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PENGARUH PERUBAHAN TAHUN TERHADAP PRODUKSI PERTANIAN DI INDONESIA MENGGUNAKAN PENDEKATAN REPEATED MEASURES MANOVA Selly Rizkiyah; Indira Zein Rizqin; Milla Akbarany Baktiar Putri; Muhammad Nasrudin; Trimono Trimono
RAGAM: Journal of Statistics & Its Application Vol 4, No 1 (2025): RAGAM: Journal of Statistics & Its Application
Publisher : Universitas Lambung Mangkurat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20527/ragam.v4i1.14970

Abstract

This study aims to analyze significant differences in rice paddy production in Indonesia based on year factors using the Repeated Measures MANOVA method. The data used includes harvest areas, productivity, and total rice production from various provinces during the period 2020-2024.  The results showed that there was a significant relationship between the variables tested, so the independence assumption in the MANOVA method was not met. Therefore, Repeated Measures-MANOVA was used as an alternative approach that is more suitable for repeated data. The analysis showed that there were significant differences in rice production by year, with a p-value of <0.05 in all multivariate statistics. The results highlight the importance of efficient crop land management and increased productivity to support the sustainability of the agricultural sector. The Repeated Measures-MANOVA approach proved effective in identifying variations in production based on time factors and can be a relevant analytical tool.
Optimalisasi Deteksi Wajah Real-Time Menggunakan HAAR Cascade Classifier berbasis OpenCV Alfan Rizaldy Pratama; Muhammad Nasrudin; Andri Faudzan Adziima; Shindi Shella May Wara
JASIEK (Jurnal Aplikasi Sains, Informasi, Elektronika dan Komputer) Vol. 7 No. 1 (2025): Juni 2025
Publisher : Universitas Merdeka Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26905/jasiek.v7i1.15485

Abstract

Nowadays, the face is one of the features that is widely used in various aspects of life such as security which includes access control and surveillance, biometrics which includes attendance systems, and many others. The obstacles found in implementing this are generally about speed performance when detecting, this is vital because if the process takes a long time, misconceptions and system errors will occur. HAAR Cascade Classifier is one of the most widely used lightweight face detection algorithms. In this research, by analyzing the use of grayscale color compared to RGB, a performance increase of 6.17% is obtained with an average FPS on RGB of 25.63 while on grayscale it is 27.21.