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All Journal HAYATI Journal of Biosciences Jurnal Ilmu Dasar Statistika BERKALA SAINSTEK CAUCHY: Jurnal Matematika Murni dan Aplikasi Kreano, Jurnal Matematika Kreatif-Inovatif Prosiding Seminar Matematika dan Pendidikan Matematik AJIE (Asian Journal of Innovation and Entrepreneurship) UNEJ e-Proceeding Martabe : Jurnal Pengabdian Kepada Masyarakat Mathvision : Jurnal Matematika Abdimas Universal JUSTINDO (Jurnal Sistem dan Teknologi Informasi Indonesia) ESTIMASI: Journal of Statistics and Its Application Majalah Ilmiah Matematika dan Statistika (MIMS) International Journal of Quantitative Research and Modeling Jurnal Hasil Pengabdian Kepada Masyarakat Universitas Jember Indonesian Journal of Statistics and Its Applications
Alfian Futuhul Hadi
Departement Of Mathematics, Faculty Of Mathematics And Natural Science, University Of Jember, Jember, 68121, Indonesia
Agriculture, Biological Sciences & Forestry Arts Humanities Biochemistry, Genetics & Molecular Biology Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Engineering Environmental Science Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Mathematics Physics Social Sciences Other

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PERBANDINGAN MODEL ACCELERATED FAILURE TIME DAN MODEL COX PROPORTIONAL HAZARD PADA KASUS KARDIOVASKULAR Fatmala, Siti Febriana; Fatekurohman, Mohamat; Hadi, Alfian Futuhul
Majalah Ilmiah Matematika dan Statistika Vol 18 No 1 (2018): Majalah Ilmiah Matematika dan Statistika
Publisher : Jurusan Matematika FMIPA Universitas Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19184/mims.v18i1.17244

Abstract

Cardiovascular disease is a disease that attacks the heart and blood vessels. Many types of cardiovascular diseases, but the most famous are coronary heart disease and stroke. Coronary heart disease is a disease that is the first cause of death that occurs in the world caused by risk factors and the length of time of survival of coronary heart disease patients, then using survival analysis with the Cox Proportional Hazard model and Accelerated Failure Time model. Comparison between Cox Proportional Hazard model and Accelerated Failure Time model expedited time can be determined by the survival time with a safe function, the hazard function and density function (comparison of income) of each questioned duration of time with the help of different AIC policies and the rate of deterioration. Estimation of the survival time of this cardiovascular case is determined from the Cox Proportional Hazard’s hazard ratio model and the Accelerated Failure Time’s time ratio model. The results showed that the Accelerated Failure Time model was better than the Cox Proportional Hazard model because the rate of deterioration and the AIC value was smaller than the other models and related to risk factors, namely the age and status of diabetes mellitus and the length of survival of the patient for 11 days obtained from the estimation of the survival time distribution between the Cox Proportional Hazard model and the Accelerated Failure Time model. Keywords: Coronary heart disease, survival analysis, Cox Proportional Hazard, Accelerated Failure Time
PERBAIKAN MODEL SEASONAL ARIMA DENGAN METODE ENSEMBLE KALMAN FILTER PADA HASIL PREDIKSI CURAH HUJAN Wibisono, Dwi Anugrah; Anggraeni, Dian; Hadi, Alfian Futuhul
Majalah Ilmiah Matematika dan Statistika Vol 19 No 1 (2019): Majalah Ilmiah Matematika dan Statistika
Publisher : Jurusan Matematika FMIPA Universitas Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19184/mims.v19i1.17262

Abstract

Forecasting is a time series analytic that used to find out upcoming improvement in the next event using past events as a reference. One of the forecasting models that can be used to predict a time series is Kalman Filter method. The modification of the estimation method of Kalman Filter is Ensemble Kalman Filter (EnKF). This research aims to find the result of EnKF algorithm implementation on SARIMA model. To start with, preticipation forecast data is changed in the form of SARIMA model to obtain some SARIMA model candidates. Next, this best model of SARIMA applied to Kalman Filter models. After Kalman Filter models created, forecasting could be done by applying pass rainfall data to the models. It can be used to predict rainfall intensity for next year. The quality of this forecasting can be assessed by looking at MAPE’s value and RMSE’s value. This research shows that enkf method relative can fix sarima method’s model, proved by mape and rmse values which are smaller and indicate a more accurate prediction. Keywords: Ensemble Kalman Filter, Forecast, SARIMA
APLIKASI MESIN PENCACAH DAN FERMENTASI JERAMI DALAM PRODUKSI KOMPOS DI KECAMATAN SILO KABUPATEN JEMBER Halimatus Sa’diyah; Alfian Futuhul Hadi; Bambang Herry Purnomo; Sudarko Sudarko
Asian Journal of Innovation and Entrepreneurship Vol 4 No 01 (2015): January 2015
Publisher : UII

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20885/ajie.vol4.iss1.art5

Abstract

Farmers Group JokoTole and BaruMuncul are from Karangharjo Village, Silo subdistrict, Jember.  Both groups had the awareness to use organic fertilizers in farming. In fact, they make their own organic fertilizer in the form of compost, using a mixture of forage or leaves and cow dung. During the process of making compost, they encounter time inefficiency in the process of cutting the leaves and dried cow dung. It is because it is done conventionally using a dagger. The amount of compost produced is not sufficient for both farmer groups. Therefore, the application of compost thrasher (chopper) can increase the productivity and also saves time and energy for the process. In addition to the increase in the amount of compost produced, quality improvement is also needed by increasing the levels of macro nutrients in fertilizers, such as N, P, and K. This will be achieved by improving the nutrition of cattle feed, especially taken as a mixture of manure compost through hay fermentation technology. Nutritious fodder increased nutrients in the cow dung, and its utilization will also increase the nutrient content of the compost that is made. Keywords: trasher, silage, compost
PENGEMBANGAN USAHA TEPUNG IKAN DI DESA NELAYAN PUGER WETAN Halimatus Sa’diyah; Alfian Futuhul Hadi; Nasrul Ilminnafik
Asian Journal of Innovation and Entrepreneurship Vol 1 No 01 (2016): January 2016
Publisher : UII

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20885/ajie.vol1.iss1.art4

Abstract

Puger Wetan is the largest fisheries center in Jember. One of the fish type produced is SardinellaLemuru.  Due to its small size and prickly nature, it is rarely consumed directly. It is commonly sold as raw material for canned sardines. Canned sardines manufacture needs fresh Lemuru, because it will cause itching on the tongue if not fresh. Whereas, fishermen mostly piled the fish in the boat hatch then gave ice cubes, so that the majority of it will no longer be fresh when arrived in the mainland because its perishable nature due to its thin skin.As the result, most of fishermen’s catch is not feasible for canned sardines and become leftovers. During this time, it will be sold at a low price. Fish leftovers that are not absorbed by the market aredumped into the river, becomingleftovers. The waste pollutes the environment and harms the health and hygiene. There will be more wastes during the fishing season, as more and more lemuru leftovers are dumped. This activity aims to resolve the problem by transforming the leftovers into fish meal, using appropriate tech machines. The activities are carried out in several stages. The first stage is the counseling about the negative impact of fisheries waste and the possibility of utilizing it into fish meal, also about the business opportunity that is still potential because domestic demand is still not yet met. The explanation of the importance of business management was also given.The third stage is the practice of making fish meal with the help of tools that have been previously converted technology. The fourth stage is the evaluation of activities for the benefit of partnering groups. Lemuru leftover utilization into fish meal is one of the important components in animal feed which can increase the fishermen income, while reducing environmental pollution.
Analysis of Simultaneous Equation Model (SEM) on Non normally Response used the Method of Reduce Rank Vector Generalized Linear Models (RR-VGLM) Miftahul Ulum; Alfian Futuhul Hadi; Dian Anggraeni
UNEJ e-Proceeding 2016: Proceeding The 1st International Basic Science Conference
Publisher : UPT Penerbitan Universitas Jember

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Abstract

Multivariate linear regression is a statistical analysis methods used to data in the case of multiple response variables associated with several predictor variables. In this method of analysis there is an assumption of matrix coefficient regression must be full rank. In the case of simultaneous equations, full rank condition is not fulfilled. Consequently, to analyze that case is not possible because it would produce a regression coefficient that is very large so needed reduction in rank. Reduce Rank Regression (RRR) Method is an alternative method in the case where this method if there is a weak regression coefficients will be cut. However, Reduced rank regression method only applies in response which continuous and normal in econometric data analysis and others. Therefore, to overcome that problem so introduced to f analysis method of Reduce Rank Vector Generalized Linear Model (RR-VGLM). This article will discuss simultaneous equations with non-normal variable response using RR-VGLM by simulating non normal conditions.
Handling Outlier In The Two Ways Table By Using Robust Ammi And Robust Factor Kurnia Ahadiyah; Alfian Futuhul Hadi; Dian Anggraeni
UNEJ e-Proceeding 2016: Proceeding The 1st International Basic Science Conference
Publisher : UPT Penerbitan Universitas Jember

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Abstract

Robust Regression is a regression methods were used to analyze the data that contains some outliers. This regression is a statistical model were easy to influenced to small changes in the data. This method is often used for data analysis on additive model. In a modeling of two ways table, it has been known AMMI (Additive Main and Multiplicative Interaction) which can be used to analyze the stability of genotypes at several different environments by combining the additive model of main effect and multiplicative model of interaction. AMMI models used for data with normally distribution. AMMI models will against the same problem if there are outliers in two ways table. Because of that problem, it is necessary a robust method in decompotition of interaction matrix including robust SVD and Robust PCA. This study analyzed data on two-way tables that contain contain outliers by using approach of robust SVD and approach of robust PCA. The results of this study on both methods will be compared the goodness of model through the comparison of biplot of each model.
Application Cluster Analysis on Time Series Modelling with Spatial Correlations for Rainfall Data in Jember Regency Ira Yudistira; Alfian Futuhul Hadi; Dian Anggraeni; Budi Lestari
UNEJ e-Proceeding 2016: Proceeding The 1st International Basic Science Conference
Publisher : UPT Penerbitan Universitas Jember

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Abstract

Forecasting is a statistical analysis to obtain an overview the development of event in the future. Forecasting performed on time series data, is a series of data observation data that affected by previous data. In addition, time series data is also affected by the location of research, it is called spatial correlations. This correlation can be analyzed by cluster analysis method. Cluster analysis aims to group objects based on similar characteristics. Variability of rainfall in Jember Regency depends on time and space so that there is a spatial correlation. Cluster analysis is expected to form groups that optimal in the data so that the forecasting results more optimal. Selection of the best forecasting models in this study is determined by the smallest RMSE value.
Handling Outlier in Two-Ways Table by Robust Alternating Regression of FANOVA Models: Towards Robust AMMI Models Alfian Futuhul Hadi
Jurnal ILMU DASAR Vol 12 No 2 (2011)
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (211.783 KB)

Abstract

AMMI (Additive Main Effect Multiplicative Interaction) model for interactions in two-way table provide the major mean for studying stability and adaptability through genotype × environment interaction (GEI), which modeled by full interaction model. Eligibility of AMMI model depends on that assumption of normally independentdistributederrorwithaconstantvariance. Nowadays,AMMImodelshavebeendevelopedforany conditionofMETdatawhich violencethenormality,homogeneityassumpion. Wecanmentioninthisclassof modelling as M-AMMI for mixed AMMI models, G-AMMI for generalized AMMI models. The G-AMMI was handling non-normality i.e categorical response variables using an algorithm of alternating regression. While in handling the non-homogeneity in mix-models sense, one may use a model called factor analytic multiplicative. The development of AMMI models is also to handle any outlier that might be found coincides withnon-homogeneityconditionofthedata. Inthispaper,wewillpresentofhandlingoutlierinmultplicative model by robust approach of alternating regression algorithm.
Data Non-normality on AMMI Models: Box-Cox Transformations Alfian Futuhul Hadi; Halimatus Sa'diyah; I Made Sumertajaya
Jurnal ILMU DASAR Vol 8 No 2 (2007)
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (490.603 KB)

Abstract

AMMI (Additive Main Effect Multiplicative Interaction) model for interactions in two-way table provide the major mean for studying stability and adaptability through genotype × environment interaction (GEI), which modeled by full interaction model.  Eligibility of AMMI models depends on that assumption of normally independent distributed error with a constant variance.  In the case of non-normal data distribution, the appropriateness of AMMI model is being doubtful. Transform the observation by power family of Box-Cox transformation is an effort to handle the non-normality. AMMI model then can be applied to the transformed data appropriately following by the use of ordinary least square for estimating parameters.  This approach is investigated by applying them to (i) a count data of pest population of Poisson distribution, which came from a study of leave pest in soybean genotype, and to (ii) a study of rice genotype stability of filled grain per panicle (Binomial data).  One must be carefully considered what the meaning of the transformation in the AMMImodels and Biplot AMMI.
Generalized AMMI Models for Assessing The Endurance of Soybean to Leaf Pest Alfian Futuhul Hadi; A. A. Mattjik; IM Sumertajaya
Jurnal ILMU DASAR Vol 11 No 2 (2010)
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (217.038 KB)

Abstract

AMMI(Additive Main Effect Multiplicative Interaction)model for interactions in two-way table provide the major mean for studying stability and adaptability through genotype × environment interaction (GEI), which modeled by full interaction model. Eligibility of AMMI (Additive Main Effect Multiplicative Interaction) model depends on that assumption of normally independent distributed error with a constant variance. In the study of genotypes’ resistance, disease and pest (insect) incidence on a plant for example, the appropriateness of AMMI model is being doubtful. We can handle it by introducing multiplicative terms for interaction in wider class of modeling, Generalized Linear Models. Its called Generalized AMMI model. An algorithm of iterative alternating generalized regression of row and column estimates its parameters. GAMMI log-link model will be applied to the Poisson data distribution. GAMMI log-link models give us good information of the interaction by its log-odd ratio. 
Co-Authors A. A. Mattjik Abduh Riski Achmad Budi Susetyo Anak Agung Gede Sugianthara Awalin, Qonita Ilmi Budi Lestari D. Dafik Dian Anggraeni Dian Anggraeni Dian Anggraeni Dian Anggraeni Dian Anggraeni Dian Anggraeni Fatmala, Siti Febriana Fauziyah, Mailulah Ely Forestryani, Veniola Frida Murtinasari, Frida Halimatus Sa'diyah Halimatus Sa'diyah Halimatus Sa’diyah Herry Purnomo, Bambang Hidayat, Muhammad Jamil Hobri I Made Sumertajaya I Made Tirta Ika Hesti Agustin, Ika Hesti Ira Yudistira Kosala Dwidja Purnomo Kurnia Ahadiyah M Dika saputra Madinda, Diah Putri Miftahul Ulum Mohamad Fatekurohman Muhammad Iqbal Yunan Helmi Muharom, Lutfi Ali Nasrul Ilminnafik Nurul Fittriyah, Nurul Paramitha, Luckyta Citra Ayu Prayogo, Rizky Rio Pradani Putra Rory Ronella Agustin Rusdiana, Riza Yuli Sa’diyah, Halimatus Sudarko Sudarko Sunder, R. Syamsul Arifin Tresnawanti, Dini Wibisono, Dwi Anugrah Yuliani Setia Dewi