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All Journal ETIKONOMI Jurnal Matematika Jurnal Ekonomi Kuantitatif Terapan Media Statistika Jurnal Gaussian Jurnal Gizi Klinik Indonesia Jurnal Statistika Universitas Muhammadiyah Semarang Perfecting a Video Game with Game Metrics Jurnal Akuntabilitas Manajemen Pendidikan Jurnal BPPK : Badan Pendidikan dan Pelatihan Keuangan Jurnal Komunikasi Pendidikan

Rezzy Eko Caraka

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Author-ID : 452054

Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Languange, Linguistic, Communication & Media Mathematics Public Health Other

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Persepsi tubuh dan gangguan makan pada remaja Kurniawan, Mohamad Yulianto; Briawan, Dodik; Caraka, Rezzy Eko
Jurnal Gizi Klinik Indonesia Vol 11, No 3 (2015): Januari
Publisher : Minat S2 Gizi dan Kesehatan, Prodi S2 IKM, FK-KMK UGM

Background:Â There can no longer be any doubt that adolescents do indeed have body esteem problems. Several types of research seem to suggest that this wrong behavior caused by some negative perceptions as a result of dissatisfaction with the body and a personâ€™s level of self-confidence. Therefore they often do misperceptions of his/her body that can lead to wrong dietary behavior. Itâ€™s related to the development of more severe body image and eating-related problems.Objective:Â This study determined the relationship of body image perception and eating disorders in adolescents.Method:Â A cross-sectional study was applied in this study. The subjects were 120 new students majoring in a nutritional program in Bogor Agricultural University (IPB). They completed a questionnaire measuring appearance evaluation, appearance orientation, body areas satisfaction, overweight preoccupation, self-classified weight and eating disorders. Multidimensional Body Self-Relations Questionnaire-Appearance Scale (MBSRQ-AS) method is used to assess body image perception and Eating Attitude Test 40 (EAT-40) to predict eating disorders.Results:Â Descriptive analysis showed nutritional status were categorized as normal (83.3%), overweight (10.0%), obesity (4.2%) and thin (2.5%). With MBSRQ-AS method, most of the adolescents have appearance evaluation (80.0%), appearance orientation (99.2%), body areas satisfaction (80.8%), self-classified weight (71.7%) were categorized as negative, whereas overweight preoccupation (57.5%) were categorized as positive. There was (7.8%) female subject with eating disorders with more risk or have attitude the desire to eat continuously and canâ€™t stop eating (2-3 times a month).Conclusion:Â Statistically using a significance level (Î±=5%) obtained a significant correlation between body image perception in overweight preoccupation subscale with eating disorders. However, there were no significant correlations for other subscales.

PEMODELAN INFLASI BERDASARKAN HARGA-HARGA PANGAN MENGGUNAKAN SPLINE MULTIVARIABEL Prahutama, Alan; Utama, Tiani Wahyu; Caraka, Rezzy Eko; Zumrohtuliyosi, Dede
MEDIA STATISTIKA Vol 7, No 2 (2014): Media Statistika
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Inflation is defined as a sustained increase in the general level of price for goods and services. Some of the events that led to inflation in Indonesia is rising fuel prices, rising prices of meat and chili. Inflation has negative impact, because decreased purchasing power. Â So that the inflation model is needed. Modeling inflation can be use regression models. The approach can be performed with nonparametric regression, one of method of nonparametric regression is spline method. In this case, use three predictors to modeling inflation using spline multivariable. The predictors are price of rice, price of chicken, and price of chili. Obtained multivariable spline models with R-square of 93.94% with optimal m = 2 (quadratic) for 1 knots.Â Keywords: Spline Multivariable, GCV, Inflation

TIME SERIES ANALYSIS USING COPULA GAUSS AND AR(1)-N.GARCH(1,1) Caraka, Rezzy Eko; Yasin, Hasbi; Sugiarto, Wawan; Ismail, Kadi Mey
MEDIA STATISTIKA Vol 9, No 1 (2016): Media Statistika
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

In this case, the Gaussian Copula is used to connect the data that correlates with the time and with other data sets. Most often, practitioners rely only on the linear correlation to describe the degree of dependence between two or more variables; an approach that can lead to quite misleading conclusions as this measure is only capable of capturing linear relationships. Correlation doesnâ€™t mean causation, prediction using Copula is built on three things that the marginal distribution function, the kernel function, and the function of the Copula. Gaussian Copula involves the covariance matrix are approximated by using kernel functions. Kernel acts as the correlation between the approach of the data values that have the same characteristics. In this case, the characteristics used is the time. The advantage of the kernel function is able to calculate the correlation between random variables that have a realization using data characteristics. The advantage of using the kernel based Copula able to capture the dependencies between data and process data that have the same characteristics with time. Another benefit is that it allows a sequence of random variables have a joint distribution function so that the conditional probability of the prediction can be calculated.Â Keywords: Binding, Copula, GARCH, Gauss, Time Series

Neurocomputing fundamental climate analysis Rezzy Eko Caraka; Sakhinah Abu Bakar; Muhammad Tahmid; Hasbi Yasin; Isma Dwi Kurniawan
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 17, No 4: August 2019
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v17i4.11788

Rainfall is a natural phenomenon that needs to be studied more deeply and interesting to be analyzed. It involves numbers of human activities such as aviation, agriculture, fisheries, and also disaster risk reduction. Moreover, the characteristics of rainfall data follows seasonality, fluctuation, not normally distributed and it makes traditional time series challenging to use. Therefore, neurocomputing model can be used as an alternative to extraction information from rainfall data and give high performance also accuracy. In this paper, we give short preview about SST Anomalies in Manado, Northern Sulawesi and at the same time comparing the performance of rainfall forecasting by using three types of neurocomputing methods such as Generalized Regression Neural Network (GRNN), Feed forward Neural Network (FFNN), and Localized Multi Kernel Support Vector Regression (LMKSVR). In a nutshell, all of neurocomputing methods give highly accurate forecasting as well as reach low MAPE FFNN 1.65%, GRNN 2.65% and LMKSVR 0.28%, respectively.

The step construction of penalized spline in electrical power load data Rezzy Eko Caraka; Sakhinah Abu Bakar; Gangga Anuraga; M. A. Mauludin; Anwardi Anwardi; Suwito Pomalingo; Vidila Rosalina
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 17, No 2: April 2019
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v17i2.8460

Electricity is one of the most pressing needs for human life. Electricity is required not only for lighting but also to carry out activities of daily life related to activities Social and economic community. The problems is currently a limited supply of electricity resulting in an energy crisis. Electrical power is not storable therefore it is a vital need to make a good electricity demand forecast. According to this, we conducted an analysis based on power load. Given a baseline to this research, we applied penalized splines (P-splines) which led to a powerful and applicable smoothing technique. In this paper, we revealed penalized spline degree 1 (linear) with 8 knots is the best model since it has the lowest GCV (Generelized Cross Validation). This model have become a compelling model to predict electric power load evidenced by of Mean Absolute Percentage Error (MAPE=0.013) less than 10%.

Inflation Rate Modelling in Indonesia Rezzy Eko Caraka; Wawan Sugiyarto
ETIKONOMI Vol 15, No 2 (2016)
Publisher : Faculty of Economic and Business

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15408/etk.v15i2.3260

The purposes of this research were to analyse: (i) Modelling the inflation rate in Indonesia with parametric regression. (ii) Modelling the inflation rate in Indonesia using non-parametric regression spline multivariable (iii) Determining the best model the inflation rate in Indonesia (iv) Explaining the relationship inflation model parametric and non-parametric regression spline multivariable. Based on the analysis using the two methods mentioned the coefficient of determination (R2) in parametric regression of 65.1% while non-parametric amounted to 99.39%. To begin with, the factor of money supply or money stock, crude oil prices and the rupiah exchange rate against the dollar is significant on the rate of inflation. The stability of inflation is essential to support sustainable economic development and improve people's welfare. In conclusion, unstable inflation will complicate business planning business activities, both in production and investment activities as well as in the pricing of goods and services produced.DOI: 10.15408/etk.v15i2.3260

PEMODELAN DANA BOS TERHADAP RATA-RATA NILAI RAPOT Sugiarto Sugiarto; Rezzy Eko Caraka
Jurnal Komunikasi Pendidikan Vol 1, No 1 (2017)
Publisher : Universitas Veteran Bangun Nusantara

Penelitian ini bertujuan untuk menganalisis hubungan dana BOS terhadap nilai rata-rata rapot siswa. Aspek dana BOS yang diperhatikan antara lain adalah pengembangan perpustakaan, pembelajaran dan ekstrakurikuler siswa, langganan daya dan jasa, dan membantu siswa miskin. Nilai rapot siswa merupakan salah satu indicator dalam pencapaian belajar maupun prestasi belajar. Instrumen penelitian ini adalah catatan rapot siswa, observasi lapangan dan angket siswa berdasarkan analisis dapat disimpulkan bahwa sebesar 77,33% rata-rata nilai rapot siswa (Y) dapat dijelaskan oleh variabel X1,X2,X3,X4, dan X5 sedangkan 22,67% lain dipengaruhi oleh faktor lain diluar penelitian ini. Pendidikan memiliki peranan pentingdalam menciptakan masyarakat yang cerdas, damai, terbuka, dan demokratis.Keywords: BOS; Regresi Berganda; Prestasi; Pendidikan

Peramalan Crude Palm Oil (CPO) Menggunakan Support Vector Regression Kernel Radial Basis Rezzy Eko Caraka; Hasbi Yasin; Adi Waridi Basyiruddin
Jurnal Matematika Vol 7 No 1 (2017)
Publisher : Mathematics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JMAT.2017.v07.i01.p81

Recently, instead of selecting a kernel has been proposed which uses SVR, where the weight of each kernel is optimized during training. Along this line of research, many pioneering kernel learning algorithms have been proposed. The use of kernels provides a powerful and principled approach to modeling nonlinear patterns through linear patterns in a feature space. Another bene?t is that the design of kernels and linear methods can be decoupled, which greatly facilitates the modularity of machine learning methods. We perform experiments on real data sets crude palm oil prices for application and better illustration using kernel radial basis. We see that evaluation gives a good to fit prediction and actual also good values showing the validity and accuracy of the realized model based on MAPE and R2. Keywords: Crude Palm Oil; Forecasting; SVR; Radial Basis; Kernel

Pemodelan Regresi Panel pada Data Pendapatan Asli Daerah (PAD) Terhadap Dana Alokasi Umum (DAU) Rezzy Eko Caraka
Jurnal Ekonomi Kuantitatif Terapan 2019: Vol. 12, No.1, Februari 2019 (pp. 1-107)
Publisher : Universitas Udayana

Data panel is a composite of the data time series (over time) and cross section (between individuals / space). To describe briefly the data panel,egg in cross section,and the value of one or more variables were collected for the sample unit at a time of time. In panel data, the same cross section units surveyed in some time. Panel data regression was used to determine the most appropriate regression model is used to model local revenue (PAD) of the general allocation fund (DAU) for seven districts / cities in Central Java province from 2008 to 2010 budgets. Models produced by REM obtained R2 values ??of 43.8893 % revenue (PAD) is influenced by the General Allocation Fund (DAU), while the rest influenced by other factors.

APPLICATION OF NON PARAMETRIC BASIS SPLINE (BSPLINE) IN TEMPERATURE FORECASTING Rezzy Eko Caraka; Alvita Rachma Devi
Jurnal Statistika Universitas Muhammadiyah Semarang Vol 4, No 2 (2016): Jurnal Statistika
Publisher : Program Studi Statistika, Fakultas Matematika dan Ilmu Pengetahuan Alam, Universitas Muham

Weather is important but hard to predictlay people and scientists alike will agree. The complexity of system limits the knowledge about it and therefore its predictability even over a few days. It is complex because many variables within the Earthsatmosphere, such as temperature and they do so nonlinearly. B-spline as a basis for one-dimensional regression and we extend this paper by using B-spline to construct a basis for bivariate regression. This construction gives a basis in two dimensions with local support and hence a fully flexible family of fitted mortality surfaces one of the principal motivations behind the use of B-spline as the basis of regression is that it doesnot suffer from the lack of stability that can so bedevil ordinary polynomial regression. The essential difference is that B-spline have local non-zero support in contrast to the polynomial basis for standard regression. The optimal B-Spline models rely on theoptimal knots that has a minimum Generalized Cross Validation (GCV)Keywords: Temperature, B-Spline, Generalized Cross Validation, non-parametric

Co-Authors Adi Waridi Basyiruddin Alan Prahutama Alan Prahutama Alvita Rachma Devi Anwardi Anwardi Dede Zumrohtuliyosi Dodik Briawan Erie Sadewo Gangga Anuraga Gustriza Erda Hasbi Yasin Hasbi Yasin Kadi Mey Ismail Kurniawan, Isma Dwi M. A. Mauludin Mohamad Yulianto Kurniawan Muhammad Tahmid Pomalingo, Suwito S. Sugiarto Sakhinah Abu Bakar Sakhinah Abu Bakar Sugiarto Sugiarto Tiani Wahyu Utama Vidila Rosalina Wawan Sugiarto, Wawan Wawan Sugiyarto Wawan Sugiyarto

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