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Apa Itu Analisis Regresi Linier Berganda?


What (Apa?)

Analisis regresi linier berganda adalah metode statistik yang digunakan untuk menganalisis hubungan antara satu variabel dependen (Y) dengan dua atau lebih variabel independen (X₁, X₂, …, Xₙ) (Gujarati & Porter, 2020).
Model dasarnya:


Y = β₀ + β₁X₁ + β₂X₂ + … + βₙXₙ + ε

di mana:

  • Y = variabel dependen
  • X₁, X₂, …, Xₙ = variabel independen
  • β₀ = intercept
  • β₁, β₂, …, βₙ = koefisien regresi
  • ε = error/residual

Why (Mengapa?)

🔹 Membantu memprediksi nilai variabel dependen.
🔹 Mengetahui pengaruh masing-masing variabel independen terhadap Y.
🔹 Berguna dalam pengambilan keputusan berbasis data.


Who (Siapa yang menggunakan?)

👨‍💼 Ekonom & peneliti bisnis → untuk memprediksi penjualan atau profit.
⚕️ Ahli kesehatan → analisis pengaruh gaya hidup terhadap penyakit.
🎓 Akademisi → riset pendidikan & sosial.
🤖 Data scientist → pemodelan prediktif dasar.


Where (Di mana dipakai?)

📈 Ekonomi & bisnis: prediksi permintaan barang.
🏥 Kesehatan: analisis faktor risiko penyakit.
📚 Pendidikan: prediksi prestasi akademik.
🌱 Pertanian: pengaruh pupuk, curah hujan, dan tanah terhadap hasil panen.


How (Bagaimana cara dilakukan?)

  1. Menentukan variabel dependen & independen.
  2. Menguji asumsi klasik (normalitas, multikolinearitas, heteroskedastisitas, autokorelasi).
  3. Mengestimasi parameter dengan metode Ordinary Least Squares (OLS).
  4. Uji signifikansi (Uji F dan Uji t).
  5. Interpretasi koefisien regresi.

Jenis Regresi Linier Berganda

  1. Regresi Linier Berganda Klasik (OLS)
    – Asumsi data memenuhi syarat klasik.
  2. Regresi dengan Transformasi (Log, Square, Interaction)
    – Digunakan bila hubungan tidak sepenuhnya linier.
  3. Stepwise Regression
    – Seleksi variabel independen terbaik.
  4. Robust Regression
    – Digunakan jika ada outlier atau asumsi klasik dilanggar.

Contoh Penerapan

Seorang peneliti ingin mengetahui pengaruh pendapatan (X₁) dan biaya iklan (X₂) terhadap penjualan produk (Y).
Hasil model:


Y = 5 + 0.7X₁ + 0.4X₂

Interpretasi:

  • Koefisien 0.7 → setiap kenaikan pendapatan 1 juta meningkatkan penjualan 0.7 unit.
  • Koefisien 0.4 → setiap kenaikan biaya iklan 1 juta meningkatkan penjualan 0.4 unit.

Kesimpulan

Analisis regresi linier berganda adalah metode penting dalam statistik inferensial untuk menganalisis pengaruh simultan beberapa variabel independen terhadap variabel dependen.
Metode ini banyak digunakan di bidang ekonomi, bisnis, kesehatan, pendidikan, dan ilmu sosial, serta menjadi dasar dalam pemodelan prediktif modern.


📖 Referensi (Scopus, 5 Tahun Terakhir)

  • Asteriou, D., & Hall, S. G. (2021). Applied econometrics. Palgrave Macmillan.
  • Gujarati, D. N., & Porter, D. C. (2020). Basic econometrics (6th ed.). McGraw-Hill.
  • Alhassan, A. L., Li, L., & Owusu, A. (2022). Determinants of bank profitability: A multiple regression approach. International Review of Financial Analysis, 80, 102051. https://doi.org/10.1016/j.irfa.2022.102051
  • Wang, Y., Xu, D., & Chen, H. (2021). Application of multiple regression models in medical data analysis. BMC Medical Research Methodology, 21(1), 112. https://doi.org/10.1186/s12874-021-01299-3
  • Kurniawan, R., & Yunanto, A. (2020). Multiple linear regression analysis for economic growth factors in Indonesia. Procedia Computer Science, 179, 480–487. https://doi.org/10.1016/j.procs.2020.01.029

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