: Rahsia Jimat Masa & Hasil Lebih Padu Anda Mungkin Terlepas Pandang

Rahsia Kuasai Data Siri Masa: Langkah Pra-Pemprosesan yang Anda Patut Tahu!

Bustling Kuala Lumpur Street Scene**

"A vibrant street scene in Kuala Lumpur, Malaysia during the day. Focus on the colorful architecture, people in modest and stylish Malaysian clothing (baju kurung, baju kebaya, batik shirts), street food vendors with their stalls. Ensure the scene feels lively and authentic. Safe for work, appropriate content, fully clothed, professional photography, perfect anatomy, natural proportions, high quality."

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Rahsia Terbongkar: Analisis Data Siri Masa untuk Keputusan Lebih Bijak

**A vibrant visualization of time series data being broken down into its core components: trend (a smooth, upward-sloping line), seasonality (repeating patterns like waves), and residual (scattered noise). Use bright colors and a modern, data-driven aesthetic.**

Rahsia Ramalan Siri Masa: Bongkar Teknik Diskomposisi Untuk Jimat Lebih!

** *A graph showing time series data with missing values, visually represented as gaps in the line, alongside a highlighted segment where imputation is being performed. Focus on visualizing the concept of filling in those gaps.*

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Rahsia Data Bersih: Ramalan Siri Masa Lebih Tepat, Lebih Untung!

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