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Optimalization of enzymatic degradation on oil palm leaves hemicellulose

AIP Conference Proceedings 2023年第1期2679卷

作者： Anita Kurniati Ni Nyoman Purwani Galih Ayhusta Laras Rohmawati Ali Rohman Afaf Baktir Hery Suwito Kazuo Sakka Makiko Sakka Ni Nyoman Tri Puspaningsih 1Mathematics and Natural Science Study Program Faculty of Science and Technology Kampus C Universitas Airlangga Mulyorejo Surabaya East Jawa 60115 Indonesia 3University-CoE-Research Centre for Bio-Molecule Engineering 2nd Floor ITD Building Kampus C Universitas Airlangga Mulyorejo Surabaya East Java 60115 Indonesia 4Department of Health Faculty of Vocational Studies Kampus B Universitas Airlangga Surabaya East Java 60286 Indonesia 2Department of Chemistry Faculty of Science and Technology Kampus C Universitas Airlangga Mulyorejo Surabaya East Java 60115 Indonesia 5Applied Microbiology Laboratory Graduate School of Bioresource Mie University 1577 Khurimamachiya-cho Tsu 514-8507 Japan

Indonesia is the largest country of oil palm production in the world. The oil palm by-product is still containing almost 80% of carbohydrates, such as cellulose and hemicellulose. This study aimed to optimize the enzymatic degradation of oil palm leaves in order to achieve zero waste of oil palm biomass by-product. Sodium hydroxide (NaOH) solution was used to isolate hemicellulose extraction from oil palm leaves. Various concentrations of NaOH such as 2 M, 2.5 M, 3 M, 3.5 M and 4 M and the reflux times of 2 hours, 4 hours, and 6 hours were used to optimize hemicellulose extraction. The optimum condition for hemicellulose extraction was 3 M NaOH and reflux time was 6 hours, while the yield at that condition was 48.94 % (w/w). The extracted hemicellulose is then hydrolyzed by a xylanolytic enzyme from recombinant Escherichia coli DH5α (namely pTP510). Temperatures of incubation were varied 50°C, 60°C, 70°C, and 80°C for 24 hours at pH 6. The hydrolysis result was analyzed using High Performance Liquid Chromatography (HPLC). Xylose was produced at an optimum temperature of 60°C (120.231 ppm), arabinose at 50°C (26.265 ppm) whereas xylo-oligosaccharide at 50°C (280.465 ppm).

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Measurement of perception and implementation of sustainable supply chain management at PT Tetra Pak Indonesia

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IOP Conference Series: Earth and Environmental science 2020年第1期426卷

作者： Helena J Kristina Agustina Christiani Eric Jobiliong Letycia Therio Reza Andreanto Industrial Engineering Study Program Universitas Tarumanegara Jakarta Indonesia Industrial Engineering Study Program Faculty of Science and Technology Universitas Pelita Harapan Lippo Village Tangerang Indonesia PT Tetra Pak Indonesia

Sustainable supply chain management (SSCM) is a form of proactive action taken by the company and its supply chain to remain competitive by introducing products and production processes that are environmentally friendly and socially *** Tetra Pak Indonesia as a company engaged in the processing and packaging for food and beverages, is committed to reduce the environmental impact of all operations and prioritize environmental aspects for each product and solution offered. Although there have been many sustainability efforts undertaken by PT Tetra Pak Indonesia, the perspective and implementation of its sustainable supply chain management has never been measured. This research was conducted to measure the perception and implementation of sustainable supply chain management (SSCM) activities of *** Pak Indonesia, in order to add information about the development of sustainable supply chain management practices in Indonesia. Data were collected in two ways: in depth interviews and questionnaires. Based on the result of interview and questionnaire, *** Pak Indonesia gets an actual implementation index value of SSCM activities of 0.88, and has an overall perception index value of 0.85. This indicates that PT. Tetra Pak Indonesia is a company that has a perception towards sustainability and has actually implemented SSCM activities.

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Web of Things to control planting seeds and watering plants for indoor smart farm

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IOP Conference Series: Materials science and engineering 2021年第5期1098卷

作者： M P T Sulistyanto E Febriawan I Sulistiyowati Informatics Study Program Faculty of Science and Technology Universitas Kanjuruhan Malang Jl. S. Supriadi No. 48 Malang Jawa-Timur Indonesia Electrical Engineering Faculty of Science and Technology Universitas Muhammadiyah Sidoarjo Jl. Raya Gelam 250 Candi Sidoarjo Jawa Timur Indonesia

With the emergence of the Web of Things (WoT) as Internet of Things (IoT) enhancement in web application, the Industrial Revolution 4.0 has developed very rapidly. Its technology has been commonly used in various fields of life, especially in agriculture. One of the crop plants is often achieved by vegetable farming, as vegetables are the staples of daily life. Aim this study is for plating mustard green seeds and watering plant using WoT. This method begins by doing literature review, requirement analysis, design and implementation. The result shows the developing of prototype to planting mustard seeds and watering plant is successful that it can be remotely operated through WoT. The planting and watering process uses Gcode command to carry out seed picks, planting seeds, and water plants.

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Application of gray level run length matrices features extraction for diabetic retinopathy detection based on artificial neural network

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AIP Conference Proceedings 2020年第1期2314卷

作者： Bestia Kumala Wardani Nathania Earlene Belinda Riries Rulaningtyas Endah Purwanti 1Biomedical Engineering Study Program Department of Physics Faculty of Science and Technology Universitas Airlangga Surabaya Indonesia

Diabetic Retinopathy (DR) is Diabetes Mellitus microvascular complication, which attacks the eyes and can cause blindness. The DR examination currently is done with the fundus photography technique. The image produced by the technique is studied by the ophthalmologist manually. This research aimed to develop a computer aided diagnosis in the DR detection system using Gray Level Run Length Matrices (GLRLM) features extraction and Artificial Neural Network. This DR detection was done by Gray Level Run Length Metrices (GLRLM) texture features extraction method. Five texture features used were: Short Run Emphasis (SRE), Long Run Emphasis (LRE), Gray Level Non-Uniformity (GLN), Run Length Non-Uniformity (RLN), and Run Perecentage (RP). The five features were used as Backpropagation Artificial Neural Network input. The parameters are varied in the Backpropagation Artificial Neural Network training phase. The data used in this research were 110 retinal fundus images consists of 20 normal retinal fundus images, 45 NPDR retinal fundus images, and 45 PDR retinal fundus images. The highest accuracy result gained in the training phase is 97.14% and testing phase is 92.5%. This detection program produces a sensitivity value of 93.33% and a specificity value of 90%, therefore, it can be used as an initial indicator to detect DR.

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Filter design on EMG multichannel based python programmer

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AIP Conference Proceedings 2020年第1期2314卷

作者： Prihartini Widiyanti Aji Sapta Pramulen Akif Rahmatillah 1Biomedical Engineering Study Program Department of Physics Faculty of Science and Technology Universitas Airlangga Surabaya Indonesia

Currently, EMG devices are used as recording and monitor device for muscle activity. However, the existing tools use licensed software that result in limited features provided. In addition, the inability of the tools to be able to record simultaneous movements involving several muscles at the same time is another problem regarding the design of EMG device systems. This research is done to design a multichannel EMG filter using python programming. Therefore, the design of this device consists of hardware in the form of instrumentation amplifier circuit, NI DAQ USB 6009 as data acquisition, and software part consisting of signal processing (filtering, rectifying, smoothing) and signal interface on Personal Computer (PC) using Python 2.7. The device testing is done in 2 ways, that is finance and tools from EMG itself. The instrumentation test got the strengthening value 15,241 times with linearity of 0.941. In addition, Butterworth IIR filter response is obtained according to the design of the cut off frequency of 15-450 Hz and 50 Hz. Performance testing of prototype EMG devices is done with compare of standard EMG and recording is done on normal male. Qualitatively the recording signal features using EMG of research with simultaneous movements identical to the recording signal features using standard EMG. The analysis of the results uses this type of qualitative analysis which sees how the similarity of the frequency range on the FFT of EMG research results with standard EMG in hospitals. The results obtained are the same frequency range at 15 – 450 Hz.

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Improvement Suggestion Performance of Blowing Machine Line 4 with Total Productive Maintenance (TPM) Method at PT. Coca-Cola Amatil Indonesia MedanUnit 1

Improvement Suggestion Performance of Blowing Machine Line 4...

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1st International Conference of SNIKOM 2018, ICoSNIKOM 2018

作者： Irwansyah, Defi Harahap, M.R.F. Erliana, Cut Ita Abdullah, Dahlan Sari, Ayuesteka Siregar, Nurintanasyiah Achmaddaengs, G.S. Indahingwati, Asmara Sumartono, Eko Wilujeng, Sri Nurmawati Subekti, Purwo Kurniasih, Nuning Rosalina, Febrianti Hartono, H. Departement of Industrial Engineering Universitas Malikussaleh Aceh Indonesia Departement of Informatics Universitas Malikussaleh Aceh Indonesia Department of Management STIE Sakti AlamKerinci Jambi Indonesia Department of Management STIE Labuhanbatu Sumatera Utara Indonesia Department of Management Universitas 45 Surabaya Indonesia Department of Management School of Economics Indonesia STIESIA Surabaya Indonesia Faculty of Agriculture Universitas Bengkulu Bengkulu Indonesia Department of Management Faculty of Economy Universitas Kanjuruhan Malang Indonesia Program Study of Industrial Engineering University of 45 Surabaya Indonesia Mechanical Engineering Pasir Pengaraian University Riau Indonesia Faculty of Communication Sciences Library and Information Science Program Universitas Padjadjaran Bandung Indonesia Department of Agrotechnology Universitas Muhammadiyah Sorong Sorong Indonesia Department of Computer Science STMIK IBBI Medan Indonesia

Maintenance is an activity to maintain facilities or equipment of the factory and make repairs or adjustments to the necessary replacement to satisfactory condition of production operations in accordance with what is planned. Companies often experience damage to the Blowing machine so that interconnected machines cannot be operated. The purpose of this study was to improve the performance of Blowing line 4 engines with the Total Productive Maintenance (TPM) method at PT. Coca-Cola Amatil Indonesia Medan Unit, also to determine the level of Blowing machine performance based on the analysis of overall equipment effectiveness (OEE) at PT. Coca-Cola Amatil Indonesia Medan Unit. The method used in this study is the overall equipment effectiveness (OEE) method to measure Ishikawa's treatments and diagrams to compare and propose low engine performance. The results of data processing shows machine maintenance has not comply the OEE standards in July 81.48%, August 81.48%, September 78.07%, October 81.22%, November 78.08%, and those that fill the standards in June amount to 86.48%, with losses that most affect the effectiveness of equipment in line 4 blowroom machine is Equipment Failure Losses of 11.42% based on the results of the study, the proposed improvement in engine performance is to provide training to employees, and increase operator awareness. against engine damage, thus the production process will run smoothly. © Published under licence by IOP Publishing Ltd.

关键词： Data handling

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Optimization of biogas production in Indonesian region by liquid anaerobic digestion (L-AD) method from rice husk using response surface methodology (RSM)

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IOP Conference Series: Materials science and engineering 2020年第1期845卷

作者： W D Nugraha Syafrudin V N Kusumastuti H H A Matin Budiyono Environmental Engineering Department Engineering Faculty Diponegoro University Semarang Indonesia Environmental Science Study Program Faculty of Science and Mathematic Sebelas Maret University Surakarta Indonesia Chemical Engineering Department Engineering Faculty Diponegoro University Semarang Indonesia

Rice husk is one of agricultural waste that is potentially converted to biogas. In this research, rice husk is used as the material to produce biogas by liquid anaerobic digestion (L-AD) with TS concentration below 15/5. The purposes of this research are finding the optimum value of total solid (TS), C/N ratio, and microbial consortium (MC) for biogas production and then analyzing the optimum biogas production rate from rice husk. Because of the high lignin content, rice husk must be through the pretreatment stage using NaOH 3%. The variations of the observed factor are 5%, 10%, 15% for TS concentration; 20, 35, 50 for C/N ratio; and 3%, 6%, 9% for MC concentration. There are 16 reactors in which the variation for each reactor was determined by Central Composite Design. Data obtained from the research will be optimized using Response Surface Methodology (RSM) in Statistica 10. The result shows that the optimum condition of biogas production from rice husk is TS in between 1%-2.5%, C/N ration 33.45, and MC in between 5.5%-7%. Reactor having a combination of value factors that close to the optimum value will be analyzed using Polymath 6.0, which is reactor 10. The kinetics constant of biogas production rate (u) is 3.625 ml/***, the maximum biogas production (A) is 277.374 ml/gr TS, and the minimum time needed to produce biogas (λ) is 3.878 days.

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Timor natural clay as TiO2 modifier to enhance DSSC efficiency using dye chlorophyll from Leucaena leucocephala (Lam.), chromolaena odorata and lannea coromandelica leaves

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AIP Conference Proceedings 2021年第1期2370卷

作者： Odi Th. E. Selan Anika E. Sari Arty N. Manafe Mares J. Nobrihas Antonius R. B. Ola Reiner I. Lerrick Alfius R. Kale 1)Chemistry Study Program Faculty of Science and Engineering Nusa Cendana University Jalan Adisucipto Penfui Kupang – NTT 85110 Indonesia 2)Bioscience Laboratory Nusa Cendana University Jalan Adisucipto Penfui Kupang – NTT 85110 Indonesia

The improvement of dye sensitized solar cell (DSSC) efficiency using clay from Timor to modify TiO2 semiconducting material with chlorophyll dyes as photosensitisers had been conducted. This investigation employed doctor blade method for photoelectrochemical cell design and testing using chlorophyll from three different plant leaves namely Leucaena leucocephala (Lam.), (A), Lannea coromandelica (B) and Cromoleana Odorata (C). Infra-Red, X-Ray Fluorescence and X-Ray Diffraction analysis show that the main chemical compositions of the clay are SiO2 (53%), Fe2O3 (22,2%) and Al2O3 (13%) identified as a typical bentonite clay. We found that the addition of clay onto TiO2 increased the efficiency of cells using these three different source of chlorophylls (A - from 0.0437 to 0.7502%, B - from 1.203 to 1.450% and C - from 0.034 to 0.284%) potential for further purifications or activations and applications.

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Simulation and computational analysis of fire sprinkle bulb activation with variation of liquid and wall thickness

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AIP Conference Proceedings 2020年第1期2314卷

作者： Alfian Pramudita Putra Erik Jan Westerman Akif Rahmatillah 1Biomedical Engineering Study Program Department of Physics Faculty of Science and Technology Universitas Airlangga Surabaya Indonesia 2Department of Biomedical Engineering Faculty of Science and Engineering University of Groningen Groningen The Netherlands

Fire sprinkler is a safety system that is active when fire is detected. It consists of a bulb that holds the water flow and made of glass with liquid inside. The increase of temperature in its environment would expand the volume of the liquid and break the glass which leads to water spray to extinguish the fire. This study aims to model and simulate the fire sprinkler bulb and optimize several parameters related to its activation including the thickness of the bulb, type of liquid and the ratio of air and liquid inside the bulb. The modeling and simulation was performed in COMSOL Multiphysics with variation of wall thickness and liquid inside the bulb. The result showed that the best parameter was the liquid of glycerol, a height of 17.5 mm and a glass thickness of 0.1 mm, this resulted in the air to liquid ratio of 0.0042428 and breaking time of 7.2400s. This result was the fastest breaking time towards several simulations. For future study, several parameters need to be considered in the simulation to minimize the gap between the simulation and the actual condition, such as room condition, and water pressure.

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Pulmonary Disease Pattern Recognition on X-Ray Radiography Image Using Artificial Neural Network (ANN) Method

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Journal of Physics: Conference Series 2020年第1期1505卷

作者： N Fitriyah L D Kurniawati E Purwanti S D Astuti Department of Physics Faculty of Science and Technology Universitas Airlangga Surabaya Indonesia 60115 Biomedical Engineering Study Program Faculty of Science and Technology Universitas Airlangga Surabaya Indonesia 60115 Department of Biomedical Engineering Post-Graduate Program Faculty of Science and Technology Universitas Airlangga Surabaya Indonesia 60115

This research aims to recognize the pattern of pulmonary disease on x-ray radiography image using artificial neural network (ANN) method. The images, which were used such as images of healthy pulmonary, pulmonary tuberculosis, and pulmonary tumour. Pattern recognition was using an extraction feature of GLCM (Gray Level Co-occurrence Matrix) and back propagation method. Before being identified, the images were processed by median filter and adaptive histogram equalization. The GLCM features that used were homogeneity, energy, contrast, variance and correlation. The parameters were learning rate and hidden layer. Learning rate was 0.3 and hidden layer was 25. Back propagation training showed 100% accuracy, which all of 44 images were used had been successfully identified. From the result, the healthy pulmonary showed 60% accuracy, 83.3% for pulmonary tuberculosis and 100% for pulmonary tumor. Hence, the overall result showed 81.25% accuracy, which 13 of 16 images had been successfully identified. From these result, extraction feature of GLCM using back propagation method was capable to recognize the pattern of pulmonary disease. However, due to narrow range of the feature, this application may not be used optimally for comparing features in every category of images. Therefore, the further research is needed to determine the best features and parameters of training back propagation.

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