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Evaluating Synthetic Minority Oversampling Technique Strategies for Diabetes Mellitus Classification using K-Nearest Neighbors Algorithm Riadi, Imam; Yudhana, Anton; Kurniawan, Gusti Chandra
Jurnal Teknik Informatika (Jutif) Vol. 6 No. 5 (2025): JUTIF Volume 6, Number 5, Oktober 2025
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2025.6.5.5189

Abstract

Data-driven classification of Diabetes Mellitus is a crucial strategy in developing medical decision support systems that are both accurate and efficient. A major challenge in this classification task is the imbalanced class distribution, which tends to reduce the model’s sensitivity to positive cases. This research utilizes a dataset of 1,000 patient medical records obtained from the Mendeley Data repository, containing clinical attributes relevant to diabetes diagnosis. This research examines the impact of various K values on the K-Nearest Neighbors (KNN) algorithm when it is combined with the SMOTE oversampling technique to enhance classification performance. The experiment employs a 10-Fold Cross-Validation methodology with five principal assessment metrics: accuracy, precision, recall, F1-score, and Area Under Curve (AUC). Compared to prior studies, this work advances the methodology by applying SMOTE within each fold of the cross-validation process, effectively preventing data leakage and improving model generalizability. Results indicate that the K=3 configuration yields the highest F1-score of 95.13% and recall of 91.83%, while the highest AUC of 96.40% is achieved at K=9 with lower sensitivity. Applying SMOTE within each fold of the cross-validation process preserves evaluation integrity and prevents potential data leakage. The model demonstrates the ability to detect positive cases more effectively while maintaining high precision. These findings highlight that combining KNN with SMOTE and proper validation strategy is a promising approach for developing a reliable early detection system for Diabetes Mellitus that is adaptive to imbalanced clinical data.
Pelatihan Edukasi Dampak Positif Dan Negatif Interaksi Media Sosial Terhadap Remaja Di SMK Muhammadiyah Bangunjiwo Sari Miranda, Bella Okta; Dahlan, Khoirul Anam; Annafii, Moch. Nasheh; Yudhana, Anton; Umar, Rusydi
Jumat Informatika: Jurnal Pengabdian Masyarakat Vol. 5 No. 2 (2024): Agustus
Publisher : LPPM Universitas KH. A. Wahab Hasbullah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32764/abdimasif.v5i2.4660

Abstract

In this dynamic technological era, changes permeate various aspects of life. Technology accelerates the shift towards the digital realm, with social media becoming the primary platform facilitating rapid interaction. However, its impact on psychological well-being and communication patterns is not always positive. To address this, an educational training program has been developed to provide adolescents with a deep understanding of the positive use of social media and how to manage its negative effects. The training takes place over one day at SMK Muhammadiyah Bangunjiwo, involving 30 students from grades 11 and 12. The methods include presentations, discussions, and interactive sessions. Survey results show that most students spend considerable time on social media, but they also recognize the importance of understanding its positive and negative impacts. This training successfully increases students' awareness of responsible social media usage, and it is hoped that similar activities can be conducted sustainably. The results indicate that with better understanding, students can optimize the use of social media to support learning and other activities, as well as develop positive character traits. This program contributes to shaping wise and responsible attitudes toward technology use among the younger generation. Awareness of the importance of digital literacy is also increasing, as evidenced by the post-test literacy index increasing by 0.49 compared to the Indonesian average in 2022.
WORKSHOP PENGENALAN EDLINK SEBAGAI MEDIA PEMBELAJARAN ONLINE DI IKIP MUHAMMADIYAH MAUMERE Saputra, Sabarudin; Anwarudin, Aang; Juliansyah, Fitrah; Ramdhani, Rezki; Yudhana, Anton; Umar, Rusydi
Reswara: Jurnal Pengabdian Kepada Masyarakat Vol 3, No 2 (2022)
Publisher : Universitas Dharmawangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46576/rjpkm.v3i2.1899

Abstract

Media pembelajaran merupakan alat untuk menyampaikan pesan atau rangsangan pada proses belajar mengajar agar dapat menimbulkan keinginan untuk belajar. Media pembelajaran dapat berupa media pembelajaran online yang digunakan sebagai perantara proses pembelajaran sehingga memenuhi kebijakan Pembelajaran Jarak Jauh (PJJ) selama masa pandemi covid-19. Edlink merupakan media pembelajaran online yang digunakan oleh mitra kegiatan workshop yaitu IKIP Muhammadiyah Maumere. IKIP Muhammadiyah Maumere menggunakan Edlink sebagai media pembelajaran online antara dosen dan mahasiswanya. Sosialisasi penggunaan Edlink telah dilakukan pada masa Orientasi Kehidupan Kampus (OKK) tetapi tidak maksimal berdasarkan hasil survei sebelum kegiatan. Pihak kampus berkolaborasi dengan Magister Informatika Universitas Ahmad Dahlan melaksanakan kegiatan workshop pengenalan Edlink sebagai media pembelajaran online. Kegiatan workshop bertujuan untuk mengenalkan Edlink kepada mahasiswa baru IKIP Muhmmadiyah Maumere sebelum proses perkuliahan berlangsung. Peserta kegiatan berjumlah 120 mahasiswa baru periode 2021-2022. Tahapan kegiatan dimulai dengan survei pemahaman awal peserta, analisis tingkat pemahaman peserta, melakukan workshop, dan melakukan proses evaluasi. Metode evaluasi menggunakan angket penilaian tingkat pemahaman peserta dan dianalisis menggunakan rata-rata skor penilaian yang diberikan oleh peserta pada setiap pernyataan angket. Berdasarkan hasil evaluasi diperoleh nilai rata-rata total skor sebesar 4,35 dengan kriteria sangat paham dan persentasi sebesar 87,09%.
IMPLEMENTASI METODE BUSINESS TO COSTUMER PADA SISTEM INFORMASI TOKO KGS RIZKY MOTOR Utama, Kiagus Muhammad Rizky Aditra; Umar, Rusydi; Yudhana, Anton
RADIAL : Jurnal Peradaban Sains, Rekayasa dan Teknologi Vol. 9 No. 2 (2021): RADIAL: JuRnal PerADaban SaIns RekAyasan dan TeknoLogi
Publisher : Universitas Bina Taruna Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1601.867 KB) | DOI: 10.37971/radial.v9i2.234

Abstract

Implemantasi Business To Costumer (B2C) merupakan bagian e-commerce dalam bentuk jual-beli produk yang melibatkan perusahaan penjual yang secara online melalui media website. Sistem yang sedang berjalan saat ini masih menggunakan sistem manual atau offline. Ini terjadi apabila pelanggan konsumen membeli produk sparepart harus datang langsung ke tokonya. Pada implementasi business to customer ini pada Toko Kgs Rizky Motor berupa online melalui media website yang mencakup berbagai informasi bagi pelaku consumer tentang penjualan sparepart secara online, dapat menampilkan produk-produk sparepart, cara pembelian pemesanan, keranjang belanja, catalog, akun pengusaha dan kontak pengusaha. Pada penelitian ini konsep tahapan-tahapan menggunakan metode waterfall dengan mengikuti alur proses analisis kebutuhan, desain sistem, coding dan implementasi, penerapan dan pemeliharaan.. Hal ini juga memakan waktu biaya yang dikeluarkan bisa jadi lebih tinggi. Dengan salah satu upaya adanya menggunakan implementasi E-Commerce business to customer diharapkan terus meningkatkan pelaku konsumen yang terjangkau dan memudahkan pelaku konsumen ingin membeli produk sparepart tanpa harus datang langsung ketoko pada saat jam tertentu. Hal ini dapat membantu menghemat biaya yang dikeluarkan. Sistem informasi yang dibangun mengimplementasikan tahapan-tahapan pengembangan dengan bahasa pemrograman PHP dengan Adobe Dreamweaver CS 5 dan My SQL menggunakan XAMPP.
Sistem Monitoring dan Estimasi Konsumsi Listrik untuk Rumah Tangga Berbasis IoT dengan Antarmuka React Basri, Mhd.; Anton Yudhana; Abdul Fadlil
CESS (Journal of Computer Engineering, System and Science) Vol. 10 No. 2 (2025): Juli 2025
Publisher : Universitas Negeri Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24114/cess.v10i2.66675

Abstract

Konsumsi energi listrik rumah tangga di Indonesia terus meningkat, mencapai 1.337 kWh per kapita pada 2023, naik 13,98% dari tahun sebelumnya. Penelitian ini mengembangkan sistem monitoring konsumsi listrik berbasis Internet of Things (IoT) menggunakan sensor PZEM-004T dan mikrokontroler ESP32, yang mampu mengukur tegangan, arus, daya aktif, dan energi kumulatif secara akurat. Backend dibangun dengan Node.js dan database real-time, sementara antarmuka frontend menggunakan React.js untuk menampilkan visualisasi data yang interaktif dan responsif. Dashboard menampilkan informasi penting seperti estimasi biaya (Rp14.673), konsumsi real-time (34,90W), konsumsi saat ini (10 kWh), konsumsi kumulatif (1450,500 kWh), serta pemantauan beban peralatan rumah tangga. Sistem menunjukkan status konsumsi “EFISIEN” dan berhasil meningkatkan kesadaran pengguna, terbukti dari pengurangan konsumsi energi rata-rata sebesar 16,8%. Akurasi sensor mencapai 98,5% untuk daya dan 97,2% untuk energi. Survei menunjukkan tingkat kepuasan pengguna sebesar 89,1%, dengan antarmuka dinilai mudah digunakan (4,4/5,0). Hasil penelitian membuktikan bahwa integrasi sensor PZEM dengan teknologi IoT dan React mampu menghasilkan solusi monitoring energi yang akurat, real-time, dan mendukung pengelolaan energi rumah tangga yang efisien dan berkelanjutan.
KLASIFIKASI JENIS KULIT WAJAH MENGGUNAKAN ALGORITMA RANDOM FOREST Irwansyah, Irwansyah; Yudhana, Anton; Fadlil, Abdul
Infotech: Journal of Technology Information Vol 11, No 2 (2025): NOVEMBER
Publisher : ISTEK WIDURI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37365/jti.v11i2.423

Abstract

Skin can be considered the largest organ in the human body. Healthy skin is not only good for the body, but alsoenhances the appearance. Good skin care is essential at any age. In the first few decades of life, the skin has aconsiderable supply of elastin and collagen, but it will gradually decrease. In addition, daily lifestyle can also directlyaffect the appearance of human skin. The purpose of the research is to develop a model that classifies facial skin typesbased on physiological data using random forest algorithm and measure the results of accuracy, precision, and recall.This research uses Rapidminer tools and four facial skin types namely dry, combination, normal, and oily. The resultsof random forest research obtained accuracy results of 93.25%. dry precision 98.02%, combination precision 92.94%,normal precision 93.46%, and oily precision 88.79%. While dry recall 99%, combination recall 79%, normal recall100%, and oily recall 95%. The findings of this research can help create a skincare recommendation system that ismore suited to the needs of each individual.
Rancang Bangun Purwarupa Pendeteksi Kesegaran Ikan Berbasis Ciri Warna Dan Bau Khalif, Fajar Al; Yudhana, Anton
Journal of Science and Engineering Vol 7, No 1 (2024): Journal Of Science And ENgineering (JOSAE)
Publisher : Fakultas Teknik Universitas Khairun

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33387/josae.v7i1.8207

Abstract

At this time the development of technology is rapid that there are many tools facilitate human work, one of which is to detect the freshness of fish. In Indonesia alone there are many types of fish consumption derived from sea water and fresh water. Fish consumtion in Indonesia increased every year by an average of 3% based on statistics from the Ministry of Fisheries and Marine Affairs from 2014-2019.  The system designed in this study uses color sensors and odor sensors that serve to detect the freshness of fish. The microcontroller used is arduino nano which serve to process programs that have been designed. The study used TCS-3200 and MQ-135 sensors as inputs that were then processed in the Arduino Nano which was then displayed on the LCD. Tets on this study used catfish as objects. Catfish will be classified into two, namely fresh and not fresh. The worse the quality of the fish, the greater the PPM value. The error rate in this study is quite large at 7,1.
Performance Analysis for Classification of Malnourished Toddlers Using K-Nearest Neighbor Lonang, Syahrani; Yudhana, Anton; Biddinika, Muhammad Kunta
Scientific Journal of Informatics Vol 10, No 3 (2023): August 2023
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v10i3.45196

Abstract

Purpose: Malnutrition in toddlers is a nutritional issue that Indonesia is still dealing with. Toddlers can suffer from decreasing cognitive and physical abilities, as well as being categorized as having a high risk of death. Early detection is crucial for preventing this and providing appropriate treatment if malnutrition is detected. Classification is a machine-learning technique widely used in disease detection. Because it is simple and easy to implement, K-Nearest Neighbor is the most used classification algorithm. Detecting malnutrition can be done automatically and more quickly by utilizing classification and machine learning algorithms. The aim of this study was to analyze performance to find out which model is best for detecting malnutrition by evaluating the performance of classification using KNN with the Euclidean distance function.Methods: The dataset used in this study is the nutritional status of toddlers from Puskesmas Ubung. The classification method proposed in this research is the KNN algorithm with Euclidean distance. There are three scenarios for the classification model that will be used. Performance classification will compare each model in terms of accuracy, precision, recall, f1-score, and mean absolute error.Results: The experimental results show that KNN k = 15 using the first model generates excellent classification when classifying malnourished toddlers using the Euclidean distance function. The model obtains 91% accuracy, 86.6% precision, 83.8% recall, 85.2% recall, and a mean absolute error of 0.09.Novelty: In this experiment, we analyzed the performance of the KNN to classify malnourished children using a nutritional status dataset, which resulted in an excellent classification that could be used for early detection.
Analysis Impact of Rapid Application Development Method on Development Cycle and User Satisfaction: A Case Study on Web-Based Registration Service Riadi, Imam; Yudhana, Anton; Elvina, Ade
Scientific Journal of Informatics Vol 11, No 1 (2024): February 2024
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v11i1.49590

Abstract

Purpose: This research was conducted to respond to obstacles and inefficiencies in the new student registration system at RA Plus Rabbani. Currently, the conventional method of using physical documents for registration is vulnerable to damage and data loss. Therefore, the proposed solution is implementing a website-based online registration system using the Rapid Application Development (RAD) method. This aims to simplify the process, increase accessibility for prospective students, and reduce the costs and time required.Methods: This research commenced by identifying constraints within the conventional student registration system at RA Plus Rabbani through observations and interviews. The development, following the RAD methodology, involved testing with PHPUnit and Blackbox Testing to ensure the functionality of the system aligned with specifications. In addition, usability evaluation was conducted based on the ISO 9126 standard.Result: The research results show that testing on MVC indicated a 100% success rate for each architectural feature. Referring to expectations with a “valid” conclusion on functionality using Blackbox testing, based on ISO 9126 percentage displayed, it is known that the criterion with the most significant value is the understandability characteristic with a value of 83%. Novelty: This research makes a significant contribution by improving student registration services at RA Plus Rabbani through the implementation of various testing techniques, following the research flow offered by RAD. The study also provides substantial references for further research in web-based system development.
Multi-Label Opinion Mining Based on Random Forest with SMOTE and ADASYN Ardiansyah, Ricy; Yuliansyah, Herman; Yudhana, Anton
Compiler Vol 14, No 2 (2025): November
Publisher : Institut Teknologi Dirgantara Adisutjipto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28989/compiler.v14i2.3185

Abstract

Multi-label classification is essential to categorize data into multiple labels simultaneously. However, data imbalance poses a challenge, where some labels have much less representation, thus reducing the model performance. This study aims to propose a candidate-based sentiment analysis model on the 2024 Jakarta Presidential and Gubernatorial Election review. The SMOTE and ADASYN oversampling methods are applied to handle class imbalance. Both oversampling methods are compared with the Random Forest machine learning method. The experimental results show that. The experimental results show that in the classification of Presidential candidates, Random Forest achieves an accuracy of 0.947 with SMOTE and 0.948 with ADASYN. For sentiment labels, the accuracy of Random Forest remains high with a result of 0.989 for both SMOTE and ADASYN. In the classification of Jakarta Gubernatorial candidates, Random Forest + SMOTE produces an accuracy of 0.975, while with ADASYN it decreases slightly to 0.973. For sentiment labels, both SMOTE and ADASYN have the highest accuracy of 0.993. The application of SMOTE and ADASYN helps to improve the distribution of the minority class without decreasing the overall accuracy, as well as improving the stability in recognizing various multi-label classes in a balanced manner.
Co-Authors Aang Anwarudin Abd. Rasyid Syamsuri Abdel-Nasser Sharkawy Abdillah, Muhamad Aznar Abdul Azis Abdul Djalil Djayali Abdul Fadil Abdul Fadil Abdul Fadlil Abdul Fadlil Abe, Tuska Ade Firli Ansyori Adi Permadi Agung Dwi Nugroho, Agung Dwi Agus Jaka Sri Hartanta Ahmad Azhar Kadim Ahmad Ikrom Ahmad Ikrom Ahmad Syahril Mohd Nawi Ahmadi, Ahwan Akhwandi, Dasef AKRIMA, ASRA Alameka, Faza Alameka, Faza alders paliling Aldi Bastiatul Fawait Fawait Alfian Ma’arif Alin Khaliduzzaman Aminuyati Andhy Sulistyo Andiko Putro Suryotomo Andri Pranolo Anggara Ibnu Sidharta Annafii, Moch. Nasheh Anom Wahyu Asmorojati Anshori, Ikhwan Anton Satria Prabuwono Anton Satria Prabuwono Anwar Siswanto Anwarudin, Aang Ardiansyah, Ricy Arief Setyo Nugroho Aris Rakhmadi Ashari, Irvan Asno Azzawagama Firdaus Asra Akrima Astika AyuningTyas, Astika Aznar Abdillah, Muhamad Azrul Mahfurdz Bahagiya, Multika Untung Balza Achmad Basri, Mhd. Bella Okta Sari Miranda Belly Apriansyah Bintang, Rauhulloh Noor budi putra Budi Setianto, Arif Bulaka, Bardan Cahya Subrata, Arsyad Choirul Fajri Darso, Muhammad Daryono Daryono Dasef Akhwandi Deni Murdiani Denny Yoga Pratama Dewi Eko Wati Dian Nova Kusuma Hardani Didi Siprian Drezewski, Rafal Dwi Susanto Dwi Susanto Dwi Susanto Dzakarasma Tazakka Ma’arij Edi Ismanto Eka Rahmat B Eko Prianto Eko Prianto Elvina, Ade Fadil, Abdul Fadlil, Abdul Fadlillah Mukti Ayudewi Fahmi, Miftahuddin Fahrizal Djohar Fakhri, La Jupriadi Fathoni, Listya Febri Fatma Nuraisyah, Fatma Faza Alameka Faza Alameka Febryansah, M. Iqbal Fitrah Juliansyah Fitri Anggraini Fitri Anggraini, Fitri Fitriyanto, Rachmad Furizal Furizal Furizal Furizal, Furizal Galih Pramuja Inngam Fanani H, Hermansa Habibah, Nurina Umy Habsah Hasan Hadi Sasongko, Hadi Halil, Nur Ihsan Hanif, Abdullah Hanif, Kharis Hudaiby Hartanta, Agus Jaka Sri Hartono, Susilo Helmiyah, Siti Herman Herman Herman Herman Herman Herman Yuliansyah Herman Yuliansyah, Herman Hermansa Herwindo Rahadian Hidayat, Lalu Amam Hikmatyar Insani Himawan I Azmi Igo Putra Pratama Iif Alfiatul Mukaromah Ikhsan Sugianto Ikhsan Zuhriyanto Ikhsan Zuhriyanto Ikhsan Zuhriyanto Ikhwan Anshori Ikrom, Ahmad Ilham Mufandi Imam Riadi Imam Riadi Imam Riadi Imam Riadi Imam Riadi Imam Riadi Imam Riadi Imam Riadi Imam Riadi Intan Puspitasari Irfan, Syahid Al Irwansyah Irwansyah Ivan Triyatno Jafri Din Jaka Dernata Jaka Dernata Jaka Japkowicz, Nathalie Jendri Juliansyah, Fitrah Kalbuadi, Dimas Baskoro Kartika Firdausy Kaspul Anwar Kaswijanti, Wilis Kawarul Hawari Ghazali Kgs Muhammad Rizky Alditra Utama Kgs Muhammad Rizky Alditra Utama Khaliduzzaman, Alin Khalif, Fajar Al Khoir, Syaiful Amrial Khoirul Anam Dahlan Kintung Prayitno, Kintung Kitagawa, Kodai Kurniawan, Gusti Chandra Kusuma , Damar Yoga Listya Febri Fathoni Liya Yusrina Sabila Luh Putu Ratna Sundari Lutfatul Kholifah M Rosyidi Djou M Rosyidi Djou M. Rosyidi Djou Mahsun Mahsun Mardi Sugama Marlina Mustafa, Marlina Maulana, Irvan Mawadati, Siti Mawarni, Syifa’ah Setya Mega Reski4, Julia Miftahuddin Fahmi Miftahus Surur, Miftahus Miko Wardani Mitra Adhimukti Moch. Nasheh Annafii Muchamad Kurniawan Muchlas Muchlas Muchlas Muchlas, Muchlas Mudinillah, Adam Muflih, Ghufron Zaida Muh. Fadli Hasa Muhamad Caesar Febriansyah Putra Muhamad Caesar Febriansyah Putra, Muhamad Caesar Febriansyah Muhamad Fahrul Reza Muhamad Rosidin Muhammad Aris Fajar Ilmawan Muhammad Darso Muhammad Irfan Pure Muhammad Jundullah Muhammad Kunta Biddinika Muhammad Kunta Biddinika Muhammad Miftahul Amri Muhammad Noor Fadillah Muhammad Noor Fadillah Muhammad Nur Faiz Muhammad Nur Faiz Muhammad Rizki Setyawan Muhammad Sabiq Dzakwan Muhammad Sabiq Dzakwan Muhammad, Khairul Muis, Alwas Mukaromah, Iif Alfiatul Murinto Murinto Mushab Al Barra Mushlihudin Mushlihudin Mushlihudin Mushlihudin Mushlihudin, Mushlihudin Mushlihudin, Mushlihudin Musliman, Anwar Siswanto Nathalie Japkowicz Novitasari, Putri Rachma Nuraeni, Eneng Nuryana, Zalik Nuryono Satya Widodo Ockhy Jey Fhiter Wassalam Peryanto, Ari Prasongko, Riski Yudhi Pratama, Denny Yoga Pratama, Genta Pratama, Gilang Ariya PRATAMA, IGO PUTRA prayudi, Andi Prianto, Eko Prihatmadi, Farhan Adyaqsa Priyatno Priyatno Putra, Aji Surya Kurniawan Putra, Marta Dwi Darma Putra, Satriya Dwi Putra, Seno Aji Putri, Dadva Pramesty Etsria Rachmad Fitriyanto Rachmad Very Ananda Saputra Raden Mohamad Herdian Bhakti Rafal Drezewski Rahmawan, Jihad Raja Bidin Raja Hassan Ramadhani, Muhammad Ramdhani, Rezki Rani Rotul Muhima Rauhulloh Ayatulloh Khomeini Noor Bintang Renangga Yudianto Reski, Julia Mega Resmi Aini Retnosyari Septiyani Reza, Muhamad Fahrul Rezki Ramdhani Rio Subandi Riski Prasongko Yudhi Prasongko Riski Yudhi Prasongko Rizky Andhika Surya Rosyady, Phisca Aditya Ruly Erwin AfanDika Rumagia, Yusril Rusdi Umar Rusydi Umar Rusydi Umar Rusydi Umar Rusydi Umar S, Sunardi Sabarudin Saputra Saberi Mawi Sabila, Liya Yusrina Safiq Rosad Sahta, Bobo Saifullah, Shoffan Samadri Samadri Saputra, Candra Deska Saputra, I Gede Purwana Edi saputro, tahap Sarjimin Sarjimin Sarjimin, Sarjimin Satriya Dwi Putra Sefindra Purnama Seno Aji Putra Septa, Frandika Septiyani, Retnosyari Septiyawan Rosetya Wardhana Sharipah Salwa Mohamed Shoffan Saifullah Sidharta, Anggara Ibnu Sidiq, Ahmad Fajar Sigit Wijaya Silmina, Esi Putri Siswaya Siswaya Siswaya, Siswaya Siti Hajar Siti Helmiyah Siti Helmiyah Son Ali Akbar sri suharti Sri Suharti Subandi, Rio Sulistyo, Andhy Sunardi Sunardi - Sunardi - Sunardi Sunardi sunardi sunardi Sunardi, Sunardi Suwanti Suwanti Suyadi Suyadi Syahid Al Irfan Syahrani Lonang Syed Abdullah Syinta Brata Tarisno Amijoyo Tiara Widyakunthaningrum Tole Sutikno Tri Wahono Tugiman Tugiman Umar, Rusydi Ummi Syafiqoh Ummi Syafiqoh Utama, Kgs Muhammad Rizky Alditra Utama, Kiagus Muhammad Rizky Aditra W, Yunanri Wahidah Mahanani Rahayu Wahyu Prawoto Wahyu Sapto Aji Wardani, Miko Wicaksono Yuli Sulistyo Wicaksono Yuli Sulistyo Widhianto, Trisno Wijaya, Setiawan Ardi Wilis Kaswijanti Windra Putri, Anggi Rizky Wintolo, Hero Yudianto, Renangga Zeehaida Mohamed