bluuebunny/crossref_metadata_2025 huggingface dataset:
Design of Sliding Mode Controller for Tilting Quadrotor UAV Based on Predetermined Performance
Authors: Zhou Wen , Wang Xiaoping , Wang Xiaoguang , Wang Wenhua , Liu Bo
Published: January 2021

Aiming at the influence of modeling error and uncertain interference such as external sidewind in the control system of tilting quadrotor UAV, a non-singular fast terminal sliding mode controller based on predetermined performance is designed for its vertical take-off and landing mode. Firstly, based on the classical mechanics theory, the nonlinear dynamics model of tilt-rotor UAV in vertical take-off and landing mode was established. Then, on the basis of the non-singular fast terminal sliding mode controller, the predetermined performance function was introduced to make the system error within the specified performance range, and the final bounded convergence of the tracking error in the closed-loop system was proved based on the Lyapunov stability theory. Finally, the simulation experiment was carried out in MATLAB/Simulink. The simulation results show that the designed method can still achieve the stable tracking of the predetermined trajectory under the circumstance of uncertain external interference, and it has good control performance and anti-interference ability.
Human Motion State Recognition Based on Multi-input ConvLSTM
Authors: Yiming Zhang , Liuai Wu
Published: January 2021

The human body generates acceleration signals during movement. After collecting and processing this signal, the movement state of the human body can be analyzed and the behavior of the human body can be judged. Human motion state recognition has a wide range of applications in fields such as health monitoring, somatosensory games, and user social behavior analysis. In this paper, the UCI data set collected by mobile phone sensors is used to build the model using convolutional long and short-term memory neural network (ConvLSTM) combined with multi-input CNN (Multi-head CNN), and combined with long and short-term memory neural network (LSTM) and convolutional memory Neural network (ConvLSTM) for comparative evaluation. The accuracy of the model in this paper reached 93.75%. Experimental results show that the new algorithm can more accurately classify and recognize the human motion state.
A Simulation Study on the Reentrant Waves in the Pacing Ventricular Tissues
Authors: Zhang Yue , Shi Xibo , Sui Dong
Published: January 2021

The aim of the study is to investigate the relationship between the reentrant waves and I
K1, and probe the effect of I
K1 on the reentrant waves. Firstly, based on the TNNP06 model, the single pacing cell is derived by depressing I
K1. And then, a 400 cells ×400 cells 2D tissue is developed by coupling the pacing cells together. Thirdly, the S1-S2 protocol is applied to inspire the reentrant waves. Next, the processes of the reentrant waves in the tissue corresponding to different I
K1 are analysed. In addition, the action potentials of the cells in special locations are recorded and discussed. With the decrease of the I
K1, the reentrant waves spin slowly and the period of reentrant waves increases. Meanwhile, the range of the action potential of the cells becomes larger when I
K1 becomes smaller. The results suggest that with the decrease of I
K1, the reentrant wave is weakened, and the systolic and diastolic functions of the tissue are enhanced at the same time.
High precision on-line liquid level detection system based on microwave penetration method
Authors: Wang Hui , Meng Fanmeng , Xu Changbin , Xu Lenian
Published: January 2021

In order to meet the high precision and low cost of liquid level detection for bottled drinks in industrial production line, based on microwave transmission principle a liquid level detection method was designed on the basis of radar level meter. The rectangular microstrip antenna sent and received specific microwave signals. The signal was processed by the embedded ARM(Advanced RISC Machines) processor and digital signal processing method, and finally the data was transmitted. It was verified by experiments that the microwave penetration method can be used for liquid level detection, and the detection accuracy can reach ±1mm. Due to the use of microwave for measurement, the system has high stability and can be applied to the liquid level detection of bottled drinks on the production line.
Numerical method in riemann invariant form for a submerged bar breakwater model
Authors: Magdalena I , Rif’atin H Q , Kristianto I J
Published: January 2021

Recently, Geotextiles are widely used for coastal protection in Indonesia. Geotextile is one of the implementations of a submerged bar as a breakwater. Here, we will study the damping mechanism of the Geotextile to reduce the incoming wave amplitudes through a mathematical model. The model that we use based on the Shallow Water Equations. Analytical solutions for wave transmission coefficient are derived using the Separation of Variables Method. Numerically, we construct a scheme using the Riemann Invariant Method to approximate the analytical model. For validation, the numerical results are compared against the analytical wave transmission coefficient, which resulted in a very good agreement between the two findings. Further, we investigate the effect of the changes in the dimension of a submerged bar to the reduction of the transmitted wave amplitude.
Incident and reflected wave separation on wave propagation over breakwater
Authors: Magdalena I , Atras M F
Published: January 2021

The quantification of the reflection waves is of paramount importance in coastal engineering. The reflection wave that affects the incoming waves over time will gradually affect the calculation of the transmitted waves after passing through a submerged breakwater. In this study, the reflection waves that affect the incident waves will be separated so that the appropriate transmission coefficient is obtained. The accuracy of this separation method of the incident waves and reflections will be evaluated using a numerical scheme. The numerical scheme that we use here is a staggered finite volume method. A small error in the comparison indicates the wave separation process is good enough to produce a reflection coefficient following the numerical results.
Survival analysis with the Cox Proportional Hazard Method to determine the factors that affect how long the Large-Scale Social Distancing (LSSD) will applied in various areas affected by the covid-19 pandemic
Authors: Fauziah A A , Budiman  , Safitri D L , Meiza A
Published: January 2021

This study will determine the length of time for large-scale social restrictions, in Indonesia is known as the Large-Scale Social Distancing (LSSD), which requires in a region to reduce the number of different covid-19 cases. Associated with the implementation of the LSSD, it turns out that many things can influence the LSSD to be able to run effectively in the community, from internal and external factors. This research was conducted for 15 days from 1 June 2020 to 15 June 2020, to find out the factors that had a significant influence on the effectiveness of LSSD using Cox Proportional Hazard Regression. The dependent variable used in the study is the length of time the LSSD system (Y). From the results can concluded that the socialization variable (X1) has a significant effect to the effectiveness of LSSD.
An Agent-Based Model of Contagion Effects in Affected Depression and Its Recovery Process
Authors: Andarlia H T , Gunawan I
Published: January 2021

Depression, as the most common mental worldwide disorder, has been the major contributor to suicide deaths. In this paper, we model how depression is contagious among the population using Agent-Based Modeling approach. A sufferer can be affected due to contagion effects of social interactions, particularly from close relationships, then undergo a depressive episode that categorized by mild, moderate, severe. Every episode can be recovered by doing therapy. Those transition processes are described based on gender in a flowchart diagram and simulations, which depend on time using software. Our simulation results represent that the greater contacts rate with someone who affected depression, the more severe of depressive episodes that will be experienced. Further, the greater probability of someone who is going to a therapy can reduce the number of depressed persons over time, especially for contagious depression. Thus, these program simulations and modeling method will be used to calculate and handle the contagion of depression, helping for sufferers’ recovery, and decreasing number of depressed people who commit suicide.
Survival Analysis Using Cox Proportional Hazard Regression Approach in Dengue Hemorrhagic Fever (DHF) Case in Abdul Moeloek Hospital Bandar Lampung in 2019
Authors: Irfan M , Usman M , Saidi S , Warsono  , Kurniasari D , Widiarti
Published: January 2021

Survival analysis is one of the statistical procedures analyzing data in the form of survival time and variables that affect survival time, namely survival time data starting from the beginning of the study (time origin/start point) until the time an event or endpoint occurs. In the field of health data is obtained from observations of patients who were observed and recorded the time event of each individual. The event in question can be in the form of death, recurrence of new diseases, or recovery. This study will discuss the application of cox proportional hazard regression to determine the cox proportional hazard model on DHF patients. Determine the factors that affect the recovery rate of DHF patients and determine the hazard ratio value of DHF patients at Abdul Moeloek Hospital in Bandar Lampung in 2019. Regression Cox proportional hazard is used because the cox proportional hazard model does not depend on the assumption of the distribution of the time of occurrence; the results are almost the same as the parametric model. They can estimate the hazard ratio without knowing the baseline hazard. Based on the selection of the best model with backward elimination and the Akaike Information Criterion (AIC), the best model is obtained with a four-variable model, namely Leukocyte, Hemoglobin, Hematocrit, and Thromobocyte. These four variables are factors that have a significant effect on the patient’s length of stay. Then this study also looked at the value of the hazard ratio which thrombocyte are the variables with the largest hazard ratio value, which means the thrombocyte variable has the highest risk level.
Application of Vector Autoregressive with Exogenous Variable: Case Study of Closing Stock Price of PT INDF.Tbk and PT ICBP.Tbk
Authors: Putri A R , Usman M , Warsono  , Widiarti  , Virginia E
Published: January 2021

Multivariate time series are widely used in various fields such as finance, economics, and the stock market. One analysis model that is widely used for multivariate time series data is the VAR model. Vector autoregressive (VAR) is a model used to describe the relationship between several variables. The VAR model provides an alternative approach that is very suitable for forecasting purposes and is very suitable for solving economic data problems. The variables used in this study consisted of endogenous variables with closing prices of ICBP and INDF shares and exogenous variables with exchange rates collected from January 2017 to July 2020. In this study, the best model, VARX (1,0), was obtained. also the relationship between variables through the impulse response function and granger causality. Furthermore, forecasting is also carried out for the next 30 days using the best model, VARX (1,0).
Modeling Multivariate Time Series by Vector Error Correction Models (VECM) (Study: PT Kalbe Farma Tbk. and PT Kimia Farma (Persero) Tbk)
Authors: Loves L , Usman M , Warsono  , Widiarti  , Russel E
Published: January 2021

Time series analysis (time series) is one method with the aim to find out events that will occur in the future based on data and past circumstances. Time series are widely used in economics, business, environmental science, and finance. The analytical tool that is widely used to answer quantitative research problems is the Autoregressive Vector (VAR). The VAR model is used if the data is stationary. If the variable has cointegration and stationary at the first difference value, the VAR model is modified to become the Error Correction Model (VECM). Then we can find out the influence of variables with other variables by looking at the Impulse Response Function and Granger Causality. In this research, PT Kalbe Farma Tbk’s stock data will be analyzed. (KLBF) and PT Kimia Farma (Persero) Tbk (KAEF). The data used are weekly data from January 2010 to June 2020. Based on data analysis, it is known that the data is not stationary and there are unit roots. Furthermore, first differencing is done to make the data stationary. Because there was cointegration, a VECM analysis was performed and a VECM (p) was obtained with a lag of p = 4. So the best model for this research is VECM (4) with rank = 2. Causal relationships between variables using Granger Causality showed that KLBF influenced KAEF in the past. Based on IRF analysis, each variable gives a fluctuating response with itself and with other variables.
Dynamic Modeling Data Return by Using BEKK-GARCH (Study: PT. Indofarma Tbk (INAF) and PT. Kimia Farma Tbk (KAEF) from June 2015 to July 2020)
Authors: Indryani N , Usman M , Warsono  , Nabila S U , Widiarti  , Kurniasari D
Published: January 2021

The Vector Autoregressive (VAR) model is a statistical model that can be used for modeling multivariate time series data which is commonly applied in the fields of finance, management, business and economics. However, economic data, especially return values, have quite high data fluctuations, so we need to add the Generalized Autoregressive Conditional Heteroscedasticity (GARCH) model in the analysis to obtain efficient results. This study will discuss the formation of the best model for multivariate time series data, namely return data of PT. Indofarma Tbk. (INAF) and PT. Kimia Farma Tbk. (KAEF) from June 2015 to July 2020, where data retuned for the two variables tended to have a high volatility shock at some time and low volatility at other times which characterizes the data as having an ARCH effect so that the GARCH model will be used in this analysis, namely the BEKK-model. GARCH. This model proposes a new parameterization which is easily given a restriction, namely the requirement that H_t must be positive for all values of ε_t and x_t in sample room. Based on the selection of the best model using the AICC, HQC, AIC and SBC criteria, it is found that the VAR (1)-GARCH (1,1) model is the best model for the data used. Then this research will also examine the behavior and relationship between INAF and KAEF based on Granger Causality and Impulse Response. In addition, based on the forecasting results of the VAR (1)-GARCH (1,1) model, it shows that this model is good for short-term forecasting.
Dynamic Modeling Data Time Series By Using Constant Conditional Correlation-Generalized Autoregressive Conditional Heteroscedasticity
Authors: Nabila S U , Usman M , Warsono  , Indryani N , Widiarti  , Kurniasari D
Published: January 2021

The Constant Conditional Correlation-Generalized Autoregressive Conditional Heteroscedasticity (CCC-Garch) model as one of the multivariate time series models is used to model economic variables, especially in stock price data with high volatility characteristics that result in heterogeneous variations. The higher the volatility, the higher the level of uncertainty of the stock returns that can be obtained. The CCC-Garch Multivariate model is the simplest model in its class. The principle of this model is to decompose the conditional covariance matrix into conditional standard deviation and correlation. In this study, we will discuss and determine the best model that can describe the relationship between two vector data timeseries, namely stock return data for companies engaged in mining and construction in Indonesia, namely United Tractor Tbk (UNTR) and Petrosea Tbk (PTRO) where the data is the daily stock return data for the period July 2015 to August 2020. Several models that involve modeling the mean and variance with CCC-GARCH parameterization are applied to data such as the VAR (1)-Garch (1,1), VAR (2)-Garch (1) model., 1), VAR (3) Garch (1,1) and VAR (4)-Garch (1,1). The result was that the VAR (1)-Garch (1,1) model was selected as the best model with the criteria for selecting the AICC, SBC, AIC and HQC models. The dynamic behavior of both UNTR and PTRO stock return variables is explained by Granger Causality and Impulse Response. Furthermore, the forecasting of this data was carried out for some time in which the VAR (1)-Garch (1,1) model which was selected as the best model was only suitable for forecasting in a short time.
The Locating-Chromatic Number of Certain Barbell Origami Graphs
Authors: Irawan A , Asmiati  , Suharsono S , Muludi K
Published: January 2021

The locating-chromatic number of a graph combined two graph concept, coloring vertices and partition dimension of a graph. The locating-chromatic number, denoted by χL
(G), is the smallest k such that G has a locating k-coloring. In this paper, we discuss the locating-chromatic number for certain barbell Origami graphs.
Asymptotically Unbiased, Efficient, and Consistent Properties of the Bayes estimator in the Binomial Distribution with Prior Beta
Authors: Simanjuntak E G , Widiarti  , Kurniasari D , Amanto
Published: January 2021

This study will examine the characteristics of the Bayes estimator in the Binomial distribution with prior Beta theoretically and empirically. The theoretical result shows that the Bayes estimator in this distribution is an asymptotically unbiased and consistent, but inefficient estimator. Meanwhile, empirically, Bayes’s estimator is an unbiased estimator, efficient, and consistent.
Determining the Number of Disconnected Vertices Labeled Graphs of Order Six with the Maximum Number Twenty Parallel Edges and Containing No Loops
Authors: Putri D , Wamiliana  , Fitriani  , Faisol A , Dewi K S
Published: January 2021

If there exist two vertices on a given graph that are not connected by a path, then we call that graph is disconnected. Given a graph with n vertices and m edges, then a lot of graphs can be constructed. In this paper, we discuss the number of disconnected vertices labeled graphs of order six (n = 6) with the maximum number of parallel edges is twenty. Moreover, a maximum number of edges that connect different pair of vertices is ten (parallel edges are counted as one) and containing no loops (isomorphic graphs are counted as one).
Calculating the Number of vertices Labeled Order Six Disconnected Graphs which Contain Maximum Seven Loops and Even Number of Non-loop Edges Without Parallel Edges
Authors: Pertiwi F A , Amanto  , Wamiliana  , Asmiati  , Notiragayu
Published: January 2021

A labeled graph is a graph where each vertex or edge is given a value or label. A line/edge with the same starting and ending vertex is called a loop. If given n vertices and m edges, then there are lot disconnected vertices labeled graphs that can be formed. Among those graphs, there are graphs with maximum seven loops and whose non-loop edges are even. In this research, we will discuss the formula for finding that kinds of graphs.
Mathematical Modeling of Heat Transper in Agricultural Drying Machine Room (Box Dryer)
Authors: Ruby T , Sutrisno A
Published: January 2021

Differential equations arise in many fields of science and technology, when the deterministic relationships involving a continuously changing quantity (modeled by a mathematical function) and its rate of change (expressed as a derivative) are known or postulated. This can be seen for example in the problem of heat transfer. The problems raised in this study are how to model the heat equation and how to solve the heat equation model. The research was conducted to find a model of the heating equation in a rice dryer and solve the heat equation using the variable separation method. This discussion is carried out in two conditions, namely the steady state (constant time) and unsteady (changing time).
Risk Analysis in the Application of Financore Information Systems Using FMEA Method
Authors: Triana Y S , Pangabean R A M
Published: January 2021

In the banking world maintaining customer data is very important so as not to experience various risks, including leakage of customer data. Leakage of customer data is one of the big risks that may occur in the banking world, whereas customer confidentiality should be guaranteed. Possible risks such as misuse of identity or theft of transaction data by unauthorized parties. This will certainly harm both the customer and the bank. So that customer data is not leaked, lost or misused, it is necessary to have a regulation or verification system of customer data that can be reviewed for security and use. The solution that can be done to prevent this event is to use the FMEA methods that can be used to reduce errors and system failures. Information system security has a positive and very significant effect on decision making, therefore it is necessary to have an information system risk analysis that supports it comprehensively so that it can help in decision making.
Effect of mono corpus quantity on statistical machine translation Indonesian – Lampung dialect of nyo
Authors: Abidin Z , Permata  , Ahmad I , Rusliyawati
Published: January 2021

Lampung Province is located on the island of Sumatera. For the immigrants in Lampung, they have difficulty in communicating with the indigenous people of Lampung. As an alternative, both immigrants and the indigenous people of Lampung speak Indonesian. This research aims to build a language model from Indonesian language and a translation model from the Lampung language dialect of nyo, both models will be combined in a Moses decoder. This research focuses on observing the effect of adding mono corpus to the experimental statistical machine translation of Indonesian - Lampung dialect of nyo. This research uses 3000 pair parallel corpus in Indonesia language and Lampung language dialect of nyo as source language and uses 3000 mono corpus sentences in Lampung language dialect of nyo as target language. The results showed that the accuracy value in bilingual evalution under-study score when using 1000 sentences, 2000 sentences, 3000 sentences mono corpus show the accuracy value of the bilingual evaluation under-study, respectively, namely 40.97 %, 41.80 % and 45.26 %.
Abstract Classification Using Support Vector Machine Algorithm (Case Study: Abstract in a Computer Science Journal)
Authors: Lumbanraja F R , Fitri E , Ardiansyah  , Junaidi A , Prabowo Rizky
Published: January 2021

Jurnal Komputasi is an online journal written by researchers and published by the Department of Computer Science, University of Lampung. Specific scientific information contained in journals is difficult to find because journals have not been structured and are classified into more specialized categories of computer science. Text mining can convert the shape of a journal into structured by homogeneous data form in it. 144 journal abstracts are collected into one corpus document in CSV format used as a research dataset. Journal abstract classification is done using one of the supervised machine learning methods, namely Support Vector Machine (SVM) so that the classification process is faster than the manual method. The TF-IDF technique is used to transform sentences in the abstract into vector so that they can be modelled with SVM. The classification model will be validated by applying the 10-fold cross validation technique. From these classifications a calculation of the resulting performance will be calculated based on the confusion matrix calculation of the resulting performance will be calculated based on the confusion matrix calculation and the use of 3 SVM kernels. The conclusion based on this research is that there are two factors that affect classification accuracy, that is the number of members between scientific classes that are not balanced and the number of features generated from text mining. The highest accuracy of testing result obtained on the use of 205 features and SVM Linear kernel with a value of 58,3%.
Identification of SNPs Associated with Iron Toxicity Tolerance in Rice
Authors: Chrisnawati L , Miftahudin  , Utami D W
Published: January 2021

Iron (Fe) toxicity is one of the limiting factors that can lead to the decrease of rice yield in paddy fields. Association studies to identify potential alleles or markers linked to iron toxicity tolerant trait can be carried out using high throughput single nucleotide polymorphisms (SNPs). We conducted an association study for Fe toxicity tolerance characters, using Forty-five double haploid lines derived from reciprocal double-crossing, i.e. IR54 / Parekaligolara // Bio110 / Markuti in high Fe wetland rice field. Genome-wide association study was carried out using 384 SNP-plex markers distributed on 12 rice chromosomes. A total of 77 SNPs were significantly associated with the Fe toxicity tolerance-related traits. Functional annotation allowed us to shortlist four SNP markers associated with Fe toxicity tolerance trait, i.e.: TBGI204006, TBGI310247, id9006377, and id10000498. The research suggests that association studies followed by functional annotation can effectively detect potential alleles and candidate genes for the trait. The identified QTL and genes provided valuable sources for future genetic improvement of Fe tolerant rice lines.
Altering Physical Characteristics of Sinking Fish-Feed through Sub-Optimal Fermentation Using Tempeh Mould without Mechanical Extrusion
Authors: Sriherwanto C , Rahmanisa H , Yunita E , Suja’i I , Nadaviana A
Published: January 2021

Sinking pellets disintegrates easily in water, hence reducing water quality and fish productivity due to oxygen-consuming biodegradation of the unconsumed feed. Modifying sinking pellets into more stable floating pellets using an edible tempeh mould through solid fermentation has previously been studied as an alternative to the more expensive extrusion method. However, the fermentation resulted in the uncontrolled growth of the fungal mycelium, causing the individual pellets to aggregate into a single compact mass. The fermentation also contributed to the dry weight loss of the initial pellets. Thus, using a laboratory-scale bioreactor, this study aimed at generating water-stable and floating properties on sinking-pellets through sub-optimal fermentation using tempeh mould. The conditions varied were the amount of sinking pellets substrate, fermentation duration, and aeration-humidification. Results showed that less pellet aggregation was observed with shorter fermentation time. Based on 40-minute laboratory tests in water, the best 80% floating ability was achieved for 10 g sinking pellets fermented for 72 h with humidified bubble aeration. The fermented pellets showed 42% water stability and 4.86% dry weight loss.
Monosex male formation of juvenile redclaw crayfish using natural steroid hormone from gamma sea cucumber and different doses of honey bee
Authors: Susanto G N , Sutyarso  , Widianto W
Published: January 2021

In a new commercial commodity aquaculture, tropical freshwater crayfishCherax quadricarinatus, it is known that female has a slower growth rate than male. One way to increase production rate is through monosex cultures comprising all-male population by using genital reversion technique. This biotechnology method can be applied by using hormones and natural products. The natural hormones extracted from gamma sea cucumber,Stichopus variegatushas bioactive substances including steroid compounds, while honey bee contains chrysin compounds that act as aromatase inhibitors. Therefore, the combination of both substances expected can increase in testosterone level and accelerate production in the male monosex population of juvenile crayfish. The purpose of the study is to determine the most effective dose of honey bee in masculinization of juvenile freshwater crayfish combined with 2 mg. L−1steroid extract of gamma sea cucumber. Furthermore, a Completely Randomized Design (CRD) was designed in the experiment with five different dose of honey bee treatment and dipping method in 2 mg. L−1steroid extract of gamma sea cucumber for 18 h. Each treatment with four replications. The highest male formation was found in the dose of 20 ml. L−1 honey bee at 83.75% and the lowest was in control. The present of honey bee at different doses in 2 mg. L−1of gamma steroid extract did not significantly give an effect on percentage of female, intersex formation, survival, and growth rate of juvenile redclaw crayfish.
Antidiabetic Potency of Jeruju (Acanthus ilicifolius L.) Ethanol Extract and Taurine on Histopathological Response of Mice Kidney (Mus musculus L.) Induced by Alloxan
Authors: Widiastuti E L , Ardiansyah B K , Nurcahyani N , Silvinia A
Published: January 2021

Diabetes arises due to interference with the work of the pancreas in secreting the hormone insulin. The disease can cause a decrease in body immunity and complications of various vital organs such as the kidneys. Jeruju (Acanthus ilicifolius L.) leaf and taurine is reported to have antioxidant activity that is potential as antidiabetic agents. The purpose of this study was to determine the effect of jeruju and taurine on blood glucose levels and the ability to regenerate kidney organs damaged by alloxan induction. This study used a Completely Randomized Design with 5 treatment groups and 5 replications each. K1 group as a negative control (no treatment given), K2 group as a positive control (only induced by alloxan), group P1 induced alloxan and given 100% ethanol extract of jeruju leaf 22.4 mg/bw/day, group P2 induced alloxan and given alloxan 50% ethanol extract of jeruju leaf dose 22.4 mg/bw/day, group P3 was induced by alloxan and given a taurine dose of 15.6 mg/bw/day for 14 days. Data were analyzed by ANOVA followed by LSD at 5% of significant level. The results showed that the administration of jeruju extract and taurine affected the bodyweight of mice, and was significantly able to reduce blood glucose levels by 69.39% (P1), 67.06% (P2), 73.77% (P3), able to repair kidney damage after alloxan induction.
Effect of Duwet fruit (Syzgium cumini) extract on MDA level and Caspase 3 expression in Rat (Rattus sp) Testes exposed to cigarette smoke
Authors: Sukmaningsih A A S A , Suarni R , Wiratmini I , Setyawati I , Sudatri Ni Wayan , Pangestiningsih T W
Published: January 2021

This research evaluates the MDA levels, number and apoptosis of spermatogenic cells in Rat provided with duwet fruit extract and exposed to cigarette smoke towards. The study involved 4 experimental animal groups and 6 replications, where K0 was the negative control group, K1 was exposed the cigarette smoke, K2 was given orally duwet fruit, and K3 was given orally duwet fruit after being exposed to cigarette smoke. Therefore, data obtained were analyzed using One way Anova test. The results showed significantly lower number of spermatocytes and MDA levels in the testes in all groups compared to K1 at p <0.05. Spermatogenic cell apoptosis occurred in all groups, and there was also a high tendency for reduction in K2 compared to K1, although not significant at p > 0.05. In addition, apoptosis was expressed by Caspase 3 in the testes. The highest MDA levels found in K1. This phenomenon was assumed to have resulted in lower numbers of spermatocytes. These decreased number of spermatocytes were related with the decline in number of spermatogenic cells prone to apoptosis. In conclusion, duwet fruit had the ability to reduce free radicals with the tendency to inhibit spermatogenesis. This case features an increase in spermatocytes and a potential decline in the incidence of spermatogenic cell apoptosis.
Bacterial support as a biostimulant agent (BPNIII, Azzofor) for marginal soil fertility and stimulating seedlings growth in nursery
Authors: Widawati S , Suliasih
Published: January 2021

A nursery is the first preparation step for the reclamation of marginal land, supported by fertile, strong, and adaptable seedling to the environment. Therefore, the role of bacteria as a bio stimulating agent is needed to stimulate the growth of seedling during nursery and to enable their subsequent adaptation to the environment. The purpose of this study is to determine the effectiveness and survival rate of bacteria as a growing medium in marginal soil fertilization as well as the accelerated effect of the vegetative growth of seedling during the nursery. This research used the Completely Randomized Design with 3 treatments and 10 replications. The two biostimulant agents used were BPN III (Burkholderia Metallica, B.anthina, Rhizobium radiobacter, Azotobacter sp., Azospirillum sp.) and AZZOFOR (Enterobacter sp., Lysinibacillus xylanilyticus, Achrimobacter ruhlandii, Enterobacter hormaechei, Comamonas testosterone, Enterobacter cancerogeneus, Pseudomonas mosselii, Leclercia adecarboxylata, Citrobacter youngae, Enterobacter hormaechei, Chyuseobaterium indologenes, Achrimobacter xylosoxidans, and Citrobacter farmer), mixed with BPN III and AZZOFOR. The results showed that the biostimulant agents and rhizobacteria (BPN III + AZZOFOR) were suitable and effective in supporting the fertility of the marginal soil with bacterial population 107 CFU gram soil−1. Furthermore, all bacteria stimulated the vegetative growth of seedling, such as plant height, number of leaves, and branch, monthly during the nursery.
Antioxidant and Antimicrobial Activity of Endophytyc Fungi Isolated from Syzygium aqueum Leaves
Authors: Habisukan U H , Elfita  , Widjajanti H , Setiawan A , Kurniawati A R
Published: January 2021

Syzygium aqueum is a widely used medicinal plant species with ethnomedicinal values. Despite the plant, the endophytes are recognized as a rich source of secondary metabolites with potentially useful pharmacological properties. This study was aimed to identify the endophytic fungi from S.aqueum leaves and discover their antioxidant and antimicrobial activity. The ethyl acetate extracts of the isolated endophytic fungi were investigated for their antioxidant and antimicrobial activity using 1,1diphenyl-2-picryl hydrazyl (DPPH) method and paper disc diffusion assay, respectively. The antimicrobial activity was evaluated against three pathogen bacteria : Staphylococcus aureus, Salmonella thypi, and Escherichia coli, and one yeast: Candida albicans. Three endophytic fungi were obtained from S. aqueum leaves. Based on morphological characteristics, those fungi identified as Cochliobolus sp (D22), Penicillium sp. (D32), and Fusarium sp. (D41). Penicillium sp. (code D32) showed significant antioxidant potential activity as an also significant antimicrobial activity with IC50 59,16% and highest zone inhibition against E. coli 13.38 ± 0.25 mm. It is worth considering a further investigation of their bioactive secondary metabolites and isolates the bioactive compound for the antioxidant and antimicrobial agents.
Analysis of Total Carbohydrate and Chlorophyll Content of The Orchid Plantlet [Phalaenopsis amabilis (L.) Bl.] Resistant Fusarium Wilt Disease
Authors: Nurcahyani E , Sholekhah  , Sumardi  , Qudus H I
Published: January 2021

The moon orchid [Phalaenopsis amabilis (L.) Bl.] is a popular orchid in the community, native orchid from Indonesia, and included in the list of endangered species. The pathogenic fungus that often attacks orchid leaves is Fusarium oxysporum, which causes fusarium wilt. Control of diseases that do not cause negative impacts can be done using superior cultivars resistant to F. oxysporum infection, through in vitro selection in the medium with the addition of fusaric acid. Fusaric acid is a metabolite produced by several fungal species of the genus fusarium and at non-toxic concentrations it helps to induce phytoalexin synthesis, increase chlorophyll and carbohydrate content when pathogen infasion. The purpose of this study was to find out the total chlorophyll content, chlorophyll a, chlorophyll b, and total dissolved carbohydrate content. This study used a Completely Randomized Design (CRD) with one factor, namely the concentration of fusaric acid divided into 5 levels, namely 0 ppm, 10 ppm, 20 ppm, 30 ppm, and 40 ppm with 5 replications each. The results showed an increase in the total chlorophyll content, chlorophyll a, chlorophyll b, and total dissolved carbohydrate content.
The effect of fermentation on acidity, caffeine and taste cascara robusta coffee
Authors: Komaria N , Suratno  , Sudarti  , Dafik
Published: January 2021

Robusta coffee is in demand by the global market because of its distinctive aroma. Along with the high demand, robusta coffee waste known as cascara needs processing. Cascara which has a unique taste needs innovation to improve its quality. One of the efforts made is by varying the fermentation process. The purpose of this study is to examine the effect of the fermentation process on pH, caffeine and flavor in cascara robusta coffee. This type of research is experimental. The results showed that the fermentation process had an effect on pH, caffeine and flavor values. The non-fermented cascara has the lowest pH average value of 4.22, the natural fermented cascara has a pH value of 4.58, while the fermented cascara wrapped in banana leaves has a pH value of 5.24. Calculation of caffeine content in non-fermented cascara, natural fermented cascara and fermented cascara wrapped in banana leaves were 1.22%, 1.17%, and 1.14%, respectively. The taste test results of the non-fermented cascara, natural fermented cascara and cascara wrapped in banana leaves were different for each treatment.
Influence of Dy-doping in Nd2Fe14B on its structural and magnetic properties
Authors: Sukmara S , Manaf A , Adib W A
Published: January 2021

Study about Influence of Dy-doping in Nd2Fe14B on its structural and magnetic properties have been performed. The combination of Nd2-xDyxFe14B with x= 0.00, 0.33, 0.67, and 1.00 were using the conventional method of arc melting. The result of ingot then milled and compacted to produce a permanent magnet sample. The results of phase analysis with XRD show that the sample contained 3 phases, namely Nd2Fe14B, Fe, and Nd with dominant phase above 50% is Nd2Fe14B. Magnetic properties was measured using permeagraph and produce saturation magnetization of 0.6, 0.56, 0.42, and 0.4, remanent of 0.15, 0.19, 0.26, and 0.25, and coersivitas field of 0.35, 0.39, 3.0, and 1.29 kOe for composition of 0, 0.33, 0.67, and 1, respectively. The remanent magnetization ratio toward saturation of Br/Bs of this increase significantly from 0.34 to 0.62 for the composition x= 0.67, and has the highest energy product of 0.195 MGOe. To determine the effect of Dy substitution towards micro structure was observed with an optical microscope. It was concluded that the effect of Dy substitution towards optimum magnetic behavior was found in the composition x= 0.67.
Impact of Mn4+ ion substitution on La0.4Sr0.6Fe1-xMnxO3 perovskite conductivity (x = 0.2, 0.4 and 0.6) as a solid fuel cell cathode
Authors: Gunanto Y E , Izaak M P , Sitompul H , Adi W A
Published: January 2021

The samples La0.4Sr0.6Fe1-xMnxO3 (x = 0.2, 0.4, and 0.6) as solid fuel cell cathodes have been successfully synthesized and characterized. Samples were made using the solid-state reaction method with the wet milling technique. X-ray diffraction is used to see the phases formed. Surface morphology in the form of particle shape and size is characterized using scanning electron microscopy, while electronic conductivity at room temperature is measured by measuring its resistivity. Sample x = 0.4 has a single phase, while two other samples, x = 0.2 and 0.6 are still detected secondary phase. Surface morphology has a heterogeneous grain shape with a size between 63-250 nm. The best electronic conductivity at room temperature is obtained at a composition of x = 0.4 of 3.39 x 10-3 S.cm-1 so that it can be used as a candidate material for a solid fuel cell cathode.
Measurement of Physical Parameters of Water Quality in Real-Time Based on Arduino
Authors: Junaidi  , Putra T M , Surtono A , Puazi G A , Suciyati S W , Firdaus I , Rumiyanti L
Published: January 2021

In this study, a physical parameter measurement system has been implemented for real-time monitoring of Arduino-based water quality for catfish farming applications. This system aims to detect physical parameters of water quality such as pH and water temperature using the Analog pH Meter and DS18B20 sensors. Data were collected by inserting the two sensor probes into the catfish pond water medium. The results showed that the system can detect parameters, display and store sampling data on the Visual Studio 2013 interface application in real-time. The sensors in this system are able to detect pH and water temperature with an average accuracy rate of 90.94% and 99.71%.
Sintering temperature effect on optical properties of zinc oxide thin film on glass substrate prepared by sol-gel spin coating method
Authors: Rumiyanti L , Aryanto D , Garcia S , Syafriadi  , Firdaus I
Published: January 2021

Research on the optical properties of the ZnO thin film with the use of sol-gel method and spin coating method using 0.5 M concentrate solution of (Zn(CH3COO)2·2H2O) and 30 mL isopropyl alcohol as a solvent has been carried out. The production process of ZnO solution and the fabrication of the thin film with the optical properties test of the thin film are included in the scope of this research. UV-Vis Spectroscopy is used to obtain the transmittance and absorbance values on each wavelength and the band gap energy value using the Tauc Plot method. The transmittance value obtained is directly proportional with the temperature. The absorbance value obtained is inversely proportional with the temperature due to higher temperature causes the reaction rate to become faster and in turn causes the absorbance value to become lower. The band gap energy value obtained is on the range of 3.23 eV – 3.27 eV and it fit with the literature.
Structure analysis of electromagnetic waves absorbing material a lanthanum manganite system of (La0.8Ba0.2)(Mn(1-x)/2ZnxFe(1-x)/2)O3
Authors: Rumiyanti L , Wandira I , Adi W A , Junaidi  , Sembiring S
Published: January 2021

Solid compound of lanthanum manganite system of (La0.8Ba0.2)(Mn(1-x)/2ZnxFe(1-x)/2)O3 has been synthesized via conventional solid state reaction route using lanthanum oxide (La2O3), barium carbonate (BaCO3), zinc oxide (ZnO), ferric oxide (Fe2O3) and manganese carbonate (MnCO3) powders as it raw materials. High energy ball milling was used to mix the material for 5 hours. It is then sintered at 1000°C for 5 hours. X-ray powder diffraction method (XRD) and scanning electron microscopy (SEM) was used to analyze the change of structure of the solid compound. The refinement pattern result of the XRD shown that a single phase was occurred in the form of (La0.8Ba0.2)(Mn0.4Zn0.2Fe0.4)O3. It has trigonal lattice crystal structure of (r-3c) point group with lattice parameter of a = b = 5.515 Å and c = 13.551 Å, α = β = 90° and γ = 120°, a volume unit cell of V = 356.904 Å3 and a density of ρ = 6.745 g.cm−3. The SEM result shown that the surface morphology of (La0.8Ba0.2)(Mn0.4Zn0.2Fe0.4)O3 has a homogeneous sphere structure. The XRD and SEM structure analysis result of the lanthanum manganite system of (La0.8Ba0.2)(Mn0.4Zn0.2Fe0.4)O3 shown that the compound is feasible for further studied.
Rietveld analysis of geopolymer prepared from amorphous rice husk silica with different thermal treatment
Authors: Riyanto A , Sembiring S , Husain S , Karimah R S , Firdaus I
Published: January 2021

The work aims to study the temperature effect on the geopolymer’s crystal structure prepared from amorphous silica rice husk. The samples were prepared via the sol-gel method and then subjected to thermal at a temperature of 250-650 °C. EDS identified the element and compound composition on the surface of the sample. The crystal structure of samples identified by Rietveld refinement of XRD. The sample was dominated by the gibbsite phase at relatively low temperatures (250 °C). The boehmite phase dominates at a temperature of 350-450 °C. The amorphous structure of the geopolymer was formed at a temperature of 550-650 °C. The geopolymer mainly formed from the reaction of boehmite and silica. This study shows a significant effect of temperature on the formation of the geopolymer structure.
Effect of calcination temperature on silica-asphalt composite properties using amorphous rice husk silica
Authors: Sembiring S. , Riyanto A. , Firdaus I. , Junaidi  , Situmeang R.
Published: January 2021

This study aims to investigate the effect of thermal treatment on the phase formation and physical characteristics of silica asphalt composite prepared from rice husk silica and asphalt powders. The mass ratio of asphalt to silica is 1:2, and subjected to calcining temperatures of 200-450 °C. Development of structures was characterized using X-ray diffraction (XRD), Fourier Transform Infrared (FTIR) spectroscopy and scanning electron microscopy (SEM). Further evaluation was made by comparing the characteristics of the silica-asphalt composite include the density, porosity, and compressive strength. The XRD study revealed that the major phases were carbon and silica amorphous, The XRD study revealed that the major phases were silica and carbon amorphous, which were associated with are Si-OH, Si-O-Si and C-H functional groups according to FTIR analysis. In addition, an increased calcination temperatures was followed by an increase in the density and compressive strength. Based on these characteristics, the samples are considered for the roof material, suggesting their potential use in substitute lightweight steel roof devices.
Deep learning for detection cassava leaf disease
Authors: Ayu H R , Surtono A , Apriyanto D K
Published: January 2021

In this research, an intelligent system for detecting cassava leaf disease has been developed by utilizing the MobileNetV2 deep learning model and displaying it using a python graphical user interface (GUI). There are five disease classes used in this study, namely Cassava Bacterial Blight (CBB), Cassava Brown Steak Disease (CBSD), Cassava Green Mite (CGM), and Cassava Mosaic Disease (CMD) and Healthy. The results showed that the overall accuracy of the test data obtained was 65,6%. The GUI application program was made to be operated efficiently for beginners and can be used by cassava farmers in the field.
One hadron exchange non-relativistic model for K+p potential
Authors: Glenno  , Fachruddin I , Salam A
Published: January 2021

K+p potential is modeled as one hadron exchange. The hadrons being exchanged include scalar meson (σ), vector mesons ( ω, p ), hyperons (Λ, Σ), and their resonances (Λ*(1600), Σ*(1385)). This interaction model is derived for non-relativistic calculations and for that purpose the potential model is formulated within Blankenbecler-Sugar reduction. The values of the potential parameters are fixed by fitting to experimental data of K+p spin-averaged differential cross section for kaon laboratory energies from 88.13 MeV to 380.58 MeV. Scattering calculations are performed by using a 3D technique without partial wave expansion.