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All Journal PROSIDING SEMINAR NASIONAL Media Statistika SAINS DAN MATEMATIKA Jurnal Gaussian Jurnal Statistika Universitas Muhammadiyah Semarang E-Dimas: Jurnal Pengabdian kepada Masyarakat Seminar Nasional Variansi (Venue Artikulasi-Riset, Inovasi, Resonansi-Teori, dan Aplikasi Statistika) EKO-REGIONAL JURNAL PENGEMBANGAN EKONOMI WILAYAH

Abdul Hoyyi

Departemen Statistika, Fakultas Sains Dan Matematika, Universitas Diponegoro

Author-ID : 3131506

Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Mathematics Social Sciences Other

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IMPLEMENTASI METODE LEAN SIX SIGMA SEBAGAI UPAYA MEMINIMALISASI CACAT PRODUK KEMASAN CUP AIR MINERAL 240 ml (STUDI KASUS PERUSAHAAN AIR MINUM) Ari Fakhrus Sanny; Mustafid Mustafid; Abdul Hoyyi
Jurnal Gaussian Vol 4, No 2 (2015): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Efforts to increase productivity can not be said that the human factor is not the only factor which should be observed, studied, analyzed, and repaired in the effort to increase productivity, but also other factors such as machine, equipment, raw materials, factory buildings, etc. may also affect the productivity improvement efforts remain to be considered. Quality is the customer's main factor to decide products and services. Therefore, quality is a key factor which brings business success and growth, and improves competitive position. Lean six sigma method is a method to identify and eliminate waste or activities which are not value added and analyze defect rate product approaches zero defect products. This study aims to implement lean six sigma methods in quality control with case studies of product quality bottled water cup 240 ml at the quality control process produces eleven types of disabilities. Efforts should be made to improve the quality of products, one of them by monitoring the production process control diagram. The results obtained in this study is the value of DPMO on line 1 of 546 machines produce sigma level of 4.766 and a percentage of 99.95%, which means that in a million products cup 240 ml mineral water contained 0.05% units of a product that does not fit in production line machine 1. The DPMO values on line 2 of 291 machines produce sigma level of 4.932 and a percentage of 99.97%, which means that in a million products cup 240 ml mineral water contained 0.03% units of a product that does not fit in production line machine 2. Keywords : Quality, Quality Control, Lean Six Sigma

ANALISIS JALUR TERHADAP FAKTOR-FAKTOR YANG MEMPENGARUHI INDEKS PRESTASI KUMULATIF (IPK) MAHASISWA STATISTIKA UNDIP Malik Hakam; Sudarno Sudarno; Abdul Hoyyi
Jurnal Gaussian Vol 4, No 2 (2015): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/j.gauss.v4i2.8581

Education is a priority thing everyone today. Education is implemented in learning, by learning humans can develop all the potential there is in him. Learning is always related to the achievement of learning, because learning is a process while learning achievement is the result of the learning process. In the course of learning achievement levels measured by GPA (Grade Point Average). Factors that influence GPA among allowance, age, value of the UN Senior High School, many organizations, the internet long, long time to learn. Path analysis is the development of multiple regression which the independent variables affect the dependent variable not only directly but also indirectly affect. Based on the results of the discussion of the factors that affect the GPA is concluded that the allowance has indirect effect of -0,211, age has direct effect of age at 0,1901, the UN has direct effect of 0,258, many organizations have a direct effect of -0,3582 and has indirect effect of -0,132, the internet long direct effect of -0,2376 and has indirect effect of -0,038, long learning has a direct effect of 0,2344. Keywords: Education, GPA, Path analysis, Direct effect, Indirect effect

ANALISIS KETAHANAN HIDUP PENDERITA DENGUE HEMORRHAGIC FEVER (DEMAM BERDARAH) DENGAN REGRESI COX KEGAGALAN PROPORSIONAL SENSOR TIPE III Studi Kasus di Rumah Sakit Umum Daerah (RSUD) Temanggung Irfan Afifi; Di Asih I Maruddani; Abdul Hoyyi
Jurnal Gaussian Vol 6, No 3 (2017): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Dengue Fever is a disease caused by the dengue virus, transmitted from person to person through the bite of Aedes Aegypti and Aedes Albopictus mosquitoes. Dengue Fever mainly found in the tropical countries, such as Indonesia. According to World Health Organization (WHO) data, Indonesia reported as the 2nd country with the largest dengue cases among 30 endemic countries between 2004 until 2010. Therefore, it is important to identify the factors influencing the recovery speed of dengue patients. This study utilize statitistical approach through regression analysis. One of the analysis methode choosen is survival analysis. This analysis is utilized to figure out the time series data analysis, of origin undefined time until the occurrence of certain events. In Survival Analysis, one of the regression method which is commonly used is Cox regression. This study uses statistical methods approach through Cox regression proportional hazard to take into consideration the time of failure as the dependent variable. as well as the response variable function tends to a constant failure. object of research in this study are patients with dengue fever and the time the patient entered in a separate viewing the selected sensor type III This study used medical records of dengue fever patients of regional public hospital in Temanggung City, Central Java, from period of January to November 2016. Results obtained shows that the factors affecting the recovery speed of patients is Hematocrit state of the patient. Patients with normal Hematocrit state have faster recovery that patients with upnormal circumtances. Keywords: Dengue, Survival Analysis, Regression Cox Proportional Hazard

Analisis Kesehatan Bank Menggunakan Local Mean K-Nearest Neighbor dan Multi Local Means K-Harmonic Nearest Neighbor Alwi Assegaf; Moch. Abdul Mukid; Abdul Hoyyi
Jurnal Gaussian Vol 8, No 3 (2019): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

The classification method continues to develop in order to get more accurate classification results than before. The purpose of the research is comparing the two k-Nearest Neighbor (KNN) methods that have been developed, namely the Local Mean k-Nearest Neighbor (LMKNN) and Multi Local Means k-Harmonic Nearest Neighbor (MLM-KHNN) by taking a case study of listed bank financial statements and financial statements complete recorded at Bank Indonesia in 2017. LMKNN is a method that aims to improve classification performance and reduce the influence of outliers, and MLM-KHNN is a method that aims to reduce sensitivity to a single value. This study uses seven indicators to measure the soundness of a bank, including the Capital Adequacy Ratio, Non Performing Loans, Loan to Deposit Ratio, Return on Assets, Return on Equity, Net Interest Margin, and Operating Expenses on Operational Income with a classification of bank health status is very good (class 1), good (class 2), quite good (class 3) and poor (class 4). The measure of the accuracy of the classification results used is the Apparent Error Rate (APER). The best classification results of the LMKNN method are in the proportion of 80% training data and 20% test data with k=7 which produces the smallest APER 0,0556 and an accuracy of 94,44%, while the best classification results of the MLM-KHNN method are in the proportion of 80% training data and 20% test data with k=3 which produces the smallest APER 0,1667 and an accuracy of 83,33%. Based on APER calculation shows that the LMKNN method is better than MLM-KHNN in classifying the health status of banks in Indonesia.Keywords: Classification, Local Mean k-Nearest Neighbor (LMKNN), Multi Local Means k-Harmonic Nearest Neighbor (MLM-KHNN), Measure of accuracy of classification

PENDUGAAN AREA KECIL TERHADAP PENGELUARAN PER KAPITA DI KABUPATEN SRAGEN DENGAN PENDEKATAN KERNEL Bitoria Rosa Niashinta; Dwi Ispriyanti; Abdul Hoyyi
Jurnal Gaussian Vol 5, No 1 (2016): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Data of Social Survey and Economic National is a relatively small sample of data, so that data is called small area. Estimation of parameter in small area can be done in two ways, there are direct estimation and indirect estimation. Direct estimation is unbias estimation but give a high variance because from small sample of data. The technique that use to increase efectivity of sample size is indirect estimation or called Small Area Estimation (SAE). SAE is done by adding auxiliary variable. on estimating parameter. Assumed that auxiliary variable has a linear correlation with the direct estimation. If that assumption is incomplete, use an nonparametric approaching. This research is using Kernel Gaussian approaching to build a correlation between direct estimation which expenditure per capita and auxiliary variable which population density. Evaluation of estimation result is done by comparing the value of direct estimation variance with the value of indirect estimation variance using Kernel Gaussian approaching. The result of parameter estimation which approached by SAE is the best estimation, because it produce the small value of variance that is 5,31275, while the value of direct estimator variance is 6,380522. Keywords : Direct Estimation, Small Area Estimation (SAE), Kernel Gaussian

ORDINARY KRIGING DALAM ESTIMASI CURAH HUJAN DI KOTA SEMARANG Ahmat Dhani Riau Bahtiyar; Abdul Hoyyi; Hasbi Yasin
Jurnal Gaussian Vol 3, No 2 (2014): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

In a measurement of rainfall data, not all points are gauges because of a limitation. Given these limitations, a method is needed to estimate a value for points that are not measurable. Kriging as geostatistical analysis used in the estimation of a value in a point which is not sampled based sample points in the surrounding areas by taking into account the spatial correlation using a spatial weighting, where the correlation is shown by the variogram. Ordinary Kriging is the most widely used. By using the experimental variogram were compared with some theoretical variogram (Exponential, Gaussian, Spherical) selected one of the best semivariogram models to estimate the value that want to find. In this study, conducted rainfall estimates in Semarang in February where the result obtained is the value of rainfall each district and village

RISIKO KREDIT PORTOFOLIO OBLIGASI DENGAN CREDIT METRICS DAN OPTIMALISASI PORTOFOLIO DENGAN METODE MEAN VARIANCE EFFICIENT PORTFOLIO (MVEP) Nurul Fauziah; Abdul Hoyyi; Di Asih I Maruddani
Jurnal Gaussian Vol 1, No 1 (2012): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Investing is a important thing in a capital market. Bond investment must be noticed the risk especially credit risk. From the information of credit risk, investor can choose the right investment. Credit Metrics is a reduced form model to estimate the risk. Credit Metrics is centered by the corporate rating. The risk not only occur when corporate rating be default but also if the rating upgrade or downgrade. For a bond portfolio, can calculate the optimal portfolio by Mean Variance Efficient Portfolio method. Empirical study can be used for two bonds, first bond is Obligasi Adira Dinamika Multi Finance V Tahun 2011 Seri A and second one is Obligasi BFI Finance Indonesia III Tahun 2011 Seri A. First bond has 127.01640 (Billion) of credit risk and the second one bonds has 18.33472 (Billion). For a portfolio of that two bonds, they have 179.82460 (Billion). For the optimal portfolio, first bond has propotion 66.39% and 33.61% for the second bond.

PENDEKATAN MODEL FUNGSI TRANSFER MULTI INPUT UNTUK ANALISIS HUBUNGAN ANTARA LUAS PANEN DAN LUAS TAMBAH TANAM DENGAN PRODUKSI BAWANG MERAH DI JAWA TENGAH Yunisa Ratna Resti; Abdul Hoyyi; Rita Rahmawati
Jurnal Gaussian Vol 4, No 3 (2015): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Onion is one of holticulture commoditie which is consumed by many Indonesians with Central Java as its largest producer. The consumer’s need of onion keeps raising but, unfortunately, its number in the marketplace is limited. The onion supply depend on onion’s production which is affected by some factors, such as the land condition from the beginning when cultivation is started until the harvesting come such as area of harvesting and area of additional cultivation. So that onion’s production modeling which influenced by significant factores is needed to predict the crops volume in the future. Data which is used to production modeling are data of onion’s production in Jawa Tengah, these data is written by Dinas Pertanian Tanaman Pangan dan Hortikultura Jawa Tengah in everymonth. This research use multiple input transfer function model, which is an integration of ARIMA and regression model. This reseach aimed at modelling output series of onion production using two input series, i.e. area of harvesting and area of additional cultivation, from January 2004 to November 2014. The result showed that there is a significant correlation between area of harvesting and onion production, starting from lag t=0 during two periods, as well as area of additional cultivation toward the production from lag t=0. This multiple input transfer function method resulted in AIC valued at 3088.484. Keywords: Multiple Input Transfer Function, Onion

PEMODELAN PERSENTASE BALITA GIZI BURUK DI JAWA TENGAH DENGAN PENDEKATAN GEOGRAPHICALLY WEIGHTED REGRESSION PRINCIPAL COMPONENTS ANALYSIS (GWRPCA) Novika Pratnyaningrum; Hasbi Yasin; Abdul Hoyyi
Jurnal Gaussian Vol 4, No 2 (2015): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Geographically Weighted Regression Principal Components Analysis (GWRPCA) is a combination of method of Principal Components Analysis (PCA) and Geographically Weighted Regression (GWR). PCA is used to eliminate the multicollinearity effect in regression analysis. GWR is a local form of regression and a statistical method used to analyze the spatial data. In GWRPCA predictor variables is a principal components of the PCA result. Estimates of parameters of the GWRPCA model can use Weighted Least Square (WLS). Selection of the optimum bandwidth use Cross Validation (CV) method. Conformance testing PCA regression and GWRPCA models approximated by the F distribution, while the partial identification of the model parameters using the t distribution. In PCA obtained variables that affect the percentage of severe children malnutrition in Central Java in 2012 can be represented or replaced with PC1 and PC2 which can explain the total variance of data is 78.43%. Application GWRPCA models at the percentage of severe children malnutrition in Central Java in 2012 showed every regency locations have different model with global coefficient of determination is 0.6313309 and the largest local coefficient of determination is 0.72793026 present in Batang regency, while the smallest local coefficient of determination is 0.03519539 present in Sukoharjo regency. Keywords : Severe Malnutrition, Multicollinearity, Geographically Weighted Regression Principal Components Analysis, Weighted Least Square,Coefficient of Determination.

KETEPATAN KLASIFIKASI TINGKAT KEPARAHAN KORBAN KECELAKAAN LALU LINTAS MENGGUNAKAN METODE REGRESI LOGISTIK ORDINAL DAN FUZZY K-NEAREST NEIGHBOR IN EVERY CLASS Candra Silvia; Yuciana Wilandari; Abdul Hoyyi
Jurnal Gaussian Vol 4, No 3 (2015): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Traffic accident is an accidental event on the road involving vehicles with or without another road users which causes damage for the victims. Semarang has quite high number of traffic accidents, which in 2014 occured 801 cases of traffic accidents. Based on the government regulation number 43 of 1993 about highway infrastructure and traffic, the impact of traffic accidents can be classified based on victims conditions such as minor injuries, serious injuries, and died. In this research will discuss about the accuracy of severity traffic accidents victim classification in Semarang in 2014 using Ordinal Logistic Regression method and Fuzzy K-Nearest Neighbor in Every Class (FK-NNC). The result of Ordinal Logistic Regression method analysis produces the accuracy of classification value is 90,5405%, meanwhile Fuzzy K-Nearest Neighbor in Every Class method produces the accuracy of classification method is 89,19%. Keywords: Traffic accidents, Ordinal Logistic Regression, Fuzzy K-Nearest Neighbor in Every Class

Co-Authors Abdurakhman Abdurakhman Afifah Alrizqi Agus Rusgiyono Agus Somantri Ahmat Dhani Riau Bahtiyar Alan Prahutama Alan Prahutama Alifah Zahlevi Allima Stefiana Insani Alvi Waldira Alwi Assegaf Amelia Crystine Anggit Ratnakusuma Anggita, Esta Dewi Anik Nurul Aini Annisa Intan Mayasari ANNISA RAHMAWATI Ari Fakhrus Sanny Arief Rachman Hakim Arya Huda Arrasyid Aulia Desy Deria Avia Enggar Tyasti Bella Cynthia Devi Besya Salsabilla Azani Arif Bisri Merluarini Bitoria Rosa Niashinta Budi Warsito Budi Warsito Candra Silvia Chyntia Arum Widyastusti Cindy Wahyu Elvitra Darwanto Darwanto Dea Manuella Widodo Deby Fakhriyana, Deby Dede Zumrohtuliyosi Deden Aditya Nanda, Deden Aditya Dedi Rosadi Dermawanti Dermawanti Desriwendi Desriwendi Dewi Erliana Dewi Setya Kusumawardani Dhea Kurnia Mubyarjati Di Asih I Maruddani Di Asih I Maruddani Di Asih I Maruddani Diah Safitri Diah Safitri Diah Wulandari Dilla Retno Deswita Dwi Ispriyanti DWI RAHMAWATI Emyria Natalia br Sembiring Endah Cahyaningrum Erna Musri Arlita Esti Pratiwi Faiqotul Himmah Fiki Farkhati Firda Dinny Islami Fitra Ramdhani Gayuh Kresnawati Hasbi Yasin Hasbi Yasin Henny Setyowati Herwindhito Dwi Putranto Ikha Rizky Ramadani Indri Puspitasari Irfan Afifi Isowedha Widya Dewi Issabella Marsasella Christy Jeffri Nelwin J. O. Siburian Juli Sekar Sari, Juli Sekar Kartikaningtiyas Hanunggraheni Saputri Khotimatus Sholihah Khusnul Umi Fatimah Kiki Febri Azriati Koko Arie Bowo Kristika Safitri Kumo Ratih Leni Pamularsih Maidiah Dwi Naruri Saida Malik Hakam Mega Fitria Andriyani Mega Fitria Andriyani Mia Anastasia Sinulingga Moch. Abdul Hoyyi Moch. Abdul Mukid Moch. Abdul Mukid MUHAMMAD HARIS Mustafid Mustafid Mustafid Mustafid Mutiara Ardin Rifkiani Nadya Kiki Aulia Nandang Fahmi Jalaludin Malik Novika Pratnyaningrum Nurissalma Alivia Putri Nurul Fauziah Ovie Auliya’atul Faizah Priska Rialita Hardani Purina Pakurnia Artiguna Rita Rachmawati Rita Rahmawati Rita Rahmawati Rizki Pradipto Widyantomo Rizky Oky Ari Satrio Rukun Santoso Saputri, Ani Funtika Saraswati, Mei Sita Shaumal Luqman Silvia Nur Rinjani SITI NURLATIFAH Sudarno Sudarno Sudarno Sudarno Sugito - Sugito Sugito Sugito Sugito Suparti Suparti Suparti Suparti Tarno Tarno Tarno Tarno Tatik Widiharih Tatik Widiharih Tatik Widiharih Titis Nur Utami Tresno Sayekti Nuryanto Triastuti Wuryandari Triastuti Wuryandari Trisnawati Gusnawita Berutu Ubudia Hiliaily Chairunnnisa Ulfah Sulistyowati Yosi Dhyas Monica Yuciana Wilandari Yuciana Wilandari Yudia Yustine Yunisa Ratna Resti Yustian Dwi Saputra

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