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PEMODELAN DATA INFLASI INDONESIA PADA SEKTOR TRANSPORTASI, KOMUNIKASI, DAN JASA KEUANGAN MENGGUNAKAN METODE KERNEL DAN SPLINE Suparti, Suparti; Tarno, Tarno
MEDIA STATISTIKA Vol 8, No 2 (2015): 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 (249.852 KB) | DOI: 10.14710/medstat.8.2.103-110

Abstract

In this research, we study data modeling of Indonesian inflation in the  transportation, communication and financial services sector using the kernel and spline models. Determination of the optimal models based on the smallest of GCV  value and determination of the best model based on the smallest out sampels of Mean Square Error (MSE) value. By modeling the yoy (year on year) inflation data in Indonesia in the transportation, communication and financial services sector In January 2007 to January 2015, shows that the kernel model  using Gaussian kernel function obtained optimal model with a bandwidth  0.24 and the optimal spline model with order 5 and  4 points knots. Based on out sampels data  in February to August 2015, obtained out sampels  MSE value of the spline model is smaller than the kernel model. So that the spline model is better than the kernel model  to analyze  the inflation data  of transportation, communication and financial services sector.Keywords: Inflation, Transportation, Communication and Financial Services Sector, Kernel, Spline, GCV, MSE.
PERBANDINGAN ANALISA IMAGE WAJAH DIGITAL MENGGUNAKAN METODE COSINUS PAKET (CPT) DAN METODE WAVELET (DWT) suparti, Suparti; Farikhin, Farikhin
MATEMATIKA Vol 6, No 3 (2003): Jurnal Matematika
Publisher : MATEMATIKA

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Abstract

Dalam perkembangan IPTEK seringkali dilakukan pengiriman image melalui suatu media misalnya satelit. Dalam proses pengiriman image ini seringkali mengalami noise (gangguan) yang mengakibatkan image yang diterima menjadi tidak jelas (kabur). Untuk mendapatkan image yang mirip dengan aslinya maka ganguan ini harus dihilangkan (denoising). Dalam analisa image, dapat ditentukan image terbaik dengan menghilangkan gangguan. Analisa image ini dapat dilakukan dengan metode cosinus Fourier (DCT) yang kemudian dikembangkan dalam metode cosinus paket (CPT) maupun dengan metode wavelet (DWT) yang kemudian dikembangkan menjadi metode wavelet paket (WPT). Kebaikan dalam analisa dapat dilihat dari besar kecilnya penyimpangan yang terjadi. Semakin kecil penyimpangannya semakin baik analisa imagenya. Salah satu ukuran untuk menentukan besar penyimpangan adalah dengan menentukan besar MSE (Mean Squared Error). Dalam penelitian ini dilakukan perbandingan analisa image wajah digital menggunakan metode cosinus paket (CPT) dan metode wavelet (DWT) dengan tujuan menentukan image wajah terbaik menggunakan metode CPT dan DWT serta menentukan metode yang lebih efektif. Penelitian ini merupakan kajian literatur yang dikembangkan dengan simulasi menggunakan software S+Wavelets. Dalam analisa image wajah digital metode DWT lebih efektif dari metode CPT.  
ESTIMASI REGRESI WAVELET THRESHOLDING DENGAN METODE BOOTSTRAP Suparti, Suparti; Mustofa, Achmad; Rusgiyono, Agus
MATEMATIKA Vol 10, No 2 (2007): JURNAL MATEMATIKA
Publisher : MATEMATIKA

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Abstract

Wavelet is a function that has the certainly characteristic for example, it oscillate about zero point ascillating, localized in the time and frequency domain and construct the orthogonal bases in  L2(R) space. On of the wavelet application is to estimate non parametric regression function. There are two kinds of wavelet estimator, i.e., linear and non linear wavelet estimator. The non linear wavelet estimator is called a thresholding wavelet rstimator. The application of the bootstrap methode in the thresholding wavelet function estimation is resample the wavelet coefficient of residual. The best of the thresholding wavelet estimator with bootstrap method has minimal of mean square error (MSE). The minimal MSE depend from the number of replication.  
PERBANDINGAN ESTIMATOR REGRESI NONPARAMETRIK MENGGUNAKAN METODE FOURIER DAN METODE WAVELET Suparti, Suparti
MATEMATIKA Vol 8, No 3 (2005): JURNAL MATEMATIKA
Publisher : MATEMATIKA

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Abstract

Let  be independent observation data and follows a model  Yi = f(Xi) + eI ,  i =1,2,...,n  with f is an unknown regression function and ei are independent random variables with mean 0 and variance s2. The function f could be estimated by parametric and nonparametric appro-aches. In nonparametric approach, the function f is assumed to be a smooth function or quadratic integrable function. If f belongs to the Hilbert space L2(R) then the function f could be estimated by estimator of orthogonal series, especially by Fourier series estimator. Another estimator of orthogonal series  which could be use  to estimate f is wavelet estimator. Wavelet estimator is an extention of Fourier series estimator  but it is more effective than the Fourier series estimator because the its IMSE converges to zero quicker than the Fourier series estimator.
EFEKTIVITAS PEMBELAJARAN MODEL TALKING STICK UNTUK MENINGKATKAN HASIL BELAJAR SISWA PADA POKOK MATERI EKOSISTEM KELAS VII D SMP NEGERI 3 KARTASURA SUKOHARJO TAHUNPELAJARAN 2011/2012 Puspitasari, Happy Suci; Suparti, Suparti; Asngad, Aminah
Prosiding Seminar Biologi Vol 9, No 1 (2012): Seminar Nasional IX Pendidikan Biologi
Publisher : Prodi Pendidikan Biologi FKIP UNS

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Abstract

ABSTRAK   Tujuan penelitian ini adalah untuk meningkatkan hasil belajar siswa pada aspek kognitif dan afektif dalam proses pembelajaran Biologi khususnya pokok materi ekosistem menggunakan pembelajaran model Talking Stick. Penelitian ini merupakan jenis penelitian tindakan kelas bersifat kolaboratif antara peneliti yaitu sebagai pelaku yang memberikan tindakan kelas dengan guru mata pelajaran biologi sebagai subjek yang membantu dalam perencanaan dan pengumpulan data. Subjek penelitian tindakan yaitu siswa kelas VII D SMP Negeri 3 Kartasura, Sukoharjo yang berjumlahkan 35 siswa. Penelitian ini dilaksanakan dalam dua siklus, masing-masing siklus terdiri dari  perencanaan, pelaksanaan, observasi, dan refleksi. Pengumpulan data dilaksanakan dengan teknik dokumentasi, observasi, dan post test. Analisis data yang digunakan dengan teknik deskriptif kualitatif yang terdiri atas tahap reduksi data, penyajian data, dan penarikan kesimpulan. Dalam penelitian ini menunjukkan adanya peningkatan hasil belajar siswa dalam pembelajaran biologi. Hal ini dapat dilihat dari peningkatan banyaknya siswa yang tuntas KKM (?69) yaitu sebelum adanya tindakan terdapat 7 siswa (20%), pada siklus I meningkat menjadi 23 siswa (65,8%), dan setelah pelaksanaan siklus II menjadi 31 siswa (88,6%) tuntas. Peningkatan ketuntasan KKM siswa menjadikan rata-rata kelas turut meningkat yaitu dari sebelumnya 55,77 menjadi 73,06 dan meningkat lagi menjadi 74,77. Peningkatan pada aspek afektif dilihat dari hasil penskoran tiap indikator yang menunjukkan peningkatan minat belajar biologi. Hal ini dapat dilihat dari peningkatan prosentase ketuntasan siswa, yaitu pada siklus I sebanyak 25,7% menjadi 65,7% pada siklus II. Berdasarkan penelitian tersebut dapat disimpulkan bahwa pembelajaran model Talking Stick terbukti dapat meningkatkan hasil belajar siswa pada pokok materi ekosistem kelas VII D SMP Negeri 3 Kartasura, Sukoharjo tahun pelajaran 2011/2012.   Kata kunci : Hasil belajar, Talking Stick, ekosistem.
KAJIAN RELIABILITAS DAN AVAILABILITAS PADA SISTEM KOMPONEN PARALEL Pradewi, Riana Ayu Andam; Sudarno, Sudarno; Suparti, Suparti
Jurnal Gaussian Vol 3, No 2 (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 (428.85 KB) | DOI: 10.14710/j.gauss.v3i2.5911

Abstract

Reliability and availability are a measure of item or system performance. System reliability and system availability obtained from the calculation of reliability and availability of the components in the system. Reliability of components in the system are affected by the time to failure (TTF). While the availability of components in the system are affected by the mean time to failure (MTTF) and mean time to repair (MTTR). Given observed time data of lifting machines consists of trolley drive and hoist in parallel, is measured its system availability. Parameter values determined using simple linear regression and maximum likelihood estimation. Furthermore observation time test data distributions in the Kolmogorov-Smirnov test. Trolley drive has exponential distribution for failure time data with  while repair time data is normal distribution with  and . Hoist has weibull failure time data with  and  while lognormal repair time data has  and . The higer value of ti,system reliability value will be close to 0 and the engine can survive until the specified time. Due to MTTF is 4000 hours and MTTR is 45,70 hours, trolley drive’s availability is 98,87%. Availability of hoist is 98,84% from MTTF is 5821,61 hours and MTTR is 67,80 hours. The parallel system availability is 99,986% means the probability of system is in the state of functioning at given time is 99,986%.
KAJIAN DATA KETAHANAN HIDUP TERSENSOR TIPE I BERDISTRIBUSI EKSPONENSIAL DAN SIX SIGMA Murti, Victoria Dwi; Sudarno, Sudarno; Suparti, Suparti
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 (675.946 KB) | DOI: 10.14710/j.gauss.v1i1.917

Abstract

Analisis data tahan hidup biasanya digunakan untuk mengetahui ketahanan hidup suatu produk dalam bidang industri. Data waktu hidup dapat berupa data tersensor tipe I, tipe II dan tipe III. Dalam penelitian ini digunakan data tersensor tipe I yang merupakan suatu data waktu kematian atau kegagalan dimana semua unit uji n masuk pada waktu yang sama dan percobaan dihentikan sampai waktu tertentu. Salah satu distribusi yang dapat digunakan untuk menggambarkan waktu hidup adalah distribusi eksponensial dengan parameter l. Parameter l diestimasi dengan menggunakan metode Maximum Likelihood Estimation (MLE). Untuk mengetahui hubungan linear data kegagalan dengan intensitas kegagalan produk digunakan regresi linier. Selain itu, untuk memperkecil tingkat kegagalan yaitu dengan memprediksi kegagalannya menggunakan tingkat sigma. Nilai tingkat sigma bisa didapatkan dari DPMO (Defect Per Million Opportunity) yang berhubungan dengan MTTF (Mean Time To Failure) atau fungsi Reliabilitas. Jika nilai DPMO semakin kecil maka nilai tingkat sigma semakin besar.
PENDEKATAN SERVQUAL-LEAN SIX SIGMA MENGGUNAKAN DIAGRAM KONTROL T2 HOTELLING UNTUK MENINGKATKAN KUALITAS PELAYANAN PENDIDIKAN (Studi Kasus di Jurusan Statistika Universitas Diponegoro) Darwati, Lulus; Mustafid, Mustafid; Suparti, Suparti
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 (339.505 KB) | DOI: 10.14710/j.gauss.v4i2.8578

Abstract

Measurement the service of quality has an important role in improving and evaluating the performance of a service process. Measuring the service of quality is not as easy as measuring the goods quality, because the assessment service is subjective. Therefore, ServQual dimension is used as a tool to measure the performance of service from the perspective of service’s users. Lean Six Sigma method is used to improve the performance of the services of quality that focused on the reduction of variations and the increasing of the speed of the process through the elimination of waste that occur in the flowing process. This research aims to implement the integration of ServQual and Lean Six Sigma method by controlling the process using Hotelling T2 control charts on the improvement of the quality of education services. The performance of the education services process overall is indicated by the value of the capabilities and the level of the sigma. The capability value amount 0.8407 and the level of sigma amount 2.748 indicates that the waste percentage in the process of educational services is about 10.6%. The waste of dominant on improving the quality of education services such as lecturer competencies, the status of departement accreditation, the speed in the administrative services, and the refinement of laboratory facilities especially the improvement on the computer facilities.Keywords : ServQual, Hotelling T2 control charts, Process Capability, Lean Six Sigma
ANALISIS ANTRIAN PASIEN INSTALASI RAWAT JALAN POLIKLINIK LANTAI 1 DAN 2 RSUD CENGKARENG, JAKARTA Nadeak, Sanitoria; Sugito, Sugito; Suparti, Suparti
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 (705.218 KB) | DOI: 10.14710/j.gauss.v5i1.11059

Abstract

The queue process associates with the arrival of the costumers of a service facility, waiting in a queue line when all waiters are busy, and finally left the facility after being served. Queuing phenomena can be found in public service facilities, such as in District General Hospital (RSUD) Cengkareng. The length of the registration procedure, consultation services for physicians, and waiting time for the pharmacy services, can influence the satisfaction of the patients of Outpatient Installation of RSUD Cengkareng. Therefore, it is necessary to have an appropriate queue model to get an effective service, balanced and efficient, that can reduce the long queues and waiting time. From the analysis, the queue model for the registration of the Workers Social Security Agency (BPJS) patient is (M /M/6):(GD/∞/∞) with the number of server is 6 counters and for the non BPJS patients is (M/M/2):(GD/∞/∞) with the number of server is 2 counters. The queue model for the psychiatrist clinic and anesthetic is (M/M/1):(GD/∞/∞) with the number of server is 1 counter. The queue model for the other Polyclinic is (M/M/c):(GD/∞/∞) with the number of server depends on the clinic itself.Keywords: Queue, Outpatient Installation, District General Hospital (RSUD) Cengkareng
PEMODELAN PERSENTASE PENDUDUK MISKIN DI KABUPATEN DAN KOTA DI JAWA TENGAH DENGAN PENDEKATAN MIXED GEOGRAPHICALLY WEIGHTED REGRESSION Hakim, Arief Rachman; Yasin, Hasbi; Suparti, Suparti
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 (593.43 KB) | DOI: 10.14710/j.gauss.v3i4.8068

Abstract

Regression analysis is a statistical analysis that models the relationship between the response variable and the predictor variable. Geographically Weighted Regression (GWR) is the development of linear regression with the added factor of the geographical location where the response variable is taken, so that the resulting parameters will be local. Mixed Geographically Weighted Regression (MGWR) has a basic concept that is a combination of a linear regression model and GWR, by modeling variables that are local and which are global variables. Methods for estimating the model parameters MGWR no different from the GWR using Weighted Least Square (WLS). Selection of the optimum bandwidth using the Cross Validation (CV). Application models MGWR the percentage of poor people in the district and town in Central Java showed MGWR models that different significantly from the global regression model. As well as models generated for each area will be different from each other. Based on the Akaike Information Criterion (AIC) between the global regression model, the GWR and MGWR models, it is known that MGWR models with Gaussian kernel weighting function is the best model is used to analyze the percentage of poor in the counties and cities in Central Java because it has the smallest AIC value.Keywords: Akaike Information Criterion, Cross Validation, Kernel Gaussian function, Mixed Geographically Weighted  Regression, Weighted Least Square.
Co-Authors A. Sulaksono, A. A.A. Ketut Agung Cahyawan W Abdul Hoyyi Adhytia, Rizkyhimawan Agus Cahyono Agus Rusgiyono Agus Triyono Akbari, Windusiwi Asih Alan Prahutama Alanindra Saputra Alvita Rachma Devi Amanda Devi Paramitha Aminah Asngad Ananda, Refisa Angelia, Yuni Any Setyaningsih, Any Arianti Suhartini Arieanti, Dian Dinarafika Arief Rachman Hakim Arief Rachman Hakim Arnisa Melani Kahar Asismarta Asismarta, Asismarta AYU LESTARI Azizah, Adilla Nur Badriyah, Ratu Bahtiar Ilham Triyunanto Brillianing Pratiwi Budi Warsito C Yuwono Sumasto, C Yuwono Deden Aditya Nanda, Deden Aditya Dewi, Anggra Lita Sandra Dewi, P A R Dhea Dewanti Di Asih I Maruddani Diah Safitri Dwi Ispriyanti Dwi Sambada Dwi Wahyuningsih, Dwi Dwikoranto Eka Anisha Eka Destiyani Eka Fadilah Eka Wijayanti Erna Sulistianingsih Ernik Yuliana Esti Pratiwi Evelyna, Feby Fadilah, Eka Fitri Juniaty Simatupang, Fitri Juniaty Gina Wangsih Hanifah Nur Aini Happy Suci Puspitasari Hasbi Yasin Ihdayani Banun Afa Immawati Ainun Habibah Intaniasari, Yossinta Iut Tri Utami Iut Triutami Izzudin Khalid, Izzudin Jefferio Gusti Putratama Jody Hendrian Juwanda, Farikhin Karwanto, Karwanto Khansa Amalia Fitroh Khansa, I H Khoirunnisa, Siti Intan Khulaifiyah, Khulaifiyah Lamik Nabil Mu'affa Lanjari , Restu Lintangesukmanjaya, R T Lismiyati Marfuah, Lismiyati Lulu Maulatus Saidah Lulus Darwati, Lulus M. Noris Maman Suryaman Meiliawati Aniska Milawati Milawati Moch. Abdul Mukid Mokhamad Nurjam'i MUHAMAD SHOLEH Muhammad Sulaiman Muhammad Taufan Muqorobin, Masculine Muhammad Mustafid Mustafid Mustofa, Achmad Nastiti, Tri Dyah Netriwati Noer Rachma, Gustyas Zella Nunuk Hariyati Nurina Salma Alfiyyah Nurul Fitria Fitria Rizani Ovie Auliya’atul Faizah Paula Meilina Dwi Hapsari Prastya, Agus Puspita Kartikasari Putra, D A Rahma Dewi Hartati Rahman Kosasih, Fauzy Rahman, Syair Dafiq Faizur Rahmawati Patta, Rahmawati Rahyu Setiani Rambat Rambat, Rambat Riana Ayu Andam Pradewi Richy Priyambodo Rismawati Rismawati Rita Rahmawati Rudi Saputro Setyo Purnomo Rukun Santoso Sa'adah, Alfi Faridatus Sadjati, Ida Malati Safitri, Wardani Ana Salma Farah Aliyah Salsabila Rizkia Gusman Sania Anisa Farah Sanitoria Nadeak, Sanitoria Setiawan, Fuad Alfaridzi Setyoko Prismanu Ramadhan Setyowati, Titik Sholihah, Zaimatu Silvia Elsa Suryana Silvia Nur Rinjani Singgih Subiyantoro Siti Fadhilla Femadiyanti Sofiana Sofiana Sola Fide Sri Budiasih, Sri Sri Sumiyati Sri Wahyuni Sri Wahyuningrum Sudargo Sudarno Sudarno Sudarno Sudarno Sugito - Sugito Sugito Sunardi Sunardi Supeno Supratmi, Nunung Surasmi, W A Surasmi, Wuwuh Asrining Syafruddin Syafruddin Syafruddin*, Syafruddin syah, naziah Syazwina Aufa Syiva Multi Fani T. Mart, T. Tarno Tarno Tarno Tarno Tatik Widiharih Tiani Wahyu Utami Triastuti Wuryandari Tyas Estiningrum Ul Haq, Hasna Faridah Dhiya Vera Handayani Victoria Dwi Murti WAHYU SUKARTININGSIH Wahyu Tiara Rosaamalia Widari Widari, Widari Yasir Sidiq YATIM RIYANTO Yon Haryono Yunianika, Ika Tri Yupitasari, Yupitasari Yusak, Suharno Zein, Secondta Habib Syarifah Zia, Nabila Ghaida Zubaidah, Lailia