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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) 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) JURPIKAT (Jurnal Pengabdian Kepada Masyarakat) Enthusiastic : International Journal of Applied Statistics and Data Science Seminar Nasional Hasil Riset dan Pengabdian (SNHRP) SAINSMAT: Jurnal Ilmiah Ilmu Pengetahuan Alam Aurelia: Jurnal Penelitian dan Pengabdian Masyarakat Indonesia Indonesian Vocational Research Journal Jurnal Pendidikan Matematika PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON DATA SCIENCE AND OFFICIAL STATISTICS Jurnal Pengabdian Nasional (JPN) Indonesia Feelings: Journal of Counseling and Psychology Seminar Nasional Riset dan Teknologi (SEMNAS RISTEK) 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 Jurnal Riset Sosial Humaniora dan Pendidikan
Nur Chamidah
Departemen Matematika, Fakultas Sains Dan Teknologi, Universitas Airlangga
Agriculture, Biological Sciences & Forestry Arts Humanities Biochemistry, Genetics & Molecular Biology Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Public Health Social Sciences Transportation Other

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Multimodal deep learning from sputum image segmentation to classify Mycobacterium tuberculosis using IUATLD assessment Saurina, Nia; Chamidah, Nur; Rulaningtyas, Riries; Aryati, Aryati
Bulletin of Electrical Engineering and Informatics Vol 14, No 2: April 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v14i2.9250

Abstract

Tuberculosis (TB) continues to be a major global health issue, especially in areas with limited resources where diagnostic tools are often insufficient. Traditional TB detection methods are slow and lack sensitivity, particularly for early-stage or low bacterial load cases. This study introduces a new multimodal deep learning model that integrates sputum image segmentation across RGB, hue, saturation, and value (HSV), and CIELAB color channels, using the YOLOv8 model for real-time detection and segmentation. The model uses the International Union Against Tuberculosis and Lung Disease (IUATLD) grading scale for accurate Mycobacterium tuberculosis (MTB) classification. Our approach shows high accuracy (92.24%) and precise forecasting (mean absolute percent error (MAPE) of 0.23%), greatly enhancing diagnostic speed and reliability. This research offers a novel method for classifying MTB using a multimodal deep learning model that integrates sputum image segmentation across RGB, HSV, and CIELAB color channels. By using the YOLOv8 model for real-time bounding box detection and segmentation, and the IUATLD grading scale for classification, our method achieves high accuracy and precision in identifying TB bacteria. Our findings indicate that this multimodal deep learning approach significantly improves diagnostic accuracy and speed, providing a reliable tool for early TB detection.
Comparison of Logistic Regression and Support Vector Machine in Predicting Stroke Risk Safitri, Lensa Rosdiana; Chamidah, Nur; Saifudin, Toha; Firmansyah, Mochammad; Alpandi, Gaos Tipki
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.v7i2.20420

Abstract

The issue of health is the third goal of Indonesia's Sustainable Development Goals (SDGs) which is state to ensuring a healthy life and promoting prosperity for all people at all ages. One of the SDGs’s concerns is deaths caused by non-communicable diseases (NCDs) including strokes. One prevention that can be done is by making a prediction of stroke for early detection. There are various methods available which are statistical methods and machine learning methods. In this research work, we aim to compare the two methods based on statistical method and machine learning method on stroke risk prediction. The data used in this research is primary data from Universitas Airlangga Hospital (RSUA) from June until August 2023. In this research, we compare the statistical method that is Logistic Regression (LR), and the machine learning method which is Support Vector Machine(SVM). We use Phyton to analyze all methods in this research. The results show that SVM with Radial Basis Kernel is better than LR in predicting stroke risk based on three goodness criteria namely sensitivity, F-1 score and accuracy where these three goodness criteria values of SVM are greater than those of LR.
Prediksi Risiko Gagal Bayar Kredit Kepemilikan Rumah dengan Pendekatan Metode Random Forest Ulandari, Kartini Putri; Chamidah, Nur; Kurniawan, Ardi
Sainsmat : Jurnal Ilmiah Ilmu Pengetahuan Alam Vol 13, No 2 (2024): September
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Negeri Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/sainsmat132630212024

Abstract

Home Ownership Credit (KPR) is a credit facility provided by banks to individual customers who want to buy or repair a house. KPR also has problems with credit payment failures. This research aims to predict the risk of fraud on home ownership loans by applying the Random Forest method. Random Forest (RF) is a method that can increase accuracy results in generating attributes for each node which is done randomly. Based on the analysis results, it was found that the model with the smallest classification error was using mtry 2 and ntree 50 using a combination of training and testing data of 60%:40%. By applying the random forest algorithm, we obtained an accuracy rate of 84.75% with an Area Under the Curve (AUC) value of 84.32%, which is included in the very good classification category.
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.
Respon Pengemudi Ojek Online terhadap Gerakan Stop Tot tot wuk wuk sebagai Wujud Kesadaran Toleransi di Jalan Raya (Studi Kasus di Kota Surabaya) Nur Azizah Rahayu Ningsih; Nur Chamidah; Sasmia Desinta Wulandari; Siti Maizul Habibah
Jurnal Ilmu Sosial dan Humaniora Vol. 1 No. 4 (2025): OKTOBER-DESEMBER
Publisher : Indo Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63822/t7seaa63

Abstract

The roadway, as a shared public space, requires all users to develop awareness, tolerance, and adherence to traffic regulations. The response of online motorcycle taxi drivers to the stop tot tot wuk wuk movement represents a form of articulated tolerance awareness in road interactions, particularly within the socio-traffic context of Surabaya City. This study employs a descriptive qualitative approach with a case study design. Data were collected through semi-structured interviews and non-participant observations. The analysis process utilized the Miles and Huberman model, while data validity was ensured through technique triangulation. The findings indicate that the stop tot tot wuk wuk movement is perceived by drivers as a critique of the improper use of sirens, which often generates psychological pressure, discomfort, and unequal relations among road users. Although online motorcycle taxi drivers frequently choose to yield for the sake of safety and traffic flow, they also experience ethical imbalance in the use of public road space. This phenomenon illustrates that tolerance on the road has not yet matured as a shared moral consciousness. Thus, the movement serves not only as an expression of social critique but also as a reflective moment to strengthen the values of tolerance and traffic ethics.
Analisis Hasil Belajar Siswa Kelas IX pada Pembelajaran Matematika Menggunakan Alat Peraga dalam Program Asistensi Mengajar dengan Uji Paired t-Test Aulia, Niswa Faizah; Nur Chamidah
Jurnal Pendidikan Matematika Vol. 3 No. 1 (2025): November
Publisher : Indonesian Journal Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47134/ppm.v3i1.2296

Abstract

Penelitian ini bertujuan untuk mengkaji pengaruh penggunaan alat peraga matematika dalam kegiatan Asistensi Mengajar terhadap hasil belajar siswa kelas IX di SMP Negeri 45 Surabaya. Penelitian ini menggunakan pendekatan kuantitatif dengan desain satu kelompok pre-test dan post-test. Subjek penelitian terdiri atas 45 siswa kelas IX yang mengikuti pembelajaran matematika dengan dukungan alat peraga sebagai media pembelajaran. Pengumpulan data dilakukan melalui pemberian tes awal (pre-test) dan tes akhir (post-test) untuk mengukur perubahan hasil belajar siswa sebelum dan setelah perlakuan. Data yang diperoleh dianalisis menggunakan uji normalitas, uji korelasi, dan uji paired samples t-test untuk mengetahui perbedaan rata-rata hasil belajar siswa. Hasil penelitian menunjukkan adanya peningkatan nilai rata-rata hasil belajar siswa setelah penerapan pembelajaran matematika menggunakan alat peraga. Hasil uji paired samples t-test menunjukkan bahwa terdapat perbedaan yang signifikan antara nilai pre-test dan post-test siswa, yang mengindikasikan bahwa perlakuan yang diberikan memberikan pengaruh positif terhadap hasil belajar. Temuan ini menunjukkan bahwa penggunaan alat peraga matematika mampu membantu siswa memahami konsep secara lebih konkret, meningkatkan keterlibatan siswa dalam proses pembelajaran, serta menciptakan suasana belajar yang lebih aktif dan interaktif. Dengan demikian, dapat disimpulkan bahwa penggunaan alat peraga matematika dalam kegiatan Asistensi Mengajar efektif dalam meningkatkan hasil belajar siswa kelas IX di SMP Negeri 45 Surabaya.
Penguatan Konsep Diri dan Pelatihan Konseling Dasar Sebagai Pencegahan Bullying di MI Maarif NU 1 Gunung Lurah Fakih Hamdani; Galih Yoga Santiko; Ahmad Fauzi; Nur Chamidah; Kuni Safingah
JURPIKAT (Jurnal Pengabdian Kepada Masyarakat) Vol. 7 No. 1 (2026)
Publisher : Politeknik Piksi Ganesha Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37339/jurpikat.v7i1.2767

Abstract

Bullying in elementary schools has become a serious issue as it affects students’ social and emotional development. This community service focused on bullying prevention by enhancing students’ self-awareness and teachers’ empathetic communication skills. The objective was to build a healthy, safe school ecosystem that supports character development. The program was implemented at MI Ma’arif NU 1 Gunung Lurah using the Participatory Action Research (PAR) approach, involving the school community actively. The strategy included socialization, self-analysis training for students, basic counseling training for teachers, and structured mentoring. The results showed that students were able to recognize themselves, express emotions, and commit to rejecting bullying, while teachers successfully applied empathetic communication and developed simple counseling modules. The impact of this program was evident in the creation of a reflective culture in the classroom through reflection corners, as well as improved openness in interactions between teachers and students.
Penanganan Ketidakseimbangan Data pada Pemodelan Risiko Diabetes Tipe 2 Menggunakan SMOTE-MARS Fizkadana, Canada Mewa; Chamidah, Nur; Kurniawan, Ardi; Siregar, Naufal Ramadhan Al Akhwal
Semnas Ristek (Seminar Nasional Riset dan Inovasi Teknologi) Vol 10, No 1 (2026): SEMNAS RISTEK 2026
Publisher : Universitas Indraprasta PGRI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30998/semnasristek.v10i1.8891

Abstract

Diabetes Melitus Tipe 2 (DMT2) merupakan tantangan kesehatan kritis di Indonesia, namun pemodelan faktor risikonya sering terhambat oleh ketidakseimbangan kelas di mana individu sehat melebihi jumlah kasus positif. Penelitian ini memodelkan risiko DMT2 menggunakan pendekatan hybrid yang menggabungkan Synthetic Minority Over-sampling Technique (SMOTE) dan Multivariate Adaptive Regression Splines (MARS). Penelitian ini menggunakan data medis dengan ketidakseimbangan awal 62% sehat dan 38% kasus DMT2. SMOTE diterapkan untuk menyeimbangkan distribusi training, diikuti dengan pemodelan MARS untuk menangkap interaksi non-linear. Hasil penelitian menunjukkan bahwa model SMOTE-MARS secara signifikan mengungguli MARS standar, mencapai Akurasi 0,70 dan AUC 0,73, dibandingkan dengan AUC model standar yang hanya 0,458. Model optimal mengidentifikasi Berat Badan, Tinggi Badan, dan Konsumsi Gula sebagai prediktor utama. Secara spesifik, berat badan di bawah 48 kg teridentifikasi sebagai faktor protektif yang kuat (OR 0,22), sedangkan tinggi badan kurang dari 165 cm (OR 1,22) dan interaksi berat badan berlebih (>62 kg) dengan konsumsi gula (OR 1,12) merupakan faktor risiko signifikan. Tingginya nilai sensitivitas mengindikasikan bahwa model SMOTE-MARS sangat potensial digunakan sebagai instrumen deteksi dini untuk mengidentifikasi pasien yang berisiko tinggi terkena diabetes.
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.
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).
Co-Authors A Meylin Abdul Aziz Abidin, Qumadha Zaenal Afriani Agus Satmoko Adi Ahmad Fauzi Aisharezka, Mutiara Akbar, Aditya Syarifudin Al Farizi, Muhammad Fikry Al Hasri, Ilham Maulana Alda Fuadiyah Suryono 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 Anies Yulinda W Anisa Laila Azhar Any Tsalasatul Fitriyah Ardi Kurniawan Ardi Kurniawan Ardiyanto, Figo Surya Ariyawan, Jovansha Aryati Aryati Aulia, Niswa Faizah Auliyah, Nina Azizah, Khansa Azzen, Fiyadika Amalia Nurizah Baihaqi, Mochamad Baihaqi, Muhammad Rizaldy Baktiar Aris Belindha Ayu Ardhani Brenda Bunga Prasenda Budi Lestari Budi Lestari Budijono, Gabriella Agnes Christopher Andreas D Lestari Darmawan, Kezia Eunike Dhohirrobbi, Achmad Dhyana Venosia Dhyana Venosia Diah Puspita Ningrum Diana Ulya Dita Amelia Dita Amelia, Dita Dzuria Hilma Qurotu Ain Hilma Easyfa Wieldyanisa, Ezha Eko Tjahjono Elfhira Juli Safitri Fachrian, Muhammad Nadhil Faiza, Atikah Faizun, Nurin Fajrina, Sofia Fajrina, Sofia Andika Nur Fakih Hamdani Fania, Azzahra Farida Farida Fatmawati Fatmawati Fatmawati Fatmawati Fauziah, Nathania Feevrinna Yohannes Harianto Fibryan, Muhammad Hilmi FIRMANSYAH, MOCHAMMAD Fitri Syaharani, Amadea Fitri, Marfa Audilla Fitri, Marfa Audilla Fizkadana, Canada Mewa Galih Yoga Santiko Gaos Tipki Alpandi Halimatuzzahro, Fitria Hammami, Martha Sayyida Hariadi, Salsabila Niken Hendrawan, Ardana Tegar Herdianto, Muhammad Hendra Hidayat, Rizky Ismaul Uyun Horidah Horidah Huda, Mi'rojul I Nyoman Budiantara Insania Dewanty, Sanda Islamudin, Mohamad Mujahid IZZAH, NURUL Januarta, R. Arya Julianto, Agnes Happy Juniar, Muhammad Althof Kamiilah, Nadhira Safa Kamil, M. Aqil Zaidan Kamila, Yasmin Kinanti Hanugera Gusti Kuni Safingah 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 Maulidya, Utsna Rosalin MAYA MUSTIKA KARTIKA SARI, MAYA Mediani, Andini Putri Mediani, Andini Putri Melati Tegarina Mohamad David Hermawan Muhammad Falah El Fahmi Muhammad Fikry Al Farizi Mutiara Aisharezka Mutiara Arlisyah Putri Utami 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 Ramadhani, Azzah Nazhifa Wina 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 Sihite, Rivaldi Siregar, Naufal Ramadhan Al Akhwal Siti Maizul Habibah Slamet Muchsin Soewignjo, Steven Sofia Andika Nur Fajrina Subiyanto, Marcel Laverda Sufyan Ats Tsauri Sugha Faiz Al Maula Suliyanto Sunariyanto, Sunariyanto Suryono, Alda Fuadiyah Suryono, Alda Fuadiyah Suwarno Suwarno Syahputra, Bimo Okta Syifaun Nadhiro Teguh Susanto 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 Zhafira, Azizah Atsariyyah Zidni Ilmatun Nurrohmah