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All Journal J@TI (TEKNIK INDUSTRI) Media Statistika JURNAL MATEMATIKA STATISTIKA DAN KOMPUTASI CAUCHY: Jurnal Matematika Murni dan Aplikasi Jurnal Ilmiah Kursor BIOTIK: Jurnal Ilmiah Biologi Teknologi dan Kependidikan Jurnal Ilmiah Pangabdhi Journal of Natural Sciences and Mathematics Research Jurnal Ekonomi dan Bisnis Islam Jurnal Pengukuran Psikologi dan Pendidikan Indonesia (JP3I) Jurnal Sains Matematika dan Statistika INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi Jurnal Matematika: MANTIK MUST: Journal of Mathematics Education, Science and Technology BAREKENG: Jurnal Ilmu Matematika dan Terapan JOURNAL OF APPLIED INFORMATICS AND COMPUTING JTAM (Jurnal Teori dan Aplikasi Matematika) Zeta - Math Journal J Statistika: Jurnal Ilmiah Teori dan Aplikasi Statistika Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI) Mathvision : Jurnal Matematika Journal of Islamic Monetary Economics and Finance Variance : Journal of Statistics and Its Applications Jurnal Varian Publica: Jurnal Pemikiran Administrasi Negara Jurnal ABDINUS : Jurnal Pengabdian Nusantara G-Tech : Jurnal Teknologi Terapan Inferensi Contemporary Mathematics and Applications (ConMathA) ESTIMASI: Journal of Statistics and Its Application Didaktika: Jurnal Pemikiran Pendidikan JAMBURA JOURNAL OF PROBABILITY AND STATISTICS Journal of Mathematics Education and Science Tensor: Pure and Applied Mathematics Journal Jurnal Jeumpa Biofaal Journal Indonesian Community Journal Islamiconomic: Jurnal Ekonomi Islam Journal of Health and Nutrition Research Prosiding Konferensi Nasional Penelitian Matematika dan Pembelajarannya Journal of Scientific Research, Education, and Technology Journal Focus Action of Research Mathematic (Factor M) Jurnal Statistika dan Komputasi (STATKOM) Jurnal Pengabdian Masyarakat Bangsa PCJN Pharmaceutical and Clinical Journal of Nusantara Eksponensial Jurnal Kebijakan Ekonomi dan Keuangan Jurnal Pendidikan Matematika Jurnal Agroteknologi Merdeka Pasuruan Limits: Journal of Mathematics and Its Applications
M. Fariz Fadillah Mardianto
Department Of Mathematics, Faculty Of Science And Technology, Universitas Airlangga, Jl. Dr. Ir. H. Soekarno, Mulyorejo, Kec. Mulyorejo, Kota Surabaya, Jawa Timur 60115
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Peningkatan Retensi Konsep Turunan Trigonometri Melalui Kegiatan Asistensi Mengajar Dengan Metode Mnemonik Sihite, Rivaldi; Mardianto, M Fariz Fadillah
Jurnal Pengabdian Masyarakat Bangsa Vol. 3 No. 9 (2025): November
Publisher : Amirul Bangun Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59837/jpmba.v3i9.3448

Abstract

Rendahnya retensi konsep siswa terhadap turunan fungsi trigonometri masih menjadi permasalahan utama dalam pembelajaran matematika di tingkat menengah. Permasalahan ini mendorong pelaksanaan program Asistensi Mengajar di SMAN 20 Surabaya dengan penerapan metode Mnemonik sebagai strategi inovatif untuk memperkuat daya ingat dan pemahaman konseptual siswa. Kegiatan dilaksanakan melalui tiga tahap, yaitu perencanaan, implementasi, dan evaluasi pembelajaran pada dua kelas dengan perlakuan berbeda, yakni metode ceramah dan metode Mnemonik. Analisis efektivitas menggunakan uji Mann-Whitney U menunjukkan perbedaan signifikan hasil tes akhir antara kedua kelompok dengan nilai p-value sebesar 0,004 < 0,05. Nilai rata-rata tes akhir kelas eksperimen mencapai 78, meningkat sebesar 10,49% dibandingkan nilai awal, serta lebih tinggi dibandingkan kelas kontrol. Siswa menghasilkan beragam bentuk Mnemonik, meliputi Mnemonik rima dengan aspek fonetik, Mnemonik frasa dan rima, dan Mnemonik pola yang mengintegrasikan simbol dan bahasa matematis. Program ini menghasilkan modul dan media pembelajaran inovatif yang berpotensi direplikasi sebagai praktik baik pembelajaran adaptif era Society 5.0.
Spatial Estimation of Land Surface Temperature using Cokriging Approach in Buleleng Regency Muhammad Daffa Bintang Setyawan; Suliyanto; Dita Amelia; M. Fariz Fadillah Mardianto
Journal of Scientific Research, Education, and Technology (JSRET) Vol. 5 No. 1 (2026): Vol. 5 No. 1 2026
Publisher : Kirana Publisher (KNPub)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58526/jsret.v5i1.1006

Abstract

Urban Heat Island (UHI) information plays a crucial role in microclimate monitoring and understanding environmental phenomena. However, the availability of observation station data is often spatially limited. This study aims to estimate Land Surface Temperature (LST) distribution in Buleleng Regency using Cokriging, utilizing the Normalized Difference Vegetation Index (NDVI) as a secondary variable due to its physical correlation with temperature. Addressing the significant scale disparity between LST and NDVI, this study applies Z-score transformation prior to modeling to ensure covariance matrix stability. Experimental variograms were constructed using Sturges' rule for lag distance determination and modeled using the Linear Coregionalization Model (LCM) to maintain a positive definite kriging matrix. Model evaluation using Leave-One-Out Cross-Validation (LOOCV) revealed a strong negative correlation between LST and NDVI (Pearson coefficient of -0.890). The Gaussian model was selected as the best fit, indicated by a low Mean Squared Error (MSE) of 2.7680 and a Mean Absolute Percentage Error (MAPE) of 3.63%. These results demonstrate that integrating NDVI through Cokriging significantly improves spatial estimation accuracy. Furthermore, this study supports the Sustainable Development Goals (SDGs), particularly Goal 13 (Climate Action) and Goal 15 (Life on Land), by providing high-precision environmental data essential for effective climate resilience planning.
STUDI KOMPARATIF MODEL MACHINE LEARNING DALAM MEMPREDIKSI KETERLAMBATAN PEGAWAI: LOGISTIC REGRESSION, SVM, DAN RANDOM FOREST Palupi, Inggrid Nindia Aprila; Mardianto, M Fariz Fadillah; Yuadi, Imam; Mariyadi, Budiyan
J@ti Undip: Jurnal Teknik Industri Vol 21, No 1 (2026): Januari 2026
Publisher : Departemen Teknik Industri, Fakultas Teknik, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/jati.21.1.76-87

Abstract

Keterlambatan karyawan adalah salah satu jenis pelanggaran terhadap disiplin kerja yang dapat berdampak pada produktivitas dan efektivitas organisasi. Penelitian ini bertujuan untuk mengembangkan serta membandingkan performa dari tiga algoritma machine learning Regresi Logistik, SVM, dan Random Forest dalam memprediksi keterlambatan pegawai dengan menggunakan data keterlambatan dan karakteristik individu. Dataset yang digunakan terdiri dari 1902 data, yang dibagi 80% data training dan 20% data testing dengan enam variabel, mencakup usia, lama bekerja, status pernikahan, jarak tempat tinggal ke kantor, jenis kendaraan yang digunakan, dan gaya hidup. Hasil analisis menunjukkan bahwa Random Forest memberikan kinerja prediktif yang paling baik dalam mengenali pegawai yang memiliki potensi untuk terlambat, dengan nilai akurasi tertinggi sebesar 0.82, presisi sebesar 0.93, recall sebesar 0.84, dan F1-score sebesar 0.88. Model ini terbukti dapat menunjukkan kemampuan klasifikasi yang andal dan seimbang. Analisis feature importance mengidentifikasi usia dan masa kerja sebagai faktor paling berpengaruh terhadap prediksi keterlambatan. Temuan ini tidak hanya memberikan wawasan baru dalam pengelolaan kedisiplinan pegawai, tetapi juga membuka peluang implementasi sistem peringatan dini yang dapat diintegrasikan ke dalam sistem kehadiran digital organisasi. Penelitian ini merekomendasikan perluasan variabel untuk studi lanjutan dan pemanfaatan hasil model sebagai dasar penyusunan kebijakan SDM yang lebih adaptif dan berbasis data. Abstract[Comparative Study of Machine Learning Models in Predicting Employee Delay: Logistic Regression, SVM, and Random Forest] Employee tardiness is one type of violation of work discipline that can impact organizational productivity and effectiveness. This study aims to develop and compare the performance of three machine learning algorithms Logistic Regression, SVM, and Random Forest in predicting employee tardiness using tardiness data and individual characteristics. The dataset used consists of 1902 data, which is divided into 80% training data and 20% with six variables, including age, length of service, last education level, marital status, distance from residence to office, type of vehicle used, and lifestyle. The results of the analysis show that Random Forest provides the best predictive performance in identifying employees who have the potential to be late, with the highest accuracy value of 0.82, precision of 0.93, recall of 0.84, and F1-score of 0.88. This model is proven to be able to demonstrate reliable and balanced classification capabilities. Feature importance analysis identifies age and length of service as the most influential factors in predicting tardiness. These findings not only provide new insights into employee discipline management but also open up opportunities for the implementation of an early warning system that can be integrated into the organization's digital attendance system. This study recommends expanding the variables for further studies and utilizing the model results as a basis for formulating more adaptive and data-based HR policies.Keywords: sustainability industry; developing strategy; MCDM
Prediksi Harga Saham Big Four Banks di Indonesia Menggunakan Deret Fourier Multirespon Mochamad Rasyid; Sediono Sediono; M. Fariz Fadillah Mardianto; Elly Pusporani
Limits: Journal of Mathematics and Its Applications Vol. 22 No. 1 (2025): Limits: Journal of Mathematics and Its Applications Volume 22 Nomor 1 Edisi Ma
Publisher : Pusat Publikasi Ilmiah LPPM Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/limits.v22i1.3379

Abstract

Antibacterial Activity of Staphylococcus capitis, Bacillus cereus, Pantoea dispersa From Telang Flower (Clitoria ternatea L) Kombucha Bath Soap as a Pharmaceutical Biotechnology Product Kolo, Yuliana; Rezaldi, Firman; Fadillah, M. Fariz; Ma'ruf, Aris; Pertiwi, Fernanda Desmak; Hidayanto, Fajar
PCJN: Pharmaceutical and Clinical Journal of Nusantara Vol. 1 No. 01 (2022): PCJN: Pharmaceutical and Clinical Journal of Nusantara
Publisher : CV. Nusantara Scientific Medical

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (437.276 KB) | DOI: 10.58549/pcjn.v1i01.1

Abstract

Telang lower kombucha is a probiotic drink that has the potential to enhance the immune system, active cosmetic ingredients, and its waste has been proven to be used as an organic liquid fertilizer preparation. The purpose of this study was to make a formulation and preparation of liquid bath soap with an active ingredient in a solution of seagrass kombucha fermentation at a sugar concentration of 20%, 30%, and 40% in inhibiting the growth of S. capitis, B. cereus, and P. dispersa bacteria. via the disc diffusion method. The results of the study have proven that based on the post hoc test analysis, kombucha bath soap at a concentration of 40% is significantly different from the concentration of 20% and 30% but not significantly different from the positive control and the concentration of 40% is the best concentration in inhibiting the growth of the three test bacteria. compared with the treatment and the two comparisons.
Exchange Rate Prediction of BRICS Countries against US Dollar Based on Multiresponse Fourier series Estimator Mardianto, M. Fariz Fadillah; Maulidya, Utsna Rosalin; Ginzel, Bryan Given Christiano; Putra, Mochamad Rasyid Aditya; Pusporani, Elly; Miswan, Nor Hamizah
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.v10i2.36983

Abstract

The dominance of the US dollar (USD) as the global reserve currency has begun to face structural challenges since the 2007-2008 financial crisis, which triggered the strengthening of the BRICS alliance. Although this alliance now controls 35% of the world's GDP and is actively pursuing de-dollarization, analysis of the volatility of their collective currencies is often limited to univariate parametric models that fail to capture inter-country dependencies and complex periodic fluctuation patterns. This study aims to fill this gap by applying a nonparametric multiresponse Fourier series regression to simultaneously model the interdependence of the five major BRICS currencies against the USD. Using weekly secondary data from June 2009 to February 2025 (817 observations) from investing.com, this study positions time as the predictor and the exchange rates of the five BRICS currencies as the response. The analysis results show that the best estimation model is obtained through a sine function without a trend component with an optimal oscillation parameter k=1, based on a minimum Generalized Cross Validation (GCV) value of 0.000702363. The prediction results from the training data produce a MAPE value of 4.7521%, which classifies the analysis as highly accurate. These findings strategically support the validation of the de-dollarization movement, providing a predictive instrument for developing countries to reduce their dependence on the USD, as well as strengthening the bargaining position of Eastern economies in a more multipolar international financial order.
Air Temperature Prediction in Sleman Yogyakarta using Fourier Series and Markov Switching Syahzaqi, Idrus; Riefky, Muhammad; Cahyoko, Fajar Dwi; Nahar, Muhammad Hafidzuddin; Pratama, Fachriza Yosa; Mardianto, Muhammad Fariz Fadillah
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.v10i2.35371

Abstract

Global warming increases the urgency of accurate local temperature forecasting, particularly in Sleman, Yogyakarta, a region characterized by diverse topography and high exposure to climate-related risks such as volcanic activity, agricultural vulnerability, and rapid urbanization. Such conditions increase the urgency for localized predictive models that can support agricultural planning, energy management, and disaster preparedness. This research used quantitative approach with a comparative predictive modelling design to predict the weekly average air temperature in Sleman by comparing two models: the Fourier Series regression and the Markov Switching Autoregressive (MSAR) model. The Fourier Series was selected for its ability to capture smooth seasonal and periodic behavior typical of climatological data, whereas the MSAR model was employed to accommodate regime shifts and nonlinear structural variations. The dataset comprises 127 weekly observations from January 2023 to June 2025 (BMKG), the data were split into 70% training and 30% testing. Model performance was assessed using GCV, MSE, MAE, MAPE, and residual diagnostics. Results show that the Fourier Series model performs substantially better, achieving lower GCV (0.3520), MSE (0.00415 training; 0.00114 testing), and MAE (0.34015 training; 0.12940 testing), as well as lower MAPE (1.26% training; 0.47% testing). In contrast, the MSAR model yields higher errors with GCV (0.5747), MSE (0.9113 training; 0.4686 testing), MAE (0.8005 training; 0.5512 testing), and MAPE (1.96% training; 1.34% testing). These results indicate that Sleman’s temperature dynamics characterized by stable oscillatory patterns with minimal regime shifts are more effectively captured through harmonic decomposition. The study reinforces the importance of periodic modeling for mixed-topography regions like Sleman and recommends future research integrating additional climatic variables, hybrid statistical–machine-learning frameworks, and longer time spans to improve responsiveness to extreme events and nonlinear atmospheric behavior.
Pemodelan Faktor yang Mempengaruhi Indeks Demokrasi Indonesia Menggunakan Spline Truncated Hanny Valida; M. Fariz Fadillah Mardianto; Dita Amelia; Suliyanto Suliyanto
Jurnal Pendidikan Matematika Vol. 3 No. 2 (2026): February
Publisher : Indonesian Journal Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47134/ppm.v3i2.2478

Abstract

Penelitian ini bertujuan menganalisis faktor-faktor yang memengaruhi Indeks Demokrasi Indonesia (IDI) menggunakan pendekatan regresi spline linier terpotong nonparametrik. Data yang digunakan merupakan data sekunder cross-section dari 34 provinsi di Indonesia pada tahun 2024, dengan variabel prediktor berupa Indeks Pemberdayaan Gender, Indeks Kebebasan Pers, dan Indeks Pembangunan Manusia. Pemilihan model dilakukan menggunakan kriteria Generalized Cross Validation (GCV) untuk menentukan jumlah dan posisi knot yang optimal. Hasil analisis menunjukkan bahwa model terbaik diperoleh dengan tiga titik knot, menghasilkan nilai GCV sebesar 6,79 dan koefisien determinasi (R²) sebesar 89,37 persen. Hasil penelitian menunjukkan adanya hubungan nonlinier antara variabel prediktor dan IDI. Indeks Pemberdayaan Gender memberikan pengaruh positif pada tingkat rendah hingga menengah, namun berubah menjadi negatif pada tingkat yang lebih tinggi. Indeks Kebebasan Pers menunjukkan pengaruh positif pada tingkat rendah tetapi cenderung negatif setelah melewati titik tertentu. Sementara itu, Indeks Pembangunan Manusia memberikan pengaruh positif yang konsisten terhadap IDI. Temuan ini menunjukkan bahwa kualitas demokrasi di Indonesia dipengaruhi oleh dinamika sosial dan institusional yang kompleks.
Forecasting Rupiah Exchange Rate Volatility using a Hybrid ARIMA–SVR Model as an Early Warning System to Address Global Dynamics Idrus Syahzaqi; Selvina Cindy Kusumaningrum; Naufal Ainul Hayat; M. Fariz Fadillah Mardianto
JTAM (Jurnal Teori dan Aplikasi Matematika) Vol 10, No 3 (2026): July
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jtam.v10i3.38570

Abstract

Exchange rate volatility of the Indonesian Rupiah against the US Dollar has increased due to global uncertainty. This study addresses the limitation of prior research that predominantly relies on single linear or nonlinear models in emerging markets by developing a Hybrid ARIMA SVR approach, thereby enhancing exchange rate predictability to support macroeconomic stability. This study contributing to the advancement of quantitative forecasting methods aligned with SDG 8 and SDG 16 through enhanced financial predictability. This research uses a univariate time-series dataset of weekly Rupiah US Dollar exchange rates obtained from Bank Indonesia, comprising 150 observations from March 2023 to January 2026. Novelty from this research is ARIMA model selected to capture linear temporal dependencies, while SVR is employed to model nonlinear patterns in residuals justifying the hybrid approach as a complementary integration of statistical and machine learning methods. Data preprocessing includes Box-Cox transformation and second order differencing to ensure stationarity, followed by diagnostic tests (Ljung Box, Kolmogorov Smirnov, and ARCH LM). SVR parameters are optimized using grid search to ensure robust model performance. The analysis included visualization, Box–Cox transformation (λ = −1), and second-order differencing to achieve stationarity. Diagnostic tests (Ljung Box, Kolmogorov Smirnov, ARCH LM) confirmed that ARIMA (3,2,0) met model assumptions. ARIMA residuals were subsequently model using SVR, with parameters optimized through grid search, forming the Hybrid ARIMA–SVR model. Results show that the Hybrid ARIMA SVR model outperformed the standalone ARIMA, achieving a lower MAPE. The best performance (MAPE = 0.56%) was obtained using the Radial kernel with ε = 0.2, C = 23, and γ = 28. These findings indicate that integrating linear and nonlinear models improves forecasting accuracy.
Factors Affecting Interest in Revisiting Kare Tourism Village Based on Structural Equation Modeling M Fariz Fadillah Mardianto; Elly Pusporani; Suliyanto Suliyanto; Sri Endah Nurhidayati; Na’imatul Lu’lu’a; Marcelena Vicky Galena
Inferensi Vol 9 No 1 (2026)
Publisher : Department of Statistics ITS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j27213862.v9i1.9951

Abstract

This research focuses on analyzing the factors that affect tourists' intentions to revisit Kare Tourism Village. Utilizing quantitative methods, primary data were gathered through questionnaires from 105 tourists who had previously visited the village. The SEM-PLS method was employed for analysis. In this study, several latent variables were identified, including facilities and services in Kare Tourism Village as exogenous latent variables, tourist satisfaction as both an endogenous latent variable and an intermediate variable, and tourist interest as the dependent variable. The findings reveal an value of 0.876 for tourist satisfaction, indicating that 87.6% of the variation in satisfaction can be explained by the model, which is considered strong. In contrast, the R² value for tourist interest is 0.548, suggesting that 54.8% of the variation in interest is explained by the model, classified as moderate. Additionally, the GoF value of 0.673 demonstrates a high model fit. Furthermore, the service variables in Kare Tourism Village significantly impact tourist satisfaction.
Co-Authors Abdilah, Nurullah Asep Abdillah, Adrian Wahyu Adma Novita Sari Adnan Syawal Adilaha Sadikin Adriansyah, Muhammad Haykal Afifa, Fitriana Nur Aflaha, Nabila Shafa Agnes Happy Julianto Agustiansyah, Lucky Dita Ahmad Saddam Hussein Ain, Dzuria Hilma Qurotu Ainaya Zakiyah Nabila Aini Divayanti Arrofah Aldawiyah, Najwa Khoir Aldawiyah, Najwa Khoir Alexandra, Victoria Anggia Alfi Nur Nitasari Alfredi Yoani Aliffia, Netha Almira Sophie Syamsudin Alya Rahma Inneztiana Amalia, Nadinta Kasih Amalia, Rica Ana, Elly Andi Vania Ghalliyah Putrie Andri Tri Cahyono Andriani, Putu Eka Anggara Teguh Previan Anggriawan, Muhammad Rizal Anggriawan, Muhammad Rizal Annisa Putri Nayumi Antonio Nikolas Manuel Bonar Simamora Anwari, Anwari Apidianti, Sari Pratiwi Aprilia Prastyaningrum Ardi Kurniawan Ardi Kurniawan Ariyawan, Jovansha Arum Eka Ismiranda Putri Astuti, Aprillia Audilla, Marfa Aulia Ramadhanti Aulia, Niswa Faizah Ayu Safitri Ayuning Dwis Cahyasari Ayuning Dwis Cahyasari Azzah Nazhifa Wina Ramadhani Bimo Okta Syahputra Bintang Alyaa Sabila Br Pangaribuan, Fani Agustina Budijono, Gabriella Agnes Cahyoko, Fajar Dwi Candra Junaedi Chaerobby Fakhri Fauzaan Purwoko Chairunnisa, Nurul Rizky Christopher Andreas Citra Imama Cynthia Anggelyn Siburian Darmawan, Kezia Eunike Davina Shafa Vanisa Deshinta Arrova Dewi Devayanti Anugerahing Husada Dewanty, Sanda Insania Dewi, Berlianti Alisa Dewi, Deshinta Arrova Disty Ridha Hastuti Dita Amelia Dita Amelia Dita Amelia, Dita Doni Muhammad Fauzi Dwiyanto, Adelia Sukma Dyah Rohma Wati Efan Yudha Winata Eka Rani Fitrianingsih Eko Fajar Cahyono, David Kaluge Elly Anna Elly Pusporani Elok Zubaidah Eris Tri Kurniawati Erlina Anggraini Erlina Anggraini, Erlina Evi Wijayawati Faisol Faisol Faisol, Faisol Faizun, Nurin Fajar Hidayanto, Fajar Fajrina, Sofia Andika Nur Faradilla Harianto Farah Fauziah Putri Farizi, Muhammad Fikry Al Fatiha Nadia Salsabila Fatihah, Amelia Fauzi, Doni Muhammad Febriyani, Eka Riche Fernanda Desmak Pertiwi Firda Aulia Pratiwi Fitri, Marfa Audilla Fitria Eka Resti Wijayanti Fitriyani, Mubadi’ul Fortunata, Regina Galena, Marcelena Vicky Ghasani, Anisah Nabilah Ginzel, Bryan Given Christiano Girsang, Anne Vinella Grace Lucyana Koesnadi Hanny Valida Haq, Affan Fayzul Hari Hariadi, Hari Hasanah, Sarmiatul Helda Urbhani Rosa Helfira Lady Ari Pramesti Hermawan, Mohamad David Humaira, Edla Putri I Kadek Pasek Kusuma Adi Putra I Nyoman Budiantara Idrus Syahzaqi Ika Purnamasari Imam Yuadi Immanuel Alexander Sirait Inneztiana, Alya Rahma Ira Yudistira Irma Ayu Indrasta Ismi, Ferissa Maulida Isna Nurul Izza Amalia Karina Rubita Makhbubah Karina Tri Handayani Koesnadi, Grace Lucyana Koesnadi, Grace Lucyana Kresna Oktafianto Kurnia, Rizky Dwi Kusuma, Shalwa Oktavia Kusumasari Kartika Hima Darmayanti Kuzairi Larisa Mutiara Putri Leni Halimatusyadiah Lu'lu'a, Na'imatul Lu’lu’a, Na’imatul M. Nabil Saputra Ma'ruf, Aris Mahadesyawardani, Arinda Makhbubah, Karina Rubita Mamdudah, Siti Marbun, Barnabas Anthony Philbert Marcel Laverda Subiyanto Marcel Laverda Subiyanto Marcelena Vicky Galena Marcelena Vicky Galena Maria Setya Dewanti Maritha, Vevi Marthabakti, CitraWani Maulidya, Utsna Rosalin Meliyawati Meliyawati Miswan, Nor Hamizah Mochamad Rasyid Mochammad Baihaqi Mochammad Imron Awalludin Muhammad Andry Muhammad Daffa Bintang Setyawan Muhammad Faizal Fathurrohim Muhammad Faizhal Fathurrohim Muhammad Fikry Al Farizi Muhammad Hafid Fauzan Muhammad Luthfi Muhammad Rizaldy Baihaqi Muhammad Rosyid Ridho Az Zuhro Muhammad Walid Jumlat Mu’jijah Mu’jijah Na&#039;imatul Lu&#039;lu&#039;a Nabila Angel Nafisha Nadia Dwi Marwanda Nahar, Muhammad Hafidzuddin Nariswari, Anggita Naufal Ainul Hayat Naufal Ramadhan Al Akhwal Siregar Nauvaldy, Muhammad Na’imatul Lu’lu’a Netha Aliffia Nitasari, Alfi Nur Noer Azizah Nur Chamidah Nurdin, Nabila Nurfitriyah, Luluk Nurmaulawati, Rina Nurrohmah, Zidni ‘Ilmatun Nurul M’rifatil Laila Nurvadilah, Eva Palupi, Inggrid Nindia Aprila Pambudi, Daffa Satrio Pamungkas, Barolym Tri Panjaitan5, Leni Sartika Permana, Made Riyo Ary Pertiwi, Fernanda Desmak Pratama, Bagas Shata Pratama, Fachriza Yosa Pratiwi, Firda Aulia Prayitno Prayitno Pressylia Aluisina Putri Widyangga Previan, Anggara Teguh Purba, Gaby Valenia Rosa Pusporani, Elly Putra, Mochamad Rasyid Aditya Putra, Mochamad Rasyid Aditya Putri Fardha Asa Oktavia Hans Putri Masyita Qomaryah Putri, Asyifa Charmadya Putri, Farah Fauziah Putri, Ferdiana Friska Rahmana Putri, Larisa Mutiara Putrie, Andi Vania Ghalliyah Putu Eka Andriani Rachma Hikmaya Rahmada, Indrastanto Oktodian Rahmi Fadhillah, Fitri Raka Andriawan Ramadhan, Achmad Wahyu Ramadhani, Maulana Syah Putra Ramadhanty, Devira Thania Rani, Lina Nugraha Recylia, Rien Reswara, Aqil Azmi Reynaldy Aries Ariyanto Reza Febrian Nugroho Rica Amalia Riefky, Muhammad Rohman, Naylur Romadhoni, M. Suma Firman Romadhoni, Moh Suma Firman Rosyida Widadina Ulya Rosyida Widadina Ulya Sadikin, Adnan Syawal Adilaha Safitri , Endang Safitri, Endang Sahidah, Sahidah Sakinah Priandi Salsabila, Fatiha Nadia Sanda Insania Dewanty Sari, Adma Novita Sari, Adma Novita Sasy Okti Karima Sa’idah Zahrotul Jannah Sa’idah Zahrotul Jannah Sa’idah, Andini Sediono, Sediono Selvina Cindy Kusumaningrum Setyaji, Diyan Yunanto Shafira Renianti, Fayza Sholiha, Anisatus Siagian, Kimberly Maserati Sifa, Ghisella Asy Sifriyani, Sifriyani Sihite, Rivaldi Sihombing, Abednego Siregar, Naufal Ramadhan Al Akhwal Siswahyudianto Siti Maghfirotul Ulyah Siti Maghfrotul Ulyah Siti Romlah Sofia Andika Nur Fajrina Sri Endah Nurhidayati Sri Wahyuningsih Steven Soewignjo Sugha Faiz Al Maula Al Maula Sukardi Sugeng Rahmad Sulaiman, Faizah Jauhar Suliyanto Suliyanto Suliyanto Suliyanto Suryono, Alda Fuadiyah Swastika Oktavia Syahfitri, Nabila Syahzaqi, Idruz Tagawa, Dustin Nathanael Tanjung, Siti Aisiyah Tika Widiastuti Toha Saifudin Tony Yulianto Ucu Wandi Somantri Ukhrowi, Putri Usman Setiawan Vanisa, Davina Shafa Wibawa, Yoga Setya Widyangga, Pressylia Aluisina Putri Widyangga, Pressylia Aluisina Putri Wijayanti Wijayanti Wulandari, Indana Zulfa Yenny, Ratna Fitry Yudistira, Ira Yuliana Kolo Yuniar, Muhammad Alvito Dzaky Putra Yusuf, Bima Sakti Putra Yuwinani, Iin Zah, Alfian Iqbal Zahrani, Vista Vanadya Zalfaa Nur Amalia Zhafirab, Azizah Atsariyyah Zuleika, Talitha Zuleika, Talitha Zuleika, Talitha