bluuebunny/crossref_metadata_2025_split huggingface dataset:
The development and the growth of salak pondoh fruit (Salacca edulis L.) planted using different planting methods
Authors: Prihastanti E , Haryanti S 
Published: July 2021

Abstract
The cultivation plays an important role in determining the quality of salak pondoh (Sallaca. L), for instance, the planting methods. There are various methods of planting salak pondoh (Sallaca. L), monoculture (only salak pondoh) and polyculture (salak pondoh is cultivated with other plants). The goal of this research is to analyze the development and the growth of stamens on salak pondoh (Sallaca. L) using different patterns of cultivating. The plot for this research is a garden only for salak pondoh plants (monoculture) and for salak pondoh plants cultivated with other plants (polyculture). The parameters to observe are the morphology of plants, size of stamens, and environmental factors such as temperature, pH, and moist of soil. The result shows that different patterns of cultivating affect the development and the growth of stamens on salak pondoh with polyculture system. The soil temperature in monoculture system is higher than polyculture and the morphology observation towards salak pondoh plant also shows the difference between polyculture and monoculture system.
Species diversity and dominance of Oligochaeta in copper and cadmium polluted soil
Authors: Ulfah M , Anggoro S , Soeprobowati T R , Syafrudin S 
Published: July 2021

Abstract
The aim of this study was to determine the dominance and species diversity of oligochaeta were studied incopper and cadmium polluted soil. This location is used for the garbage disposal of Jatibarang Landfill Semarang City residents, Central Java. Oligochaeta were collected from 5 research sites. The research method used is field experiment. Oligochaeta sampling was carried out based on a random sampling method. Oligochaeta sampling in Jatibarang Landfill was carried out at a depth of 25 cm. Analysis of oligochaeta diversity includes species diversity using the index formula Shannon-Wienner and dominance with the index formula Simpson. The species diversity (Shannon-Weiner Index) showed value of 0.191 (site 1), 0.411 (site 2), 0.539 (site 3), 0.137 (site 4), 0.443 (site 5) and the dominance calculated was 0.207 (site 1), 0.024 (site 2), 0.279 (site 3), 0.045 (site 4), 0.031 (site 5) which indicates that the diversity and the dominance were inversely related. The population density (individuals/m2) of the Oligochaeta species at 5 research sites showed variations. The total density of L. terrestris recorded was 280.66 (site 1), 59.66 (site 2), 130.33 (site 3), 136.66 (site 4), 62 (site 5), and the total density of Pheretrima sp 14 (site 1), 10 (site 2), 39 (site 3), 4.33 (site 4), 12 (site 5). Two species of Oligochaeta showed high richness whereas some were sparsely populated.
Intron 4 VNTR A/B polymorphism of endothelial nitric oxide synthase gene in periodontitis
Authors: Pradita L W , Kamilla D N , Soedarsono N , Yunaini L , Auerkari E I 
Published: July 2021

AbstractNitric Oxide (NO) is an important mediator in the inflammatory and immune systems. The eNOS gene is one of the three isoforms of Nitric Oxide Synthase (NOS), which is responsible for synthesizing NO. Periodontitis is an inflammatory disease in periodontal tissue with genetic involvement. Polymorphism in eNOS gene changes the functional aspect of this gene and is associated with several inflammatory diseases including periodontitis. Aim: To detectEndothelialNitric Oxide Synthaseintron 4 gene polymorphism in Indonesian population with periodontitis. Analysis of theEndothelialNitric Oxide Synthase(eNOS) intron 4 gene polymorphism was observed by carrying out PCR method followed by electrophoresis for the analysis, without the usage of restriction enzyme. The chi-square test and odds ratio were performed for statistical analysis. In this study, there were 34 samples with AA genotype, 3 samples with AB genotype, and 13 samples with BB genotype in periodontitis group. Whereas in the control group, there were 41 samples with AA genotype and 9 samples with BB genotype. AB genotype was absent in the control group. In periodontitis group, there were 71 A alleles and 29 B alleles, and in the control group, 82 A alleles and 18 B alleles were found. Polymorphic genotypes and alleles were found higher in periodontitis sample (32% and 29%) than healthy controls (18%). The polymorphism of eNOS intron 4 was found in periodontitis patients. There is no significant distribution difference was found between the periodontitis patients and the control group. ENOS intron 4 gene polymorphism does not affect the risk of periodontitis.
Genetics and epigenetics of class II and class III malocclusions
Authors: Subono M , Alima I R N , Auerkari E I 
Published: July 2021

Abstract
Malocclusion is the major diagnosis in orthodontic field. According to Angle’s classification, malocclusion is divided into Class I, Class II, and Class III malocclusion. All of these classifications have etiologic factors that establish every specific characteristic of malocclusion. Genetic, is one of the most important etiology in malocclusion since it can be inherited congenitally, for instance many variations in transcription and translation of multifarious genes occurred in masseter muscles, which is the main mastication muscle in human. MYH/MyH-C, MMPs and IGF genes are frequently used to determine the expression of genes in masseter muscle using RT-PCR or cRT-PCR. On the other hand, polymorphism of ACTN3, which can influence fibre type proportions and also muscle performance is found in muscle and skeletal type of Class II malocclusion. MATN1, HSPG2, ALPL, and EPB41 genes are found linked to lp36 related to Class III malocclusion. However, genetic factor does not usually stand alone. It can be influenced by environment which called epigenetic factors. Increasing acetylation activity will initiate a chromatin domain formation that consists of genes for MyH-C fast type gene expression. In contrast, increased of deacetylation activity resulting in closed chromatin confirmation on the chromatin area to limit the access into transcription complexes for MyHC type I gene expression in malocclusion cases. Recently, the most common way to study about heritability in malocclusion is using masseter muscles by analyzing their types of fibers related to every malocclusion’s phenotype. In this review, writer will explain more about genetic study in masseter, histone modification, and also genetic and epigenetic factors of Class II and Class III malocclusions, which involve gene mutation and polymorphism for genetic factors and histone acetylation and deacetylation for epigenetic factors.
Genetic contributions to craniofacial growth: a review
Authors: Andriani A T , Zahra P K , Auerkari E I 
Published: July 2021

Abstract
The human head consist of numerous bones. The bones of the face are suspended from the anterior portion of the cranium. These bones are responsible for the face and head form. The facial surface is immediately recognizable and seen which has a close association to the skeletal and cartilaginous structures. The diversity in shape, relative size, and spatial arrangement (vertical, horizontal and depth) between the assorted facial features such as nose, eyes. lips. etc., make individual human face unique, respectively. In recent years, study of various number of genes that contribute to craniofacial growth continuous to evolve, while the impact of individual genes on normal craniofacial variation is few established. Genes such as Homeobox. Sonic Hedgehog, transcription factor and IHH take important roles in craniofacial growth. In the other hand, it is also known that the genetic disorder of these signalling pathways may result abnormalities in the growth or fusion of the craniofacial processes and numerous anomalies. Genes may therefore take part in the development of craniofacial complex. Furthermore, clinicians need to be knowledgeable the combination and interaction of genetic and environmental factors of growth potential to perform an appropriate diagnose and treatment planning. In this review, the function of various individual genes involved in growth of facial region are discussed.
Chemical compounds in essential oil of nutmeg leaves (Myristica fragrans) from Batang Indonesia
Authors: Kusumaningrum H P , Zainuri M , Endrawati H , Loka B D , Widiasa I N , Sulistyowati E 
Published: July 2021

Abstract
Nutmeg oil has an important function as natural tropical biomedicine activity which commonly found in Batang region. This essential oil is one of the dominant traditional export product from Batang instead of patchouli oil, Clove oil, and lemongrass oil. The objective of the research was to analyze chemical compound of essential oil of nutmeg leaves from Batang region produced by traditional destillation. Research methods was conducted by GCMS method. The biomedical activity against some tropical diseases was analysed in-silico. The results showed that essential oil from nutmeg leaves showed potential antimicroabial activities in silico againts several tropical diseases in skin. The GCMS result showed 2-.BETA.-PINENE and .gamma.-Terpinene as the major compound with values 34,46% and 30,28%.
Comparison of double exponential smoothing and triple exponential smoothing methods in predicting income of local water company
Authors: Khairina D M , Daniel Y , Widagdo P P 
Published: July 2021

Abstract
Local Water Company is a government-owned business entity that has a business scope in the management of drinking water and water facilities to improve the welfare of the community, which includes social, health, and public service aspects and has a very important role for the community in terms of supporting the smooth development of the region so that the company’s success must always be sought. This effort certainly needs to be supported also in terms of setting revenue targets at the company. Determination of revenue targets in local water companies is currently using manual calculation methods so that the accuracy and effectiveness of setting revenue targets is less accurate. Forecasting models with mathematical methods are needed to predict future revenue targets so that monitoring of the success of regional development and consideration in decision making can be monitored. Forecasting this revenue target is based on actual data within the previous 5 (five) years, namely from January 2014 until December 2018, by comparing the two forecasting methods, namely the Double Exponential Smoothing (DES) and Triple Exponential Smoothing (TES) methods. The forecasting accuracy method is used the Mean Absolute Percentage Error (MAPE) method to measure the accuracy of the forecasting results from the two forecasting methods used. Forecasting test results are performed using alpha constant values of 0.1, 0.3, 0.5, 0.7, and 0.9 as trial data. Based on the trials conducted, the forecasting results presented show that forecasting results with the Double Exponential Smoothing method provide a more optimal forecasting result at alpha 0.7 with a MAPE value of 9.54%, so that the use of the Double Exponential Smoothing method is recommended in forecasting revenue targets in the Local Water Company because it has an error value under 10%.
Business architecture and information system architecture design in savings and payment unit Koperasi Pegawai Republik Indonesia (KPRI) Diponegoro University using TOGAF 9 framework
Authors: Noranita B , Nugraheni D M K , Fitriyani M I , Nurhayati Y 
Published: July 2021

Abstract
Savings dan Payment unit is one of the units of the Koperasi Pegawai Republik Indonesia Diponegoro University (KPRI). In the development of these units already have information systems infrastructure, namely the Cooperative Information Systems (SIMASPRI) and KPRI website. However, data processing on the system has not been integrated also not all business processes can be handled through the information system. SIMASPRI does not have features that allow members to carry out registration processes, loan applications, deposit payments, and installments online. So, members must come to the cooperative every time they want to carry out a registration or transaction process. Meanwhile, KPRI has a target for members to be able to process registration, deposit payments, apply for loans, and pay installments online using a website or mobile application. So it is necessary to improve the features and functions of the Cooperative Information Systems and KPRI website, as well as the design in the mobile version with the aim to offer convenience to members in accessing. Therefore, an analysis of business architecture and information system architecture design as a basic framework of business solutions to solve problems in optimizing the use of information technology. This study uses the TOGAF (The Open Group Architecture Framework) framework with the stages passed, namely preliminary, vision architecture, requirements management, business architecture and information system architecture consisting of data architecture and application architecture. From the analysis of the architectural design and approval of KPRI Diponegoro University manager, the proposed blueprint business architecture, data architecture and application architecture as the basic foundation needed to support business activities in the Saving dan Payment unit KPRI Diponegoro University.
Predict recovery risk rate of Covid-19
Authors: Wulandari R , Surarso B , Irawanto B , Farikhin  
Published: July 2021

Abstract
The outbreak of the 2019 novel coronavirus (2019-nCoV) in Wuhan, China has become expanded globally, the current novel coronavirus (2019-nCoV) or also called COVID-19 pandemic is unprecedented, but the global response draws on the lessons learned from other disease outbreaks over the past several decades. WHO (World Health Organisation) said that Person-to-person transmission may occur through droplet or contact transmission and according to early estimates by China’s National Commission (NHC) people with high risk for severe disease and death people is an old age and people with pre-existing health conditios (comorbid) as hyertention, diabetes, cardiovasculer disease, chronic respiratory diseas (asthma, lung etc), heart disease, kidney disease, liver disease, immunodeficiency, cancer and other. The fatality cases about 80% were over the age of 60 and 75% of them had pre-existing health conditios (comorbid). The government prevent further spread of novel coronavirus (2019-nCoV) disease with advice for public on how to keep healthy. In this article we consider a predict recovery risk rate of COVID-19 using fuzzy tsukamoto inference system, representation linguistic variable using linear membership function up and down, use two input, age and comorbid with “IF-THEN” rules, fuzzy logic conjunction connectives. The defuzzification or output mortality rate using centroid triangular fuzzy number.
Logistic regression model on land productivity of Pagar Alam coffee farming
Authors: Irmeilyana  , Ngudiantoro  , Samsuri M N , Suprihatin B 
Published: July 2021

AbstractPagar Alam coffee farming is a smallholder plantation, the majority of which is a hereditary business. The success of this coffee farming cannot be separated from existing resources, including land productivity. Land productivity concerns the amount of production, land resources, and land management efforts. This paper discusses the factors that influence the land productivity of coffee farms in Kota Pagar Alam, using binary logistic regression analysis. In general, there are 5 factors discussed, namely the identity of farmers and their internal factors, agricultural land, the performance of farmers in the production process, yields, and external factors on the productivity of Pagar Alam coffee farms. The data used are 191 respondents with 33 independent variables and one dependent variable. Each variable is divided into categories. Land Productivity as the dependent variable is divided into 2 categories, namely low and high. Based on bivariate analysis, variables related to land productivity are land area, number of trees, frequency of fertilizer used, frequency of pesticides used, length of harvest, production, female labor in the family, gross income, net income, and production costs. Furthermore, based on the binary logistic regression model of land productivity probability, variables that significantly affect land productivity of Pagar Alam coffee farms are area, number of trees, crop production, and net income. The accuracy of the model simultaneously was 93.2%. The probability value of the model is predominantly influenced by the harvest production variable with an odds ratio of 49.505. If the category of harvest production and net income increases, the probability for high land productivity will also increase. Conversely, if the area of land and the number of trees increases, the probability of high land productivity will decrease.
Generalizations of pareto distribution with applications to lifetime data
Authors: Haj Ahmad H , Almetwally E 
Published: July 2021

Abstract
In this paper, we consider five different generalizations of the well-known Pareto distribution. In literature, different generalizations were used so that the newly generated lifetime distributions were more flexible and can be used to model skewed, symmetric, and monotone data. We consider some important characteristics of the generalized Pareto distributions, such as monotonicity and hazard rate function. Comparisons are performed between the different generalizations of Pareto distribution. Modelling real data examples are done using the different goodness of fit tests. Numerical methods are used to conduct the suggested tests, and resulted with the models that are most suitable for describing the behaviour for these data. Finally, the conclusion is given to illustrate the purpose of this work
Variance gamma for stock model performance with excess kurtosis
Authors: Hoyyi A , Tarno  , Maruddani D A I , Rahmawati R 
Published: July 2021

Abstract
The Geometric Brownian Motion (GBM) model is used widely for model the dynamic of asset price movement. One of the company’s assets is a stock. The distribution of stock data that is normally distributed can be modeled using the Geometric Brownian Motion model. However, the distribution of stock data showed excess kurtosis and tail when using the Brown Geometry Motion model was less precise. One model for data showing excess kurtosis and tail was Variance Gamma (VG). In this research, the sample used was the stock data of PT Bank Danamon Indonesia Tbk for the period April 25
th
, 2018 to April 24
th
, 2020. The data sample was divided into two parts, namely training data and testing data. Based on the result of the stock description statistics, the value of skewness = -2.105417 and kurtosis = 22.16438 was obtained, while hypothesis testing concluded that the stock distribution did not spread normally. The resulting parameters for the VG model were σ = 0.08071, v = 8.00500 and θ = 0.01976. Based on the results of testing on the last 38 observations, the MAPE value was = 6.97560%. These results gave the conclusion that the VG model provided excellent forecasting results.
Determination parameter of exponential function based positive number
Authors: Sudarno  , Widiharih T 
Published: July 2021

AbstractThe relationship between variables can be made a model or function. The use of the function is as a tool for making a prediction of the response, provided the value of the predictor is known. A function has independent variable, dependent variable, and parameter. The function discussed is an exponential function with base number in positive number. Furthermore, it is developed in the form of the exponential function with one parameter, the exponential function with two parameters and the exponential regression model. To create a function required some parameters. We need a certain method to find parameter. The accuracy of obtained function model shows the goodness of the function in approaching the distribution of the data. The method used to find parameter using the sum square error and logarithm function. Using logarithm function produces a linear function. Computation of parameters using R and Matlab programs. To measure the value of model accuracy using the mean square error. The purpose of this study is to find parameter of the exponential function with one parameter, the exponential function with two parameters and the exponential regression model. The presentation of the result of this discussion is in form of table and picture in the hope that it is easy to understand and interesting. The output of the exponential function with one parameter shows that the base value is 1.050021, the parameter value α is 7.969737 and the prediction accuracy value is 99.996%. The exponential function with two parameters shows that the base value is 0.5, the parameter value α is 7.969737, and the parameter value β is - 0.071, while for the base value is 10, the parameter value α is 7.969737, and the parameter value β is 0.02. The prediction accuracy of the exponential function with two parameters is 99.996%. While the exponential regression model shows that the base value is 0.5, the parameter value α is 128.336, and the parameter value β is -55.828. The prediction accuracy of the exponential regression model is 84.8%.
Development of R-Shiny interface for implementation of backpropagation neural network model in breast cancer classification
Authors: Islahuzaman G , Santoso R , Warsito B , Ispriyanti D , Yasin H 
Published: July 2021

Abstract
Artificial Neural Network or Neural Network (NN) is an information processing system that has similar characteristics to the neural network in living things. One type of NN that is often used in classification is Backpropagation Neural Network (BPNN). BPNN is an NN model that is often used for classification because it does not need to use assumptions and has high accuracy. One of the classification problems that can be solved with BPNN is the classification of breast cancer. The breast cancer data used in this study came from the UCI Machine Learning website. The problem with BPNN is that programming is difficult for users who do not understand the program, especially the R program. Therefore, to make it easier for users to analyze BPNN, an R-Shiny application or interface is created using the RStudio program. The application or R-Shiny interface that has been created has several advantages, namely the application process that is fast in displaying classification results, the use of user-friendly applications and the use of applications that are more comfortable when compared to having to write syntax such as in the R program. BPNN classification results use The R-Shiny interface has a different level of accuracy for each experiment due to the random distribution of training & testing data. The experiments conducted in this study resulted in a range of accuracy values ranging from 58.33% to 91.67% with an average accuracy of 74.17%.