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CAUCHY
Jurnal CAUCHY secara berkala terbit dua (2) kali dalam setahun. Redaksi menerima tulisan ilmiah hasil penelitian, kajian kepustakaan, analisis dan pemecahan permasalahan di bidang Matematika (Aljabar, Analisis, Statistika, Komputasi, dan Terapan). Naskah yang diterima akan dikilas (review) oleh Mitra Bestari (reviewer) untuk dinilai substansi kelayakan naskah. Redaksi berhak mengedit naskah sejauh tidak mengubah substansi inti, hal ini dimaksudkan untuk keseragaman format dan gaya penulisan.
Articles
144
Articles
The Estimation of Generalized Method Moment Poisson Regression Model on the Prevalence of Acute Respiratory Tract Infection (RTI) in South Kalimantan

Mahpolah, Mahpolah, Suharto, Suharto, Wibowo, Arief, Otok, Bambang Widjanarko

CAUCHY Vol 5, No 3 (2018): CAUCHY
Publisher : Mathematics Department, Maulana Malik Ibrahim State Islamic University of Malang

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Abstract

ACUTE (RTI) is still an important health problem because the cause of the death of infants and children under five high enough, 1 from 4 death that happens. The purpose of this research examines the factors that affect the genesis ACUTE (RTI) using poisson regression approach with estimates of the maximum likelihood estimator (MLE) and generalized method moment (GMM). This research done in the area of Health Clinic in South Kalimantan. The results of the study showed that the estimates of the GMM method on Poisson regression model gives better performance in terms of the significance of the parameters than the MLE method. The factors that affect an increasing number of the prevalence of ACUTE (RTI) a region namely persentase Breast Feeding non-exclusive (0.0279), the percentage of low birth weight (0.0569), the percentage of shelter density (0.028), the percentage of the existence of smoker family members in the house (0.0308), the percentage of immunization is not complete (0.0193). While the factors that affect a downturn in the number of the prevalence of ACUTE (RTI) in a region which is the percentage of the number of infants less than 2 (0.0364), the percentage of normal nutrition status (0.0224), the percentage of Mothers Education on high school (0.0339), and the percentage of social economy (UMP enough to top) (0.0194).

Improving the Guidance Learning (LBB) Consumer Satisfaction in Malang using DANP - TOPSIS method

Andawaningtyas, Kwardiniya, Handamari, Endang Wahyu, Karim, Corina

CAUCHY Vol 5, No 3 (2018): CAUCHY
Publisher : Mathematics Department, Maulana Malik Ibrahim State Islamic University of Malang

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Abstract

Decision analysis of Multiple Attribute Decision Making (MADM) model is used to assess the performance, not only in a rank but also in a plan of marketing strategy as an effort to increase consumers?? satisfaction by combining DEMATEL-based Analytical Network Process (DANP) method and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method. One of the industrial services in the education nowadays is the services of the Guidance Learning (LBB). This article has 3 alternatives to 6 criteria. The questionnaire was distributed to 80 LBB?? students and 55 LBB?? mentors. The result of the dominant criteria affecting customer satisfaction of LBB in Malang by DANP method is the mentor quality. Meanwhile, the TOPSIS result showed that the LBB of Avicenna Education Malang is the best alternative to the marketing strategy..

Restricted Maximum Likelihood Method As An Alternative Parameter Estimation in Heteroscedastic Regression

Masrokhah, Dwi, Soehono, Loekito Adi, Astutik, Suci

CAUCHY Vol 5, No 3 (2018): CAUCHY
Publisher : Mathematics Department, Maulana Malik Ibrahim State Islamic University of Malang

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Abstract

Students are part of the community who have an income. The income of students are pocket money, scholarships, part-time jobs and so forth. They are trying to become trendsetter in get dress and . The consumption patterns are very influential in behavior of saving. If the savings increases not only the public funds will increase but also the investment. If the investment increases the economic growth has also increased. The purpose of this research is to estimate multiple regression parameters using REML methods in modeling the student??s saving in Faculty of Mathematics and Natural Science, Brawijaya University. The variables used were X_1= The student??s age (years), X_2= The amount of income of student??s parent (thousand rupiah), X_3= The amount of student??s pocket money (thousand rupiah), X_4= The amount of student??s additional income (thousand rupiah), X_5= The amount of student??s consumption (thousand rupiah) and Y= The amount of student??s saving (thousand rupiah).REML method can overcome heteroscedasticity error variance and unbiased estimator. The model of student??s saving is using REML method as follows:Y ?_i= -1855,66 +121,5 X_1+0.0098X_2+0.0524 X_3+0.5587 X_4-0.5851X_5Student??s saving affected by: student??s age (years), the amount of student??s additional income (thousand rupiah), and the amount of student??s consumption (thousand rupiah).

Front -Matter

Matter, Front

CAUCHY Vol 5, No 3 (2018): CAUCHY
Publisher : Mathematics Department, Maulana Malik Ibrahim State Islamic University of Malang

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Abstract

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Simulation Study The Using of Bayesian Quantile Regression in Nonnormal Error

Muharisa, Catrin, Yanuar, Ferra, Devianto, Dodi

CAUCHY Vol 5, No 3 (2018): CAUCHY
Publisher : Mathematics Department, Maulana Malik Ibrahim State Islamic University of Malang

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Abstract

The purposes of this paper is  to introduce the ability of the Bayesian quantile regression method in overcoming the problem of the nonnormal errors using asymmetric laplace distribution on simulation study. Method: We generate data and set distribution of error is asymmetric laplace distribution error, which is non normal data.  In this research, we solve the nonnormal problem using quantile regression method and Bayesian quantile regression method and then we compare. The approach of the quantile regression is to separate or divide the data into any quantiles, estimate the conditional quantile function and minimize absolute error that is asymmetrical. Bayesian regression method used the asymmetric laplace distribution in likelihood function. Markov Chain Monte Carlo method using Gibbs sampling algorithm is applied then to estimate the parameter in Bayesian regression method. Convergency and confidence interval of parameter estimated are also checked. Result: Bayesian quantile regression method results has more significance parameter and smaller confidence interval than quantile regression method. Conclusion: This study proves that Bayesian quantile regression method can produce acceptable parameter estimate for nonnormal error.

On The Metric Dimension of Some Operation Graphs

Marsidi, Marsidi, Agustin, Ika Hesti, Dafik, Dafik, Alfarisi, Ridho, Siswono, Hendrik

CAUCHY Vol 5, No 3 (2018): CAUCHY
Publisher : Mathematics Department, Maulana Malik Ibrahim State Islamic University of Malang

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Abstract

Let  be a simple, finite, and connected graph. An ordered set of vertices of a nontrivial connected graph  is  and the -vector  represent vertex  that respect to , where  and  is the distance between vertex  and  for . The set  called a resolving set for  if different vertex of  have different representations that respect to . The minimum of cardinality of resolving set of G is the metric dimension of , denoted by . In this paper, we give the local metric dimension of some operation graphs such as joint graph , amalgamation of parachute, amalgamation of fan, and .

Back - Matter

Matter, Back

CAUCHY Vol 5, No 3 (2018): CAUCHY
Publisher : Mathematics Department, Maulana Malik Ibrahim State Islamic University of Malang

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Abstract

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Structural Equation Modeling Based on Variance The Density Index of Larvae of The Rainy Season in the City of Banjarbaru

Isnawati, Isnawati, Otok, Bambang Widjanarko, Suharto, Suharto, Wibowo, Arief

CAUCHY Vol 5, No 3 (2018): CAUCHY
Publisher : Mathematics Department, Maulana Malik Ibrahim State Islamic University of Malang

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Abstract

Climate change causes changes rainfall, temperature, air humidity and wind direction so that affect the reproduction of vectors of diseases such as the mosquito Aedes, Malaria, etc. that it needs to be monitored the increase in many cases DB. free number of larvae (ABJ) is one of the larva density indicator, although ABJ has more than 90 percent but morbidity remains high. The condition of the ABJ not describes the density of larvae jentik, so that the need to study the density jentik indicator that more can describe as the larvae density index with SEM based Variance approach. The results of the study showed that the structural model nonparametric to larva density is the best model based on the criteria of R2 and Q2. The Ministry of Health and behavior, environment condition and breeding place/site effect on the larva density of 87.7%. The dominant indicator counseling on health services, knowledge on the behavior of the temperature of the water on the conditions in the environment and the material container on the breeding place/sites. While on the larva density each indicator provides value loading, larvae density index (0.864), House index (0.459), Container index (0.894), and Breateau index (0.925). Environmental conditions the dominant factor in affecting larva density decline of 32.4%, with each indicator larvae density index (28%), House index (15%), Container index (29%), and Breateau index (30%).

Simulation Study The Implementation of Quantile Bootstrap Method on Autocorrelated Error

Saputri, Ovi Delviyanti, Yanuar, Ferra, Devianto, Dodi

CAUCHY Vol 5, No 3 (2018): CAUCHY
Publisher : Mathematics Department, Maulana Malik Ibrahim State Islamic University of Malang

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Abstract

Quantile regression is a regression method with the approach of separating or dividing data into certain quantiles by minimizing the number of absolute values from asymmetrical errors to overcome unfulfilled assumptions, including the presence of autocorrelation. The resulting model parameters are tested for accuracy using the bootstrap method. The bootstrap method is a parameter estimation method by re-sampling from the original sample as much as R replication. The bootstrap trust interval was then used as a test consistency test algorithm constructed on the estimator by the quantile regression method. And test the uncommon quantile regression method with bootstrap method. The data obtained in this test is data replication 10 times. The biasness is calculated from the difference between the quantile estimate and bootstrap estimation. Quantile estimation methods are said to be unbiased if the standard deviation bias is less than the standard bootstrap deviation. This study proves that the estimated value with quantile regression is within the bootstrap percentile confidence interval and proves that 10 times replication produces a better estimation value compared to other replication measures. Quantile regression method in this study is also able to produce unbiased parameter estimation values.

Geographically Weighted Regression to Predict the Prevalence of Hypertension Based on the Risk Factors in South Kalimantan

Suroto, Suroto, Otok, Bambang Widjanarko, Suharto, Suharto, Wibowo, Arief

CAUCHY Vol 5, No 3 (2018): CAUCHY
Publisher : Mathematics Department, Maulana Malik Ibrahim State Islamic University of Malang

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Abstract

Hypertension is one of the disease is not contagious diseases which is a public health problem. Uncontrolled Hypertension can trigger a degenerative diseases such as congestive heart failure, renal failure and vascular disease. Hypertension is called the silent killer because his nature the condition is asymptomatic and can cause a fatal stroke. With the increasing prevalence of cases of degenerative diseases, one only hypertension, then the researchers want to predict the variables very big role as one of the risk factors of Genesis hypertension. With clearly know the risk factors that play against genesis hypertension is expected to be used as a reference for the prevention and control so that they can reduce the prevalence of hypertension and prevent deaths from degenerative diseases, especially hypertension. The results of the study showed that the results of the modeling the prevalence of hypertension in South Kalimantan Province using linier regression there is no factor that affect the genesis of hypertension. The prevalence of hypertension spread spatially because there are heterogenitas between the location of the observation that means that observations of a location depends on the observations in another location that the distance is near so do spatial regression modeling with Adaptive Gaussian kernel function, meghasilkan 5 groups. Group I consists of the districts Tanah Laut and Tanah Bumbu; group II, Kota Baru; Group III consists of Banjar, Kota Banjar Baru, Kota Banjarmasin; Group IV on the Barito Kuala Regency and the Group V consists of Tapin, H S Selatan, H S Tengah, H S Utara, Tabalong, Balangan.