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Pattimura Proceeding : Conference of Science and Technology
Published by Universitas Pattimura
ISSN : -     EISSN : 28293770     DOI : https://doi.org/10.30598/PattimuraSci.2021.KNMXX
Core Subject : Science, Education, Agriculture, Engineering,
Agriculture, Biological Sciences & Forestry Astronomy Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Control & Systems Engineering Energy Engineering Materials Science & Nanotechnology Mathematics Physics
This journal is created to archieve collection of publications from a national or international seminar at Pattimura University for Science, Technology, and Its Applications
Arjuna Subject : Umum - Umum
Articles 18 Documents
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Search results for , issue "2017: Proceedings of the 3rd International Seminar of Basic Science" : 18 Documents clear
THE USE AS BIO-INDICATORS SPONGE Callispongia sp. HEAVY METALS CD METAL CONTAMINATION IN THE WATERS OF THE AMBON BAY A. N. Siahaya; Alfian Noor; Nicole de Voogd
Pattimura Proceeding 2017: Proceedings of the 3rd International Seminar of Basic Science
Publisher : Pattimura University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (453.357 KB) | DOI: 10.30598/PattimuraSci.2017.ICBS3.089-094

Abstract

The deposition of heavy metals in Ambon Bay was investigated by using sponge species (Callispongia sp.) as bioindicator. Two different sampling schemes are discussed in this paper: a random sampling scheme with 8 sampling sites distributed over the whole territory of Ambon Bay. Unwashed, dried samples were totally the concentrations of metal elements were determined by inductively coupled plasma atomic emission spectroscopy (ICP-AES). Heavy metal Cd. The median concentrations and statistical parameters of elements were discussed by comparing two sampling schemes. The results of both sampling schemes are compared with the results of other the location of the net. Different levels of the contamination valuated by the respective contamination factor (CF) of each element are obtained for both sampling schemes, while the local contamination identified like cadmium metallurgy and cement industry, oil refinery, mining industry, and transport have been the same for both sampling schemes. In addition, the natural sources, from the accumulation of these metals in sponge caused by metal-enriched soil, associated with activity in the land were pointed as another possibility of local factors.
ANALYSIS OF SEAWEED CARBOHYDRATE Eucheuma cottonii AND EFFECT ON THE HYDROLYSIS PROCESS AND FERMENTATION TIME IN PRODUCING BIOETANOL Voulda D Loupatty
Pattimura Proceeding 2017: Proceedings of the 3rd International Seminar of Basic Science
Publisher : Pattimura University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (387.234 KB) | DOI: 10.30598/PattimuraSci.2017.ICBS3.095-100

Abstract

Research "Analysis of Seaweed Carbohydrate Eucheuma cottonii and Its Influence on Hydrolysis Process and Fermentation Time in Produce Bioethanol", conducted with the aim to know the value of carbohydrate seaweed type Eucheuma cottonii to get the correct hydrolysis and fermentation techniques so that the bioethanol produced more optimal. Seaweed bioethanol production process is liquefaction, scarification and fermentation. The tests were performed at each stage of bioethanol production including carbohydrate and glucose using SNI (1992), PH using PH meter, sugar content using refractometer (brix) and alcohol content using Alcoholmeter. Testing alcohol levels performed on fermentation day 3rd, 4th and 5th. The results showed that the functional component of carbohydrate constituent seaweed type Eucheuma cottonii is kappa carrageenan. Technical hydrolysis in the production of bioethanol is water, because water is the main carrageenan solvent. The best fermentation time is on the 5th day with 7% bioethanol content.
SIMPLE VISUALIZATION THEORY FOR INVESTIGATING THE MECHANICAL BEHAVIOR OF A NOVEL FIBER Julian Lord Natasian; Hendry Izaac Elim
Pattimura Proceeding 2017: Proceedings of the 3rd International Seminar of Basic Science
Publisher : Pattimura University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1339.532 KB) | DOI: 10.30598/PattimuraSci.2017.ICBS3.101-116

Abstract

In this paper, a simple theoretical and visualized explanation of a novel fiber with their mechanical behaviors have been derived to investigate a novel fabricated fibers made by the changing a natural garbage structure. By solving a simple string theory consisted of two to three coupled differential equations, the internal frequencies (w) and the fiber string constants (k) of two different fiber structures which have a uniform fiber structure and a not uniform fibers structure, respectively were obtained as follows: ω1,2 = ± 7.312 Hz, for the value of k1 = k2 = k = 0.46 kg/s2, and ω1,2 = ± 12.657 Hz, for the values of k1 = 0.5 kg/s2, and k2 = 0.426 kg/s2. While the w and k of three different fiber structures in one fiber were found in the following values: ω1,2 = ± 7.313 Hz, for k1 = 1.974 kg/s2, k2 = 0.353 kg/s2, and k3 = 0.989 kg/s2 , and ω1,2 = ± 7.313 Hz, for the value of k1 = k2 =k3 = k = 0.69 kg/s2, respectively. In addition, by incorporating a scientific mathematica 10.3 software, the visualizations from the coupled-two and coupled-three differential equations closely related to mechanical fiber behaviors produce the amplitude (A) ratio in those coupled equations.
ALCOHOL CONCENTRATION DETECTOR IN LIQUOR BASED ON MICROCONTROLLER Mirtha Y. S. Risakotta; Ronaldo Talapessy; Rosita De Fretes
Pattimura Proceeding 2017: Proceedings of the 3rd International Seminar of Basic Science
Publisher : Pattimura University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (747.731 KB) | DOI: 10.30598/PattimuraSci.2017.ICBS3.117-122

Abstract

Has made an alcohol concentration detector based on microcontroller that can detect alcohol concentration in liquor is accurate, fast, stable and has a high sensitivity. In this research, use traditional liquor of Moluccas “Sopi”, and liquors on the market. An alcohol concentration detector was built based on microcontroller ATmega16 which can receive and process data from the sensor MQ-3 in a form that can be converted into the form of an electrical signal and the output is displayed on the LCD. Calibration of the sensor MQ-3 shows that the greater the value of resistance sensor, the smaller the value of an alcohol concentration. The correlation of resistance sensor to alcohol concentration is plotted in a graph of linearity with R2 = 0,9982. The results of liquor on the market and Sopi (premium quality) had alcohol concentration ranging between 3 – 5% per mL, while an alcohol concentration of Sopi (regular quality) is below 3% per mL.
CONVERSION OF SUGARS INTO 5-HMF Amutha Chinnappan; Shikha Baskar; Chinnappan Baskar
Pattimura Proceeding 2017: Proceedings of the 3rd International Seminar of Basic Science
Publisher : Pattimura University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (378.182 KB) | DOI: 10.30598/PattimuraSci.2017.ICBS3.123-130

Abstract

At present, fossil fuels are playing the major role to meet the energy requirements of the world. The large consumption of fossil fuels creates so many environmental problems, such as green-house gases have motivated the search for alternative, renewable fuel options. Biomass is one of the few resources that have the potential to meet the challenges of sustainable and green energy systems. Current biomass resources comprise primarily industrial waste materials such as sawdust or pulp process wastes, hog fuel, forest residues, clean wood waste from landfills, and agricultural prunings and residues from plants such as lignocellulosic materials. There are already a considerable range of chemical building blocks derived from renewable resources. Among them, 5-hydroxymethylfurfural (HMF) is a versatile platform chemical for the synthesis of a wide range of industrially important materials, including biofuels.
APPLICATION OF ARTIFICIAL NEURAL NETWORK BACKPROPAGATION TO PREDICT HOUSEHOLD CONSUMPTION OF ELECTRICITY IN AMBON S. H. Saija; Y. A. Lesnussa; F. Kondolembang
Pattimura Proceeding 2017: Proceedings of the 3rd International Seminar of Basic Science
Publisher : Pattimura University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (510.174 KB) | DOI: 10.30598/PattimuraSci.2017.ICBS3.131-138

Abstract

Electricity is one of the energy most widely used in the universe. Electric power demand in Ambon city tends to increase due to the growing of population in Ambon. The necessary of electricity power in Ambon City by utilizing two systems are interconnected such as: PLTD Poka and PLTD Hative Kecil (Galala). In this research forecast the demand for household electricity consumption in 2016 based on validation data from 2011-2015 using Application of Neural Networks Backpropagation method. The validation data are using in JST-Backpropagation training, with the best network architecture that is 20 10 5 1 neurons and 0.8 learning rate, can produce the best pattern with the accuracy is 75% and the value of Mean Square Error is 0.298335.
APPLICATION OF ARTIFICIAL NEURAL NETWORK BACKPROPAGATION FOR PREDICTING THE AVAILIBILITY OF PREMIUM FUEL (CASE STUDY: PREDICTION OF PREMIUM FUEL AVAILIBILITY ON SPBU GALALA AMBON) Vicky Riyadi; E. R. Persulessy; Y. A. Lesnussa
Pattimura Proceeding 2017: Proceedings of the 3rd International Seminar of Basic Science
Publisher : Pattimura University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (660.463 KB) | DOI: 10.30598/PattimuraSci.2017.ICBS3.139-148

Abstract

This study aims to predicting the availability of premium fuel using pattern recognition techniques named neural network with backpropagation method. Neural network is used to give solution for many problem, including taking a decision from the training data. Neural network can be applied to various specific fields of human life. In this study, Neural Network is used to predict the availability of premium fuel using backpropagation method. The data which is used in this study consist of 48 data, where 36 data (years 2012-2014) as training and 12 data (years 2015-2016) as testing. The result shows that the availability of premium fuel in 2017 for 12 months with the prediction results availability in January 2017 is 337490 kL and December 2017 is 344120 kL. It can be seen that the prediction results to be achieved fully met with a small error rate and the level of accuracy 83.33% where the results of the testing data showed the value of Mean Square Error for prediction the availability of premium fuel in 2017 is and also to the process of training produces the best network architecture with hidden layer 20 10 5 1 neurons and the best training algorithm by using learning rate 0.74 with MSE 0.00100. Thus, Backpropagation method is pretty well in predicting the availability of fuel.
THE TOTAL IRREGULARITY STRENGTH OF SOME COMPLETE BIPARTITE GRAPHS Pranaya D. M. Taihuttu; Meilin I. Tilukay; F. Y. Rumlawang; Z. A. Leleury
Pattimura Proceeding 2017: Proceedings of the 3rd International Seminar of Basic Science
Publisher : Pattimura University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (627.593 KB) | DOI: 10.30598/PattimuraSci.2017.ICBS3.149-157

Abstract

This paper deals with the total irregularity strength of complete bipartite graph where and .

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