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All Journal Jurnal Pendidikan Matematika (JUDIKA EDUCATION) Scientica: Jurnal Ilmiah Sains dan Teknologi
Damanik, Ade Yuri F
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Religion Agriculture, Biological Sciences & Forestry Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Mathematics Social Sciences Other

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Implementasi Algoritma Haar Cascade untuk Deteksi dan Penghitungan Kendaraan pada Pengolahan Citra Damanik, Ade Yuri F; Yudistira, Dimas; Algifahri, Muhammad Dzar
Scientica: Jurnal Ilmiah Sains dan Teknologi Vol. 3 No. 1 (2024): Scientica: Jurnal Ilmiah Sains dan Teknologi
Publisher : Komunitas Menulis dan Meneliti (Kolibi)

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Abstract

Peningkatan jumlah kendaraan di jalan raya telah menciptakan tantangan besar dalam manajemen lalu lintas. Pengelolaan yang efisien memerlukan sistem yang dapat mendeteksi dan menghitung jumlah kendaraan secara real-time. Algoritma Counter, yang menggabungkan teknik background subtraction dan object tracking, menawarkan solusi potensial untuk tantangan ini. Penelitian ini bertujuan untuk mengimplementasikan dan mengevaluasi efektivitas algoritma tersebut dalam konteks pengolahan citra digital. Hasil penelitian menunjukkan bahwa algoritma Counter mampu mendeteksi dan menghitung kendaraan dengan akurasi tinggi di berbagai kondisi pencahayaan dan kepadatan lalu lintas.
Model Regresi Linier Berganda untuk Peramalan Hasil Panen Kelapa Sawit Damanik, Ade Yuri F; Armansyah, Armansyah
Jurnal Pendidikan Matematika : Judika Education Vol. 8 No. 4 (2025): Jurnal Pendidikan Matematika:Judika Education
Publisher : Institut Penelitian Matematika, Komputer, Keperawatan, Pendidikan dan Ekonomi (IPM2KPE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31539/38c7q867

Abstract

This study aims to forecast oil palm production using a multiple linear regression model by considering the relationships among several independent variables: rainfall , number of productive trees , harvested area , labor , fertilizer use , and a seasonal variable . Using secondary data from the company’s Daily Work Logs (Lembar Kerja Harian/LKH), the study employs the Ordinary Least Squares (OLS) estimator to obtain the coefficient vector. The results show a coefficient of determination  of 65%, indicating that 65% of the variation in production can be explained by the input variables. The findings indicate that rainfall has a negative coefficient (-0.34305) suggesting a non-linear and inconsistent relationship with production levels. Thus, the study concludes that internal plantation factors—such as the number of productive trees play a more dominant role in increasing yield, whereas higher rainfall tends to negatively affect production.   Keywords: Palm Oil Production, Linear Regression, Forecasting, Agricultural Yield, Climatic Influence, Plantation Management.
Co-Authors Algifahri, Muhammad Dzar Armansyah Armansyah Yudistira, Dimas