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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 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 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 JURNAL LENTERA AKUNTANSI Abdi Psikonomi Journal of Education Research Jurnal Locus Penelitian dan Pengabdian 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

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OPTIMASI PARAMETER MODel AUTOREGRESSIVE MENGGUNAKAN ALGORITMA PARTICLE SWARM OPTIMIZATION Setyoko Prismanu Ramadhan; Hasbi Yasin; Suparti Suparti
Jurnal Gaussian Vol 8, No 2 (2019): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Box-Jenkins ARIMA method is a linear model in time series analysis which is widely used in various fields. One estimation method for Box-Jenkins ARIMA model is OLS method which aims to minimize the number of squared errors. This method is not effective when applied to time series data that is random, nonlinear and non-stationary. In this study discussed the alternative method of the PSO algorithm as an parameter optimization of the ARIMA model. PSO algorithm is an optimization method based on the behavior of a flock of birds or fish. The main advantage of the PSO algorithm is having a simple, easy to implement and efficient concept in calculations. This method is applied to data from PT Perusahaan Gas Negara shares. The results of both methods will be compared. In the AR model (1) the value of MSE is 0.532 and MAPE is 0.993. Meanwhile, the PSO algorithm obtained MSE 0.531 and MAPE 0.988. It was found that the PSO algorithm resulted in smaller MSE and MAPE values and could provide better results.Keywords : Time Series Analysis, Autoregressive, PSO

ANALISIS SENTIMEN ULASAN APLIKASI TIKTOK DI GOOGLE PLAY MENGGUNAKAN METODE SUPPORT VECTOR MACHINE (SVM) DAN ASOSIASI Sola Fide; Suparti Suparti; Sudarno Sudarno
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.v10i3.32786

Corona virus pandemic requires people to do activities from home so the number of internet usage in Indonesia has increased because information is carried out through social media. One of the popular social media in Indonesia is TikTok. However, the Tiktok’s popularity cannot be separated from the footsteps of TikTok in Indonesia which was blocked by government for committing many violations. Each application allows users to provide a review about the application. To find out the users TikTok’s sentiment, sentiment analysis was carried out to classify reviews into positive and negative sentiments. Classification is carried out using the Support Vector Machine (SVM) with kernel Radial Basis Function (RBF) method which is more effective classification algorithm and kernel function, seen from previous studies. The parameters used in the SVM gamma default 0.0004255 and the Cost (C) parameter experiment used is 0,01; 0,1; 1; 10; 100; 1000. The results can provide information that can be retrieved using the association method. The steps are scrapping data, data preprocessing, sentiment scoring, TF-IDF weighting, classifying using the SVM RBF kernel method and text association. Evaluation of the model using a confusion matrix with the value of accuracy and kappa. The greater the value of accuracy and kappa, the better the performance of the classification model. The review classification resulted in the best accuracy rate of 90.62% and the best kappa of 81.24% which means that it includes an almost perfect classification result. Based on the data association, positive reviews are given because users like and are comfortable with the current version of TikTok which contains funny videos on fyp. Meanwhile, negative reviews were given because the user failed to register and his account was blocked, so the user asked TikTok to continue to make improvements.

PEMODELAN FUNGSI TRANSFER DAN BACKPROPAGATION NEURAL NETWORK UNTUK PERAMALAN HARGA EMAS (Studi Kasus Harga Emas Bulan Juli 2007 sampai Februari 2019) Silvia Nur Rinjani; Abdul Hoyyi; Suparti Suparti
Jurnal Gaussian Vol 8, No 4 (2019): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

The prestige of investment is increasingly rising as the people educates in managing finances. Gold is an alternative that most people tend to choose to invest. One of the important knowledge in gold investing is to predict the price in the future with factors that influence the price of gold. Therefore, in this research we made a model of gold prices based on crude oil prices. One method to forecast gold prices based on crude oil prices is the transfer function and backpropagation neural network. The results of transfer function model will be used as input for the backpropagation neural network method. The purpose of this research is to get the right forecasting method through the transfer function and backpropagation neural network model that can be used to predict gold prices. The results showed that the transfer function model with b = 0, r = [2], s = 0 and the ARMA noise model (0, [6]) is the best model to forecast the price of gold with the MAPE value of data out sample as 3,3507%. Keywords : Gold Price, Crude Oil Prices, Transfer Function,Backpropagation Neural Network, Forecasting

ANALISIS KURVA SURVIVAL KAPLAN MEIER MENGGUNAKAN UJI LOG RANK (Studi Kasus :Pasien Penyakit Jantung Koroner di RSUD Undata Palu) Arianti Suhartini; Rita Rahmawati; Suparti Suparti
Jurnal Gaussian Vol 7, No 1 (2018): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Coronary heart disease is one of the leading causes of death in the world, including Indonesia. Based on doctor-diagnosed interviews, coronary heart disease’s prevalence in Indonesia on 2013 is 0,5% and based on a doctor-diagnosed is 1,5%. Central Sulawesi is ranked first and second for prevalence based on doctor-diagnosed interviews and doctor-diagnosed. The high number of people with coronary heart disease caused by lack of self-awareness in lifestyle changes. One of the parameters used to assess the success of treatment is the probability of survival. Survival analysis is a data analysis where the outcome of the variables studied is the time until an event occurs. This study raised the problem of survival of coronary heart patients at Undata Palu Hospital which is the main referral hospital for Central Sulawesi region. This research uses nonparametric method that is Kaplan Meier and Log Rank Test based on six factors are age, gender, stadium, disease status, complication and status of anemia. Nonparametric methods do not follow a particular distribution for survival time. Kaplan Meier's survival curve will describe the patient's characteristics of survival probability and followed by a Log Rank test to see if there are differences between curves. The result of analysis and discussion based on Log Rank test result showed that the factors of age, sex and disease status differ significantly. Keywords: Coronary heart disease, RSUD Undata Palu, Kaplan Meier analysis, Log Rank test.

PEMODELAN INDEKS HARGA PROPERTI RESIDENSIAL DI INDONESIA MENGGUNAKAN METODE GENERALIZED SPACE TIME AUTOREGRESSIVE Syazwina Aufa; Rukun Santoso; Suparti Suparti
Jurnal Gaussian Vol 11, No 1 (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.v11i1.34001

Generalized Space Time Autoregressive (GSTAR) is a model used for space time data analysis. Space time data is data related to events at previous times and different locations. GSTAR is an expansion of the Space Time Autoregressive (STAR) method. The STAR method is only suitable for homogeneous locations while GSTAR can be used for heterogeneous locations. This research uses Residensial Property Price Index (IHPR) data. IHPR data is in the form of a multivariate time series consisting of 18 cities/regions with a certain time span. In this study, the analysis of IHPR data is carried out by looking at the relationship between the previous time and other cities/regions. Therefore, the method that can be used is GSTAR method. Analysis of IHPR data in each city/region can help increase the supply of housing, thereby reducing the number of backlogs. The backlog of houses in Indonesia is still relatively high. Backlog is an indicator that is often used by the government to measure the number of housing needs in Indonesia. Based on the fulfillment of the assumptions and the smallest MSE value, the best model obtained is GSTAR(4;1,1,1,1) using cross-correlation normalized weight. The largest IHPR data on forcasting results is in the cities of Makassar, Manado, and Surabaya while the smallest IHPR data is in the city of Balikpapan. The GSTAR method produces forcasted data that is close to the actual data so it is good to use.Keywords : GSTAR, OLS, IHPR

Penerapan Text Mining untuk Melakukan Clustering Data Tweet Akun Blibli Pada Media Sosial Twitter Menggunakan K-Means Clustering Syiva Multi Fani; Rukun Santoso; 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.v10i4.30409

Social media is computer-based technology that facilitates the sharing of ideas, thoughts, and information through the building of virtual networks and communities. Twitter is one of the most popular social media in Indonesia which has 78 million users. Businesses rely heavily on Twitter for advertising. Businesses can use these types of tweet content as a means of advertising to Twitter users by Knowing the types of tweet content that are mostly retweeted by their followers . In this study, the application of Text Mining to perform clustering using the K-means clustering method with the best number of clusters obtained from the Silhouette Coefficient method on the @bliblidotcom Twitter tweet data to determine the types of tweet content that are mostly retweeted by @bliblidotcom followers. Tweets with the most retweets and favorites are discount offers and flash sales, so Blibli Indonesia could use this kind of tweet to conduct advertising on social media Twitter because the prize quiz tweets are liked by the @bliblidotcom Twitter account followers.

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.

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 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 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 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 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 M. Pratama Aryansah 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 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 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 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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