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I Dewa Made Subrata
Departemen Teknik Mesin Dan Biosistem, Fakultas Teknologi Pertanian, Institut Pertanian Bogor, Jl. Raya Darmaga Kampus IPB Darmaga, Bogor 16680
Agriculture, Biological Sciences & Forestry Computer Science & IT Education Energy Engineering Environmental Science Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mechanical Engineering Social Sciences Other

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Performance Enhancement of Microbial Fuel Cells from Fishery Wastewater Using Boost Converter Device Ibrahim, Bustami; Uju; Subrata, I Dewa Made; Ramadhan, Rahmat Agung
Coastal and Ocean Journal (COJ) Vol 8 No 2 (2024): COJ (Coastal and Ocean Journal)
Publisher : Pusat Kajian Sumberdaya Pesisir dan Lautan IPB

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/coj.v8i2.55742

Abstract

Electricity is a basic necessity in everyday life. Fossil energy is typically used to generate electricity, and non-renewable energy sources will eventually be depleted without innovation in the form of renewable energy. Liquid waste from fisheries is a commodity that can generate electricity through Microbial Fuel Cell (MFC) systems. However, the electricity generated is relatively small. The research aimed to increase the electrical voltage from fish curing waste in a Microbial Fuel Cell system by using an additional boost converter circuit. The research was conducted using 5 MFC systems connected in series and connected to a boost converter device. The electrical values of the MFC system with the boost converter circuit were a voltage of 12.13±0.87 V, a current of 0.86±0.20 mA, and a power of 10.50±3.11 mW. Meanwhile, without the boost converter circuit, the voltage value was 2.24±0.26 volts, the current was 0.17±0.03 mA, and the power was 0.38±0.11 mW. The increase in electricity in the MFC system indicated that the boost converter circuit functioned properly. The MFC system was able to reduce BOD, COD, and TAN values.
Application of Stereo Vision to Control the Movement of the Robot Arm Towards the Position of Red Chilies I Dewa Made Subrata; Ahmad Dzaky Baiquni
Jurnal Teknik Pertanian Lampung (Journal of Agricultural Engineering) Vol 13, No 3 (2024): September 2024
Publisher : The University of Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jtep-l.v13i3.615-627

Abstract

The trend of decreasing young workers in the agricultural sector needs to be anticipated by developing intelligent machines known as agricultural robots. This research aims to apply a stereo vision system to control the movement of the robot's grip towards the 3D position of the red chili fruit. The stereo vision system installed on the robot waist (joint-2) is used to capture plant images and process them using HSV masking filters and triangulation principal to obtain the 3D center point position of the fruit. The robot joint movement is calculated using geometric based inverse kinematics. The research results show that the average accuracy of the stereo vision system is 93.9 %. The average grip positioning accuracy is 95.6 % to the actual chili fruit position and 98.5 % to the stereo vision calculation value. The average stability of the stereo vision values is 99.5 %, while the average positioning stability of the robot's grip is 99.6 %. Time consumption for image processing is 0.053 s while time consumption for robot grip movement is 9 s. Therefore, the stereo vision system can be used to control robot's grip movement with a good accuracy. Keywords: Red chili fruit, Robot arm, Stereo vision, Three-dimensional position.
Rancangan pencampuran nutrisi otomatis intermitten pada budidaya melon sistem Dutch Bucket untuk urban farming Subrata, I Dewa Made
Jurnal Ilmiah Rekayasa Pertanian dan Biosistem Vol 13 No 1 (2025): Jurnal Ilmiah Rekayasa Pertanian dan Biosistem
Publisher : Fakultas Teknologi Pangan & Agroindustri (Fatepa) Universitas Mataram dan Perhimpunan Teknik Pertanian (PERTETA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jrpb.v13i1.1156

Abstract

This research aims to design an automatic nutrient mixing system for urban farming Dutch Bucket melon cultivation. The process of mixing nutrients for dutch bucket fertigation system begins by measuring the water level in the tank, then the raw water is flowed into the reservoir until it reaches the maximum height according to the set point. Next, the peristaltic pump is turned on for 300 ms and turned off for 2 s to supply A and B nutrient concentrations alternately until the TDS sensor reaches the set point value. The mixed nutrient solution is circulated continuously into the Dutch bucket and the nutrient runoff from theDutch bucket is flowed back into the reservoir. The research results show that the TDS sensor calibration has a root mean square error (RMSE) value of 28 ppm, the average sensor reliability error is 31,5 ppm and the maximum error is 87,4 ppm from three repetitions under the same conditions. The time required for mixing Aand B nutrient concentrations is 3 minutes. The average nutrient flow rate through the emitter pipe is 7,3 ml/s. The TDS sensor reading values are displayed on the LCD screen and also sent to the ThingSpeak cloud for monitoring purposes. Theoverall test results provide the conclusion that the designed dutch bucket nutrient mixing and fertigation system is able to work well in melon cultivation for urban farming.
PENGENDALIAN MANIPULATOR ROBOT PEMANEN BUAH DALAM GREENHOUSE MENGGUNAKAN LABVIEW Sutisna, Setya Permana; Subrata, I Dewa Made
AME (Aplikasi Mekanika dan Energi): Jurnal Ilmiah Teknik Mesin Vol. 2 No. 1 (2016)
Publisher : Universitas Ibn Khaldun Bogor

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (167.028 KB) | DOI: 10.32832/ame.v2i1.320

Abstract

Peningkatan kebutuhan pangan tidak hanya pada jumlah melainkan kualitas. Untuk menjaga kualitas buah hasil produksi pertanian diperlukan kegiatan pemanenan pada tingkat kematangan yang merata. Umumnya tingkat kematangan buah dalam suatu pohon tidak merata sehingga diperlukan pemanenan yang selektif. Pemanenan dengan tenaga manusia seringkali menghasilkan buah yang dipanen tidak matang secara merata, oleh karena itu dibutuhkan suatu alat yang mampu melakukan pemanenan secara selektif. Robot pemanen diharapkan mampu memanen secara selektif sehingga dieroleh hasil pemanenan dengan tingkat kematangan yang merata. Salah satu bagian terpenting dalam kesuksesan pada suatu robot pemanen adalah manipulator. Fungsi manipulator yaitu untuk memposisikan end-effector untuk menjangkau target buah yang akan dipanen. Kesalahan dalam menjangkau target dapat menyebabkan kegalalan robot dalam memanen. Pengendalian pergerakan manipulator menggunakan pemrograman LabView dengan Ni-Daq 6009 untuk menghubungkan manipulator ke perangkat komputer. Pengujian dilakukan dengan mengukur besar simpangan ujung manipulator terhadap koordinat target. Manipulator telah berhasil dibuat dengan tiga derajat bebas yang terdiri dari dua rotational joint (joint 1 dan joint 2) serta satu perismatic joint (joint 3). Rata-rata simpangan manipulator pengujian tanpa beban sumbu x 13.85 mm dengan ketepatan 95.70 %, sumbu y 15.05 mm dengan ketepatan 92.31 %, dan sumbu z 3.2 mm dengan ketepatan 99.42%.
Robot Kartesian Dua Dimensi untuk Penerapan Pestisida Nabati pada Budidaya Sayuran Hidroponik Vertikultur Subrata, I Dewa Made
Teknotan: Jurnal Industri Teknologi Pertanian Vol 19, No 2 (2025): TEKNOTAN, Agustus 2025
Publisher : Fakultas Teknologi Industri Pertanian

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24198/jt.vol19n2.12

Abstract

Budidaya sayuran secara hidroponik memiliki kemungkinan yang sama untuk terserang Organisme Pengganggu Tanaman (OPT) sehingga perlu penerapan pestisida. Pestisida kimia yang diterapkan selama ini cenderung mencemari lingkungan maupun mengganggu kesehatan operator penyemprot oleh karena itu perlu diterapkan pestisida yang lebih ramah lingkungan dengan cara yang lebih aman. Tujuan dari penelitian ini adalah untuk menerapkan manipulator robot tipe kartesian dua dimensi sebagai penyemprot pestisida nabati pada budidaya sayuran hidroponik vertikultur. Manipulator memiliki dua mekanisme geser yang satu bergerak pada rel horizontal dan yang lain bergerak pada rel vertical.  Rel vertical dipasang pada mekanisme geser horizontal. Dua batang nosel yang masing masing berisi tiga kepala nosel dipasang pada rel vertical manipulator sehingga batang nosel bisa digerakkan dalam arah horizontal. Batang nosel diposisikan di atas tanaman sayuran dengan kepala nosel menghadap ke bawah untuk menyemprotkan cairan pestisida nabati ke arah sayuran tiga kali seminggu. Konsentrat pestisida nabati yang digunakan terbuat dari bahan bawang putih, bawang merah, kunyit dan air abu gosok. Hasil pengujian menunjukkan bahwa robot mampu menggerakkan nosel sepanjang pipa hidroponik dengan ketelitian 2,1 mm. Nosel mampu menyemprotkan pestisida nabati dengan rataan debit 7,8 ml/detik dan dengan keseragaman 91 % pada nilai siklus kerja PWM pengendali pompa 98,04 %. Lama penyemprotan untuk luasan 3,73 m2 adalah 16,02 detik. Kapasitas lapang efektif robot adalah 0.072 ha/jam. Penerapan robot penyemprot pestisida nabati otomatis ini mampu mengurangi kerusakan tanaman sayuran akibat serangan OPT.
Macro-Nutrient Prediction of Paddy Field Soil Using Artificial Neural Network and NIR Spectroscopy Ahmad, Usman; Budiastra, I Wayan; Subrata, I Dewa Made; Firdaus, Jonni
Jurnal Keteknikan Pertanian Vol. 12 No. 2 (2024): Jurnal Keteknikan Pertanian
Publisher : PERTETA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19028/jtep.012.2.242-258

Abstract

Understanding soil fertility, influenced by macronutrients like nitrogen, phosphorus, and potassium, is essential for adaptive agriculture implementation based on various soil conditions. Near-infrared spectroscopy technology provides non-destructive, rapid soil property measurements without chemicals, applicable both in-field and in-laboratory. However, the wide NIR spectrum range and neural network complexities can hinder Artificial Neural Network (ANN) training and inference, leading to time and resource inefficiency, especially without sophisticated computing devices. This study examines data reduction methods to enhance ANN performance in predicting soil macronutrients using NIR spectra. Multiple Linear Regression (MLR) and Principal Component Analysis (PCA) were applied to select wavelengths from the 1000–2500 nm for ANN input, comparing their performance. About 237 NIR reflectance data from paddy soil were transformed into absorbance data. MLR used forward selection to identify wavelengths with correlations higher than 0.9, while PCA selected wavelengths corresponding to the loading factor peaks for each principal component. These selected wavelengths served as inputs for the ANN model. The ANN’s performance was assessed using correlation and determination coefficients, RMSE, RPD, and model consistency. For nitrogen, the PCA+ANN model with reflectance spectra performed better (RPD 2.4-4.8) than the MLR+ANN model (RPD 2.2-2.6) using fewer wavelengths (5-9 for PCA+ANN vs. 9-12 for MLR+ANN). For phosphorus estimation, the PCA+ANN model also excelled (RPD 2.3-7.0 vs. 2.3-2.4) with fewer wavelengths (4-7 vs. 7). For potassium estimation, the PCA+ANN model showed superior performance (RPD 4.3-9.5 vs. 4.2-4.4), using the same number of wavelengths (4-8 vs. 4-6).
Development of Microalgae Growth Monitoring System Using TSD-10 Sensor and ThingSpeak Platform Subrata, I Dewa Made; Novrizal, Mulki Azmi
Jurnal Teknik Pertanian Lampung (Journal of Agricultural Engineering) Vol. 13 No. 2 (2024): June 2024
Publisher : The University of Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jtep-l.v13i2.394-404

Abstract

Microalgae chlorella sp. is one of the low-level plants that has many benefits and need to be harvested when they have reached optimum density. This study aims to develop a microalgae density monitoring system using the TSD-10 sensor and the ThingSpeak platform. The output voltage from the TSD-10 sensor was calibrated into microalgae density using hemocytometer and then sent wirelessly to the ThingSpeak cloud server using the ESP8266 module. A linear equation of y = –1.633 x +1421.3 was obtained from the calibration process where y is microalgae density (cell/ml) and x is analog to digital conversion (ADC) value of the TSD-10 sensor. The determination coefficient of the calibration and validation process is 0.9921 and 0.938 respectively. The measurement stability was quite good with a standard deviation ranging from 1.15×104 cell/ml to 2×104 cells/ml of culture medium. The measurement accuracy of the validation process using the RMSE (Root Mean Square Error) formula is 3.25. The time response of the sensor after power on is 5.85 s and the time it takes to display data on the ThingSpeak cloud is 16.03 s. Thus the measuring instrument developed can be said to have a fairly good performance. Keywords: Density monitoring, Microalgae, ThingSpeak platform, Tsd-10 sensor.
Application of Stereo Vision to Control the Movement of the Robot Arm Towards the Position of Red Chilies Subrata, I Dewa Made; Baiquni, Ahmad Dzaky
Jurnal Teknik Pertanian Lampung (Journal of Agricultural Engineering) Vol. 13 No. 3 (2024): September 2024
Publisher : The University of Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jtep-l.v13i3.615-627

Abstract

The trend of decreasing young workers in the agricultural sector needs to be anticipated by developing intelligent machines known as agricultural robots. This research aims to apply a stereo vision system to control the movement of the robot's grip towards the 3D position of the red chili fruit. The stereo vision system installed on the robot waist (joint-2) is used to capture plant images and process them using HSV masking filters and triangulation principal to obtain the 3D center point position of the fruit. The robot joint movement is calculated using geometric based inverse kinematics. The research results show that the average accuracy of the stereo vision system is 93.9 %. The average grip positioning accuracy is 95.6 % to the actual chili fruit position and 98.5 % to the stereo vision calculation value. The average stability of the stereo vision values is 99.5 %, while the average positioning stability of the robot's grip is 99.6 %. Time consumption for image processing is 0.053 s while time consumption for robot grip movement is 9 s. Therefore, the stereo vision system can be used to control robot's grip movement with a good accuracy. Keywords: Red chili fruit, Robot arm, Stereo vision, Three-dimensional position.
Co-Authors . Dwinanto . Harmen . Suroso Abdul Azis. S Achmad Zurhafidz Ramadhan Agus Sutejo Ahmad Dzaky Baiquni Ajat Zatmika Alimuddin Alimuddin Andreas . Anjar Suprapto Anjar Suprapto, Anjar Anna C. Erungan Arief Sabdo Yuwono Armansyah H. Tambunan Baiquni, Ahmad Dzaky Budi Indra Setiawan Budi Priyonggo Bustami Ibrahim Bustani Ibrahim Danang Suganjar Dedy Wirawan Soedibyo Desrial Edy Hartulistiyoso Fahmi Riadi Fakhrul Irfan Khalil Fuad Chalim Rusdana Husin Alatas I Wayan Astika I Wayan Budiastra Ichsan Nurfitra Jacklyn Melania Joko Prasetyo Joko Sumarsono Jonni Firdaus, Jonni Jusran Jusran Kudang Boro Seminar Lenny Saulia Leopold O. Nelwan Lisyanto . Muhammad Rizal Muhammad Sigit Gunawan Mulki Azmi Novrizal Nakao Nomura Novrizal, Mulki Azmi Okta Danik Nugraheni Pomalingo, Moh Fikri Popi Rejekiningrum Purbakawaca, Rady Radite Praeko A. Setiawan Radite Praeko Agus Setiawan Ramadhan, Rahmat Agung Roh Santoso Budi Waspodo Sam Herodian Satyanto Krido Saptomo Setya Permana Setya Permana Sutisna Sjahrul Annas Steven G. Tunas Suhermanto Agung Wibowo Sumiati Sumiati Suroso . Tineke Mandang Uju Usman Ahmad Wawan Hermawan Wibowo, Suhermanto Agung