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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Teknotan: Jurnal Industri Teknologi Pertanian TELKOMNIKA (Telecommunication Computing Electronics and Control) Jurnal Mahasiswa TEUB Journal of Environmental Engineering and Sustainable Technology Jurnal Keteknikan Pertanian Tropis dan Biosistem Jurnal Teknologi Pertanian agriTECH Jurnal Ilmiah Rekayasa Pertanian dan Biosistem Industria: Jurnal Teknologi dan Manajemen Agroindustri Advances in Food Science, Sustainable Agriculture and Agroindustrial Engineering (AFSSAAE) Journal of Robotics and Control (JRC) Insyst : Journal of Intelligent System and Computation Jurnal Abdi Masyarakat Indonesia J-Icon : Jurnal Komputer dan Informatika
Dimas Firmanda Al Riza
University of Brawijaya
Aerospace Engineering Agriculture, Biological Sciences & Forestry Humanities Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Immunology & microbiology Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mechanical Engineering Medicine & Pharmacology Public Health Other

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STUDI EKSPERIMENTAL INKUBATOR TENAGA SURYA TIPE PANEL PELAT DATAR DENGAN EFEK TERMOSIPON Al Riza, Dimas Firmanda; Damayanti, Retno; Izza, Ni'matul
Jurnal Teknologi Pertanian Vol 16, No 3 (2015)
Publisher : Fakultas Teknologi Pertanian Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1612.212 KB)

Abstract

Inkubator telah banyak dimanfaatkan untuk berbagai macam proses seperti penetasan telur dan proses lain yang memerlukan ruang dengan suhu terkendali umumnya pada sekitar 40 °C. Penggunaan inkubator yang relatif lama memerlukan jumlah energi yang cukup besar. Penggunaan energi surya sebagai sumber energi alternatif untuk inkubator akan memberikan hasil berupa penggunaan energi yang lebih murah dan lebih bersih. Pada penelitian ini telah dilakukan studi mengenai potensi pemanfaatan tenaga surya dengan tipe panel pelat datar untuk inkubator. Prinsip aliran fluida alami dengan efek termosipon digunakan untuk meminimalisir penggunaan energi tambahan seperti pompa. Panel surya dapat bekerja dengan baik pada kondisi cuaca normal dengan temperatur maksimum mencapai lebih dari 60 °C. Efek termosipon dapat terjadi dengan perbedaan temperatur minimum sekitar 10 °C. Perbedaan temperatur maksimum yang diamati dari performansi kerja panel surya yakni 22.7 °C. Rekomendasi untuk sistem kontrol dan menajemen energi diberikan berdasarkan fenomena yang diamati dari hasil eksperimen.
Pemodelan Dan Optimasi Sistem Kontrol Pada Multiple Effect Evaporator Dengan Menggunakaan Particle Swarm Optimization Jayalaksono, Anung Nugroho; Argo, Bambang Dwi; Hendrawan, Yusuf; Al Riza, Dimas Firmanda
Jurnal Keteknikan Pertanian Tropis dan Biosistem Vol 3, No 1 (2015)
Publisher : Universitas Brawijaya

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Abstract

Sistem produksi dalam proses industri begitu kompleks, dan dinamis, sehingga proses sering mengalami kondisi yang kurang diharapkan karena kurangnya kemampuan sistem pengendalian dalam menjaga proses. Penelitian ini bertujuan untuk meningkatkan performansi kontrol PID dengan menambahkan faktor bobot inersia untuk meredam kecepatan dalam pencarian titik-titik optimal pada proses penguapan evaporator dan memodelkan evaporatornya. Optimasi parameter tuning kontrol PID menggunakan PSO (Particle Swarm Optimization) diharapkan mampu menangani sistem nonlinier evaporator dengan karakteristik respon undershoot yang sulit ditangani dan memperbaiki respon sistem dengan overshoot, rise time yang cukup lama dan besar. Prosedur perancangan dan simulasi tuning kontrol PID berdasarkan PSO meliputi 2 tahapan. Tahapan 1 pemodelan sistem, dilakukan dengan proses identifikasi berdasarkan data variabel plant pada evaporator. Tahapan yang kedua yaitu perancangan PSO sebagai tuning kontrol PID. Hasil penelitian menunjukkan PSO mampu memberikan peningkatan performansi tuning sistem pengendalian kontrol PID dalam meningkatkan respon sistem pada sistem pengendalian Multiple Effect Evaporator dengan rise time 0.01 detik, overshoot 3.35%, settling time 6.102 detik serta mampu memberikan respon undershoot plant  MEE sebesar 28.11%. Dari analisa dengan metode tuning kontrol PID Ziegler-Nichols dapat dilihat dari segi settling time, overshoot, rise time, dan kesetabilan respon plant MEE, metode tuning kontrol PID dengan PSO mampu memperbaiki respon sistem plant MEE. Dari hasil penerapan pada plant MEE, PSO dengan penambahan bobot inersia w memberikan tuning yang lebih baik dibandingkan  kontrol PID dengan metode Ziegler-Nichols dari kriteria max over shoot, rise time dan settling time sebesar 5.38%, 3.05 detik, 10.1 detik, dibanding metode tuning kontrol PID dengan PSO (3.35%, 0.01 detik, 6.102 detik).   Kata kunci : PSO, PID, Evaporator, MEE, Inersia
Classification of water stress in cultured Sunagoke moss using deep learning Yusuf Hendrawan; Retno Damayanti; Dimas Firmanda Al Riza; Mochamad Bagus Hermanto
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 19, No 5: October 2021
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v19i5.20063

Abstract

Water stress greatly determines plant yield as it affects plant metabolism, photosynthesis rate, chlorophyll content index, number of leaves, physiological, biochemical compound, and vegetative growth. The research aimed to detect and classify water stress of cultured Sunagoke moss into several categories i.e. dry, semi-dry, wet, and soak by using a low-cost commercial visible light camera combined with a deep learning model. Cultured Sunagoke moss is a commercial product which has the potential use as rooftop-greening and wall-greening material. This research compared the performance of four convolutional neural network models, such as SqueezeNet, GoogLeNet, ResNet50, and AlexNet. The best convolutional neural network model according to the training and validation result was ResNet50 with RMSProp optimizer, 30 epoch, and 128 mini-batch size; this also gained an accuracy rate at 87.50%. However, the best result of the convolutional neural network model on data testing using confusion matrices on different data sample was ResNet50 with Adam optimizer, 30 epoch, 128 mini-batch size, and average testing accuracy of 94.15%. It can be concluded that based on the overall results, convolutional neural network model seems promising as a smart irrigation system that real-time, non-destructive, rapid, and precise method when controlling water stress of plants.
PV SYSTEM FOR PHOTOBIOREACTOR SIZING AND EVALUATION USING TRNSYS SIMULATION Bambang Susilo; Dimas Firmanda Al Riza; M Bagus Hermanto; Syed Ihtsham Ul Haq Gilani
Journal of Environmental Engineering and Sustainable Technology Vol 1, No 1 (2014)
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (622.506 KB) | DOI: 10.21776/ub.jeest.2014.001.01.9

Abstract

This paper presents sizing and performance evaluation of a standalone photovoltaic system to supply power of small scale photo-bioreactor system. PSH method is used to determine PV panel and battery capacity, then the sizing results is tested and evaluated using TRNSYS model. The results shows for small scale photobioreactor daily electricity load of 1440 Wh, the PV system requirement is consist of 500 Wp PV panel and 500 Ah battery capacity for 12V system.
Rancang Bangun Fermentor Yogurt dengan Sistem Kontrol Logika Fuzzy Menggunakan Mikrokontroler ATMega32 Dimas Firmanda Al Riza; Retno Damayanti; Yusuf Hendrawan
agriTECH Vol 34, No 4 (2014)
Publisher : Faculty of Agricultural Technology, Universitas Gadjah Mada, Yogyakarta, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (733.041 KB) | DOI: 10.22146/agritech.9441

Abstract

Yogurt is milk fermented product that becomes popular recently. In yogurt processing, fermenter is the main device. Lactobacillus sp. and Streptococcus sp. are two probiotic bacteria species that are common to be used in yogurt fermentation process. Both bacteria grow well in a specific range of temperature between 40-45 C, so temperature control in fermenter operational becomes one of the important things to ensure speed and quality of fermentation process. Fermentation process is a process with high degree of uncertainty and categorized as non-linear time invariant system. Thus, classical control system method is difficult to be implemented. To overcome this issue, intelligent control system can be implemented to yogurt’s fermenter temperature control. One of intelligent control system method that can be implemented is fuzzy logic-based control system. In this study, fuzzy control system has been designed and implemented for fermenter temperature control. Control system algorithm is integrated in ATMega16 (for On-Off logic control) and ATMega32 (for Fuzzy Logic control) microcontrollers. Experimental results of fermenter control system shows that temperature profile of fermenter with fuzzy logic control system is more stable by settling time around an hour and 15 minutes and error average of -0.36 oC. Fermentation process for 16 hours with fuzzy logic controller produce yogurt with pH value of 3.66, total number of Lactobacillus sp. is 4.85 x 10 cfu/mL and Streptococcus sp. is 1.34 x 106 cfu/mL.ABSTRAKYogurt merupakan produk olahan susu terfermentasi yang akhir-akhir ini mulai banyak disukai oleh masyarakat. Pada pengolahan susu menjadi yogurt, fermentor digunakan sebagai alat utama. Lactobacillus sp. dan Streptococcus sp. merupakan dua spesies bakteri yang biasa digunakan dalam proses fermentasi yogurt. Kedua jenis bakteri ini tumbuh dengan baik pada suhu yang spesifik yaitu antara 40–45 C, sehingga pengendalian suhu pada operasi fermentor merupakan hal yang penting agar proses fermentasi dapat berjalan secara cepat dan baik. Proses fermentasi merupakan proses yang memiliki tingkat ketidakpastian yang tinggi dan merupakan sistem non-linear time variant, sehingga desain sistem kontrol klasik akan sulit untuk diterapkan. Untuk mengatasi hal ini sistem kontrol cerdas dapat untuk diimplementasikan pada pengendalian suhu fermentor yogurt. Salah satu dari metode sistem kontrol cerdas yang dapat digunakan adalah sistem kontrol dengan logika fuzzy. Pada penelitian ini telah dilakukan rancang bangun sistem pengendalian suhu berbasis algoritma fuzzy pada fermentor yogurt. Algoritma sistem kendali diintegrasikan dalam mikrokontroler ATMega16 (untuk logika ON-OFF) dan ATMega32 (untuk logika fuzzy). Hasil uji sistem pengendalian suhu fermentor menunjukkan bahwa dengan menggunakan algoritma fuzzy sistem pengendalian lebih stabil dengan settling time selama 1 jam 20 menit dan rata-rata error sebesar -0,36 oC. Proses fermentasi selama 16 jam menggunakan fermentor dengan kontroler fuzzy menghasilkan yogurt dengan pH sebesar 3,66, jumlah mikroba Lactobacillus sp. sebanyak 4,85 x 108cfu/mL, dan Streptococcus sp. sebanyak 1,34 x 10 6 cfu/mL.
Optimasi Dengan Algoritma RSM-CCD Pada Evaporator Vakum Waterjet Dengan Pengendali Suhu Fuzzy Pada Pembuatan Permen Susu Yusuf Hendrawan; Bambang Susilo; Angky Wahyu Putranto; Dimas Firmanda Al Riza; Dewi Maya Maharani; Mutiara Nisa' Amri
agriTECH Vol 36, No 2 (2016)
Publisher : Faculty of Agricultural Technology, Universitas Gadjah Mada, Yogyakarta, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (790.355 KB) | DOI: 10.22146/agritech.12868

Abstract

Milk candy is a product which has to be produced under a high temperature to achieve the caramelization process. The use of vacuum system during a food processing is one of the alternatives to engineer the value of a material’s boiling point. The temperature control system and the mixing speed in machine that produce the milk candy were expected to be able to prevent the formation of off-flavour in the final product. A smart control system based on fuzzy logic was applied in the temperature control within the double jacket vacuum evaporator machine that needs stable temperature in the cooking process. The objective of this research is developing vacuum evaporator for milk candy production using fuzzy temperature control. The result in machine and system planning showed that the process of milk candy production was going on well. The parameter optimization of water content and ash content purposed to acquire the temperature point parameter and mixing speed in milk candy production. The optimization method was response surface methodology (RSM), by using the model of central composite design (CCD). The optimization resulted 90.18oC for the temperature parameter and 512 RPM for the mixing speed, with the prediction about 4.69% of water content and 1.57% of ash content.ABSTRAKPermen susu merupakan salah satu produk yang diolah dengan suhu tinggi untuk mencapai proses karamelisasi. Pengolahan pangan dengan sistem vakum merupakan salah satu alternatif untuk merekayasa nilai titik didih suatu bahan. Sistem pengendalian suhu serta kecepatan pengadukan pada mesin produksi permen susu diharapkan dapat mencegah terbentuknya partikel hitam (off-flavour) pada produk akhir. Sistem kontrol cerdas logika fuzzy diaplikasikan dalam pengendalian suhu pada mesin evaporator vakum double jacket yang membutuhkan tingkat stabilitas suhu pemasakan permen susu. Tujuan dari penelitian ini adalah membuat rancang bangun evaporator vakum pada pembuatan permen susu dengan menggunakan pengendali suhu fuzzy. Hasil perancangan mesin dan sistem menunjukkan bahwa proses produksi permen susu dapat berlangsung dengan baik. Optimasi parameter kadar air dan kadar abu dilakukan untuk mendapatkan titik parameter suhu dan kecepatan pengadukan produksi permen susu yang optimum. Metode optimasi menggunakan response surface methodology (RSM) model central composite design (CCD). Hasil optimasi didapatkan parameter suhu 90,18oC dan kecepatan pengadukan 512 RPM, dengan prediksi produk permen susu memiliki nilai kadar air 4,69% dan kadar abu 1,57%.
Optimization of pulsed electric field processing time and hydrolyzed bovine collagen concentration in pasteurized milk Angky Wahyu Putranto; Anugerah Dany Priyanto; Dimas Firmanda Al Riza; Ferina Tiara Safitri; Nurul Istiqomah Khoirunnisa; Arrahmadiana Estuwilujeng; Candika Pambayun
Advances in Food Science, Sustainable Agriculture and Agroindustrial Engineering (AFSSAAE) Vol 5, No 1 (2022)
Publisher : Advances in Food Science, Sustainable Agriculture and Agroindustrial Engineering (AFSSAAE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/ub.afssaae.2022.005.01.3

Abstract

Milk is a highly perishable food due to its nutritional composition for microbial growth. Improper milk handling practices cause nutritional reduction and microbial contamination in milk. Collagen drinks are currently a growing commercial product. Therefore, this study aimed to determine the effect of hydrolyzed bovine collagen concentration and pulsed electric field (PEF) time on the physical, microbiological, and organoleptic qualities of milk enriched with hydrolyzed bovine collagen, as well as to determine the best treatment. Central composite design (CCD) for Response Surface Methodology (RSM) was used in this experimental design to explore optimal response based on the relationship between collagen concentration and PEF processing time. This CCD experiment was proposed to optimize TPC and viscosity and obtained a total of 13 experimental designs. The model results suggested by RSM-CCD are quadratic models. The result showed the optimization of the supplemented milk using a concentration of 2.837% hydrolyzed bovine collagen and PEF processing time of 116.369 seconds were the optimal designs with the desirability value of 0.809. Validation results using three repetitions produced an average TPC of 3.38 log CFU/mL  and viscosity results of 4.56 mPas. Under these conditions, the error rate value of both responses is less than 5%, indicating that the model optimization can be accepted.
Prediction of Robusta green bean coffee moisture content based on bioelectric properties with artificial neural network method Retno Damayanti; Wahyu Dwi Ristianingrum; Nazhif Ubaidillah; Dimas Firmanda Al Riza
Advances in Food Science, Sustainable Agriculture and Agroindustrial Engineering (AFSSAAE) 6th International Conference on Green Agro-industry and Bioeconomy (ICGAB) July 2022 - Special Issue
Publisher : Advances in Food Science, Sustainable Agriculture and Agroindustrial Engineering (AFSSAAE)

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Abstract

An artificial neural network (ANN) is presented for predicting the moisture content of Robusta green-bean coffee. Moisture content is measured based on bioelectric properties using a capacitance sensor, where coffee beans are considered capacitors. This research aimed to develop predictive models of the moisture content of Robusta green bean coffee using bioelectrical properties with the ANN method. Moisture content was affected by the bioelectrical properties, and the bioelectric model of green bean coffee moisture content became a resistor-inductance-capacitor (R-L-C) series. Moisture content is observed for 37.5 hours, with data collection time intervals every 2.5 hours. This research obtains 4800 data with eight samples at a frequency of 100 Hz, 1 kHz, and 10 kHz. The best ANN structure to predict moisture content based on the bioelectrical properties is 9-30-30-1. The selected ANN topology results in an R training correlation coefficient of 0.99123, an R validation correlation coefficient of 0.90343, a training MSE of 0.0099, and a validation MSE of 0.1047. ANN models based on the bioelectrical properties have been proposed to develop an accurate, simple, and reliable technique as a sensor for the detection of the moisture content of green bean coffee during the drying process.
Moringa leaf chlorophyll content measurement system based on optimized artificial neural network Yusuf Hendrawan; Titon Elang Perkasa; Joko Prasetyo; Dimas Firmanda Al-Riza; Retno Damayanti; Mochamad Bagus Hermanto; Sandra Sandra
Advances in Food Science, Sustainable Agriculture and Agroindustrial Engineering (AFSSAAE) 6th International Conference on Green Agro-industry and Bioeconomy (ICGAB) July 2022 - Special Issue
Publisher : Advances in Food Science, Sustainable Agriculture and Agroindustrial Engineering (AFSSAAE)

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Abstract

This research aimed to measure the chlorophyll content of Moringa leaves using machine vision and an optimized artificial neural network (ANN). A total of 480 images were used, 70% as training data and 30% as validation data. Features extraction was used to extract color and textural features. ANN was used as a modeling method, and the filter method was used as a feature selection method to optimize the best ANN input. Sensitivity analysis was done by varying the attribute evaluator in the filter method, as well as the learning function, the activation function, the learning rate, the momentum, the number of hidden layers, and the number of hidden nodes in the ANN. The best ANN structure was 10 input nodes, 30 nodes in the hidden layer 1, 40 nodes in the hidden layer 2, and 1 output node when using a learning rate of 0.1, a momentum of 0.5, the traincgf learning function, a logsig activation function in the hidden layer, and a tansig activation function in the output layer. The correlation coefficient between predicted and real data in the training process was 0.9792 with the training mean square error (MSE) of 0.0100, and the correlation coefficient of the validation process was 0.9794 with the validation MSE of 0.0099.
Effect of relative humidity and light exposure on fluorescence compound dynamics, soluble solid and acidity of Japanese Citrus Iyokan during postharvest treatment Muharfiza Muharfiza; Dimas Firmanda Al-Riza; Nie Sen; Yasushi Kohno; Tetsuhito Suzuki; Makoto Kuramoto; Yuichi Ogawa; Naoshi Kondo
Advances in Food Science, Sustainable Agriculture and Agroindustrial Engineering (AFSSAAE) Vol 6, No 2 (2023)
Publisher : Advances in Food Science, Sustainable Agriculture and Agroindustrial Engineering (AFSSAAE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/ub.afssaae.2023.006.02.6

Abstract

The Miyauchi iyokan (iyokan) citrus fruit is typically harvested in late December to prevent damage from the winter weather. At the time of harvest, the ratio of Soluble Solids (SS) to acid content is generally low, commonly used to assess the quality of the juice. Therefore, the goal during postharvest treatment is to decrease the acid content and improve the SS levels. The quality of citrus can be influenced by environmental factors such as relative humidity (RH) and exposure to light, so it is important to monitor their effects. Hence, this study aims to observe the changes in internal quality indicators, such as the SS/acid ratio and fluorescence compounds, under different RH and light conditions to understand how the citrus characteristics are affected. The postharvest treatment involved storing the citrus fruit at temperatures between 5-10°C for two months under various conditions i.e., in the dark and exposed to light, with high RH (80-90%) and low RH (40-50%). The SS/acid ratio did not show significant changes during the two months of storage under any treatments. However, the high RH condition resulted in a slightly higher SS/acid ratio. Similarly, the Tryptophan-like compound did not exhibit any significant response to the different treatments. However, the intensity of fluorescence from polymethoxylated flavones (PMFs) was higher in the dark treatment compared to the light treatment. PMFs play various roles in signaling and defense mechanisms in plants. Additionally, there was a notable increase in PMFs after thirty days of storage, indicating a response to light-induced stress.
Co-Authors Agus Supriatna Somantri Angky Wahyu Putranto Anugerah Dany Priyanto Anung Nugroho Jayalaksono Ariani, Safitri Diah Ayu Arrahmadiana Estuwilujeng Bambang Dwi Argo Bambang Susilo Candika Pambayun Darmanto Darmanto Dewi Maya Maharani Fausi, Ria Risti Ferina Tiara Safitri Fitriyah, Hurriyatul Hamzah, Ilham Fathurrahman Himawan, Harki Huda, Surya Izza, Ni'matul Joko Prasetyo Kondo, Naoshi Kusumawardani, Mila M Bagus Hermanto Ma'rifah, Puteri Nurul Maharsih, Inggit Kresna Makoto Kuramoto Mochamad Bagus Hermanto Moechammad Sarosa Muhammad Lutfi Almer Hasan, Muhammad Lutfi Almer Muharfiza Muharfiza Mutiara Nisa' Amri Naoshi Kondo Nauri, Afid Rahman Nazhif Ubaidillah Nie Sen Nughi Arie Nugraha Nurul Istiqomah Khoirunnisa Nurussa’adah, n/a Ogawa, Yuichi Ramadhani, Zahra Cahya Retno Damayanti Rhamadan, Ilham Sadimantara, Muhammad Syukri Sandra Sandra Sandra Sandra Simping Yuliatun, Simping Sucipto Sucipto Supriyanto Supriyanto Suzuki, Tetsuhito Syed Ihtsham Ul Haq Gilani Tetsuhito Suzuki Titon Elang Perkasa Wahyu Dwi Ristianingrum Wahyudi, Naufal Hilmiy Nizar Yasushi Kohno Yuichi Ogawa Yusuf Hendrawan Zaqlul Iqbal