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Journal : Jurnal Gaussian

Ketepatan Klasifikasi Status Pemberian Air Susu Ibu (ASI) Menggunakan Multivariate Adaptive Regression Splines (MARS) dan Algoritma C4.5 di Kabupaten Sragen Yusuf Arifka Rahman; Suparti Suparti; Sugito Sugito
Jurnal Gaussian Vol 5, No 1 (2016): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (502.401 KB) | DOI: 10.14710/j.gauss.v5i1.11062

Abstract

The progress of a nation influenced and determined by the level of public health, the indicator of the level of health is determined by nutritional status. Nutrition can be given early, namely breastfeeding to infants. This research aims to compare the classification of exclusive breastfeeding and nonexclusive breastfeeding. It used two methods for classifying a breastfeeding to babies in Sragen subdistrict on 2014, the methods are Multivariate Adaptive Regression Splines (MARS) and C4.5 Algorithm. MARS is nonparametric regression method that use to overcome the high dimension of data that produces accurate prediction and continuous models on knot. C4.5 Algorithm is a way of classifying methods from data mining that use to construct a decision tree. To evaluate the result of classification use Apparent Error Rate (APER) calculation. The best classification  result using MARS method is by using the combination of Basis Function (BF)=40, Maximum Interaction (MI)=3, Minimum Obsevation (MO)=3 because it will result on the smallest Generalized Cross Validation (GCV). Classification result using MARS method obtained APER is 19,7674% and 80,2326% of accuracy. Classification result using C4.5 Algorithm obtained APER is 18,6047% and 81,3953% of accuracy. From proportion test, concluded classification that formed by MARS is as good as by C4.5 Algorithm. Keywords: Breastfeeding, Classification, MARS, C4.5 Algorithm
PENDEKATAN REGRESI POLINOMIAL ORTHOGONAL UNTUK MENENTUKAN KADAR SALINITAS DAN KONSENTRASI LARUTAN KITOSAN PADA PEMBUATAN ANTIBAKTERI Haryanti Novitasari; Triastuti Wuryandari; Sugito Sugito
Jurnal Gaussian Vol 3, No 3 (2014): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (433.73 KB) | DOI: 10.14710/j.gauss.v3i3.6452

Abstract

Indonesia is one of the countries with big marine resource. It can cause increased marine waste, such as the shells. Shells can be processed into chitosan. Chitosan has the benefits with high economic value, one of the benefit is became a source of natural antibacterial. Antibacterial test of the chitosan and salinity of the S. aureus bactery indicating inhibition zone formation. The larger inhibition zone indicated that antibacterial produced  is better. To optimize the level of salinity and concentration of chitosan so this is used polynomial orthogonal regression approach. This approach can be done on design with the quantitative factors and it have same distance. Determination of the degree of polynomial orthogonal based on orthogonal contrasts that have significant factor of salinity and concentration of chitosan, then it can be determined the shape of regression equation. From the that equation can be determined the extreme points using a differential count. When return to the form of the design it can be determined in what  levels of salinity and concentration of chitosan that can maximize the inhibition zone in millimeters. After optimization obtained maximum value of salinity is 18,2846375915% and concentration of chitosan is 1,999699328% with assessment of inhibition zone of antibacterial for S. aureus is 1,72486650 mm. 
PENERAPAN TEORI ANTRIAN PADA PELAYANAN TELLER BANK X KANTOR CABANG PEMBANTU PURI SENTRA NIAGA Nia Puspita Sari; Sugito Sugito; Budi Warsito
Jurnal Gaussian Vol 6, No 1 (2017): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (676.136 KB) | DOI: 10.14710/j.gauss.v6i1.14771

Abstract

Bank X Puri Sentra Niaga branch office is one of bank that can not be separated from the queue issue. The customers want a fast and easy service. The length of queueing and the long waiting times may cause customers cancel the transaction and choose another bank. Therefore, it is necessary to define a suitable queueing model of teller service. Bank X Puri Sentra Niaga branch office have two types of teller service namely Antrian 1 and Antrian 2. Queueing model for Antrian 1 is (M/G/1):(GD//). The model describe that the customers arrival distribution is Poisson, the customer service distribution is General, the number of server is 1, the service disipline is FIFO (first in first out), the customers capacity and the resource of customers are infinite. Queueing model for Antrian 2 is (M/M/2):(GD//). The model describe that customers arival distribution and service distribution are Poisson, the number of server is 2, the service disipline is FIFO (first in first out), the customers capacity and the resource of customers are infinite. Software Arena is applied in simulation to compare the measures of performance if the number of teller added.Keywords: Queue, Queueing System Model, Bank, Teller.
PEMILIHAN MODEL REGRESI LINIER MULTIVARIAT TERBAIK DENGAN KRITERIA MEAN SQUARE ERROR Aminuddin Aminuddin; Sudarno Sudarno; Sugito Sugito
Jurnal Gaussian Vol 2, No 1 (2013): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (913.495 KB) | DOI: 10.14710/j.gauss.v2i1.2125

Abstract

Regresi linier multivariat merupakan salah satu metode analisis regresi yang melibatkan lebih dari satu variabel respon, dengan model regresinya adalah . Penggunaan banyak variabel dalam analisis regresi linier multivariat dapat menjadi hal yang menyulitkan untuk menentukan besarnya pengaruh variabel prediktor terhadap variabel respon. Oleh karena itu, dilakukan penyeleksian variabel guna mendapatkan model regresi terbaik. Prosedur seleksi variabel dengan kriteria Mean Square Error (MSE) merupakan suatu metode untuk mendapatkan model terbaik dengan cara mencari model yang memiliki nilai MSE terkecil dari seluruh model yang mungkin
KLASIFIKASI KEIKUTSERTAAN KELUARGA DALAM PROGRAM KELUARGA BERENCANA (KB) DI KOTA SEMARANG MENGGUNAKAN METODE MARS DAN FK-NNC Aryono Rahmad Hakim; Diah Safitri; Sugito Sugito
Jurnal Gaussian Vol 5, No 3 (2016): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (366.753 KB) | DOI: 10.14710/j.gauss.v5i3.14690

Abstract

Classification method is a statistical method for grouping or classifying data. A good classification method will produce a little bit of misclassification. Classification method has been greatly expanded and two of the existing classification methods are Multivariate Adaptive Regression Spline (MARS) and Fuzzy k-Nearest Neighbor in Every Class (FK-NNC). This study is aimed to compare a classification of Keluarga Berencana  participation based on suspected factors that affect them between the methods of MARS and FK-NNC. This study uses secondary data which one is the participation of Keluarga Berencana in Semarang on 2014. Evaluation of errors use an Apparent Error Rate (APER). In the method MARS best classification results is obtained with the combination of BF = 24, MI = 3, MO = 0 for generating a smallest Generalized Cross Validation (GCV) value and  the APER is obtained by 19%. While FK-NNC method is obtained the best classification results in k = 3 for generating the greatest accuracy of classification value and APER value is obtained by 22%. Based on APER (Apparent Error Rate) calculation, it shown that the classification of family participation in Keluarga Berencana (KB) programs in Semarang using MARS method is better than FK-NNC method.Keywords: Classification, MARS, FK-NNC, APER, Keluarga Berencana
ESTIMASI PARAMETER DISTRIBUSI WEIBULL DUA PARAMETER MENGGUNAKAN METODE BAYES Indria Tsani Hazhiah; Sugito Sugito; Rita Rahmawati
Jurnal Gaussian Vol 1, No 1 (2012): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (431.31 KB) | DOI: 10.14710/j.gauss.v1i1.578

Abstract

Interval estimation of a parameter is one part of statistical inference. One of the methods that used is the Bayes method. A Bayesian method is combine prior distribution and distribution of samples, so that the posterior distribution can be obtained. Interval estimation using a method Bayes called credibel interval estimation. In this thesis, the distribution of the sample is used a two-parameter Weibull distribution scale-shape-version of survival distribution (reliability). Data that used are data that is not censored data type and data type II censored if prior distribution using non-informative which of the produce distribution the resulting posterior distribution is gamma distribution. Parameters of the sample distribution that to find out is a parameter that  by the parameter c (shape parameter) known while the parameter b (scale parameter) had unknown.
PERAMALAN INDEKS HARGA KONSUMEN MENGGUNAKAN MODEL INTERVENSI FUNGSI STEP Dita Ruliana; Sugito Sugito; Dwi Ispriyanti
Jurnal Gaussian Vol 4, No 4 (2015): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (563.062 KB) | DOI: 10.14710/j.gauss.v4i4.10134

Abstract

Intervention model is a model for time series data in which practically there is an extreme fluctuation, whether it’s anupward or downward fluctuation. Consumer price index is one of economic data which plot has a fluctuation, the data that will being used for analyze is consumer price index of Indonesia in January 2009 until March 2015, on data detectable downward fluctuation significantly on January 2014 (T=61). Intervention in data was occurred in long time period (T=61 until T=75), so the model of intervention’s assumption is step function. Based on the result and analysis, the obtaining best model of intervention is ARIMA (2,1,3) with intervention order b=0 s=15 and r=0 which later on being used for predicting Indonesian consumer price index in six periods ahead. Keywords : consumer price index, stationery, ARIMA, step function intervention analysis, forecasting
KLASIFIKASI LAMA STUDI MAHASISWA FSM UNIVERSITAS DIPONEGORO MENGGUNAKAN REGRESI LOGISTIK BINER DAN SUPPORT VECTOR MACHINE (SVM) Sri Maya Sari Damanik; Dwi Ispriyanti; Sugito Sugito
Jurnal Gaussian Vol 4, No 1 (2015): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (597.038 KB) | DOI: 10.14710/j.gauss.v4i1.8152

Abstract

Wisuda adalah hasil akhir dari proses kegiatan belajar mengajar selama mengikuti perkuliahan di perguruan tinggi. Dalam mencapai gelar S1 membutuhkan waktu normal yaitu selama empat tahun, tetapi ada banyak mahasiswa yang menyelesaikan studinya melebihi batas normal (lebih dari empat tahun) dan ada juga yang kurang dari empat tahun. Lama studi mahasiswa dapat dipengaruhi oleh banyak faktor antara lain Indeks Prestasi Kelulusan (IPK), jenis kelamin, jurusan, lama studi yang ditempuh, beasiswa, part time, organisasi, dan jalur masuk universitas. Pada penelitian ini, akan dilakukan klasifikasi berdasarkan status lama studi mahasiswa lebih dari empat tahun dan kurang dari sama dengan empat tahun. Metode yang digunakan untuk klasifikasi lama studi mahasiswa dengan jenis data nominal adalah Metode Support Vector Machine (SVM) dan akan dibandingkan dengan metode Regresi Logistik Biner. Berdasarkan hasil penelitian dengan metode regresi logistik biner, menunjukkan variabel yang berpengaruh terhadap lama studi mahasiswa adalah Jurusan dan IPK dengan ketepatan klasifikasi 70%. Sedangkan ketepatan klasifikasi dengan menggunakan SVM ketepatan klasifikasi tertinggi dengan menggunakan kernel linear, Polynomial dan RBF mencapai 90%.Kata kunci : Lama studi, Regresi Logistik Biner, Support Vector Machine (SVM), Ketepatan Klasifikasi.
PENENTUAN MODEL SISTEM ANTREAN KENDARAAN DI GERBANG TOL BANYUMANIK SEMARANG Dedi Nugraha; Sugito Sugito; Dwi Ispriyanti
Jurnal Gaussian Vol 2, No 2 (2013): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (475.77 KB) | DOI: 10.14710/j.gauss.v2i2.2775

Abstract

The arrival rate of vehicles that have occured at the Banyumanik tollgate is randomly and fluctuatly. Those condition would make difficult for tollgate management to determine policies in operating the substation service. If the substation service operates slightly, can occur long queues, especially at certain time. In the meantime, if the substation service operates many service, service to be inefficient. Therefore, it is necessary to determine the queuing system model in accordance with the conditions and characteristics of the queue from service facilities at the Banyumanik tollgate appropriately. So it can be determined the efektif and efisien number of service substation. Based on the analysis of data obtained, a queue model system that occurred at the Banyumanik tollgate is . The efektif number of substations service for directions Ungaran-Semarang are two subtations service. While for direction Semarang-Ungaran, the efektif number of substation service is three.
PENERAPAN FORMULA BENEISH M-SCORE DAN ANALISIS DISKRIMINAN LINIER UNTUK KLASIFIKASI PERUSAHAAN MANIPULATOR DAN NON-MANIPULATOR (Studi Kasus Di Bursa Efek Indonesia Tahun 2013) Issabella Marsasella Christy; Sugito Sugito; 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 | Full PDF (543.868 KB) | DOI: 10.14710/j.gauss.v4i2.8576

Abstract

Discriminant analysis is a statistical analysis method is used to classify an individual into a certain group which has determined based on the independent variables. In linear discriminant analysis, there are two assumptions to be fulfilled i.e. independent variables have to be multivariate normal distributed and variance covariance matrix of the observed two groups are the same. In this graduating paper is applied Beneish M-Score formula and linier discriminant analysis for classification of cases companies manipulators and non-manipulators are listed in Indonesia Stock Exchange in 2013. Linear discriminant function to continue Beneish M-Score formula to predict the classification, in order to obtain the percentage of fault classification, to determine the size of the performance of linear discriminant function. Percentage of classification error of 2,70 percent. Keywords: Beneish M-Score, Linear Discriminant Analysis
Co-Authors . Aprizal Abdul Hoyyi Abdullah Nur Aziz abdullah nur aziz Abellisa Abellisa Acnes Ratu Dea Adek Cerah Kurnia Azis Adin Ariyanti Dewi Agung - Kusasti Agus Rusgiyono Al Azhar Alan Prahutama Alief Abdullah Faqih Aminuddin Aminuddin Aminuyati Amiruddin Amiruddin Andi Novita Andry Dwira Utama Anggit Ratnakusuma Anggraini Susanti Kusumawardani Anjan Setyo Wahyudi Anna Farida Annisa Annisa Annisa Rifka Alifia Anton Suhartono Any Nurhasanah Aqila Yusriyya Hanun Aref Vai Arham Arham Arief Rachman Hakim Arief Seno Nugroho Arif Widagdo Ariyo Kurniawan Arman Sayuti Aryani Sairun Aryono Rahmad Hakim Aselina Pratidina Wrediningsih Aulia Syafidah Ayuni Ruslina B.Y. Eko Budi Jumpeno Baehaqi Bandhia Ayu Lestari Budi Warsito Cakra Kurniawan Christina Irnani Cut Nila Thasmi Cyntia Surya Utami Darari Rahma Lalita Darmanto Silalahi Darmawi Darmawi Dasrul Dasrul Daulat Saragi Dede Rusmawan Dedi Nugraha Delfiana Anggraini Permatasari Devi Peggy Utami Dhiniaty Gularso Di Asih I Maruddani Diah Safitri Dian Febriana Dita Rosita Sari Dita Ruliana Djoko Adi Walujo Dwi Ispriyanti Dwi Ispriyanti Dwi Ispriyanti Dwi Sari Tristiana Eko Adyan Sukanianto Elsa Mariane Ramadani Endra Susila Erna Fransisca Angela Sihotang Erna Musri Arlita Erwin Erwin Esti Pratiwi Etriwati E F, Arumi Savitri Fakhrurrazi Fakhrurrazi Farzand Abdullatif Fatkhan Arissetya Fatma Septy Deviana Firda Shintia Dewi Friska Irnas Adiyani Frisyi Alfiah Gholib Gholib Ginta Riady Hamdan Hamdan Hamdani Budiman hartono hartono Hartono Hartono Hartono Hartono Haryanti Novitasari Hasbi Yasin Hayuk Permatasari Ilham Indra Bakti Al-Irsyad Ilhan Samudra Fattah Indah Nurhayati Indrarini D. I. Indria Tsani Hazhiah Ira Susanti Ismail Ismail Issabella Marsasella Christy Jenesia Kusuma Wardhani Joko Sutrisno Julia Kardin Juliani Juliani Kelik Isbiyantoro Khusnul Yeni Widiyanti Kiky Moelviani Kofifah Indar Prawansyah Lailatus Sya’diyah Laily Nadhifah Lenti Agustina Lianasari Tambunan Leny Darlem Luthfi Nashukha Dewi M Daud AK M Nur Salim M. Chairul Amri M. Hasan Mahdi Abrar Mahdi Abrar Martyanto Tedjo Masfuhurrizqi Iman Mekar Sekar Sari Melati Puspa Nur Fadlilah Meliy Marsanda Merynda Indriyani Syafutri Moch. Abdul Mukid Muhammad Al Kholif Muhammad Faizin Muhammad Hambal Muhammad Hanafiah Muslim Akmal Mustafid Mustafid Muzammil Muzammil Nabigus Thoriq Harasta Nandita Aprilia Ayu Virnanda Nia Puspita Sari Niha Kamaliya Niken Nindyaiswari Noveda Mulya Wibowo NOVIA RAHMAWATI Nur Paramita Nira Mulyono Nurliana Nurliana NURLIANA NURLIANA Nursihan Nursihan Nurul Trianda Prameswari R. Kusumo Pratiwi Purnama Sari Prizka Rismawati Arum Pujiono Pujiono Pungut Pungut Pungut, Pungut Purina Pakurnia Artiguna Putra Halomoan Siregar R. Burhan Sn. Diningrat Rahmah Merdekawaty Rany Wahyuningtias Ratnawati, Rhenny Razali Daud Razali Razali Resti Tiara Kastrovia Restu Dewi Kusumo Astuti Rinidar Rinidar Rintan Aulal Ilmy Rita Rachmawati Rita Rahmawati Rivaldi Luthfi Rizki Aulia Rohiman Rohiman Roslizawaty Roslizawaty Rukun Santoso Rusli Rusli Salsabilah Balqis Sehah Sehah Sigit Puspito Sigma Wahyuni Silvia Rahmawati Simon Petrus Silalahi Siti Aisyah Siti Anisah Siti Azizah Siti Maghfirotin Soimah Siti Ma’rifah Slamet Slamet Slamet Slamet Sofia Cahyatilmasamah Sri Maya Sari Damanik Sri Wahyuni Sudarno Sudarno Suparno Suparno Suparti Suparti Susi Darmayanti Susy Sriwahyuni Sutrasno Sutrasno Swasnita Swasnita Syaiful, Friska Sylvi Natalia P P T. Armansyah TR T. Fadrial Karmil Tarno Tarno Tatik Widiharih Teuku Reza Ferasyi Teuku Reza Ferasyi Teuku Zahrial Helmi Tiani Wahyu Utami Titin Afriana Tongku Nizwan Siregar Triastuti Wuryandari Tristanti Tristanti Ulya Chofifah Ummu Balqis USWATUN HASANAH Vara Tassa Sutari Velly Ika Arfianda P A Vita Dwi Rachmawati Wahyu Wibawa Wayaning Apsari Widodo Soemadi Widya Ayu Yuliana Widya Nanda Wilis Ardiana Pradana Yuciana Wilandari Yudan Hermawan Yunanur Hanikmah Yustina Tri Handayani Yusuf Arifka Rahman Zamroni Zamroni Zaroh Irayani Zuhrawati NA Zulpikar Zulpikar