bluuebunny/crossref_metadata_2025 huggingface dataset:
Breve Reseña sobre el Contexto Social, Histórico y Cultural de la Novela “Kartápolis, la Enfermera del San Simón
Authors: Marrero González Cristo Manuel
Published: September 2020

Se trata de una reseña sobre la novela “Kartápolis, la Enfermera del San Simón” del autor el doctor José Siles González. No se trata en sí de un análisis literario completo ya que no resumo ni abordo la trama ni el argumento de forma directa, sino que abordo el contexto social, histórico y cultural de la obra.
Los círculos bolivarianos: el mito de la unidad del pueblo
Authors: Arenas Nelly , Gómez Calcaño Luis
Published: September 2020

Este artículo analiza los círculos bolivarianos, organizaciones promovidas por el presidente de Venezuela, Hugo Chávez, desde el año 2001. Se examinan la definición, los objetivos y las formas de acción de estas organizaciones, para comprender su función en la construcción de un mito de la unidad del pueblo, parte integrante de la doctrina de la «Revolución Bolivariana». La profunda crisis sociopolítica que precedió a la elección de Chávez, asociada a la arraigada presencia del culto a Bolívar en el imaginario político venezolano, contribuyen a explicar la creación de estas organizaciones y su denominación. Se analizan los papeles asignados a los círculos como organizadores, canalizadores de demandas y formadores de ideología, así como también el de defender con las armas la «revolución».
Evaluation of the bacteriocin produced by strain 9 lactic acid bacteria isolate for biopreservation
Authors: Sukrama I Dewa Made , Franciska Juliana , Suardana I Wayan
Published: September 2020

Aim: This study aimed to determine the effect of the bacteriocin produced by strain 9 lactic acid bacteria (LAB) isolate on the biopreservation of beef.

Materials and Methods: The strain 9 LAB isolate was identified conventionally by culturing with de Man, Rogosa, and Sharpe broth medium followed by Gram staining and catalase testing. The molecular confirmation of the isolate involved analyzing the 16S rRNA gene with specific primers, that is, B27F (5-AGAGTTTGATCCTGGCTCAG-3) and U1492R (5-GGTTACCTTGTTACGACTT-3). Then, the isolate was centrifuged to evaluate the bacteriocin production, and the effect of the biopreservative activity in beef was evaluated by measuring the NH3 produced with the Eber test and the organoleptic acceptance from expert panels.

Results: This study confirmed that the strain 9 LAB isolate was a strain of Pediococcus pentosaceus, and the bacteriocin product showed biopreservative potential. The biopreservative potential was characterized by a significant decline in the production of NH3 and the panel's acceptance of the texture and tenderness of the beef, compared with the control, after 10 days of constant treatment.

Conclusion: This study highlighted the high biopreservative potency of pediocin produced by P. pentosaceus strain 9. This was noted by the production of NH3 and the modifications in texture and tenderness.
Poligami dalam Hermeneutika Feminis Amina Wadud
Authors: Anam Haikal Fadhil
Published: September 2020

Artikel ini menelaah poligami dalam perspektif hermeneutika feminisme ala Amina Wadud. Buku Qur’an and Woman Rereading the Sacred Text from a Woman’s Perspective adalah landasan dasar dalam perwakilan pandangan Amina Wadud pada tiga pembahasan penting dalam pemikiran pada konsep pembebasan, konsep patriarkhi, dan klasifikasi makna feminis. Penulisan ini membedah hakikat pemikiran Amina Wadud pada hak perempuan dan kebebasan poligami dengan syarat. Islam adalah agama kebebasan dalam menata muamalat dalam pola pernikahan yang rahmatan lilalamin.[The article talks about polygamy in Amina Wadud's hermeneutic feminism theory. The base paper, the Qur'an and Woman Rereading the Sacred Text from a Woman's Perspective, is an essential root in Amina Wadud's thought view. Three meaningful discussions are in Amina Wadud's thoughts on freedom concepts in human rights, patriarchal concepts inhabit rule and classification of feminist meaning in the text Qur'an. This paper examines Amina Wadud's thoughts on women's rights and the polygamy perspective with the rule. Islam is a peaceful religion in engaging relationships in a pattern of marriage.]
OPTIMALISASI PORTOFOLIO SAHAM MENGGUNAKAN METODE MEAN ABSOLUTE DEVIATION DAN SINGLE INDEX MODEL PADA SAHAM INDEKS LQ-45
Authors: Wulandari Diah , Ispriyanti Dwi , Hoyyi Abdul
Published: September 2020

Stock investment is the planting of money in a securities that indicates the ownership of a company in order to provide benefits in the future. In obtaining optimal results from stock investments, investors are expected to create a series of portfolios. The portfolio will help investors in allocating some funds in different types of investments in order to achieve optimal profitability. For selection of optimal stocks representing LQ-45 Index, used 2 methods of Mean Absolute Deviation (MAD) method and Single Index Model (SIM) method. In MAD method, 5 best stocks are BBCA with weight 23%, INDF 8%, KLBF 23%, TLKM 23%, and UNVR 23%. While the SIM method of candidate portfolio obtained is AKRA with weight 15,459%, BBCA 48,193%, BBNI 5,028%,KLBF 0,258% and TLKM 31,062%. Portfolio performance meter is used by sharpe ratio. The value of sharpe ratio is 0,36754 for optimal portfolio using MAD method and 0,40782 for optimal portfolio using SIM method, this means that optimal portfolio using SIM method has better performance than MAD. Keywords: Investment, Portfolio, Index LQ-45, Mean Absolute Deviation, Single Index Model, Sharpe Ratio
PEMODELAN INDEKS HARGA SAHAM GABUNGAN MENGGUNAKAN REGRESI SPLINE MULTIVARIABEL
Authors: Afa Ihdayani Banun , Suparti Suparti , Rahmawati Rita
Published: September 2020

The Composite Stock Price Index (CSPI) is a composite index of all types of shares listed on the stock exchange and their movements indicate the conditions occurring in the stock market. CSPI movement is an important indicator for investors to determine whether they will sell, hold, or buy a stock. One of the factors that influence the movement of CSPI is Inflation (X1), Exchange Rate (X2) and SBI rate (X3). This study aims to obtain the best CSPI model using a multivariable nonparametric spline regression approach. The approach is done by nonparametric regression because the regression curve obtained does not show a certain relationship pattern. Spline is very dependent on the order and location of the knot point. The best spline model is the model that has the minimum MSE (Mean Square Error) value. In this study, the best spline regression model is when X1 is 4 order, X2 is 2 order and X3 is 2 order. The number of knots on X1 is 1 knot at 8.22, X2 is 2 knots at 13066.82 and 13781.75 While X3 is 2 knots at 6.6 and 6.67 with value of MSE equal to 6686.85.Keywords: Composite Stock Price Index, Multivariable Spline Regression, MSE
ANALISIS ANTREAN BUS NONPATAS AKAP DAN AKDP JALUR TIMUR TERMINAL TIRTONADI KOTA SURAKARTA
Authors: Sitomurang Rosalina Aprilda , Sugito Sugito , Mukid Moch. Abdul
Published: September 2020

The queuing system is a set of customers, services and a set of rules governing the arrival of its customers and services. Queue is a waiting phenomenon that is part of everyday human life. The queue is formed if the number of subscribers to be served exceeds the available service capacity. Queue phenomenon one of them seen in the queue nonpatas buses at Terminal Tirtonadi Surakarta. Nonpatas bus lanes studied include non-purpose buses Surabaya, Karanganyar, Wonogiri, Purwodadi and Pedesaan. The queue displant used is FIFO (First In First Out). For the five nonpatas bus lanes it meets steady state conditions because it has utility value less than 1. The selected model is a model that has the following 4 types of distributions: Erlang, Weibull, Gamma and Lognormal. The queue model generated for the five tracks (ERLA/ERLA/1):(GD/∞/∞) for Surabaya nonpatas buses, (ERLA/WEIB/1):(GD/∞/∞) for Karanganyar nonpatas buses, (GAMM/WEIB/1):(GD/∞/∞) for Wonogiri nonpatas buses, (ERLA/WEIB/1):(GD/∞/∞) for Purwodadi nonpatas buses, (WEIB/LOGN/1):(GD/∞/∞) for Pedesaan nonpatas buses. Based on the value of the system performance measure indicated that the five lines are queue system is good. Keywords: Beta, Erlang, FIFO, Gamma, Steady State Conditions, Lognormal, Queue Model, Queuing Systems, System Performance Measure, Weibull
PEMODELAN DEFORESTASI HUTAN LINDUNG DI INDONESIA MENGGUNAKAN MODEL GEOGRAPHICALLY AND TEMPORALLY WEIGHTED REGRESSION (GTWR)
Authors: Adiningrumh Thea Zulfa , Prahutama Alan , Santoso Rukun
Published: September 2020

Regression analysis is a statistical analysis method that is used to modeling the relationship between dependent variables and independent variables. In the linear regression model only produced parameter estimators are globally, so it’s often called global regression. While to analyze spatial data can be used Geographically Weighted Regression (GWR) method. Geographically and Temporally Weighted Regression (GTWR) is the development of  GWR model to handle the instability of a data both from the spatial and temporal sides simultaneously. In this GWR modeling the weight function used is a Gaussian  Kernel, which requires the bandwidth value as a distance parameter. Optimum bandwidth can be obtained by minimizing the CV (cross validation) coefficient value. By comparing the R-square, Mean Square Error (MSE) and Akaike Information Criterion (AIC) values in both methods, it is known that modeling the level of deforestation in protected forest areas in Indonesia in 2013 through 2016 uses the GTWR method better than global regression. With the R-square value the GTWR model is 25.1%, the MSE value is 0.7833 and AIC value is 349,6917. While the global regression model has R-square value of 15.8%, MSE value of 0.861 and AIC value of 361,3328. Keywords : GWR, GTWR, Bandwidth, Kernel Gaussian
KAPABILITAS PROSES DENGAN ESTIMASI FUNGSI DENSITAS KERNEL PADA PRODUKSI DENIM DI PT APAC INTI CORPORA
Authors: Ramadhani Puput , Ispriyanti Dwi , Safitri Diah
Published: September 2020

The quality of production becomes one of the basic factors of consumer decisions in choosing a product. Quality control is needed to control the production process. Control chart is a tool used in performing statistical quality control. One of the alternatives used when the data obtained is not known distribution is analyzed by nonparametric approach based on estimation of kernel density function. The most important thing in estimating kernel density function is optimal bandwidth selection (h) which minimizes Cross Validation (CV) value. Some of the kernel functions used in this research are Rectangular, Epanechnikov, Triangular, Biweight, and Gaussian. If the process control chart is statistically controlled, a process capability analysis can be calculated using the process conformity index to determine the nature of the process capability. In this research, the kernel control chart and process conformity index were used to analyze the slope shift of Akira-F style fabric and Corvus-SI style on the production of denim fabric at PT Apac Inti Corpora. The results of the analysis show that the production process for Akira-F style is statistically controlled, but Ypk > Yp is 0.889823 > 0,508059 indicating that the process is still not in accordance with the specified limits set by the company, while for Corvus- SI is statistically controlled and Ypk < Yp is 0.637742 < 0.638776 which indicates that the process is in accordance with the specification limits specified by the company. Keywords:     kernel density function estimation, Cross Validation, kernel control chart, denim fabric, process capability
ANALISIS KEPUASAN DAN LOYALITAS PELANGGAN DALAM PEMESANAN TIKET PESAWAT SECARA ONLINE MENGGUNAKAN PENDEKATAN PARTIAL LEAST SQUARE (PLS)
Authors: Berutu Trisnawati Gusnawita , Hoyyi Abdul , Sugito Sugito
Published: September 2020

Technology advances are bring rapid changes, thus bringing the world to the information society. From this technological progress thus e-commerce emerged, as a means to meet the needs of goods and services through internet access (online). This is what the airlines utilized by cooperating with various internet service providers (online), to provide convenience and comfort of airplane passengers in buying tickets without having to come directly to the place and through intermediaries. To provide the best service, need to know what factors that influence customer satisfaction in ordering airline tickets online. Appropriate modeling for this problem using structural equation modeling, with Partial Least Square (PLS) approach. The PLS approach is chosen because it is not based on several assumptions, one of these is the normal multivariate assumption. In this research, the exogenous latent variables used are performance, access, security, sensation, information, and web design, while the endogenous latent variables are satisfaction and loyalty. Based on the results of the analysis it can be concluded that the latent variables of access, security, sensation, information, and web design are able to explain the latent satisfaction variable of 70.32% while the satisfaction latent variable is able to explain the latent variable of loyalty by 36.02%.
ESTIMASI VALUE AT RISK PORTOFOLIO SAHAM MENGGUNAKAN METODE GARCH-COPULA (Studi Kasus : Harga Penutupan Saham Harian Unilever Indonesia dan Kimia Farma Periode 1 Januari 2013- 31 Desember 2016)
Authors: Prasetya Lingga Bayu , Ispriyanti Dwi , Prahutama Alan
Published: September 2020

Any investment in the stock market will earn returns accompanied by risks. Return and risk has a mutual correlation that equilibrium. The formation of a portfolio is intended to provide a lower risk or with the same risk but provide a higher return. Value at Risk (VaR) is a instrument to analyze risk management. Time series model used in stock return data that it has not normal distribution and heteroscedastisicity is Generalized Autoregressive Conditional Heteroscedasticity (GARCH). GARCH-Copula is a combined method of GARCH and Copula. The Copula method is used in joint distribution modeling because it does not require the assumption of normality of the data and can capture tail dependence between each variable. This research uses return data from stock closing prices of Unilever Indonesia and Kimia Farma period January 1, 2013 until December 31, 2016. Copula model is selected based on the highest likelihood log value is Copula Clayton. Value at Risk estimates of Unilever Indonesia and Kimia Farma's stock portfolio on the same weight were performed using Monte Carlo simulation with backtesting of 30 days period data at 95% confidence level. Keywords : Stock, Risk, Generalized Autoregressive Conditional Heteroscedasticity (GARCH), Copula, Value at Risk
ANALISIS TEKNIKAL SAHAM DENGAN INDIKATOR GABUNGAN WEIGHTED MOVING AVERAGE DAN STOCHASTIC OSCILLATOR
Authors: Saputra Yustian Dwi , Maruddani Di Asih I , Hoyyi Abdul
Published: September 2020

The Stochastic Oscillator which is one of the leading indicators has the disadvantage of opening the gap for false signals. To minimize false signals, the smoothing process is carried out using the Moving Average. Stochastic Oscillator is usually combined with SMA (Simple Moving Average). But SMA has the disadvantage of giving the same weight to all data, even though in reality the data that best reflects the next value is the last data. This makes the basis of weighting the WMA (Weighted Moving Average) method.This study aims to test the combination of Stochastic Oscillator with SMA and WMA and use the best combination to predict the trends that will occur and trading decisions taken from the results of these predictions. The research samples were ANTM, BBRI, and GIAA stocks from November 9 2015 to November 9, 2018.The results show a combination of Stochastic Oscillator and WMA is a better combination of predictions than Stochastic Oscillator and SMA because it has a smaller MSE value. Based on the comparison of signal accuracy based on Overbought and Oversold, the best period of combination of Stochastic Oscillator and WMA is period 25. From the predicted trend that will occur with a combination of Stochastic Oscillator and WMA period 25 a decision is made to buy shares for ANTM shares, sell shares for BBRI shares, and waiting for a buy signal for GIAA shares.Keywords: Stochastic Oscillator, SMA, WMA, Predictions, Trends
PERBANDINGAN DIAGRAM KONTROL MEWMA DAN DIAGRAM KONTROL T2 HOTELLING UNTUK PENGENDALIAN KUALITAS PRODUK KAIN POLYESTER (Studi Kasus : PT Daya Manunggal Kota Salatiga)
Authors: Arifa Abdiyasti Nurul , Santoso Rukun , Widiharih Tatik
Published: September 2020

Fabrics is one of the most important needs of human life, so demand for clothing is greatly increased. Polyester fabric is a superior product at PT Daya Manunggal Salatiga because it has good quality. The quality of the fabric is very important because it is very influential in the competition to attract consumer interest. To maintain the consistency of the quality of the products produced in accordance with specifications, it is necessary to control the quality of the production process. The quality characteristics used in the production process of polyester fabric are thick layers, thin layers, two weft threads partially and two weft threads one more interconnected with one another, so multivariate control diagrams are used. Multivariate Exponentially Weighted Moving Average (MEWMA) and T2 Hotelling are control diagrams for monitoring mean process. The results showed that the MEWMA control diagram with lambda 0.7 yielded controlled results with a BKA value of 14.56021. Whereas in the Hotelling T2 control diagram a data reduction of four revisions was made to achieve controlled results with a final BKA value of 10.10928. The controlled production process obtained multivariate process capability values of 0.9672105 <1 which means the process is not capable. Comparison of results from the two methods shows that the MEWMA control diagram is more sensitive than the T2 Hotelling control diagram.Keywords: Fabric, Multivariate Exponentially Weighted Moving Average (MEWMA), Hotelling T2, Process Capability Analysis
ANALISIS STRUCTURAL EQUATION MODELLING PENDEKATAN PARTIAL LEAST SQUARE DAN PENGELOMPOKAN DENGAN FINITE MIXTURE PLS (FIMIX-PLS) (Studi Kasus: Kemiskinan Rumah Tangga di Indonesia 2017)
Authors: Anggita Esta Dewi , Hoyyi Abdul , Rusgiyono Agus
Published: September 2020

Poverty is a complex and multidimensional problem that links several dimensions. Statistical method that can explain the relationship between one latent variable with others is Structural Equation Modelling (SEM). The purpose of this study is to create a structural model of the relationship between education, health, economy and poverty in Indonesia in 2017 by using Structural Equation Modeling with Partial Least Square approach (SEM-PLS) based on predetermined indicators with the results of 11 valid indicators. Based on the model obtained, health has a significant positive effect on education, health and education have a significant positive effect on the economy and the economy has a significant negative effect on poverty. Segmentation based on the relationship of latent variables in structural models can be overcome by Finite Mixture Partial Least Square (FIMIX-PLS) so that it can identify poverty areas in each province in Indonesia with more homogeneous characteristics. The best segmentation result is number of segments (K) = 2 obtained based on the criteria of AIC, BIC, CAIC and Normed Entropy (EN) with an EN value of 0.964 which means the quality of segment separation is very good. Papua and West Papua provinces form one segment in segment 2, while 32 other provinces form one segment in segment 1.Keywords: Poverty, Structural Equation Modelling, Partial Least Square, Finite Mixture, Segmentation.
ANALISIS ANTREAN DAN KINERJA SISTEM PELAYANAN GARDU TOL OTOMATIS GERBANG TOL MUKTIHARJO (Studi Kasus: Gardu Tol Otomatis Gerbang Tol Muktiharjo)
Authors: Sihotang Erna Fransisca Angela , Sugito Sugito , Mukid Moch. Abdul
Published: September 2020

Queue process is a process related to the arrival of customers in a service facility, waiting in line queue if it cannot be served, get service and finally leaves the facility after being served. Research on the queue process can be seen directly through the queue system at the automatic toll booth Muktiharjo. Queue models and their distribution were obtained using the Sigma Magic program. The model of the vehicle queue system at the Muktiharjo Automatic Toll Gate is (GAMM/ GAMM/ 4): (GD/ ∞/ ∞). Based on the values of the queue system performance measures obtained through the MATLAB GUI program as a whole it can be concluded that the queue of vehicles at the Muktiharjo Automatic Toll Gate has a condition where the average number of vehicles estimated in the system every 15 minutes is 25,5646 vehicles. The average number of vehicles in the queue system every 15 minutes is 24,5639 vehicles. The waiting time in the system is estimated to be around 7,99332 seconds. The estimated waiting time in line is around 7,68042 seconds. The queue system has a busy opportunity of 63.2849% and the remaining 36.7106% is a chance the queue system is not busy. The simulation of the vehicle queue system at the Automatic Toll Gate of Muktiharjo Toll Gate by using ARENA is optimal with the number of service points as many as 4 automatic toll booths. Keywords: Automatic Toll Booth, Queue, Gamma Distribution, Performance Size, Queue Simulation
PREDIKSI HARGA EMAS MENGGUNAKAN FEED FORWARD NEURAL NETWORK DENGAN METODE EXTREME LEARNING MACHINE
Authors: Izati Nisa Afida , Warsito Budi , Widiharih Tatik
Published: September 2020

The prediction of gold price aims to find out the gold price in the future on the basis of historical data on gold prices in the past, so it can be used as a consideration by gold investors to investing in gold. Prediction methods that do not require assumptions, one of which is Artificial Neural Networks. In this study, using Artificial Neural Networks, Feed Forward Neural Network with Extreme Learning Machine (ELM). ELM is a non-iterative algorithm so ELM has advantages in process speed. The input weight and bias for this method are determined randomly. After that, to find the final weight using the Moore-Penrose Generalized Inverse calculation on the hidden layer output matrix. The best model selection criteria uses the Mean Absolute Percentage Error (MAPE). This study shows that the results of the training and testing process from the model 1 input neuron and 7 hidden neurons are very good, because it produces MAPE training = 0.6752% and MAPE testing = 0.8065%. Also gives a very good prediction result because it has MAPE = 0.5499% Keywords: gold price, Extreme Learning Machine, MAPE
OPTIMASI PARAMETER MODel AUTOREGRESSIVE MENGGUNAKAN ALGORITMA PARTICLE SWARM OPTIMIZATION
Authors: Ramadhan Setyoko Prismanu , Yasin Hasbi , Suparti Suparti
Published: September 2020

Box-Jenkins ARIMA method is a linear model in time series analysis which is widely used in various fields. One estimation method for Box-Jenkins ARIMA model is OLS method which aims to minimize the number of squared errors. This method is not effective when applied to time series data that is random, nonlinear and non-stationary. In this study discussed the alternative method of the PSO algorithm as an parameter optimization of the ARIMA model. PSO algorithm is an optimization method based on the behavior of a flock of birds or fish. The main advantage of the PSO algorithm is having a simple, easy to implement and efficient concept in calculations. This method is applied to data from PT Perusahaan Gas Negara shares. The results of both methods will be compared. In the AR model (1) the value of MSE is 0.532 and MAPE is 0.993. Meanwhile, the PSO algorithm obtained MSE 0.531 and MAPE 0.988. It was found that the PSO algorithm resulted in smaller MSE and MAPE values and could provide better results.Keywords : Time Series Analysis, Autoregressive, PSO
PEMODELAN INDEKS PEMBANGUNAN MANUSIA DI JAWA TENGAH DENGAN REGRESI KOMPONEN UTAMA ROBUST
Authors: Faizia Tsania , Prahutama Alan , Yasin Hasbi
Published: September 2020

Robust principal component regression is development of principal component regression that applies robust method at principal component analysis and principal component regression analysis. Robust principal component regression does not only overcome multicollinearity problems, but also overcomes outlier problems. The robust methods used in this research are Minimum Covariance Determinant (MCD) that is applied when doing principal component analysis and Least Trimmed Squares (LTS) that is applied when doing principal component regression analysis. The case study in this research is Human Development Index (HDI) in Central Java in 2017 which is influenced by labor force participation rates, school enrollment rates, percentage of poor population, population aged 15 years and over who are employed, health facilities, gross enrollment rates, and net enrollment rates. The model of HDI in Central Java in 2017 using robust principal component regression MCD-LTS provides the most effective result for handling multicollinearity and outliers with Adjusted R2 value of 0.6913 and RSE value of 0.469. Keywords: Robust Principal Component Regression, Multicollinearity, Outliers, Minimum Covariance Determinant (MCD), Least Trimmed Squares (LTS), Human Development Index (HDI).
PERAMALAN JUMLAH WISATAWAN YANG BERKUNJUNG KE OBJEK WISATA DI JAWA TENGAH MENGGUNAKAN VARIASI KALENDER ISLAM REGARIMA
Authors: Jesica Haniela Puja , Ispriyanti Dwi , Tarno Tarno
Published: September 2020

Tourism is one of the most strategically controlled areas that have been developed.The number of tourists in Central Java is constantly rising in the month of Eid Al-Fitr caused by holiday and mudik to hometown. The shift of the Eid Al-Fitr month on the data will form a seasonal pattern with an unequal period, then called moving holiday effect.One of the calendar variationsare often used to remove the moving holiday effect is RegARIMA model. RegARIMA is a combination of the linier regression and ARIMA, which a weight was used as a regression variable and error of regression model was used a variable in the ARIMA process. Based on the analysis carried out on the monthly number of tourists visiting tourist attractions in Central Java data for the period January 2011 to December 2017, the RegARIMA (1,1,1) (0,0,1)12model as the best model because it have the lowest AIC value than other model. The forecasting results in 2018 shows an increase on number of tourists data on June 2018 which coincided with the Eid Al-Fitr holiday on 15 June 2018. sMAPE value is 23,298%.Keyowrds:Time Series, Tourists, RegARIMA, Moving Holiday Effect
REGRESI ROBUST ESTIMASI-M DENGAN PEMBOBOT ANDREW, PEMBOBOT RAMSAY DAN PEMBOBOT WELSCH MENGGUNAKAN SOFTWARE R
Authors: Deria Aulia Desy , Hoyyi Abdul , Mustafid Mustafid
Published: September 2020

Robust regression is one of the regression methods that robust from effect of outliers. For the regression with the parameter estimation used Ordinary Least Squares (OLS), outliers can caused assumption violation, so the estimator obtained became bias and inefficient. As a solution, robust regression M-estimation with Andrew, Ramsay and Welsch weight function can be used to overcome the presence of outliers. The aim of this study was to develop a model for case study of poverty in Central Java 2017 influenced by the number of unemployment, population, school participation rate, Human Development Index (HDI), and inflation. The result of estimation using OLS show that there is violation of heteroskedasticity caused by the presence outliers. Applied robust regression to case study proves robust regression can solve outliers and improve parameter estimation. The best robust regression model is robust regression M-estimation with Andrew weight function. The influence value of predictor variables to poverty is 92,7714% and MSE value is 370,8817. Keywords: Outliers, Robust Regression, M-Estimator, Andrew, Ramsay, Welsch
REGRESI KOMPONEN UTAMA ROBUST S-ESTIMATOR UNTUK ANALISIS PENGARUH JUMLAH PENGANGGURAN DI JAWA TENGAH
Authors: Siburian Jeffri Nelwin J. O. , Rahmawati Rita , Hoyyi Abdul
Published: September 2020

Robust principal component regression s-estimator is principal component regression that applies robust approach method at principal component analysis and s-estimator at principal component regression analysis. The aim of robust principal component regression s-estimator is to overcome multicollinearity problems in multiple linier regression Ordinary Least Square (OLS) and to overcome outlier problems in principal component regression so get the most effective model. Minimum Volume Ellipsoid (MVE) is one of the robust approach methods that applied when doing principal component analysis and S-Estimator is one of the estimation methods that applied when doing principal component regression analysis. The case in this study is the factors that influence the Number of Unemployment in Central Java in 2017. The model that provides the most effective result to handling multicolliniearity and ouliers in the case study  Number of Unemployment in Central Java in 2017 is using robust principal component regression MVE-(S-Estimator) with Adjusted R2 value of 0.9615 and RSE value of 0.4073. Keywords: Robust Principal Component Regression S-Estimator, Multicollinearity, Outliers, Minimum Volume Ellipsoid (MVE), Number of Unemployment.
ANALISIS KLASTER METODE WARD DAN AVERAGE LINKAGE DENGAN VALIDASI DUNN INDEX DAN KOEFISIEN KORELASI COPHENETIC (Studi Kasus: Kecelakaan Lalu Lintas Berdasarkan Jenis Kendaraan Tiap Kabupaten/Kota di Jawa Tengah Tahun 2018)
Authors: Pratiwi Sisca Indah , Widiharih Tatik , Hakim Arief Rachman
Published: September 2020

Based on Central Java Regional Police data, traffic accidents from 2017 to 2018 increased from 17.522 to 19.016 or 8,54 percent. To reduce the number of traffic accidents in Central Java, the initial step was carried out by grouping districts/cities that had the same accident level characteristics based on vehicle type with cluster analysis. The ward and average linkage method is a hierarchical cluster analysis method. ward method can maximize cluster homogeneity. While the average linkage method can generate clusters with small cluster variants. In this study using a measure of squared euclidean distance to measure the similarity between pairs of objects. To determine the quality of clustering results, the validation dunn index and cophenetic coefficients corelation are used. Based on the results of the clustering, the optimal number of clusters is obtained at q = 5 for the average linkage method with the results of validation dunn index = 0,08571196 and the rcoph = 0,687458. Keywords: Accidents, Cluster Analysis, Ward Method, Average linkage, Squared Euclidean Distance, Dunn Index, Cophenetic Correlation Coefficient
KETEPATAN KLASIFIKASI PEMBERIAN KARTU KELUARGA SEJAHTERA DI KOTA SEMARANG MENGGUNAKAN METODE REGRESI LOGISTIK BINER DAN METODE CHAID
Authors: Suhendra Muhammad Arif , Ispriyanti Dwi , Sudarno Sudarno
Published: September 2020

Menurut BPS, jumlah penduduk miskin di Kota Semarang pada Maret 2018 adalah sebesar 73,65 ribu orang. Salah satu program pemerintah dalam percepatan penanggulangan kemiskinan adalah dengan mengeluarkan Kartu Keluarga Sejahtera (KKS) yang diberikan kepada masyarakat yang kurang mampu. Penelitian ini bertujuan untuk mengetahui besarnya ukuran ketepatan klasifikasi pemberian KKS di Kota Semarang. Metode klasifikasi statistik yang digunakan adalah metode Regresi Logistik Biner dan metode Chi-Squared Automatic Interaction Detection (CHAID). Pemberian KKS dipengaruhi oleh banyak faktor, diantaranya jumlah anggota keluarga, status perkawinan, jenis kelamin kepala keluarga, usia kepala keluarga, jenjang pendidikan kepala keluarga dan kepemilikan/penguasaan HP. Pada penelitian ini, data yang digunakan adalah data sekunder hasil Survey Sosial Ekonomi Nasional (SUSENAS) tahun 2018 yang diperoleh dari Badan Pusat Statistik (BPS) Provinsi Jawa Tengah. Perbandingan data training dan testing yang digunakan adalah 60:40. Hasil analisisnya menunjukkan bahwa dengan menggunakan Regresi Logistik Biner, faktor-faktor yang berpengaruh adalah jumlah anggota keluarga dan jenjang pendidikan kepala keluarga dengan ketepatan klasifikasi sebesar 88% dan kesalahan 12%, sedangkan dengan menggunakan CHAID, faktor-faktor yang berpengaruh adalah jumlah anggota keluarga, status perkawinan, usia kepala keluarga, jenjang pendidikan kepala keluarga dan kepemilikan/penguasaan HP dengan ketepatan klasifikasi sebesar 90,2% dan kesalahan 9,8%.Kata kunci: Kartu Keluarga Sejahtera, Klasifikasi, Regresi Logistik Biner, CHAID
PENGELOMPOKAN PROVINSI-PROVINSI DI INDONESIA MENGGUNAKAN METODE WARD (StudiKasus: Produksi Tanaman Pangan di Indonesia Tahun 2018)
Authors: Arif Besya Salsabilla Azani , Rusgiyono Agus , Hoyyi Abdul
Published: September 2020

Cluster analysis is a technique for grouping objects or observations into homogeneous groups. Cluster analysis is divided into two methods, namely hierarchy and non-hierarchy. The hierarchy method generally involves a series of n-1 decisions (n is the number of observations) that combine observations into a tree-like structure or dendogram. Hierarchy is divided into two methods, namely agglomerative (concentration) and splitting (distribution). For non-hierarchical methods, the number of clusters can be determined by the researcher. Ward method is a hierarchical cluster analysis method that can maximize homogeneity in the cluster. The  Sum-of-Square (SSE) formula is used in this method to minimize variations in the clusters that are formed. In this research, squared euclid distance is used to measure the similarity between object pairs. The data used in this study are secondary data on food crop production, namely rice, corn, soybeans, peanuts, green beans, sweet potatoes, and cassava in Indonesia 2018. To determine the cluster, the elbow method is used to form optimal clusters using WSS formula. Based on the analysis results, it was found that the optimal cluster is four clusters. The first cluster consists of 9 Province, the second cluster consists of 20 Province, the third cluster consists of 1 Province, the fourth cluster consists of  2 Province, and the fifth cluster consists of 2 Province.Keywords: Food Crop, Cluster Analysis, Ward Method, Squared Euclid, Elbow Method
PENYUSUNAN DAN PENERAPAN METODE REGRESSION ADAPTIVE NEURO FUZZY INFERENCE SYSTEM (RANFIS) UNTUK ANALISIS DATA KURS IDR/USD
Authors: Mu'affa Lamik Nabil , Tarno Tarno , Suparti Suparti
Published: September 2020

The exchange rate of rupiah is one of the important prices in an open economy because the exchange rate can be used as a tool to measure the economic condition of a country. The movement of the rupiah exchange rate affected the Indonesian economy, maintaining the stability of the rupiah exchange rate became an important thing to do. In an effort to maintain the stability of the rupiah exchange rate, the factors that influence it must first be identified. Several factors affect the IDR / USD exchange rate, namely the large trade price index, foreign exchange reserves, money supply and interest rates. In this study, the Regression Adaptive Neuro Fuzzy Inference System (RANFIS) method was used to analyze the effect of predictor variables on IDR / USD exchange rates. The optimal RANFIS model is strongly influenced by three things, namely the determination of input predictor variable, membership functions, and number of clusters. Determination of the optimal RANFIS model is measured based on the smallest MAPE in-sample. Based on empirical studies applied to predictor variables on IDR / USD exchange rates, it was found that the RANFIS model was optimal, namely with 3 predictor variable inputs consisting of large trade price index variables, money supply and interest rates; with the gauss membership function; 2 clusters and rules produce an MAPE in-sample of 1.93% and an MAPE out-sample of 2.68%, so the performance of the RANFIS model has a very good level of accuracy.
PEMODELAN JUB DAN BI RATE TERHADAP INFLASI DAN KURS RUPIAH MENGGUNAKAN REGRESI SEMIPARAMETRIK BIRESPON BERDASARKAN ESTIMATOR PENALIZED SPLINE
Authors: Femadiyanti Siti Fadhilla , Suparti Suparti , Warsito Budi
Published: September 2020

Some indicators of the Indonesian economy are inflation and the exchange rate of rupiah against US dollar. Inflation and the rupiah exchange rate are thought to be influenced by the money supply (JUB) and the BI Rate. The money supply has a nonparametric relationship pattern to inflation and the rupiah exchange rate, while the BI Rate has a parametric relationship pattern  to inflation and the rupiah exchange rate. The right method for detecting the relationship between inflation and the exchange rate with JUB and BI Rate is birespon semiparametric regression with a splined penalized estimator. The semiparametric regression coefficient of birespon spline penalized is estimated using the Weighted Least square (WLS) method which is determined based on the degree of polynomials, the number and location of the optimal knot points, and the optimal lambda determined based on the minimum of Generalized Cross Validation (GCV). This research uses the R Program. Based on the results of the analysis, the best spline penalized birespon semiparametric regression model is located in the number of knots is 5 at the knot points of 5257,783; 6649,469; 8976,871; 11099,19 and 13535,51 found in the first degree of response is 1 and the second degree of response is 2 with an optimal lambda of 99,99. The results of the performance evaluation of the model produce value of  is 99,9007%, meaning that the model's performance is very good for out samples of the data and the MAPE value of 2.89169% is less than 10% which means the model's performance is very good.
PEMODELAN WAVELET NEURAL NETWORK UNTUK PREDIKSI NILAI TUKAR RUPIAH TERHADAP DOLAR AS
Authors: Nababan Tri Yani Elisabeth , Warsito Budi , Rusgiyono Agus
Published: September 2020

Each country has its own currency that is used as a tool of exchange rate valid in the transaction process. In the process of transaction between countries often experience problems in terms of payment because of the difference in the value of money prevailing in each country. The price movement of the exchange rate or the value of foreign currencies that fluctuate from time to time it encouraged predictions of the value of the rupiah exchange rate against the U.S. dollar. Wavelet Neural Network (WNN) is a combination of methods between wavelet transforms and Neural networks. WNN modeling begins with wavelet decomposition resulting in wavelet coefficients and scale coefficients. Selection of inputs is based on PACF plots and divides into training data and testing data. To determine the final output by calculating the value of MAPE in data testing. The best architecture on WNN model for prediction of the value of the rupiah exchange rate against the U.S. dollar is a model with sigmoid logistic activation function, 2 neurons in the input layer, 10 neurons in the hidden layer, and 1 neuron in the output layer. The MAPE value is obtained at 0.2221%.
KEBIASAAN MAKAN TERIPANG (ECHINODERMATA: HOLOTHURIIDAE) DI PERAIRAN PANTAI PULAU PRAMUKA, KEPULAUAN SERIBU
Authors: Agusta Oriza
Published: September 2020

Teripang adalah biota laut yang bergerak lambat, hidup pada dasar substrat pasir, pasir berlumpur maupun dalam lingkungan terumbu yang. merupakan salah satu sumber protein hewani dan telah lama dikonsumsi oleh masyarakat di dalam maupun di luar negeri. Penelitian dilaksanakan pada bulan April 2012 di Perairan pantai Pulau Pramuka, Kepulauan Seribu. Identifikasi kebiasaan makan teripang dilakukan di Laboratorium Hidrobiologi Fakultas Perikanan dan Ilmu Kelautan Universitas Diponegoro. Tujuan dari penelitian ini adalah Mengetahui kebiasaan makanan teripang di Perairan pantai Pulau Pramuka, Kepulauan Seribu. Pada penelitian ini, menggunakan metode Index of Preponderance. Nilai Index of Preponderance diketahui dengan cara mengamati makanan yang terdapat pada usus Teripang. Teknik sampling teripang yang digunakan dalam penelitian ini adalah metode sensus. Hasil penelitian didapatkan, saat sampling di lapangan diperoleh 3 spesies teripang yaitu Holothuria hilla, Holothuria leucospilota, Holothuria impatiens. Makanan utama dari ke tiga jenis teripang yang di temukan adalah jenis Bacillariophyceae dengan nilai Index of Preponderance masing-masing jenis sebesar Holothuria hilla 51%, Holothuria leucospilota 35,1% dan Holothuria impatiens 52,5%.Kata kunci : Kebiasaan makanan, Pulau Pramuka, TeripangAbstractSea cucumbers are types of sea animals that move slowly, living on the bottom substrate of sand, silt and in the reef environment that one source of animal protein and have long been consumed by people within and outside the country. The research was conducted in April 2012 in the coastal waters of Pramuka Island, Seribu Islands. Identification of the feeding habits of sea cucumbers performed performed in the Laboratory of Hydrobiology Faculty of Fisheries and Marine Science Diponegoro University. The purpose of this study is to food habits of sea cucumber in the waters of the Pramuka Island, Seribu Island. In this study, using the method Index of Preponderance. Value Index of Preponderance is know by observing that there is food in the gut cucumber. The sampling technique used for sea cucumber in this study is the census method. The results obtained when sampling in the field gets the 3 species of sea cucumber are Holothuria hilla, Holothuria leucospilota, Holothuria impatiens. The main meal of the three types of the sea cucumber found such as Bacillariophyceae which have I Index of Preponderance value of each type of Holothuria hilla is 51%, Holothuria leucospilota is 35,1% and Holothuria impatiens is 52,5%.Key words : Food Habits, Pramuka Island, Sea Cucumber
*) Penulis Penanggung Jawab STUDI TAKSONOMI BINTANG LAUT (Asteroidea, Echinodermata) DARI KEPULAUAN KARIMUNJAWA, JEPARA
Authors: - Puspitasari
Published: September 2020

Bintang laut merupakan salah satu kelompok echinodermata yang berperan penting dalam jaring makanan, umumnya sebagai predator dan pemakan detritus. Penelitian ini dilaksanakan pada bulan Desember 2011 – Maret 2012. Penelitian ini bertujuan untuk mengetahui jenis, habitat dan ciri-ciri khusus bintang laut dari perairan Karimunjawa, Jepara. Pengambilan sampel dilakukan di kepulauan Karimunjawa, mencakup sisi barat dan timur pulau Karimunjawa, sisi barat pulau Menjangan Kecil, sisi utara pulau Cemara Kecil dan sisi utara pulau Cemara Besar, menggunakan metode purposive sampling. Sampel bintang laut dikumpulkan dari berbagai habitat di daerah intertidal sampai kedalaman 3 meter. Identifikasi setiap spesies dan pembuatan kunci identifikasi dilakukan di Pusat Penelitian Oseanografi (P2O-LIPI), Jakarta. Sebelas individu bintang laut dari 9 spesies yang mewakili 6 genera dari 4 famili dan 2 ordo berhasil di identifikasi. Sebagian besar bintang laut ditemukan di daerah terumbu karang. Berdasarkan karakter morfologi diketahui bahwa spesies yang tampaknya sama bahkan hidup di lokasi yang sama ternyata adalah spesies yang berbeda yaitu Archaster angulatus dan Archaster typicus, Nardoa frianti dan Nardoa pauciforis serta Linckia laevigata dan Linckia multifora. Semua jenis bintang laut yang dikumpulkan merupakan jenis-jenis yang umum ditemukan di perairan Indonesia.Kata Kunci : Taksonomi, Identifikasi, Bintang Laut, KarimunjawaAbstractSea stars play an important role in food webs, generally as predators and detritus feeder. This research has been conducted in December 2011 – March 2012. This research is subjected to achieved its biodiversity in the Karimunjawa Islands. Samples were collected from western and eastern side of Karimunjawa Island, western side of Menjangan Kecil, northern side of Cemara Kecil and northern side of Cemara Besar island, up to the depth of three meters. Species identification was done at Biology Laboratory of the Research Center for Oceanography (P2O-LIPI) Jakarta. A total of 11 asteroid individuals belonging to 9 species of 6 genera, which represented 4 families and 2 orders have been identified. Most of sea stars were found on the coral reef. Based on morphological characters of sea stars that apparently similar, even living in the same location, however after identified are different species, that is Archaster angulatus and Archaster typicus, Nardoa frianti and Nardoa pauciforis then Linckia laevigata and Linckia multifora. All species was considered common for tropical Indo Pasific region, including Indonesian watersKeywords: Taxonomical, Identification, Asteroidea, Karimunjawa
BEBERAPA ASPEK BIOLOGI UDANG JERBUNG (Penaeus merguiensis) DI PERAIRAN PANTAI CILACAP JAWA TENGAH
Authors: Rutiyaningsih Ayu , Saputra Suradi Wijaya , Djuwito -
Published: September 2020

Eksploitasi udang P. merguiensis dengan alat tangkap jaring arad diduga terus meningkat ditandai dengan meningkatnya produksi  dalam tiga tahun terakhir. Penangkapan yang berlebihan dapat mengancam kelestariannya. Tujuan dari penelitian ini yaitu untuk mengkaji aspek-aspek biologi seperti komposisi hasil tangkapan, distribusi hasil tangkapan, struktur ukuran, ukuran pertama tertangkap (L50%), panjang infinity (L∞), nisbah kelamin, tingkat kematangan gonad (TKG), sifat pertumbuhan, dan faktor kondisi. Selain itu, membuat konsep pengelolaan sumberdaya perikanan udang P. merguiensis. Metode yang digunakan dalam pengambilan  sampel yaitu metode survei dengan sistematik random sampling. Sampel udang diambil secara proposional yaitu sekitar 10% dari total hasil tangkapan. Hasil penelitian menunjukkan bahwa ukuran pertama tertangkap (L50%) panjang karapas 43 mm. Panjang infinity (L∞) udang P. merguiensis betina  panjang karapas 63,58 mm dan udang P. merguiensis jantan 60,42 mm. Perbandingan nisbah kelamin jantan dan betina 1 : 1,61. Udang P. merguiensis  didominasi oleh TKG I. Pertumbuhan udang P. merguiensis jantan bersifat allometrik negatif yaitu pertambahan panjang lebih cepat daripada pertambahan beratnya, dikarenakan nilai b sebesar 2,626. Udang P. merguiensis betina memiliki sifat pertumbuhan isometrik yaitu pertambahan panjang selaras dengan pertambahan berat, dikarenakan nilai b sebesar 3,105. Faktor kondisi udang P. merguiensis jantan sebesar 1,152 dan betina  2,051, sehingga udang Jerbung betina lebih montok dibandingkan udang P. merguiensis jantan. Udang P. merguiensis layak ditangkap pada ukuran yang melebihi L50% yaitu panjang karapas > 43 mm.
STUDI ANALISA PLANKTON UNTUK MENENTUKAN TINGKAT PENCEMARAN DI MUARA SUNGAI BABON SEMARANG
Authors: Cahyaningtyas Ina , Hutabarat Sahala , Soedarsono Prijadi
Published: September 2020

Daerah Aliran Sungai (DAS) Babon merupakan salah satu DAS yang sangat penting bagi kelangsungan ekosistm khususnya wilayah Semarang dan sekitarnya. Plankton merupakan organisme perairan yang keberadaannya dapat menjadi indikator perubahan kualitas biologi perairan sungai. Plankton memegang peran penting dalam mempengaruhi produktivitas primer perairan sungai. Perairan sungai Babon secara nyata telah menerima limbah yang berasal dari kegiatan industri yang berada di sekitar sungai Babon dan limbah yang berasal dari kegiatan rumah tangga (domestik). Keadaan ini diduga menyebabkan menurunnya kualitas lingkungan muara Sungai Babon. Penelitian ini dilakukan untuk mengkaji bagaimana tingkat pencemaran di muara Sungai Babon. Pengamatan dilakukan berdasarkan analisis SI (Saprobik Indeks) dan TSI (Tropik Saprobik Indeks) untuk mengetahui sejauh mana tingkat pencemaran yang terjadi. Materi yang digunakan dalam penelitian ini adalah fitoplankton dan zooplankton yang berada di muara Sungai Babon berikut parameter fisika dan kimia. Kelimpahan fitoplankton  di muara Sungai Babon adalah 10.765 – 13.777 ind/L dengan 19 - 24 genera. Kelimpahan zooplankton adalah 218-241 Ind/m3 dengan 9 genera. Berdasarkan kelimpahan plankton maka didapatkan nilai Saprobik Indeks (SI) berkisar 0,07 - 0,34 dan nilai Tropik Saprobik Indeks berkisar (-0,73) – (-0,98) kualitas perairan muara sungai Babon selama penelitian termasuk dalam tingkat α-Mesosaprobik atau dalam kondisi tercemar sedang hingga berat.