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All Journal DIKSI Media Statistika MATEMATIKA Jurnal Gaussian Jurnal Statistika Universitas Muhammadiyah Semarang Jurnal Pendidikan Dasar Nusantara Majalah Kulit, Karet, dan Plastik Jurnal Spektra Bioeksperimen: Jurnal Penelitian Biologi Pedagogia: Jurnal Pendidikan E-Dimas: Jurnal Pengabdian kepada Masyarakat Catharsis JURNAL KEPEMIMPINAN DAN PENGURUSAN SEKOLAH Briliant: Jurnal Riset dan Konseptual Indonesian Journal of Applied Statistics Seminar Nasional Variansi (Venue Artikulasi-Riset, Inovasi, Resonansi-Teori, dan Aplikasi Statistika) BIOEDUSCIENCE Jurnal Pendidikan Terbuka Dan Jarak Jauh Journal of Education and Instruction (JOEAI) Jurnal Basicedu JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) JOURNAL OF ENGLISH FOR ACADEMIC Inovasi: Jurnal Ilmiah Ilmu Manajemen JIKAP PGSD: Jurnal Ilmiah Ilmu Kependidikan International Journal for Educational and Vocational Studies Social, Humanities, and Educational Studies (SHEs): Conference Series JURNAL PENDIDIKAN MIPA Jurnal Teknodik Jurnal Paedagogy Jurnal Graha Pengabdian Journal of Early Childhood Education (JECE) Indonesian Journal of Instructional Media and Model Epistema Jurnal Pendidikan dan Pembelajaran Indonesia (JPPI) EDUTECH : Jurnal Inovasi Pendidikan Berbantuan Teknologi Kalam Cendekia: Jurnal Ilmiah Kependidikan JURNAL LENTERA AKUNTANSI DIKSI: Jurnal Kajian Pendidikan dan Sosial Abdi Psikonomi Absorbent Mind Journal of Education Research Jurnal Locus Penelitian dan Pengabdian Jurnal Ilmiah Mahasiswa Manajemen, Bisnis dan Akuntansi Jurnal Basicedu Prosiding University Research Colloquium JURNAL ABDIMAS PLJ JIM: Jurnal Ilmiah Mahasiswa Pendidikan Sejarah Jurnal Edukasi Pengabdian Masyarakat: EDUABDIMAS SERIBU SUNGAI: Journal of Research and Community Service Jurnal Manajemen dan Administrasi Antartika Arty: Jurnal Seni Rupa Pinisi Journal Pendidikan Guru Sekolah Dasar Jurnal Seni Tari Jurnal Teknik Informatika dan Desain Komunikasi Visual AGRONIMAL: Jurnal Ilmiah Pertanian dan Peternakan
Suparti Suparti
Departemen Statistika, Fakultas Sains Dan Matematika, Universitas Diponegoro
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PEMODELAN KURS DOLLAR AMERIKA SERIKAT TERHADAP RUPIAH MENGGUNAKAN REGRESI PENALIZED SPLINE DILENGKAPI GUI R Gina Wangsih; Suparti Suparti; Sudarno Sudarno
Jurnal Gaussian Vol 11, No 2 (2022): 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.v11i2.35469

Abstract

United States Dollar (USD) exchange rate movement against Rupiah is the main guideline for economic actors in making decisions. Exchange rate movement of USD against Rupiah is a time series data. One of the statistical methods that can be used for modelling time series data is ARIMA. ARIMA method data must be stationery and residuals must be normally distributed, independent, and constant variance, which means an alternative model is needed so that it is not bound by any assumptions, namely a nonparametric penalized spline regression model. Selling rate data of USD against Rupiah is modeled using nonparametric penalized spline regression because the assumptions in the ARIMA model are not fulfilled. Penalized spline regression modeling is using full search algorithm in determining knot points. Lambda values are tested from 0 to 100000 on order 2, 3, and 4. Optimal penalized spline model is a model with minimum GCV value. R GUI facilitate the process of selecting the best model. Data is divided into 2 parts, namely in sample data for model formation and out sample data for evaluating the best model performance based on MAPE value. Penalized spline regression modeling produces the best model, namely optimal penalized spline model with minimum GCV value achieved on 3rd order with 35 knot points and lambda value = 2007. 96,20% value of R Squared model indicates the model is a strong model. In the evaluation of the best model, the MAPE data out sample value is 0.65%. MAPE value indicates the model has very good forecasting ability.
PEMODELAN FAKTOR EKONOMI MAKRO TERHADAP HARGA SAHAM TELKOM MENGGUNAKAN REGRESI SPLINE TRUNCATED MULTIVARIABEL DILENGKAPI GUI R Lulu Maulatus Saidah; Suparti Suparti; Sudarno Sudarno
Jurnal Gaussian Vol 11, No 3 (2022): 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.11.3.344-354

Abstract

Stock prices are an important thing that investors should know before investing. Volatile stock prices require investors to know the factors that influence their changes. Stock price instability makes it very difficult for investors to make investments and affects the integrity they get. One of the factors that affect stock prices is macroeconomic factors consisting of rupiah exchange rate (X1), inflation (X2), and SBI interest rate (X3). A statistical method that can be used to model fluctuating data is spline nonparametric regression. This study aims to model macroeconomic factors against Telkom's stock price using multivariable truncated spline nonparametric regression with optimal knot point selection methods that minimize Generalized Cross Validation (GCV). Many knots used are a combination of 1 and 2 and the order used is a combination of 2, 3, and 4. The best multivariable truncated spline model is achieved on a knot combination (2,2,2) with the order X1, X2, X3 being 3, 2, 2 which results in an R2 value of 92.71% included in the strong model criteria. In the evaluation of model performance obtained a MAPE value of 1.857% which shows the model has excellent forecasting ability. In this study, a Graphical User Interface (GUI) program was formed R that can facilitate data analysis and produce more attractive display output.
ANALISIS REGRESI FAKTOR PANEL DINAMIS BLUNDELL-BOND DENGAN ESTIMASI SYSTEM-GENERALIZED METHOD OF MOMENT PADA SAHAM FARMASI DI BEI Hanifah Nur Aini; Dwi Ispriyanti; Suparti Suparti
Jurnal Gaussian Vol 11, No 3 (2022): 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.11.3.447-457

Abstract

The pharmaceutical sector has become a concern during the Covid-19 pandemic because of the large use of drugs. Companies need to improve financial performance to increase their share prices and investors need analysis to predict future stock prices. This study aims to analyze the influence of stock prices on 10 pharmaceutical companies on the Indonesia Stock Exchange during the third quarter of 2020 to the third quarter of 2021. Based on previous research, the factors that are thought to have an effect on changes in stock prices are internal financial ratios (ROA, ROE, NPM, GPM, EPS, PER, BV, PBV, DAR, DER, CR, QR, Cash Asset Ratio) and external inflation, exchange rates, interest rates. The method used in this research is dynamic panel factor regression analysis with GMM (Generalized Method of Moment) estimation. Factor analysis to reduce the independent variables to form a factor score which is then entered into the regression. The regression model was obtained from the comparison of Arellano-Bond GMM and Blundell-Bond System. The GMM system is the development of Arellano-Bond which will produce more efficient estimates when the sample time series is short. The results of the study were obtained 3 factor scores with a total variance of 81.757% from the elimination of 6 variables that had MSA <0.5. The best model is the Blundell-Bond Twostep System which fulfills the model assumptions with RMSE 803.276.
PEMODELAN INDEKS PEMBANGUNAN MANUSIA DI JAWA TENGAH MENGGUNAKAN METODE REGRESI RIDGE DAN REGRESI STEPWISE Erna Sulistianingsih; Suparti Suparti; Dwi Ispriyanti
Jurnal Gaussian Vol 11, No 3 (2022): 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.11.3.468-477

Abstract

The Human Development Index (HDI) is an important indicator in measuring the success of national development. Central Java with a high population can be considered as an obstacle and a driver of development. To find out the factors that affect HDI, it is necessary to make a model. One of the statistical methods that can be used is multiple linear regression analysis. However, in modeling multiple linear regression there are assumptions that must be met, namely linearity, normality, homoscedasticity, non-autocorrelation, and non-multicollinearity. If the non-multicollinearity assumption is not met, then another alternative is needed to estimate the regression parameters. Several methods that can be used are ridge regression and stepwise regression methods. The best model selection is done by looking at the smallest Mean Square Error (MSE) value. In this study, ridge and stepwise regression were applied to Central Java HDI data in 2021 and the factors that influence it, namely life expectancy at birth, expected years of schooling, average length of schooling, per capita expenditure, percentage of poor people, and unemployment open. Based on the Variance Inflation Factor (VIF) value of more than 10, it can be concluded that there is a multicollinearity violation. Modeling with stepwise regression produces the best model, with the smallest MSE value. The R square model value of 0,99 indicates that the model is included in the criteria for a strong model.
PENERAPAN ALGORITMA BACKPROPAGATION DAN OPTIMASI CONJUGATE GRADIENT UNTUK KLASIFIKASI HASIL TES LABORATORIUM Wahyu Tiara Rosaamalia; Rukun Santoso; Suparti Suparti
Jurnal Gaussian Vol 11, No 4 (2022): 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.11.4.506-511

Abstract

A blood test is generally used to evaluate the condition of the blood and its components, conduct screening, and aid diagnosis. Blood tests in the laboratory are commonly used to deliberate whether a patient needs to be hospitalized or treated as an outpatient. Backpropagation algorithm was selected for its ability to solve complex problems. Conjugate gradient optimization is used because it facilitates faster solution search. An electronic medical record containing the results of patient laboratory examinations was obtained from Mendeley. The data was divided into training and testing with a 95:5 ratio, which was discovered to be the best ratio from the experiments. The best architecture was achieved by a combination of 10 neurons in the input layer, 16 neurons in the first hidden layer, 2 neurons in the second hidden layer, and a neuron in the output layer. Purelin is used as the activation function for both the first hidden and output layers, whereas the binary sigmoid is used for the second hidden layer. The analysis revealed that for 100 bootstraps in training data, the network worked with an average accuracy of 60.17% and a recall of 99.77%, while the accuracy results in testing data were 69.23%.
PEMODELAN KURS RUPIAH TERHADAP DOLAR AMERIKA SERIKAT MENGGUNAKAN REGRESI NONPARAMETRIK CAMPURAN KERNEL DAN SPLINE Khansa Amalia Fitroh; Rukun Santoso; Suparti Suparti
Jurnal Gaussian Vol 11, No 4 (2022): 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.11.4.522-531

Abstract

Exchange currency is one way for a country to be able to transact with the outside world. Fluctuating movement of the rupiah exchange currency was caused by many influencing factors, such as exports, imports, the money supply (JUB), inflation, and JCI. To find out the relationship, nonparametric regression modeling was carried out with a mixed kernel estimator and a multivariable truncated linear spline. Import variables were approached with kernel regression because the data patterns were random and spread out while the export variables, JUB, inflation, and the Jakarta Composite Index (JCI) were approached with spline regression because the data patterns changed at certain sub-intervals. The purpose of this study is to model exchange currency of the rupiah against the US dollar with a mixed kernel and spline truncated estimator. The parameter estimation method used is Ordinary Least Square (OLS). The multivariable linear truncated spline and kernel mix estimator depends on knot points and bandwidth. The best model is seen from the knot point and optimal bandwidth obtained by selecting the minimum Generalized Cross Validation (GCV). The best model is applied to data on the exchange currency of the rupiah against the US dollar with two optimal knot points resulting in value of 0.7627. The model performance evaluation was calculated using MAPE and the resulting MAPE value was 0.598%.
PERBANDINGAN MODEL ARIMA DENGAN MODEL NONPARAMETRIK POLINOMIAL LOKAL DAN SPLINE TRUNCATED UNTUK PERAMALAN HARGA MINYAK MENTAH WEST TEXAS INTERMEDIATE (WTI) DILENGKAPI GUI R Salsabila Rizkia Gusman; Suparti Suparti; Agus Rusgiyono
Jurnal Gaussian Vol 12, No 1 (2023): 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.12.1.20-29

Abstract

Crude oil as one of the most important natural resources experiences price fluctuations from time to time, even the spot price of West Texas Intermediate (WTI) world crude oil on 20th April 2020 reached -36,98 USD/barrel due to the Covid-19 pandemic. WTI oil price data was modeled using the ARIMA method, local polynomial, and spline truncated nonparametric regression then compared and obtained the best model and formed R Graphical User Interface (GUI). The ARIMA model and nonparametric time series models can be used to model time series data, but in the ARIMA model there are assumptions that must be fulfilled. Nonparametric time series models, which include local polynomial model and truncated spline do not need to fulfill these assumptions. The ARIMA model obtained did not fulfilled the assumptions of normality and residual homoscedasticity, so the modeling was stopped and modeling was only carried out using nonparametric regression methods. Based on the minimum MSE criteria, the best nonparametric model was obtained, namely nonparametric truncated spline model with degrees 3 and 3 knot points which was categorized as a strong model based on R-squared in sample value and having a very good forecasting ability based on MAPE out sample value.
PEMODELAN HARGA SAHAM PERUSAHAAN PROPERTI DAN REAL ESTATE MENGGUNAKAN REGRESI LONGITUDINAL SPLINE TRUNCATED DILENGKAPI GUI R Nurina Salma Alfiyyah; Suparti Suparti; Sugito Sugito
Jurnal Gaussian Vol 12, No 1 (2023): 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.12.1.42-51

Abstract

Stocks are one of the most popular financial instruments traded in the capital market. One of stock prices fluctuate up and down due to the influence of several factors, one of which is inflation. Stocks in the property and real estate sectors are important indicators to determine the level of a country economy. Data on several stock prices is one case of longitudinal data in economic field. The data is divided into 2 parts, namely in sample data from January 2016 to October 2020 and out sample data from November 2020 to December 2021. In this study, longitudinal stock price data is modeling using nonparametric spline truncated. The best spline truncated model is determined by the order and the optimal number of knot points based on the minimum Generalized Cross Validation value. Spline truncated nonparametric regression modeling for longitudinal data in this study is equipped with Graphical User Interface (GUI) that can facilitate the data processing. The results of the analysis show that the best longitudinal spline truncated regression model obtained on 2nd order with 5 knot points. 95.04% value of  indicates the model is a strong model. In the evaluation of the best model, the MAPE data out sample value is 16.45%. It indicates the model has good forecasting ability.
ANALISIS INDEKS HARGA SAHAM GABUNGAN DAN FAKTOR PENGARUHNYA MENGGUNAKAN PEMODELAN REGRESI SEMIPARAMETRIK KERNEL DILENGKAPI GUI-R Arnisa Melani Kahar; Suparti Suparti; Arief Rachman Hakim
Jurnal Gaussian Vol 12, No 1 (2023): 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.12.1.30-41

Abstract

Composite Stock Price Index (IDX) shows the movement of stock prices used by investors to determine their investment strategy. IDX movement is influenced by macroeconomic factors such as money supply and inflation, so regression analysis is used to determine the relationship between the variables. Based on the scatterplot, money supply is known as a parametric predictor variable as it has a linier line patterned scatterplot and inflation is a nonparametric predictor variable as it has a random patterned scatterplot, so semiparametric regression modelling is used for the analysis. Kernel regression was chosen to analyze the nonparametric component based on the random patterned scatterplot of inflation. This study aims to obtain the results of semiparametric kernel regression modelling analysis and to create a GUI to be applied to the analysis as a development of previous similar studies that still done based on CLI. This study uses monthly data from January 2013 to December 2020 with the proportion of in sample and out sample data distribution 87,5%:12,5%. Based on the smallest MSE value as the best model criteria, semiparametric regression model with triangle kernel function is the best model obtained with optimal bandwidth=3.24,  which means the model is strong and  which means that the forecasting results are very accurate. GUI has been created according to the needs of the modelling analysis implementation.
Analisis Kelayakan Pembukaan Prodi Pendidikan Bahasa Arab di Universitas Terbuka Syafruddin*, Syafruddin; Pratiwi, Brillianing; Yunianika, Ika Tri; Sulaiman, Muhammad; Rahman Kosasih, Fauzy; Supratmi, Nunung; Suparti, Suparti
JIM: Jurnal Ilmiah Mahasiswa Pendidikan Sejarah Vol 8, No 3 (2023): Juni, socio-economics, community law, cultural history and social issues
Publisher : Universitas Syiah Kuala

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24815/jimps.v8i3.25030

Abstract

Penelitian ini bertujuan untuk mengetahui respon dosen dan kaprodi terhadap pembukaan prodi PBA di UT dengan sistem pendidikan jarak jauh, mendeskripiskan tren mahasiswa untuk memilih prodi PBA, dan menjelaskan sistem pembelajaran PBA di beberapa universitas di Indonesia. Penelitian ini merupakan penelitian deskriptif dengan pendekatan kualitatif. Pengambilan data dilakukan dengan wawancara. Hasil penelitian ini yaitu: 1). dosen dan kaprodi dari universitas lain sangat mendukung UT untuk membuka prodi PBA dengan sistem PJJ; 2). Tren minat mahasiswa untuk memilih prodi PBA meningkat: 3). saat ini sistem pembelajaran di universitas lain menggunakan online dan offline dengan tujuan memiliki lulusan pendidik bahasa arab dan profesi lainnya yang relevan dengan keterampilan yang diajarkan pada prodi masing-masing.
Co-Authors A. Sulaksono, A. A.A. Ketut Agung Cahyawan W Aan Sofyan Abdul Hoyyi Adhytia, Rizkyhimawan Afandi, Adam Pri Agus Cahyono Agus Rusgiyono Agus Triyono Akbari, Windusiwi Asih Alan Prahutama Alanindra Saputra Alvita Rachma Devi Amanda Devi Paramitha Ambarwati Aminah Asngad Ananda, Refisa Angelia, Yuni Anggun Ella Indriyani Anik Rahmawati, Anik Any Setyaningsih, Any Arianti Suhartini Arieanti, Dian Dinarafika Arief Rachman Hakim Arief Rachman Hakim Arnisa Melani Kahar Aryansah, M. Pratama Ash Shiddiq, Fanchas Asismarta Asismarta, Asismarta Ayu Annisa Gharini AYU LESTARI Azizah, Adilla Nur Badriyah, Ratu Bahtiar Ilham Triyunanto Brillianing Pratiwi Budi Warsito Budiarti, Arivia Ayu Busnang, Yuliawati C Yuwono Sumasto, C Yuwono Deden Aditya Nanda, Deden Aditya Dewi, Anggra Lita Sandra Dewi, P A R Dhany Efita Sari Dhea Dewanti Di Asih I Maruddani Diah Safitri Dian Kristiana Dwi Ispriyanti Dwi Sambada Dwi Wahyuningsih, Dwi Dwikoranto Eka Anisha Eka Destiyani Eka Fadilah Eka Wijayanti Eko Sugiyanto Ermanuri, Ermanuri Erna Sulistianingsih Ernawati, Devi Ernik Yuliana Esti Pratiwi Evelyna, Feby Evi Oktaviana, Desy Fadilah, Eka Finarsih, Fita Fitri Juniaty Simatupang, Fitri Juniaty Gina Wangsih Hamid, Lukman Hanifa Adityarahma Hanifah Nur Aini Happy Suci Puspitasari Hartono Hartono Hasbi Yasin Haya, Lovina Rizki Heni Nurhaeni I Made Sulandra Ihdayani Banun Afa Immawati Ainun Habibah Intaniasari, Yossinta Iut Tri Utami Iut Triutami Izzudin Khalid, Izzudin Janaka, Janaka Jefferio Gusti Putratama Jody Hendrian Jumadi Jumadi Juwanda, Farikhin Karimawati, Nurul Kartika, Aninda Ayu Karwanto, Karwanto Khaerul Anam Khansa Amalia Fitroh Khansa, I H Khoirunnisa, Siti Intan Khulaifiyah, Khulaifiyah Lamik Nabil Mu&#039;affa Lanjari , Restu Lina Agustina Lintangesukmanjaya, R T Lismiyati Marfuah, Lismiyati Lisnayati, Lisnayati Lulu Maulatus Saidah Lulus Darwati, Lulus M. Noris Malarsih Malarsih Maman Suryaman MASLIHATIN, LINA Meiliawati Aniska Milawati Milawati Moch. Abdul Mukid Mokhamad Nurjam'i MUHAMAD SHOLEH Muhammad Sulaiman Muhammad Taufan Muhtadi Muhtadi Muqorobin, Masculine Muhammad Mustafid Mustafid Mustaji Mustaji, Mustaji Mustofa, Achmad Nastiti, Tri Dyah Nia Istiana Noer Rachma, Gustyas Zella Nunuk Hariyati Nurhayati, Rizky Nurina Salma Alfiyyah Nurlaila, Isnaeni Yasmin Nurlia, Titim Nurmanita, Tiara Sevi Nurpitasari, Dewi Nurul Fitria Fitria Rizani Ovie Auliya’atul Faizah Paula Meilina Dwi Hapsari Peter Rajagukguk Pranata, Sepbrie Mulia Bingah Prasetyo, Mario Aditya Prastowo, Srihandono Budi Prastya, Agus Puspita Kartikasari Putra, D A Putri Agustina Rahma Dewi Hartati Rahman Kosasih, Fauzy Rahman, Syair Dafiq Faizur Rahman, Winda Tri Astuti Rahmawati Patta, Rahmawati Rahyu Setiani Rambat Rambat, Rambat Renti Oktaria, Renti Retnowati, Lina Riana Ayu Andam Pradewi Richy Priyambodo Rismawati Rismawati Rita Rahmawati RIZKYHIMAWAN, ADHYTIA Rohayati, Menik Rudi Saputro Setyo Purnomo Rukun Santoso Sa'adah, Alfi Faridatus Sadjati, Ida Malati Safitri, Wardani Ana Salma Farah Aliyah Salsa Bella, Shella Salsabila Rizkia Gusman Sania Anisa Farah Sanitoria Nadeak, Sanitoria Septian Hendra Wijaya Setiawan, Fuad Alfaridzi Setyoko Prismanu Ramadhan Setyowati, Titik Sholihah, Zaimatu Silvia Elsa Suryana Silvia Nur Rinjani Singgih Subiyantoro Sirojuddin, Muhammad Siska Andriyani Siti Fadhilla Femadiyanti Siti Fatimah Sofiana Sofiana Sola Fide Sri Budiasih, Sri Sri Sumiyati Sri Wahyuni Sri Wahyuningrum Suci Kurniawati Sucipto Hadi Purnomo Sudargo Sudarno Sudarno Sudarno Sudarno Sugiarti, Ning Sugito - Sugito Sugito Sunardi Sunardi Supeno Supratmi, Nunung Supriyanto, Rudy Suranto Suranto Surasmi, W A Surasmi, Wuwuh Asrining Suratno Suratno Susilo, Mas Bayu Sutrisno, Supadi Bambang Syafruddin , Syafruddin Syafruddin Syafruddin Syafruddin*, Syafruddin syah, naziah Syazwina Aufa Syiva Multi Fani T. Mart, T. Tarno Tarno Tarno Tarno Tatik Widiharih Teguh Supriyanto Tiani Wahyu Utami Titik Suryani Triastuti Rahayu Triastuti Wuryandari Tyas Estiningrum Ul Haq, Hasna Faridah Dhiya Vera Handayani Victoria Dwi Murti Wahyu Lestari WAHYU SUKARTININGSIH Wahyu Tiara Rosaamalia Widari Widari, Widari Wiradharma, Gunawan Wulandari, Tanti Ratna Yasir Sidiq YATIM RIYANTO Yon Haryono Yunianika, Ika Tri Yuningsih Yuningsih Yupitasari, Yupitasari Yusak, Suharno Zein, Secondta Habib Syarifah Zia, Nabila Ghaida Zubaidah, Lailia Zuhri, Thoha Syaifudin