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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 Pedagogia: Jurnal Pendidikan E-Dimas: Jurnal Pengabdian kepada Masyarakat Catharsis JURNAL KEPEMIMPINAN DAN PENGURUSAN SEKOLAH Briliant: Jurnal Riset dan Konseptual Jurnal Penelitian Pendidikan IPA (JPPIPA) 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 Indonesian Journal on Learning and Advanced Education (IJOLAE) 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 JURNAL PENDIDIKAN MIPA Dinasti International Journal of Education Management and Social Science Jurnal Paedagogy Jurnal Graha Pengabdian Journal of Early Childhood Education (JECE) Indonesian Journal of Instructional Media and Model Epistema EDUTECH : Jurnal Inovasi Pendidikan Berbantuan Teknologi JURNAL LENTERA AKUNTANSI Abdi Psikonomi 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 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

Suparti Suparti

Departemen Statistika, Fakultas Sains Dan Matematika, Universitas Diponegoro

Author-ID : 393390

Religion Agriculture, Biological Sciences & Forestry Arts Humanities Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Engineering Environmental Science Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Medicine & Pharmacology Nursing Physics Social Sciences Other

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PENERAPAN METODEEXPECTED SHORTFALLPADA PENGUKURAN RISIKO INVESTASI SAHAM DENGAN VOLATILITAS MODEL GARCH Nurul Fitria Fitria Rizani; Mustafid Mustafid; Suparti Suparti
Jurnal Gaussian Vol 8, No 1 (2019): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

One of the methods that can be used to measure stock investment risk is Expected Shortfall (ES). ES is an expectation of risk size which value is greater than Value at Risk (VaR), ES has characteristics of sub-additive and convex. The Generalized Autoregressive Conditional Heteroskedasticity (GARCH) model is used to model stock data that has high volatility. Calculating ES is done with data that shows deviations from normality using Cornish-Fisher's expansion. This researchapplies the ES at the closing stock price of PT Astra International Tbk. (ASII), PT Bank Negara Indonesia (Persero) Tbk. (BBNI), and PT Indocement Tunggal Prakarsa Tbk. (INTP) for the period of 11 February 2013 - 31 March 2019. Based on the volatility of GARCH (1,1) analysis, we find ES calculation for each stock by 95% level confidence. The ES for ASII shares is 4.1%, greater than the VaR value which isonly 2.64%.The ES for BBNI shares is 4.38%, greater than it’s VaR value which is only 2,86%. The ES for INTP shares is 6.22%, which is also greater than it’s VaR value which is only3,99%. The greather of VaR then Thegreather of ES obtained.Keywords: Expected Shortfall, Value at Risk, GARCH

KOMPUTASI GUI-R UNTUK PEMODELAN REGRESI NONPARAMETRIK BIRESPON POLINOMIAL LOKAL PADA PENGARUH SUKU BUNGA BI TERHADAP INDEKS HARGA SAHAM GABUNGAN DAN KURS USD Rudi Saputro Setyo Purnomo; Suparti Suparti; Sudarno Sudarno
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.v9i3.28911

Economy is one of important indicator of development country. Capital market is one of important tool in economy. The development of the capital market in Indonesian can be seen based on the composite stock price index (CSPI). Other than capital market, international trade is an important tool in the economy. Existence of the international trade generates exchange rate, one of which is USD exchange rate. Exchange rate can be increased and weakened, so it’s stability needs to be maintained. One of the factor that can influence CSPI and USD exchange rate is the BI interest rate. To be able to predict the value of CSPI and USD exchange rate then do the birespon regression modelling because between CSPI and USD exchange rate there are relationship. The regression model approach which used in this research is local polynomial. This approach has high adaptability with data. To make the modelling easier so this research arrange Graphycal User Interface (GUI) by using R software. The local polynomial birespon regression is applied to CSPI and USD exchange rate data based on BI interest rate by using GUI. The optimal modal is obtained by General Cross Validation (GCV) optimation. The optimal model is model by combination of sequences two and three, bandwidths 6 and 2,7, and local points 5,75 and 6. The value of R Square is 66,68% and the mean absolute percentage error (MAPE) is 4,0798%. This MAPE shows that the optimal model has very high accuration in prediction the data because this value of MAPE less than 10%.Keywords: CSPI, USD exchange rate, BI interest rate, birespon, local polynomial, GUI.

ANALISIS PENGARUH KEPUASAN TERHADAP LOYALITAS KONSUMEN SMARTPHONE SAMSUNG MENGGUNAKAN METODE PARTIAL LEAST SQUARE PADA MAHASISWA UNIVERSITAS DIPONEGORO SEMARANG Jefferio Gusti Putratama; Alan Prahutama; Suparti Suparti
Jurnal Gaussian Vol 10, No 2 (2021): 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.v10i2.30948

Smartphones are one of the electronic devices that are capable of experiencing fairly rapid development. The existence of this Smartphone is considered to be the most important item for used everyday. Samsung is one of the most popular smartphone brand in Indonesia. Based on data from the website of the Statcounter survey institute, it was found that the Samsung market share in Indonesia until August 2020 was in the top position, namely 24.19%. Samsung continues to make various innovations in order to continue to dominate the top of the smartphone sales segment. In addition, to provide consumer's satisfication so that consumer’s loyalty to the Samsung brand will be maintained. The purpose of this study is to make measurement models and structural models, as well as to test the relationship of customer satisfaction to consumer loyalty of Samsung smartphones using the SEM – PLS (Partial Least Square) method. This research was conducted on Diponegoro University students who have purchased and used a Samsung smartphone. This research was conducted on Diponegoro University students who have purchased and used a Samsung smartphone. This research has produced 4 latent variables with 18 measurement models and 2 structural models. Based on the 2 structural models formed, the result shows that the R2 value in the customer satisfaction model is 0.670. This indicates that the variable customer satisfaction can be explained by the variable product quality and price by 67%. Meanwhile, in the consumer loyalty model, the R2 value is 0.478. This indicates that the consumer loyalty variable can be explained by the consumer satisfaction variable of 47.8%. Keywords: Samsung Smartphone, Consumer’s Satisfaction, Consumer’s Loyalty, Partial Least Square.

ANALISIS TECHNOLOGY ACCEPTANCE MODEL PADA APLIKASI PLATFORM SHOPEE DENGAN PENDEKATAN PARTIAL LEAST SQUARE (STUDI KASUS PADA MAHASISWA UNIVERSITAS DIPONEGORO) Ovie Auliya’atul Faizah; Suparti Suparti; Abdul Hoyyi
Jurnal Gaussian Vol 10, No 3 (2021): 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.v10i3.32802

E-commerce refers to business transactions using digital networks such as the internet. Based on the rank on the Appstore and Playstore, Shopee places the first rank. In 2019, Shopee had 56 million visitors. Meanwhile, in the same year, it had 3,225 workers. The imbalance between the number of Shopee visitors and Shopee employees allows users to be disappointed with Shopee's services, but on the other hand, there are also many users who are happy with its services. With both positive and negative responses to the services provided by Shopee, this study analyzes the factors affecting the acceptance of Shopee Apps on students of Universitas Diponegoro Semarang. The analysis was based on the Technology Acceptance Model (TAM). It used the Structural Equation Modeling with the Partial Least Square (SEM-PLS) approach. The study used primary data obtained by distributing questionnaires to students of Universitas Diponegoro. The result showed 28 valid indicators, 5 deal inner models, and 8 significant pathways. All the causality between latent variables contained in the Technology Acceptance Model (TAM) have a positive and significant effect, it's just that the results of integrating trust variables on TAM, namely the latent variable between trust and interest in usage behavior, have no significant effect.

PEMODELAN REGRESI RIDGE ROBUST-MM DALAM PENANGANAN MULTIKOLINIERITAS DAN PENCILAN (Studi Kasus : Faktor-Faktor yang Mempengaruhi AKB di Jawa Tengah Tahun 2017) Eka Destiyani; Rita Rahmawati; Suparti Suparti
Jurnal Gaussian Vol 8, No 1 (2019): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

The Ordinary Least Squares (OLS) is one of the most commonly used method to estimate linear regression parameters. If multicollinearity is exist within predictor variables especially coupled with the outliers, then regression analysis with OLS is no longer used. One method that can be used to solve a multicollinearity and outliers problems is Ridge Robust-MM Regression. Ridge Robust-MM Regression is a modification of the Ridge Regression method based on the MM-estimator of Robust Regression. The case study in this research is AKB in Central Java 2017 influenced by population dencity, the precentage of households behaving in a clean and healthy life, the number of low-weighted baby born, the number of babies who are given exclusive breastfeeding, the number of babies that receiving a neonatal visit once, and the number of babies who get health services. The result of estimation using OLS show that there is violation of multicollinearity and also the presence of outliers. Applied ridge robust-MM regression to case study proves ridge robust regression can improve parameter estimation. Based on t test at 5% significance level most of predictor variables have significant effect to variable AKB. The influence value of predictor variables to AKB is 47.68% and MSE value is 0.01538.Keywords: Ordinary Least Squares (OLS), Multicollinearity, Outliers, RidgeRegression, Robust Regression, AKB.

PERAMALAN JUMLAH PENUMPANG PESAWAT DI BANDARA INTERNASIONAL AHMAD YANI DENGAN METODE HOLT WINTER’S EXPONENTIAL SMOOTHING DAN METODE EXPONENTIAL SMOOTHING EVENT BASED Sofiana Sofiana; Suparti Suparti; Arief Rachman Hakim; Iut Triutami
Jurnal Gaussian Vol 9, No 4 (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.v9i4.29448

Forecasting the number of airplane passengers can be a consideration for the airline at Ahmad Yani International Airport related with addition of extra flight. The number of airplane passengers can be influenced by certain seasonal or special events. The seasonal influences can be known through historical data patterns and if there is a seasonal pattern, the Holt Winter’s Exponential Smoothing method can be used. Exponential Smoothing Event Based (ESEB) forecasting method can be use to see the special events that effect the number of airplane passengers at Ahmad Yani International Airport. After compared, the Holt Winter’s Exponential Smoothing method is a better method of forecasting the number of airplane passengers at Ahmad Yani International Airport because it has a smaller error value, namely the MSE value and the MAPE value than the Exponential Smoothing Event Based (ESEB)method. The MAPE and MSE values be produced from the best method each of 5,644139% and 619,998,718 .Keywords : Airplane Passengers, Seasonal Pattern, Special Event, Exponential Smoothing Event Based , Holt Winter’s Exponential Smoothing.

IMPLEMENTASI PAKET SHINY PADA PEMODELAN MULTISCALE AUTOREGRESSIVE UNTUK DATA HARGA SAHAM BBRI Bahtiar Ilham Triyunanto; Suparti Suparti; Rukun Santoso
Jurnal Gaussian Vol 10, No 3 (2021): 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.v10i3.32781

Stocks are an investment that attract people because they can earn large profits by having claim rights to the company's income and assets so investors have to observe stock price movements in the future to achieve investment goals. One of the statistical methods for time series data modeling is ARIMA. However, modeling assumptions must be fulfilled to use that method so an alternative model is proposed, namely nonparametric regression model, which has no modeling assumptions requirement. In this study, the nonparametric regression multiscale autoregressive (MAR) with two different filter and decomposition level J are compared to choose the best model and forecast it. The data are closing stock price, high stock price and low stock price of BBRI’s stocks that divided into 2 parts, namely in sample data from March 19, 2020 to February 4, 2021 to form a model and out sample data from February 5, 2021 to March 23, 2021 used for evaluation of model performance based on MAPE values. The chosen best model for each stock price are the MAR model with wavelet haar filter and decomposition level 5 for the closing stock price which produces a MAPE value of 1.194%, the MAR model with wavelet haar filter and decomposition level 5 for the high stock price which produces a MAPE value of 1.283%, and the MAR model with a wavelet haar filter and decomposition level 5 for the low stock price which produces a MAPE value of 1.141%, indicating that the models have excellent forecasting capability. In this study, Graphical User Interface (GUI) using R software with the help of shiny package is also built, making data analyzing easier and generating more interactive display output.

PENERAPAN GRADIENT BOOSTING DENGAN HYPEROPT UNTUK MEMPREDIKSI KEBERHASILAN TELEMARKETING BANK Silvia Elsa Suryana; Budi Warsito; Suparti Suparti
Jurnal Gaussian Vol 10, No 4 (2021): 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.v10i4.31335

Telemarketing is another form of marketing which is conducted via telephone. Bank can use telemarketing to offer its products such as term deposit. One of the most important strategy to the success of telemarketing is opting the potential customer to create effective telemarketing. Predicting the success of telemarketing can use machine learning. Gradient boosting is machine learning method with advanced decision tree. Gardient boosting involves many classification trees which are continually upgraded from previous tree. The optimal classification result cannot be separated from the role of the optimal hyperparameter. Hyperopt is Python library that can be used to tune hyperparameter effectively because it uses Bayesian optimization. Hyperopt uses hyperparameter prior distribution to find optimal hyperparameter. Data in this study including 20 independent variables and binary dependent variable which has ‘yes’ and ‘no’ classes. The study showed that gradient boosting reached classification accuracy up to 90,39%, precision 94,91%, and AUC 0,939. These values describe gradient boosting method is able to predict both classes ‘yes’ and ‘no’ relatively accurate.

PENYUSUNAN DAN PENERAPAN METODE REGRESSION ADAPTIVE NEURO FUZZY INFERENCE SYSTEM (RANFIS) UNTUK ANALISIS DATA KURS IDR/USD Lamik Nabil Mu'affa; Tarno Tarno; Suparti Suparti
Jurnal Gaussian Vol 9, No 2 (2020): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

The exchange rate of rupiah is one of the important prices in an open economy because the exchange rate can be used as a tool to measure the economic condition of a country. The movement of the rupiah exchange rate affected the Indonesian economy, maintaining the stability of the rupiah exchange rate became an important thing to do. In an effort to maintain the stability of the rupiah exchange rate, the factors that influence it must first be identified. Several factors affect the IDR / USD exchange rate, namely the large trade price index, foreign exchange reserves, money supply and interest rates. In this study, the Regression Adaptive Neuro Fuzzy Inference System (RANFIS) method was used to analyze the effect of predictor variables on IDR / USD exchange rates. The optimal RANFIS model is strongly influenced by three things, namely the determination of input predictor variable, membership functions, and number of clusters. Determination of the optimal RANFIS model is measured based on the smallest MAPE in-sample. Based on empirical studies applied to predictor variables on IDR / USD exchange rates, it was found that the RANFIS model was optimal, namely with 3 predictor variable inputs consisting of large trade price index variables, money supply and interest rates; with the gauss membership function; 2 clusters and rules produce an MAPE in-sample of 1.93% and an MAPE out-sample of 2.68%, so the performance of the RANFIS model has a very good level of accuracy.

Pengelolaan Data Persampahan pada Bank Sampah Sempulur Asri Gedawang Budi Warsito; Tarno Tarno; Suparti Suparti; Sugito Sugito; Sri Sumiyati
E-Dimas: Jurnal Pengabdian kepada Masyarakat Vol 9, No 2 (2018): E-DIMAS
Publisher : Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/e-dimas.v9i2.1503

Bank sampah adalah suatu sistem pengelolaan sampah kering secara kolektif yang mendorong masyarakat untuk berperan serta aktif di dalamnya. Sistem ini akan menampung, memilah, dan menyalurkan sampah bernilai ekonomi sehingga masyarakat mendapat keuntungan ekonomi dari menabung sampah. Keberadaan bank sampah mempunyai arti penting baik dari sisi lingkungan maupun ekonomi. Pada Bank Sampah Sempulur Asri pengelolaan dan pencatatan data yang dilakukan masih sangat sederhana karena keterbatasan kemampuan dari pengelola maupun masih kurangnya kesadaran akan pentingnya pencatatan data persampahan. Oleh karena itu diperlukan suatu kegiatan yang dapat meningkatkan kesadaran dan kemampuan mencatat data persampahan bagi pengelola bank sampah Sempulur Asri. Kegiatan yang dilakukan meliputi pendampingan menabung serta pelatihan terhadap pengurus bank sampah dan perwakilan warga tentang pengelolaan data persampahan pada suatu bank sampah. Tim pengabdian membuatkan buku tabungan yang memuat volume sampah yang ditabung serta nominal harga yang ditetapkan sesuai jenis dan harga sampah. Setelah dilakukan pendampingan dan pelatihan, administrasi menjadi lebih rapi dan telah sesuai dengan aturan standar pada bank sampah.

Co-Authors A. Sulaksono, A. A.A. Ketut Agung Cahyawan W Aan Sofyan Abdul Hoyyi Adhytia, Rizkyhimawan Afandi, Adam Pri Agus Cahyono Agus Prasetya 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 Anjarwati, Ani Any Setyaningsih, Any Arianti Suhartini Arieanti, Dian Dinarafika Arief Rachman Hakim Arief Rachman Hakim Arnisa Melani Kahar 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 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 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 Fitri Juniaty Simatupang, Fitri Juniaty Gina Wangsih Hamid, Lukman Hanifa Adityarahma Hanifah Nur Aini Happy Suci Puspitasari Hasbi Yasin Haya, Lovina Rizki 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 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'affa Lanjari , Restu Lina Agustina Lintangesukmanjaya, R T Lismiyati Marfuah, Lismiyati Lisnayati, Lisnayati Lulu Maulatus Saidah Lulus Darwati, Lulus M. Noris 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 Netriwati Nia Istiana Noer Rachma, Gustyas Zella Nunuk Hariyati Nurhayati, Rizky Nurina Salma Alfiyyah Nurlia, Titim Nurmanita, Tiara Sevi 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 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 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 Supriyanto, Rudy Suranto Suranto Surasmi, W A Surasmi, Wuwuh Asrining Susilo, Mas Bayu Sutrisno, Supadi Bambang Syafruddin Syafruddin Syafruddin*, Syafruddin syah, naziah Syazwina Aufa Syiva Multi Fani T. Mart, T. Tarno Tarno Tarno Tarno Tatik Widiharih Tiani Wahyu Utami Triastuti Rahayu Triastuti Wuryandari Tyas Estiningrum Ul Haq, Hasna Faridah Dhiya Vera Handayani Victoria Dwi Murti WAHYU SUKARTININGSIH Wahyu Tiara Rosaamalia Widari Widari, Widari Wiradharma, Gunawan 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

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