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All Journal Jurnal Presipitasi : Media Komunikasi dan Pengembangan Teknik Lingkungan Media Statistika MATEMATIKA SAINS DAN MATEMATIKA Jurnal Ilmu Dasar Jurnal Gaussian Jurnal Statistika Universitas Muhammadiyah Semarang Indonesian Journal of Applied Statistics Seminar Nasional Variansi (Venue Artikulasi-Riset, Inovasi, Resonansi-Teori, dan Aplikasi Statistika) BAREKENG: Jurnal Ilmu Matematika dan Terapan
Dwi Ispriyanti
Departemen Statistika, Fakultas Sains Dan Matematika, Universitas Diponegoro
Agriculture, Biological Sciences & Forestry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Energy Engineering Environmental Science Mathematics Mechanical Engineering Physics Transportation Other

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PENENTUAN MODEL REGRESI TERPOTONG ATAS DENGAN METODE MAKSIMUM LIKEHOOD Jalarno, Dydaestury; Ispriyanti, Dwi
MEDIA STATISTIKA Vol 1, No 2 (2008): Media Statistika
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (236.26 KB) | DOI: 10.14710/medstat.1.2.53-62

Abstract

Model regresi terpotong atas merupakan suatu model regresi dengan nilai-nilai variabel dependen y < a, dengan a adalah suatu titik potong atas yang dipilih berdasarkan penelitian. Dengan demikian, model regresi terpotong lebih tepat jika digunakan untuk penelitian yang berorientasi pada suatu karakteristik tertentu dari obyek pengamatan yaitu variabel dependennya. Distribusi yang digunakan untuk model regresi ini adalah distribusi normal terpotong atas. Estimasi parameter regresinya menggunakan metode Maksimum Likelihood dan metode iteratif Newton Raphson sedangkan pengujian signifikansi model menggunakan Uji Likelihood Rasio, uji t dan harga koefisien determinasi (R2)
PENENTUAN MODEL ANTRIAN BUS ANTAR KOTA DI TERMINAL MANGKANG Ispriyanti, Dwi; Sugito, Sugito
MEDIA STATISTIKA Vol 5, No 2 (2012): Media Statistika
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (282.19 KB) | DOI: 10.14710/medstat.5.2.119-127

Abstract

In daily activities, we often face in a situation of queueing. The Queue is dull. Most people have experienced in a queue situation or a waiting situation. It  is  a part of the state that occurs in a series of operations that are random in a service facility. The Queue can be found easily in a human life, for example bus queue in Terminal Mangkang. It means that a bus wait to be dispatched and from the bus that will go to the service station. Therefore make an arrival and departure of buses not on schedule which resulted in the accumulation of customers in the terminal. To analyze the extent of the effectiveness of terminal Mangkang particularly inter-city terminal Queue theory it is used in the service system in the terminal.   Keywords: Queue, Terminal Mangkang  
ESTIMASI PARAMETER REGRESI TERPOTONG KIRI DENGAN METODE MAKSIMUM LIKELIHOOD Pratiwi, Ratna; Ispriyanti, Dwi
MATEMATIKA Vol 9, No 2 (2006): JURNAL MATEMATIKA
Publisher : MATEMATIKA

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (111.608 KB)

Abstract

Left truncated regression model is a regression model which the parameters prevailed for the dependent variable values y > a, with a is a left truncation point that is choosen according to the experiment goals, and a is also the observation object itself at once. Thus, truncated regression model is more correct if it is used for the experiment that oriented on a specific characteristic of the observation object, that is dependent variable. The distribution that is used for this regression model is normal left truncated distribution. Estimation of regression parameters used Maksimum Likelihood method with Newton’s iteratif method.
UJI LINEARITAS DATA TIME SERIES DENGAN RESET TEST Budi, Warsito; Ispriyanti, Dwi
MATEMATIKA Vol 7, No 3 (2004): JURNAL MATEMATIKA
Publisher : MATEMATIKA

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Abstract

  Tulisan ini membahas prosedur pengujian linearitas data time series menggunakan uji RESET test versi Ramsey dan Lagrange Multiplier. Uji yang digunakan adalah uji yang telah diperbaiki dengan pembentukan komponen utama dari bentuk polinomial pada persamaan uji. Prosedur uji kemudian diterapkan pada data simulasi untuk model linear AR(2), AR(2) dengan outlier dan model nonlinear  LSTAR(2) dengan n = 200. Pengujian menunjukkan hasil yang mirip diantara kedua uji dimana data simulasi dari model linear tidak menjamin kelinearan, sedangkan data simulasi model nonlinear secara signifikan berbentuk nonlinear pada taraf 5%.  
PENDEKATAN REGRESI UNTUK ANALISIS RAGAM KLASIFIKASI DUA-ARAH Ispriyanti, Dwi
MATEMATIKA Vol 10, No 1 (2007): JURNAL MATEMATIKA
Publisher : MATEMATIKA

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Abstract

Regression approach can be used for solving analysis of variance problems, wether of one way or two ways ANOVA . In ANOVA, model is an important factor. In this paper, we will study two ways classification ANOVA with regression approach for solving the fixed effect model. It can be done if the model is indentified truly and if the preventive procedure have been done so we have an independent normal equation. A characteristic of ANOVA is that the analysis model is overparameterized, so we have to make constraint for the parameters. In the Regression model approach for ANOVA problems, the independent variable X at categorical form 0 and 1 , or we have to make dummy variables at row and colom factors.  
PEMODELAN STATISTIKA DENGAN TRANSFORMASI BOX COX Ispriyanti, Dwi
MATEMATIKA Vol 7, No 3 (2004): JURNAL MATEMATIKA
Publisher : MATEMATIKA

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Abstract


Pemodelan Regresi untuk Rancangan Percobaan Faktor Tunggal Ispriyanti, Dwi
JURNAL SAINS DAN MATEMATIKA Volume 15 Issue 2 Year 2007
Publisher : JURNAL SAINS DAN MATEMATIKA

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Abstract

ABSTRAK---Metode Statistik yang sering digunakan dalam percobaan adalah analisis ragam. Dalam tulisan ini akan dibahas analisis ragam dengan pengaruh tetap diselesaikan dengan pendekatan metode regresi,hal itu dapat dilakukan kalau modelnya diindetifikasi secara benar dan kalau langkah-langkah pencegahan telah diambil agar diperoleh persamaan normal yang bebas. Suatu ciri analisis ragam adalah bahwa model analisis ini terparameterisasi secara berlebih (Overparameterized), sehingga perlu membuat kendala terhadap parameter-parameternya. Pendekatan model regresi terhadap masalah analisis ragam mengharuskan peubah bebas X dalam bentuk katagori, yaitu nol dan satu. Kata kunci : analisis ragam, kendala
PENERAPAN METODE KLASIFIKASI SUPPORT VECTOR MACHINE (SVM) PADA DATA AKREDITASI SEKOLAH DASAR (SD) DI KABUPATEN MAGELANG Octaviani, Pusphita Anna; Wilandari, Yuciana; Ispriyanti, Dwi
Jurnal Gaussian Vol 3, No 4 (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 (587.385 KB) | DOI: 10.14710/j.gauss.v3i4.8092

Abstract

Accreditation is the recognition of an educational institution given by a competent authority, that is Badan Akreditasi Nasional Sekolah/Madrasah (BAN - S/M) after it is assessed that the institution has met the eight components of the accreditation assessment. An elementary school, as one of the compulsory basic education, should have the status of accreditation to ensure the quality of education. This study aimed to apply the classification method Support Vector Machine (SVM) on the data accreditation SD in Magelang. Support Vector Machine (SVM) is a method that can be used as a predictive classification by using the concept of searching hyperplane (separator functions) that can separate the data according to the class. SVM using the kernel trick for non-linear problems which can transform data into a high dimensional space using a kernel function, so that the data can be classified linearly. The results of this study indicate that the prediction accuracy of SVM classification using Gaussian kernel function RBF is 93.902%. It is calculated from 77 of 82 elementary schools that are classified correctly with the original classes. Keywords : Accreditation, Classification, Support Vector Machine (SVM), hyperplane, Gaussian RBF Kernel, Accuracy 
PERAMALAN HARGA SAHAM DENGAN METODE EXPONENTIAL SMOOTH TRANSITION AUTOREGRESSIVE (ESTAR) (Studi Kasus pada Harga Saham Mingguan PT United Tractors) Rahmayani, Dwi; Ispriyanti, Dwi; Mukid, Moch. Abdul
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 (433.906 KB) | DOI: 10.14710/j.gauss.v4i2.8424

Abstract

The stock price data series of PT United Tractors in the period of December 1th 2008 to December 29th 2014 is fluctuative. To model data nonlinear time series one method that can be used is Smooth Transition Autoregressive (STAR), if the function of an exponential transition then a method that can be used is Exponential Smooth Transition Autoregressive (ESTAR). In modelling ESTAR determined transition variable ( of transition function ). Of the research result obtained model ESTAR (1,1). With significance level of 5% obtainedthe value of the stock price data for pt united tractors in the next four to the original. It was also strengthened by Mean Absolute Percentage Error (MAPE) 0,768233 %  are relatively small. Keywords : Autoregressive,time series, nonlinearity, ESTAR, MAPEThe stock price data series of PT United Tractors in the period of December 1th 2008 to December 29th 2014 is fluctuative. To model data nonlinear time series one method that can be used is Smooth Transition Autoregressive (STAR), if the function of an exponential transition then a method that can be used is Exponential Smooth Transition Autoregressive (ESTAR). In modelling ESTAR determined transition variable ( of transition function ). Of the research result obtained model ESTAR (1,1). With significance level of 5% obtainedthe value of the stock price data for pt united tractors in the next four to the original. It was also strengthened by Mean Absolute Percentage Error (MAPE) 0,768233 %  are relatively small. Keywords : Autoregressive,time series, nonlinearity, ESTAR, MAPE
PEMODELAN JARINGAN SYARAF TIRUAN DENGAN ALGORITMA ONE STEP SECANT BACKPROPAGATION DALAM RETURN KURS RUPIAH TERHADAP DOLAR AMERIKA SERIKAT Najwa, Maulida; Warsito, Budi; Ispriyanti, Dwi
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 (767.388 KB) | DOI: 10.14710/j.gauss.v6i1.14768

Abstract

Exchange rate is the currency value of a country that is expressed by the value of another country's currency. Changes in exchange rates indicate risks or uncertainties that would return obtained by investors. With the predicted value of return, investors can make informed decisions when to sell or buy foreign currency to gain an advantage. Forecasting of return values can be using artificial neural network with backpropagation. In backpropagation procedure, data is divided into two pairs, namely training data for training process and testing data for testing process. In the training process, the network is trained to minimize the MSE. One of optimization method that can minimize the MSE is one step secant backpropagation. In this research, the data used is the return of the exchange rate of rupiah against US dollar in the period of January 1st, 2015 until December 31st, 2015. The results were obtained architecture best model neural network that was built from 8 neurons in the hidden layer, 1 unit of input layer with input xt-1 and 1 unit of output layer. The activation function used in the hidden layer and output layer are bipolar sigmoid and linear, respectively. The architecture chosen based on the smallest MSE of testing data is 0.0014. After obtaining the best model, data is foreseen in the period of November 2016 produce MAPE=153.23%.Keyword : Artificial Neural Network, Backpropagation, One Step Secant, Time Series, Exchange Rate.
Co-Authors A Rusgiyono Abdul Hoyyi Agus Rusgiyono Agustinus Salomo Parsaulian Ain Hafidita Ajeng Dwi Rizkia Alan Prahutama Alan Prahutama Alvi Waldira Ana Kartikawati Anisa Septi Rahmawati Anjan Setyo Wahyudi Annisa Ayu Wulandari Arief Rachman Hakim Arkadina Prismatika Noviandini Taryono Arya Despa Ihsanuddin Arya Huda Arrasyid Atika Elsadining Tyas Aulia Ikhsan Avia Enggar Tyasti Azizah Mulia Mawarni Berta Elvionita Fitriani Bitoria Rosa Niashinta Budi Warsito Budi Warsito Cylvia Evasari Margaretha Dedi Nugraha Di Asih I Maruddani Di Asih I Maruddani Diah Safitri Diah Safitri Diah Wulandari Dita Ruliana Dwi Rahmayani, Dwi Dyan Anggun Krismala Dydaestury Jalarno Eis Kartika Dewi Endah Fauziyah Erna Sulistianingsih Erna Sulistio Evi Yulia Handaningrum Fadhilla Atansa Tamardina Firda Dinny Islami Firdha Rahmatika Pratami Fithroh Oktavi Awalullaili Gandhes Linggar Winanti Gera Rozalia Ghina Nabila Saputro Putri Hanifah Nur Aini Hasbi Yasin Hasbi Yasin Henny Widayanti, Henny Ilham Maggri Imam Desla Siena Innosensia Adella Irawati Tamara Iut Tri Utami Jesica, Haniela Puja Kishatini Kishartini Lifana Nugraeni Lingga Bayu Prasetya M. Ali Ma&#039;sum Marlia Aide Revani Masfuhurrizqi Iman Maulida Azkiya, Maulida Maulida Najwa, Maulida Merinda Pangestikasari Moch. Abdul Mukid Moch. Abdul Mukid Muhammad Fitri Lutfi Anshari Muhammad Rosyid Abdurrahman Muhammad Zidan Eka Atmaja Mustafid Mustafid Mustafid Mustafid Nanci Rajagukguk, Nanci Nandang Fahmi Jalaludin Malik Nida Adelia Nidaul Khoir Nova Nova Noviana Nurhayati Nurwihda Safrida Umami Oka Afranda Pandu Anggara Pritha Sekar Wijayanti Puput Ramadhani Pusphita Anna Octaviani Puspita Kartikasari Putri Fajar Utami Rafida Zahro Hasibuan Rahafattri Ariya Fauzannissa Rahmah Merdekawaty Rahmaniar, Ratna Rany Wahyuningtias Ratih Nurmalasari, Ratih Ratna Pratiwi Ria Sutitis Rio Tongaril Simarmata Riszki Bella Primasari Rita Rahmawati Rita Rahmawati Riza Adi Priantoro Riza Fahlevi Sa'adah, Alfi Faridatus Sania Anisa Farah Setiani Setiani Sherly Candraningtyas Sindy Saputri Sisca Agustin Diani Budiman Sri Maya Sari Damanik Sudarno Sudarno Sudarno Sudarno Sudarno Sudarno Sudarno Sudarno Sugito - Sugito Sugito Sugito Sugito Suhendra, Muhammad Arif Suparti Suparti Suparti Suparti Suparti, S. Suryaningrum, Fahlevi Syilfi Syilfi Sylvi Natalia P P Tarno Tarno Tarno Tarno Tarno Tarno Tatik Widiharih Tatik Widiharih Tatik Widiharih Tiani Wahyu Utami Triastuti Wuryandari Triastuti Wuryandari Trimono Trimono Ulya Tsaniya Umiyatun Muthohiroh Warsito Budi Yani Puspita Kristiani Yashmine Noor Islami Yuciana Wilandari Yuciana Wilandari