FATHAHILLAH, MUHAMMAD (2026) SISTEM PREDIKSI HARGA JUAL AYAM BROILER MENGGUNAKAN REGRESI LINEAR BERGANDA BERBASIS WEB. S1 thesis, Universitas Mercu Buana Jakarta.
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Abstract
The selling price of chicken is a crucial component of the poultry industry, often subject to instability due to fluctuations in production factors. Changes in feed prices, variations in production volume, and reseller demand dynamics directly impact market selling prices, making it difficult for farms to determine appropriate and profitable pricing. This study aims to develop a web-based broiler chicken selling price prediction system by applying a multiple linear regression algorithm to three independent variables—feed price (X1), production volume (X2), and reseller demand (X3)—against the dependent variable, chicken selling price (Y). A quantitative approach with a descriptive-predictive design was employed, utilizing 24 months of historical data (January 2023 to December 2024) obtained through direct observation and documentation at a broiler farm. Regression coefficients were estimated using the Ordinary Least Squares (OLS) method, and the model was evaluated using the coefficient of determination (R²), F-test, t-test, Mean Absolute Error (MAE), and Root Mean Square Error (RMSE). The system was developed using the Laravel framework for the backend and MySQL for the database, with system design incorporating Use Case Diagrams, Activity Diagrams, Class Diagrams, and Entity Relationship Diagrams (ERD). The results yielded the regression equation Y = -8,453.21 + 3.72X1 – 1.85X2 + 2.14X3 with an R² of 0.949, indicating that the three independent variables explain 94.9% of the variation in chicken selling prices. The F-test showed a calculated F-value of 124.38 with a significance of 0.000, demonstrating that the model is simultaneously significant. Black-box testing confirmed that all system functions operated according to specifications, and usability testing achieved a user satisfaction score of 4.2 out of 5.0. This system is expected to assist poultry business operators in making more accurate and efficient business decisions. Keywords: Price Prediction, Broiler Chicken, Multiple Linear Regression, Laravel, Web-based System. Harga Jual ayam merupakan salah satu komponen penting dalam industri unggas yang sering mengalami ketidakstabilan akibat fluktuasi faktor produksi. Perubahan harga pakan, variasi kuantitas produksi, dan dinamika permintaan reseller secara langsung memengaruhi harga jual ayam di pasaran, sehingga peternakan sulit menentukan harga jual yang tepat dan menguntungkan. Penelitian ini bertujuan membangun sistem prediksi harga jual ayam broiler berbasis web dengan menerapkan algoritma regresi linear berganda terhadap tiga variabel bebas, yaitu harga pakan (X1), jumlah produksi (X2), dan permintaan reseller (X3), terhadap variabel terikat harga jual ayam (Y). Penelitian menggunakan pendekatan kuantitatif dengan desain deskriptif-prediktif, menggunakan data historis bulanan selama 24 bulan (Januari 2023 sampai Desember 2024) yang diperoleh melalui observasi langsung dan dokumentasi pada peternakan ayam broiler. Estimasi koefisien regresi dilakukan dengan metode Ordinary Least Squares (OLS), dan model dievaluasi menggunakan koefisien determinasi (R²), Uji F, Uji t, Mean Absolute Error (MAE), dan Root Mean Square Error (RMSE). Sistem dikembangkan menggunakan framework Laravel sebagai backend dan MySQL sebagai basis data, dengan perancangan sistem menggunakan Use Case Diagram, Activity Diagram, Sequence Diagram, Class Diagram, dan Entity Relationship Diagram (ERD). Hasil penelitian menunjukan persamaan regresi Y = -8.453,21 + 3,72X1 – 1,85X2 + 2,14X3 dengan koefisien determinasi R² sebesar 0,949, yang berarti ketiga variabel bebas mampu menjelaskan 94,9% variasi harga jual ayam. Hasil Uji F menunjukkan nilai F hitung 124,38 dengan signifikan 0,000, yang membuktikan model signifikan secara simultan. Pengujian Black Box menunjukkan seluruh fungsi sistem berjalan sesuai spesifikasi, dan pengujian usability memperoleh skor kepuasan pengguna 4,2 dari skala 5,0. Sistem ini diharapkan membantu pelaku usaha unggas dalam mengambil keputusan bisnis yang lebih akurat dan efisien. Kata kunci: Prediksi Harga, Ayam Broiler, Regresi Linear Berganda, Laravel, Sistem Berbasis Web.
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