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All Journal Communication in Biomathematical Sciences Innovative: Journal Of Social Science Research
G.K. GANDHIADI
Faculty of Mathematics and Natural Sciences, Udayana University
Humanities Computer Science & IT Law, Crime, Criminology & Criminal Justice Public Health Social Sciences Other

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Perbandingan Antara Latent Root Regression dan Ridge Regression dalam Mengatasi Multikolinearitas Candra W, Putu Ariesta; Gde Sukarsa, I Komang; Gandhiadi, G.K.
Innovative: Journal Of Social Science Research Vol. 4 No. 1 (2024): Innovative: Journal Of Social Science Research
Publisher : Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/innovative.v4i1.8893

Abstract

Analisis regresi adalah metode yang digunakan untuk mengetahui pengaruh variabel independen terhadap variabel dependen. Model regresi dianggap baik ketika asumsi model regresi telah terpenuhi. Salah satu asumsi yang harus dipenuhi dalam analisis regresi linier berganda adalah multikolinearitas. Multikolinearitas terjadi ketika ada hubungan sempurna antara variabel independen. Multikolinearitas dapat dideteksi dengan melihat nilai faktor inflasi varians (VIF) yang lebih besar dari 10. Ada beberapa metode yang dapat digunakan untuk mengatasi masalah multikolinearitas, antara lain latent root regression dan ridge regression. Regresi akar laten dapat mengatasi multikolinearitas dengan lebih baik daripada regresi ridge dengan membandingkan nilai VIF karena menghasilkan nilai VIF sama dengan 1.
Optimal Control Strategies for the Population Management of the Bali Starling: A Mathematical Modeling Approach Gandhiadi, G.K.; Tastrawati, N.K.; Gautama, P.W.; Dharmawan, K.
Communication in Biomathematical Sciences Vol. 8 No. 2 (2025)
Publisher : The Indonesian Bio-Mathematical Society

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5614/cbms.2025.8.2.3

Abstract

The Bali Starling (Leucopsar rothschildi), an endemic species of Bali, faces severe threats from habitat loss, poaching, and environmental changes, necessitating effective conservation strategies. This study presents a mathematical model to describe the population dynamics of the Bali Starling within the breeding center at USS Tegal Bunder, TNBB, integrating optimal control theory to improve conservation efforts. The model incorporates key biological factors such as growth, transfer, and habituation processes, and utilizes Pontryagin’s Maximum Principle to determine an optimal control strategy that balances population sustainability with resource efficiency. Numerical simulations compare controlled and uncontrolled scenarios, highlighting the impact of different control cost weights (q) on population management. The results suggest that moderate control interventions (q = 0.06 − 0.10) are most effective, ensuring sustainable population growth while min- imizing intervention costs. These findings provide valuable insights for optimizing captive breeding programs and offer a scientific basis for adaptive conservation strategies to protect endangered species like the Bali Starling.
Co-Authors Candra W, Putu Ariesta Gautama, P.W. Gde Sukarsa, I Komang Komang Dharmawan Tastrawati, N.K.