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All Journal Pedagogi: Jurnal Ilmu Pendidikan 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 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 Griya Journal of Mathematics Education and Application 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 Pattimura International Journal of Mathematics (PIJMath) IIJSE 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.
ANALYZING OPEN UNEMPLOYMENT RATE IN JAVA USING PENALIZED SPLINE NONPARAMETRIC REGRESSION Santi, Vera Maya; Ningsih, Nia Rahayu; Ladayya, Faroh
International Journal of Applied Science and Sustainable Development (IJASSD) Vol. 4 No. 2 (2022): International Journal of Applied Science and Sustainable Development (IJASSD)
Publisher : Lembaga Penelitian dan `Pengabdian Kepada Masyarakat (LPPM)

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Abstract

In regression analysis, there are three regression curve approach methods: parametric approach, semiparametric approach, and nonparametric approach. One of the estimation methods in nonparametric regression is spline regression with parameter estimation methods, namely smoothing, truncated, and penalized. Penalized spline estimation controls the smoothness of the curve so that the curve avoids stiffness and overfitting and does not require assumptions. This study aims to analyze the open unemployment rate in Java, which has the highest open unemployment rate in Indonesia, where studies using this approach have never been conducted. The study's results resulted in an additive Mean Square Error (MSE) of 4.137 with a coefficient of determination of 44.58%, indicating that explanatory variables of 44.58% could explain the open unemployment rate. Based on the parameter significance test, the factors that significantly effect the open unemployment rate are the dependency ratio, the GDP growth rate, senior high school gross enrollment, percentage of the poor population, and population growth rate.
Forecasting Indonesia’s Export Revenue through a Vector Autoregressive Exogenous Approach Sudarwanto, Sudarwanto; Puteri, Syafa Marisha; Santi, Vera Maya; Alwansyah, Muhammad Arib
JTAM (Jurnal Teori dan Aplikasi Matematika) Vol 10, No 2 (2026): April
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jtam.v10i2.36760

Abstract

The Vector Autoregressive with Exogenous Variables (VARX) model extends the conventional VAR framework by explicitly incorporating external macroeconomic drivers, offering a more structurally informed approach to export forecasting. This study contributes to the literature by introducing a disaggregated modeling strategy that treats oil and gas exports and non-oil and gas exports as separate endogenous components, an aspect that has been largely overlooked in previous studies on Indonesia’s export performance. By positioning VARX as a system-based forecasting tool rather than a purely statistical extension, this research provides an updated methodological perspective on export revenue analysis. Using monthly data from January 2015 to December 2024, this study evaluates several VARX specifications that integrate the rupiah–US dollar exchange rate and West Texas Intermediate (WTI) crude oil prices as exogenous variables. Model selection is conducted based on a combination of information criteria and forecasting performance indicators, leading to the identification of VARX(5,6) as the most suitable specification. The inclusion of exogenous variables is shown to substantially enhance predictive accuracy, confirming the relevance of external economic shocks in shaping Indonesia’s export revenue dynamics. Empirical results indicate that WTI oil prices exert a significant causal influence on export revenue, while the exchange rate effect becomes meaningful when jointly evaluated with oil prices and endogenous export components. The selected VARX(5,6) model demonstrates strong forecasting performance, achieving a MAPE of 5.60% and an nRMSE of 6.40%. From a policy standpoint, these findings suggest that export planning and stabilization policies should explicitly account for global oil price volatility and exchange rate interactions. The proposed VARX framework can therefore serve as a practical analytical tool for policymakers to anticipate short-term export fluctuations and design responsive trade and macroeconomic strategies under external uncertainty.
Peningkatan Kompetensi Guru melalui Pelatihan Pembuatan Infografis sebagai Media Pembelajaran Digital Interaktif Sari, Nilam Novita; Sumargo, Bagus; Santi, Vera Maya; Rahayu, Widyanti; Adzima, Khaola Rachma; Khotimah, Tiara Husnul; Sahila, Sahiba; Mahardika, Baihaqy; Fadya, Khansa Salsabil
Jurnal SOLMA Vol. 15 No. 1 (2026)
Publisher : Universitas Muhammadiyah Prof. DR. Hamka (UHAMKA Press)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22236/solma.v15i1.21350

Abstract

Background: Kualitas pendidikan yang unggul menuntut guru untuk memiliki kompetensi literasi digital, kemampuan berpikir kritis, dan keterampilan kolaboratif. Namun, kesenjangan kompetensi digital guru di Indonesia masih cukup besar, khususnya dalam kemampuan mendesain media pembelajaran visual seperti infografis. Penelitian ini bertujuan untuk menganalisis pengaruh pelatihan pembuatan infografis terhadap peningkatan kompetensi guru dalam mendesain media pembelajaran digital interaktif. Metode penelitian menggunakan desain eksperimen semu (quasi-experimental) dengan model one-group pre-test and post-test. Sampel penelitian berjumlah 15 guru SMP di Kabupaten Sukabumi yang dipilih secara purposif. Data dikumpulkan melalui kuesioner pre-test dan post-test untuk mengukur pengetahuan konseptual dan persepsi guru terhadap infografis. Analisis data dilakukan dengan uji Wilcoxon Signed-Rank dan perhitungan effect size. Hasil penelitian menunjukkan adanya peningkatan signifikan pada kompetensi guru setelah pelatihan (p = 0,000714 < 0,05) dengan nilai effect size sebesar 0,881 yang termasuk kategori pengaruh sangat besar. Hal ini menunjukkan bahwa pelatihan pembuatan infografis efektif dalam meningkatkan keterampilan guru baik secara teknis maupun pedagogis. Dengan demikian, pelatihan ini berkontribusi dalam memperkuat literasi digital dan kemampuan komunikasi visual guru di era pembelajaran digital.
Co-Authors Abi Wiyono Adzima, Khaola Rachma Afifah Nur Mutia Alwansyah, Muhammad Arib Ambarwati, Defina Auria Yusrin Fathya Bagus Sartono Bagus Sumargo Bagus Sumargo Bagus Sumargo, Bagus Baihaqi, Aulia Binoto, Rustham Michael Contillo, Gerry Dania Siregar Dania Siregar Devi Eka Wardani Dian Handayani Doni Koesoema Albertus 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 Herlina Nofita Ibnu Hadi Indahwati Indiyah, Fariani Hermin Indriana, Devi Jadid Irtakhoiri Jaisy Aulia Janna Sri Bina Br Barus Kamil, Adine Ihsan Kamilia, Rifa Khoirunnisa Koeshella, Ajeng Ladayya, Faroh Lina Nafisah Lukita Ambarwati Lukman El Hakim Mahardika, Baihaqy Mahatma, Yudi Makmuri Maulida Audia Firdaus Megafajari, Dhioatmaja Meidianingsih, Qorry Meila Nadya Muhammad Alief Ghifari Muhammad Rafli Muzakki Tamami NATALIE EFRATA SUSANTI Nilam Novita Sari Ningsih, Nia Rahayu Novia Sucy Aristawidya Pinta Deniyanti Sampoerno Pinta Deniyanti Sampoerno Prima Riyani Puteri, Syafa Marisha Rahayuningsih, Yuliana Rahfa Qur’aniyatin Dhuha Rahma, Alifia Taufika Rahmi Rahmi Ria Arafiyah Riam Nurussilmah Rianiati Monica Ridana, Farah Fadhilah Rifqy Marwah Akhsanti Riska Agustin Riyantobi, Ariq Muammar Safira Datu Sahila, Sahiba Sangaji, Abdul Canter Sari Febrianti 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 Wahyu, Rahadian Wardani Rahayu Widyanti Rahayu Widyanti Rahayu Widyanti Rahayu Widyanti Rahayu Widyanti Rahayu Wilsen Wilsen Yusuf, Marweli Zahra Ayu Rahmadani Zahrah Hashifah