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All Journal Jurnal Ilmu Pertanian Indonesia Jurnal Manajemen dan Agribisnis FORUM STATISTIKA DAN KOMPUTASI Jurnal Ekonomi Pembangunan ETIKONOMI EKSAKTA: Journal of Sciences and Data Analysis MATRIK: JURNAL MANAJEMEN, STRATEGI BISNIS, DAN KEWIRAUSAHAAN Media Statistika Sosiohumaniora Statistika Techno.Com: Jurnal Teknologi Informasi CAUCHY: Jurnal Matematika Murni dan Aplikasi TELKOMNIKA (Telecommunication Computing Electronics and Control) Indonesian Journal of Business and Entrepreneurship (IJBE) Jurnal Berkala Ilmu Perpustakaan dan Informasi Jurnal Teknologi Informasi dan Ilmu Komputer Jurnal Aplikasi Bisnis dan Manajemen (JABM) E-Journal Scientific Journal of Informatics Journal of Consumer Science Jurnal Ilmiah Arena Tekstil MIX : Jurnal Ilmiah Manajemen JOIN (Jurnal Online Informatika) Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) International Journal of Artificial Intelligence Research MAJALAH ILMIAH GLOBE Journal of Consumer Sciences Matra Pembaruan: Jurnal Inovasi Kebijakan Seminar Nasional Variansi (Venue Artikulasi-Riset, Inovasi, Resonansi-Teori, dan Aplikasi Statistika) Informatika Pertanian CogITo Smart Journal Inovasi : Jurnal Ekonomi, Keuangan, dan Manajemen Indonesian Journal of Artificial Intelligence and Data Mining JEPA (Jurnal Ekonomi Pertanian dan Agribisnis) Albacore : Jurnal Penelitian Perikanan Laut BAREKENG: Jurnal Ilmu Matematika dan Terapan JOURNAL OF APPLIED INFORMATICS AND COMPUTING JTAM (Jurnal Teori dan Aplikasi Matematika) Warta Penelitian Perhubungan Jambura Journal of Mathematics Journal of Humanities and Social Studies International Journal of Remote Sensing and Earth Sciences (IJReSES) Aptisi Transactions on Technopreneurship (ATT) STI Policy and Management Journal Jurnal Aplikasi Statistika & Komputasi Statistik TELKA - Telekomunikasi, Elektronika, Komputasi dan Kontrol Jurnal Matematika UNAND Variance : Journal of Statistics and Its Applications Ecces: Economics, Social, and Development Studies International Journal of Zakat (IJAZ) Inferensi InPrime: Indonesian Journal Of Pure And Applied Mathematics International Journal of Science, Engineering and Information Technology Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistika Jurnal Statistika dan Aplikasinya Jurnal Pengabdian Masyarakat Indonesia Euler : Jurnal Ilmiah Matematika, Sains dan Teknologi SRIWIJAYA JOURNAL OF ENVIRONMENT Jurnal Natural Eduvest - Journal of Universal Studies Xplore: Journal of Statistics STATISTIKA IIJSE Jurnal Informatika: Jurnal Pengembangan IT PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON DATA SCIENCE AND OFFICIAL STATISTICS Jurnal Ekonomi dan Pembangunan Indonesia The Indonesian Journal of Computer Science Journal of Mathematics, Computation and Statistics (JMATHCOS) Scientific Contribution Oil and Gas Indonesian Journal of Statistics and Its Applications Diophantine Journal of Mathematics and Its Applications Khazanah Informatika : Jurnal Ilmu Komputer dan Informatika Warta Penelitian Perhubungan The International Journal of Remote Sensing and Earth Sciences (IJReSES) Teknobuga : Jurnal Teknologi Busana dan Boga

Bagus Sartono

Departmen Statistika Institut Pertanian Bogor Gedung IPB Dramaga, Jl. Meranti Wing 22 Lantai 2 Kampus IPB Darmaga Bogor (16680) Indonesia Phone: +62-811-118-508

Author-ID : 373849

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Penggerombolan Desa di Jawa Barat Berdasarkan Daerah Rawan Bencana Defri Ramadhan Ismana; Seta Baehera; Anwar Fitrianto; Bagus Sartono; Sachnaz Desta Oktarina
Jurnal Statistika dan Aplikasinya Vol 6 No 2 (2022): Jurnal Statistika dan Aplikasinya
Publisher : Program Studi Statistika FMIPA UNJ

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21009/JSA.06210

Indonesia is one of the countries that has a large potential for natural disasters. Indonesia's position at the confluence of 4 continental plates makes the potential for earthquakes even greater. The tropical climate with 2 seasons makes changes in weather, temperature and wind direction quite extreme. These climatic conditions combined with the relatively diverse surface and rock topography conditions, these conditions can cause several bad consequences for the community such as hydrometeorological disasters such as floods, landslides, forest fires, and droughts. Particularly in West Java province, natural disasters that have occurred include: landslides, droughts, cyclones/typhoons, tidal waves, fires, volcanic eruptions, tsunamis, and other disasters. The purpose of this study was to cluster villages in the West Java region based on the level of disaster-prone in 2018. The research was carried out using K-Prototypes clustering and testing evaluation using the silhouette coefficient. The results showed that the optimal number of clusters in this study was nine clusters. These clusters can be distinguished based on the disaster category and the characteristics of the area.

Analisis Karakteristik Keberadaan Perbankan di Nusa Tenggara Barat Terhadap Kondisi Perekonomian Daerah Menggunakan K-Means Clustering Anisa Nurizki; Muhammad Irfan Hanifiandi Kurnia; Anwar Fitrianto; Bagus Sartono; Sachnaz Desta Oktarina; Dian Handayani
Jurnal Statistika dan Aplikasinya Vol 6 No 2 (2022): Jurnal Statistika dan Aplikasinya
Publisher : Program Studi Statistika FMIPA UNJ

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21009/JSA.06211

In certain areas, there are still many people who have to travel long distances to access some banks. Difficult mobility is considered to hinder business activities. The West Nusa Tenggara (NTB) Province is one of the favorite travel destinations for some foreigner tourists as well as domestic tourists because of its natural beauty and cultural diversity. the existence of some banks in the NTB Province , is important to facilitate the circulation of money. For this reason, this study aims to analyze the existence of some banks in the NTB Province and the condition of mobility in accessing themto regional economic conditions by applying K-Means clustering. Our results show that there are two clusters, , where the cluster 2 is an urban area and a tourist area. It has charactersitic has a GDP greater than cluster 1.

Regency Clusterization Based on Village Characteristics to Increase the Human Development Index (IPM) in Papua Province Rais; Amir Abduljabbar Dalimunthe; Anwar Fitrianto; Bagus Sartono; Sachnaz Desta Oktarina
Jurnal Ekonomi Pembangunan Vol. 20 No. 02 (2022): Jurnal Ekonomi Pembangunan
Publisher : Pusat Pengkajian Ekonomi dan Kebijakan Publik

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/jep.v21i02.22911

Inequality in the Human Development Index (IPM) in Papua Province amid the disbursement of development funds needs to be studied adequately so that the policies and programs that have been planned can be more directed and on target. For this reason, research is needed that can map the priority needs of each district in Papua Province by identifying regional characteristics, namely villages. By using Cluster Analysis and Factor Analysis, the results of this research show that 4 district clusters in Papua Province were formed with different priority focuses on increasing the HDI. The main focus of the district HDI improvement priorities in Papua Province is divided into three through factor analysis: the infrastructure-telecommunication factor, the sanitation-economic factor, and the health-education factor. Each cluster is generally still dominated by districts with a low HDI category. The main obstacle to increasing HDI in Papua Province is the transportation and telecommunications infrastructure factor. Local governments are expected to be able to formulate human development programs and policies concerning the priority needs of each district as a result of this research.

Analysis of factors affecting car purchasing decision Bagus Randhyartha Gumilar; Ujang Sumarwan; Bagus Sartono
INOVASI Vol 16, No 1 (2020): Mei
Publisher : Faculty of Economics and Business Mulawarman University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30872/jinv.v16i1.7289

The sales of Mitsubishi Xpander have successfully penetrated the Low MPV car market after 13 years won by its competitors in first-year sales of 2017. The purpose of this study is to analyze the characteristics of Mitsubishi Xpander consumers, the effects of the marketing mix and brand awareness on purchasing decisions, and strategies to increase purchasing decisions. Primary data were obtained from 300 respondents who had bought a Mitsubishi Xpander. Furthermore, the data were analyzed by using the SEM method. The results show the price, product, and location positively and significantly influenced purchasing decisions. Promotion and brand awareness variables have positive but not significant influences on purchasing decisions. The company needs to evaluate the price range of the product, maintain quality, and increase dealer location points on Google Maps. In addition, companies can conduct promotional and branding activities adjusted to the middle-class consumer segment.

Implementation of Winsorizing and random oversampling on data containing outliers and unbalanced data with the random forest classification method FAHREZAL ZUBEDI; BAGUS SARTONO; KHAIRIL ANWAR NOTODIPUTRO
Jurnal Natural Volume 22 Number 2, June 2022
Publisher : Universitas Syiah Kuala

Many researchers conduct research using the classification method, to find out the best method for predicting the class of an observation. Some of these studies explain that random forest is the best method. However, the classification of data containing outliers and unbalanced data is a complicated problem. Many researchers are also conducting research to deal with these problems. In this study, we propose a winsorizing to deal with outliers by replacing the outlier values with the upper and lower limit values obtained from the interquartile range method and random oversampling to balance the data. It is also known that cases of the Human Development Index (HDI) in regencies/cities in eastern Indonesia vary widely, so cases of HDI in these areas can be used as case studies of data containing outliers and unbalanced data. The purpose of this study was to compare the performance of the random forest before and after the data were applied to the winsorizing and random oversampling to predict HDI in districts/cities in eastern Indonesia. Classification method random forest after handling data containing outliers and unbalanced data has better performance in terms of accuracy and kappa values, which are 96.43% and 93.41%, respectively. The variables of expenditure per capita and the mean years of schooling are the most important.

A generalized linear mixed model for understanding determinant factors of student's interest in pursuing bachelor's degree at Universitas Syiah Kuala ASEP RUSYANA; KHAIRIL ANWAR NOTODIPUTRO; BAGUS SARTONO
Jurnal Natural Volume 21 Number 2, June 2021
Publisher : Universitas Syiah Kuala

Generalized Linear Mixed Model (GLMM) is a framework that has a response variable, fixed effects, and random effects. The response variable comes from an exponential family, whereas random effects have a normal distribution. Estimating parameters can be calculated using the maximum likelihood method using the Laplace approach or the Gauss-Hermite Quadrature (GHQ) approach. The purpose of this study was to identify factors that trigger student's interest to continue studying at Universitas Syiah Kuala (USK) using both techniques. The GLMM is suitable for the data because the variable response has a Bernoulli distribution, and the random effects are assumed to be having a normal distribution. Also, the model helps identify the relationship between the dependent variable and the predictors. This study utilizes data from six high schools in Banda Aceh city drawn using a two-stage sampling technique. Stage 1, we randomly chose six out of sixteen public senior high schools in Banda Aceh. Stage 2, we selected students from each school from four different major classes. The GLMM model includes one binary response variable, five numerical fixed-effects, and two random effects. The response variable is the interest of high school students to continue study at USK (yes or no). The five fixed effects in the model including scores of collaboration (C), Action (A), Emotion (E), Purposes (P), and Hope (H). Finally, the random effects are schools (S) and majors (M). In this study, both Laplace and GHQ techniques produce identical results. The predictors that can explain student interest are A, E, and H. These predictors have a positive effect. The random effects of schools and majors are not significantly different from zero. The model with three significant predictors is better than the complete predictor model.

Study on the performance of Robust LASSO in determining important variables data with outliers ROCHYATI ROCHYATI; KUSMAN SADIK; BAGUS SARTONO; EVITA PURNANINGRUM
Jurnal Natural Volume 23 Number 1, February 2023
Publisher : Universitas Syiah Kuala

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24815/jn.v23i1.26279

A variable selection method is required to deal with regression models with many variables, and LASSO has been the most widely used methodology. However, as several authors have noted, LASSO is sensitive to outliers in the data. For this reason, the Robust-LASSO approach was introduced by applying some weighting schemes for each sample in the data. This research presented a comparative study of the three weighting schemes in Robust LASSO, namely Huber-LASSO, Tukey-LASSO, and Welsch-LASSO. The study did a rich simulation containing many scenarios with various characteristics on the covariance structures of the explanatory variable, the types of outliers, the number of outliers, the location of active variables, and the number of variables. The study then found that Tukey-LASSO outperformed Huber-LASSO and Welsch-LASSO in identifying significant variables. The Robust LASSO performance generally decreased as the covariances among explanatory variables increased and the data dimension increased. Exploration of sembung leaf extract data shows that the data is high dimensional data which contains outliers of about 14,28% on the response variable and about 25,71% on the explanatory variables. Based on the research, the number of variables selected using the Tukey-LASSO method was nine compounds, Huber-LASSO and Welsch-LASSO were eight compounds, and LASSO 13 compounds. The Tukey-LASSO prediction accuracy is superior to the other three methods.

CLASSIFICATION OF RICE-PLANT GROWTH PHASE USING SUPERVISED RANDOM FOREST METHOD BASED ON LANDSAT-8 MULTITEMPORAL DATA Triscowati, Dwi Wahyu; Sartono, Bagus; Kurnia, Anang; Dirgahayu, Dede; Wijayanto, Arie Wahyu
International Journal of Remote Sensing and Earth Sciences (IJReSES) Vol 16, No 2 (2019)
Publisher : National Institute of Aeronautics and Space of Indonesia (LAPAN)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/j.ijreses.2019.v16.a3217

Data on rice production is crucial for planning and monitoring national food security in a developing country such as Indonesia, and the classification of the growth phases of rice plants is important for supporting this data. In contrast to conventional field surveys, remote sensing technology such as Landsat-8 satellite imagery offers more scalable, inexpensive and real-time solutions. However, utilising Landsat-8 for classification of rice-plant phase required spectral pattern information from one season, because these spectral patterns show the existence of temporal autocorrelation among features. The aim of this study is to propose a supervised random forest method for developing a classification model of rice-plant phase which can handle the temporal autocorrelation existing among features. A random forest is a machine learning method that is insensitive to multicollinearity, and so by using a random forest we can make features engineering to select the best multitemporal features for the classification model. The experimental results deliver accuracy of 0.236 if we use one temporal feature of vegetation index; if we use more temporal features, the accuracy increases to 0.7091. In this study, we show that the existence of temporal autocorrelation must be captured in the model to improve classification accuracy.

The Impact of Oil Price Shocks on Stock Market Returns in Each Regime using Vector Autoregressive Method Wahida Ainun Mumtaza; Asep Saefuddin; Bagus Sartono
Xplore: Journal of Statistics Vol. 8 No. 1 (2019): 30 April 2019
Publisher : Department of Statistics, IPB

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/xplore.v8i1.126

World oil prices affect the stock market in developed and developing countries, including Indonesia. Therefore, development of the Indonesian economy is affected by the shocks of world oil prices and the stock market. This study characterized the impact and causal relationship between oil price shocks and stock market in Indonesia from 1996 to 2016. In this research, there are nine sectors of the stock market, there are sector agriculture, basic, consumer, finance, infrastructure, mining, miscellaneous industry, property, and trade. To analyze the impact of oil price shocks to Indonesia stock market, we employed an autoregressive vector model (VAR) methodology involving different lags for each regime. We examined that the dynamic relationship between changes in oil prices and stock market in Indonesia in each regime varied which was indicated by impulse response and variance decomposition value. The Granger Causality test found that there were one-way relationship between oil variable with infrastructure sector variable, oil variable with agricultural sector variable and oil variable with basic sector variable in Regime 2, Regime 3 there was one way relationship significantly between oil variable with infrastructure sector variable and Regime 4 also there were one-way relationship. One-way relationship significantly between oil variable with property sector variable, but not significant in Regime 1.

Identifikasi Cepat Segmentasi Konsumen Susu Cair dalam Kemasan Fadhila Hijryani; Bagus Sartono; Utami Dyah Syafitri
Xplore: Journal of Statistics Vol. 7 No. 3 (2018): 31 Desember 2018
Publisher : Department of Statistics, IPB

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/xplore.v7i3.128

Consumer segmentation is the process of grouping customers into some segments based on some shared similar characteristics. Consumer segmentation allows companies to understand the customer's characteristics in each segment, thus make them easier to establish suitable marketing strategies for each segment's characteristics.Companies tend to use marketing strategies with demographical and consumer behavioural based scheme of consumer segmentation therefore make them easier to identify customer as the characteristics are easily measured. This research uses k-means method for segmenting 419 customers of packaged liquid milk. The life style pattern of the customers are used as the basis of the segmentation. Furthermore, this research uses decision tree algorithm to classify characteristics of the new customer. According to Hartigan index alteration (26.2433), ideal number of segments is 4. After tree pruning step, classification modelling with CART method yielded 54.61% accuracy.

Co-Authors -, Salsabila Aam Alamudi Abdul Aziz Nurussadad Achmad Fauzan Achsani, Noer Azham Adi Hadianto Adinna Astrianti Afendi, Farit M Agus M Soleh Agus M Soleh Agus M. Sholeh Agus Mohamad Soleh Agusta, Madania Tetiani Agwil, Winalia Aji Hamim Wigena Akbar Rizki Akhilla, Kharismatul Zaenab Alfa Nugraha Pradana ALFIAN FUTUHUL HADI Alifviansyah, Kevin Alona Dwinata Alwinie, Ade Agusti Amanda, Nabila Tri Amatullah, Fida Fariha Amin, Toufiq Al Amir Abduljabbar Dalimunthe Anang Kurnia Andi Susanto Andrie Agustino Anggraeni, Kartika Novira Anggraini Sukmawati Ani Safitri Anik Djuraidah Anisa Nurizki Annisa Permata Sari, Annisa Permata Annissa Nur Fitria Fathina Anton Ferdiansyah Anwar Fajar Rizki Ardhani, Rizky Ardiansyah, Muhlis Arief Daryanto Arief Daryanto Arief Gusnanto Aris Yaman Aris Yaman Aristawidya, Rafika Aruddy Aruddy Asep Rusyana ASEP SAEFUDDIN Asfar Asrirawan, Asrirawan Aulia Rizki Firdawanti Aunuddin Aunuddin Auzi Asfarian Azlam Nas Bagus Randhyartha Gumilar Bariq, Muhammad Shidqi Abdul Barokaturrizkia Ameliani Bayu Indrayana Bayu Pranata, Bayu Bayu Suseno Beny Mulyana Sukandar Billy Bimandra Adiputra Djaafara Bonar Marulitua Sinaga Budi Susetyo Bukhari, Ari Shobri Cahya, Septa Dwi Carlya Agmis Aimandiga Cici Suhaeni Cici Suhaeni Cici Suhaeni Cintari, Nanda Putri Citra, Reza Felix Dani Al Mahkya Darwis Darwis Dede Dirgahayu Dede Dirgahayu Defri Ramadhan Ismana Deiby T Salaki Deni Achmad Soeboer Deri Siswara Dessy Rotua Natalina Siahaan Dewi Margareth Lumbantoruan Dhanu Dian Ayuningtyas Dian Handayani Dian Kusumaningrum Dito, Gerry Alfa Dwi Agustin Nuriani Sirodj Dwi Fitrianti Dwi Wahyu Triscowati Eko Ruddy Cahyadi Embay Rohaeti Erfiani Erfiani Erliza Noor Erwan Setiawan, Erwan Etis Sunandi EVI RAMADHANI EVITA PURNANINGRUM Fachry Abda El Rahman Fadhila Hijryani FAHREZAL ZUBEDI Fany Apriliani Faqih Udin dan Jono M. Munandar Meivita Amelia Farit M. Afendi Farit Mochamad Afendi Fauzi, Fatkhurokhman Ferdiansyah, Anton Ferdiansyah, Anton Fitri Mudia Sari Fitrianto, Anwar Frisca Rizki Ananda Galih Hedy Saputra Gerry Alfa Dito Ghiffary, Ghardapaty Ghaly Ginting, Victor Gumilar, Bagus Randhyartha Gustara, Muhammad Hanum Rachmawati Nur Hardiana Widyastuti Hari Wijayanto Hari Yanni, Meri Harianto Harianto Hartoyo Hartoyo Hartoyo Hazan Azhari Zainuddin Hendri Wijaya Hendria, Muhammad Herlin Fransiska Herlina Herlina Hidayat, Agus Sofian Eka Hidayat, Muhammad Hilman Dwi Anggana I Made Sumertajaya I Wayan Mangku Idqan Fahmi Ilma, Hafizah Ilma, Meisyatul Ilmani, Erdanisa Aghnia Iman, Mutiara Nurul INA YATUL ULYA Indahwati Indonesian Journal of Statistics and Its Applications IJSA Intan Arassah, Fradha Irene Muflikh Nadhiroh Irfan Syauqi Beik Ismah, Ismah Ita Wulandari Itasia Dina Sulvianti Iwan Kurniawan Jaelani, Raditya Kamila, Sabrina Adnin Khairil Anwar Notodiputro Khairunnajah Khairunnajah Khairunnisa, Adlina Khikmah, Khusnia Nurul Kudang Boro Seminar Kusman Sadik Kusnaeni Kusnaeni, Kusnaeni La Surimi, La Laode Ahmad Sabil Leni Anggraini Susanti Lilik Noor Yuliati Linda Karlina Sari Luky Adrianto Lukytawati Anggraeni M. Yunus Magfirrah, Indah Matualage, Dariani Megawati - Megawati Simanjuntak Meylisah, Eni Mohamad Agus Setiawan Muhammad Hendria Muhammad Ilham Abidin Muhammad Irfan Hanifiandi Kurnia Muhammad Nur Aidi Muhammad Subianto Muhammad Syafiq Muhammad Yusran Mukhamad Najib Murpraptomo, Saka Haditya Musthafa, Hafiz Syaikhul MY, Hadyanti Utami Nofrida Elly Zendrato Novian Tamara Nugraha, Adhiyatma Nur Aulia NUR HASANAH NURADILLA, SITI Nurfadilah, Khalilah Oktaviani, Rina Pardomuan Robinson Sihombing Parwati Sofan, Parwati Pika Silvianti Popong Nurhayati Pratiwi, Windy Ayu Purnaningrum, Evita Purwanto, Arie Puspanegara, Ladia Puspita, Novi Qalbi, Asyifah Rachma Fitriati Rahardi, Naufal Rahardiantoro, Septian Rahma Anisa Rahma Anisa Rahma Dany Asyifa Rahman, Gusti Arviana Rahmatulloh, Febriandi Rais Rere Kautsar Rhendy K P Widiyanto Riantika, Ines Rina Oktaviani Rini, Dyah Setyo Riska Yulianti, Riska Riza Indriani Rakhmalia Rizal Bakri Rizka Rahmaida Rizqi, Tasya Anisah ROCHYATI ROCHYATI Roy Sembel Sachnaz Desta Oktarina salsa bila Saptowulan Sarah Putri Sari, Jefita Resti Sentana Putra, I Gusti Ngurah Seta Baehera Setiadi Djohar Setyowati, Silfiana Lis Sholeh, Agus M. Siregar, Indra Rivaldi Siskarossa Ika Oktora Sofia, Ayu Sri Amaliya Suantari, Ni Gusti Ayu Putu Puteri Suhaeni, Cici Sukarna Sukarna Suprayogi, Muhammad Azis Susanto, Andi Suseno Bayu Syam, Ummul Auliyah Syarip, Dodi Irawan Totong Martono Toufiq Al Amin Toufiq Al Amin Triscowati, Dwi Wahyu Tsabitah, Dhiya Ulayya Tsaqif, Denanda Aufadlan Ujang Sumarwan Ulfia, Ratu Risha Utami Dyah Syafitri Valentika, Nina Vera Maya Santi Wahida Ainun Mumtaza Wahyudi Setyo Wahyuni, Silvia Tri Waliulu, Megawati Zein Wawan Saputra Yanuari, Eka Dicky Darmawan Yenni Angraini Yoga Primanda Yopi Ariesia Ulfa Yudhianto, Rachmat Bintang Yuliani, Leny Zahra, Latifah Zaima Nurrusydah

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