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All Journal Pythagoras: Jurnal Matematika dan Pendidikan Matematika Media Statistika JURNAL MATEMATIKA STATISTIKA DAN KOMPUTASI SAINSMAT Jurnal Statistika Universitas Muhammadiyah Semarang CAUCHY: Jurnal Matematika Murni dan Aplikasi TELKOMNIKA (Telecommunication Computing Electronics and Control) Bulletin of Electrical Engineering and Informatics Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) Matematika dan Sains Jurnal Ketahanan Nasional Journal of Information Systems Engineering and Business Intelligence Prosiding SI MaNIs (Seminar Nasional Integrasi Matematika dan Nilai-Nilai Islami) MUST: Journal of Mathematics Education, Science and Technology BAREKENG: Jurnal Ilmu Matematika dan Terapan JTAM (Jurnal Teori dan Aplikasi Matematika) Zeta - Math Journal J Statistika: Jurnal Ilmiah Teori dan Aplikasi Statistika Zero : Jurnal Sains, Matematika, dan Terapan Cakrawala: Jurnal Litbang Kebijakan Jurnal Aplikasi Statistika & Komputasi Statistik JCRS (Journal of Community Research and Service) Jurnal Ilmiah Manajemen dan Bisnis JP2M (Jurnal Pendidikan dan Pembelajaran Matematika) G-Tech : Jurnal Teknologi Terapan Inferensi Contemporary Mathematics and Applications (ConMathA) Jurnal Layanan Masyarakat (Journal of Public Service) JURPIKAT (Jurnal Pengabdian Kepada Masyarakat) Enthusiastic : International Journal of Applied Statistics and Data Science Seminar Nasional Hasil Riset dan Pengabdian (SNHRP) SAINSMAT: Jurnal Ilmiah Ilmu Pengetahuan Alam Aurelia: Jurnal Penelitian dan Pengabdian Masyarakat Indonesia Indonesian Vocational Research Journal Jurnal Pendidikan Matematika PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON DATA SCIENCE AND OFFICIAL STATISTICS Jurnal Pengabdian Nasional (JPN) Indonesia Feelings: Journal of Counseling and Psychology Seminar Nasional Riset dan Teknologi (SEMNAS RISTEK) Jurnal Teknologi Informasi untuk Masyarakat (Jurnal Teknokrat) Indonesian Journal of Statistics and Its Applications Jurnal Ilmu Sosial dan Humaniora Limits: Journal of Mathematics and Its Applications Jurnal Riset Sosial Humaniora dan Pendidikan
Nur Chamidah
Departemen Matematika, Fakultas Sains Dan Teknologi, Universitas Airlangga
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Classification and Counting of Mycobacterium Tuberculosis using YOLOv5 Saurina, Nia; Chamidah, Nur; Rulaningtyas, Riries; Aryati, Aryati
Journal of Information Systems Engineering and Business Intelligence Vol. 11 No. 2 (2025): June
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/jisebi.11.2.267-278

Abstract

Background: Indonesia is a nation with the third-highest number of tuberculosis (TB) cases worldwide, after China and India. TB detection has been facilitated using YOLOv5 deep learning framework despite previous studies not having incorporated assessment metrics recommended by International Union Against Tuberculosis and Lung Disease (IUATLD).   Objective: This study aims to present a method for classifying and enumerating Mycobacterium tuberculosis by using YOLOv5 architecture with IUATLD evaluation standards. Sputum samples served as the primary medium for identifying the presence of Mycobacterium tuberculosis. In addition, the method showed precise delineation of bacterial boundaries to minimize classification inaccuracies and improve edge clarity through YOLOv5.  Methods: Following the acquisition of microscopic images of TB, the data were resized from 1632x1442 to 640x480 pixels. Annotation was performed using YOLOv5 bounding boxes, and the model was subsequently trained as well as tested according to IUATLD guidelines.  Results: During the analysis, YOLOv5-based classification system produced optimal performance. The model achieved 84.74% accuracy, 87.31% precision, and Mean Average Precision (mAP) score of 84.98%. These metrics showed high reliability in identifying Mycobacterium tuberculosis in the image dataset.  Conclusion: The classification and quantification of Mycobacterium tuberculosis using YOLOv5 framework shows high precision, with mAP score of 84.98%, signifying strong model performance. Additionally, the counting process achieves a MAPE (Mean Absolute Percentage Error) of 0.15%, reflecting excellent prediction accuracy.  Keywords: IUATLD, Tuberculosis, YOLOv5.
JCI MODELING IN INDONESIA BASED ON INDUSTRIAL PRODUCTION INDEX WITH LOCAL POLYNOMIAL ESTIMATOR APPROACH Hidayat, Rizky Ismaul Uyun; Prasetyo, Juan Krisfigo; Larasati, Berliani; Aisharezka, Mutiara; Chamidah, Nur
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 17 No 3 (2023): BAREKENG: Journal of Mathematics and Its Applications
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol17iss3pp1277-1286

Abstract

The industrial sector is the leading sector that contributes the most to Indonesia's economic growth. Industry can be caused by various factors, one of which is the Jakarta Composite Index (JCI). Indonesian stock prices have a high variance that requires proper modeling. Therefore, this study uses a local polynomial nonparametric regression approach. This study aims to estimate and obtain the best JCI model based on the production index of large and medium industries using a local polynomial estimator and also knowing the accuracy of the JCI model based on the production index of large and medium industries. The data used in this study is secondary data using production index data for medium-large industries and data on the composite stock index in Indonesia in the form of Time series which were obtained through the Central Statistics Agency Publication website on the page www.bps.go.id. JCI modeling in Indonesia based on the production index of large and medium industries is most effective on local polynomials with polynomial degree two which obtains an optimal bandwidth of 7,8795 with a minimum Cross-Validation (CV) value of 163170,3 and a Mean Absolute Percentage Error (MAPE) value of 9,1%. From the MAPE value it is said that the model is good for making future predictions.
CATEGORICAL ANALYSIS TO PERCEPTIONS OF GOVERNMENT POLICY IN ELECTRICITY FUEL MANAGEMENT AS ALTERNATIVE TO SUBSTITUTE OIL FUEL USING CHI-SQUARE TEST Chamidah, Nur; Siregar, Naufal Ramadhan Al Akhwal; Al Farizi, Muhammad Fikry; Pratama, Bagas Shata; Faiza, Atikah; Fibryan, Muhammad Hilmi
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 17 No 3 (2023): BAREKENG: Journal of Mathematics and Its Applications
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol17iss3pp1287-1300

Abstract

The scarcity and increase in world oil prices is a tough dilemma that must be responded to by the Indonesian government. In order to prevent fuel consumption from swelling, the government plans to reduce fuel subsidies. The plan certainly has many positive impacts, including savings on government finances so that they can be diverted to fund other programs that are more effective and on target. These savings are also useful in reducing the budget deficit, controlling the consumption of fuel oil, and saving non-renewable natural resources. It is appropriate for the state to think hard about switching energy to New and Renewable Energy (EBT) so that people's dependence on fossil energy consumption can be shifted. Therefore, this study aims to determine the current public perception of government policies in the management of fossil fuel energy so that they can be considered by the government in making comprehensive policy decisions. The data used in this study is in the form of primary data obtained from respondents with a population of Indonesian people and collected online through a questionnaire. The data analysis method in this study used the independence test with the chi-square test on categorical data. The results of this study indicate that there is a relationship between the level of public perception of the basic policy of managing electric fuel with the last level of education, type of work, and the area of the population.
COMPARISON OF LOCAL POLYNOMIAL REGRESSION AND ARIMA IN PREDICTING THE NUMBER OF FOREIGN TOURIST VISITS TO INDONESIA Pratama, Bagas Shata; Suryono, Alda Fuadiyah; Auliyah, Nina; Chamidah, Nur
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 18 No 1 (2024): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol18iss1pp0043-0052

Abstract

Indonesia is a country that has a variety of exotic tourist destinations and can attract tourists to visit. Currently, tourism is one of the sectors that plays a major role in driving the Indonesian economy. Various tourists, both domestic and foreign, are expected to continue to increase in number every year. Therefore, appropriate policies are needed from the government to develop the tourism sector so that it can be even better over time. This research aims to predict the number of foreign tourist visits to Indonesia using the Autoregressive Integrated Moving Average (ARIMA) model and local polynomial regression. The data used in this research is the number of foreign tourist visits per month from January 2017 to December 2022 obtained from the the Kemenparekraf website. This data is fluctuating so that the method a local polynomial approach is appropriate for this study. The data analysis method used are local polynomial regression and ARIMA model. In the ARIMA model there are assumptions that must be met. In this study, the ARIMA model obtained has met the assumption of residual normality but does not meet the assumption of homoscedasticity so that ARIMA modeling cannot be continued and analysis is only carried out with local polynomial regression. The result of this study is a prediction of future tourist visits. The MAPE value of the local polynomial regression approach is 1.43% which is categorized as a prediction with high accuracy because the value is less than 10%. Thus, the local polynomial regression approach is very well used to predict the number of foreign tourist visits to Indonesia.
MODELING LONGITUDINAL FLOOD DATA IN WEST SUMATRA USING THE GENERALIZED ESTIMATING EQUATION (GEE) APPROACH Nitasari, Alfi Nur; Sa'idah, Andini; Faizun, Nurin; Darmawan, Kezia Eunike; Fitri, Marfa Audilla; Chamidah, Nur
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 18 No 4 (2024): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol18iss4pp2181-2190

Abstract

Flooding is one of the many natural disasters that often hit Indonesia. In July 2023, three areas in West Sumatra experienced floods and landslides which caused damages and even 2 missing victims. Since November 16th, 2023, 8 hamlets in Meranti Village, Landak District, West Sumatra have been inundated by floods which affected families and many public facilities. This research uses data from West Sumatra Province Central Statistics Agency. The data used is 2014, 2018 and 2021. The response variable used is the number of villages/sub-districts experiencing natural disasters according to district/city ( ). The predictor variables used are regional topography , the number of water channels such as rivers, reservoirs, etc. , the number of fields cleared through burning , the number of villages/sub-districts in C excavation area , and the number of dumpsters . This research uses Negative Binomial Regression with the Generalized Estimating Equation (GEE) approach. In the Poisson regression test, the QIC value based on Independent Working Correlation Structure (WCS) is with deviance value of , degree of freedom of , and dispersion score of 4,6144. Because the dispersion value is greater than 1, it can be concluded that there is overdispersion. Because there is more than one overdispersion, it is overcome by using negative binomial. The results of parameter estimation using negative binomial regression based on Independent WCS showed that only one variable was significant, which is the number of fields cleared through burning with deviance value of , degrees of freedom of and a QIC of . Negative Binomial regression model that was formed is ). From the two regression models used, namely Poisson and negative binomial, it was found that the negative binomial regression model was the best model because it had the lowest QIC value of .
MODELLING CRIME RATES IN INDONESIA USING TRUNCATED SPLINE ESTIMATOR Juniar, Muhammad Althof; Fania, Azzahra; Ulya, Diana; Ramadhan, Rico; Chamidah, Nur
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 18 No 2 (2024): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol18iss2pp1201-1216

Abstract

Criminal acts are actions that violate the law and can arise from various factors such as emotions, psychological pressure, and others. Crime rate is a number that indicate the level of crime vulnerability in a certain area at a certain time. Higher crime rates correspond to increased vulnerability in an area, and vice versa. Among various forms of criminal acts, the number of criminal acts and narcotics crimes in Indonesia tends to increase in 2020 and 2021. The aim of the research is to identify the characteristics of crime rate data based on the number of decency and narcotics incidents in Indonesia using a nonparametric regression approach. This research uses a nonparametric regression method spline truncated and linear regression as comparison. It was found that West Papua Province has the highest crime rate, based on a comparison between linear regression model and truncated spline nonparametric regression model, it can be concluded that the best model is the truncated spline nonparametric regression model with a Generalized Cross Validation (GCV) of 2468.487 and a coefficient of determination of 0 .7389091, indicating that approximately 73% of the variability of the dependent variable can be explained by the independent variables included in the model.
ANALYSIS OF RELATIONSHIP BETWEEN THE USAGE OF ONLINE LOAN SERVICES AND THE WELL-BEING OF INDONESIAN USING CHI-SQUARE TEST Chamidah, Nur; Kamiilah, Nadhira Safa; Andriani, Putu Eka; Siburian, Cynthia Anggelyn; Baihaqi, Muhammad Rizaldy; S, Salma Bethari Andjani
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 18 No 2 (2024): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol18iss2pp1217-1228

Abstract

Online fintech lending offers convenience by providing flexibility for both lenders and borrowers. It led to a significant increase in users. Despite this encouraging growth, it comes with risks, such as the emergence of illegal loan companies. The controversial positive and negative aspects of online loans have sparked the researchers' interest in understanding how the Indonesian public perceives the existence of online loans and whether there is a relationship between the use of online loans and the well-being of users. The data were collected through the questionnaire using Google Form and then distributed to respondents who meet the specified sample criteria, namely Indonesian, aged 17 years old or above, and still able to think rationally. The total study sample are 191 respondents, with the total male is 90 and the total female is 101. Since the results of the data gathered were in the form of categorical data, so the Chi-square test is utilized in this study. With the calculated chi-square less than the chi-square table, it showed that there is no correlation between the frequency of using online loan services and the well-being of the Indonesian people, whether based on age, level of education, or type of job. Hence, it can be concluded that the usage of online loan services is not influences the well-being of Indonesian. It is also known that public perceptions of online loans vary and cannot be generalized. However, those less prosperous, tend to agree with and appreciate the online loan services’ existence compared to those who are prosperous.
PREDICTION OF CRUDE OIL PRICES IN INDONESIA USING FOURIER SERIES ESTIMATOR AND ARIMA METHOD Rahma, Alma Khalisa; Abidin, Qumadha Zaenal; Prasetyo, Juan Krisfigo; Larasati, Berliani; Amelia, Dita; Chamidah, Nur
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 18 No 3 (2024): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol18iss3pp1673-1682

Abstract

Crude oil is one of the non-renewable natural resources that is crucial for countries around the world in driving economic development. However, the availability of crude oil is decreasing over time. The high demand for crude oil results in scarcity which causes price fluctuations. Low oil prices can reduce state revenues, disrupt development programs, and even trigger budget deficits. On the other hand, an increase in crude oil prices can make a positive contribution to state revenues. Crude oil exports become more profitable, which can increase state revenue through royalties and taxes levied on the oil and gas sector. This additional revenue can be used to support infrastructure development, social programs, and investment in key sectors of the economy. High oil prices can also harm the economy. With the many impacts that can be caused by crude oil prices, the government must be able to anticipate and prepare for it. The data used in this study are data on crude oil prices in Indonesia for monthly periods from January 2018 to October 2023 sourced from the official website of the Ministry of Energy and Mineral Resources (ESDM) of the Republic of Indonesia. The researcher tried to compare two analysis methods, namely the Fourier series and the ARIMA estimator. The results of this study show that the best method in predicting crude oil prices in Indonesia is the Fourier series estimator with Cos-Sin function which produces RMSE and MAPE values of 7.93 and 8.4%. The prediction results can be used as a reference for the government to anticipate and make programs or policies that are more focused and targeted toward the impacts that can be caused by changes in crude oil prices.
CHINESE YUAN EXCHANGE RATE AGAINST THE INDONESIAN RUPIAH PREDICTION USING SUPPORT VECTOR REGRESSION Soewignjo, Steven; Septia Sari, Ni Wayan Widya; Mediani, Andini Putri; Kamil, M. Aqil Zaidan; Amelia, Dita; Chamidah, Nur
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 18 No 3 (2024): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol18iss3pp1683-1694

Abstract

This study aims to forecast the exchange rate between the Chinese Yuan (CNY) and the Indonesian Rupiah (IDR) using Support Vector Regression (SVR), a machine-learning technique that can handle nonlinear and complex data. The authors utilize the monthly selling exchange rate of CNY against IDR from January 2012 to October 2023 sourced from the “investing” platform. The optimal SVR model is obtained by splitting the data into 113 training samples and 28 testing samples and using the Radial Basis Function (RBF) kernel. The model achieves high accuracy, with a Mean Absolute Percentage Error (MAPE) of 1.738%, a Root Mean Squared Error (RMSE) of 50.661 for the training data and a MAPE of 2.516%, and an RMSE of 64.735 for the testing data. The results of this paper can provide valuable insights for policymakers, investors, and traders who are interested in the CNY/IDR exchange rate dynamics and the economic implications of the Belt and Road Initiative (BRI). The study aligns with the Sustainable Development Goals (SDGs), specifically SDG 8, aiming to promote sustained, inclusive, and sustainable economic growth.
MODELING HYPERTENSION DISEASE RISK IN INDONESIA USING MULTIVARIATE ADAPTIVE REGRESSION SPLINE AND BINARY LOGISTIC REGRESSION APPROACHES Chamidah, Nur; Hendrawan, Ardana Tegar; Ardiyanto, Figo Surya; Hammami, Martha Sayyida; Izzah, Nurul; Hariadi, Salsabila Niken
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 18 No 4 (2024): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol18iss4pp2217-2230

Abstract

In the pursuit of the Sustainable Development Goals (SDGs), health-related challenges, especially hypertension, remain a significant global issue. The third goal of the SDGs aims to improve the quality of life and well-being of all individuals, but hypertension is a serious problem that can hinder these goals. Often referred to as the "silent killer" by the World Health Organization (WHO), hypertension is exacerbated by low awareness. Globally, more than 1.28 billion adults suffer from hypertension, with most cases in lower to middle-income countries, including Indonesia. Indonesia has an alarming rate of hypertension incidence, ranking fifth highest in the world. Riset Kesehatan Dasar (Riskesdas) 2023 and the Indonesia Family Life Survey (IFLS) are critical for understanding hypertension risk factors in Indonesia. The IFLS data, obtained from www.rand.org, includes observations from October 2014 to April 2015, totalling 85 observations. Despite being over 10 years old, this dataset was selected because it remains the most recent comprehensive data available from RAND, representing 83% of the Indonesian population. The IFLS is conducted every 7-8 years, with the next wave of data expected soon. Most studies on hypertension globally and in Indonesia use parametric regression methods. However, a research gap exists as no studies have used Multivariate Adaptive Regression Splines (MARS) on IFLS data to analyze hypertension risk factors. This study addresses this gap by comparing binary logit regression and MARS. The analysis shows the Apparent Error Rate (APPER) for MARS is 84.706%, while for binary logistic regression it is 80%, indicating MARS is better at classifying hypertension data in Indonesia. Using MARS offers a novel approach to understanding hypertension risk factors in Indonesia. Despite the data's age, it remains relevant as primary causes and risk factors for hypertension have not changed, making the findings valuable for current health policy and strategies.
Co-Authors A Meylin Abdul Aziz Abidin, Qumadha Zaenal Afriani Agus Satmoko Adi Ahmad Fauzi Aisharezka, Mutiara Akbar, Aditya Syarifudin Al Farizi, Muhammad Fikry Al Hasri, Ilham Maulana Alda Fuadiyah Suryono Aldawiyah, Najwa Khoir Alexandra, Victoria Anggia Alfiatur Rakhma, Syavrilia Alfinda Novi Kristanti Alpandi, Gaos Tipki Amanda, Yulia Aminuyati Aminy, Aisyah Ana, Elly Ananda Dwi Andini Putri Mediani Andriani, Putu Eka Andriani, Putu Eka Angga Kusuma Bayu Viargo Anies Yulinda W Anisa Laila Azhar Any Tsalasatul Fitriyah Ardi Kurniawan Ardi Kurniawan Ardiyanto, Figo Surya Ariyawan, Jovansha Aryati Aryati Aulia, Niswa Faizah Auliyah, Nina Azizah, Khansa Azzen, Fiyadika Amalia Nurizah Baihaqi, Mochamad Baihaqi, Muhammad Rizaldy Baktiar Aris Belindha Ayu Ardhani Brenda Bunga Prasenda Budi Lestari Budi Lestari Budijono, Gabriella Agnes Christopher Andreas D Lestari Darmawan, Kezia Eunike Dhohirrobbi, Achmad Dhyana Venosia Dhyana Venosia Diah Puspita Ningrum Diana Ulya Dita Amelia Dita Amelia, Dita Dzuria Hilma Qurotu Ain Hilma Easyfa Wieldyanisa, Ezha Eko Tjahjono Elfhira Juli Safitri Fachrian, Muhammad Nadhil Faiza, Atikah Faizun, Nurin Fajrina, Sofia Fajrina, Sofia Andika Nur Fakih Hamdani Fania, Azzahra Farida Farida Fatmawati Fatmawati Fatmawati Fatmawati Fauziah, Nathania Feevrinna Yohannes Harianto Fibryan, Muhammad Hilmi FIRMANSYAH, MOCHAMMAD Fitri Syaharani, Amadea Fitri, Marfa Audilla Fitri, Marfa Audilla Fizkadana, Canada Mewa Galih Yoga Santiko Gaos Tipki Alpandi Halimatuzzahro, Fitria Hammami, Martha Sayyida Hariadi, Salsabila Niken Hendrawan, Ardana Tegar Herdianto, Muhammad Hendra Hidayat, Rizky Ismaul Uyun Horidah Horidah Huda, Mi'rojul I Nyoman Budiantara Insania Dewanty, Sanda Islamudin, Mohamad Mujahid IZZAH, NURUL Januarta, R. Arya Julianto, Agnes Happy Juniar, Muhammad Althof Kamiilah, Nadhira Safa Kamil, M. Aqil Zaidan Kamila, Yasmin Kinanti Hanugera Gusti Kuni Safingah Larasati, Berliani Lensa Rosdiana Safitri Lilik Hidayati, Lilik Listyaningsih Listyaningsih M. Fariz Fadillah Mardianto Mahadesyawardani, Arinda Mahadesyawardani, Arinda Marbun, Barnabas Anthony Philbert Marisa Rifada Marthabakti, CitraWani Maulidya, Utsna Rosalin MAYA MUSTIKA KARTIKA SARI, MAYA Mediani, Andini Putri Mediani, Andini Putri Melati Tegarina Mohamad David Hermawan Muhammad Falah El Fahmi Muhammad Fikry Al Farizi Mutiara Aisharezka Mutiara Arlisyah Putri Utami Muzakki, Naufal N. A. Aprilianti Nadia Murbarani Nahar, Muhammad Hafidzuddin Naufal Ramadhan Al Akhwal Siregar Nia Saurina Nitasari, Alfi Nur Nur Azizah Rahayu Ningsih Prasetyo, Juan Krisfigo Pratama, Bagas Shata Pratama, Fachriza Yosa Purnama, Titania Faisha Putra, Mochamad Rasyid Aditya Qumadha Zainal Abidin Rahayu, Rizky Dwi Kurnia Rahma, Alma Khalisa Rahmatika, Nabila Syahfitri Ramadhani, Azzah Nazhifa Wina Ramadhanti, Aulia Ramadhina, Fidela Sahda Ilona Ramadhita, Ghina Recylia, Rien Reiza Sahawaly Rico Ramadhan, Rico Rimuljo Hendradi Riries Rulaningtyas Rizza Sulistiana Rohim, Achmad Yazid Busthomi S, Salma Bethari Andjani Sa'idah, Andini Sabrina Falasifah Safitri, Lensa Rosdiana Salsabilla, Shafira Salsabylla Nada Apsariny Sasmia Desinta Wulandari Sa’idah, Andini Sediono, Sediono Sely Novika Norrachma Septia Sari, Ni Wayan Widya Setyawan, Muhammad Daffa Bintang Setyowati, Raden Roro Nanik Siagian, Kimberly Maserati Siburian, Cynthia Anggelyn Sihite, Rivaldi Siregar, Naufal Ramadhan Al Akhwal Siti Maizul Habibah Slamet Muchsin Soewignjo, Steven Sofia Andika Nur Fajrina Subiyanto, Marcel Laverda Sufyan Ats Tsauri Sugha Faiz Al Maula Suliyanto Sunariyanto, Sunariyanto Suryono, Alda Fuadiyah Suryono, Alda Fuadiyah Suwarno Suwarno Syahputra, Bimo Okta Syifaun Nadhiro Teguh Susanto Thohari, Habib Nihla Tiani Wahyu Utami Toha Saifudin Toha Saifudin Trias Novia L. Trisa, Nadya Lovita Hana Ulandari, Kartini Putri Ulya, Diana Umi Tri Ruhana Usmi, Rianda Valida, Hanny Wahyuli, Diana Warsono Warsono Widyangga, Pressylia Aluisina Putri Widyawati, Ayu Wieldyanisa, Ezha Easyfa Wulandari, Nuryuliana Yolanda Swastika Yolanda Swastika Yonani Zahrotul Azizah Zhafira, Azizah Atsariyyah Zidni Ilmatun Nurrohmah