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All Journal Jurnal Ilmu Pertanian Indonesia Jurnal Manajemen dan Agribisnis FORUM STATISTIKA DAN KOMPUTASI Jurnal Ekonomi Pembangunan Indonesian Journal of Geography IJCCS (Indonesian Journal of Computing and Cybernetics Systems) 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 JUITA : Jurnal Informatika Jurnal Aplikasi Bisnis dan Manajemen (JABM) E-Journal Scientific Journal of Informatics Journal of Consumer Science CESS (Journal of Computer Engineering, System and 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 Asia-Pacific Management and Business Application Knowledge Engineering and Data Science MAJALAH ILMIAH GLOBE 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 Jurnal Organisasi Dan Manajemen JOURNAL OF APPLIED INFORMATICS AND COMPUTING JTAM (Jurnal Teori dan Aplikasi Matematika) 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 Administrasi dan Manajemen Jurnal Matematika UNAND Variance : Journal of Statistics and Its Applications Ecces: Economics, Social, and Development Studies International Journal of Zakat (IJAZ) Indonesian Journal of Electrical Engineering and Computer Science 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 Dinasti International Journal of Economics, Finance & Accounting (DIJEFA) Euler : Jurnal Ilmiah Matematika, Sains dan Teknologi SRIWIJAYA JOURNAL OF ENVIRONMENT Jurnal Natural Xplore: Journal of Statistics STATISTIKA 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) Journal of International Accounting, Taxation and Information Systems 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 Scientific Contributions Oil and Gas
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
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Meta-stacking models for electricity load forecasting in West Java Denanda Aufadlan Tsaqif; Bagus Sartono; Hari Wijayanto
Indonesian Journal of Electrical Engineering and Computer Science Vol 42, No 2: May 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v42.i2.pp442-453

Abstract

Indonesia’s electricity demand continues to increase due to population growth, urbanization, and industrial expansion, therefore making accurate load forecasting is essential to maintain supply-demand balance. However, electrical load demand in West Java has a complex pattern (seasonality, nonlinear behavior, weather variability, and holiday effects), which motivates the use of a meta-stacking approach to effectively capture such complexity. Previous research shows that meta-stacking outperforms individual models, but it fails to capture sudden changes and its performance consistency remains unclear. Therefore, this study proposes a meta-stacking framework for daily electricity load forecasting in West Java (2006-2023) that includes weather and holiday variables by combining CNN-BiLSTM, CNN-BiGRU, and Windowed-XGBoost forecasts through linear regression and evaluates its performance across five data-splitting scenarios and nine forecast horizons, which represents the main novelty in this research. Meta stacking shows strong generalization across scenarios and strong long-term forecasting performance across horizons, while consistently providing a balanced trade-off between MAPE and trend accuracy, where the model trained on the longest historical dataset achieves the best performance with 1.89% MAPE and 86% trend accuracy. The proposed approach successfully captures seasonal and holiday-related load patterns, indicating its potential to support PLN in improving demand planning and operational decision making.
Performance Analysis of Tree-Based Models for Classifying Complete Basic Childhood Immunization in West Java Windi Pangesti; Mega Maulina; Hazelita Dwi Rahmasari; Bagus Sartono; Budi Susetyo; Aulia Rizki Firdawanti; Gerry Alfa Dito
Inferensi Vol 9 No 1 (2026)
Publisher : Department of Statistics ITS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j27213862.v9i1.9167

Abstract

Complete basic immunization is a key public health indicator, and disparities in coverage remain a major concern in West Java. The 2024 Universal Child Immunization (UCI) rate in West Java reached only 77.47%, declining from 2023 and reflecting persistent disparities in access to immunization services, particularly between urban and rural areas. This study aims to identify the determinants of complete basic immunization among children in West Java using SUSENAS 2024 survey data (n = 4,672). Three tree- based classification algorithms CART, Random Forest, and LightGBM were applied, with class imbalance addressed using SMOTE, Tomek Links, and the SMOTE–Tomek Links hybrid method. Model performance was evaluated using balanced accuracy. The Random Forest model combined with SMOTE achieved the highest performance, with a balanced accuracy of 60.3% and an overall accuracy of 70.3%. This model also demonstrated superior capability in identifying children with incomplete immunization. Global feature importance results indicate that household spending category, KIA book ownership, maternal age at first birth, and maternal education are the strongest predictors of complete basic immunization. SHAP analysis reveals contrasting patterns: knowledge- based factors dominate in urban areas, while structural and socioeconomic constraints are more influential in rural areas. These findings underscore the importance of geographically targeted immunization strategies to support equitable access across urban and rural communities in West Java.
CART and Random Forest Analysis on Graduation Status of Halu Oleo University Students Gusti Arviana Rahman; Khairil Anwar Notodiputro; Bagus Sartono; La Surimi
Inferensi Vol 8 No 3 (2025)
Publisher : Department of Statistics ITS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j27213862.v8i3.23336

Abstract

Classification and Regression Tree (CART) is a popular classification method and it is used in various fields. The method is capable to be applied on various data conditions. An alternative method of CART is random forest. These two methods of classification were studied in this paper using graduation data of Halu Oleo University. This data was interesting due to the imbalance problem existed in the data. We compared several scenarios, namely the CART and Random Forest methods, Random Forest with oversampling, and Random Forest with undersampling. There were three explanatory variables considered in the model including Study Program, GPA, and TOEFL score. The results showed that the best method to classify the student’s graduation status at Halu Oleo University is Random Forest without handling imbalanced data, as it provided the highest sensitivity. This suggests that Random Forest, even without specific adjustments for data imbalance, can effectively capture the patterns in the data and provide accurate classifications, making it a robust choice for this dataset.
Identification of Earthquake Prone Zones in Sumatra using Density Based Spatial Clustering of Applications with Noise Dwi Agustin Nuriani Sirodj; Muhammad Nur Aidi; Bagus Sartono; Utami Dyah Syafitri; Bayu Pranata
CAUCHY: Jurnal Matematika Murni dan Aplikasi Vol 10, No 2 (2025): CAUCHY: JURNAL MATEMATIKA MURNI DAN APLIKASI
Publisher : Mathematics Department, Maulana Malik Ibrahim State Islamic University of Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18860/cauchy.v10i2.36120

Abstract

This study investigates the spatial distribution of earthquakes in Sumatra using the DBSCAN clustering algorithm applied to seismic data spanning 1 January 2000 to 31 December 2023. The analysis identified two distinct seismic clusters: one in the northern region (Aceh and North Sumatra) and another in the southern region (Lampung, Bengkulu, and West Sumatra), while several events in central areas were classified as noise. Cluster validity assessment confirmed that the identified groups are compact and well separated, reflecting meaningful seismotectonic segmentation. Statistical testing further revealed significant differences in earthquake depth and magnitude between the clusters, supporting the robustness of the findings. Notably, the southern cluster corresponds to the Mentawai Fault system, whereas the northern cluster aligns with the subduction zone and the Sumatran Fault. DBSCAN proved particularly effective in this context as it can capture clusters of arbitrary shapes, consistent with the complex geological structures governing seismicity in Sumatra.
Evaluasi Perbandingan Model XGBoost, Random Forest, LightGBM, dan Artificial Neural Network dalam Klasifikasi Kerawanan Pangan Mardatunnisa Isnaini; Dela Gustiara; Rizqi Annafi Muhadi; Shalshabilla Shafa; Bagus Sartono; Aulia Rizki Firdawanti; Budi Susetyo; Gerry Alfa Dito
Euler : Jurnal Ilmiah Matematika, Sains dan Teknologi Volume 14 Issue 1 April 2026
Publisher : Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/euler.v14i1.36227

Abstract

Food insecurity remains a serious household-level issue, particularly in densely populated regions such as West Java, highlighting the need for analytical approaches capable of accurately identifying vulnerable groups. Machine learning algorithms offer the potential to improve the accuracy and precision of food insecurity classification based on survey data. This study aims to compare the predictive performance and variable importance identification of four machine learning algorithms—Random Forest, Light Gradient Boosting Machine (LightGBM), Extreme Gradient Boosting (XGBoost), and Artificial Neural Network (ANN)—in predicting household food insecurity status. The analysis employs SUSENAS 2023 data covering 26,012 households with 14 predictor variables, and food insecurity is classified using the Food Insecurity Experience Scale (FIES). Class imbalance is addressed using the Synthetic Minority Over-sampling Technique (SMOTE) within a 10-fold cross-validation framework. The results show that XGBoost achieves the highest accuracy of 71%, while Random Forest provides the best balanced accuracy under the SMOTE scenario. Moreover, all algorithms consistently identify the Wealth Index as the most influential predictor based on their respective Variable Importance measures, followed by variables related to water access and food assistance. Accordingly, XGBoost is recommended in terms of accuracy, whereas Random Forest demonstrates superior balanced accuracy and prediction stability.
IndoBERT Optimization for Sentiment Analysis on DeepSeek App Reviews Muh. Sunan; Unique Desyrre A. Resiloy; Desy Endriani; Cici Suhaeni; Bagus Sartono; Gerry Alfa Dito
IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Vol 20, No 1 (2026): January
Publisher : IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijccs.107507

Abstract

In the digital era, sentiment analysis is important to evaluate public opinion, especially in the context of Play Store apps with Indonesian-language reviews. This research aims to improve the performance of the IndoBERT model in sentiment analysis of DeepSeek app reviews by using data augmentation and hyperparameter tuning techniques. Data augmentation is done through the back-translation technique, while the hyperparameters tested include the number of epochs, learning rate, and batch size. Experimental results show that the combination of data augmentation with epoch 10, learning rate 2e-5, and batch size 16 produces the highest accuracy of 93.95% and F1-score of 0.94, with better stability than the model without augmentation. The model without augmentation showed fluctuations in performance, indicating overfitting in some configurations. These findings confirm the importance of applying augmentation techniques and hyperparameter tuning in improving the accuracy and stability of sentiment analysis models, and contribute to the development of NLP models for Indonesian and other resource-constrained languages.
The Influence of Marketing Mix, Perceived Risk, and Satisfaction on Word of Mouth in XYZ Clinic Saka Haditya Murpraptomo; Lilik Noor Yuliati; Bagus Sartono
Journal of Consumer Sciences Vol. 4 No. 1 (2019): Journal of Consumer Sciences
Publisher : Department of Family and Consumer Sciences, Faculty of Social and Human Ecology, IPB University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/jcs.4.1.13-24

Abstract

The increasing need for health services, peoples who lived in the Pekayon, Bekasi City were given the opportunity to choose the right clinic. Word of mouth is a marketing technique that can be used by clinics. This study aims to analyze the effects of the marketing mix, perceived risk, and satisfaction on word of mouth at XYZ clinic. The research is a descriptive method with a survey using questionnaires and 200 respondents as the sample. Furthermore, the data analysis technique is descriptive with SPSS16.0 software and Structural Equation Model (SEM) with LISREL 8.70. Based on the results, it can be concluded that the marketing mix has a positive effect on perceived risk, marketing mix has a positive effect on satisfaction, perceived risk has a negative effect on satisfaction, marketing mix has a positive effect on word of mouth, perceived risk has a negative effect on word of mouth, and satisfaction has a positive effect on word of mouth. Referring to these conclusions, it can be confirmed that the clinical management of doctor XYZ needs to improve employee services, convenience the patient that this clinic has expert doctors, and utilizing the use of social media as a marketing strategy.
The Role of 7P Marketing Mix toward Consumer Satisfaction and Loyalty of XYZ Beauty Clinic Ade Agusti Alwinie; Popong Nurhayati; Bagus Sartono
Journal of Consumer Sciences Vol. 9 No. 1 (2024): Journal of Consumer Sciences
Publisher : Department of Family and Consumer Sciences, Faculty of Social and Human Ecology, IPB University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/jcs.9.1.40-62

Abstract

The XYZ Beauty Clinic has many branches throughout Indonesia, including the Metropolitan Mall (MM) Bekasi branch, which has been established since 2011. Over time, the XYZ MM Clinic has faced various challenges, such as a decrease in the frequency of customer visits. This study aims to analyze consumer perceptions, factors that affect consumer satisfaction and loyalty, and the level of satisfaction and loyalty of XYZ Beauty Clinic consumers. The study used a cross-sectional design. The sampling technique used purposive sampling involving 152 respondents who were at least 17 years old and had visited at least twice in the last year. Data were processed quantitatively using SEM-PLS, Customer Satisfaction Index (CSI), and Customer Loyalty Index (CLI) to test the hypotheses and measure the level of consumer satisfaction and loyalty. The results indicated that consumer perception with low satisfaction and low loyalty are consumers who work as entrepreneurs, consumers who earn less than 5 million a month, as well as consumers who live in Tangerang and Bogor. The marketing mix that affects consumer satisfaction includes product, promotion, process, people, and physical evidence. Customer satisfaction affects customer loyalty. The level of customer satisfaction shows satisfactory results and the level of customer loyalty shows loyal results. Based on the research results, clinics are advised to prioritize consumer groups with low perceptions of satisfaction
AN APPLICATION OF GENETIC ALGORITHM FOR CLUSTERING OBSERVATIONS WITH INCOMPLETE DATA Frisca Rizki Ananda; Asep Saefuddin; Bagus Sartono
Indonesian Journal of Statistics and Applications Vol 1 No 1 (2017)
Publisher : Statistics and Data Science Program Study, SSMI, IPB University, in collaboration with the Forum Pendidikan Tinggi Statistika Indonesia (FORSTAT) and the Ikatan Statistisi Indonesia (ISI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/ijsa.v1i1.48

Abstract

Cluster analysis is a method to classify observations into several clusters. A common strategy for clustering the observations uses distance as a similarity index. However distance approach cannot be applied when data is not complete. Genetic Algorithm is applied by involving variance (GACV) in order to solve this problem. This study employed GACV on Iris data that was introduced by Sir Ronald Fisher. Clustering the incomplete data was implemented on data which was produced by deleting some values of Iris data. The algorithm was developed under R 3.0.2 software and got satisfying result for clustering complete data with 95.99% sensitivity and 98% consistency. GACV could be applied to cluster observations with missing value without filling in the missing value or excluding these observations. Performance on clustering incomplete observations is also satisfying but tends to decrease as the proportion of incomplete values increases. The proportion of incomplete values should be less than or equal to 40% to get sensitivity and consistency not less than 90. Keywords: Cluster Analysis, Genetic Algorithm, Incomplete Data.
PENGGUNAAN SUPPORT VECTOR REGRESSION DALAM PEMODELAN INDEKS SAHAM SYARIAH INDONESIA DENGAN ALGORITME GRID SEARCH Galih Hedy Saputra; Aji Hamim Wigena; Bagus Sartono
Indonesian Journal of Statistics and Applications Vol 3 No 2 (2019)
Publisher : Statistics and Data Science Program Study, SSMI, IPB University, in collaboration with the Forum Pendidikan Tinggi Statistika Indonesia (FORSTAT) and the Ikatan Statistisi Indonesia (ISI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/ijsa.v3i2.172

Abstract

Indonesia as the largest Muslim population country in the world is a very potential market for sharia stocks. Sharia stocks performance can be seen from the Indonesia Sharia Stock Index (ISSI). Stock index modeling is conducted to determine the factors that affect the stock index or to predict the value of the stock index. Modeling using regression analysis is based on assumptions that do not always match with the characteristics of stock data that fluctuate. Support Vector Regression (SVR) method is a non-parametric approach based on machine learning. The problem often encountered in the analysis using SVR is to determine the optimal parameters to produce the best model. The determination of the optimal parameters can be solved by using the grid search algorithm. The purpose of this research is to make ISSI model using SVR with grid search algorithm with independent variable BI Rate, money supply, and exchange rate (USD / IDR). The best SVR model was obtained using weekly data with a total of 343 periods as well as a linear kernel with parameters ε = 0.03 and C = 2. The evaluation of the best model SVR is RMSE of 2.289 and correlation value of 0.873.
Co-Authors -, Salsabila Aam Alamudi Abdul Aziz Nurussadad Achmad Fauzan Achmad Fauzan, Achmad Achsani, Noer Azham Ade Agusti Alwinie Adi Hadianto, Adi Adinna Astrianti Afendi, Farit M Agus M Soleh Agus M Soleh Agus M. Sholeh Agus Mohamad Soleh Agusta, Madania Tetiani Agwil, Winalia Ain Fitri Basri Aji Hamim Wigena Akbar Rizki 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 Anggraini Sukmawati Ani Safitri Anik Djuraidah Anisa Nurizki Annisa Permata Sari Annissa Nur Fitria Fathina Anton Ferdiansyah Ardhani, Rizky Ardiansyah, Muhlis Arie Wahyu Wijayanto Arief Daryanto Arief Daryanto Arief Gusnanto Arif Imam Suroso Aris Yaman Aris Yaman Aristawidya, Rafika Aruddy Aruddy Asep Rusyana ASEP SAEFUDDIN Asfar Asrirawan, Asrirawan Aulia Rizki Firdawanti Aulia Rizki Firdawanti Aunuddin Aunuddin Auzi Asfarian Ayu Sofia Azlam Nas Bagus Randhyartha Gumilar Bariq, Muhammad Shidqi Abdul Barokaturrizkia Ameliani Bayu Indrayana Bayu Pranata 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 Claudian Tikulimbong Tangdilomban Dani Al Mahkya Dede Dirgahayu Dede Dirgahayu Defri Ramadhan Ismana Deiby T Salaki Dela Gustiara Denanda Aufadlan Tsaqif Deni Achmad Soeboer Deri Siswara Desi Prabandari Kusuma Ningtyas Desi Prabandari Kusuma Ningtyas Dessy Rotua Natalina Siahaan Desy Endriani Dewi Margareth Lumbantoruan Dhanu Dhanu Saptowulan Dian Ayuningtyas Dian Handayani Dian Kusumaningrum Dito, Gerry Alfa Dwi Agustin Nuriani Sirodj Dwi Agustin Nuriani Sirodj Dwi Erzalianti Dwi Wahyu Triscowati Dyah Setyo Rini 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 Farit M. Afendi Farit Mochamad Afendi Fatiya Hanifah Fauzi, Fatkhurokhman Fauziah, Nadira Aribah 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 Gusti Arviana Rahman Hanum Rachmawati Nur Hari Wijayanto Harianto Harianto Hartoyo Hartoyo Hartoyo Hazan Azhari Zainuddin Hazelita Dwi Rahmasari Hendri Wijaya Hendria, Muhammad Herlin Fransiska Herlina Herlina Hidayat, Agus Sofian Eka Hidayat, Muhammad Hilman Dwi Anggana I Gusti Ngurah Sentana Putra 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 Ines Riantika Irene Muflikh Nadhiroh Irfan Syauqi Beik Ismah, Ismah Itasia Dina Sulvianti Iwan Kurniawan Jaelani, Raditya Joice Junansi Tandirerung Kamila, Sabrina Adnin Kenny Masbagusdanta Khairil Anwar Notodiputro Khairunnajah Khairunnajah Khairunnisa, Adlina Kharismatul Zaenab Akhilla Khikmah, Khusnia Nurul Kinanti Rizky Pangestutik Kudang Boro Seminar Kusman Sadik Kusnaeni Kusnaeni, Kusnaeni La Surimi La Surimi, La Laode Ahmad Sabil Leni Anggraini Susanti Lilik Noor Yuliati Linda Karlina Sari Lisa Amelia Luh Putu Widya Adnyani Luky Adrianto Lukytawati Anggraeni M. Yunus Magfirrah, Indah Mardatunnisa Isnaini Matualage, Dariani Mega Maulina Mega Ramatika Putri Megawati - Megawati Simanjuntak Meri Hari Yanni Meylisah, Eni Mohamad Agus Setiawan Muh. Sunan Muhammad Hendria Muhammad Ilham Abidin Muhammad Irfan Hanifiandi Kurnia Muhammad Nur Aidi Muhammad Rizal Muhammad Subianto Muhammad Syafiq Muhammad Yusran Mukhamad Najib Murpraptomo, Saka Haditya MY, Hadyanti Utami Nimmi Zulbainarni Nisa Nur Aisyah Nofrida Elly Zendrato Novian Tamara Nugraha, Adhiyatma Nur Aulia NUR HASANAH NURADILLA, SITI Nurfadilah, Khalilah Oktaviani, Rina Pardomuan Robinson Sihombing Pika Silvianti Popong Nurhayati Pratiwi, Windy Ayu Purwanto, Arie 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 Rina Oktaviani Riska Yulianti, Riska Riza Indriani Rakhmalia Rizal Bakri Rizka Rahmaida Rizqi Annafi Muhadi Rizqi, Tasya Anisah ROCHYATI ROCHYATI Roy Sembel Rupmana Br Butar Sachnaz Desta Oktarina Saka Haditya Murpraptomo salsa bila Saptowulan Sarah Putri Sari, Jefita Resti Sentana Putra, I Gusti Ngurah Seta Baehera Setiadi Djohar Setyowati, Silfiana Lis Shalshabilla Shafa Sholeh, Agus M. Siregar, Indra Rivaldi Siskarossa Ika Oktora Siti Aisyah Suantari, Ni Gusti Ayu Putu Puteri Suhaeni, Cici Sukarna Sukarna Suprayogi, Muhammad Azis Susanto, Andi Suseno Bayu Syaifullah Yusuf Ramdhan Syam, Ummul Auliyah Syarip, Dodi Irawan Syella Zignora Limba Totong Martono Toufiq Al Amin Toufiq Al Amin Triscowati, Dwi Wahyu Tsabitah, Dhiya Ulayya Ujang Sumarwan Ulfia, Ratu Risha Unique Desyrre A. Resiloy Utami Dyah Syafitri Valentika, Nina Vera Maya Santi Wahida Ainun Mumtaza Wahyudi Setyo Wahyuni, Silvia Tri Waliulu, Megawati Zein Wawan Saputra Widiyanto, Rhendy K P Windi Pangesti Yani Prihantini Hiola Yanuari, Eka Dicky Darmawan Yenni Angraini Yoga Primanda Yopi Ariesia Ulfa Yudhianto, Rachmat Bintang Zahra, Latifah Zaima Nurrusydah Zulhijrah Zulmi, Muhammad Indra