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Investigating the influence of methanol:chloroform:water solvent ratios on the extraction process of tocotrienols from rice bran oil

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AIP Conference Proceedings 2024年第1期3215卷

作者： Kanya Ardelia Fathina Rita Arbianti Tania Surya Utami Bioprocess Engineering Study Program Department of Chemical Engineering Faculty of Engineering Universitas Indonesia Kampus UI – Depok West Java Indonesia 16436

Tocotrienols, belonging to the vitamin E family, exhibit neuroprotective, antioxidant, anticancer, and cholesterol-lowering attributes. A significant reservoir of tocotrienols is found within rice bran. Notably, rice bran oil stands as one of the most abundant vegetable oils in terms of tocotrienol content. This study aims to amplify tocotrienol levels in rice bran oil by fermenting rice bran with the fungus Aspergillus terreus, and by modulating the solvent ratio of methanol:chloroform:water during the extraction process. The research involves a comprehensive approach that encompasses solid-state fermentation of rice bran, succeeded by rice bran oil extraction utilizing the Bligh-Dyer method. This extracted oil is subsequently analyzed using UV spectrophotometry and GC/MS to ascertain tocotrienol levels within the rice bran oil. Findings from the study highlight an optimum solvent ratio of methanol:chloroform:water at 1:1.5:0.9 (v/v/v). Through this optimal configuration, the tocotrienol concentration escalates from 2541.44 ppm to 3642.79 ppm. Furthermore, the introduction of fermentation leads to a rise in tocotrienol levels within the extracted rice bran oil, ascending from 2541.44 ppm to 3257.66 ppm. The resultant rice bran oil extract also presents an array of antioxidant compounds, including n-hexadecanoic acid, benzoic acid, and chlorogenic acid. This collective insight underscores the potential for enhancing tocotrienol levels in rice bran oil through controlled fermentation and strategic solvent ratio adjustments, thereby enriching its potential health benefits.

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Renewable Energy Potential of Rice Straw and Paunch Manure as Bioethanol Feedstocks in Central Java, Indonesia

SSRN

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SSRN 2024年

作者： Chanifah Arianti, Forita Dyah Triastono, Joko Pertiwi, Miranti Dian Prabowo, Agung Prasetyo, Teguh Haryanto, Bambang Megawati Astuti, Widi Djarot, Ira Nurhayati Santoso, Arif Dwi Widjayanti, Sri Peni Research Center for Sustainable Production System and Life Cycle Assessment National Research and Innovation Agency Banten15314 Indonesia Research Center for Behavioral and Circular Economics National Research and Innovation Agency Jakarta12710 Indonesia Chemical Engineering Study Program Faculty of Engineering E1 Building 2nd floor Semarang Negeri Semarang Semarang50229 Indonesia

Almost all farmers are unaware that rice straw and paunch manure are potential feedstocks for bioethanol besides organic fertilizer, biochar, and biogas. Farmers' perceptions regarding the multiattributes of bioethanol development are still underestimated, indicating that farmers are still indecisive about the potential use of rice straw and paunch manure as feedstock for bioethanol. They still need extension and training to improve their knowledge. The Location Quotient (LQ) value of rice straw and cow paunch manure is > 1, indicating that Karanganyar Regency could become a base for bioethanol development from rice straw and cow paunch manure © 2024, The Authors. All rights reserved.

关键词： Manures

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Automatic watering and fertilizing with microcontrol wemos D1 R2 based on IoT (internet of things)

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AIP Conference Proceedings 2023年第1期2706卷

作者： Setyo Supratno Seta Samsiana Dwi Panji Gunawan Nur Fauzi Yuliyono Andi Hasad Aeri Sujatmiko Abdul Hafid Paronda Electrical Engineering Study Program Faculty of Engineering Islamic University “45” Bekasi Jl. Cut Meutia No. 83 Bekasi Indonesia

Watering and liquid fertilization carried out by plant owners are still manual, where the owner's involvement in these two things requires a long free time until the plants are wet and adequate fertilization is achieved. In other conditions, more attention to the survival and maintenance of plants through watering and fertilization is an absolute necessity so that plants do not wilt easily and eventually die. A solution for watering and fertilizing liquids is automatically offered through the design of watering and fertilizing liquids with a microcontroller as a control center based on Internet of Things communication. The tool is designed to automatically water and fertilize plants and generate a remote monitoring system for soil moisture using the *** application. The method used in realizing this design includes several stages, namely system block diagram planning, electrical and mechanical system planning, software design, and system testing to prove the tool can work properly according to the initial design. Supporting components for controlling watering and liquid fertilization using Wemos D1 R1, Capacitive soil moisture sensor as a soil moisture sensor, Real-Time Clock (RTC) module as a fertilizer timer. Relay that functions as a switch to turn the pump on and off. The results of the performance of the designed tool can do watering automatically when the soil moisture level is below 20% and will stop when the soil moisture is more than 40%. Meanwhile, liquid fertilization will automatically work according to a predetermined time. The existing monitoring system is accessed using smartphones and computers with the help of the *** application as long as the device is connected to the internet network. Meanwhile, liquid fertilization will automatically work according to a predetermined time. The existing monitoring system is accessed using smartphones and computers with the help of the *** application as long as the device is connected to the

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Image Processing Implementation to Classify Coffee Fruit Ripeness Using K-Nearest Neighbor (KNN) Algorithm

Image Processing Implementation to Classify Coffee Fruit Rip...

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International Conference on Information Management and Technology (ICIMTech)

作者： M. Farhan Hussaini Dermawan Deden Witarsyah Dedy Syamsuar Hanif Fakhrurroja Ahmad Luthfi Muhammad Izman Herdiansyah Faculty of Industrial Engineering Telkom University Bandung Indonesia Information Systems Department School of Information Systems Bina Nusantara University Jakarta Indonesia Department of Informatics Faculty of Industrial Technology Islamic University of Indonesia Jogjakarta Indonesia Informatics Study Program Faculty of Science and Technology Universitas Bina Darma Palembang Indonesia

Coffee is one of the plantation crops that has long been a cultivated plant in Indonesia. The classification of coffee fruit maturity manually still has several weaknesses and requires a long process, has low accuracy and is inconsistent, this is because the determination is made subjectively by coffee farmers. As for the classification of coffee fruit maturity levels automatically, it can be faster with objective determination, therefore the use of image processing is relatively easier, faster, and based on a quantified descriptive assessment to determine coffee maturity. Image Processing is a method used to process or manipulate images in 2-dimensional form. In the classification process, there are many methods used to obtain classification of objects based on training data. One of the algorithms used for the classification process is K-Nearest Neighbor (KNN). KNN is a classification technique for objects based on training data that is the closest or has similar characteristics to the object. KNN includes supervised learning algorithms, where the results of the new query instance are classified based on the majority of the categories in K-Nearest Neighbors (K-NN). The finding indicated that class classification of ripe and unripe were 88,24 % and 100% respectively with 93,33% accuracy level.

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Smart Home Security System Using Face Recognition Based on IoT- CNN

Smart Home Security System Using Face Recognition Based on I...

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Information Technology Research and Innovation (ICITRI), International Conference on

作者： M. Aldiki Febriantono Alvin Zuhair Khaeruddin Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia Electrical Engineering Department University of Islam Blitar Blitar Indonesia Diploma III Electronic Technology Vocational Study Program University of Muhammadiyah Malang Malang Indonesia

Home security is a crucial aspect that requires careful attention, particularly when it comes to addressing theft concerns. Hence, implementing smart door technology equipped with facial recognition holds promising potential for enhancing home security. This study aims to develop a more secure and regulated home entry system by leveraging Internet of Things (IoT) technology and Machine Learning Computer Vision for facial recognition. The system integrates IoT devices, such as cameras and automatic doors, wherein facial image data is captured by the camera and processed using the Convolutional Neural Network (CNN) algorithm to identify individuals. Once an individual is recognized, the system grants access to the home through an automated door. By relying on facial features, the system effectively restricts unauthorized access and safeguards homes against theft risks. Therefore, the advancement of a safer and more controlled home entry system utilizing IoT technology and Machine Learning Computer Vision holds tremendous benefits for homeowners.

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Optimization of ultrasonic extraction parameters for enhanced total flavonoid content from Jengkol peel

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AIP Conference Proceedings 2024年第1期3215卷

作者： Amanda Emilia Rafifah Hasna Rita Arbianti Tania Surya Utami Bioprocess Engineering Study Program Department of Chemical Engineering Faculty of Engineering University of Indonesia Kampus UI – Depok West Java Indonesia 16436

Jengkol, a commonly consumed food ingredient, is frequently utilized without its outer layer. However, the outer peel of the jengkol fruit harbors a multitude of secondary metabolites that hold potential as bioinsecticides. Among these compounds, flavonoids stand out as toxic to insects. The quantification of flavonoid content within jengkol peel extracts is denoted as TFC (Total Flavonoid Content). Employing ultrasonic wave extraction, the conversion of jengkol peel into bioinsecticides can be facilitated. This research employs ultrasonic wave extraction, utilizing an ethanol solvent, with a frequency of 53 kHz and a temperature of 40℃. Through systematic variation of sonication duration and solvent concentration, this investigation scrutinizes the impact of these variables on TFC values and extracts yields. The assessment of TFC is conducted using UV-Vis spectrophotometry and referencing a quercetin standard solution. Optimal TFC output, specifically 1.643±0.026 mg QE/g of dried jengkol peel extract, is achieved at a 60-minute extraction period using 70% ethanol solvent. Liquid Chromatography-Mass Spectrometry (LCMS) analysis identifies various compounds with bioinsecticidal potential, including phenolic acids, fatty acids, flavonoids, phytoalexins, and coumarins, exhibiting the highest TFC levels. Employing ANOVA analysis followed by a post hoc LSD (Least Significance Different) test, it is evident with 95% confidence that both extraction time and solvent concentration significantly influence flavonoid content within jengkol peel extracts.

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Unbalance Fault Diagnosis in Electric Motors under Non-Stationary Load Conditions: An Iterative Filter Decomposition Approach

Unbalance Fault Diagnosis in Electric Motors under Non-Stati...

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International Conference on Instrumentation Control and Automation (ICA)

作者： Imron Rosyadi Yul Yunazwin Nazaruddin Parsaulian Ishaya Siregar Doctoral Program of Engineering Physics Faculty of Industrial Technology Institut Teknologi Bandung Bandung Indonesia Electrical Engineering Department Universitas Jenderal Soedirman Purwokerto Indonesia Department of Engineering Physics Instrumentation and Control Research Group Institut Teknologi Bandung Bandung Indonesia National Center for Sustainable Transporation Technology Institut Teknologi Bandung Bandung Indonesia

In electric vehicles, the dynamic nature of driving conditions, speed variations, and fluctuations in loads introduce non-stationary loads on electric motors. These non-uniform load distributions can result in mechanical imbalance faults within the motor, leading to increased vibrations, reduced motor performance, and potential mechanical stress on its components. The development of advanced diagnostic methods is crucial for detecting and addressing these mechanical balance faults in electric motors. This article introduces a novel approach for diagnosing mechanical unbalance faults using local iterative filter decomposition, specifically designed for electric motors operating under non-stationary load conditions. The experimental results demonstrate that the application of iterative filter decomposition yields superior outcomes compared to the absence of decomposition. By employing this method, the algorithm achieves a classification accuracy exceeding 80% for all types of unbalances, including the detection of low-speed rotation unbalance faults, which are known to be challenging to identify.

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Hypocenter dimension of 7.5 mw Palu earthquake using fractal approach 2

Hypocenter dimension of 7.5 mw Palu earthquake using fractal...

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2nd International Conference of Interdisciplinary Research on Green Environmental Approach for Sustainable Development, ICROEST 2020

作者： Rasimeng, Syamsurijal Alimuddin Rustadi Sinambela, Rudy Z. Mandang, Idris Bakri, Samsul Zaenudin, Ahmad Department of Geophysical Engineering Faculty of Engineering University of Lampung Indonesia Disaster and Mitigation Center Faculty of Engineering University of Lampung Indonesia Study Program of Geophysics Faculty of Mathematics and Natural Science Mulawarman University Indonesia Department of Forestry Graduate Program of Environmental Sciences University of Lampung Indonesia

Research on the Palu earthquake in the period of August to October 2018 has been carried out in the Palu Koro Fault (PKF) zone with a hypocenter of 5-20 km. This study aims to determine the fractal dimensions of these earthquakes based on the relationship between logarithmic frequency and earthquake magnitude correlation introduced by Gutenberg-Richter. Statistical correlation between logarithmic frequency and earthquake magnitude was calculated using the inversion approach. Based on the calculation results obtained fractal dimension value of 1.0378, which describes the seismicity pattern at a depth of 5-20 km. It indicates that the earthquakes triggered by the movement in rupture segments which seen as points along the PKF zone. © Published under licence by IOP Publishing Ltd.

关键词： Earthquakes

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RLS-based Interference Cancellation 17

RLS-based Interference Cancellation

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17th International Conference on electrical engineering/Electronics, Computer, Telecommunications and Information Technology, ECTI-CON 2020

作者： Punchalard, Rachu Thitinauremit, Aphirak Mahanakorn University of Technology Department of Telecommunication Engineering Bangkok10530 Thailand Mahanakorn University of Technology Electrical Engineering Graduate Program Faculty of Engineering Bangkok Thailand

ISBN: (纸本)9781728164861

Adaptive Sinusoidal interference cancellation (ASIC) based on recursive least square (RLS) algorithm is proposed. RLS algorithm allows us to use a recursion instead of inversion of the autocorrelation matrix to evaluate the optimum weights. The main advantage of RLS algorithm is that it exhibits extremely high rate of convergence. Computer simulations are performed to demonstrate the performance of the proposed algorithm. © 2020 IEEE.

关键词： Adaptive algorithms

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Cognitive dissonance analysis students choosing the higher education program in undergraduate program

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AIP Conference Proceedings 2024年第1期2891卷

作者： Akbar Fernanda Atyanti Dyah Prabaswari Muhammad Ragil Suryoputro Syafa Thania Prawibowo Industrial Engineering Program Study Faculty of Industrial Technology Universitas Islam Indonesia Yogyakarta Indonesia

Technological developments also affect the development of science. Universities, as one of the media that play an important role in science and discoveries, are also growing rapidly. The varied majors encourage students to be more selective in choosing them. This study examines the formation of cognitive dissonance in The Higher Education program in Undergraduate program students at the Higher Education program (HEP) Indonesia. The dimensions involved of cognitive dissonance were including emotional, wisdom of purchase, and concern over the deal. The emotional dimension is measured by 15-question indicators, the wisdom of purchase dimension is measured by 44-question indicators, and concern over the deal is measured by 3-question indicators. The research sample used 111 students of the 2017 and 2018 batches or third and fourth-year students of the HEP in Undergraduate Level. The analytical technique applied in this study uses factor analysis. The results of cognitive dissonance analysis using factor analysis on emotional variables showed that students were not upset to choose the intended undergraduate level of HEP in Indonesia, on the wisdom of purchase variable, it shows that students felt the need to choose the HEP in Undergraduate program. The concern over the deal variable showed that students did not feel confused in choosing the HEP in the Undergraduate Level.

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