Article Per Year (5 Year)
p-Index From 2021 - 2026
7.28
P-Index
This Author published in this journals
All Journal IAES International Journal of Artificial Intelligence (IJ-AI) MATEMATIKA JURNAL MATEMATIKA STATISTIKA DAN KOMPUTASI Jurnal Ilmu Sosial dan Humaniora CAUCHY: Jurnal Matematika Murni dan Aplikasi Matematika dan Sains Journal of Information Systems Engineering and Business Intelligence Prosiding SI MaNIs (Seminar Nasional Integrasi Matematika dan Nilai-Nilai Islami) Syntax Literate: Jurnal Ilmiah Indonesia MUST: Journal of Mathematics Education, Science and Technology BAREKENG: Jurnal Ilmu Matematika dan Terapan JTAM (Jurnal Teori dan Aplikasi Matematika) Zero : Jurnal Sains, Matematika, dan Terapan Cakrawala: Jurnal Litbang Kebijakan PengabdianMu: Jurnal Ilmiah Pengabdian kepada Masyarakat Jurnal Aplikasi Statistika & Komputasi Statistik JP2M (Jurnal Pendidikan dan Pembelajaran Matematika) G-Tech : Jurnal Teknologi Terapan Critical Medical and Surgical Nursing Journal Inferensi Contemporary Mathematics and Applications (ConMathA) Jurnal Keselamatan Transportasi Jalan (Indonesian Journal of Road Safety) Jurnal Layanan Masyarakat (Journal of Public Service) Seminar Nasional Hasil Riset dan Pengabdian (SNHRP) PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON DATA SCIENCE AND OFFICIAL STATISTICS Economic Development Analysis Journal Jurnal Keselamatan Transportasi Jalan Limits: Journal of Mathematics and Its Applications
Toha Saifudin
Departement Of Mathematics, Faculty Of Science And Technology, Airlangga University
Agriculture, Biological Sciences & Forestry Arts Humanities Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Energy Engineering Environmental Science Health Professions Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Mathematics Mechanical Engineering Nursing Physics Public Health Social Sciences Transportation Other

Published : 54 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 54 Documents
Search

 2   3   4   5   6 
Modeling the Percentage of Tuberculosis Cure in Indonesia Using a Multivariate Adaptive Regression Spline Approach Novianti, Dita Aris; Marwanda, Nadia Dwi; Saifudin, Toha; Suliyanto, Suliyanto
Inferensi Vol 7, No 2 (2024)
Publisher : Department of Statistics ITS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j27213862.v7i2.20344

Abstract

Tuberculosis (TB) is an infectious disease caused by the bacterium Mycobacterium Tuberculosis. After India, Indonesia is the country with the second highest number of TB sufferers in the world. TB prevention efforts in Indonesia have been carried out, even since 1995. However, in general, 2006-2022 the TB cure in Indonesia tends to experience a downward trend. Therefore, it is important to know what variables have a significant effect and how the pattern relates to the percentage of TB cures. We urgently need this information to optimize TB handling efforts and achieve Sustainable Development Goals (SDGs) point 3, which focuses on good health and well-being. For that purpose, this study used the Multivariate Adaptive Regression Spline (MARS) approach. MARS is considered more flexible in overcoming cases of predictor variables that do not form a certain pattern to their response variables and can accommodate possible interactions between predictor variables. The best model was obtained at BF=18,MI=2, and MO=0 with minimum GCV value is 37.053 and R^2 is 91.6%, with significant predictor variables are food management sites meet the requirements according to standards, complete treatment, smoking population over 15 years, families with healthy latrines, and districts/municipalities implement healthy living germas policy. The significance of the nine predictors should prioritize enhancing the quality of health services for example ensuring a fair distribution of complete treatment for TB patients.
Analysis of Geographically Weighted Logistic Regression Models with A Bisquare Weighting Matrix on Poverty Status in West Java Saifudin, Toha; Chamidah, Nur; Aldawiyah, Najwa Khoir; Marthabakti, Citrawani; Ramadhanti, Aulia; Nahar, Muhammad Hafidzuddin; Muzakki, Naufal
CAUCHY: Jurnal Matematika Murni dan Aplikasi Vol 10, No 2 (2025): CAUCHY: JURNAL MATEMATIKA MURNI DAN APLIKASI
Publisher : Mathematics Department, Universitas Islam Negeri Maulana Malik Ibrahim Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18860/cauchy.v10i2.36315

Abstract

This research addresses the first Sustainable Development Goal and aims to analyze poverty status in West Java Province, which has the second highest number of poor people in Indonesia. The study employs Geographically Weighted Logistic Regression (GWLR) and compares it with global logistic regression. Influential variables include GDP, unemployment, population density, access to safe water, and roof type (bamboo/wood). Results show that 55.6% of regions are classified as poor, with the GWLR model using a Fixed Bisquare kernel achieving 81.4% accuracy, outperforming global logistic regression at 66.7%. Significant variables vary by region: unemployment rate in Bogor, Depok, and Bekasi; population density in Bekasi, Karawang, and Purwakarta; water access in Sukabumi; and roof type in Indramayu and Bogor. These spatial variations suggest that poverty reduction requires a region-specific approach. Consequently, policies should be formulated considering the priorities and characteristics of each region in West Java Province.
ANALYSIS OF FACTORS AFFECTING PNEUMONIA IN INDONESIAN TODDLERS USING NONPARAMETRIC REGRESSION WITH LEAST SQUARE SPLINE AND FOURIER SERIES METHODS Saifudin, Toha; Suliyanto, Suliyanto; Nurdin, Nabila; Christiano Ginzel, Bryan Given; Oktavia, Sabrina Salsa; Ariyawan, Jovansha; Ubadah, Mohammad Noufal
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 20 No 1 (2026): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol20iss1pp0087-0104

Abstract

Pneumonia is the leading cause of death among children under five, with the highest prevalence in Indonesia found in West Papua Province (75%) and the lowest in North Sulawesi (0.3%). This study aims to analyze the factors influencing the prevalence of pneumonia in Indonesian toddlers using nonparametric regression approach by comparing Least Square Spline (LS-Spline) and Fourier Series. Data sourced from the Indonesian Ministry of Health website, consisting of 34 provinces in Indonesia in 2023, with one response variable (Y) and five predictor variables (X). The analyzed factors include the coverage of vitamin A supplementation, malnutrition rates, low birth weight prevalence, measles immunization coverage, and exclusive breastfeeding rates. The analysis was conducted by modeling with nonparametric Least Square Spline regression using up to three optimal knot points, then performing analysis using nonparametric regression with the Fourier series approach. The two methods were compared based on GCV and R², with the best model having lower GCV and higher R². The results showed that LS-Spline was better than Fourier Series, with a GCV value of 233.16 and a coefficient of determination of 92.5%. The findings reveal that the relationships between predictor factors and pneumonia prevalence are nonlinear, with varying influence patterns across different variable ranges. These results indicate that LS-Spline has a strong ability to explain data variability. The Fourier series is limited in this study because it is best suited for periodic data, unlike pneumonia data and its causal factors which do not show such patterns. The weakness of the Fourier Series in this study lies in its suitability for periodic data, while pneumonia cases and their causal factors do not follow such patterns. This study offers insights into health policy making to reduce pneumonia cases, improve their lives, in line with the SDGs target on Good Health and Well-being.
Peningkatan Kompetensi Guru dalam Analisis Data Hasil Pembelajaran dengan Metode Statistika Menggunakan Microsoft Excel di SD Muhammadiyah 1 Trenggalek: Improving Teachers’ Competence in Analyzing Learning Outcomes Data Using Statistical Methods with Microsoft Excel at SD Muhammadiyah 1 Trenggalek Rifada, Marisa; Saifudin, Toha; Kurniawan, Ardi; Ramadhani, Azzah Nazhifa Wina; Maharani, Prima; Sentosa, Martha Ayu
PengabdianMu: Jurnal Ilmiah Pengabdian kepada Masyarakat Vol. 11 No. 1 (2026): PengabdianMu: Jurnal Ilmiah Pengabdian kepada Masyarakat
Publisher : Institute for Research and Community Services Universitas Muhammadiyah Palangkaraya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33084/pengabdianmu.v11i1.10675

Abstract

Muhammadiyah 1 Trenggalek Elementary School is one of the leading private elementary schools in Trenggalek Regency that implements an innovative system in its learning and has a strong commitment to improving the quality of education. However, most of the teachers in this elementary school still lack understanding of the concept of statistics along with the application of technology to analyze student learning data, so that the evaluation of student learning outcomes becomes less than optimal. Therefore, this community service program is carried out to provide intensive training on basic understanding of statistics, the use of Microsoft Excel to process data, and the application of analysis results to improve teaching methods. This program was carried out through several stages, consisting of providing offline training and assistance to groups of teachers in applying the training results to student learning data. The evaluation results show an increase in teacher understanding of the training material provided, with evidence of an increase in the average pre-test score of 64.46 to 71.08 in the post-test. Thus, this community service activity can be said to have succeeded in increasing teacher competence in using Microsoft Excel as a means of analyzing student learning data, which is also a start to improving the quality of Muhammadiyah 1 Trenggalek Elementary School teachers.
PERBANDINGAN PENDEKATAN DATA PANEL UNIVARIAT DAN PANEL SUR DALAM PEMODELAN STUNTING, WASTING, DAN UNDERWEIGHT DI INDONESIA Teguh Susanto; Toha Saifudin; Nur Chamidah
Seminar Nasional Hasil Riset dan Pengabdian Vol. 7 (2025): Seminar Nasional Hasil Riset dan Pengabdian (SNHRP) Ke 7 Tahun 2025
Publisher : LPPM Universitas PGRI Adi Buana

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

Abstract

Indonesia berkomitmen untuk mewujudkan Sustainable Development Goals khususnya Zero Hunger 2030. Penelitian ini bertujuan untuk mengevaluasi efisiensi komparatif dan konsistensi struktural antara model regresi data panel univariat dengan model multivariat Panel Seemingly Unrelated Regression dalam memodelkan kasus stunting, wasting, dan underweight pada periode 2007–2023 di Indonesia. Pemilihan model Panel SUR didasarkan pada hasil uji diagnostik yang menunjukkan adanya korelasi signifikan antar error term pada ketiga persamaan (p < 0,001). Metode estimasi yang digunakan adalah FGLS dua arah. Hasil penelitian menunjukkan bahwa model univariat menghasilkan anomali tanda koefisien, di mana variabel berat badan lahir rendah (BBLR) berhubungan negatif dengan wasting, yang bertentangan dengan teori biologis. Sebaliknya, model Panel SUR melalui estimasi simultan berhasil memperbaiki arah hubungan tersebut menjadi positif dan meningkatkan nilai koefisien determinasi (R²) pada persamaan wasting secara signifikan. Selain itu, hasil evaluasi efisiensi berdasarkan Mean Square Error (MSE) menunjukkan bahwa model Panel SUR memberikan estimasi yang lebih efisien (MSE lebih rendah dibandingkan model univariat). Secara keseluruhan, temuan ini menunjukkan bahwa model Panel SUR lebih tepat digunakan untuk analisis sistem malnutrisi karena menawarkan konsistensi parameter yang lebih baik dan efisiensi statistik yang lebih tinggi, sehingga memberikan dasar yang lebih kuat bagi perumusan kebijakan gizi terpadu di Indonesia.
FORECASTING THE INFLATION RATE IN INDONESIA USING ARIMA-GARCH MODEL Saifudin, Toha; Suliyanto, Suliyanto; Afifa, Fitriana Nur; Arrofah, Aini Divayanti; Fauzi, Doni Muhammad; Pratama, Fachriza Yosa; Adyatma, Isryad Yoga
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 20 No 2 (2026): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol20iss2pp0955-0970

Abstract

Inflation is a key economic indicator that affects purchasing power, economic growth, and financial stability. Accurate forecasting is essential for policymakers to implement effective monetary and fiscal policies. However, traditional models like ARIMA (Autoregressive Integrated Moving Average) mainly capture general trends and often fail to address inflation volatility. This study enhances inflation forecasting accuracy by applying the ARIMA-GARCH hybrid model, which combines trend estimation with volatility modelling. Focusing on Indonesia’s inflation patterns using recent data, it addresses a gap in existing research. This type of research uses quantitative methods, and the data were obtained from the official website of Bank Indonesia. The dataset consists of 240 monthly Indonesian inflation data points spanning from September 2004 to August 2024. The ARIMA (0,1,1)-GARCH (2,0) model is used to analyze inflation trends and volatility dynamics. The model evaluation shows strong predictive performance, with a Mean Absolute Percentage Error (MAPE) of 2.73% and Root Mean Squared Error (RMSE) of 0.74 for training data. Testing data results in a MAPE of 18.95% and RMSE of 0.702, which remains within an acceptable range. These findings highlight the importance of incorporating volatility modelling in inflation forecasting to enhance economic decision-making. A reliable forecast mitigates economic uncertainty, thereby providing a stronger foundation for achieving long-term economic growth. This study contributes by demonstrating the practical application of ARIMA-GARCH in Indonesia’s inflation modelling, providing valuable insights for policymakers in managing inflation-related risks.
SPATIAL EXTRAPOLATION OF MALARIA CASES IN CENTRAL PAPUA USING CO-KRIGING BASED ON RAINFALL AND OBSERVATIONAL DATA FROM PAPUA PROVINCE Saifudin, Toha; Chamidah, Nur; Zhafira, Azizah Atsariyyah; Budijono, Gabriella Agnes; Sihite, Rivaldi; Baihaqi, Mochamad; Januarta, R. Arya
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 20 No 2 (2026): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol20iss2pp1485-1500

Abstract

Malaria is an infectious disease that remains a significant health burden in Indonesia, particularly in Papua Province. This province has the highest malaria incidence rate nationally, influenced by various environmental factors such as rainfall. This study aims to estimate the number of malaria cases in districts/cities of Central Papua Province that do not have direct observation data, by utilizing the Co-Kriging method based on rainfall as a secondary variable and malaria cases as a primary variable from Papua Province. The secondary data used in this study were obtained from the official website of the Badan Pusat Statistik (BPS) of Papua Province, which includes the number of malaria cases in districts/cities as well as rainfall data from meteorological stations in the same region, collected in 2023. Three types of semivariogram models-spherical, exponential, and gaussian-were used to select the best model through statistical evaluation using Mean Squared Error (MSE) and Mean Absolute Percentage Error (MAPE). The results showed that the Gaussian semivariogram model provided the most optimal prediction results with an MSE of 10.895 and an MAPE of 4.67%. The estimates show that malaria cases in Central Papua are relatively uniform, with the highest incidence in Puncak Jaya district (219/1000 population) and the lowest in Mimika district (211/1,000 population). This approach is expected to be an important tool in spatially based disease planning and control and support the achievement of Sustainable Development Goals (SDGs), especially goals 3 (Good Health and Well-Being) and 13 (Climate Action).
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.
SPATIAL MODELING OF CHILD MALNUTRITION IN INDONESIA USING GEOGRAPHICALLY WEIGHTED MULTIVARIATE REGRESSION (GWMR) Teguh Susanto; Toha Saifudin; Nur Chamidah
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 20 No 3 (2026): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol20iss3pp1837-1854

Abstract

In Indonesia aspires to become a developed nation by 2045, with one of its key pillars being the improvement of human resource quality through the achievement of Sustainable Development Goal (SDG) 2: ending hunger and ensuring access to adequate nutrition. However, the prevalence of stunting, wasting, and underweight among children under five remains a critical challenge that hampers these efforts. This study aims to simultaneously analyze the determinants influencing these three forms of malnutrition among Indonesian children by incorporating spatial aspects through the Geographically Weighted Multivariate Regression (GWMR) approach. The analysis employs nine predictor variables representing socioeconomic, demographic, and environmental factors across all provinces in Indonesia. The findings reveal that Complete Basic Immunization, Knowledge of Stunting Prevention, and Lower-Middle Economic Status consistently have significant effects on stunting and underweight. Meanwhile, Complete Basic Immunization and Complementary Feeding Practices play major roles in influencing wasting across provinces.Spatial analysis highlights varying patterns of determinants across regions. Western Indonesia (Java, Sumatra, and western Kalimantan) is more influenced by community behavior (mothers without a MCH Book,Children receiving complete basic immunizations receiving and children recheived complementary feeding), access to adequate sanitation, and lower-middle economic status. In contrast, Eastern Indonesia (Maluku and Papua) is more affected by structural conditions such as preterm births, low immunization coverage, knowledge of stunting prevention, and economic limitations. Central Indonesia demonstrates a more complex and varied combination of influencing factors. Furthermore, the GWMR model exhibits substantially better performance compared to the global (multivariate linear regression) model, as indicated by a significantly lower AIC value (Global AIC = 287.537; GWMR AIC = 44.956). These findings underscore the importance of spatially adaptive and decentralized nutrition policies to ensure more targeted and context-specific interventions.
Co-Authors Abdul Aziz Aditya Syarifudin Akbar Adyatma, Isryad Yoga Afifa, Fitriana Nur Aflaha, Nabila Shafa Aisharezka, Mutiara Aisyah, Arlisya Shafwan Al Hasri, Ilham Maulana Aldawiyah, Najwa Khoir Alfi Nur Nitasari Alfredi Yoani Alpandi, Gaos Tipki Ameliatul 'Iffah Ana, Elly Andini Putri Mediani Angga Kusuma Bayu Viargo Angga Kusuma Bayu Viargo Aniq Atiqi Any Tsalasatul Fitriyah Ardi Kurniawan Ardi Kurniawan Ariani, Fildzah Tri Januar Ariyawan, Jovansha Arrofah, Aini Divayanti Aulia, Niswa Faizah Auliyah, Nina Ayuning Dwis Cahyasari Azis, Aurelia Islami Azizah, Khansa Baihaqi, Mochamad Belindha Ayu Ardhani Budijono, Gabriella Agnes Chaerobby Fakhri Fauzaan Purwoko Christiano Ginzel, Bryan Given Christopher Andreas Dewanti, Maria Setya Dewanty, Sanda Insania Diah Puspita Ningrum Dita Amelia Dita Amelia Dita Amelia, Dita Dwika Maya Harsanti Easyfa Wieldyanisa, Ezha Elly Pusporani Erfiana Erfiana Faiza, Atikah Fajrina, Sofia Falasifah, Sabrina Fatmawati Fatmawati Fauzi, Doni Muhammad Fauziah, Nathania Fa’iqotus Zuqna Dwi Syauqie Felix Reba Fina Insyiroh Firmansyah, Mochamad FIRMANSYAH, MOCHAMMAD Fitriani, Mubadi'ul Fortunata, Regina Gaos Tipki Alpandi Gaos Tipki Alpandi Hardiansyah, Fernanda Rizky Hasyim, Maylita Herdianto, Muhammad Hendra Ibrahim, Auron Saka Ilma Amira Rahmayanti Indrasta, Irma Ayu Insania Dewanty, Sanda Januarta, R. Arya Johanna Tania Victory Khairian, Farhan Aldan Kholidiyah, Azizatul Koesnadi, Grace Lucyana Leni Sartika Panjaitan Lensa Rosdiana Safitri M. Fariz Fadillah Mardianto Maelcardino Christopher Justin Mahadesyawardani, Arinda Maharani, Prima Makhbubah, Karina Rubita Marisa Rifada Marpaung, Josua Ronaldo Davico Marshanda Aprilia Marthabakti, CitraWani Marwanda, Nadia Dwi Mediani, Andini Putri Mia Khoirunnisa Mochamad Firmansyah Mochamad Rasyid Aditya Putra Muhammad Rosyid Ridho Az Zuhro Mutiara Aisharezka Muzakki, Naufal Nahar, Muhammad Hafidzuddin Naufal Ramadhan Al Akhwal Siregar Naura, Sheila Sevira Asteriska Novianti, Dita Aris Nugraha, Galuh Cahya Nur Chamidah Nur chamnidah Nur Rahmah Miftakhul Jannah Nurdin, Nabila Nurrohmah, Zidni 'Ilmatun Oktavia, Sabrina Salsa Panjaitan, Leni Sartika Pratama, Fachriza Yosa Purnama, Titania Faisha Puspasari, Laili Raaulia Gita Nafsi Rahayu, Rizky Dwi Kurnia Ramadhani, Azzah Nazhifa Wina Ramadhanti, Aulia Ramadhanty, Devira Thania Ramadhina, Fidela Sahda Ilona Recylia, Rien Rimuljo Hendradi Risky Wahyuningsih Sa'idah, Andini Safitri, Lensa Rosdiana Salma Bethari Andjani Sumarto Salsabila, Fatiha Nadia Sa’idah Zahrotul Jannah Sediono, Sediono Sentosa, Martha Ayu Setyawan, Muhammad Daffa Bintang Shalwa Oktavrilia Kusuma Siagian, Kimberly Maserati Sihite, Rivaldi Sihotang, Raja Van Den Bosch Siti Maghfirotul Ulyah Sugha Faiz Al Maula Suliyanto Suliyanto Suliyanto Suwarno, Michelle Adelia Syaugi Sungkar, Salman Teguh Susanto Teguh Susanto Tiani Wahyu Utami Trisa, Nadya Lovita Hana Ubadah, Mohammad Noufal Valida, Hanny Verina Tita Nabila Victory, Johanna Tania VITA FIBRIYANI Wahyuli, Diana Widyawati, Ayu Wieldyanisa, Ezha Easyfa Wulandari, Indana Zulfa Yan Dwi Zhafira, Azizah Atsariyyah