Article Per Year (5 Year)
p-Index From 2021 - 2026
5.618
P-Index
This Author published in this journals
All Journal Jurnal Gamma EKSAKTA: Journal of Sciences and Data Analysis JURNAL SAINS PERTANIAN EQUATOR Jurnal Ekonomi : Journal of Economic Paradigma Pro Bisnis Jurnal Dinamika Pengabdian (JDP) JOIV : International Journal on Informatics Visualization Knowledge Engineering and Data Science BAREKENG: Jurnal Ilmu Matematika dan Terapan JTAM (Jurnal Teori dan Aplikasi Matematika) Jurnal Teknologi Sistem Informasi dan Aplikasi Jurnal Teknologi Informatika dan Komputer Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistika Enthusiastic : International Journal of Applied Statistics and Data Science Proceedings Series on Physical & Formal Sciences Healthy Tadulako Journal (Jurnal Kesehatan Tadulako) Blend Sains Jurnal Teknik Jurnal Informatika dan Teknologi Pendidikan Jurnal Ilmiah MEA (Manajemen, Ekonomi, dan Akuntansi) Borneo Journal of Language and Education Innovative: Journal Of Social Science Research Ahsana: Jurnal Penelitian dan Pengabdian kepada Masyarakat STATISTIKA Buletin Ilmiah Ilmu Komputer dan Multimedia (BIIKMA) Medic Nutricia : Jurnal Ilmu Kesehatan Jurnal Ilmu Komunikasi dan Sosial Politik Journal of Intelligent Systems and Information Technology Jurnal Sains dan Teknologi Kesehatan Emerging Statistics and Data Science Journal Jurnal Hukum dan Ekonomi Syariah
Achmad Fauzan, Achmad
brawijaya university
Religion Agriculture, Biological Sciences & Forestry Humanities Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture 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 Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Neuroscience Nursing Physics Public Health Social Sciences Transportation Veterinary Other

Published : 45 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 45 Documents
Search

 1   2   3   4   5 
Pendekatan Naïve Bayes untuk Mengidentifikasi Perokok Tembakau Berdasarkan Faktor Sosio-Demografi dan Kesehatan Faza Izzatul Muttaqin; Fauzan, Achmad
Statistika Vol. 24 No. 2 (2024): Statistika
Publisher : Department of Statistics, Faculty of Mathematics and Natural Sciences, Universitas Islam Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29313/statistika.v24i2.4224

Abstract

ABSTRAK Merokok adalah kebiasaan yang berdampak negatif pada kesehatan masyarakat Indonesia. Untuk mengatasi masalah ini, diperlukan pemahaman tentang faktor-faktor demografi, pendidikan, dan kesehatan yang mempengaruhi perilaku merokok. Penggunaan metode klasifikasi Naïve Bayes relevan karena dapat memberikan wawasan menyeluruh mengenai faktor-faktor yang mempengaruhi perilaku perokok tembakau di Kota Tasikmalaya. Penelitian ini menggunakan data dari Survei Sosial Ekonomi Nasional (SUSENAS) Maret 2023 di Kota Tasikmalaya. Data dibagi menjadi data pelatihan dan data pengujian, dan kemudian dibagi lagi untuk validasi model. Model tersebut dibuat dan dievaluasi dengan mengacak sampel, membuat model, dan mengevaluasi sebanyak 100 kali. Hasil evaluasi kinerja model dalam mengklasifikasi data validasi menunjukkan akurasi rata-rata 87% dengan standar deviasi 0,0689 dan standar error 0,00689. Confidence interval antara 85.64% dan 88.35% menunjukkan model yang dapat diandalkan. Pengujian akhir model pada data testing mencapai akurasi 83.33%, menunjukkan model berkemampuan baik dalam mengklasifikasikan perokok tembakau di Kota Tasikmalaya pada Februari 2023. ABSTRACT Smoking is a habit that negatively impacts the health of the Indonesian population. To address this issue, it is essential to understand the demographic, educational, and health factors influencing smoking behavior. The use of the Naïve Bayes classification method is relevant as it provides comprehensive insights into the factors affecting tobacco smoking behavior in the city of Tasikmalaya. This study uses data from the National Socio-Economic Survey (SUSENAS) conducted in March 2023 in Tasikmalaya. The data is divided into training and testing datasets, with the training data further split for model validation. The model was built and evaluated by randomizing samples, creating models, and evaluating them 100 times. The model's performance evaluation in classifying the validation data showed an average accuracy of 87% with a standard deviation of 0.0689 and a standard error of 0.00689. The confidence interval between 85.64% and 88.35% indicates a reliable model. The final testing of the model on the testing data achieved an accuracy of 83.33%, model demonstrating a good capability in classifying tobacco smokers in Tasikmalaya in February 2023.
Peningkatan Distribusi Bantuan Sosial di Pangkalpinang dengan Pengelompokan Berbantuan Algoritma K-Means Dwitra Gusti Alriscki; Fauzan, Achmad
Statistika Vol. 24 No. 2 (2024): Statistika
Publisher : Department of Statistics, Faculty of Mathematics and Natural Sciences, Universitas Islam Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29313/statistika.v24i2.4305

Abstract

ABSTRAK Program bantuan sosial (Bansos) merupakan kebijakan penting yang diimplementasikan untuk mengatasi kemiskinan dan meningkatkan kesejahteraan masyarakat. Penelitian ini bertujuan untuk meningkatkan efektivitas program bantuan sosial di Kota Pangkalpinang melalui penerapan metode K-Means Clustering dalam pengelompokan kelurahan dengan tingkat kesejahteraan rendah. Data yang digunakan adalah Data Terpadu Kesejahteraan Sosial (DTKS) yang mencakup penerima bantuan dari berbagai program seperti PBI, BST, dan lainnya. Metode K-Means Clustering diterapkan untuk mengelompokkan kelurahan berdasarkan indikator kemiskinan, yang kemudian dianalisis untuk profilisasi cluster. Analisis Principal Component Analysis (PCA) dilakukan untuk mengatasi multikolinearitas antar variabel. Silhouette coefficient digunakan untuk menentukan jumlah cluster yang ideal untuk memastikan validitas pengelompokan. Hasil penelitian menunjukkan tiga cluster utama dengan nilai silhouette coefficient sebesar 0.458. Cluster pertama memiliki penerima bantuan terbanyak, sedangkan cluster ketiga memiliki penerima bantuan terendah. Penggunaan metode ini diharapkan dapat meningkatkan efektivitas dan efisiensi distribusi bantuan sosial dengan memastikan bantuan tepat sasaran sesuai dengan tingkat kemiskinan masing-masing kelurahan. Oleh karena itu, penelitian ini diharapkan dapat membantu kebijakan bantuan sosial Kota Pangkalpinang. ABSTRACT The social assistance program (Bansos) is an important policy implemented to address poverty and improve community welfare. This research aims to improve the effectiveness of social assistance programs in Pangkalpinang City through the application of the K-Means clustering method in grouping sub-districts with low welfare levels. The data used is the Integrated Social Welfare Data (SWD), which includes recipients of assistance from various programs such as PBI, BST, and others. The K-Means clustering method is applied to group villages based on poverty indicators, which are then analyzed for cluster profiling. Principal Component Analysis (PCA) is conducted to address multicollinearity among variables. The silhouette coefficient is used to determine the ideal number of clusters to ensure the validity of the clustering. The research results show three main clusters with a silhouette coefficient value of 0.458. The first cluster has the most aid recipients, while the third cluster has the fewest aid recipients.The use of this method is expected to improve the effectiveness and efficiency of social assistance distribution by ensuring that aid is targeted according to the poverty levels of each sub-district. Therefore, this research is expected to assist the social assistance policies of Pangkalpinang City.
ANALISIS INPUT-OUTPUT DAMPAK SEKTOR PARIWISATA TERHADAP PEREKONOMIAN DI PROVINSI DAERAH ISTIMEWA YOGYAKARTA Buana, Arya Galih; Ghefira Nurhaliza, Celine; Fauzan, Achmad; Sutisna, Irwan
Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistika Vol. 6 No. 1 (2025): Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistik
Publisher : LPPM Universitas Bina Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46306/lb.v6i1.865

Abstract

The tourism sector plays an important role in increasing employment absorption, promoting equitable business opportunities, and contributing to foreign exchange earings. In 2023, optimism in Indonesia's tourism sector grew, with the number of domestic tourist trips reaching 825.80 million, an increase of 12.37 percent compared to 2022. The Special Region of Yogyakarta (DIY) is one of the most popular tourist destinations in Indonesia, known for its cultural, historical, and natural richness. The growth of tourist visits in DIY not only increases direct income from tourism activities but also positively impacts other economic sectors such as culinary, handicrafts, transportation, and services. This study aims to analyze the role of the tourism sector in DIY in driving and contributing to the regional economy using the Input-Output table. Backward and forward linkage analysis is used to identify key sectors in the economy. The results show that the air transportation sector has the highest spread value among other tourism sectors, while the food and beverage provision sub-sector contributes the most to the total Gross Regional Domestic Product (GRDP) at Current Market Prices in DIY. Simulations of a 1000 billion rupiah investment in each tourism sub-sector show that the air transportation sub-sector provides the largest total impact, while the food and beverage provision sub-sector makes a significant contribution to economic output. Employment projections indicate that the transportation and warehousing sector can create approximately 37,183 new jobs, while the accommodation and food and beverage sector can generate around 3,523 new jobs. Equal investment in each sub-sector is estimated to increase economic growth by 4.25% and reduce the number of unemployment people by 1.832%.
Penerapan Media Pembelajaran Berbasis Web Responsive Bagi Mahasiswa Penyandang Disabilitas Muktiadi, Ridho; Fauzan, Achmad; Faridli, Efi Miftah
Jurnal Informatika dan Teknologi Pendidikan Vol. 4 No. 2 (2024): Desember 2024 - Jurnal Informatika dan Teknologi Pendidikan
Publisher : Indonesian Scientific Journal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59395/jitp.v4i2.109

Abstract

Pandemi yang melanda di Indonesia menjadi salah satu pendorong semakin cepatnya perkembangan teknologi, khususnya dibidang teknologi informasi. Masa pandemi membatasi adanya interaksi antara orang dengan orang lain, sehingga komunikasi secara daring menjadi salah satu pilihan. Perkembangan komunikasi yang semakin cepat juga berpengaruh terhadap proses pembelajran di perguruan tinggi, yang melaksanakan kegiatan perkuliahan secara daring. Dalam perkembangannya banyak model pembelajaran yang diselenggarakan secara daring dan menjadi salah satu solusi bagi mahasiswa disabilitas yang tidak bisa mengikuti perkuliahan secara langsung, dengan menggunakan media pembelajaran dalam bentuk web. Menggunakan aplikasi web harapannya mahasiswa disabilitas mampu mengikuti perkuliahan dimanapun dan melalui perangkat apapun yang disajikan secara responsive. Menggunakan metode Extreme Programing dalam pembuatan web responsive menjadi pertimbangan khusus dimana akan memprsingkat waktu pengerjaan yang akan meliputi beberapa tahapan: tahap perencanaan dilakukan dengan wawancara dan dokumentasi, tahap perancangan dibuat desain aplikasi menggunakan Use Case Diagram, tahap pengkodean menggunakan bahasa pemrograman php dan template bootstrap untuk membuat aplikasi dan tahap pengujian menggunakan Black Box Testing untuk menguji fungsi yang ada pada aplikasi tersebut.     
ESTIMATING EARTHQUAKE MAGNITUDE USING SPATIAL INTERPOLATION WITH THE INVERSE DISTANCE WEIGHTING AND ORDINARY KRIGING APPROACH Amalia, Fitri; Fauzan, Achmad
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 19 No 2 (2025): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol19iss2pp937-948

Abstract

The West Java region is known for its high disaster vulnerability, particularly to earthquakes, due to the presence of many active faults. Based on this, information is needed as an initial step for disaster mitigation to reduce disaster risk and guarantee community safety in the West Java region, one of which is by carrying out spatial interpolation. In this study, the Inverse Distance Weighted (IDW) and Ordinary Kriging (OK) methods were used. The research sample included data on earthquake magnitude in West Java within the same coordinate range, from 01 January 2022 to 31 December 2022. This research was conducted to find out a more precise spatial interpolation method in estimating the strength of the earthquake in West Java in 2022. From the OK analysis results, the best theoretical semivariogram model was obtained, namely the Exponential model with nugget, sill and range values ​​of 0.07, 0.12 and 11451 meters. From the results of the IDW analysis, the best power value parameter was obtained, namely 2. This research was conducted to develop a more precise spatial interpolation method for estimating earthquake strength in West Java in 2022. The OK method results indicated that most of the West Java region has the potential for earthquakes with a magnitude of around 1.5 to 4.0, while the IDW method suggested a potential magnitude of around 2.0 to 4.0. The potential for a high-magnitude earthquake is in Kp. Cileuley, Garumukti, Pamulihan District, Garut Regency, West Java. Based on the results of Holdout Cross Validation, the IDW method is the best for estimating earthquake magnitude in West Java, with a MAPE value of 17.8%. The IDW method's estimation of earthquake magnitude is superior to OK, with smaller MAPE and MAE values.
Temporal and Spatial Analysis of Vegetation and Non-Vegetation Using Landsat 8 Imagery with a Support Vector Machine Approach Syifa Fauziyah; Fauzan, Achmad
EKSAKTA: Journal of Sciences and Data Analysis VOLUME 6, ISSUE 1, April 2025
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20885/EKSAKTA.vol6.iss1.art5

Abstract

Kertajati International Airport is one of the newest airports located in Majalengka regency, West Java province. The establishment of this airport has sparked interest as a case study, particularly regarding land-use changes around the Kertajati area and, more broadly, in Majalengka Regency. This study aims to measure the extent of changes in vegetated and non-vegetated land around Kertajati International Airport, Majalengka Regency, West Java Province. The methodology employed involves the Support Vector Machine (SVM) classification method. Various kernels, including (1) linear, (2) polynomial, (3) radial basis function (RBF), and (4) sigmoid, were simulated in the analysis. The data used in this study comprise Landsat 8 satellite imagery obtained from Google Earth Engine, utilizing bands such as red, green, blue, near-infrared (NIR), and shortwave infrared (SWIR) for the years 2013 and 2023. The dataset was split using the hold-out method into four scenarios, with varying training and testing data proportions: 75%-25%, 80%-20%, 85%-15%, and 90%-10%. Each scenario was repeated 40 times to ensure robust results. The best results were achieved using the SVM model with an RBF kernel at a data split ratio of 75%-25%, as indicated by the highest accuracy scores. Consistent with the accuracy, the evaluation metrics also fell into a high-performance category. Land area predictions for the vicinity of Kertajati International Airport were analyzed based on the optimal data split proportion. The results of this study reveal a significant reduction in vegetated land from 2013 to 2023, accompanied by a notable increase in non-vegetated land over the same period.
Spatial Analysis of Earthquake Intensity Distribution in Java Using the Interpolation Method (2022–2024) Cahyani, Laras Niken Dwi; Pradana, Wahyu Aji; Ariyadi, Fandy Akhmad; Fauzan, Achmad; Primatika, Roza Azizah
Enthusiastic : International Journal of Applied Statistics and Data Science Volume 5 Issue 1, April 2025
Publisher : Universitas Islam Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20885/enthusiastic.vol5.iss1.art5

Abstract

Java, situated in the Pacific Ring of Fire, is one of the most seismically active regions in the world, with frequent earthquakes posing significant risks to its dense population and critical infrastructure. This study aimed to analyze the spatial distribution and intensity patterns of earthquakes in Java from 2022 to 2024 using data from the Meteorology, Climatology, and Geophysics Agency (Badan Meteorologi, Klimatologi, dan Geofisika, BMKG). Spatial interpolation techniques—inverse distance weighted (IDW), nearest neighbor, and Thiessen polygon—were applied to evaluate their effectiveness in mapping earthquake intensity patterns. The dataset included the earthquake magnitude, location, and occurrence time, with performance evaluated using mean absolute percentage error (MAPE) and mean absolute error (MAE). Results showed that the nearest neighbor method achieved the highest accuracy (MAPE of 12.27%, MAE of 0.37), followed by IDW, while the Thiessen polygon method demonstrated limited suitability for continuous seismic phenomena. These findings underscore the importance of selecting appropriate interpolation methods for seismic risk mapping, providing actionable insights for disaster preparedness and urban planning in Java.
TRANSFORMER-BASED OPTICAL CHARACTER RECOGNITION APPROACH FOR IDENTIFYING MOTOR VEHICLES WITH OVERDUE TAXES Fazira, Nabila Dwi; Fauzan, Achmad
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 19 No 3 (2025): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol19iss3pp1597-1608

Abstract

The high growth in the number of motorized vehicles in Indonesia has given rise to special attention in managing traffic administration, especially in relation to vehicle taxes. To present innovative solutions in vehicle tax administration, this research was conducted to detect the five-year tax status of motor vehicles in Indonesia using the Transformer Optical Character Recognition (TrOCR) model. The aim of this research is to evaluate the performance of the TrOCR model in recognizing text on motor vehicle number plates in Indonesia and classifying number plates that have and have not paid tax. The data used is primary data in the form of images of motor vehicle number plates taken around the Faculty of Mathematics and Natural Sciences, Universitas Islam Indonesia, using a purposive sampling with constraints on the representation of each class. Although the data collection was limited to this location, Indonesian vehicle plates follow a standardized format, with regional differences primarily in the prefix letters. Additionally, the university attracts students from various regions who often use vehicles registered in their home provinces. Consequently, the collected dataset reflects a diverse range of number plates, making it a reasonable representation of motor vehicle plates across Indonesia. The research results show that the TrOCR model succeeded in achieving a Character Error Rate (CER) value of 2.9% with a data configuration of 90% for training and 10% for testing, and using 8 epochs. Evaluation of model performance indicates that overall text detection is very effective in classifying the five-year tax status of motor vehicles. Although there are some prediction errors, the overall performance of the model can be considered good and is able to provide reliable information regarding the five-yearly vehicle tax status
Analyzing Multiclass Land Cover and Spatial Point Patterns on Sentinel-2 Imagery Using Machine Learning and Deep Learning Nabilah, Muna Faizatun; Fauzan, Achmad
JTAM (Jurnal Teori dan Aplikasi Matematika) Vol 9, No 2 (2025): April
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jtam.v9i2.29683

Abstract

Land cover conversion around educational centers, such as universities, is an inevitable consequence of increasing urban activity. The development of boarding houses, commercial zones, and other infrastructure often follows the expansion of academic institutions. To support sustainable spatial planning, early identification of land cover and analysis of spatial distribution patterns are crucial for zoning regulation and infrastructure management. This study focuses on classifying land cover and analyzing spatial patterns around Universitas Riau (UNRI) using Sentinel-2 satellite imagery with a 10-meter spatial resolution. The research applied a supervised classification approach, utilizing spectral bands—specifically Near-Infrared (NIR) and Short-Wave Infrared (SWIR)—as explanatory variables. The response variable was land cover, categorized into vegetation, non-vegetation, and water. Three machine learning models—Support Vector Machine (SVM), Naïve Bayes (NB), and Backpropagation Neural Network (BNN)—were compared based on overall accuracy and the Kappa coefficient. The models were trained and tested using a stratified 80-20 data split to ensure a balanced evaluation. Among the models, SVM demonstrated the highest accuracy, achieving an average of 91.15% in 2022 and 83.90% in 2023 with minimal variance, confirming its reliability for land cover classification. Spatially, non-vegetation areas were concentrated near major access routes and facilities, highlighting the influence of infrastructure development on land conversion. The study also identified potential growth zones within a 3–5 km radius from UNRI, emphasizing the need for anticipatory and sustainable land use policies. These findings support the formulation of spatial strategies aligned with Law No. 26 of 2007 on Spatial Planning and offer valuable insights for guiding urban development around academic hubs.
Prediksi Nilai Ekspor Non Migas Di Jawa Barat Menggunakan Metode Seasonal Auto Regresif Integrated Moving Average (SARIMA) Agung Dwi Ramadhan, Agung; Fauzan, Achmad
Emerging Statistics and Data Science Journal Vol. 1 No. 1 (2023): 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.vol1.iss.1.art2

Abstract

Ekspor merupakan kegiatan yang memiliki peran penting bagi perekonomian di Jawa Barat. Diyakini bahwa Provinsi Jawa Barat memberikan sumbangan terbesar terhadap ekspor nasional pada januari – juni 2021. Semakin tinggi kinerja ekspor, semakin besar pula dampak positifnya. Oleh karena itu Penelitian ini bertujuan untuk melihat jumlah nilai ekspor non migas kedepan nya, dengan menggunakan data perkembangan nilai ekspor non migas di Provinsi Jawa Barat yang di dapat melalui situs badan pusat statistik Provinsi Jawa Barat. Data yang digunakan merupakan data time series atau deret waktu beberapa periode kedepan. Metode yang digunakan adalah metode Seasonal Auto Regressive Integrated Moving Average (SARIMA). Berdasarkan analisis yang sudah dilakukan hanya ada 1 model SARIMA yang signifikan yaitu model SARIMA (2,1,0)(0,1,0) dengan niali AIC sebesar 1177.34 dan nilai MAPE sebesar 7.098304. Dengan menggunakan model SARIMA (2,1,0)(0,1,0) juga dilakukan prediksi nilai ekspor non migas di Provinsi Jawa Barat pada tahun 2022 dari bulan Januari hingga Desember didapatkan hasil bahwa pada tahun 2022 nilai ekspor non migas di Provinsi Jawa Barat berkisar pada 40.244 juta dollar .
Co-Authors A Fahira Nur Adhar Arifuddin Adhi Pribadi Agung Dwi Ramadhan, Agung Ahmad, A. Sri Sartika Sufiina Amalina, Nur Dina Anang Kurnia Andreas Wahyu Gunawan Ariyadi, Fandy Akhmad Ayu Wulandari Bagus Sartono Bariklana, Muhammad Buana, Arya Galih Cahyani, Laras Niken Dwi Christopher Yudha Erlangga Dafrian, Rafli Danang Bagus Wibowo Dany Hilmanto Daryono Daryono, Daryono Denta, Anggeria Dewi, Sawitri Diana Apriyanti, Diana Dwitra Gusti Alriscki Efi Miftah Faridli Elsa Pudji Setiawati Evicenna Naftuchah Riani Fachry Abda El Rahman Fadliansyah, Azhimy Fauzi, Fatkhurokhman Faza Izzatul Muttaqin Fazira, Nabila Dwi Febrianti, Nur Qadri Feri Wibowo Fitri Amalia Fitri Yanti Ghefira Nurhaliza, Celine Hafidz, Syauqi Jauzza Hakim, Raden Bagus Fajriya Humairah, Nanda Lailatul Lahan Adi Purwanto LUKMAN, LUKMAN Marisi Aritonang Marisma, Murni Maulana, Ashabul Akbar Maziyah Mazza Basya Mohamad Irkham Mamungkas Munandar Munandar Nabilah, Muna Faizatun Najlah Nur Faizin Nur Kusmiyati Oktaviani, Nabila Pradana, Wahyu Aji Pratiwi, Erlina Lutfiayu Primandari, Arum Handini Purwanto, Kalis Purwanto, Muhammad Idris Rahmawati, Octavia Ramadhan, Muhammad Rizal Ramadhan, Rizki Fauzian Rantisi, Muhamad Zia Ridho Muktiadi Rinaldi Sjahril, Rinaldi Rosdiana, Siti Roza Azizah Primatika, Roza Azizah Sadat, Fauzan Safira, Nuzulia Nur Santoso, Alfian Saputra, Aditia Shenny Oktoriana Siregar, Ayu Lestari Siregar, Rania Febriyola Supriyono Supriyono Suri, Mulhamatus Latifatus Suria, Muh. Yunus Sutisna, Irwan Syahdony, Farrel Nolan Wahyudin, M. Abyan Widiyanto, Rhendy K P Widyastuti, Galuh Widyawati, Dwi Kartika Wilis Dwi Pangesti Wiranti, Ridha Yanasari, Herlinda Yuliana Watiningrum, Rahayu Yuliana, Alfa Zahidah, RA Ghina