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All Journal Kontinu: Jurnal Penelitian Didaktik Matematika MUST: Journal of Mathematics Education, Science and Technology Jurnal SOLMA BAREKENG: Jurnal Ilmu Matematika dan Terapan JTAM (Jurnal Teori dan Aplikasi Matematika) Sainmatika: Jurnal Ilmiah Matematika dan Ilmu Pengetahuan Alam Jurnal Saintika Unpam : Jurnal Sains dan Matematika Unpam Dinasti International Journal of Education Management and Social Science Pelita Eksakta Abdi: Jurnal Pengabdian dan Pemberdayaan Masyarakat InPrime: Indonesian Journal Of Pure And Applied Mathematics Jurnal Riset Pembelajaran Matematika Sekolah Jurnal Statistika dan Aplikasinya Euler : Jurnal Ilmiah Matematika, Sains dan Teknologi International Journal of Progressive Mathematics Education MATHunesa: Jurnal Ilmiah Matematika International Journal of Applied Science and Sustainable Development (IJASSD) Prosiding Seminar Nasional Pengabdian Kepada Masyarakat Journal of General Education and Humanities Pattimura International Journal of Mathematics (PIJMath) JMT (Jurnal Matematika dan Terapan) Parameter: Jurnal Matematika, Statistika dan Terapannya BAKTI : Jurnal Pengabdian Kepada Masyarakat E-Jurnal Matematika
Vera Maya Santi
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Damped Trend Exponential Smoothing and Holt-Winters in Forecasting the Number of Airplane Passengers at Kualanamu Airport Binoto, Rustham Michael; Sudarwanto, Sudarwanto; Santi, Vera Maya
Pattimura International Journal of Mathematics (PIJMath) Vol 4 No 1 (2025): Pattimura International Journal of Mathematics (PIJMath)
Publisher : Pattimura University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/pijmathvol4iss1pp29-40

Abstract

Airplanes are one of the most frequently chosen modes of transportation by Indonesians today. Kualanamu Airport is one of the busiest airports in terms of the number of passengers. The number of airplane passengers often fluctuates, increasing and decreasing, so an analysis method is required to predict the number of passengers. This study uses the Double Exponential Smoothing Damped Trend and Multiplicative Holt-Winters models. The number of Kualanamu Airport domestic airplane passengers from January 2006 to December 2023 was used as research data. The best model is then used to forecast the number of Kualanamu Airport domestic airplane passengers for 12 periods from the last data used. The results showed that the Multiplicative Holt-Winters model with smoothing parameters and obtained smaller (Mean Absolute Error) MAE and (Mean Square Error) MSE values of 21415.556 and 961525264.508, compared to the Double Exponential Smoothing Damped Trend model with smoothing parameters,, and which obtained MAE and MSE values of 23612.461 and 1061042411.507 in predicting the number of domestic aircraft passengers at Kualanamu Airport. Forecasting accuracy for the next 12 periods using Holt-Winters Exponential Smoothing produces a MAPE value of 9.2%. It shows the accuracy of forecasting in the very good category.
PENCAPAIAN SDGs: LITERASI DATA STATISTIK POTENSI DESA DI KELURAHAN KAMPUNG RAWA, JAKARTA PUSAT Bagus Sumargo; Suyono; Dian Handayani; Ria Arafiyah; Nilam Novita Sari; Vera Maya Santi
Prosiding Seminar Nasional Pengabdian Kepada Masyarakat Vol. 6 No. 1 (2025): PROSIDING SEMINAR NASIONAL PENGABDIAN KEPADA MASYARAKAT - SNPPM2025
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat Universitas Negeri Jakarta

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Abstract

Abstrak Program Desa Cantik (Cinta Statistik) bertujuan untuk meningkatkan literasi data serta kemampuan aparat kelurahan, dan masyarakat dalam mengelola serta memanfaatkan data statistik secara mandiri dan sistematis. Sehubungan dengan hal ini, kami hadir di Kelurahan Kampung Rawa, Jakarta pusat dalam progam pengabdian kepada masyarakat. Kami sebagai civitas akademika terpanggil untuk melaksanakan Tri Dharma Perguruan Tinggi yaitu sesuai tujuan Sustainable Development Goals SDGs Nomor 4 yaitu pendidikan berkualitas dan Nomor 17 yaitu Kemitraan untuk mencapai tujuan. Pendidikan berkualitas dalam rangka memberikan literasi tentang data statistik – khususnya data PODES potensi Desa. Abstract The Beautiful Village (Love Statistics) program aims to improve data literacy and the ability of village officials and communities to manage and utilize statistical data independently and systematically. In this regard, we are present in Kampung Rawa Village, Central Jakarta, as part of a community service program. As academics, we are called to implement the Tri Dharma of Higher Education, in accordance with Sustainable Development Goals (TPB) Number 4, namely quality education, and Number 17, Partnership to Achieve Goals. Quality education aims to provide statistical data literacy—specifically PODES data regarding village potential. The statistical data literacy activity was held on July 15, 2025, with 19 participants: 2 village officials, 12 Regional Community members, and 5 Dasawisma cadres (Village Community Empowerment). The effectiveness of the training was evaluated through analysis of pre- and post-test results, which consisted of 10 statements with "Yes" and "No" answer options. The analysis was conducted using the McNemar test. The results of the pre- and post-test evaluations showed a significant increase in participant understanding, as confirmed by analysis using the McNemar test. Most participants also stated that the material presented was easy to understand, applicable, and useful for supporting data management at the sub-district level. Keywords: Beautiful Village, Village Potential, Statistical Data Literacy; McNemar; Improvements
Bivariate Binary Logistic Regression Analysis for Modeling Educational Level and Employment Status in Central Java Santi, Vera Maya; Ridana, Farah Fadhilah; Sumargo, Bagus
InPrime: Indonesian Journal of Pure and Applied Mathematics Vol. 7 No. 2 (2025)
Publisher : Department of Mathematics, Faculty of Sciences and Technology, UIN Syarif Hidayatullah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15408/k25zyf65

Abstract

Education and employment are two essential components of human development, yet studies that simultaneously examine both outcomes in the context of Central Java remain limited. This research makes a novel contribution by applying bivariate binary logistic regression to jointly model educational attainment and employment status, an approach that has not been previously used for the Central Java population. Using 3,874 observations from the 2024 National Labor Force Survey (Sakernas), the study incorporates two binary response variables and ten predictors to capture the interdependence between education and labor market outcomes. The independence test confirms a significant association between the two responses, supporting the need for a joint modeling framework. Parameter estimation using the Maximum Likelihood method, followed by partial and simultaneous likelihood ratio testing, reveals that marital status and type of institution significantly and simultaneously affect both educational attainment and employment status. The final model achieves classification accuracies of 85.932% and 80.356%, demonstrating strong predictive performance. This study contributes to the literature by presenting an integrated statistical approach that enhances our understanding of how sociodemographic and institutional factors jointly influence human capital and labour participation in Central Java. Keywords: Educational level; Employment status; Bivariate binary logistic regression; Maximum Likelihood method.   Abstrak Pendidikan dan pekerjaan adalah dua komponen penting dari pembangunan manusia, namun studi yang secara bersamaan memeriksa kedua hasil dalam konteks Jawa Tengah masih terbatas. Penelitian ini memberikan kontribusi baru dengan menerapkan regresi logistik biner bivariat untuk memodelkan bersama pencapaian pendidikan dan status pekerjaan, suatu pendekatan yang belum pernah digunakan sebelumnya untuk populasi Jawa Tengah. Dengan menggunakan 3.874 observasi dari Survei Angkatan Kerja Nasional (Sakernas) 2024, studi ini menggabungkan dua variabel respons biner dan sepuluh prediktor untuk menangkap saling ketergantungan antara pendidikan dan hasil pasar tenaga kerja. Uji independensi mengonfirmasi hubungan yang signifikan antara kedua respons, yang mendukung perlunya kerangka kerja pemodelan bersama. Estimasi parameter menggunakan metode Kemungkinan Maksimum, diikuti oleh pengujian rasio kemungkinan parsial dan simultan, mengungkapkan bahwa status perkawinan dan jenis lembaga secara signifikan dan simultan memengaruhi pencapaian pendidikan dan status pekerjaan. Model akhir mencapai akurasi klasifikasi sebesar 85,932% dan 80,356%, yang menunjukkan kinerja prediktif yang kuat. Penelitian ini memberikan kontribusi terhadap literatur dengan menyajikan pendekatan statistik terpadu yang meningkatkan pemahaman kita tentang bagaimana faktor sosiodemografi dan kelembagaan bersama-sama memengaruhi modal manusia dan partisipasi tenaga kerja di Jawa Tengah. Kata Kunci: Tingkat pendidikan; Status pekerjaan; Regresi logistik biner bivariat; Metode Kemungkinan Maksimum. 2020MSC: 62J12, 62P20.
PELATIHAN ANALISIS STATISTIK MENGGUNAKAN WEBSITE INTERAKTIF UNTUK MENDUKUNG PENGAMBILAN KEPUTUSAN BERBASIS DATA PENDIDIKAN BAGI GURU SMA MATEMATIKA DI KABUPATEN SUKABUMI Siregar, Dania; Suyono; Vera Maya Santi; Auria Yusrin Fathya; Sinta Rahmadani; Jaisy Aulia; Maulida Audia Firdaus
Prosiding Seminar Nasional Pengabdian Kepada Masyarakat Vol. 6 No. 1 (2025): PROSIDING SEMINAR NASIONAL PENGABDIAN KEPADA MASYARAKAT - SNPPM2025
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat Universitas Negeri Jakarta

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Abstract

Tantangan utama dalam pengambilan keputusan pendidikan adalah keterbatasan literasi statistik dan keterampilan guru dalam mengolah data, terutama melalui teknologi interaktif. Hal ini terlihat dari kuesioner pra-pelatihan, di mana sebagian besar guru menyatakan keraguan atau ketidaksetujuan terhadap pengetahuan mereka, dan mayoritas belum pernah menggunakan situs web interaktif untuk analisis statistik. Program layanan masyarakat ini bertujuan untuk meningkatkan literasi statistik guru melalui pelatihan analisis data menggunakan situs web interaktif berbasis R-Shiny. Pelatihan dilaksanakan pada 13 Agustus 2025, dengan peserta terdiri dari guru matematika SMA di Kabupaten Sukabumi, bekerja sama dengan MGMP Matematika SMA Sukabumi sebagai mitra layanan masyarakat. Materi pelatihan mencakup statistik deskriptif, analisis inferensial, pengujian hipotesis, dan regresi. Evaluasi pasca-pelatihan menunjukkan peningkatan yang signifikan: lebih dari 80% peserta setuju atau sangat setuju bahwa materi pelatihan sistematis, mudah dipahami, dan relevan, serta aplikasi tersebut mudah diakses dan ramah pengguna. Selain itu, 75% peserta sangat setuju bahwa mereka memperoleh pengetahuan baru yang berguna untuk pengambilan keputusan berbasis data dalam pendidikan. Kesimpulannya, pelatihan berbasis teknologi interaktif secara efektif meningkatkan kompetensi guru, memperkuat motivasi mereka, dan menumbuhkan budaya pengambilan keputusan berbasis data di sekolah. Translated with DeepL.com (free version) Abstract The main challenge in educational decision-making is the limited statistical literacy and skills among teachers in processing data, particularly through interactive technology. This was evident from the pre-training questionnaire, in which most teachers expressed doubt or disagreement about their knowledge, and the majority had never used an interactive website for statistical analysis. This community service program aimed to enhance teachers’ statistical literacy through training in data analysis using an R-Shiny-based interactive website. The training was conducted on August 13, 2025, with participants consisting of senior high school mathematics teachers in Sukabumi Regency, in collaboration with the Sukabumi Senior High School Mathematics MGMP as the community service partner. The training materials covered descriptive statistics, inferential analysis, hypothesis testing, and regression. Post-training evaluation showed a significant improvement: more than 80% of participants agreed or strongly agreed that the materials were systematic, easy to understand, and relevant, and that the application was accessible and user-friendly. Furthermore, 75% of participants strongly agreed that they gained new knowledge useful for data-driven decision-making in education. In conclusion, interactive technology-based training effectively improved teachers’ competence, strengthened their motivation, and fostered a data-driven decision-making culture in schools.
PCR DAN PLSR ALGORITMA NIPALS DALAM MENANGANI MULTIKOLINIERITAS PADA PREVALENSI STUNTING DI NUSA TENGGARA TIMUR NATALIE EFRATA SUSANTI; VERA MAYA SANTI; DEVI EKA WARDANI
E-Jurnal Matematika Vol. 14 No. 4 (2025)
Publisher : Mathematics Department, Faculty of Mathematics and Natural Sciences, Udayana University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/MTK.2025.v14.i04.p491

Abstract

Nutritional problems contribute to 50% of deaths among children under five, particularly in low- and middle-income countries. One of the most common issues in Indonesia is stunting, a condition where a child's height falls below the standard for their age. In 2022, East Nusa Tenggara (NTT) recorded the highest stunting prevalence in Indonesia at 35.3%. However, quantitative statistical analyses of its contributing factors in NTT remain limited. This study aims to compare partial least squares regression (PLSR) using the NIPALS algorithm with principal component regression (PCR) in addressing multicollinearity. The secondary data were obtained from the 2022 Indonesian Nutrition Status Survey (SSGI), published by the Ministry of Health and BPS NTT, consisting of one response variable and ten predictor variables. Results showed that the PLSR model outperforms PCR, with an adjusted R² of 0.741 compared to 0.322. The superiority of PLSR is also evident from its lower RMSE and MAE values (2.783 and 1.910) compared to PCR (4.742 and 3.346). PLSR identified five significant predictors: average daily protein consumption per capita, number of children receiving DPT and HB immunizations, Human Development Index, percentage of households with access to safe drinking water, and number of people living in poverty.
PELATIHAN PENGENALAN ALGORTIMA DAN PEMROGRAMAN VISUAL SISWA SMP DENGAN SCRATH Faroh Ladayya; Dian Handayani; Siti Rohmah Rohimah; Nilam Novita Sari; Vera Maya Santi; Erin Naudy Kemalasari; Zahra Ayu Rahmadani
Prosiding Seminar Nasional Pengabdian Kepada Masyarakat Vol. 6 No. 1 (2025): PROSIDING SEMINAR NASIONAL PENGABDIAN KEPADA MASYARAKAT - SNPPM2025
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat Universitas Negeri Jakarta

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Abstract

Abstrak Perkembangan teknologi di abad ke-21 menuntut generasi muda untuk memiliki keterampilan berpikir komputasional, pemecahan masalah, dan dasar pemrograman. Namun, di daerah pedesaan seperti Kabupaten Sukabumi, pemanfaatan teknologi dalam proses pembelajaran masih terbatas. Kegiatan pengabdian ini bertujuan untuk mengenalkan dasar-dasar algoritma dan pemrograman visual kepada siswa SMP Negeri 1 Kabupaten Sukabumi melalui media Scratch. Scratch adalah software pemrograman berbasis visual yang mudah digunakan bagi pemula, serta mampu menstimulasi kreativitas siswa dalam membuat animasi dan permainan sederhana. Kegiatan ini sejalan dengan Sustainable Development Goals (SDGs) pada poin Quality Education dengan membekali siswa keterampilan algoritma dan pemrograman dasar agar lebih siap menghadapi tantangan era digital. Metode pelaksanaan kegiatan meliputi penyampaian materi, serta praktik langsung menggunakan modul pembelajaran yang telah disusun. Hasil kegiatan menunjukkan bahwa siswa antusias mengikuti pelatihan dan mampu memahami konsep dasar algoritma melalui praktik pemrograman visual. Analisis kuesioner pendahuluan dan akhir menunjukkan adanya peningkatan motivasi, wawasan, serta keterampilan siswa dalam memahami algoritma dan pemrograman visual. Dengan demikian, pelatihan ini berkontribusi positif dalam memberikan bekal awal literasi digital dan pemrograman bagi siswa SMP, yang diharapkan dapat menjadi fondasi untuk pembelajaran teknologi lebih lanjut. Abstract The development of technology in the 21st century requires young generations to possess computational thinking, problem-solving skills, and basic programming literacy. However, in rural areas such as Sukabumi Regency, the integration of technology into the learning process remains limited. This community service activity aims to introduce the fundamentals of algorithms and visual programming to students at SMP Negeri 1 Sukabumi Regency, through the use of Scratch. Scratch is a visual-based programming software that is easy for beginners to use and encourages students’ creativity in creating simple animations and games. This activity aligns with the Sustainable Development Goals (SDGs), particularly Goal 4: Quality Education, by equipping students with basic algorithmic and programming skills to prepare them for the challenges of the digital era. The implementation method included material delivery, and hands-on practice using a specially designed learning module. The results showed that students were enthusiastic during the training and successfully understood basic algorithmic concepts through visual programming practice. Analysis of pre- and post-questionnaires indicated an increase in students’ motivation, knowledge, and skills in understanding algorithms and visual programming. Therefore, this training contributed positively by providing an initial foundation in digital literacy and programming for junior high school students, which is expected to serve as a stepping stone for more advanced technology learning in the future.
LINEAR MIXED MODEL-LASSO WITH MLE AND REML ESTIMATION ON POVERTY DATA IN JAVA ISLAND Santi, Vera Maya; Indriana, Devi; Ladayya, Faroh; Tonah
Jurnal Statistika dan Aplikasinya Vol. 9 No. 2 (2025): Jurnal Statistika dan Aplikasinya
Publisher : LPPM Universitas Negeri Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21009/JSA.09202

Abstract

Poverty in Indonesia, especially in Java, remains a major challenge despite the island being the economic and political centre of the country. The government has made many efforts but has not been effective in overcoming poverty. The hierarchical structure of poverty data may cause higher-level clusters to be random effect. One approach that can be used to represent the relationship between the poverty rate in each regency/city in Java and the factors that influence it with the province as a random effect is a linear mixed model (LMM). The number of factors that can affect poverty results in multicollinearity. The application of LASSO is used in this study to overcome multicollinearity, select, and generate variables that are significant to poverty in Java. The data used in this study consists of 85 regencies and 34 cities in Java Island involving 20 independent variables. The results show that the factors that influence the poverty rate are average years of schooling, non-food expenditure, number of households with housing assets owned, percentage of households with a dirt floor, and percentage of households with PLN lighting. The LMM-LASSO is a linear model augmented with a LASSO penalty function to address multicollinearity and incorporates random effects into the model. This approach is suitable for modeling the poverty rate, as indicated by its smaller AIC and BIC values compared to the conventional linear mixed model. In addition, based on the ICC value, the province as a random effect contributes significantly to the variability of the data at the district/city observation level in Java Island.
Profile Of Critical Thinking Errors Of Junior High School Students Based On Facione's Theory In Solving Problems On SLETV Material Barus, Janna Sri Bina Br; Makmuri, Makmuri; Santi, Vera Maya
JURNAL PENDIDIKAN MATEMATIKA Vol. 10, No. 1: May 2026
Publisher : Universitas Islam Sultan Agung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30659/kontinu.10.1.1-17

Abstract

This study aims to describe the profile of mathematical critical thinking errors among junior high school students, based on the components of Facione's Theory (Interpretation, Analysis, Evaluation, and Inference), in the context of solving Systems of Linear Equations in Two Variables (SLETV) problems. Specifically, this study cross-mapped Facione's cognitive failures with observed procedural errors, analysing them using the Newman Error Analysis framework (Reading, Understanding, Transformation, Process Skills, and Final Answer Writing). This study uses a qualitative method. This study found that students' critical thinking skills were generally low, with 42.05% in the low category. The highest cognitive failure point was located in the Analysis, Evaluation, and Inference domain. Triangulation analysis showed that weaknesses in Facione's Analysis Skills were the leading cause of the high frequency of Newman Transformation Errors, reflecting students' inability to model contextual problems as mathematical models. This study provides a more precise diagnostic basis for designing targeted learning interventions to optimise students' higher-order cognitive skills.Keywords: critical thinking; indicators Facione; procedural errors; SLETV.
Analysis of Esa Unggul University Students’ Preferences for Leadership Seminars Using Conjoint Analysis Hastuti, Lili; Widiastuti, Widiastuti; Ichsan, Muhammad; Santi, Vera Maya
Journal of General Education and Humanities Vol. 5 No. 1 (2026): February
Publisher : MASI Mandiri Edukasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58421/gehu.v5i1.928

Abstract

This research addresses the need to understand student preferences in leadership seminar design at Esa Unggul University and aims to identify the seminar attributes that most strongly influence participation decisions. A quantitative approach was applied using Conjoint Analysis, involving 100 active students from various study programs who are members of the Student Executive Board (BEM). Data were gathered through structured questionnaires and analyzed to estimate utility scores and relative importance values across five attributes: seminar topic, speaker, delivery format, participation cost, and benefits. The findings show that students favor seminars on Leadership and Entrepreneurship, delivered by expert lecturers, implemented in a hybrid format, priced between IDR 20,000 and 50,000, and offering certificates combined with SKP or competency recognition. Importance value analysis indicates that speaker credibility, cost considerations, and topic relevance are the dominant factors shaping student preferences. Model validation results demonstrate strong predictive accuracy, with a Pearson correlation of 0.815 and Kendall’s tau of 0.407, both statistically significant. These results provide an empirical basis for universities and event organizers to develop leadership seminars that better align with student expectations, thereby improving engagement and program effectiveness.
Contribution of Educational and Economic Factors to HDI Scores of Districts/Cities in East Java: A Multiple Linear Regression Study Septio, Giovani; Hatami, Alifa Syauqi; Luthfiani, Luthfiani; Santi, Vera Maya
Dinasti International Journal of Education Management and Social Science Vol. 7 No. 3 (2025): Dinasti International Journal of Education Management and Social Science (Febru
Publisher : Dinasti Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38035/dijemss.v7i3.6066

Abstract

The Human Development Index (HDI) is a strategic indicator that reflects the quality of life, achievements of society, particularly in the domains of education and economy. This study aims to analyze the contribution of educational and economic factors to the variation in HDI scores across districts and municipalities in East Java Province. A quantitative approach was employed using multiple linear regression analysis. The independent variables include the number of senior high schools, the student–teacher ratio in senior high schools, the Net Enrollment Rate (NER) at the senior high school level, the poverty rate, and per capita expenditure. The dependent variable is the Human Development Index (HDI). Data were obtained from the 2023 publication of Statistics Indonesia (BPS), covering 38 districts/municipalities in East Java Province. The results indicate that the educational and economic factors significantly contributing to HDI are the NER, poverty rate, and per capita expenditure, while the number of senior high schools and student–teacher ratio show no significant contribution. The regression model strongly explains the proportion of HDI variance with a high R-square value, making it a reliable basis for formulating regional development policies. This study underscores that interventions aimed at improving educational attainment and strengthening the local economy are key strategies for accelerating human development in East Java. Although the multiple linear regression model used in this study shows strong explanatory power in identifying the educational and economic determinants of HDI across districts and cities in East Java, this model assumes independence between observation units and still cannot explain other indicators that influence HDI in detail. Therefore, future research on HDI indicators could utilise a multilevel or linear mixed modelling framework to achieve a more robust analytical level that could assist policymakers in formulating policies.
Co-Authors Abi Wiyono Adzima, Khaola Rachma Afifah Nur Mutia Alwansyah, Muhammad Arib Ambarwati, Defina Arafiyah, Ria Auria Yusrin Fathya Bagus Sartono Bagus Sumargo Bagus Sumargo Bagus Sumargo, Bagus Baihaqi, Aulia Barus, Janna Sri Bina Br Binoto, Rustham Michael Contillo, Gerry Dania Siregar Dania Siregar Devi Eka Wardani Dian Handayani Dwi Antari Wijayanti Ellis Salsabila, Ellis Erin Naudy Kemalasari Fadya, Khansa Salsabil Fanya Izmi Hawa Faoza Saaroh Fariani Hermin Faroh Ladayya Gatri Eka Kusumawardhani Gusnia, Farida Hashifah, Zahrah Hatami, Alifa Syauqi Herlina Nofita Ibnu Hadi Indahwati Indiyah, Fariani Hermin Indriana, Devi Jadid Irtakhoiri Jaisy Aulia Kamil, Adine Ihsan Kamilia, Rifa Khoirunnisa Koeshella, Ajeng Ladayya, Faroh Lili Hastuti Lina Nafisah Lukman El Hakim Luthfiani, Luthfiani Mahardika, Baihaqy Mahatma, Yudi Makmuri Makmuri Maulida Audia Firdaus Meidianingsih, Qorry Meila Nadya Muhammad Alief Ghifari Muhammad Ichsan Muhammad Rafli Muzakki Tamami NATALIE EFRATA SUSANTI Nilam Novita Sari Ningsih, Nia Rahayu Novia Sucy Aristawidya Nurkhotimah, Siti Fadilah Pinta Deniyanti Sampoerno Pinta Deniyanti Sampoerno Prima Riyani Puteri, Syafa Marisha Putri, Kinanti Anindia Rahayuningsih, Yuliana Rahfa Qur’aniyatin Dhuha Ria Arafiyah Riam Nurussilmah Rianiati Monica Ridana, Farah Fadhilah Rifqy Marwah Akhsanti Riska Agustin Riyantobi, Ariq Muammar Safira Datu Sahila, Sahiba Sarwa, Amira Basyila Septio, Giovani Sinta Rahmadani Siregar, Dania Siti Rohmah Rohimah Sudarwanto Sudarwanto, Sudarwanto SUYONO Suyono Suyono Suyono Suyono Syarifah Ayu Angela Syifa Azzahra Tamami, Muzakki Tian Abdul Aziz Tiara Husnul Khotimah Tonah Tri Murdiyanto Ul Aliyah, Ayda Syifa Wahyu, Rahadian Wardani Rahayu WIDIASTUTI - Widyanti Rahayu Widyanti Rahayu Widyanti Rahayu Widyanti Rahayu Widyanti Rahayu Wilsen Wilsen Zahra Ayu Rahmadani Zahrah Hashifah