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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 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 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 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 RAGAM: Journal of Statistics and Its Application
M. Al Haris
Program Studi Statistika, Universitas Muhammadiyah Semarang
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ANALISIS PERAMALAN CUACA KOTA SURABAYA MENGGAnalisis Peramalan Cuaca Kota Surabaya Menggunakan Pendekatan Autoregressive Integrated Moving Average (ARIMA) UNAKAN PENDEKATAN AUTOREGRESSIVE INTEGRATED MOVING AVERAGE (ARIMA) Latisa Alifa Maura; Nikmah Handayani; Devina Nadifa Nur Aulia; M. Al Haris
RAGAM: Journal of Statistics & Its Application Vol 3, No 2 (2024): RAGAM: Journal of Statistics & Its Application
Publisher : Universitas Lambung Mangkurat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20527/ragam.v3i2.12963

Abstract

Erratic weather is a crucial issue that can disrupt activities in all aspects. Weather monitoring needs to be done to avoid adverse consequences. ARIMA is one of the methods that can be used in weather forecasting because it is produce high accuracy, especially on short-term data. This research aims to get the best ARIMA model that produces accurate forecasting with the smallest error. Based on the research results, the best models obtained for temperature and humidity variables are (0,0,2) and (1,01) with MAPE values of 2.57% and 6.5%. Thus, the ARIMA model has very accurate forecasting performance.
Forecasting the Rupiah exchange rate against the US Dollar using the LSTM algorithm Multiyaningrum, Riska; Dawi, Herculianus Rowa; Hartanto, Raka Nurhaq Mulya; Haris, M. Al; Amri, Ihsan Fathoni
Journal Focus Action of Research Mathematic (Factor M) Vol. 8 No. 2 (2025): December 2025
Publisher : Universitas Islam Negeri (UIN) Syekh Wasil Kediri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30762/f_m.v8i2.6530

Abstract

Exchange rates are a vital indicator of an economy's balance. The fluctuations of Indonesia's currency, the rupiah, against the USD influenced trade patterns, investment, and both monetary and fiscal policy. Exchange rate fluctuations affect international trade, investment, inflation, and overall economic stability. The high volatility of the Rupiah against the USD, driven by macroeconomic and monetary factors, has a significant impact on national economic policy, necessitating research that utilizes the latest data and adaptive models. To capture the nonlinear and complicated behavior of exchange rates, an advanced methodology for forecasting is needed. This journal utilizes the Long Short-Term Memory (LSTM) neural network model to forecast the exchange rate of the rupiah towards the dollar from March 1, 2022, up to February 28, 2025, in daily data. The data used in this research are sourced from www.bi.go.id, which provides the official daily exchange rate of USD to IDR. The Long Short-Term Memory method was chosen for modeling long-term dependencies within time series. After normalization, an 80/20 split is performed for training and testing on the dataset. The network runs optimization using three hidden layers with 50 neurons each and a batch size of 32 for 200 epochs. The optimal configuration, achieved through experimental trials, consisted of two hidden layers with 50 neurons, a batch size of 32, and 200 epochs. This is manifest in the fact that LSTM effectively captures movements in exchange rates, with an RMSE of 0.6226 and a MAPE of 0.3031%. This degree of accuracy enables the model to inform economic policy decisions based on data.
Analysis of DHF Patients Based on Laboratory Examination Results with Nonparametric Approach Utami, Tiani Wahyu; Haris, M. Al; Salma, Nadia Khoirunnafisa
JTAM (Jurnal Teori dan Aplikasi Matematika) Vol 10, No 1 (2026): January
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jtam.v10i1.33609

Abstract

The dengue virus, which is spread by the Aedes aegypti mosquito, is the cause of Dengue Hemorrhagic Fever (DHF). In the city of Semarang, there was a threefold increase in cases of DHF compared to previous years. This type of research is quantitative research because it produces function that describes the relationship to what extent changes in predictor variable are related to changes in response variable to understand the level of association. Modelling the link between response and predictor factors is the aim of this study. Platelet as the response variable and hemoglobin and leukocyte as the predictor variables, so that the obtained model can be used as a prediction, especially regarding the dynamics of platelet changes influenced by hemoglobin and leukocytes. The pattern of the relationship between platelets and the suspected influencing factors does not form specific pattern, so the Nonparametric Spline method is used in this study. The Spline method is chosen for its flexibility; this model tends to independently seek data estimates, the completion of this study using R software. In the Spline method, there are knot points indicating data changes. The selection of optimum knot points is done by choosing the minimum GCV value The secondary data used came from Roemani Muhammadiyah Hospital's 2023 medical records. The data include platelet count, hemoglobin, and leukocyte. Based on the modeling conducted using truncated spline, the optimum knot points on the linier spline are determined to be 3 knot points with a coefficient determination of 83.58%. The coefficient of determination of 83.58% indicating that 83.58% of the variation in response variable can be explained by predictor variables studied in the regression model. This value indicates that predictor variables have a strong ability to explain changes in response variable.
Peramalan Produksi Tanaman Padi Indonesia Tahun 2025 Menggunakan Metode Triple Exponential Smoothing Holt-Winters : Peramalan Produksi Tanaman Padi Indonesia Tahun 2025 Menggunakan Metode Triple Exponential Smoothing Holt-Winters Inayah Pangestu, Eka; Wulandari, Siti; Salwa Salsabila, Galuh; Nur Arifah, Miftah; Ardana Setiawan, Deftha; Fathoni Amri, Ihsan; Bahaudin, Muhammad; M. Al Haris
Emerging Statistics and Data Science Journal Vol. 4 No. 1 (2026): Emerging Statistics and Data Science Journal
Publisher : Statistics Department, Universitas Islam Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20885/esds.vol4.iss.1.art07

Abstract

Produksi padi memiliki peran penting dalam mendukung ketahanan pangan nasional. Untuk memastikan ketersediaan pangan di tengah peningkatan jumlah penduduk, diperlukan peramalan produksi yang akurat. Penelitian ini bertujuan untuk memodelkan peramalan produksi padi Indonesia tahun 2025 selama periode Januari 2019 hingga Desember 2024 menggunakan Triple Exponential Smoothing Holt-Winters, baik model aditif maupun model multiplikatif. Hasil penelitian menunjukkan bahwa model aditif merupakan model terbaik untuk meramalkan produksi tanaman padi Indonesia tahun 2025. Dengan parameter optimal α=0,3, β=0,4, dan γ=0,1, serta nilai MAPE sebesar 25,72% yang menunjukkan bahwa hasil peramalan cukup akurat.
Forecasting Rice Prices in Indonesia Using a Hybrid HWES-MLP Time Series Prediction Model Supriadin, Supriadin; Haris, M. Al; Amri, Saeful; Abas, Hafiza; Fadugba, Sunday Emmanuel
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.v10i2.35445

Abstract

Rice is the main staple food for the majority of the Indonesian population. However, the fluctuation in rice prices and future uncertainty emphasize the importance of forecasting rice prices, thus requiring a forecasting model capable of providing accurate predictions. Various previous forecasting methods have been limited in capturing the combination of linear and non-linear patterns in rice price data, spurring the need for a more comprehensive hybrid approach. This research applies a quantitative approach by utilizing secondary data sourced from publications of the Central Statistics Agency (BPS) of Indonesia. This study aims to forecast rice prices in Indonesia using a hybrid approach combining Holt–Winters Exponential Smoothing (HWES) with Multilayer Perceptron (MLP). The hybrid model is designed to overcome the limitations of the Holt-Winters Exponential Smoothing method, which can only capture linear patterns such as trend and seasonality, by adding the Multilayer Perceptron method to capture non-linear patterns that cannot be handled by the linear approach. The dataset comprises monthly rice prices in Indonesia from January 2010 to December 2024, while the period of January–December 2025 is used as the prediction period. The data analysis process was carried out using the software R-Studio and Minitab, which provide a variety of features to support time series modeling. The results indicate that the most effective method for forecasting rice prices in Indonesia is the Hybrid Holt Winters Exponential Smoothing (α = 0.5; β = 0.3; γ = 0.3)-Multilayer Perceptron (12-12-1), which achieved the highest accuracy with a MSE of 9666.12, a RMSE of 310.9117, and a MAPE of 1.9949%. This finding indicates that the Hybrid HWES-MLP approach is highly capable of capturing rice price data patterns. Thus, this model holds significant potential to be utilized as a benchmark supporting government policy in maintaining rice price stability, market intervention, and optimizing the management of national rice reserves stock.
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. 
Analysis Autocorrelation Spatial on Amount Fundraising at LAZISMU Semarang City Using Moran's Index: Analisis Autokorelasi Spasial pada Jumlah Penghimpunan Dana di LAZISMU Kota Semarang Menggunakan Indeks Moran Nisa, Choirunnisa Hasna; 'Abidah, Khansa' Ni'mal; Al Haris, M.; Fauzi, Fatkhurokhman
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.v3i2.314

Abstract

Institution Zakat and Infaq Collectors And Sed e kah Muhammadiyah (LAZISMU) , has role important in gather And distribute funds activity social use help communities in need . L AZISMU Semarang City in general special focus on management funds at the level city , with not quite enough answer gather And allocate funds from public to humanitarian programs like help education , health , and help social research​ This aim For increase effectiveness collection funds Institution Zakat, Infaq , and Charity Collectors Alms Muhammadiyah in Semarang City. With apply approach spatial , research This analyze pattern distribution geographical donors , potential donations , and characteristics economy as well as demographics in each sub-district . Methodology study involving spatial data collection and analysis statistics . Results study This expected can give contribution on understanding scientific related zakat- based management spatial And become guidelines for institution similar in optimize collection And allocation funds .
Stock Price Forecasting of PT. Bank Rakyat Indonesia (Persero) Tbk. Using Long Short-Term Memory (LSTM) Method Sa'adah, Lydia Nur; 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.
Co-Authors 'Abidah, Khansa' Ni'mal Abas, Hafiza Abdul Ghufron Abidah, Khansa Ni'mal Adhwaningrum, Arullah Salsabila Agi Khoerunnisa Ahmad Jundi Ismail AHMADI Ainurrafiq Dawam Ainurrofiah, Safira Alambara, Ach Ridoi Ali Imron Ali Imron Alwan Fadlurohman Alya Febriyani Amalia Jihan Syafiqoh Amin Samiasih Amri, Ihsan Fathoni Amri, Saeful Amrullah, Ahmad Amrullah, Setiawan Andy Purnomo, Eko Angelina, Lea Anggoro, Vernanda Kresna Anis Priyanti Anne Mutiara Wardani Ardana Setiawan, Deftha Ariska Fitriyana Ningrum Arsusma, Jesicha Arya Praditya Arya Praditya Arya, Abimanyu Astuti, Sofi Anggi Asyfani, Yusrisma athoni Amri, Ihsan F Aulia Dewi Gustiarni Aulia Fadhli Boer Ayesha Nayla Salsadella Ayomi, Nun Maulida Suci Ayu Wulandari Azzahrani, Rahma Dewi Bahaudin, Muhammad Barlian, Seftia Amelia Rizki Bunga Ayuningrum Choirudin, Mochamad Fahmi Cika Awani Ayuwida Dannu Purwanto danu priambodo Dawi, Herculianus Rowa Devina Nadifa Nur Aulia Diani, Nandini Lova Dzeaulfath, Muhammad Eny Winaryati Eny Winaryati Ermawati, Asti Evida Oktaviana Fabiola, Gwenda Fadhilah Azzahra Fadillah, Muhammad Reza Fadugba, Sunday Emmanuel Fauzi, Fatkhurokhman Fauzi, Fatkhurrokhman Fazia Risnita Widiyana Fazza Baita, Miftakhiyah Febrianti, Fatika Lovina Febryana Dilla Setyaningrum Firdatul Fahria Firdaus, Falah Tinton Fisabilillah, Muh. Irodat Fitri Anjani Fitria Fatichatul Hidayah Gautama, Rahmad Putra Ginasputri, Heppy Nur Asavia Haris, M Al Haris, M. Al Hartanto, Raka Nurhaq Mulya Heppy Nur Asavia Ginasputri Hidayat, Muhamad Arif Hilma Hanna Mahanna Haqq Himmaturrohmah, Laily Husna, Rizqa El Iffah Norma Hidayati Ihsan Fathoni Ihsan Fathoni Amri Ihsan Fathoni Amri Ikhwanudin, Muhamad Ilham Khairul Anam Imelya Susianti Inayah Pangestu, Eka Indah Fitriyani Indah Manfaati Nur Indah Manfaati Nur Indriani, Anita Retno Inta Nur Kholifah, Revika Irawan, Alfian Chandra Isnaini Maulida Iva Aurellia Khalif Izzah, Nasyiatul Kaia Raissa Akmalia Kaia Raissa Akmalia Kamilah Citra Chumairoh Kamilah Citra Khumairoh Khikman, Muhammad Alvaro Khoirul Huda Kholifah , Revika Inta Nur Kinanta, Ailsha Syafa Latisa Alifa Maura Lein, Raymond Bolly Linda Puspitasari Lydia Nur Sa'adah Mandala Adikara Sencoko Marsela Ayu Irdiana Masichah, Firochul Masudah, Nurhidayatul Miftakhul Haris Miftakhurizki Mochamad Hasyim Mualim Tahari Mufidatul Ulya Muhammad Hali Mukron Muhammad Najwan Kamil Muhammad Rifqy Ardiansyah Muhammad Saifuddin Nur Multiyaningrum, Riska Musa, Fitri Diana Nadia Khoirunnafisa Salma Nasyiatul Izzah Nikmah Handayani Ninu, Maria Febronia Nisa, Choirunnisa Hasna Nugroho, Muhammad Dimas Alfian Nur Arifah, Miftah Nur, Rachmat Kahfiwan Nurfuad, Khilmi Nurhalisa, Siti Nurhidajah Nurmalita, Rahma Nurohmah, Nufita Okiyanto, Rizal Pandiriyan, Muhammad Tegar Permata, Alia Prastiwi, Harvina Sindy Prastyo, Ikwan Pratama, Rifin Fadilla Pratama, Rizky Adi Priambodo, Danu Prissy Nusaiba Yulisa Prizka Rismawati Arum Purnama, Estyaningsi Purnomo Putro, Dwi Puspitasari, Linda Putra, Septian Malik Putri Wahyu Muharamah Putri, Agata Dwi Putri Putri, Melfia Verahma R.A Qonita Syalsabilla Handayani RA. Qonita Syalsabilla Handayani Rahma Nurmalita Ramadhan, Abimanyu Arya Ramadhan, Wulan Nur Rangga Sa'adillah SAP Rendi Andika Putra Ridwanulhaq, Alfina Fauziah Rochdi Wasono Rochdi Wasono Rochdi Wasono Ryan Mahardika Sa'adah , Lydia Nur Sa'adah, Lydia Nur Safira, Elfina Latifah Safira, Rahma Salma, Nadia Khoirunnafisa Salmah Salmah Salsabila Rahma Anisa Salsabilla, Havinka Angel Salwa Salsabila, Galuh Sam'an, Muhammad Sanmas, Safril Ahmadi Saputri, Atika Dwi Sarah, Albertus Dion Sari, Selvi Ana Windia Sawiah Adam, Asriyanti Septi Winda Utami Septia, Siti Fajar Sesotyaning Harum Prabuningrat Shinta Amaria Sidqi, Isnaeni Miftahul Sintya, Salsabila Dhea Siswahyudianto Siti Hamidah Ardhy siti wulandari Suci Izzati Suci Laeliyah Suci Mega Puji Lestari Suherdi, Andri Sulistiya, Indah Sulistiyani, Dwi 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 Wahid, Siti Nurasriyanti Wahyuningsih, Andria Watur, Annisa Cahyaningrum Widiyanti, Karin Dita Widyasari, Velia Arni Wulan Sari Wulan Sari, Wulan Yan Nazala Bisoumi Yolan Triky Yulia Nur Kumala Yulianita, Tanti