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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

Author-ID : 3131513

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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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

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

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

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.

Pemodelan Regresi 2-Level Dengan Metode Iterative Generalized Least Square (IGLS) (Studi Kasus: Tingkat Pendidikan Anak di Kabupaten Semarang) Dyan Anggun Krismala; Dwi Ispriyanti; Moch. Abdul Mukid
Jurnal Gaussian Vol 3, No 1 (2014): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

In a research, data was used often hierarchical structure. Hierarchical data is data obtained through multistage sampling from a population with independent variables can be defined within each level and dependent variable can be defined at the lowest level. One analysis that can be used for data with a hierarchical structure is a multilevel regression analysis. Multilevel regression analysis is the most simple regression analysis 2-levels. 2-level regression analysis will be used to construct a regression model the education level of children in Semarang where children (level-1) nested on the distrits (level-2) with the factors that influence. Estimation of parameter in 2-level regression model can use some methods, one of them is Iterative Generalized Least Square (IGLS). From the results of the discussion indicates that the factors which affect the level of education of children in Semarang is the mother’s education, father’ education, and percentage of farm families. The diversity level of the education of children in Semarang caused more variation among children than the variation between districts.

OPTIMALISASI PORTOFOLIO SAHAM MENGGUNAKAN METODE MEAN ABSOLUTE DEVIATION DAN SINGLE INDEX MODEL PADA SAHAM INDEKS LQ-45 Diah Wulandari; Dwi Ispriyanti; Abdul Hoyyi
Jurnal Gaussian Vol 7, No 2 (2018): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Stock investment is the planting of money in a securities that indicates the ownership of a company in order to provide benefits in the future. In obtaining optimal results from stock investments, investors are expected to create a series of portfolios. The portfolio will help investors in allocating some funds in different types of investments in order to achieve optimal profitability. For selection of optimal stocks representing LQ-45 Index, used 2 methods of Mean Absolute Deviation (MAD) method and Single Index Model (SIM) method. In MAD method, 5 best stocks are BBCA with weight 23%, INDF 8%, KLBF 23%, TLKM 23%, and UNVR 23%. While the SIM method of candidate portfolio obtained is AKRA with weight 15,459%, BBCA 48,193%, BBNI 5,028%,KLBF 0,258% and TLKM 31,062%. Portfolio performance meter is used by sharpe ratio. The value of sharpe ratio is 0,36754 for optimal portfolio using MAD method and 0,40782 for optimal portfolio using SIM method, this means that optimal portfolio using SIM method has better performance than MAD. Keywords: Investment, Portfolio, Index LQ-45, Mean Absolute Deviation, Single Index Model, Sharpe Ratio

KOMPUTASI METODE MULTIVARIATE EXPONENTIALLY WEIGHTED MOVING AVERAGE (MEWMA) UNTUK PENGENDALIAN KUALITAS PROSES PRODUKSI MENGGUNAKAN GUI MATLAB (STUDI KASUS: PT. Pismatex Textile Industry Pekalongan) Riza Fahlevi; Hasbi Yasin; Dwi Ispriyanti
Jurnal Gaussian Vol 9, No 3 (2020): 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.v9i3.28908

Control chart is one of the effective statistical tools to overcome the problem of process quality in a production. Multivariate Exponentially Weighted Moving Average (MEWMA) control chart is an effective quality control tool in processes with more than one variable and correlated (multivariate). The MEWMA control chart has a weight value (λ) which makes this chart more sensitive in detecting small shifts process mean. The weight (λ) has values ranging from 0 to 1 ( ), where this weight will be given to each data. The MEWMA control chart in this study was used to form a control chart by the product defects percentage of grade B and grade B at PT. Pismatex Textile Industry Pekalongan. In this study, GUI Matlab was formed to assist the computational process in forming MEWMA control charts to control the quality of production at PT. Pismatex Textile Industry Pekalongan. Based on the result, the optimal weight is obtained at the weight value λ = 0.9. Keywords: Multivariate Exponentially Weighted Moving Average (MEWMA), Weight (λ), GUI Matlab, Percentage of product defects.

ANALISIS REGRESI LINIER PIECEWISE DUA SEGMEN Syilfi Syilfi; Dwi Ispriyanti; Diah Safitri
Jurnal Gaussian Vol 1, No 1 (2012): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Regression analysis is a statistical method that is widely used in research. In general, the regression analysis is the study of the relationship of one or more independent variables with the dependent variable. In analyze the functional relationship between X as the independent variables and Y as the dependent variable, there may be a linear relationship is different for each interval X. If the regression of X on Y has a linear relationship on the certain of the interval of X, but also has a distinct linear relationship at another interval of X, so the use of piecewise linear regression is appropriate in this case. Piecewise linear regression is a method in regression analysis that divided the independent variable into several segments based on a particular value called the X-knots, and in each segment of the data contained linear regression model. X-knot is a value on the independent variable, where X is the current value of the X-knots, it will form a linear regression equation of the line that is different than the current value of X is under X-knots. Piecewise linear regression can be applied in many fields, one of them in the waters of the analysis regarding the influence of river discharge on the basis of the number of transport sediman. By comparison MSE simple linear regression and multiple linear piecewise two segments, the result that the two segments piecewise linear regression is a model that describes the influence of river discharge on the basis of the number of bedload transport

PERAMALAN BEBAN PEMAKAIAN LISTRIK JAWA TENGAH DAN DAERAH ISTIMEWA YOGYAKARTA DENGAN MENGGUNAKAN HYBRID AUTOREGRESIVE INTEGRATED MOVING AVERAGE – NEURAL NETWORK Berta Elvionita Fitriani; Dwi Ispriyanti; Alan Prahutama
Jurnal Gaussian Vol 4, No 4 (2015): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Excessive use of electronic devices in household and industry has made the demand of nation’s electrical power increase significantly these days. As a corporation that aim to provide national electrical power, Perusahaan Listrik Negara (PLN) that distributes electrical power to Central Java and Yogyakarta has to be able to provide an economical and reliable system of electrical power provider. This study aimed to forecast data of electrical power usage in Central Java and Yogyakarta for the next 30 days. There were three forecasting methods used in this study; Neural Networks and Hybrid ARIMA-NN. The data used in this study was electrical power usage data in January 2014 - November 2014 in Central Java and Yogyakarta. The accuracy of the study was measured based on MSE criteria where the best model chosen was the model that has lowest MSE value. According to the result of the analysis, using Neural Networks model to forecast electrical power usage for the next 30 days has better forecasting result than Hybrid ARIMA-NN model.Key Word : electrical power usage, forecasting of electrical power usage, ARIMA, NN, hybrid ARIMA-NN

ALGORITMA ITERATIVE DICHOTOMISER 3 (ID3) UNTUK MENGIDENTIFIKASI DATA REKAM MEDIS (Studi Kasus Penyakit Diabetes Mellitus Di Balai Kesehatan Kementerian Perindustrian, Jakarta) Avia Enggar Tyasti; Dwi Ispriyanti; Abdul Hoyyi
Jurnal Gaussian Vol 4, No 2 (2015): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Iterative Dichotomiser 3 (ID3) Algorithm is a basic decision tree learning algorithm. These algorithms perform a thorough search (greedy) in all possible decision tree. ID3 algorithm can be implemented using a recursive function, (function that calls itself). One of the problems that can be solved using the ID3 algorithm is a classification of diabetic patients. Diabetic is a disease because of the body is not able to control the amount of sugar or glucose in the bloodstream. Classification using ID3 in the case of diabetics produce trees with many vertices to 32 knot where 21 of them is a leaf node and attribute two-hour postprandial glucose fasting elected as the root node in the decision-making tree. Based on the classification performance measurements show that the classification accuracy or measurement accuracy reaches 89,75%. While the measurement accuracy of the classification algorithm ID3 using test samples totaling 84 samples showed an accuracy of 72,619%. Keywords: ID3 Algortihm, Decision Tree, DiabetesALGORITMA ITERATIVE DICHOTOMISER 3 (ID3) UNTUK MENGIDENTIFIKASI DATA REKAM MEDIS(Studi Kasus Penyakit Diabetes Mellitus Di Balai Kesehatan Kementerian Perindustrian, Jakarta)

KLASIFIKASI KELOMPOK RUMAH TANGGA DI KABUPATEN BLORA MENGGUNAKAN MULTIVARIATE ADAPTIVE REGRESSION SPLINE (MARS) DAN FUZZY K-NEAREST NEIGHBOR (FK-NN) Yani Puspita Kristiani; Diah Safitri; Dwi Ispriyanti
Jurnal Gaussian Vol 4, No 4 (2015): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Good classification method will result on less classification error. Classification method developed rapidly. Two of the existing classification methods are Multivariate Adaptive Regression Spline (MARS) and Fuzzy K-Nearest Neighbor (FK-NN). This research aims to compare the classification of poor household and prosperous household based on per capita income which has been converted according to the poverty line between MARS and FK-NN method. This research used secondary data in the form of result of National Economy and Social Survey (SUSENAS) in Blora subdistrict in 2014. The result of the classification was evaluated using APER. The best classification result using MARS method is by using the combination of BF= 76, MI= 3, MO= 1 because it will result on the smallest Generalized Cross Validation (GCV) and the APER is 10,119 %. The best classification result using FK-NN method is by using K=9 because it will result on the smallest error and the APER is 9,523 %. The APER calculation shows that the classification of household in Blora subdistrict using FK-NN method is better than using MARS method. Keywords: Classification, MARS, FK-NN, APER, SUSENAS, Blora

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'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

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