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All Journal Bioma : Berkala Ilmiah Biologi Jurnal Penelitian Kelapa Sawit Jurnal Teknik Pertanian Lampung (Journal of Agricultural Engineering)
Primananda, Septa
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Agriculture, Biological Sciences & Forestry Education Engineering

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A Study on Barn Owl Population (Tyto alba var. javanica) in Reducing Rat Attacks and Parthenocarpy in Oil Palm Fresh Fruit Bunches Budihardjo, Kadarwati; Wirianata, Herry; Primananda, Septa
Bioma : Berkala Ilmiah Biologi Vol. 21, No 2, Tahun 2019
Publisher : Departemen Biologi, Fakultas Sains dan Matematika, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (529.548 KB) | DOI: 10.14710/bioma.21.2.100-105

Abstract

In mature oil palms, rat attacks fruit bunches, causing significantly reduction in the potential yield and the quality of oil palm fruit bunches. Rat is also known to consume the post anthesis male flowers which act as the breeding sites for the eggs and larvae of Elaeidobius kamerunicus pollinator beetle. Indirectly, the pollinator beetle population can be reduced in high rat infestation area, affecting the pollination and increasing the percentage of parthenocarpic fruit bunches. The barn owl (Tyto alba var. javanica) is a rat biological control agent in the oil palm plantations. The study conducted at PT. Mustika Sembuluh in Central Borneo shows that barn owl (T. alba) population is significantly correlated with both rat attacks and parthenocarpic percentage of oil palm fruit bunches in oil palm plantation
Analisis Perilaku Air Di Perkebunan Kelapa Sawit Pada Tanah Spodosol dan Ultisol Menggunakan Soil Moisture Content Monitoring System (SMCMS) Sukarman, Sukarman; Sutiarso, Lilik; Suwardi, Suwardi; Wirianata, Herry; Prima Nugroho, Andri; Primananda, Septa; Syarovy, Muhdan; Pradiko, Iput; Hijri Darlan, Nuzul
Jurnal Penelitian Kelapa Sawit Vol 32 No 1 (2024): Jurnal Penelitian Kelapa Sawit
Publisher : Pusat Penelitian Kelapa Sawit

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22302/iopri.jur.jpks.v32i1.270

Abstract

Ketersediaan air merupakan aspek yang sangat penting agar kelapa sawit dapat tumbuh dan berproduksi secara optimal. Tujuan penelitian ini adalah untuk menganalisis perilaku air melalui monitoring dinamika kelembaban dan suhu tanah menggunakan Soil Moisture Content Monitoring System (SMCMS). SMCMS terdiri atas sensor yang dipasang di lapangan dan sistem monitoring berbasis internet. SMCMS dipasang di perkebunan kelapa sawit pada tanah Ultisol (A), Spodosol dengan perlakuan pecah hardpan dan mounding (B), dan Spodosol tanpa perlakuan (C). Sensor kelembaban dan suhu tanah dipasang pada tiga kedalaman yang berbeda. Hasil menunjukkan bahwa SMCMS dapat beroperasi secara otomatis dan real-time dalam mengukur perilaku air. Berdasarkan hasil monitoring dan pengukuran, dapat diketahui bahwa kelembaban tanah tertinggi terdapat pada lokasi A dengan rerata 46,91%, kemudian diikuti lokasi B 38,40%, dan C yaitu 29,49%. Spodosol dengan perlakuan (B) memiliki suhu tanah terendah dengan rerata 27,36°C, kemudian diikuti Ultisol (A) 27,58°C, dan Spodosol kontrol (C) 28,40°C. Lebih lanjut, kelembaban tanah berkorelasi lemah dengan suhu tanah. Suhu tanah memiliki korelasi yang lemah dengan suhu udara. Sementara itu, kedua perilaku air tanah tersebut memiliki korelasi yang sangat lemah dengan variabel lingkungan, khususnya curah hujan.
The Prediction of Nitrogen, Phosphate, and Potassium Contents of Oil Palm Leaf Using Hand-Held Spectrometer Hariadi, Badi; Sastrohartono, Hermantoro; Krisdiarto, Andreas Wahyu; Sukarman, Sukarman; Primananda, Septa; Sagoro, Tri Haryo
Jurnal Teknik Pertanian Lampung (Journal of Agricultural Engineering) Vol. 13 No. 1 (2024): March 2024
Publisher : The University of Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jtep-l.v13i1.71-81

Abstract

A hand-held spectrometer can be used to evaluate oil palm (Elaeis guineensis Jacq.) leaf nutrient contents without being destructive. This study aims to develop regression equations and analyze the performance of the prediction models for Nitrogen, Phosphate, and Potassium leaf nutrient contents. The dependent variable in this study was the result of the analysis of nutrient contents in frond number 17 which was carried out in the laboratory, while the independent variable was the leaf reflectance value scanned with a hand-held spectrometer. The Normalized Difference approach is used to create a vegetation index from the combination of reflectance values at two wavelengths. Vegetation index with the highest correlation value to the nutrient content of leaves, is used to make a prediction model for leaf nutrients using the Simple Linear Regression. The regression equations formed to predict the contents of nutrients N, P, and K have high R2. The RMSE values of the predicted contents of N, P, and K nutrients, respectively were 0.21, 0.01, and 0.13; and correctness values of those nutrients respectively were 93.29%, 95.5%, and 88.81%. Keywords:  Hand-held spectrometer,  Oil palm,  Prediction,  Leaf nutrients contents.  
The Use of the Normalized Difference Red Edge (NDRE) Vegetation Index from Multispectral Cameras Mounted on Unmanned Aerial Vehicle to Estimate the Nutrient Content in Oil Palm Leaves Hariadi, Badi; Sastrohartono, Hermantoro; Krisdiarto, Andreas Wahyu; Sukarman, Sukarman; Sagoro, Tri Haryo; Primananda, Septa; Akbar, Arief Rahmad Maulana; Uktoro, Arief Ika
Jurnal Teknik Pertanian Lampung (Journal of Agricultural Engineering) Vol. 13 No. 4 (2024): December 2024
Publisher : The University of Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jtep-l.v13i4.1051-1063

Abstract

This study aimed to develop a prediction model for the nutrient content of N, P, K, Mg, and Ca in oil palm leaves using the Normalized Difference RedEdge (NDRE) vegetation index derived from multispectral camera data. Data acquisition was carried out by an unmanned aerial vehicle (UAV), which was correlated to leaf sample analysis of the 17th frond number. Results showed that simple regression analysis successfully represented nutrient content (N, P, K, Mg, and Ca) based on NDRE values. Based on the MAPE and Correctness values, the nutrient content prediction model for N and P yields reliable results, while for K, Mg, and Ca, they are considered good, with Correctness values of 95.5%, 96.6%, 88.8%, 87.3%, and 90.0% for N, P, K, Mg, and Ca, respectively. The study found that the NDRE vegetation index can be used to predict the nutrient content of oil palm leaves with  reliable results in accuracy for N and P, and good accuracy for K, Mg, and Ca. This is a promising finding, as it could lead to the development of a non-destructive and rapid method for monitoring the nutrient status of oil palm trees, with the validation models for N, P, K, Mg, and Ca are yN = 1.1089x - 0.2497, yP = 0.99x + 0.002, yK = 1.204x - 0.1576, yMg = 0.9149x + 0.0183, and yCa = 1.0418x - 0.0218. Keywords: Multispectral Cameras, Oil Palm, Leaf Nutrient Contents, Prediction.
Co-Authors Akbar, Arief Rahmad Maulana Budihardjo, Kadarwati Hariadi, Badi Hijri Darlan, Nuzul Krisdiarto, Andreas Wahyu Lilik Sutiarso Muhdan Syarovy Pradiko, Iput Prima Nugroho, Andri Sagoro, Tri Haryo Sastrohartono, Hermantoro Sukarman Sukarman Suwardi Suwardi Uktoro, Arief Ika Wirianata, Herry Wirianata, Herry