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All Journal EKSAKTA: Journal of Sciences and Data Analysis Jurnal Statistika Universitas Muhammadiyah Semarang Jurnal Karya Pendidikan Matematika Jurnal Matematika dan Statistika serta Aplikasinya (Jurnal MSA) Register: Jurnal Ilmiah Teknologi Sistem Informasi Jurnal Fourier Indonesian Journal of Applied Statistics Seminar Nasional Variansi (Venue Artikulasi-Riset, Inovasi, Resonansi-Teori, dan Aplikasi Statistika) BAREKENG: Jurnal Ilmu Matematika dan Terapan JITK (Jurnal Ilmu Pengetahuan dan Komputer) Unisda Journal of Mathematics and Computer Science (UJMC) JTAM (Jurnal Teori dan Aplikasi Matematika) J Statistika : Jurnal Ilmiah Teori Dan Aplikasi Statistika Jurnal Ilmiah Pendidikan dan Pembelajaran B-Dent, Jurnal Kedokteran Gigi Universitas Baiturrahmah EIGEN MATHEMATICS JOURNAL Variance : Journal of Statistics and Its Applications Jurnal Saintika Unpam : Jurnal Sains dan Matematika Unpam Square : Journal of Mathematics and Mathematics Education Community Development Journal: Jurnal Pengabdian Masyarakat ESTIMASI: Journal of Statistics and Its Application Majalah Ilmiah Matematika dan Statistika (MIMS) Soeropati: Journal of Community Service Journal of Intelligent Computing and Health Informatics (JICHI) JAMBURA JOURNAL OF PROBABILITY AND STATISTICS LOSARI: Jurnal Pengabdian Kepada Masyarakat JURNAL INOVASI DAN PENGABDIAN MASYARAKAT INDONESIA Tepis Wiring : Jurnal Pengabdian Masyarakat Journal Focus Action of Research Mathematic (Factor M) Jurnal Statistika dan Komputasi (STATKOM) Journal of Data Insights Jurnal Statistika dan Sains Data Prosiding Seminar Nasional Unimus Parameter: Jurnal Matematika, Statistika dan Terapannya Jurnal Statistika Industri dan Komputasi Journal of Mathematics, Computation and Statistics (JMATHCOS) Emerging Statistics and Data Science Journal Amalgamasi: Journal of Mathematics and Applications Data Science Insights RAGAM: Journal of Statistics and Its Application
M. Al Haris
Department Of Statistics, Universitas Muhammadiyah Semarang, Semarang, Indonesia
Religion Agriculture, Biological Sciences & Forestry Arts Humanities Chemical Engineering, Chemistry & Bioengineering Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Nursing Physics Public Health Social Sciences Transportation Other

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Pemberdayaan Siswa melalui Pelatihan Eco Enzyme di Madrasah Aliyah Wahid Hasyim Bangsri Jepara Heppy Nur Asavia Ginasputri; Kamilah Citra Chumairoh; Kaia Raissa Akmalia; Muhammad Najwan Kamil; Ahmad Jundi Ismail; M. Al Haris
JURNAL INOVASI DAN PENGABDIAN MASYARAKAT INDONESIA Vol 5 No 1 (2026): Januari
Publisher : Fakultas Kesehatan Masyarakat, Universitas Muhammadiyah Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26714/jipmi.v5i1.910

Abstract

Latar belakang: Madrasah Aliyah (MA) Wahid Hasyim Bangsri, yang berlokasi di Desa Kedungleper, Jepara, menghadapi tantangan lingkungan akibat rendahnya kesadaran ekologis siswa yang mayoritas berasal dari keluarga petani dan nelayan. Permasalahan utama terletak pada pengelolaan limbah organik yang belum terstruktur, sehingga menimbulkan bau tidak sedap, pencemaran, serta menurunkan kenyamanan proses belajar. Tujuan: Menerapkan program Eco Enzyme (EE) untuk meningkatkan pemahaman dan keterampilan siswa dalam pengelolaan limbah organik, serta mengetahui dampak penerapan EE terhadap perilaku siswa dan efektivitasnya dalam mengurangi pencemaran lingkungan berkelanjutan. Metode: Pelaksanaannya kegiatan meliputi survei, sosialisasi, pelatihan pembuatan EE serta monitoring dan evaluasi. Hasil: Kegiatan yang telah dilaksanakan berkontribusi peningkatan pemahaman siswa sebesar 86% berdasarkan pre-test dan post-test, serta penurunan volume sampah organik hingga 60% dalam tiga minggu pelaksanaan. Selain itu, telah dibuat wadah fermentasi dan buku pedoman EE sebagai bahan ajar pendukung keberlanjutan program. Terbentuknya kelompok “Siswa Peduli Lingkungan” dan adanya pakta integritas memperkuat komitmen sekolah untuk melanjutkan program. Kesimpulan: Program Pelatihan EE terbukti efektif meningkatkan literasi, keterampilan, dan perilaku peduli lingkungan siswa menuju sekolah hijau berkelanjutan. _______________________________________________________________________ Abstract Background: Madrasah Aliyah (MA) Wahid Hasyim Bangsri, located in Kedungleper Village, Jepara, faces environmental challenges due to the low ecological awareness of its students, most of whom come from farming and fishing families. The main issue lies in the unstructured management of organic waste, which causes unpleasant odours, pollution, and reduces the comfort of the learning environment. Objective: This study aims to implement the Eco Enzyme (EE) program to enhance students’ understanding and skills in organic waste management, as well as to examine the impact of EE implementation on student behaviour and its effectiveness in reducing sustainable environmental pollution. Method: The activities included surveys, socialisation, training in EE production, and continuous monitoring and evaluation. Result: The program contributed to an 86% increase in students’ understanding, as measured by pre-test and post-test assessments, and a 60% reduction in organic waste volume within three weeks of implementation. In addition, fermentation containers and an EE handbook were developed as supporting teaching materials to ensure program sustainability. The establishment of the “Environmentally Concerned Students” group and the signing of an integrity pact further strengthened the school’s commitment to continuing the program. Conclusion: The EE training program proved effective in improving students’ environmental literacy, practical skills, and pro-environmental behaviour, thereby supporting the development of a sustainable green school. 
Stock Price Forecasting of PT. Bank Rakyat Indonesia (Persero) Tbk. Using Long Short-Term Memory (LSTM) Method Lydia Nur Sa'adah; Nasyiatul Izzah; Kamilah Citra Khumairoh; M. Al Haris; Ihsan Fathoni Amri
Journal of Data Insights Vol 3 No 2 (2025): Journal of Data Insights
Publisher : Department of Sains Data UNIMUS Universitas Muhammadiyah Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26714/jodi.v3i2.847

Abstract

Stock price forecasting is a major challenge in financial market analysis due to the volatility and unpredictability of price movements. The limitations of traditional statistical methods in capturing nonlinear patterns and long-term temporal dependencies have encouraged the adoption of deep learning–based approaches. This research aims to predict the stock price of PT Bank Rakyat Indonesia (Persero) Tbk. (BBRI) using the Long Short-Term Memory (LSTM) method, which is effective at handling problems with fading information and identifying long-term trends in time series data. The dataset comprises historical BBRI share prices from April 16, 2015, to April 16, 2025, with 80% of the data used for training and 20% for testing. LSTM’s model was trained for 10 epochs with a batch size of 32 using the Adam optimizer. The results prove that the LSTM model can effectively capture stock price movement patterns, achieving a mean absolute error (MAE) of 8.42 and a mean absolute percentage error (MAPE) of 1.50%, indicating a high level of accuracy. The visualization of the prediction results reveals a trend that closely aligns with the actual values. These findings reinforce LSTM’s position as a reliable approach to stock price forecasting and highlight its potential as a strategic tool for investors and policymakers in managing market risk.
HYBRID RESAMPLING METHOD AND HYPERPARAMETER OPTIMIZATION FOR HIV/AIDS PREDICTION: EVIDENCE FROM EIGHT MACHINE-LEARNING MODELS Lydia Nur Sa'adah; Fatkhurokhman Fauzi; Prizka Rismawati Arum; M Al Haris; Yan Nazala Bisoumi
JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer) Vol. 11 No. 4 (2026): JITK Issue May 2026
Publisher : LPPM Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/jitk.v11i4.7533

Abstract

HIV/AIDS remains a global health challenge with continuously increasing infection rates, highlighting the importance of accurate prediction models to support prevention and early detection. However, the development of such models is often constrained by class imbalance and irrelevant features. This study aims to improve HIV/AIDS infection prediction by integrating feature selection, data balancing techniques, and eight machine learning algorithms. Feature selection was performed using Mutual Information and Chi-Square to identify the most relevant features. The dataset used was the HIV/AIDS Infection Prediction Dataset from Kaggle, consisting of 2,139 instances and 23 features, with an imbalanced distribution of 1,618 non-infected and 521 infected cases. The dataset was divided into 80% training data and 20% testing data, with resampling applied only to the training set to prevent data leakage. Three resampling scenarios were evaluated: no sampling, SMOTE, and SMOTE-ENN. Hyperparameter tuning was conducted using Bayesian Optimization integrated with 5-fold Cross-Validation to improve model robustness and reliability. Eight machine learning algorithms were evaluated, including Decision Tree, Random Forest, AdaBoost, Gradient Boosting, XGBoost, LightGBM, K-Nearest Neighbors, and Logistic Regression. The results show that SMOTE-ENN combined with hyperparameter optimization significantly improved model performance. The best model, Gradient Boosting + SMOTE-ENN, achieved 96.1% accuracy, 94.8% precision, 98.4% recall, and 96.5% F1-score. These findings indicate that the proposed integrated framework is highly effective for predicting HIV/AIDS infection and has strong potential to support early diagnosis and data-driven decision-making in healthcare.
PENINGKATAN LITERASI CINTA TANAH AIR BAGI SISWA DI SANGGAR BIMBINGAN, SELANGOR MALAYSIA M Al Haris; Fitria Fatichatul Hidayah; Arya Praditya; R.A Qonita Syalsabilla Handayani; Anis Priyanti; Salmah Salmah
Community Development Journal : Jurnal Pengabdian Masyarakat Vol. 5 No. 6 (2024): Vol. 5 No. 6 Tahun 2024
Publisher : Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/cdj.v5i6.34429

Abstract

Sekolah Indonesia Kuala Lumpur (SIKL) adalah lembaga pendidikan Indonesia yang berlokasi di luar negeri di bawah naungan Kedutaan Besar Republik Indonesia (KBRI). Sekolah ini melayani anak-anak para migran Indonesia di Malaysia. Anak-anak Indonesia di Malaysia menghadapi tantangan terkait adaptasi budaya, mereka sering merasa lebih dekat dengan budaya Malaysia dan kadang ragu untuk kembali ke Indonesia. oleh karena itu, sangat penting untuk memberikan pendidikan karakter yang menanamkan rasa nasionalisme pada anak-anak ini. Peran guru di SIKL sangat krusial dalam membentuk karakter siswa dan mempertahankan identitas budaya Indonesia. Akan tetapi tidak banyak guru yang mampu memanfaatkan data dan informasi untuk meningkatkan proses pembelajaran. Memperhatikan situasi tersebut, Tim pengabdian melakukan kegiatan penyuluhan literasi nasionalisme dan pelatihan analisis data untuk mendukung penelitian para guru. Hasil kegiatan menunjukkan bahwa peserta sangat antusias dan menyatakan kepuasan terhadap kegiatan yang diselenggarakan oleh Tim pengabdian Universitas Muhammadiyah Semarang. Kepuasan peserta juga terlihat dari hasil survei yang dilakukan setelah kegiatan. Hasil survei menunjukkan bahwa terdapat 82% peserta yang menyatakan aktif berpartisipasi selama kegiatan dan 86% peserta menyatakan bahwa mereka memahami pentingnya cinta pada tanah air dan makna dari nilai-nilai yang terkandung di dalamnya.
EVALUASI PARADIGMA KRITIS TERHADAP INTEGRASI, KONEKSI, DAN APLIKASI DALAM METODE KADIR PADA PEMBELAJARAN MATEMATIKA DENGAN PENDEKATAN NILAI NILAI ISLAM Ainurrafiq Dawam; M. Al Haris
Jurnal Karya Pendidikan Matematika Vol 12, No 1 (2025): Jurnal Karya Pendidikan Matematika Volume 12 Nomor 1 Tahun 2025
Publisher : Universitas Muhammadiyah Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26714/jkpm.12.1.2025.1-18

Abstract

This study evaluated the effectiveness of the KADIR method (Connection, Application, Discourse, Improvisation, and Reflection) in integrating Islamic values into mathematics education. The KADIR method aimed to enhance conceptual understanding, critical thinking skills, and student motivation by connecting mathematical concepts with Islamic values. Using a qualitative literature-based approach, this study found that the KADIR method effectively improves students' understanding of mathematical concepts and their application in everyday life. Integrating Islamic values through this method also strengthens students' character and morals and increases their motivation to learn. The main challenges in implementing this method included the limitations of resources and support for teachers, as well as the complexity of connecting mathematical concepts with Islamic values. This study provided theoretical and practical contributions to the development of a holistic mathematics learning model. Recommendations for educators included competency development through training, the design of contextual learning, and the implementation of holistic evaluation. These findings were expected to improve the quality of mathematics education and help students develop a more comprehensive and meaningful understanding of the context of Islamic values.
Analysis of Passenger Flight Distance as an Indicator of Economic Activity Ihsan Fathoni Amri; Suci Izzati; Rendi Andika Putra; Iva Aurellia Khalif; Febryana Dilla Setyaningrum; Isnaini Maulida; M. Al Haris
Parameter: Jurnal Matematika, Statistika dan Terapannya Vol 5 No 1 (2026): Parameter: Jurnal Matematika, Statistika dan Terapannya
Publisher : Jurusan Matematika FMIPA Universitas Pattimura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/parameterv5i1pp111-124

Abstract

Understanding macroeconomic dynamics in the United States requires advanced forecasting techniques capable of capturing both seasonal structures and external shocks. This study investigates the relationship between passenger flight distance and the unemployment rate through the implementation of the Seasonal Autoregressive Integrated Moving Average with Exogenous Variables (SARIMAX) model—an enhancement of the SARIMA framework. While SARIMA accounts for autoregressive, differencing, and moving average components with seasonal integration, SARIMAX further augments this structure by incorporating exogenous predictors, enhancing explanatory and predictive power. Monthly time series data from 2015 to 2024 were utilized, with flight distance as the endogenous variable and the unemployment rate as the exogenous regressor. The modeling procedure involved rigorous stationarity testing via the Augmented Dickey-Fuller (ADF) test, model selection using the Akaike Information Criterion (AIC), and residual diagnostics employing the Box–Ljung and Shapiro–Wilk tests. SARIMAX(0,1,0)(0,1,1)[12] + X emerged as the optimal specification, with all parameters statistically significant and a MAPE of 3.68%, denoting excellent forecast accuracy. Empirical findings reveal a significant and negative association between unemployment and air travel activity, emphasizing the role of labor market dynamics in shaping mobility trends. These results reinforce the utility of SARIMAX as a robust tool in macroeconomic forecasting and evidence-based policy formulation.
MODELING OF POVERTY INDICATORS IN EAST JAVA PROVINCE USING BOOTSTRAP AGGREGATING MULTIVARIATE ADAPTIVE REGRESSION SPLINE (BAGGING MARS) danu priambodo; Rochdi Wasono; M. Al Haris
Jurnal Statistika Universitas Muhammadiyah Semarang Vol 12, No 2 (2024): Jurnal Statistika Universitas Muhammadiyah Semarang
Publisher : Department Statistics, Faculty Mathematics and Natural Science, UNIMUS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26714/jsunimus.12.2.2024.19-28

Abstract

Poverty is a situation where a person is below the minimum standard value line. The view regarding poverty can be said that poverty is a multidimensional phenomenon where there are many indicators that influence poverty, so modeling needs to be carried out to find out what indicators influence poverty. This research uses The Multivariate Adaptive Regression Spline (MARS) with Bootstrap Aggregating. MARS is a nonparametric regression method that can handle high- dimensional data. The best model produced by MARS is a combination of BF=24, MI=1, MO=0 with a GCV of 9.231184. Then Bagging was carried out on the initial dataset with 35, 45, 50, 75 and 100 bootstrap replications. The best model was produced by MARS Bagging on 45 replications with a GCV of 3.84492. The GCV value obtained by Bagging MARS is smaller than MARS. This shows that Bagging can reduce GCV and increase accuracy, so this method can be used in this research.
Penerapan algoritma Decision Tree untuk klasifikasi status stunting pada balita di Indonesia Miftakhiyah Fazza Baita; Siti Nurhalisa; M Al Haris; Saeful Amri
Jurnal Statistika dan Sains Data Vol 3, No 2 (2026): Jurnal Statistika dan Sains Data
Publisher : Universitas Negeri Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21831/jssd.v3i2.24754

Abstract

Stunting merupakan permasalahan kesehatan masyarakat yang serius di Indonesia. Kondisi ini terjadi akibat kekurangan gizi kronis yang berlangsung dalam jangka waktu lama, sehingga menyebabkan anak balita memiliki tinggi badan lebih rendah dibandingkan standar usianya. Selain menghambat pertumbuhan fisik, stunting juga berdampak pada perkembangan kognitif dan produktivitas anak di masa depan. Berdasarkan Survei Status Gizi Indonesia (SSGI) tahun 2022, prevalensi stunting di Indonesia mencapai 21,6%, melebihi ambang batas yang ditetapkan WHO, yaitu kurang dari 20%. Pemerintah menargetkan penurunan angka tersebut menjadi 14% pada tahun 2024. Salah satu pendekatan yang dapat digunakan untuk mendukung upaya ini adalah dengan menerapkan algoritma pohon keputusan dalam klasifikasi status stunting . Hasil penelitian menunjukkan bahwa model pohon keputusan C4.5 yang dibangun menggunakan 10.000 data balita dari dataset WHO mampu mencapai akurasi 57,80%, presisi 79,93%, dan recall 30,29%, dengan atribut tinggi badan dan umur sebagai batas utama. Hasil ini menunjukkan bahwa pohon keputusan dapat digunakan sebagai model awal deteksi stunting, meskipun perlu peningkatan kinerja melalui teknik penyeimbangan data.
Peramalan Indeks Harga Konsumen Kota Semarang dengan Metode Autoregressive Integrated Moving Average: Forecasting Consumer Price Index (CPI) of Semarang City using Autoregressive Integrated Moving Average (ARIMA) Method Sesotyaning Harum Prabuningrat; M. Al Haris; Nadia Khoirunnafisa Salma; Putri Wahyu Muharamah; Muhammad Saifuddin Nur
Journal of Data Insights Vol 1 No 1 (2023): Journal of Data Insights
Publisher : Department of Sains Data UNIMUS Universitas Muhammadiyah Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26714/jodi.v1i1.124

Abstract

Indeks Harga Konsumen (IHK) merupakan salah satu indikator untuk menentukan tingkat stabilitas ekonomi suatu negara. IHK dapat memberikan informasi mengenai perkembangan harga barang dan jasa yang dibayar oleh konsumen, khususnya masyarakat kota. Pemerintah selalu menjaga mengenai presentase perubahan nilai IHK agar tetap rendah dan stabil sehingga mampu memberikan kesejahteraan untuk masyarakat. Oleh karena itu, perlu adanya peramalan data IHK untuk membantu pemerintah dalam menyusun kebijakan kedepannya. Salah satu metode yang tepat untuk meramalkan data IHK Kota Semarang yaitu dengan menggunakan model time series dengan proses Autoregressive Integrated Moving Average (ARIMA). Berdasarkan hasil analisis diperoleh Model ARIMA terbaik adalah ARIMA (0,1,1). Model terbaik menghasilan nilai kesalahan prediksi berdasarkan nilai MAPE sebesar 6,07% yang menandakan bahwa kemampuan model dalam memprediksi IHK Kota Semarang sangat akurat.
Prediction of Covid-19 Cases in Indonesia Using the Auto Regressive Integrated Moving Average Method: Prediksi Kasus Covid-19 di Indonesia Menggunakan Metode ARIMA Asriyanti Sawiah Adam; Rahma Safira; M. Al Haris; Saeful Amri
Journal of Data Insights Vol 3 No 1 (2025): Journal of Data Insights
Publisher : Department of Sains Data UNIMUS Universitas Muhammadiyah Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26714/jodi.v3i1.212

Abstract

This study discusses the use of the ARIMA (Auto Regressive Integrated Moving Average) model to predict the number of COVID-19 cases in Indonesia based on previous data. The results of the analysis show that the ARIMA (1,0,0) model is the most accurate in predicting the spread of COVID-19. Based on this model, the prediction results obtained that confirmed COVID-19 data from January to December 2022 are predicted to decrease. The number of confirmed cases of COVID-19 until December 2022 is predicted to reach 20,0365 cases of spread. So this Covid-19 case still needs special and more serious attention from the government and the public must still be vigilant because based on the results of the study there have been no signs of a significant decrease in the spread of Covid-19 cases. This study provides important insights for the government, medical personnel, and the public in planning strategies for preventing and handling the pandemic
Co-Authors Abdul Ghufron Abidah, Khansa Ni'mal Abimanyu Arya Ramadhan Ach Ridoi Alambara Adhwaningrum, Arullah Salsabila Agata Dwi Putri Putri Agi Khoerunnisa Ahmad Jundi Ismail AHMADI Ainurrafiq Dawam Ainurrofiah, Safira Al Aghni Naufalia Albertus Dion Sarah Ali Imron Ali Imron Alia Permata Alwan Fadlurohman Alya Febriyani Amalia Jihan Syafiqoh Amin Samiasih Amri, Saeful Amrullah, Ahmad Amrullah, Setiawan Anggoro, Vernanda Kresna Anis Priyanti Anne Mutiara Wardani Ardana Setiawan, Deftha Ariska Fitriyana Ningrum Arya Praditya Arya, Abimanyu Asriyanti Sawiah Adam Astuti, Sofi Anggi Asyfani, Yusrisma Aulia Dewi Gustiarni Aulia Fadhli Boer Ayesha Nayla Salsadella Ayomi, Nun Maulida Suci Ayu Wulandari Ayuda Nur Sukmawati Azzahrani, Rahma Dewi Bahaudin, Muhammad Barlian, Seftia Amelia Rizki Bunga Ayuningrum Choirudin, Mochamad Fahmi Choirunnisa Hasna Nisa Cika Awani Ayuwida Dannu Purwanto danu priambodo Dea Zahra Khairunnisa Devina Nadifa Nur Aulia Diani, Nandini Lova Dimar Pangestika Sari Dwi Purnomo Putro Dzeaulfath, Muhammad Eko Andy Purnomo Elfina Latifah Safira Eny Winaryati Eny Winaryati Ermawati, Asti Erna Julia Nanga Evida Oktaviana Fabiola, Gwenda Fadhilah Azzahra Fadillah, Muhammad Reza Faninda Aidina Fitri Fathir Naufal Hasan Fatkhurrokhman Fauzi Fauzi, Fatkhurokhman Fazia Risnita Widiyana Febrianti, Fatika Lovina Febryana Dilla Setyaningrum Firdatul Fahria Firdaus, Falah Tinton Firochul Masichah Fisabilillah, Muh. Irodat Fitri Anjani Fitri Diana Musa Fitria Fatichatul Hidayah Gautama, Rahmad Putra Hafiza Abas Haris, M Al Haris, M. Al Havinka Angel Salsabilla Havinka Angel Salsabilla Heppy Nur Asavia Ginasputri Heppy Nur Asavia Ginasputri Herculianus Rowa Dawi Hidayat, Muhamad Arif Hilma Hanna Mahanna Haqq Himmaturrohmah, Laily Husna, Rizqa El Iffah Norma Hidayati Ihsan Fathoni Ihsan Fathoni Amri Ikhwanudin, Muhamad Ilham Khairul Anam Imelya Susianti Inayah Pangestu, Eka Indah Fitriyani Indah Manfaati Nur Indah Manfaati Nur Indriani, Anita Retno Irawan, Alfian Chandra Isnaini Maulida Iva Aurellia Khalif Jesicha Arsusma Kaia Raissa Akmalia Kaia Raissa Akmalia Kamilah Citra Chumairoh Kamilah Citra Khumairoh Khansa' Ni'mal 'Abidah Khikman, Muhammad Alvaro Khoirul Huda Kinanta, Ailsha Syafa Latisa Alifa Maura Lea Angelina Lein, Raymond Bolly Linda Puspitasari Lydia Nur Sa'adah Lydia Nur Sa'adah Lydia Nur Sa'adah Mandala Adikara Sencoko Marsela Ayu Irdiana Masudah, Nurhidayatul Miftakhiyah Fazza Baita Miftakhul Haris Miftakhurizki Mochamad Hasyim Mualim Tahari Mufidatul Ulya Muhammad Alvaro Khikman Muhammad Bahaudin Muhammad Hali Mukron Muhammad Najwan Kamil Muhammad Rifqy Ardiansyah Muhammad Saifuddin Nur Multiyaningrum, Riska Nadia Khoirunnafisa Salma Nandini Lova Diani Nasyiatul Izzah Nikmah Handayani Ninu, Maria Febronia Nufita Nurohmah Nugroho, Muhammad Dimas Alfian Nur Arifah, Miftah Nurfuad, Khilmi Nurhidajah Nurmalita, Rahma Nurmawati Ainun Hidayana Okiyanto, Rizal Pandiriyan, Muhammad Tegar Prastiwi, Harvina Sindy Prastyo, Ikwan Pratama, Rifin Fadilla Pratama, Rizky Adi Priambodo, Danu Prissy Nusaiba Yulisa Prizka Rismawati Arum Purnama, Estyaningsi Puspitasari, Linda Putra, Septian Malik Putri Wahyu Muharamah Putri, Melfia Verahma R.A Qonita Syalsabilla Handayani RA. Qonita Syalsabilla Handayani Rahma Nurmalita Rahma Safira Raka Nurhaq Mulya Hartanto Ramadhan, Abimanyu Arya Ramadhan, Wulan Nur Rangga Sa'adillah SAP Rendi Andika Putra Revika Inta Nur Kholifah Ridwanulhaq, Alfina Fauziah Riska Multiyaningrum Riska Multiyaningrum Riska Multiyaningrum Rochdi Wasono Rochdi Wasono Rochdi Wasono Ryan Mahardika Saeful Amri Saeful Amri Salmah Salmah Salsabila Dhea Sintya Salsabila Rahma Anisa Salwa Salsabila, Galuh Sam'an, Muhammad Sanmas, Safril Ahmadi Saputri, Atika Dwi Sari, Selvi Ana Windia Septi Winda Utami Septia, Siti Fajar Sesotyaning Harum Prabuningrat Shinta Amaria Sidqi, Isnaeni Miftahul Siswahyudianto Siti Hamidah Ardhy Siti Nurhalisa siti wulandari Suci Izzati Suci Laeliyah Suci Mega Puji Lestari Suherdi, Andri Sulistiya, Indah Sulistiyani, Dwi Sunday Emmanuel Fadugba Supriadin Supriadin Supriadin Supriadin Syafina Amira Firdaus Syaharani, Nabbila Dyah Tiani Wahyu Utami Tresiani Yunitasari Tri zahrotun Wahyuningsih Ulinuha, Samikoh Utami, Rossy Prima Nada Utiningtyas, Almas Rizki Velia Arni Widyasari Wahid, Siti Nurasriyanti Wahyuningsih, Andria Watur, Annisa Cahyaningrum Widiyanti, Karin Dita Wulan Sari Wulan Sari, Wulan Yan Nazala Bisoumi Yolan Triky Yulia Nur Kumala Yulianita, Tanti