Efisiensi Teknis Pengelolaan Tanaman Terpadu Padi Sawah di Kabupaten Karanganyar, Provinsi Jawa Tengah

English A way to increase rice productivity and production is to increase efficiency by technological innovation. Integrated Crop Management (ICM) is an approach to improve the efficiency of rice farming by integration of technological components that are applied according to local specific condition. This study aims to analyze technical efficiency and inefficiency of integrated crop management implementation in rice farming. The study was conducted in Jaten Subdistrict, Karanganyar Regency, Central Java Province, in 2017. Primary data was collected from samples of 51 farmers that implemented the ICM and 42 farmers that did not use ICM. Data were analyzed using stochastic frontier production function that was estimated with the Maximum Likelihood Estimation method. The results show that rice farms have been technically efficient in general. The technical efficiency of ICM adopters in the range of 71,41-98,14% with average 94,04%, higher than those of non ICM adopters in the range of 68,50-96,96% with average 91,72%. There is a room for increasing efficiency. Formal education and ICM adoption increase technical efficiency. Farmer's ability to implement PTT can be improved through extension and training programs. Indonesian Salah satu cara untuk meningkatkan produktivitas dan produksi padi adalah dengan meningkatkan efisiensi melalui inovasi teknologi. Pengelolaan Tanaman Terpadu (PTT) merupakan sebuah pendekatan untuk meningkatkan efisiensi usaha tani padi dengan integrasi komponen-komponen teknologi yang diterapkan sesuai spesifik lokasi. Penelitian ini bertujuan untuk menganalisis efisiensi dan sumber inefisiensi teknis pada penerapan PTT usaha tani padi sawah. Penelitian dilakukan di Kecamatan Jaten, Kabupaten Karanganyar, Jawa Tengah, pada 2017. Data primer dikumpulkan dari 51 petani yang menerapkan PTT dan 42 petani yang tidak menerapkan PTT. Analisis data menggunakan fungsi produksi stokastik frontier yang diduga dengan metode Maximum Likelihood Estimation (MLE). Hasil analisis menunjukkan bahwa usaha tani padi sawah umumnya sudah efisien secara teknis. Nilai efisiensi teknis usaha tani dengan penerapan PTT berkisar 71,41-98,14% dengan rata-rata 94,04%, lebih tinggi daripada usaha tani tanpa penerapan PTT yang formal berkisar 68,50-96,96% dengan rata-rata 91,72%. Masih ada peluang untuk meningkatkan efisiensi teknis. Pendidikan dan penerapan PTT berpengaruh positif terhadap efisiensi teknis. Kemampuan petani dalam menerapkan PTT dapat ditingkatkan melalui program penyuluhan dan pelatihan.

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Prediction of modulus of elasticity of UHPC using maximum likelihood estimation method

Structures ◽

10.1016/j.istruc.2021.11.002 ◽

2021 ◽

Author(s):

Ali Alsalman ◽

Rahman Kareem ◽

Canh N. Dang ◽

José R. Martí-Vargas ◽

W. Micah Hale

Keyword(s):

Maximum Likelihood ◽

Maximum Likelihood Estimation ◽

Modulus Of Elasticity ◽

Estimation Method ◽

Likelihood Estimation ◽

Maximum Likelihood Estimation Method

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A Stochastic Model of Stress Evolution in a Bolted Structure in the Presence of a Joint Elastic Piece: Modeling and Parameter Inference

Advances in Materials Science and Engineering ◽

10.1155/2020/9601212 ◽

2020 ◽

Vol 2020 ◽

pp. 1-11

Author(s):

Mohammed Haiek ◽

Youness El Ansari ◽

Nabil Ben Said Amrani ◽

Driss Sarsri

Keyword(s):

Numerical Simulation ◽

Maximum Likelihood ◽

Maximum Likelihood Estimation ◽

Stochastic Model ◽

Estimation Method ◽

Likelihood Estimation ◽

Stress Evolution ◽

Parameter Inference ◽

Maximum Likelihood Estimation Method ◽

Over Time

In this paper, we propose a stochastic model to describe over time the evolution of stress in a bolted mechanical structure depending on different thicknesses of a joint elastic piece. First, the studied structure and the experiment numerical simulation are presented. Next, we validate statistically our proposed stochastic model, and we use the maximum likelihood estimation method based on Euler–Maruyama scheme to estimate the parameters of this model. Thereafter, we use the estimated model to compare the stresses, the peak times, and extinction times for different thicknesses of the elastic piece. Some numerical simulations are carried out to illustrate different results.

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Calibration of MEMS Triaxial Accelerometers Based on the Maximum Likelihood Estimation Method

Mathematical Problems in Engineering ◽

10.1155/2020/4617365 ◽

2020 ◽

Vol 2020 ◽

pp. 1-10

Author(s):

Yifan Sun ◽

Xiang Xu

Keyword(s):

Maximum Likelihood ◽

Maximum Likelihood Estimation ◽

Random Noise ◽

Estimation Method ◽

Likelihood Estimation ◽

Least Square ◽

Triaxial Accelerometer ◽

Zero Bias ◽

Estimation Function ◽

Maximum Likelihood Estimation Method

As a widely used inertial device, a MEMS triaxial accelerometer has zero-bias error, nonorthogonal error, and scale-factor error due to technical defects. Raw readings without calibration might seriously affect the accuracy of inertial navigation system. Therefore, it is necessary to conduct calibration processing before using a MEMS triaxial accelerometer. This paper presents a MEMS triaxial accelerometer calibration method based on the maximum likelihood estimation method. The error of the MEMS triaxial accelerometer comes into question, and the optimal estimation function is established. The calibration parameters are obtained by the Newton iteration method, which is more efficient and accurate. Compared with the least square method, which estimates the parameters of the suboptimal estimation function established under the condition of assuming that the mean of the random noise is zero, the parameters calibrated by the maximum likelihood estimation method are more accurate and stable. Moreover, the proposed method has low computation, which is more functional. Simulation and experimental results using the consumer low-cost MEMS triaxial accelerometer are presented to support the abovementioned superiorities of the maximum likelihood estimation method. The proposed method has the potential to be applied to other triaxial inertial sensors.

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