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All Journal DIKSI Media Statistika MATEMATIKA Prosiding Seminar Biologi Jurnal Gaussian Jurnal Statistika Universitas Muhammadiyah Semarang Jurnal Pendidikan Dasar Nusantara Majalah Kulit, Karet, dan Plastik Jurnal Spektra Bioeksperimen: Jurnal Penelitian Biologi E-Dimas: Jurnal Pengabdian kepada Masyarakat Catharsis JURNAL KEPEMIMPINAN DAN PENGURUSAN SEKOLAH Indonesian Journal of Applied Statistics Seminar Nasional Variansi (Venue Artikulasi-Riset, Inovasi, Resonansi-Teori, dan Aplikasi Statistika) Jurnal Pendidikan Terbuka Dan Jarak Jauh Jurnal Basicedu JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) JOURNAL OF ENGLISH FOR ACADEMIC JIKAP PGSD: Jurnal Ilmiah Ilmu Kependidikan International Journal for Educational and Vocational Studies JURNAL PENDIDIKAN MIPA Dinasti International Journal of Education Management and Social Science Jurnal Graha Pengabdian Indonesian Journal of Instructional Media and Model Epistema Journal of Education Research Jurnal Ilmiah Mahasiswa Manajemen, Bisnis dan Akuntansi Journal of Advanced Sciences and Mathematics Education Innovation Business Management and Accounting Journal Jurnal Basicedu JIM: Jurnal Ilmiah Mahasiswa Pendidikan Sejarah Jurnal Edukasi Pengabdian Masyarakat: EDUABDIMAS SERIBU SUNGAI: Journal of Research and Community Service Arty: Jurnal Seni Rupa Pinisi Journal Pendidikan Guru Sekolah Dasar Jurnal Seni Tari

Suparti Suparti

Departemen Statistika, Fakultas Sains Dan Matematika, Universitas Diponegoro

Author-ID : 393390

Religion Agriculture, Biological Sciences & Forestry Arts Humanities Chemistry Computer Science & IT Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Engineering Environmental Science Languange, Linguistic, Communication & Media Mathematics Physics Social Sciences Other

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PEMODELAN REGRESI SPLINE MENGGUNAKAN METODE PENALIZED SPLINE PADA DATA LONGITUDINAL (Studi Kasus: Harga Penutupan Saham LQ45 Sektor Keuangan dengan Kurs USD terhadap Rupiah Periode Januari 2011-Januari 2016) Zia, Nabila Ghaida; Suparti, Suparti; Safitri, Diah
Jurnal Gaussian Vol 6, No 2 (2017): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Nonparametric regression is one type of regression analysis used when parametric regression assumptions are not fulfilled. Nonparametric regression is used when the curve does not form a specific pattern of connections. One of the approach by using nonparametric regression is spline regression with penalized spline method. Spline regression using penalized spline method was applied to three closing stock prices on the financial sector such as Bank BRI, BCA and Mandiri with the data of USD currency rate in rupiah. Closing price of stock data and the USD currency rate in rupiah were taken from January 2011 up to January 2016 for in sample data and from February 2016 up to December 2016 for out sample data. The data taken is called longitudinal data which is observing some subjects on specific period. Best spline regression model with penalized spline method is derived from the minimum value of GCV, the number of optimal knots and the optimal orde. Best spline regression model with penalized spline method for longitudinal data was obtained on the orde of 1, the 59 knots, the smoothing parameter with λ value of 1 and the GCV value of 889,797. The R2 value of in sample data was 99,292%, best model performance for in sample data. MAPE value of out sample data is 1,057%, the best accurate performance model.Keyword: stock price, USD currency rate, longitudinal data, spline regression, penalized spline

PENERAPAN RANCANGAN BLOK RANDOM TIDAK LENGKAP SEIMBANG PADA KOMBINASI PUPUK NANOSILIKA DAN PUPUK NPK TERHADAP PERTUMBUHAN TANAMAN JAGUNG Asismarta, Asismarta; Suparti, Suparti; Sudarno, Sudarno
Jurnal Gaussian Vol 5, No 1 (2016): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Balanced Incomplete Block Design (BIBD) when all treatment comparisons are equally important, the treatment combinations used in each block should be selected in a balanced manner so that any pair of treatments occur together the same number of times as any other pair. The data used is the result a simulation of the generation of data using program packages MINITAB 16 that normal distributing with a and varying Based on the study of cases the combined effect fertilizer nanosil and fertilizer NPK on the growth of corn plant, tested on 6 treatment and 10 block with every treatment repeated as many as 5 times and each block unfilled 3 treatment. Assuming model that is residual the normal distribution, independence and variant homogeneous. When third this assumption be accepted then followed the effect treatment (adjusted) against an observed, when having effect and undergone a further Tukey to know treat which that differ significantly. Of treatment to be adjusted obtained with combination 25% fertilizer nanosil + 75% fertilizer NPK who gives the average the biggest contributor to the growth of plants corn.Keywords : BIBD, Tuckey test, normality, independence, equal variance

ANALISIS PENGARUH JUMLAH UANG BEREDAR DAN NILAI TUKAR RUPIAH TERHADAP INDEKS HARGA SAHAM GABUNGAN MENGGUNAKAN PEMODELAN REGRESI SEMIPARAMETRIK KERNEL Nanda, Deden Aditya; Suparti, Suparti; Hoyyi, Abdul
Jurnal Gaussian Vol 5, No 3 (2016): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Stocks are one of the many forms of investment chosen by the investor. Investors can use Composite Stock Price Index (CSPI) as one of the indicators that show the movement of stock prices. CSPI fluctuates every day, where one of the causes are macroeconomic factors. Therefore needs to be done a proper analysis to model the CSPI and the factors that influence it. This study is using 1 parametric component variable (money supply) and 1 nonparametric component variable (exchange rate the rupiah against the dollar). So that proper modeling is semiparametric regression. Nonparametric component will be using kernel regression method by selecting the optimal bandwidth using a generalized cross validation method (GCV). This study uses monthly data. Data in sample is used as much as 68 data that is taken from Januari 2010 to August 2015, meanwhile out sample that is used as much as 6 data from September 2015 to February 2016. Based on the results of the analysis that has been done, the best kernel semiparametric regression model is using gaussian kernel function with bandwidth is around 47.94 and GCV=34675.27047. Determination coefficient value is 0.9781. Evaluation result of the model for value of Mean Absolute Percentage Error (MAPE) data out sample is around 4,036%, which indicates that the model is very accurate.Keywords: Composite Stock Price Index (CSPI), Semiparametric regression, Kernel, GCV

KLASIFIKASI RUMAH LAYAK HUNI DI KABUPATEN BREBES DENGAN MENGGUNAKAN METODE LEARNING VECTOR QUANTIZATION DAN NAIVE BAYES Simatupang, Fitri Juniaty; Wuryandari, Triastuti; Suparti, Suparti
Jurnal Gaussian Vol 5, No 1 (2016): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

House is a very basic need for everyone besides food and clothing. House can reflect the level of welfare and the level of health of its inhabitants. The advisability of a house as a good shelter can be seen from the structure and facilities of buildings. This research aims to analyze the classification of livable housing and determine the criteria of houses uninhabitable. The statistical method used are the Learning Vector Quantization and Naive Bayes. The data used in this final project are data of Survei Sosial Ekonomi Nasional (Susenas) Kor Keterangan Perumahan in 2014 Quarter 1 district of Kabupaten Brebes. In this research, the data divided into training data and testing data with the proportion that gives the highest accurate is 95% for training data and 5% for testing data. Training data will be used to generate the model and pattern formation, while testing data used to evaluate how accurate the model or pattern formed in classifying data through confusion tables. The results of analysis showed that the Learning Vector Quantization method gives 71,43% of classification accuracy, while Naive Bayes method gives 95,24% of classification accuracy. The Naive Bayes method has better classification accuracy than the Learning Vector Quantization method.Keywords: House, Learning Vector Quantization, Naive Bayes, Classification

PREDIKSI TINGGI PASANG AIR LAUT DI KOTA SEMARANG DENGAN MENGGUNAKAN METODE SEASONAL AUTOREGRESSIVE INTEGRATED MOVING AVERAGE (SARIMA) DAN DETEKSI OUTLIER Sa'adah, Alfi Faridatus; Ispriyanti, Dwi; Suparti, Suparti
Jurnal Gaussian Vol 3, No 3 (2014): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Semarang as the capital of the province of Central Java is a central transportation that has a high intensity and strategic activities. However, this area has a tidal disaster threat level is high enough. Tidal flood is a phenomenon where sea water entered the land area when the sea level has getting tides. In the future impact of tidal inundation in Semarang city is predicted to be greaterso that has needed the forecasting of high tide. The data pairs tend to experience seasonal monthly and contained outliers that may affect the suitability of the model so that Seasonal Autoregressive Integrated Moving Average (SARIMA) and outlier detection is used for forecasting method. For outlier detection, there are four types of outliers are additive outlier (AO), innovational outlier (IO), level shift (LS) and temporary change (TC). The study was conducted on the data of tide in Semarang period January 2004 - December 2012 based on the average high tide occurs when the maximum. The results of research showed that the model SARIMA with 7 outliers result predictions with high accuracy because it has a smaller AIC value is 649,1083 compared to the SARIMA models without outlier is 705,6404.

ANALISIS PAJAK KENDARAAN BERMOTOR MENGGUNAKAN MODEL MULTISCALE AUTOREGRESSIVE DENGAN MAXIMAL OVERLAP DISCRETE WAVELET TRANSFORM (Studi Kasus di UP3AD Kab.Temanggung) Wahyuningrum, Sri; Suparti, Suparti; Mukid, Moch. Abdul
Jurnal Gaussian Vol 3, No 1 (2014): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Time series analysis is applied in many fields, one of them is in the economic field. In this paper will consider analysis of the time series on data income taxes motor vehicles UP3AD Kab.Temanggung using Maximal Overlap Wavelet Transform Discrete (MODWT). Data time series decomposed using wavelet transform, namely MODWT with filter Haar and D4. From this transformation wavelet coefficients and scales coefficients are used for the modeling of time series. Modeling is done using the Multiscale Autoregressive (MAR) forecasting to get period ahead. Results of analysis showed that the model MAR with filter D4 is better than on the model MAR with filter Haar.

ANALISIS ANTREAN BUS KOTA DI TERMINAL INDUK PURABAYA SURABAYA Priyambodo, Richy; Sugito, Sugito; Suparti, Suparti
Jurnal Gaussian Vol 1, No 1 (2012): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Transportation is an important factor to grow the economy of a region. This is because the more smoothly transport then the faster the economy growth of a region. For that, Purabaya bus station always try to provide optimum service to avoid long queue. Queue process is a process of the coming of a customer to a service facility, then waiting in line (queue) when the officers busy, and leaving the place after getting the service. If the queue at Purabaya bus station is pretty much, it will reduce the amount of revenue generated by the transport service provider. Therefore, we need a model of the queue to optimize service to customers in Purabaya bus station. From the analysis, the best queuing models obtained on the service system in Purabaya bus station is (M/G/c): (GD/∞/∞) to service system at the postal arrival with 5 counters, service system for each bus line in passenger service post is (M/G/1): (GD/∞/∞), and (G/G/2): (GD/∞/∞) to service system at the postal departure.

PEMODELAN REGRESI NONPARAMETRIK DATA LONGITUDINAL MENGGUNAKAN POLINOMIAL LOKAL (Studi Kasus: Harga Penutupan Saham pada Kelompok Harga Saham Periode Januari 2012 – April 2015) Khalid, Izzudin; Suparti, Suparti; Prahutama, Alan
Jurnal Gaussian Vol 4, No 3 (2015): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Stocks are securities that can be bought or sold by individuals or institutions as a sign of participating or possessing a company in the amount of its proportions. From the lens of market capitalization values, stocks are divided into 3 groups: large capitalization (Big-Cap), medium capitalization (Mid-Cap) and small capitalization (Small-Cap). Longitudinal data is observation which is conducted as n subjects that are independent to each subject observed repeatedly in different periods dependently. Smoothing technique used to estimate the nonparametric regression model in longitudinal data is local polynomial estimator. Local polynomial estimator can be obtained by WLS (Weighted Least Square) methods. Local polynomial estimator is very dependent on optimal bandwidth. Determination of the optimal bandwidth can be obtained by using GCV (Generalized Cross Validation) method. Among the Gaussian kernel, Triangle kernel, Epanechnikov kernel and Biweight kernel, it is obtained the best model using Gaussian kernel. Based on the application of the model simultaneously, it is obtained coefficient of determination of 97,80174% and MSE values of 0,03053464. Using Gaussian kernel, MAPE out sample of data is obtained as 11,74493%. Keywords: Longitudinal Data, Local Polynomial, Stocks

MEDIA ALTERNATIF CAMPURAN DAUN PISANG KERING DAN KULIT JAGUNG UNTUK MENINGKATKAN PRODUKTIVITAS JAMUR MERANG (VOLVARIELLA VOLVACEA (BULL) SINGER.) DALAM KERANJANG Suparti, Suparti; Safitri, Wardani Ana
Bioeksperimen: Jurnal Penelitian Biologi Vol 6, No 1: Maret 2020
Publisher : Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/bioeksperimen.v6i1.10435

The growth of mushroom requires nutrients such as cellulose, hemicellulose and lignin which can be obtained from rice straw. However, the availability of rice straw at certain times is difficult to obtain. Dried banana leaves and corn husk have the potential to be used as alternative growing media because they contain cellulose, hemicellulose and lignin for the growth of mushrooms. This research was conducted to determine the productivity of straw mushrooms on a mixture of dried banana leaf media and corn husk planted in a basked. The method used RAL (Completely Randomized Design) which consisted of one factor, namely a mixture of 500gr, 375gr, 250gr, 125gr, and 0gr corn shells with Ogr dried banana leaves, 125gr, 250gr, 375gr, and 500gr. Data were tested by one-way Anova analysis. The result showed that there was no effect of the mixture of dried banana leaves and corn husk on the productivity of straw mushrroms. Mushroom can grow on all treatments.

ANALISIS BAHAN AJAR SASTRA DALAM BUKU TEKS BAHASA INDONESIA SMP/MTs KELAS VII Suparti, Suparti; Suryaman, Maman
Diksi Vol. 26 No. 2: DIKSI SEPTEMBER 2018
Publisher : Fakultas Bahasa, Seni, dan Budaya, Universitas Negeri Yogyakarta

(Title: An Analysis of Literary Materials in Indonesian Textbook to Junior Hig School/MTs VII). This study attempted to describe (1) knowledge aspects of literary teaching materials; (2) skill aspects of literary teaching materials; and (3) attitude aspects of literary teaching materials in Indonesian textbook for Junior Hig School/MTs VII grades by using education character approach. This research used qualitative descriptive approachment type of document analysis. The source of the research data was based on the Indonesian textbook of SMP/MTs VII. The technique to collect the data was done by reading and recording technique by using instrument which had been validated in the form of document analysis guide. The research data were analyzed using Miles and Hubermen model which included data reduction, presentation, and conclusion. The results of this study indicated that the knowledge, skills, and attitude aspect of literary materials had fulfilled in the Indonesian textbook for SMP/MTs VII with details (1) based on knowledge aspect of literary materials, the conceptual knowledge was more dominated than factual and procedural knowledge, (2) based on skills aspects of literary materials, the reading skills most often taught than listening, speaking, and writing skills; and (3) based on attitude aspects literary materials, the social attitudes is more dominated than spiritual attitudes.Keywords: literary materials, textbooks, character education.

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

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