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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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Application of SHAP on CatBoost classification for identification of variabels characterizing food insecurity occurrences in Aceh Province households MUHAMMAD SUBIANTO; INA YATUL ULYA; EVI RAMADHANI; BAGUS SARTONO; ALFIAN FUTUHUL HADI
Jurnal Natural Volume 23 Number 3, October 2023
Publisher : Universitas Syiah Kuala

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24815/jn.v23i3.33548

Abstract

Classification is the process of building a model that can distinguish between different classes of data. The model aims to predict the class of testing data based on patterns or relationships learned from training data. One of the data processing algorithms used to build classification models is Categorical Boosting (CatBoost). However, in general, the resulting models are difficult to interpret. To facilitate the interpretation of complex classification models, methods such as SHAP (SHapley Additive exPlanations) are needed. SHAP is a method to explain individual predictions. SHAP is based on the game theoretically optimal shapley values. In this study, an analysis of important SHAP variables was conducted on the CatBoost classification model to identify variables characterizing occurrences of food insecurity in households. The data used in this study was obtained from the Survei Sosial Ekonomi Nasional (Susenas) in March 2021 in Aceh Province, sourced from the Badan Pusat Statistik (BPS). There are 13,126 observations in the research data. The results from four evaluated classification models on the testing data showed that the best model had accuracy, sensitivity, specificity, and AUC values of 0.703, 0.349, 0.798, and 0.637, respectively. Furthermore, the results of the analysis of important SHAP variables showed that the variables number of household members who smoke ( ), education of the household head ( ), wall types ( ), drinking water source ( ), and decent sanitation ( ) significantly contributed to the occurrences of food insecurity in households in Aceh Province in the year 2021.
Performance of copula and nested error regression models in estimating per capita expenditure of sub-district in Pidie Regency NUR HASANAH; KHAIRIL ANWAR NOTODIPUTRO; BAGUS SARTONO
Jurnal Natural Volume 23 Number 2, June 2023
Publisher : Universitas Syiah Kuala

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24815/jn.v23i2.31095

Abstract

In unit-level small area estimation (SAE), the commonly used nested error regression (NER) model assumes normality which is not always the case. To handle non-normal data, researchers in statistics have developed a novel approach using exchangeable and extendible copula called the multivariate exchangeable copula (MEC) model. This study compares the performance of parametric MEC and NER models in estimating the sub-district average of per capita expenditure (PCE) in Pidie Regency, Aceh Province. This study presents PCE, which has a skewed distribution of the three-parameter skew-normal. The parametric MEC model uses a Gaussian copula from the Elliptical family and an empirical best unbiased prediction (EBUP) estimator. Meanwhile, the NER model uses an empirical best linear unbiased prediction (EBLUP) estimator. The results reveal that at a 95% confidence level, the parametric MEC model outperforms the NER model with a smaller root of mean squared error (RMSE) and provides a more precise estimate of the sub-district average of PCE. This study highlights the importance of considering the parametric MEC model as an alternative method for skewed data in unit-level SAE. The results of this study have the potential to support the achievement of Goal 1 (to end poverty) and Goal 10 (to reduce inequality) of the sustainable development goals (SDGs) by providing average PCE estimates at the sub-district level.
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

Abstract

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.
Studi bibliometrik tentang trend penelitian restrukturisasi organisasi riset menggunakan VOSviewer Nur Aulia; Eko Ruddy Cahyadi; Bagus Sartono
Berkala Ilmu Perpustakaan dan Informasi Vol 19 No 2 (2023): December
Publisher : Perpustakaan Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/bip.v19i2.7073

Abstract

Introduction. The development of organizational restructuring has growth rapidly. The research aims to see and find out the development of research trends on organizational restructuring. It also aims to see opportunities for future research on organizational restructuring, particularlyin public research organizations.Data Collection Methods. The paper used a quantitative bibliometric analysis with the Scopus database for the last 10 years from 2013 to 2022. Data Analysis. Bibliometric data analysis uses co-occurrence to visualize keywords, networks, density, and overlays. The visualization results are presented using VOSviewer software with a comprehensive narrative method. Results and Discussion. The finding showed that the organizational restructuring research has been dominated by the private sector. Meanwhile however, in the public sector, it showed that the health sector played a significant role. The United States became the country that has discussed the topic of organizational restructuring most extensively. In addition, based on keywords, there were four visualization clusters: human, organizational change, organizational culture, and health care organization. Conclusion. Opportunities show for organizational restructuring research at public research institutions. Other approaches need to be explored instead of using bibliometric analysis.
PERBANDINGAN ORDINAL FOREST DAN REGRESI LOGISTIK ORDINAL Yunus, M.; Khairil Anwar Notodiputro; Bagus Sartono
Jurnal Aplikasi Statistika & Komputasi Statistik Vol 15 No 2 (2023): Journal of Statistical Application and Computational Statistics
Publisher : Politeknik Statistika STIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34123/jurnalasks.v15i2.399

Abstract

Terdapat banyak metode yang digunakan untuk mengidentifikasi prediktor penting dan memprediksi nilai dari peubah respons ordinal. Namun saat ini, terdapat metode prediksi untuk peubah respons ordinal yang tidak menggunakan sifat ordinal dari peubah respons tersebut. Penelitian ini menggunakan metode ordinal forest dan sebagai pembanding digunakan juga metode regresi logistik ordinal. Nilai akurasi dan kappa metode ordinal forest pada setiap ulangan (5 ulangan) selalu lebih besar dari pada regresi logistik ordinal. Selanjutnya, nilai akurasi dan kappa setiap kelompok berdasarkan PDRB pada metode ordinal forest selalu lebih besar dari pada regresi logistik ordinal. Sehingga didapatkan metode ordinal forest lebih baik digunakan pada data peringkat status indeks desa membangun Provinsi Maluku Utara tahun 2020.
Performance Study of Prediction Intervals with Random Forest for Poverty Data Analysis Valentika, Nina; Notodiputro, Khairil Anwar; Sartono, Bagus
Jurnal Aplikasi Statistika & Komputasi Statistik Vol 16 No 1 (2024): Jurnal Aplikasi Statistika & Komputasi Statistik
Publisher : Politeknik Statistika STIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34123/jurnalasks.v16i1.542

Abstract

Introduction/Main Objectives: Determine the prediction interval with for analyzing poverty data at the Regency/City level in Indonesia. Background Problems: Poverty will be a topic in various discussion and debates in the future. Novelty: This study’s methods for constructed prediction intervals are LM, Quant, SPI, HDR, and CHDR. This method can improve the prediction interval performance with Random Forests. Research Methods: The method for building forests and obtaining BOP in this study is CART with the LS splitting rule. Finding/Results: The results of this study are that the best method for one replication is HDR with 500 trees. The best method for 100 repetitions is LM. Based on hypothesis testing, there is sufficient evidence to say no difference between the LM, SPI, Quant, HDR, and CHDR methods for 100 replications at a 5% significance level.
Metode Hutan Ordinal untuk Klasifikasi Desa Sesuai dengan Status Indeks Desa Membangun Sirodj, Dwi Agustin Nuriani; Khairil Anwar Notodiputro; Bagus Sartono
Jurnal Aplikasi Statistika & Komputasi Statistik Vol 15 No 2 (2023): Journal of Statistical Application and Computational Statistics
Publisher : Politeknik Statistika STIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34123/jurnalasks.v15i2.547

Abstract

Metode hutan acak merupakan metode klasifikasi berbasis pohon yang cukup populer. Metode ini jika diterapkan pada peubah respon ordinal akan memberikan hasil yang mengubah karakteristik dari data ordinal itu sendiri. Dalam tulisan ini akan dibahas kinerja dari metode hutan ordinal dan hutan ordinal Naïve untuk klasifikasi status berbagai desa sesuai dengan Indeks Desa Membangun (IDM) di kabupatenTasikmalaya dan Indramayu. Hasilnya memperlihatkan bahwa untuk Kabupaten Tasikmalaya kinerja metode hutan ordinal mengungguli kinerja hutan ordinal Naïve dengan rataan akurasi sebesar 73.8% dan rataan nilai kappa sebesar 0.18 sedangkan pada Kabupaten Indramayu kinerja metode hutan ordinal naïve yang justeru mengungguli metode hutan ordinal dengan rataan akurasi sebesar 51.6 % dan rataan nilai kappa sebesar 0.162. Selain itu ditunjukkan pula bahwa peubah yang penting dalam proses klasifikasi status IDM di Kabupaten Tasikmalaya dan Kabupaten Indramayu adalah peubah Jumlah Koperasi dan Jarak terdekat ke rumah sakit.
Investigating The Asymmetric Effect of Food Commodity Price on The Volatility in Indonesia Sari, Linda Karlina; Achsani, Noer Azam; Sartono, Bagus; Anggraeni, Lukytawati
Jurnal Manajemen & Agribisnis Vol. 20 No. 3 (2023): JMA Vol. 20 No. 3, November 2023
Publisher : School of Business, Bogor Agricultural University (SB-IPB)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17358/jma.20.3.440

Abstract

Volatility can be measured, but in fact, there is still frequent debate over the selection of precise measurements in describing volatility. In Indonesia, the commodity market is known for its volatile prices, which can impact the livelihood of farmers, traders, and the wider economy. The existence of possible asymmetry in the behavior of food commodity price volatility in the Indonesian market is not yet known. This paper aims to determine the best model to describe the volatility and to investigates the presence of the asymmetric effect on the volatility of food prices in Indonesia, over the period 2009-2019, on a monthly basis. Modeling of volatility uses the GARCH family model, both symmetric and asymmetric. The results showed that the GARCH asymmetric model produces better performance than the symmetric GARCH. Through the best GARCH asymmetric model, the food commodities used in this study showed a statistically significant asymmetrical effect on volatility. Nevertheless, policymakers and market players need to be aware of the impact of market volatility and implement measures such as real-time price information systems to mitigate its effects. The government can increase food production by providing support to farmers in managing supply efficiency and improving agricultural infrastructure. Keywords: agricultural commodity, asymmetric effect, asymmetric GARCH, modeling volatility
Tata Kelola Digital Layanan Lalu Lintas Jalan Tol di Indonesia: Studi Aplikasi Travoy Jasa Marga Setiawan, Mohamad Agus; Hartoyo; Seminar, Kudang Boro; Sartono, Bagus; Fitriati, Rachma
Matra Pembaruan: Jurnal Inovasi Kebijakan Vol 8 No 1 (2024)
Publisher : Research and Development Agency Ministry of Home Affairs

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21787/mp.8.1.2024.1-16

Abstract

Digital transformation has transformed the governance approach into digital governance, essential in improving performance and service quality in various sectors, including the toll road industry. This article explores the implementation of digital governance in toll road traffic services in Indonesia. The research method uses a qualitative approach with data collection techniques through observation, literature studies, focus group discussions, and in-depth interviews with a study time of six (6) months from September 2023 to February 2024. The study results show that toll road users face various problems in toll road traffic services in Indonesia, such as severe traffic congestion, over-capacity rest areas, dirty toilets, lack of gas station facilities, and lack of information about congestion points and alternative routes. As an Indonesian state-owned enterprise engaged in toll road operations, PT. Jasa Marga Tbk. launched the Travoy application to provide practical solutions for toll road users to get the necessary information services, facilitate the search for rest areas, and reduce congestion by managing traffic distribution. The study results confirm the importance of continued investment in digital technology and effective data processing to ensure the satisfaction and convenience of future toll road users.
MODEL KLASIFIKASI UNTUK PREDIKSI FASE PERTUMBUHAN PADI DENGAN MACHINE LEARNING BERDASARKAN CITRA SATELIT: (Classification Model for Paddy Growth Phase Prediction with Machine Learning Based on Satellite Imagery) Novian Tamara; Aji Hamim Wigena; Bagus Sartono
Majalah Ilmiah Globe Vol. 23 No. 2 (2021): GLOBE Vol 23 No 2 TAHUN 2021
Publisher : Badan Informasi Geospasial

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Padi memegang peranan penting bagi masyarakat Indonesia. Rumah Tangga Usaha Pertanian (RTUP) padi sebesar 64,85% dari RTUP sub sektor tanaman pangan tahun 2018. Data padi yang akurat dapat membantu pemerintah dalam menyusun perencanaan, mengeksekusi program, dan membuat keputusan yang tepat. Tujuan penelitian kami yaitu membangun model klasifikasi untuk prediksi fase pertumbuhan padi sebagai upaya dalam mendukung keakuratan data padi. Pemodelan multi kelas dilakukan dengan teknik machine learning yaitu Random Forest dan Support Vector Machine. Penelitian ini menggunakan citra Landsat-8 dan Sentinel-2 sebagai fitur yang disupervisi oleh data Kerangka Sampling Area (KSA) dari BPS sebagai variabel target. Sebanyak 1239 fitur statistik temporal turunan dari 18 indeks spektral Sentinel-2 dan 15 indeks spektral Landsat-8 diseleksi dengan plot korelasi dan teknik stepwise. Ketidakseimbangan data ditangani dengan teknik sampling SMOTE+TL. Pada klasifikasi tahap 1, performa model dalam memprediksi sawah padi, sawah bukan padi, dan bukan sawah mencapai akurasi 0,95 dan Matthews Correlation Coefficient (MCC) 0,84. Pada klasifikasi tahap 2, performa model dalam memprediksi fase pertumbuhan padi mencapai akurasi 0,87 dan MCC 0,73. Hasil menunjukan kombinasi citra Landsat-8 dan Sentinel-2, seleksi fitur temporal, serta pemilihan metode klasifikasi mampu meningkatkan performa model.
Co-Authors -, Salsabila Aam Alamudi Abdul Aziz Nurussadad Achmad Fauzan Achmad Fauzan, Achmad Achsani, Noer Azham Ade Agusti Alwinie Adi Hadianto 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 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