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Science and Technology Indonesia

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Published by Universitas Sriwijaya

ISSN : 25804405 EISSN : 25804391 DOI : -

Core Subject : Science, Social, Engineering,

Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Environmental Science Materials Science & Nanotechnology Physics

An international Peer-review journal in the field of science and technology published by The Indonesian Science and Technology Society. Science and Technology Indonesia is a member of Crossref with DOI prefix number: 10.26554/sti. Science and Technology Indonesia publishes quarterly (January, April, July, October). Science and Technology Indonesia is an international scholarly journal on the field of science and technology aimed to publish a high-quality scientific paper including original research papers, reviews, short communication, and technical notes. This journal welcomes the submission of articles that covers a typical subject of natural science and technology such as: > Chemistry > Biology > Physics > Marine Science > Pharmacy > Chemical Engineering > Environmental Science and Engineering > Computational Engineering > Biotechnology Journal Commencement: October 2016

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Articles 551 Documents

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Simulation Study of Autocorrelated Error Using Bayesian Quantile Regression Nayla Desviona; Ferra Yanuar
Science and Technology Indonesia Vol. 5 No. 3 (2020): July
Publisher : Research Center of Inorganic Materials and Coordination Complexes, FMIPA Universitas Sriwijaya

The purpose of this study is to compare the ability of the Classical Quantile Regression method and the Bayesian Quantile Regression method in estimating models that contain autocorrelated error problems using simulation studies. In the quantile regression approach, the data response is divided into several pieces or quantiles conditions on indicator variables. Then, The parameter model is estimated for each selected quantiles. The parameters are estimated using conditional quantile functions obtained by minimizing absolute asymmetric errors. In the Bayesian quantile regression method, the data error is assumed to be asymmetric Laplace distribution. The Bayesian approach for quantile regression uses the Markov Chain Monte Carlo Method with the Gibbs sample algorithm to produce a converging posterior mean. The best method for estimating parameter is the method that produces the smallest absolute value of bias and the smallest confidence interval. This study resulted that the Bayesian Quantile method produces smaller absolute bias values and confidence intervals than the quantile regression method. These results proved that the Bayesian Quantile Regression method tends to produce better estimate values than the Quantile Regression method in the case of autocorrelation errors. Keywords: Quantile Regression Method, Bayesian Quantile Regression Method, Confidence Interval, Autocorrelation.

Quantile Regression Approach to Model Censored Data Sarmada Sarmada; Ferra Yanuar
Science and Technology Indonesia Vol. 5 No. 3 (2020): July
Publisher : Research Center of Inorganic Materials and Coordination Complexes, FMIPA Universitas Sriwijaya

Abstract The censored quantile regression model is derived from the censored model. This method is used to overcome problems in modeling censored data as well as to overcome the assumptions of linear models that are not met. The purpose of this study is to compare the results of the analysis of the quantile regression method with the censored quantile regression method for censored data. Both methods were applied to generated data of 150, 500, and 3000 sample size. The best model is then chosen based on the smallest absolute bias and the smallest standard error as an indicator of the goodness of the model. This study proves that the censored quantile regression method tends to produce smaller absolute bias and a smaller standard error than the quantile regression method for all three group data specified. Thus it can be concluded that the censored quantile regression method could result in acceptable model for censored data. Keywords: Censored data; quantile regression; quantile regression censored; standard error; absolute bias.

Improved the Cans Waste Classification Rate of Naïve Bayes using Fuzzy Approach Yulia Resti; Firmansyah Burlian; Irsyadi Yani; Des Alwine Zayanti; Indah Meiliana Sari
Science and Technology Indonesia Vol. 5 No. 3 (2020): July
Publisher : Research Center of Inorganic Materials and Coordination Complexes, FMIPA Universitas Sriwijaya

Cans is one type of inorganic waste that can take up to hundreds of years to be decomposed on the ground so that recycling is the right solution for managing cans waste. In the recycling industry, can classification systems are needed for the sorting system automation. This paper discusses the cans classification system based on the digital images using the Naive Bayes method, where the input variables are the pixel values of red, green, and blue (RGB) color, and the image of the can is captured by placing it on a conveyor belt which runs at a certain speed. The average accuracy rate of the k-fold cross-validation which is less satisfactory from the classification system obtained using the original Naive Bayes model is corrected using the fuzzy approach. This approach succeeded in improving the average accuracy of the can classification system which was originally from 52.99% to 88.02% or an increase of 60.2%, where the standard deviation decreased from 15.72% to only 3%. Cans is one type of inorganic waste that can take up to hundreds of years to be decomposed on the ground so that recycling is the right solution for managing cans waste. In the recycling industry, can classification systems are needed for the sorting system automation. This paper discusses the cans classification system based on the digital images using the Naive Bayes method, where the input variables are the pixel values of red, green, and blue (RGB) color, and the image of the can is captured by placing it on a conveyor belt which runs at a certain speed. The average accuracy rate of the k-fold cross-validation which is less satisfactory from the classification system obtained using the original Naive Bayes model is corrected using the fuzzy approach. This approach succeeded in improving the average accuracy of the can classification system which was originally from 52.99% to 88.02% or an increase of 60.2%, where the standard deviation decreased from 15.72% to only 3%.

Transesterification Reaction from Rice Bran Oil to Biodiesel over Heterogeneous Base Calcium Oxide Nanoparticles Catalyst Nur Fatin Sulaiman; Abdul Rahim Yacob; Siew Ling Lee
Science and Technology Indonesia Vol. 5 No. 3 (2020): July
Publisher : Research Center of Inorganic Materials and Coordination Complexes, FMIPA Universitas Sriwijaya

This research focused on the use of heterogeneous base catalyst, calcium oxide (CaO), an alkaline earth metal oxide to produce biodiesel. The aim of this research is to investigate the potential of commercial calcium carbonate, CM-CaCO3 to be transformed to nanostructured CaO and further used as a heterogeneous base catalyst for single step transesterification of rice bran oil to biodiesel. The CaO samples were calcined at temperatures of 100°C to 700°C under vacuum at 10-3 mbar. TGA-DTA result displayed that the calcination temperature for CM-CaCO3 to form CaO must be higher than 600°C. This was supported by FTIR results which indicated the complete formation of CaO at 700°C. XRD showed the rhombohedral CaCO3 and hexagonal Ca(OH)2 were totally disappeared, leaving only crystalline cubic CaO at 700oC. Interestingly, CaO obtained at 700°C (CaO-700) showed the larger BET surface area and highest basicity with 11.5 m2g-1 and 1.959 mmol/g, respectively. The prepared nanostructured CaO-700 was selected and applied for single step transesterification reaction of rice bran oil to produce biodiesel. NMR and GC-FID results further confirmed that biodiesel was successfully formed using CaO-700 as catalyst.

The Chitosan-Sodium Alginate Submicro Particles Loading Herbal of Ethanolic Exract of Leaves Senna Alata. L for Curing of Bacterial Infection on Skin Mardiyanto Mardiyanto; Indah Sholihah; Thio Gunawan Jaya
Science and Technology Indonesia Vol. 5 No. 3 (2020): July
Publisher : Research Center of Inorganic Materials and Coordination Complexes, FMIPA Universitas Sriwijaya

Abstract Mardiyanto 1*, Indah Solihah 1, and Thio Gunawan Jaya 1 1Department of Pharmacy Faculty of Science Sriwijaya University *Corresponding Author : mardiyantoUNSRI@gmail.com This research was performed to detect the activity of the optimum formula of chitosan and sodium alginate submicro particles loading of the ethanol extract of leaves ketepeng cina (Senna alata L.) to P. acne growth. Submicro manufactured particles was used three variations of the formula from three of volume used of calcium chloride (CaCl2): 20, 40, and 100 mL based on ionic gelation method. The results obtained of %EE in formulas 1, 2 and 3 were 78.56%, 81.71%, and 77.48%. Formula 2 with a value of % EE of 81.71% was used as an optimum formula which indicates that the particles are well protected by chitosan and sodium alginate polymers so as to prevent particle damage during the homogenization process. The results of the diameter measurements showed that the optimal formula enters in the submicro particle range with the value obtained is 525,9455 nm. The submicro formula of chitosan alginate particles loading the ketepeng cina leaf ethanol extract was barely homogeneous which based on the results obtained by the PSA was 0.433 of PDI. The zeta potential value was +3.5 mV. The results of X-ray diffraction analysis or X ̶ Ray Diffraction produce a pattern shaped amorph with the resulting peak does not have a wide distance and pattern. In vivo testing using ketepeng cina leaf extract as submicro was decreased the P. acne lesion faster than using only ketepeng cina leaf extract because the submicro particle preparation has a small particle that is below to 600 nm making it easier to penetrate the skin pores to reach the target. The results of the analysis of the curing of many lesions on the skin of mice have a significance value of homogeneity. The one-way ANOVA test of < 0.05 was a significant effect of the test group on the decreasing in the number of lesions on the skin of the mouse.

Surface Wave Topography using The 4 Point FDM Simulator Adi Jufriansah; Yudhiakto Pramudya; Arief Hermanto; Azmi Khusnani
Science and Technology Indonesia Vol. 5 No. 4 (2020): October
Publisher : Research Center of Inorganic Materials and Coordination Complexes, FMIPA Universitas Sriwijaya

The 2D topography proffers a new challenge of modeling surface waves with a 4-point finite difference (FDM) model. Topographic representation of wave propagation over a certain area will result in loss of accuracy of the numerical model. Then from this the need for appropriate modifications to reduce calculation errors. The existing approach requires value representation as an internal extrapolation solution for temporary exterior conditions. It is finally by providing boundary conditions and initial conditions in the system. However, the scheme sometimes becomes unstable for very irregular topography. 1D extrapolation along the parallel path is known to produce a simple and efficient scheme. During extrapolation, the stability of the 1D hyperbolic Schema improved by disregarding the nearest interior boundary point, which is less than half the lattice distance. Given the limited difference so that the stencils from both sides of the central evaluation point can be used as a 2D form modification if there are not enough inside points. So that in propagation space, waves that move and change according to changes in time. It will be following the wave nature of one source that travels in the x and y fields whose amplitude will change exponentially against propagation time. It is by the nature of surface wave motion.

Set Covering Model in Solving Multiple Cutting Stock Problem Sisca Octarina; Devi Gusmalia Juita; Ning Eliyati; Putra Bahtera Jaya Bangun
Science and Technology Indonesia Vol. 5 No. 4 (2020): October
Publisher : Research Center of Inorganic Materials and Coordination Complexes, FMIPA Universitas Sriwijaya

Cutting Stock Problem (CSP) is the determination of how to cut stocks into items with certain cutting rules. A diverse set of stocks is called multiple stock CSP. This study used Pattern Generation (PG) algorithm to determine cutting pattern, then formulated it into a Gilmore and Gomory model and solved by using Column Generation Technique (CGT). Set Covering model was generated from Gilmore and Gomory model. Based on the results, selected cutting patterns in the first stage can be used in the second stage. The combination of patterns generated from Gilmore and Gomory model showed that the use of stocks was more effective than Set Covering model.

Characteristics of Diurnal Rainfall over Peatland Area of South Sumatra, Indonesia Puad Maulana Mandailing; Wijaya Mardiansyah; Muhammad Irfan; Arsali Arsali; Iskhaq Iskandar
Science and Technology Indonesia Vol. 5 No. 4 (2020): October
Publisher : Research Center of Inorganic Materials and Coordination Complexes, FMIPA Universitas Sriwijaya

The peak time of rainfall occurrence over an area has certain characteristics in which the difference in time and intensity of rainfall varies depending on its location and distance from the sea. This variation can be determined based on the phase and amplitude obtained using harmonic analysis. In this study, combined data from in-situ observation, satellite remote sensing and reanalysis were used to analyze spatial and temporal variations of peak rainfall events over peatland area of the South Sumatra Province. The results show that most of the South Sumatra Province has a diurnal peak of rainfall during afternoon ranging from 16.00 to 19.00 Western Indonesian Time. In addition, the results also indicate that the analysis on the in situ data revealed seasonal variation both in amplitude and time of maximum diurnal rainfall, while the reanalysis data only indicated a weak seasonal variation on the amplitude of the diurnal rainfall. Furthermore, spatial analysis shows that the time of maximum diurnal rainfall has spatial variation. Over the ocean, the time of maximum diurnal rainfall occurs during night time/early morning. Over the lowland or coastal area, the time of maximum diurnal rainfall occurs during afternoon, while over the high altitude (mountain) it occurs during late night.

Performance of Cans Classification System for Different Conveyor Belt Speed using Naïve Bayes Yulia Resti; Firmansyah Burlian; Irsyadi Yani
Science and Technology Indonesia Vol. 5 No. 4 (2020): October
Publisher : Research Center of Inorganic Materials and Coordination Complexes, FMIPA Universitas Sriwijaya

The classification system in the sorting process in the can recycling industry can be made based on digital images by exploring the basic color pixel values of images such as R, G, and B as variable inputs. In real time, the classification of cans in the sorting process occurs when cans placed on a conveyor belt move at a certain speed. This paper discusses the performance of can classification systems using the Naïve Bayes method. This method can handle all types of variables, including when all variables are continuous. Two types of conveyor belts are designed to get different speeds, and all images of the cans are captured on both conveyor belts. Two models of Bayes naive are built on the basis of the different distribution assumptions; the original model (all Gaussian distributed) and the model based on the best distribution. Performance of the classification system is built by dividing data into the learning data and the testing data with a composition of 50:50 in which each data is designed into 50 groups with different percentages on each type of cans using sampling technique without replacement. The results obtained are, first, the speed of the conveyor belt when capturing an image affects the pixel values of red, green, and blue and ultimately affects the results of the classification of cans. Second, not all input variables are Gaussian distributed. The classification system was built using assumption the best distribution model for each input variable has the better average accuracy level than the model that assumes all input variables are Gaussian distributed, and the accuracy level of classification on the first speeds of conveyor belt with a gear ratio of 12:30 and a diameter of 35 mm has an accuracy that is better than the other speed, both on the original model and the model based on the best distribution. However, it is necessary to test more statistical distribution models to obtain significant results.

Enumerating the Number of Connected Vertices Labeled Graph of Order Six with Maximum Ten Loops and Containing No Parallel Edges Wamiliana Wamiliana; Amanto Amanto; Mustofa Usman; Muslim Ansori; Fadila Cahya Puri
Science and Technology Indonesia Vol. 5 No. 4 (2020): October
Publisher : Research Center of Inorganic Materials and Coordination Complexes, FMIPA Universitas Sriwijaya

A Graph G (V, E) is said to be a connected graph if for every two vertices on the graph there exist at least a path connecting them, otherwise, the graph is disconnected. Two edges or more that connect the same pair of vertices are called parallel edges, and an edge that starts and ends at the same vertex is called a loop. A graph is called simple if it containing no loops nor parallel edges. Given n vertices and m edges, m ≥ 1, there are many graphs that can be formed, either connected or disconnected. In this research, we will discuss how to calculate the number of connected vertices labeled graphs of order six (isomorphism graphs are counted as one), with a maximum loop of ten without parallel edges.

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