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All Journal Pythagoras: Jurnal Matematika dan Pendidikan Matematika Media Statistika JURNAL MATEMATIKA STATISTIKA DAN KOMPUTASI SAINSMAT Jurnal Statistika Universitas Muhammadiyah Semarang CAUCHY: Jurnal Matematika Murni dan Aplikasi TELKOMNIKA (Telecommunication Computing Electronics and Control) Bulletin of Electrical Engineering and Informatics Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) Matematika dan Sains Jurnal Ketahanan Nasional Journal of Information Systems Engineering and Business Intelligence Prosiding SI MaNIs (Seminar Nasional Integrasi Matematika dan Nilai-Nilai Islami) MUST: Journal of Mathematics Education, Science and Technology BAREKENG: Jurnal Ilmu Matematika dan Terapan JTAM (Jurnal Teori dan Aplikasi Matematika) Limits: Journal of Mathematics and Its Applications Zeta - Math Journal J Statistika: Jurnal Ilmiah Teori dan Aplikasi Statistika Zero : Jurnal Sains, Matematika, dan Terapan Cakrawala: Jurnal Litbang Kebijakan Jurnal Aplikasi Statistika & Komputasi Statistik JCRS (Journal of Community Research and Service) Jurnal Ilmiah Manajemen dan Bisnis JP2M (Jurnal Pendidikan dan Pembelajaran Matematika) G-Tech : Jurnal Teknologi Terapan Inferensi Contemporary Mathematics and Applications (ConMathA) Jurnal Layanan Masyarakat (Journal of Public Service) Enthusiastic : International Journal of Applied Statistics and Data Science SAINSMAT: Jurnal Ilmiah Ilmu Pengetahuan Alam Aurelia: Jurnal Penelitian dan Pengabdian Masyarakat Indonesia Indonesian Vocational Research Journal PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON DATA SCIENCE AND OFFICIAL STATISTICS Jurnal Pengabdian Nasional (JPN) Indonesia Feelings: Journal of Counseling and Psychology Jurnal Teknologi Informasi untuk Masyarakat (Jurnal Teknokrat) Indonesian Journal of Statistics and Its Applications Jurnal Ilmu Sosial dan Humaniora Limits: Journal of Mathematics and Its Applications
Nur Chamidah
Departemen Matematika, Fakultas Sains Dan Teknologi, Universitas Airlangga
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CHINESE YUAN EXCHANGE RATE AGAINST THE INDONESIAN RUPIAH PREDICTION USING SUPPORT VECTOR REGRESSION Soewignjo, Steven; Septia Sari, Ni Wayan Widya; Mediani, Andini Putri; Kamil, M. Aqil Zaidan; Amelia, Dita; Chamidah, Nur
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 18 No 3 (2024): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol18iss3pp1683-1694

Abstract

This study aims to forecast the exchange rate between the Chinese Yuan (CNY) and the Indonesian Rupiah (IDR) using Support Vector Regression (SVR), a machine-learning technique that can handle nonlinear and complex data. The authors utilize the monthly selling exchange rate of CNY against IDR from January 2012 to October 2023 sourced from the “investing” platform. The optimal SVR model is obtained by splitting the data into 113 training samples and 28 testing samples and using the Radial Basis Function (RBF) kernel. The model achieves high accuracy, with a Mean Absolute Percentage Error (MAPE) of 1.738%, a Root Mean Squared Error (RMSE) of 50.661 for the training data and a MAPE of 2.516%, and an RMSE of 64.735 for the testing data. The results of this paper can provide valuable insights for policymakers, investors, and traders who are interested in the CNY/IDR exchange rate dynamics and the economic implications of the Belt and Road Initiative (BRI). The study aligns with the Sustainable Development Goals (SDGs), specifically SDG 8, aiming to promote sustained, inclusive, and sustainable economic growth.
MODELING HYPERTENSION DISEASE RISK IN INDONESIA USING MULTIVARIATE ADAPTIVE REGRESSION SPLINE AND BINARY LOGISTIC REGRESSION APPROACHES Chamidah, Nur; Hendrawan, Ardana Tegar; Ardiyanto, Figo Surya; Hammami, Martha Sayyida; Izzah, Nurul; Hariadi, Salsabila Niken
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 18 No 4 (2024): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol18iss4pp2217-2230

Abstract

In the pursuit of the Sustainable Development Goals (SDGs), health-related challenges, especially hypertension, remain a significant global issue. The third goal of the SDGs aims to improve the quality of life and well-being of all individuals, but hypertension is a serious problem that can hinder these goals. Often referred to as the "silent killer" by the World Health Organization (WHO), hypertension is exacerbated by low awareness. Globally, more than 1.28 billion adults suffer from hypertension, with most cases in lower to middle-income countries, including Indonesia. Indonesia has an alarming rate of hypertension incidence, ranking fifth highest in the world. Riset Kesehatan Dasar (Riskesdas) 2023 and the Indonesia Family Life Survey (IFLS) are critical for understanding hypertension risk factors in Indonesia. The IFLS data, obtained from www.rand.org, includes observations from October 2014 to April 2015, totalling 85 observations. Despite being over 10 years old, this dataset was selected because it remains the most recent comprehensive data available from RAND, representing 83% of the Indonesian population. The IFLS is conducted every 7-8 years, with the next wave of data expected soon. Most studies on hypertension globally and in Indonesia use parametric regression methods. However, a research gap exists as no studies have used Multivariate Adaptive Regression Splines (MARS) on IFLS data to analyze hypertension risk factors. This study addresses this gap by comparing binary logit regression and MARS. The analysis shows the Apparent Error Rate (APPER) for MARS is 84.706%, while for binary logistic regression it is 80%, indicating MARS is better at classifying hypertension data in Indonesia. Using MARS offers a novel approach to understanding hypertension risk factors in Indonesia. Despite the data's age, it remains relevant as primary causes and risk factors for hypertension have not changed, making the findings valuable for current health policy and strategies.
TRAINING ON USE OF USER-FRIENDLY R-SHINY PROGRAM FOR DETERMINING NUTRITIONAL STATUS OF TODDLERS AT POSYANDU IN THE WORKING AREA OF THE SOBO BANYUWANGI COMMUNITY HEALTH CENTER Chamidah, Nur; Kurniawan, Ardi; Saifudin, Toha; Easyfa Wieldyanisa, Ezha; Insania Dewanty, Sanda; Azizah, Khansa
Jurnal Layanan Masyarakat (Journal of Public Services) Vol. 9 No. 3 (2025): JURNAL LAYANAN MASYARAKAT
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/.v9i3.2025.406-418

Abstract

Stunting is a form of malnutrition that serves as an important indicator for monitoring the growth and development of toddlers. However, assessing the nutritional status of toddlers does not stop at stunting, but includes a comprehensive understanding of the child's nutritional condition in real time, especially by mothers who have toddlers. Although the prevalence of stunting in Indonesia has decreased, achieving the target reduction to 14% by 2024 still requires significant efforts. This community service activity aims to improve the nutritional literacy and technical skills of posyandu cadres and mothers of infants in utilizing a user-friendly R-Shiny-based application, both in web and Android versions. This application allows users to input anthropometric data of infants (weight-for-age, height-for-age, and BMI-for-age), and then automatically generates growth charts based on reference standards. The activity was conducted in a hybrid format on June 29, 2024, with a total of 69 participants (35 offline cadres and 34 online cadres). Evaluation results showed a significant increase in cadres' knowledge, with an average post-test score (76.81) higher than the pre-test score (71.66) and a p-value from the paired t-test of 0.008. Additionally, participants gave high satisfaction scores, with an average above 75 on all indicators. The program also provides intensive mentoring and long-term monitoring to ensure smooth application use. With a data-driven approach sensitive to regional characteristics, this program is expected to serve as an innovative, sustainable, and replicable community service model in other areas to accelerate stunting reduction efforts.
Platelet Modeling in DHF Patients Using Local Polynomial Semiparametric Regression on Longitudinal Data Utami, Tiani Wahyu; Chamidah, Nur; Saifudin, Toha
JTAM (Jurnal Teori dan Aplikasi Matematika) Vol 8, No 1 (2024): January
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jtam.v8i1.17427

Abstract

Regression analysis is one of the statistical methods used to model the relationship between response variables and predictor variables. Semiparametric regression is a combination of parametric and nonparametric regression. The estimator used in estimating the semiparametric regression model in this research is the Local Polynomial. Longitudinal data can be found in the health sector, including dengue hemorrhagic fever (DHF) data. The laboratory criteria for indication of DHF is thrombocytopenia. This research aims to obtain platelets model for DHF patients that can be used for forecasting so that it is hoped that it can provide information to the medical team in treating DHF patients. The estimated model used is Local Polynomial semiparametric regression on longitudinal data. The response variables in this research were platelets of DHF patients, which were influenced by hemoglobin as parametric predictor variable and examination time while hospitalized as nonparametric predictor variable. In the local polynomial regression model, it is necessary to select the optimal bandwidth and polynomial order method, GCV. The optimum bandwidth selection based on the GCV method obtained is 1.5 and polynomial order of 2, then applied to DHF patient platelet data, producing an estimated local polynomial semiparametric regression model that follows the actual data pattern. Modeling the platelets of DHF patients obtained using a local polynomial estimator resulted in an R2 value of 84.25% and MAPE of 4.5%, indicating highly accurate forecasting, so it can be concluded that the resulting model is better at predicting.
Mapping Food Insecurity: Spatial Modelling of Undernourishment Prevalence in Indonesia using Geographically Weighted Regression Saifudin, Toha; Chamidah, Nur; Ramadhina, Fidela Sahda Ilona; Al Hasri, Ilham Maulana; Trisa, Nadya Lovita Hana; Valida, Hanny; Setyawan, Muhammad Daffa Bintang
JTAM (Jurnal Teori dan Aplikasi Matematika) Vol 9, No 4 (2025): October
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jtam.v9i4.32063

Abstract

Undernourishment is a major global issue, with significant impact observed in Indonesia. A method of assessing the prevalence of energy deficiency resulting from inadequate nutrition is through the Prevalence of Undernourishment (PoU) index. From 2019 to 2022, Indonesia's PoU increased gradually, reaching 10.21% in 2022, indicating growing undernourishment and unstable food availability. This study aims to utilize Geographically Weighted Regression (GWR) to identify and analyze the factors contributing to undernourishment. The data were obtained from the Central Bureau of Statistics (BPS) in 2024, covering 38 provinces in Indonesia. This study examined six factors: per capita spending, access to potable water, mean years of schooling, access to adequate sanitation, college participation rate, and mean food expenditure. The findings show that the GWR model outperformed the conventional model, demonstrating greater explanatory power by accounting for 96.1% of the spatial variation in undernourishment and achieving the lowest AIC value of 176.7052. These findings highlight the need for region-specific food security policies, particularly in eastern Indonesia. The results can inform targeted government interventions and guide future spatial econometric research on food security.
Analisis Hubungan Antara Jalur Masuk Universitas dengan Predikat Kelulusan Mahasiswa Kamila, Yasmin; Sa’idah, Andini; Akbar, Aditya Syarifudin; Azzen, Fiyadika Amalia Nurizah; Rohim, Achmad Yazid Busthomi; Chamidah, Nur
Zeta - Math Journal Vol 8 No 1 (2023): Mei
Publisher : Universitas Islam Madura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31102/zeta.2023.8.1.23-29

Abstract

There are different characteristics of each entry route, so there will be the potential to achieve a different GPA. There are 3 types of entrance routes for public universities held by LTMPT, namely SNMPTN, SBMPTN, and SMMPTM. The achievement of student learning outcomes in tertiary institutions can be seen through the final results indicated by the GPA. Diploma and undergraduate program students have four graduation predicates, three of which are satisfactory (GPA 2.76-3.00), very satisfactory (GPA 3.01-3.50), and with honors (GPA more than 3.50). The population in this study were all PTN graduates from 2018 to 2022. The sample used in this study was at least 50 PTN graduates from 2018 to 2022 and 150 samples. This research will be tested using the Chi-Square test method. Based on the Chi-Square test on the contingency table related to the relationship between college admissions and student graduation predicates, it can be concluded that there is no relationship between college admissions and student graduation predicates. In addition, the relationship between university admissions and student graduation predicates is related to majors and campus clustering in 2020. Meanwhile, the relationship between university admissions and student graduation predicates has no relationship with gender and domicile.
Pemodelan Angka Harapan Hidup Negara G7 dengan Pendekatan Analisis Regresi Data Longitudinal Farizi, Muhammad Fikry Al; Maula, Sugha Faiz Al; Fajrina, Sofia Andika Nur; Hilma, Dzuria Hilma Qurotu Ain; Suryono, Alda Fuadiyah; Chamidah, Nur
Limits: Journal of Mathematics and Its Applications Vol. 22 No. 1 (2025): Limits: Journal of Mathematics and Its Applications Volume 22 Nomor 1 Edisi Ma
Publisher : Pusat Publikasi Ilmiah LPPM Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/limits.v22i1.3368

Abstract

Life expectancy is the average number of years of life a newborn baby will live in a given year. In general, life expectancy is a tool to evaluate government performance in improving community welfare. The aim of this research is prediction using longitudinal data regression analysis methods, namely Generalized Least Square with a Restricted Maximum Likelihood approach using a uniform correlation structure, Autoregressive (AR) (1), and Gaussian with factors that influence life expectancy, namely Tax to GDP ratio, Gross Domestic Product per Capita (GDPPC) and Health Expenditure per Capita from 2000-2020 in G7 countries. Based on the analysis results, it was found that tax revenues had a negative effect of 0.155 but the effect was not significant, GDP had a positive effect of 0.715 but had a significant effect, while health expenditure had a negative effect of 0.49 on Life Expectancy. The research results found that conditions in the G7 that were not ideal caused negative effects on taxes and health spending that were not in accordance with theory. The suggestions that can be given include tax reform from the source and its implementation, such as cigarette tax and sugary drink tax. In addition, it also provides suggestions to include universal health for a healthier and more prosperous society. This research is also in accordance with the aim of Sustainable Development Goals (SDGs) number 3, namely "Ensuring healthy lives and improving the welfare of all populations of all ages" and can be used as a policy reference for Indonesia.
Pemodelan Kasus Tuberkulosis di Jawa Tengah dengan Geographically Weighted Negative Binomial Regression Andini Putri Mediani; Toha Saifudin; Nur Chamidah
Limits: Journal of Mathematics and Its Applications Vol. 21 No. 3 (2024): Limits: Journal of Mathematics and Its Applications Volume 21 Nomor 3 Edisi No
Publisher : Pusat Publikasi Ilmiah LPPM Institut Teknologi Sepuluh Nopember

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

Abstract

Tuberkulosis (TB) dianggap sebagai permasalahan kesehatan global yang utama karena menjadi salah satu penyakit menular yang mematikan di seluruh dunia. World Health Organization (WHO) mengategorikan sebanyak 30 negara di dunia dengan beban tinggi kasus TB dengan Negara Indonesia menempati peringkat kedua dalam kategori beban tinggi tersebut. Salah satu provinsi dengan penderita terbanyak kasus TB adalah Provinsi Jawa Tengah. Banyaknya penderita TB di Kabupaten Jawa Tengah menunjukkan bahwa terdapat faktor-faktor yang memengaruhi tingginya kasus TB, sehingga perlu dilakukan analisis secara statistik untuk mengetahui penyebab terjadinya permasalahan tersebut sekaligus mendukung tercapainya target yang berkaitan dengan target SDGs pada poin 3.3, yaitu untuk mengakhiri epidemi TB. Pada jumlah kasus TB yang berupa data diskrit, regresi Poisson merupakan metode yang sesuai untuk memodelkan data diskrit dengan asumsi ekuidispersi yang harus terpenuhi. Namun, untuk kasus TB di Jawa Tengah asumsi tersebut tidak terpenuhi, dengan kata lain terdapat overdispersi. Overdispersi dapat ditangani dengan regresi Binomial Negatif, tetapi dengan mempertimbangkan faktor spasial metode yang sesuai untuk digunakan adalah Geographically Weighted Negative Binomial Regression (GWNBR). Hasil diperoleh fungsi pembobot untuk GWNBR adalah Fixed Gaussian dengan nilai CV terkecil 4427790. Pemodelan dengan GWNBR lebih baik dalam memodelkan jika dibandingkan dengan regresi global. Hal ini diperkuat oleh nilai AIC terkecil, yakni 370,14 sehingga permasalahan overdispersi sudah teratasi. Kemudian, variabel yang berpengaruh signifikan pada setiap kabupaten dan kota di Jawa Tengah adalah persentase rumah tangga yang memiliki sumber air minum layak, jumlah tenaga kesehatan, rasio jenis kelamin, dan jumlah penduduk usia produktif dengan besar pengaruh yang berbedabeda.
Prediksi Jumlah Penumpang Kereta Api Stasiun Surabaya Gubeng dengan Metode Monte Carlo Angga Kusuma Bayu Viargo; Toha Saifudin; Nur Chamidah
Limits: Journal of Mathematics and Its Applications Vol. 20 No. 3 (2023): Limits: Journal of Mathematics and Its Applications Volume 20 Nomor 3 Edisi No
Publisher : Pusat Publikasi Ilmiah LPPM Institut Teknologi Sepuluh Nopember

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

Abstract

Jumlah penumpang kereta api di Indonesia kembali mengalami peningkatan semenjak masa pandemi. Salah satu stasiun yang mengalami peningkatan penumpang adalah Stasiun Surabaya Gubeng. Penelitian ini bertujuan untuk mendapatkan hasil prediksi jumlah penumpang harian kereta api di Stasiun Surabaya Gubeng menggunakan metode Monte Carlo dengan pembangkit bilangan acak yang berbeda. Metode Monte Carlo merupakan metode yang menginterpretasikan hasil ketidakpastian probabilitas dari suatu proses dan menyimulasikan nilai frekuensi secara stokastik dari segala kemungkinan hasil. Pembangkit bilangan acak yang digunakan yaitu; multiplicative, mixed, dan random uniform . Tingkat keakuratan dari hasil penelitian dihitung berdasarkan nilai Mean Absolute Percentage Error (MAPE). Data dalam penelitian ini merupakan data time series diambil dari tanggal 16 Mei 2022 hingga 2 Oktober 2022 sebanyak 140 hari. Data dibagi menjadi tujuh kelompok berdasarkan nama hari sebanyak 20 data untuk setiap kelompok. Prediksi dilakukan menggunakan Monte Carlo diperoleh rata-rata nilai MAPE outsample dari setiap kelompok hari yaitu; hari Senin sebesar 25,25%, hari Selasa sebesar 16,74%, hari Rabu sebesar 17,73%, hari Kamis sebesar 3,32%, hari Jumat sebesar 12,36%, hari Sabtu sebesar 4,88%, dan hari Minggu sebesar 2,62%. Kesimpulan akhir diperoleh bahwa hasil prediksi sangat akurat terjadi pada hari Kamis, Sabtu dan Minggu.
IMPROVING EDUCATION AND DETERMINING THE NUTRITIONAL STATUS OF TODDLERS IN REALIZING NUTRITION-CONSCIOUS FAMILIES IN BANYUWANGI USING R-SHINY Chamidah, Nur; Kurniawan, Ardi; Saifudin, Toha; Sa'idah, Andini; Widyawati, Ayu; Fajrina, Sofia
Jurnal Layanan Masyarakat (Journal of Public Services) Vol. 8 No. 1 (2024): JURNAL LAYANAN MASYARAKAT
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/jlm.v8i1.2024.061-073

Abstract

Stunting is a condition where a child's development and growth is disturbed, which has long-term impacts, including the potential for impaired brain development due to insufficient cognitive development and a greater risk of developing chronic diseases such as diabetes, hypertension, obesity, cancer, and so on. One effort to reduce stunting rates is to increase knowledge of nutrition awareness in the family. UNAIR Statistics Study Program, participates in efforts to reduce stunting rates with community service activities (Pengmas), in the form of outreach activities regarding basic and practical knowledge in the form of workshops and training activities using R-Shiny based WEB and Android to determine the nutritional status of toddlers which can used anywhere and anytime. This community service activity was carried out in the working area of "‹"‹the Tampo Community Health Center, Banyuwangi, East Java, involving 62 female cadre representatives from 31 local posyandu. The results of this community service activity can increase knowledge regarding education and nutrition knowledge for toddlers in the context of achieving nutrition-aware families. This is proven by the results of statistical analysis of pre-test and post-test scores which conclude that there is an increase in scores from pre-test to post-test with a significance level of 5%. Based on the results of the feedback questionnaire given to participants, the posyandu cadre mother felt very satisfied with an average score of 86, gained useful knowledge, and made it easier for posyandu cadres to find out the nutritional status of toddlers.
Co-Authors A Meylin Abdul Aziz Abidin, Qumadha Zaenal Afriani Agus Satmoko Adi Aisharezka, Mutiara Akbar, Aditya Syarifudin Al Farizi, Muhammad Fikry Al Hasri, Ilham Maulana Aldawiyah, Najwa Khoir Alexandra, Victoria Anggia Alfiatur Rakhma, Syavrilia Alfinda Novi Kristanti Alpandi, Gaos Tipki Amanda, Yulia Aminuyati Aminy, Aisyah Ana, Elly Ananda Dwi Andini Putri Mediani Andriani, Putu Eka Andriani, Putu Eka Angga Kusuma Bayu Viargo Angga Kusuma Bayu Viargo Anies Yulinda W Anisa Laila Azhar Any Tsalasatul Fitriyah Ardi Kurniawan Ardi Kurniawan Ardiyanto, Figo Surya Aryati Aryati Auliyah, Nina Azizah, Khansa Azzen, Fiyadika Amalia Nurizah Baihaqi, Muhammad Rizaldy Baktiar Aris Belindha Ayu Ardhani Brenda Bunga Prasenda Budi Lestari Budi Lestari Christopher Andreas D Lestari Darmawan, Kezia Eunike Dhohirrobbi, Achmad Dhyana Venosia Dhyana Venosia Diah Puspita Ningrum Diana Ulya Dita Amelia Dita Amelia, Dita Easyfa Wieldyanisa, Ezha Eko Tjahjono Elfhira Juli Safitri Fachrian, Muhammad Nadhil Faiza, Atikah Faizun, Nurin Fajrina, Sofia Fajrina, Sofia Andika Nur Fajrina, Sofia Andika Nur Fania, Azzahra Farida Farida Farizi, Muhammad Fikry Al Fatmawati Fatmawati Fatmawati Fatmawati Fauziah, Nathania Feevrinna Yohannes Harianto Fibryan, Muhammad Hilmi FIRMANSYAH, MOCHAMMAD Fitri Syaharani, Amadea Fitri, Marfa Audilla Fitri, Marfa Audilla Gaos Tipki Alpandi Halimatuzzahro, Fitria Hammami, Martha Sayyida Hariadi, Salsabila Niken Hendrawan, Ardana Tegar Herdianto, Muhammad Hendra Hidayat, Rizky Ismaul Uyun Hilma, Dzuria Hilma Qurotu Ain Horidah Horidah Huda, Mi'rojul I Nyoman Budiantara Insania Dewanty, Sanda Islamudin, Mohamad Mujahid IZZAH, NURUL Julianto, Agnes Happy Juniar, Muhammad Althof Kamiilah, Nadhira Safa Kamil, M. Aqil Zaidan Kamila, Yasmin Kinanti Hanugera Gusti Larasati, Berliani Lensa Rosdiana Safitri Lilik Hidayati, Lilik Listyaningsih Listyaningsih M. Fariz Fadillah Mardianto Mahadesyawardani, Arinda Mahadesyawardani, Arinda Marbun, Barnabas Anthony Philbert Marisa Rifada Marthabakti, CitraWani Maula, Sugha Faiz Al Maulidya, Utsna Rosalin MAYA MUSTIKA KARTIKA SARI, MAYA Mediani, Andini Putri Mediani, Andini Putri Melati Tegarina Mohamad David Hermawan Muhammad Falah El Fahmi Mutiara Aisharezka Muzakki, Naufal N. A. Aprilianti Nadia Murbarani Nahar, Muhammad Hafidzuddin Naufal Ramadhan Al Akhwal Siregar Nia Saurina Nitasari, Alfi Nur Nur Azizah Rahayu Ningsih Prasetyo, Juan Krisfigo Pratama, Bagas Shata Pratama, Fachriza Yosa Purnama, Titania Faisha Putra, Mochamad Rasyid Aditya Qumadha Zainal Abidin Rahayu, Rizky Dwi Kurnia Rahma, Alma Khalisa Rahmatika, Nabila Syahfitri Ramadhanti, Aulia Ramadhina, Fidela Sahda Ilona Ramadhita, Ghina Recylia, Rien Reiza Sahawaly Rico Ramadhan, Rico Rimuljo Hendradi Riries Rulaningtyas Rizza Sulistiana Rohim, Achmad Yazid Busthomi S, Salma Bethari Andjani Sa'idah, Andini Sabrina Falasifah Safitri, Lensa Rosdiana Salsabilla, Shafira Salsabylla Nada Apsariny Sasmia Desinta Wulandari Sa’idah, Andini Sediono, Sediono Sely Novika Norrachma Septia Sari, Ni Wayan Widya Setyawan, Muhammad Daffa Bintang Setyowati, Raden Roro Nanik Siagian, Kimberly Maserati Siburian, Cynthia Anggelyn Siregar, Naufal Ramadhan Al Akhwal Siti Maizul Habibah Slamet Muchsin Soewignjo, Steven Subiyanto, Marcel Laverda Sufyan Ats Tsauri Suliyanto Sunariyanto, Sunariyanto Suryono, Alda Fuadiyah Suryono, Alda Fuadiyah Suwarno Suwarno Syifaun Nadhiro Thohari, Habib Nihla Tiani Wahyu Utami Toha Saifudin Toha Saifudin Trias Novia L. Trisa, Nadya Lovita Hana Ulandari, Kartini Putri Ulya, Diana Umi Tri Ruhana Usmi, Rianda Valida, Hanny Wahyuli, Diana Warsono Warsono Widyangga, Pressylia Aluisina Putri Widyawati, Ayu Wieldyanisa, Ezha Easyfa Wulandari, Nuryuliana Yolanda Swastika Yolanda Swastika Yonani Zahrotul Azizah Zidni Ilmatun Nurrohmah