Article Per Year (5 Year)
p-Index From 2021 - 2026
10.78
P-Index
This Author published in this journals
All Journal Jurnal Keperawatan PROtek : Jurnal Ilmiah Teknik Elektro Bianglala Informatika : Jurnal Komputer dan Informatika Akademi Bina Sarana Informatika Yogyakarta Promotif: Jurnal Kesehatan Masyarakat Jurnal INSYPRO (Information System and Processing) Jurnal Manajemen Kesehatan Yayasan RS.Dr. Soetomo JURNAL INSTEK (Informatika Sains dan Teknologi) Jurnal Informasi Kesehatan Indonesia (JIKI) Journal of Health Sciences Jurnal Manajemen Informasi Kesehatan Indonesia (JMIKI) Ainet : Jurnal Informatika Jurnal Ilmiah Perekam dan Informasi Kesehatan Imelda (JIPIKI) Babali Nursing Research Madaniya J-PEN Borneo : Jurnal Ilmu Pertanian Tangible Journal Jurnal Pendidikan, Sains, Geologi, dan Geofisika (GeoScienceEd Journal) Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer) Joutica : Journal of Informatic Unisla Al-Khidmah Jurnal Pengabdian Masyarakat Jurnal Ilmu Komputer PELS (Procedia of Engineering and Life Science) Economic Reviews Journal Jurnal Informatika Progres Media Bina Ilmiah International Journal of Health and Information System (IJHIS) Jurnal Abdimas Jatibara Pangulu Abdi: Jurnal Pengabdian Kepada Masyarakat VISA: Journal of Vision and Ideas Jurnal Intelek Dan Cendikiawan Nusantara ARUS JURNAL SAINS DAN TEKNOLOGI Jurnal Intelek Insan Cendikia International Journal of Research in Counseling Journal of Muhammadiyah’s Application Technology Kajian Ilmiah Mahasiswa Administrasi Publik (KIMAP) Jurnal Medis Umum
Titin Wahyuni
Informatika, Universitas Muhammadiyah Makassar
Religion Agriculture, Biological Sciences & Forestry Humanities Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management 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 Medicine & Pharmacology Neuroscience Nursing Physics Public Health Social Sciences Veterinary Other

Published : 92 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 92 Documents
Search

 6   7   8   9   10 
Pendeteksi Objek Huruf Lontara Untuk Literasi ke Teks Latin Zainuddin, Mohammad Ramadhan; Rahman, Fahrim Irhamna; Wahyuni, Titin
Journal of Muhammadiyah’s Application Technology Vol. 5 No. 1 (2026)
Publisher : Universitas Muhammadiyah Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26618/nth00674

Abstract

Kemajuan teknologi komputer telah mendorong inovasi dalam sistem pengenalan karakter otomatis, termasuk aksara Lontara’. Penelitian ini bertujuan mengevaluasi efektivitas algoritma deteksi objek YOLOv8 dalam mengenali dan mengklasifikasikan karakter aksara Lontara’ dengan akurasi tinggi. Studi dilakukan di Universitas Muhammadiyah Makassar menggunakan metode eksperimen berbasis pembelajaran mesin. Dataset yang digunakan terdiri dari gambar digital karakter Lontara’ yang telah diberi label secara manual. Data dibagi menjadi tiga bagian: 70% untuk pelatihan, 20% untuk validasi, dan 10% untuk pengujian model. Hasil evaluasi menunjukkan kinerja model sangat optimal, dengan akurasi sebesar 98,2%, presisi 98,1%, dan recall mencapai 100%. Capaian ini menandakan sistem memiliki efisiensi dan reliabilitas tinggi dalam mengenali serta mengklasifikasikan karakter aksara Lontara’ dalam berbagai kondisi visual. Temuan ini mendukung potensi implementasi model dalam dunia nyata. Sebagai pengembangan lebih lanjut, disarankan untuk memperluas variasi dataset agar model lebih mampu melakukan generalisasi. Selain itu, eksplorasi algoritma yang lebih modern atau pendekatan hibrida dengan teknik deep learning lain dapat meningkatkan kinerja dan ketahanan sistem terhadap situasi operasional yang kompleks. KATA KUNCIPengenalan Aksara Lontara’, YOLOv8, Deep Learning, Literasi. ABSTRACT: Rapid advancements in computer technology have driven innovation in automatic character recognition systems, including for the Lontara script. This study aims to evaluate the effectiveness of the YOLOv8 object detection algorithm in accurately recognizing and classifying Lontara characters. The research was conducted at Universitas Muhammadiyah Makassar using an experimental method based on machine learning. The dataset consisted of digital images of Lontara characters, which were manually labeled. The data was divided into three subsets: 70% for training, 20% for validation, and 10% for testing the model. The evaluation results showed that the model performed very well, achieving an accuracy of 98.2%, a precision of 98.1%, and a perfect recall of 100%. These results demonstrate the system’s high efficiency and reliability in recognizing and classifying Lontara characters under various visual conditions. The findings support the model's feasibility for real-world implementation. For future research, it is recommended to increase dataset diversity by involving more participants and image sources to enhance generalization capabilities. Additionally, exploring more advanced algorithms or hybrid approaches that combine multiple deep learning techniques may further improve the system’s performance and robustness in more complex operational scenarios.Keywords:Lontara Script Recognition, YOLOv8, Deep Learning, Literacy
Optimizing Early Disease Detection among Adolescents through a School-Based Health Screening Program at SMA Al-Rifa’ie Malang Masyfufah, Lilis; Setiawan, Muhammad Yusuf; Triyono, Erwin Astha; Wahyuni, Titin
Jurnal Abdimas Jatibara Vol 4, No 2 (2026): Jatibara Vol.4 No.2 Februari 2026
Publisher : STIKES Yayasan RS.Dr.Soetomo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29241/jaj.v4i2.2542

Abstract

The development of health information technology has undergone a significant transformation. One important aspect that has changed is the method of screening or early detection of diseases, which is often carried out using applications that are easily accessible to the public. Given that cases of tuberculosis, hypertension, low vision, and mental health issues are on the rise due to lifestyle changes. This activity was carried out to introduce the health screening application owned by the government for widespread use in the community. The Methods Community service activities were carried out by giving presentations to the target audience (Al-Rifa'ie High School students) and asking them to practise screening using the introduced application. The Results showed 76% of participants were unaware of the existence of screening applications for these diseases. The provision of health information related to screening through presentations and practical demonstrations was effective in ensuring that participants understood the material because they participated actively.
Analisis Sentimen dan Clustering Komentar Twitter Menggunakan Metode Lexicon-Based dan Algoritma K-Means Resky Samudra, Anugrah; Danuputri, Chyquitha; Wahyuni, Titin
Journal of Muhammadiyah’s Application Technology Vol. 5 No. 1 (2026)
Publisher : Universitas Muhammadiyah Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26618/8njz7s15

Abstract

ABSTRAK: Media sosial Twitter telah menjadi salah satu platform utama bagi masyarakat dalam menyampaikan opini dan persepsi terhadap berbagai isu publik, termasuk isu ekonomi nasional. Besarnya volume data teks yang dihasilkan menuntut adanya metode analisis yang mampu mengekstraksi informasi secara efektif. Penelitian ini bertujuan untuk memetakan opini publik di Twitter berdasarkan polaritas sentimen serta kemiripan topik pembahasan. Metode yang digunakan meliputi analisis sentimen berbasis leksikon untuk menentukan kecenderungan sentimen positif, negatif, dan netral, serta teknik clustering teks untuk mengelompokkan komentar berdasarkan kesamaan karakteristik kontennya. Data penelitian diperoleh dari hasil pengumpulan komentar Twitter yang relevan dengan isu ekonomi nasional, kemudian melalui tahapan preprocessing teks, pembobotan kata menggunakan TF-IDF, dan proses pengelompokan data. Hasil penelitian menunjukkan bahwa integrasi analisis sentimen dan clustering mampu memberikan gambaran yang lebih komprehensif mengenai pola opini publik, baik dari sisi kecenderungan sentimen maupun topik diskusi yang dominan. Temuan ini diharapkan dapat menjadi referensi dalam pemanfaatan text mining untuk analisis opini publik berbasis media sosial. KATA KUNCIAnalisis Sentimen, Text Mining, Media Sosial, Clustering Teks, Twitter. ABSTRACT: Twitter has become one of the main social media platforms for the public to express opinions and perceptions on various public issues, including national economic issues. The large volume of textual data generated requires analytical methods capable of extracting information effectively. This study aims to map public opinion on Twitter based on sentiment polarity and topic similarity. The methods employed include lexicon-based sentiment analysis to identify positive, negative, and neutral sentiments, as well as text clustering techniques to group comments according to content similarity. The research data were obtained from the collection of Twitter comments related to national economic issues, followed by text preprocessing, term weighting using TF-IDF, and clustering processes. The results indicate that the integration of sentiment analysis and text clustering provides a more comprehensive overview of public opinion patterns, both in terms of sentiment tendencies and dominant discussion topics. These findings are expected to serve as a reference for the application of text mining in social media-based public opinion analysis. Keywords:Sentiment Analysis, Text Mining, Social Media, Text Clustering, Twitter.
Optimasi Manajemen Ruang Rawat Inap RS PKU Unismuh Makassar menggunakan Simulated Annealing Setiawan, Budi; Irhamna Rahman, Fachrim; Wahyuni, Titin
Journal of Muhammadiyah’s Application Technology Vol. 5 No. 1 (2026)
Publisher : Universitas Muhammadiyah Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26618/s90z9c81

Abstract

ABSTRAKManajemen ruang rawat inap berperan penting dalam meningkatkan mutu pelayanan rumah sakit. Keterbatasan kapasitas kamar dan sistem penjadwalan konvensional sering menyebabkan ketidakefisienan dalam alokasi ruang dan meningkatnya waktu tunggu pasien. Penelitian ini bertujuan mengoptimalkan manajemen ruang rawat inap di RS PKU Unismuh Makassar menggunakan algoritma Simulated Annealing. Metode penelitian menggunakan pendekatan kuantitatif dengan simulasi berbasis data pasien dan ketersediaan ruang rawat inap. Parameter yang digunakan meliputi tingkat urgensi medis, lama rawat inap, kelas ruang, dan ketersediaan tempat tidur. Hasil penelitian menunjukkan bahwa algoritma Simulated Annealing mampu meningkatkan efisiensi alokasi ruang, mengurangi waktu tunggu pasien, dan meningkatkan tingkat keterisian kamar.Selain itu, sistem yang dikembangkan mampu menghasilkan distribusi pasien yang lebih terstruktur dan objektif sehingga membantu pihak manajemen rumah sakit dalam pengambilan keputusan terkait penjadwalan dan pemanfaatan ruang rawat inap. Penerapan algoritma Simulated Annealing dalam penelitian ini menunjukkan potensi yang baik sebagai metode optimasi untuk meningkatkan efektivitas pengelolaan sumber daya rumah sakit secara berkelanjutan. Kata Kunci: Manajemen Ruang Rawat Inap, Simulated Annealing, Penjadwalan, Alokasi Kamar, Optimasi, Rumah Sakit   ABSTRACTInpatient room management plays an important role in improving the quality of hospital services. Limited room capacity and conventional scheduling systems often lead to inefficiencies in room allocation and increased patient waiting time. This study aims to optimize inpatient room management at RS PKU Unismuh Makassar using the Simulated Annealing algorithm. The research method applies a quantitative approach using simulation based on patient data and inpatient room availability. The parameters used include medical urgency level, length of stay, room class, and bed availability. The results show that the Simulated Annealing algorithm improves room allocation efficiency, reduces patient waiting time, and increases bed occupancy rates. In addition, the developed system is able to produce a more structured and objective patient distribution, thereby assisting hospital management in decision-making related to scheduling and the utilization of inpatient rooms. The implementation of the Simulated Annealing algorithm in this study demonstrates strong potential as an optimization method to improve the effectiveness of hospital resource management in a sustainable manner. Keywords: Inpatient Room Management, Simulated Annealing, Scheduling, Room Allocation, Optimization, Hospital
Analisis Faktor-Faktor yang Mempengaruhi Penyerapan Tenaga Kerja di Kota Mataram Tahun 2011-2024 Wahyuni, Titin; Arini, Gusti Ayu; Hidayat, Ali Akbar
Economic Reviews Journal Vol. 5 No. 2 (2026): Economic Reviews Journal
Publisher : Masyarakat Ekonomi Syariah Bogor

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56709/mrj.v5i2.1096

Abstract

This study aims to analyze the influence of City Minimum Wage, Gross Regional Domestic Product and Investment on labor absorption in Mataram City in 2011-2024. This study uses quantitative research with an associative approach. The research data uses secondary data obtained from the Central Statistics Agency (BPS) of Mataram City, the Central Statistics Agency (BPS) of West Nusa Tenggara, the Investment and One-Stop Integrated Service Agency (DPMPTS) of Mataram City and the Manpower and Transmigration Agency. Data analysis was carried out using multiple linear regression through the Eviews 12 application. The results of this study indicate that the City Minimum Wage (UMK) has a positive and significant effect on labor absorption in Mataram City. Meanwhile, Gross Regional Domestic Product and Domestic Investment have a negative but insignificant effect on labor absorption in Mataram City. Simultaneously, the variables of City Minimum Wage, Gross Regional Domestic Product and Domestic Investment have a significant effect on labor absorption in Mataram City in 2011-2024.
Analisis Hubungan Obesitas dan Diabetes Melitus Berdasarkan Usia dan Jenis Kelamin Menggunakan Algoritma Apriori Kotte, Erick Yusuf; Rachman, Fahrim Irhamna; Faisal, Muhammad; Wahyuni, Titin
Arus Jurnal Sains dan Teknologi Vol 4 No 1: April (2026)
Publisher : Arden Jaya Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57250/ajst.v4i1.2556

Abstract

Penelitian ini bertujuan untuk menganalisis hubungan antara obesitas dan diabetes melitus berdasarkan usia dan jenis kelamin menggunakan algoritma Apriori. Data yang digunakan merupakan data sekunder dari Dinas Kesehatan Kota Makassar tahun 2023 hingga 2025 dalam bentuk agregat. Tahap praproses meliputi pembersihan data, transformasi, dan diskretisasi menggunakan metode tertil untuk mengubah data numerik menjadi data kategorikal. Algoritma Apriori diterapkan dengan minimum support sebesar 10% dan confidence sebesar 60% untuk mengidentifikasi aturan asosiasi. Hasil penelitian menunjukkan bahwa terdapat hubungan yang signifikan antara obesitas dan diabetes melitus, khususnya pada kelompok usia lanjut dan pasien perempuan. Nilai lift ratio tertinggi mencapai 5,581 yang menunjukkan adanya asosiasi yang kuat antar variabel. Validasi statistik menggunakan uji Chi-Square menunjukkan nilai p < 0,05, yang mengonfirmasi bahwa hubungan tersebut signifikan secara statistik. Penelitian ini memberikan wawasan yang berguna bagi institusi kesehatan dalam merancang strategi pencegahan yang lebih tepat sasaran.
Pemodelan dan Prediksi Kunjungan Pasien di Puskesmas Menggunakan Hidden Markov Model Ferdiansyah; Faisal, Muhammad; Rachman, Fahrim Irhamna; Wahyuni, Titin
Arus Jurnal Sains dan Teknologi Vol 4 No 1: April (2026)
Publisher : Arden Jaya Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57250/ajst.v4i1.2559

Abstract

Penelitian ini menganalisis pola fluktuatif kunjungan pasien hipertensi di Puskesmas Kota Makassar tahun 2024 menggunakan pendekatan Hidden Markov Model (HMM) untuk mendukung perencanaan layanan kesehatan. Dengan menerapkan tiga state tersembunyi (rendah, normal, tinggi) serta distribusi Negative Binomial dan Poisson, model ini mampu menangkap dinamika perubahan rezim (regime switching) pada data yang mengalami over-dispersion. Hasil evaluasi menunjukkan tingkat akurasi yang sangat tinggi dengan nilai MAPE sebesar 0,88%, mengungguli metode Seasonal Naïve. Prediksi untuk Januari 2025 memperkirakan kunjungan sebanyak 22.988 pasien dengan probabilitas tertinggi pada kondisi normal. Dengan demikian, HMM terbukti efektif sebagai instrumen pengambilan keputusan strategis dalam pengelolaan sumber daya kesehatan di tingkat Puskesmas.
PERBANDINGAN CNN DAN YOLO PADA SISTEM PENGENALAN WAJAH BERBASIS PRESENSI Nurfadillah; Ida; Darniati; Yusliana Bakti, Rizki; Wahyuni, Titin; Faisal, Muhammad
PROGRESS Vol 18 No 1 (2026): April
Publisher : P3M STMIK Profesional Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56708/progres.v18i1.532

Abstract

Face recognition based on image data has been widely applied in automated attendance systems; however, it still faces challenges related to accuracy and efficiency under varying lighting conditions and facial pose variations. This study aims to compare the performance of Convolutional Neural Network (CNN) and You Only Look Once (YOLO) methods for face detection and recognition in a deep learning–based attendance system. The dataset consists of facial images collected from students in a limited campus environment with several variations in viewpoint and illumination. The research stages include image preprocessing, training of CNN and YOLO models, and performance evaluation using accuracy, precision, recall, and computation time metrics. The experimental results indicate that YOLO outperforms CNN in terms of detection speed and performance stability, while CNN demonstrates competitive classification performance on limited datasets. This study provides empirical insights into the characteristics of both methods in attendance system scenarios and can serve as a reference for selecting appropriate models for real-world implementation. The main limitations of this study are the dataset size and the restricted data acquisition scope.
PENERAPAN ALGORITMA MOBILENETV2 UNTUK KLASIFIKASI HURUF HIJAIYAH BERBASIS GESTUR TANGAN Riswan, Muh.; Wahyuni, Titin; Danuputri, Chyquitha; Habi Talib, Emil Agusalim; Faisal, Muhammad; Anas, Lukman; Agung, Andi
PROGRESS Vol 18 No 1 (2026): April
Publisher : P3M STMIK Profesional Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56708/progres.v18i1.535

Abstract

The digitalization of religious education offers significant opportunities to enhance Hijaiyah letter learning, particularly for the hearing-impaired community through visual gesture recognition. This study aims to develop and evaluate a real-time web-based classification system for 28 Hijaiyah hand gestures using the MobileNetV2 architecture. The research methodology involves a quantitative approach utilizing transfer learning with a balanced dataset of augmented images. The model was trained using fine-tuning techniques and deployed on a web platform using TensorFlow.js and MediaPipe for efficient on-device inference. Experimental results demonstrate that the model achieved an overall accuracy of 84% on the independent test set, with specific classes reaching near-perfect detection in real-time scenarios, although misclassification persisted among visually similar gestures. The system effectively balances computational efficiency with classification performance, minimizing latency during user interaction. In conclusion, the implementation of MobileNetV2 facilitates a responsive and accessible educational tool, proving the viability of computer vision in creating inclusive religious learning environments without requiring complex server-side infrastructure.
PENERAPAN MODEL ESRGAN UNTUK UPSCALING CITRA DAN VIDEO DIGITAL Suhardi, Syahrul; Habi Talib, Emil Agusalim; Rachman, Fahrim Irhamna; Wahyuni, Titin; Faisal, Muhammad; S.Kuba, Muhammad Syafaat
PROGRESS Vol 18 No 1 (2026): April
Publisher : P3M STMIK Profesional Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56708/progres.v18i1.539

Abstract

Low-resolution images and videos remain a common problem in various digital applications due to limited visual quality. Conventional interpolation-based upscaling methods often produce blurry results and lead to the loss of important texture details. This study aims to apply the Enhanced Super-Resolution Generative Adversarial Network (ESRGAN) to improve the resolution of digital images and videos. The dataset used consists of low-resolution images and videos that are processed through preprocessing, model training, and testing stages using the Google Colab environment. The ESRGAN model is trained to generate high-resolution images while preserving visual details and structural information. Model performance is evaluated using the Peak Signal-to-Noise Ratio (PSNR), Structural Similarity Index Measure (SSIM), and visual comparison between images before and after the upscaling process. The results show that ESRGAN significantly improves the quality of images and videos compared to conventional interpolation methods, both quantitatively and qualitatively. Therefore, the application of ESRGAN is considered effective for enhancing the resolution of digital images and videos and can be utilized in applications that require high visual quality.
Co-Authors . Darniati A.MUHAMMAD SYAFAR Achmad Yanu Aliffianto Adi Malik Muhammad Mutsuhito Aditya, Dwi Martha Nur Adrianingsih, Rizka Agung, Andi Agustiawal Agustiawal Agustin Dwi Syalfina Ahmad Faisal Ahmad Risal Aiman , Ailul Alfina Aisatus Saadah Alfina Aisatus Saadah Amelia, Azarine Nahdah Amir Ali Anang Sulistyo ANDI AGUNG DWI ARYA BULU Andi Yusri andi Yusri Anita Dahliana ardi24, ardiansyah_01 Arfandi, Viki Fahril Arianti, Kencana Indah Arini, Gusti Ayu Arshy Prodyanatasari Arvianda Asep Indra Syahyadi Aswad, Muh. Akhwan Adam Baba, Haedir Bakti, Riski Yusliana Bakti, Rizki Yusliana Bambang Nudji Bisono, Eva Firdayanti Budi Setiawan Cantika Aprilia Santi Chatarina Umbul Wahyuni Cholifah . Cholifah, Cholifah Christine Christine Danuputri, Chyquitha Dewi, Syamrilla Djalil, Sony Achmad Dzakki Adam, Ahmad Wildan Erwin Astha Triyono Fachrim Irhamma Rahman Fachrim Irhamna Rachman Fadhillatul Lailia, Salsabilla Fahmi Ramadhan S Fahrim Irhamna Rahman Fahrim Irhmna Rachman Ferdiansyah Firdaus , Abidatu Zahrotul Firman Firman Fitrianti, Dwi Framz Hardiansyah Habi Talib, Emil Agusalim Haidul, Haidul Halisah Duli, St Nur Haruna, Hanjas Hasbir, Syahrul Hidayanti, Sukria Hidayat, Ali Akbar Hidayat, Andra Dwitama Ida Ilmiyah Rosyiari, Ahniyatul Indriani, Lis Jaelan Usman, Jaelan Kamal, Safutri Kazman Riyadi Khafi, Moh. Zainul khairat, arikal Kotte, Erick Yusuf Krisnita Dwi Jayanti Krisnita Dwi Jayanti, Krisnita Dwi La Ode Taufik Ismail Listiawan, Nadhila Lukman LUKMAN ANAS Lukman Lukman Maharani, Eva Ratih Masyfufah, Lilis Masyfufah, Lilis  Maulia, Rizky Maylina Surya Wirawati Pribadi Mone, Ansyari Muh. Akhwan Adam Aswad Muhadi, Muhadi Muhammad Faisal Muhyiddin A.M Hayat Mujadilah, Siti Muslimah, Nurul Aulia Mustakim Mustakim Nadhila Listiawan Naila, Faiqotun Nandy Rizaldy Najib Natsir, Fitra M. Nisha, Khairun Nova Mellania Novianti, Siti Nur Alam Nurfadilla, Destiani Irma Nurfadillah Octavia, Winda Dwi Pandin, Maria Yovita R. Pribadi, Maylina Surya Wirawati Puspadewi, Intan Putra, Yunior Bimasekti Rahman , Fahrim Irhamna Rahman, Fahrim Irhamna RAHMANIA Rahmania Rahmawati, Ayu Isnaini Ramadhan S, Fahmi Reski Awalia Resky Samudra, Anugrah Retnowati Prihandini Ridwang Ridwang Ridwang Ridwang Ridwang, Ridwang Rinaldy, Muh Riswan, Muh. Rosyiari, Ahniyatul Ilmiyah S. Kuba, Muhammad Syafa'at Salsabila, Damai Arsila Sari, Selvi Permata Sa’adah, Alfina Asiatus Setiawan, Mohammad Yusuf Setiawan, Muhammad Yusuf Setiawan, Tommy Reynaldy Shafira Trisnanda Fatimatus Zahra Siti Fatimatuz Zahroh Siti Mujanah Slamet Riyadi Sri Hastati Suhardi, Syahrul Sukmantoro, Agung Anjar SULASTRI Suryadinata, Rivan Virlando Sutha, Diah Wijayanti Syamsuri, Andi Makbul Syarifuddin, Nur Annisa TANTRI INDRABULAN Uddin , Ardiansyah Umi Khoirun Nisak Wibawa. Ar, Arya Wilda Faida, Eka xss, aa xx Yulianita, Novi Eka Zainuddin, Mohammad Ramadhan Zul fikar