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All Journal Teknotan: Jurnal Industri Teknologi Pertanian TELKOMNIKA (Telecommunication Computing Electronics and Control) Pelita Perkebunan Journal of Innovation and Applied Technology Indonesian Green Technology Journal Jurnal Keteknikan Pertanian Tropis dan Biosistem Jurnal Teknologi Pertanian Jurnal Edukasi dan Penelitian Informatika (JEPIN) agriTECH Indonesian Journal of Science and Technology Jurnal Ilmiah Teknologi Pertanian Agrotechno Proceeding of the Electrical Engineering Computer Science and Informatics Jurnal Ilmiah Rekayasa Pertanian dan Biosistem Jurnal Teknik Pertanian Lampung (Journal of Agricultural Engineering) Jurnal Teknologi Pertanian Andalas Advances in Food Science, Sustainable Agriculture and Agroindustrial Engineering (AFSSAAE) Journal of Robotics and Control (JRC) Jurnal Mnemonic Indonesian Journal of Electrical Engineering and Computer Science International Journal of Artificial Intelligence and Robotics (IJAIR) El-Mujtama: Jurnal Pengabdian Masyarakat Jurnal Abdi Masyarakat Indonesia
Yusuf Hendrawan
Universitas Brawijaya
Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Control & Systems Engineering Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Immunology & microbiology Industrial & Manufacturing Engineering Mechanical Engineering Public Health Social Sciences Other

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The Classification of Aflatoxin Contamination Level in Cocoa Beans using Fluorescence Imaging and Deep learning Sadimantara, Muhammad Syukri; Argo, Bambang Dwi; Sucipto, Sucipto; Al Riza, Dimas Firmanda; Hendrawan, Yusuf
Journal of Robotics and Control (JRC) Vol 5, No 1 (2024)
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jrc.v5i1.19081

Abstract

Aflatoxin contamination in cacao is a significant problem in terms of trade losses and health effects. This calls for the need for a non-invasive, precise, and effective detection strategy. This research contribution is to determine the best deep-learning model to classify the aflatoxin contamination level in cocoa beans based on fluorescence images and deep learning to improve performance in the classification. The process involved inoculating and incubating Aspergillus flavus (6mL/100g) to obtain aflatoxin-contaminated cocoa beans for 7 days during the incubation period. Liquid Mass Chromatography (LCMS) was used to quantify the aflatoxin in order to categorize the images into different levels including “free of aflatoxin”, “contaminated below the limit”, and “contaminated above the limit”.  300 images were acquired through a mini studio equipped with UV lamps.  The aflatoxin level was classified using several pre-trained CNN approaches which has high accuracy such as GoogLeNet, SqueezeNet, AlexNet, and ResNet50. The sensitivity analysis showed that the highest classification accuracy was found in the GoogLeNet model with optimizer: Adam and learning rate: 0.0001 by 96.42%. The model was tested using a testing dataset and obtain accuracy of 96% based on the confusion matrix. The findings indicate that combining CNN with fluorescence images improved the ability to classify the amount of aflatoxin contamination in cacao beans. This method has the potential to be more accurate and economical than the current approach, which could be adapted to reduce aflatoxin's negative effects on food safety and cacao trade losses.
CHANGE DETECTION IN ALUMINUM ELECTRODE IMAGE DURING OHMIC HEATING USING PRINCIPAL COMPONENT ANALYSIS Dwi Hartono, Elvianto; Hardiansyah, Bagus; Lastriyanto, Anang; Zubaidah, Elok; Hendrawan, Yusuf
Jurnal Mnemonic Vol 7 No 2 (2024): Mnemonic Vol. 7 No. 2
Publisher : Teknik Informatika, Institut Teknologi Nasional malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36040/mnemonic.v7i2.8426

Abstract

In this paper, we propose a novel technique for unsupervised change detection dataset derived from a process pasteurization using aluminium plate left and right with frequencies 1kHz, 2kHz, 100Hz, 250Hz images using principal component analysis (PCA) and k-means clustering. The distinct image is partitioned into h × h non-overlapping blocks. orthonormal eigenvectors are extracted through PCA of non-overlapping block set to create an eigenvector space. Each pixel within the distinct image is characterized by a feature vector of a certain dimensionality. This feature vector is obtained projection the distinct image data onto the eigenvector space that has been generated. Change detection is accomplished by dividing the feature vector space into two clusters through the application of k-means clustering with k=2. Each pixel is then assigned to one of these two clusters based on the minimum Euclidean distance between the pixel's feature vector and the mean feature vector of the clusters. Empirical results validate the effectiveness of the proposed approach.
Application of two-lever baglog pressing machine technology to improve the production of oyster mushroom cultivation Damayanti, Retno; Malin Sutan, Sandra; Hendrawan, Yusuf
Journal of Innovation and Applied Technology Vol 10, No 1 (2024)
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/ub.jiat.2022.010.01.009

Abstract

The baglog pressing process in the Ngadi Oyster Mushroom Cultivation Community Group is still done manually, by compressing the media in a plastic bag with a bottle or plastic pipe several times until it is solid. This work requires quite a lot of labor and a long time, also depends on the skills and accuracy of the workers. Problems that can be identified in SMEs are the division of labor duties for the pressing and steaming processes, the lack of experienced workers who can compact baglog properly. So it is necessary to apply a two-lever baglog pressing machine which aims to increase production capacity. The results of the activity show an increase in baglog production capacity, from 60 baglog/day with 2 workers to 300 baglog/day with a baglog press machine. This capacity meets the needs for the steaming process, where the steamer capacity owned by SMEs is 215 baglogs/day.
Edukasi Pembuatan Laporan Keuangan UMKM Kepada UMKM Forsamik di Kelurahan Kutabumi Kabupaten Tangerang Gultom, David Parningotan; Hendrawan, Yusuf; Herdiansyah, Deni; Syahriyah, Yayah; Apriansyah, Reza
El-Mujtama: Jurnal Pengabdian Masyarakat Vol 4 No 2 (2024): El-Mujtama: Jurnal Pengabdian Masyarakat
Publisher : Intitut Agama Islam Nasional Laa Roiba Bogor

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47467/elmujtama.v4i2.5250

Abstract

This community service activity is entitled Education for Making MSME Financial Reports to Forsamik MSMEs in Kutabumi Village, Tangerang Regency. The general objective of this community service activity is to provide understanding, training and practical knowledge of accounting that can have an impact on the preparation of simple financial reports for MSME actors. The methods used are survey methods and direct delivery of material as well as simulations and discussions regarding accounting, tariffs, rules and reporting of MSME taxes, financial management, and preparation of simple financial reports. The conclusion of this community service is that it provides knowledge related to the importance of preparing good financial reports for public welfare and the many benefits if MSME actors make good financial reports.
Analisis Transformasi Energi Biogas Kotoran Sapi Menjadi Energi Listrik di Kecamatan Bumiaji, Kota Batu Mustofa, Ary; Hendrawan, Yusuf; Putra, Reza Rienaldy
Journal of Tropical Agricultural Engineering and Biosystems - Jurnal Keteknikan Pertanian Tropis dan Biosistem Vol. 11 No. 2 (2023): August 2023
Publisher : Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/ub.jkptb.2023.011.02.11

Abstract

Biogas merupakan energi alternatif degradasi produk akhir pencernaan hewan ternak (sapi) dalam keadaan anaerobik oleh bakteri metanogen yang berupa gas metana dan semacamnya. Biogas menjadi salah satu bahan bakar alternatif yang bisa dimanfaatkan menjadi energi listrik dengan memodifikasi sistem karbulasi pada generator motor bakar. Metode yang digunakan yaitu eksperimental, pertama yaitu pengujian prestasi motor bakar dengan metode variasi pengereman poros (prony brake) yaitu 1000 rpm; 1500 rpm; 2000 rpm; 2500 rpm; dan 3000 rpm. Pengujian kedua yaitu pengujian kinerja generator yaitu pada pembebanan listrik 112 watt; 200 watt; 312 watt; 482 watt; dan 570 watt. Nilai torsi dan daya maksimum motor bakar terjadi saat menggunakan bahan bakar biogas pada putaran 2500 rpm yaitu 37.8 Nm dan 3.91 kW jika dibandingkan dengan pertalite sebesar 37.67 Nm dan 3.86 kW. Konsumsi bahan bakar spesifik (SFC) biogas lebih hemat dari pertalite yaitu sebesar 0.000015 kg/kW.s dengan 0.000069 kg/kW.s. Efisiensi termal maksimum menggunakan biogas lebih tinggi daripada pertalite yaitu 36.08% dengan 32.95%. Suhu gas buang dari bahan bakar biogas lebih tinggi dari bahan bakar pertalite. Pada pengujian generator, penggunaan biogas memiliki tingkat efektifitas lebih tinggi dibanding pertalite dan telah memenuhi standar listrik nasional.
Performance Analysis of Extraction Machine Using Ohmic Technology for Producing Anthocyanin Sugiarto, Yusron; Asy Syukri, Khoirul Anam; Lastriyanto, Anang; Hendrawan, Yusuf
Journal of Tropical Agricultural Engineering and Biosystems - Jurnal Keteknikan Pertanian Tropis dan Biosistem Vol. 11 No. 2 (2023): August 2023
Publisher : Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/ub.jkptb.2023.011.02.03

Abstract

Extraction is one of the important processes for obtaining anthocyanins as natural dyes. The aim of this study is to investigate the performance of the extraction apparatus using ohmic technology to produce anthocyanins. This study used a series of ohmic heating consisting of tubular pipes with a diameter of 6 cm and a length of 5.5 cm with a volume capacity of 100 ml. This extraction machine was completed with two electrodes that each have a thickness of 10 mm. The performance of extraction machines using ohmic technology was analyzed by using various voltages of 20, 30, 40, 50, and 60 Volts/cm. The result showed that the voltage affected the electric current of the machine. The voltage of 60 Volts/cm was able to produce the largest average electric current of 5.28 A with the greatest electric current achievement of up to 6.21 A. The result showed that increasing the voltage during the extraction process reduced the time needed to reach the expected temperature. The fastest time was achieved in the voltage of 60 Volts/cm with an average time of 11.3 seconds. The increased voltage in the extraction treatment also affects the total anthocyanin produced. The highest total anthocyanin was obtained from a voltage gradient of 60 Volts/cm with a value of 288.014 mg/L and a yield of 14.4%.
Filter Feature Selection for Detecting Mixture, Total Phenol, and pH of Civet Coffee Widyaningtyas, Shinta; Arwani, Muhammad; Sucipto, Sucipto; Hendrawan, Yusuf
International Journal of Artificial Intelligence & Robotics (IJAIR) Vol. 6 No. 2 (2024): November 2024
Publisher : Informatics Department-Universitas Dr. Soetomo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25139/ijair.v6i2.9010

Abstract

Civet coffee, a highly valued specialty coffee, is susceptible to adulteration with regular coffee, resulting in economic losses and consumer fraud. This study investigates the potential of electrical spectroscopy as a non-destructive technique for detecting civet coffee adulteration. We analyzed the bioelectrical properties of civet coffee beans and their mixtures with regular coffee, focusing on impedance parameters (Z, Lp, Ls, Rp, Rs) as potential indicators of adulteration. Two machine learning models, Artificial Neural Network (ANN) and Random Forest, were trained and evaluated using Mean Squared Error (MSE) validation to identify the most informative features for predicting mixture composition, total phenol content, and pH. The findings demonstrate that impedance parameters, particularly Z, consistently exhibited high feature importance scores across different attribute evaluators and search methods. The optimal model, an ANN with a correlation attribute evaluator and ranker search method, achieved an MSE validation of 0.0479, indicating strong predictive accuracy. These results suggest that electrical spectroscopy, coupled with machine learning, offers a promising approach for developing automated, non-invasive methods for detecting civet coffee adulteration, thereby protecting consumers and ensuring the integrity of the specialty coffee market.
Characterisation of honey using high-frequency ohmic heating based on image segmentation Hartono, Elvianto Dwi; Lastriyanto, Anang; Zubaidah, Elok; Hendrawan, Yusuf
Advances in Food Science, Sustainable Agriculture and Agroindustrial Engineering (AFSSAAE) Vol 7, No 3 (2024)
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.2024.007.03.8

Abstract

In the field of computer vision, image segmentation using a clustering approach was employed. This non-destructive method was applied to process ohmic heating in honey, aiming to achieve an efficient and time-saving mass production process. The K-means clustering algorithm converted RGB color data to Lab color space for effective segmentation. The validation of outcomes was conducted through the evolution of RMSE values and regression analysis for each frequency. Notably, at a precision frequency of 1 kHz, the results were as follows: RMSE Red 1.4902, RMSE Green 0.7017, RMSE Blue 0.3328, Regression Red 0.0792, Regression Green 0.5782, Regression Blue 0.202, and heat penetration regression 0.658. This proposed method was benchmarked against the conventional heat penetration analysis in ohmic heating.
Color-based Classification of Dried Cocoa Beans from Various Origins of Indonesia by Image Analysis Using AlexNet and ResNet Architecture-Convolutional Neural Networks Kristianingsih, Wahyu; Dwi Argo, Bambang; Jati, Misnawi; Ariefandie Febrianto, Noor; Hendrawan, Yusuf; Bagus Hermanto, Mochamad; Rahmatullah, Bagus
Pelita Perkebunan (a Coffee and Cocoa Research Journal) Vol. 40 No. 3 (2024)
Publisher : Indonesian Coffee and Cocoa Research Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22302/iccri.jur.pelitaperkebunan.v40i3.638

Abstract

Cocoa plant is widely cultivated in Indonesia and spread across various regions. Diversity in geographical conditions has been known to significantly affect the quality of cocoa beans. Practically, cocoa beans are often mixed without considering the variation in the quality and its origin. This resulted in reduced global quality and product inconsistency. Improved recognition and classification methods are needed to solve those problems. Non-destructive classification methods can be used to provide a more efficient classification process. The use of artificial intelligence with computer-based deep learning methods was used in this study. Beans samples of various origins (Aceh, Bali, Banten, Yogyakarta, East Kalimantan, West Sulawesi, and West Sumatera) were evaluated. From thecollected samples, 9100 images were then taken for data processing. Data preprocessing included denoising of the background image, cropping, resizing andchanging the storage extension through the training-validation stage and the testing process. AlexNet and ResNet architectures on a Convolutional NeuralNetwork were used for classification. The results showed that the average accuracy of cocoa image classification based on color identification by computer machines using Alexnet and ResNet was high (99.91% and 99.99%, respectively). This method can be applied to provide more efficient color-based cocoa bean classification for industrial purposes.
Exploring the Impact of Temperature and Solvent Ratio on Phenol and Flavonoid Levels in Alpinia galangal L. Extract Using Evaporative Vacuum Cooling Dina Wahyu Indriani; Firdha Dwi Anggraini; Yusuf Hendrawan; Anang Lastriyanto
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.v13i4.1064-1076

Abstract

The objective of this research is to determine the impact of temperature gradients and solvent ratios in the evaporative vacuum cooling method on the yield of phenol and flavonoid content in galangal extract; ascertain the impact of these factors on the yield generated by galangal extract; and ascertain the mass balance analysis of materials are the objectives of this study. Throughout the extraction of galangal. The study's findings demonstrated that the evaporative vacuum cooling technique, conducted at 49 ºC and with a 1:1 solvent ratio of 1.4432±0.7317 mg GAE/g, produced the highest total phenol concentration. The three differences in the temperature of the evaporative vacuum produced the total phenol content cooling. The overall phenol content obtained decreases with increasing solvent ratio addition. Although the evaporative vacuum cooling treatment at 45 °C yielded the highest total flavonoid content (1.2418±0.2365 mg QE/g) at a 1:2 solvent ratio, the total flavonoid content varied between the three evaporative vacuum cooling temperature variations. The yield of total phenolic and flavonoid compounds was not significantly affected by temperature gradient adjustments or the ratio of galangal extract to solvent (Sig. > 0.05) in any of the data samples pertaining to phenolic and flavonoid compounds. Keywords: Evaporative vacuum cooling, Flavonoids, Galangal, Phenol.
Co-Authors A.A. Ketut Agung Cahyawan W AA Sudharmawan, AA Adamsyah Harika Putra Adi Rahmanto Wibowo adiansyah, muhammad Agil Adham Reka Agus Somantri Ahmad Diyanal Arifin Ahmad Muhlisin Al-Riza, Dimas Firmanda Ali Djamhuri Alifah Maulidiyah Alvianto, Dikianur Anang Lastriyanto Anggraini, Firdha Dwi Anggraini, Sabrina Angky Wahyu Putranto Anisah Cahyani Anninatul Fuadah Anung Nugroho Jayalaksono Apriansyah, Reza Aprilia Nur Komariyah Ariefandie Febrianto, Noor Arif Hidayat Arif Wicaksono R.P Arifiandika, Rizal Aris Fanani Ary Musthofa Ahmad Ary Mustofa Ary Mustofa Ahmad Asy Syukri, Khoirul Anam Aulia Meidiati Aziz Fathur R Bagas Rohmatulloh Bambang Dwi Argo Bambang Dwi Argo BAMBANG SUSILO Bambang Susilo Cahyanto, Darmawan Dwi Chatarina Umbul Wahyuni Choirul Umam Christiana Wahyu Citra Puspita Rani Cory Vidiati Dalas Gumelar Dana Marsetya Utama Deivy Amaliya Tipdani Dendy Satyabima Dewi Maya Maharani Dian Aris Setiawan Dimas F Al Riza Dimas Firmanda Al Riza Dimas Firmanda Al Riza Dimas Firmanda Al Riza Dina Wahyu Indriani Dina Wahyu Indriani Djoko Wahyudi Dwi Setiawan Elok Zubaidah Elwin Elwin F Al Riza, Dimas Fatma Ridha Nurlaili Fauzy, Muchammad Fenti Siregar Fiqi Ibrahim Saqroth Firdaus Kurnia Putra Firdha Dwi Anggraini Fitriyah, Hurriyatul Gultom, David Parningotan Gunomo Djojowasito Gunomo Djoyowasito Gunomo Djoyowasito hardiansyah, bagus Hartono, Elvianto Dwi Hendrias Hendrias Hendy Firmanto Herdiansyah, Deni Hilmi, Miftahul Hismarto Bahua Imam Santoso Indah Mustika Sakti Indah Royani Izza, Sylvia Ni’matul Joko Prasetyo Khoirul Anam Asy Syukri Kreative Y.R, Rizka Kristianingsih, Wahyu Kusuma Faisal M La Choviya Hawa Liana, Verianti Litapuspita Rizka Perdana Madaniyyah Mustika Islami, Madaniyyah Mustika Maffudhotul Anna Malin Sutan, Sandra Mardhotillah Mardhotillah Meilani Eka Marantika Merisa Yunita Miftahudin Nawawi Miftahul Hilmi Misnawi Jati Mochamad Bagus Hermanto Moh. Risal Siregar Muchammad Fauzy Muchammad Zakaria, Muchammad Muchnuria Rachmawati Muhamad Amar Nadhif muhamad nur afidin Muhammad Arwani Muhammad Fadhil Muhammad Husain Kamaluddin Muhammad Iqbal Musthofa Lutfi Musthofa Lutfi Mustofa, Ary Mutiara Nisa' Amri Nabila Az-Zalikhah Ilham Nafi’ah, Riris Waladatun Niken Dieni Pramesi Niken Lila Widyawati Nugroho, Hermawan Nur Ida Winni Yosika Nurkholis Hamidi Oktaria Eka Y Omah Rochmah Pratama, Kanda Bagus Puguh Sudarsono Putra, Reza Rienaldy Rachmawati, Muchnuria Rahmatullah, Bagus Retno Damayanti Retno Damayanti Soejoedono Reza Rienaldy Putra Riana, Eki Rico Santoso Rini Yulianingsih Rini Yulianingsih Rochima Nisaa’IL-Firdaus Rohmatulloh, Bagas Ronald Nelson Krakuko Ryan Maulana Abdul Hakim Sadimantara, Muhammad Syukri Saiful Imron Sandra Malin Sutan Sandra Sandra Sandra Sandra Sandra Sandra Shinta Rosalia Dewi Shinta Widaningtyas Shinta Widyaningtyas Simping Yuliatun Siti Mariyah Ulfa Siti Nurhayati Somantri, Agus Sucipto, Sucipto Sukses Agustin Nahmudiyah Sumardi H. S. Sumardi Hadi Sumarlan Sumardi Hadi Sumarlan Sumardi Hadi Sumarlan Sumardi Hadi Sumarlan Supriyanto Supriyanto Supriyanto, Supriyanto Syahriyah, Yayah Titon Elang Perkasa Tunjung Mahatmanto Ubaidillah Ubaidillah Vita Noeravila Putri Wachid Rahmanjaya Wahyu Dhiki Saputro Wahyunanto Agung Nugroho Widaningtyas, Shinta Widyaningtyas, Shinta Wignyanto Wignyanto Wike A. P. Dania Yosua Yosua Yudha Firdaus Baharsyah Yuliatun, Simping Yuni Oktopiyani Yusron Sugiarto Yusuf Wibisono Yuyun Wahyuni Zahrok, Isna Arofatuz