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All Journal Jurnal Keuangan dan Perbankan Techno LPPM Pendidikan Kewarganegaraan RABIT: Jurnal Teknologi dan Sistem Informasi Univrab JFMR (Journal of Fisheries and Marine Research) AKSIOLOGIYA : Jurnal Pengabdian Kepada Masyarakat JOURNAL OF APPLIED INFORMATICS AND COMPUTING Media Ilmu Kesehatan JURNAL PENDIDIKAN TAMBUSAI Proceedings of the International Conference on Applied Science and Health Journal on Education Jurnal Pendidikan Almuslim JIKA: Jurnal Ilmu Keuangan dan Perbankan Al-Ard: Jurnal Teknik Lingkungan Jurnal Ilmu Kesehatan Bhakti Husada: Health Sciences Journal Jurnal Review Pendidikan dan Pengajaran (JRPP) Jurnal Penelitian Pembelajaran Matematika Sekolah Psychocentrum Review Jurnal Informasi dan Teknologi Jurnal Keperawatan JURNAL PENELITIAN PERAWAT PROFESIONAL Proximal: Jurnal Penelitian Matematika dan Pendidikan Matematika JPKMI (Jurnal Pengabdian Kepada Masyarakat Indonesia) Humanism : Jurnal Pengabdian Masyarakat JURNAL TEKNIK PATRA AKADEMIKA Jurnal Kesehatan Tambusai International Journal of Business, Law, and Education Rambideun : Jurnal Pengabdian Kepada Masyarakat International Journal of Engineering, Science and Information Technology Djtechno: Jurnal Teknologi Informasi Jurnal Hurriah: Jurnal Evaluasi Pendidikan dan Penelitian LEARNING : Jurnal Inovasi Penelitian Pendidikan dan Pembelajaran JURNAL ILMIAH GLOBAL EDUCATION LENTERNAL: Learning and Teaching Journal Jurnal Bina Desa Education and Counseling Journal GENIUS JOURNAL (General Nursing Science Journal) Jurnal Pendidikan Matematika Malikussaleh Jurnal Teknologi Terapan and Sains 4.0 Jurnal Gramaswara: Jurnal Pengabdian kepada Masyarakat Dedikasi: Jurnal Pengabdian Kepada Masyarakat Journal of Education, Cultural, and Politics JHeS (Journal of Health Studies) Jurnal Keperawatan Citra Delima Scientific journal of Citra Internasional Institute Jurnal Kompetitif Bisnis Jurnal Pendekar Nusantara J-ISCAN : Journal of Islamic Accounting Research Jurnal Malikussaleh Mengabdi Journal of Advanced Computer Knowledge and Algorithms Zona Kebidanan : Program Studi Kebidanan Universitas Batam Seroja Husada: Jurnal Kesehatan Masyarakat Jurnal Solusi Masyarakat Dikara Jurnal Pengabdian Kepada Masyarakat Citra Delima INOVTEK Polbeng - Seri Informatika Jurnal Proteksi Agrikultura Proceedings of International Conference on Multidisciplinary Engineering (ICOMDEN) Journal Emerging Technologies in Education
Maryana Maryana, Maryana
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Implementation Clustering Diabetes Suffering Areas Using Web-Based Dbscan Algorithm North Aceh District Ahmad Fauzi Abdillah; Rozzi Kesuma Dinata; Maryana
Jurnal Informasi dan Teknologi 2025, Vol. 7, No. 2
Publisher : SEULANGA SYSTEM PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60083/jidt.vi0.622

Abstract

Diabetes has shown a significant increase in Indonesia, including in the North Aceh District. This research implements the DBSCAN algorithm (Density-Based Spatial Clustering of Applications with Noise) web-based method to map diabetes distribution patterns in 27 North Aceh sub-districts. This system was built using the PHP programming language and database MySQL. Proses clustering utilizing data on population, number of sufferers, and number of deaths from 2021-2023 obtained from Prima Inti Medika Hospital and Cut Meutia RSU, with parameters epsilon = 0.5 and MinPts = 3. Results clustering shows an increase in high-risk areas from year to year. In 2021, 2 high-risk sub-districts were identified, Dewantara and Lhoksukon, increasing to 3 sub-districts in 2022 Dewantara, Lhoksukon, and Nisam, in 2023 to 4 sub-districts Dewantara, Lhoksukon, Nisam and Muara Batu. The resulting web-based system succeeded in visualizing diabetes distribution patterns and can be used to plan more effective and targeted health programs.
Public Sentiment Analisys on the Phenomenom of Body Shaming on Social Media X Using the Extreme Gradient Boosting Algorithm Nadya Raudathul Sofa; Dahlan Abdullah; Maryana Maryana
International Journal of Engineering, Science and Information Technology Vol 6, No 2 (2026)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v6i2.1818

Abstract

The phenomenon of body shaming on social media platform X (Twitter) has become increasingly widespread and has caused various psychological impacts on its victims. The high level of social media activity has made the spread of negative comments related to body shape more difficult to control. Therefore, a system capable of automatically performing sentiment analysis is needed to identify public opinions regarding this phenomenon. This study aims to implement the Extreme Gradient Boosting (XGBoost) algorithm in classifying public sentiment toward the body shaming phenomenon on social media X and to determine the sentiment analysis results obtained. The research data were collected using a web scraping technique through Tweet Harvest, resulting in 1,383 Indonesian-language tweets which were manually classified into three sentiment classes: positive, negative, and neutral. The text preprocessing stage included case folding, cleansing, tokenizing, normalization, and filtering without applying stemming, as it was proven to reduce model performance on social media text data. Feature weighting was carried out using the TF-IDF method, while the data were divided using an 80:20 ratio with the implementation of Random Over Sampling (ROS) to address class imbalance. The XGBoost model was built using parameters of n_estimators = 300, learning_rate = 0.05, and max_depth = 5. The evaluation results using a confusion matrix showed an accuracy value of 80.87%, with F1-scores of 0.85 for the negative class, 0.71 for the neutral class, and 0.81 for the positive class. The results indicate that the XGBoost algorithm is capable of classifying public sentiment toward the body shaming phenomenon with fairly good performance. In addition, a web-based sentiment analysis system was successfully implemented to facilitate the automatic and structured sentiment classification process.
CLUSTERING TINGKAT KECANDUAN GAME MOBILE LEGENDS TERHADAP KEHARMONISAN KELUARGA MENGGUNAKAN METODE K-MEANS Muhammad Fadhil; Wahyu Fuadi; Maryana
Rabit : Jurnal Teknologi dan Sistem Informasi Univrab Vol 10 No 2 (2025): Juli
Publisher : LPPM Universitas Abdurrab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36341/rabit.v10i2.6439

Abstract

Penelitian ini bertujuan untuk menganalisis tingkat kecanduan game Mobile Legends dan dampaknya terhadap keharmonisan keluarga menggunakan pendekatan machine learning dengan algoritma K-Means Clustering. Metode penelitian menggunakan pendekatan kuantitatif dengan mengumpulkan data dari 297 responden melalui kuesioner yang mencakup 10 variabel, terdiri dari 5 variabel addiction dan 5 variabel keharmonisan. Data yang terkumpul kemudian diproses menggunakan preprocessing dengan teknik encoding dan scaling, selanjutnya dianalisis menggunakan algoritma K-Means Clustering dengan optimasi jumlah cluster melalui kombinasi Elbow Method, Silhouette Analysis, dan Davies-Bouldin Index. Hasil penelitian menunjukkan bahwa algoritma K-Means berhasil mengidentifikasi tiga cluster optimal (K=3) dengan kualitas clustering yang memadai, ditunjukkan oleh Davies-Bouldin Index sebesar 1.580, Silhouette Score 0.233, dan Inertia 2089. Distribusi cluster menunjukkan bahwa 60.3% responden berada dalam kategori kecanduan ringan dengan keharmonisan tinggi (Cluster 1), 32.7% dalam kategori sedang-sedang (Cluster 0), dan 7.1% dalam kategori kecanduan berat dengan keharmonisan rendah (Cluster 2). Temuan utama penelitian mengkonfirmasi hipotesis adanya hubungan invers yang signifikan antara tingkat kecanduan game Mobile Legends dengan keharmonisan keluarga, dimana semakin tinggi tingkat kecanduan semakin rendah keharmonisan keluarga. Principal Component Analysis menunjukkan bahwa dua komponen utama mampu menjelaskan 60% varians data, memberikan validasi visual terhadap hasil clustering. Penelitian ini memberikan kontribusi penting dalam memahami dampak psikologis gaming addiction terhadap dinamika keluarga dan dapat menjadi dasar pengembangan strategi intervensi yang tepat sasaran untuk meningkatkan keharmonisan keluarga.
IMPLEMENTASI METODE CONTENT-BASED FILTERING DALAM REKOMENDASI KEDAI KOPI DI KOTA LHOKSEUMAWE Muhammad Arrayyan; Rozzi Kesuma Dinata; Said Fadlan Anshari; Fadlisyah; Maryana
Rabit : Jurnal Teknologi dan Sistem Informasi Univrab Vol 11 No 1 (2026): Januari
Publisher : LPPM Universitas Abdurrab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36341/rabit.v11i1.6641

Abstract

Lhokseumawe a city known for its numerous coffee shops, serves as the focus of this study, which aims to develop a coffee shop recommendation system using a content-based filtering approach based on Google Maps review analysis. A total of 54 coffee shops were collected through web scraping and filtered to 32, as only these shops provided sufficient and relevant reviews according to the selected keywords. User reviews were processed through preprocessing, TF-IDF weighting, and cosine similarity to measure the alignment between user preferences and shop characteristics. A scenario-based evaluation was conducted by using keywords such as “noodles,” “parking,” “spacious,” “toilet,” and “watching together” to represent user preferences. The results show that the system generates recommendations consistent with the presence and relevance of these keywords, with shops such as AN Coffee and Arabica Kopi frequently appearing as top suggestions. Although the evaluation is limited to scenario-based testing, the system demonstrates potential in assisting users in selecting suitable coffee shops. Future work may include hybrid filtering, machine learning methods, automated keyword extraction through topic modeling, and user-based evaluation to improve recommendation quality.
Teknologi Informasi dalam Melihat Peluang Bisnis dan Pengembangan Wirausaha dalam Dunia Industri Defi Irwansyah; Cut Ita Erliana; Maryana Maryana; Effan Fahrizal; Ezwarsyah Ezwarsyah
Jurnal Solusi Masyarakat Dikara Vol 3, No 2 (2023): Agustus 2023
Publisher : Yayasan Lembaga Riset dan Inovasi Dikara

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Perkembangan teknologi informasi terutama dengan tersedianya berbagai jenis media digital untuk melakukan kegiatan ekonomi sangat membantu siswa dalam melihat peluang wirausaha untuk meningkatkan penjualan online. Tujuan dari pengabdian ini memberikan Pengaruh teknologi informasi kepada siswa untuk berwirausaha dan siswa dapat bimbingan teknis dalam membuka lapangan pekerjaaan. Selanjutnya pengabdian ini juga bertujuan untuk mengetahui pengaruh wirasuha dalam dunia industri bagi siswa dan peluang mana yang banyak terbuka dalam membuka wirausaha baru. Metodelogi yang dilakukan observasi, kuesioner, dan dokumentasi untuk melihat bagaimana faktor-faktor yang mempengaruhi teknologi informasi dalam melihat peluang bisnis dan pengembangan wirausaha dalam dunia industri untuk siswa. Adanya pengabdian ini  dapat meningkatkan motivasi minat bagi siswa dalam tersedia lapangan kerja yang lumayan fleksibel dan dapat membantu siswa untuk mendapatkan biaya tambahan sehari-hari serta membangkitkan jiwa-jiwa ekonomi kreatif dan inovatif yang dimiliki siswa. Selanjutnya hasil dari pengabdian ini adalah untuk mengetahui Teknologi Informasi dalam melihat peluang Bisnis dan pengembangan wirausaha dalam Dunia industri serta mengetahui sistem seperti apa yang bisa digunakan untuk menjalankan suatu wirausaha secara online. hasil pengabdian juga diharapkan dapat dibangun dan membantu siswa membuka wirausaha online secara fleksibel tanpa meninggalkan kewajiban seorang siswa.
Virtual Tour Application for Cultural Heritage in North Aceh Regency using Augmented Reality Technology Melly Yani Melly; Eva Darnila; Maryana
Journal of Innovation and Technology Polbeng Series on Informatics (INOVTEK Polbeng - Seri Informatika) Vol. 10 No. 2 (2025): July
Publisher : P3M Politeknik Negeri Bengkalis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35314/3s7wyh46

Abstract

Cultural heritage refers to historical objects that must be preserved through protection, development, and utilisation. In North Aceh Regency, cultural heritage preservation faces challenges such as low interest among younger generations and the lack of interactive learning media. This study aims to design a virtual tour application using Augmented Reality (AR) and Geographic Information System (GIS) technologies as an interactive medium to digitally introduce cultural heritage sites. Data were collected from the Department of Education and Culture of North Aceh and through direct observation and documentation in the field. The application integrates AR features to display 3D cultural objects and GIS to present the geographical locations accurately. The development includes user interface design, motion-based navigation, and historical information panels. Testing results show that all markers successfully displayed 3D objects with an average detection time of 3.58 seconds, a detection distance of 75.71 cm, and a rotation angle of up to 360°. The objects appeared stable, and the historical information was well presented. The main contribution of this study is the implementation of AR technology in the local context of North Aceh, which has rarely been applied. Limitations include the small number of heritage sites and testing limited to a few AR devices. Future research is recommended to expand site coverage, improve device compatibility, and add gamification features to enhance user engagement.
K-Medoids Clustering Method Iin Transaction Data Reports of UIN IB Padang With Bank Nagari Muhammad Jihad Saputra; Bustami; Maryana
Journal of Innovation and Technology Polbeng Series on Informatics (INOVTEK Polbeng - Seri Informatika) Vol. 10 No. 2 (2025): July
Publisher : P3M Politeknik Negeri Bengkalis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35314/tq2tkw36

Abstract

Manual management of student financial transaction data remains a major challenge in many higher education institutions, including in the collaboration between Universitas Islam Negeri Imam Bonjol (UIN IB) Padang and Bank Nagari. Until now, no automated system has been developed to cluster student transaction data using the K-Medoids algorithm within higher education institutions in West Sumatra. This study aims to design a transaction clustering system that can identify student transaction patterns more efficiently. The K-Medoids algorithm is applied to transaction data that has been preprocessed through categorical transformation and normalization to address accuracy issues in distance-based analysis. The results show the formation of three main clusters: low (59 data points), medium (185 data points), and high (106 data points). This distribution reflects the variations in student transaction behavior and can be utilized by both the university and the bank to design more targeted service strategies, such as resource allocation and payment policy evaluation. This research provides an initial contribution to the application of K-Medoids-based data mining for optimizing transaction management in regional higher education institutions
ANALISIS SENTIMEN MASYARAKAT TERHADAP PEMERINTAH DI ERA KABINET PRABOWO SUBIANTO BERDASARKAN SOSIAL MEDIA X MENGGUNAKAN NAÏVE BAYES CLASSIFIER Adetia Irvanda; Wahyu Fuadi; Maryana Maryana
Djtechno: Jurnal Teknologi Informasi Vol 7, No 2 (2026): Agustus
Publisher : Universitas Dharmawangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46576/djtechno.v7i2.9459

Abstract

Kebijakan awal pemerintahan Kabinet Prabowo Subianto memicu beragam opini masyarakat di media sosial X, namun opini tersebut belum terklasifikasi ke dalam polaritas sentimen sehingga sulit dijadikan bahan evaluasi. Penelitian ini bertujuan mengimplementasikan dan mengevaluasi algoritma Naïve Bayes Classifier (NBC) dalam mengklasifikasikan sentimen masyarakat terhadap pemerintahan Kabinet Prabowo Subianto ke dalam kelas positif, negatif, dan netral. Sebanyak 587 tweet dikumpulkan melalui teknik scraping sejak 20 Oktober 2024, kemudian diproses melalui enam tahap text preprocessing, dilabeli otomatis menggunakan InSet Lexicon, dan dibobotkan dengan TF-IDF yang menghasilkan 317 fitur. Data dibagi 70:30 secara stratified menjadi 410 data latih dan 177 data uji, lalu diklasifikasikan menggunakan Multinomial Naïve Bayes dengan Laplace smoothing α=1,0. Hasil pelabelan menunjukkan dominasi sentimen negatif sebesar 55,7% (327 tweet), diikuti netral 30,7% (180 tweet) dan positif 13,6% (80 tweet). Model memperoleh akurasi 61,58% dengan presisi weighted 60,39%, recall weighted 61,58%, dan F1-score weighted 55,60%. Ketidakseimbangan kelas menyebabkan model bias terhadap kelas negatif, sehingga penyeimbangan data disarankan pada penelitian berikutnya.
Comparison of the K-Nearest Neighbor and Random Forest Methods in Classifying the Best Selling Medicines at Khan Pharmacy Matang Glumpang Dua Anya Regina Putri; Rozzi Kesuma Dinata; Maryana
Journal of Advanced Computer Knowledge and Algorithms Vol. 3 No. 2 (2026): Journal of Advanced Computer Knowledge and Algorithms - April 2026
Publisher : Department of Informatics, Universitas Malikussaleh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29103/jacka.v3i2.25183

Abstract

Khan Matang Glumpang Dua Pharmacy faces difficulties in analyzing drug sales patterns that affect inventory efficiency and customer satisfaction. The need to anticipate demand and reduce the risk of stockouts or excess stock requires an effective classification system for best-selling drugs. This study aims to test the K-Nearest Neighbor (KNN) and Random Forest methods to perform and find the best classification model. The data used in this study consisted of 382 data points. This study compared two classification models on pharmacy sales data. The K-Nearest Neighbor (KNN) model was tested using the parameter k=3, while the Random Forest model was tested with 100 trees and a max depth of 5. The results showed that the KNN and Random Forest (RF) algorithms. The Random Forest (RF) model outperformed KNN on all metrics: RF achieved an Accuracy and F1-Score of 94.81%, while KNN recorded an Accuracy of 93.51% and an F1-Score of 93.44%.
Artificial Intelligence in Personalized Learning: Enhancing Student Engagement through Adaptive Learning Systems Arief Hidayat; Maryana Maryana; Rustiyana Rustiyana; Triyugo Winarko
Journal Emerging Technologies in Education Vol. 3 No. 4 (2025)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/jete.v3i4.2508

Abstract

Background. Advancements in artificial intelligence (AI) have transformed educational practices by enabling personalized learning experiences that adapt to individual student needs. Traditional instructional methods often fail to accommodate diverse learning paces, preferences, and competencies, leading to disengagement and suboptimal learning outcomes. Purpose. This study investigates the effectiveness of AI-based adaptive learning systems in promoting personalized learning and increasing student engagement across multiple educational contexts.   Method. A mixed-methods research design was employed, combining quantitative analysis of engagement metrics and academic performance with qualitative exploration through student interviews and teacher observations. Results. Results indicated significant improvements in engagement, motivation, and learning outcomes, with adaptive feedback and personalized content contributing to sustained participation and deeper comprehension. Students reported higher satisfaction and perceived control over their learning processes, while educators noted more efficient monitoring and instructional planning. Conclusion. The study concludes that integrating AI into personalized learning systems can substantially enhance engagement and academic performance.
Co-Authors Abda Abda Abdul Aziz Jaziri, Abdul Aziz Abdul Rizal AZ Adetia Irvanda Adri Wanto Agustiani, Sirli Agustin Agustin Ahmad Fauzi Abdillah Aji Pangestu, Febriana Aklimawati Aklimawati, Aklimawati Alfahmi, M. Lutfi Alim, Muhammad Taqdirul Amelia, Cevy Amrullah, Nafis Azmi Andi Wapa Angga Pratama Anggraini, Rima Berti ani, Muli Annisa Afrilia Zahra Annisa Anya Regina Putri Aprilianda, Wiwie ARDIANSYAH ARDIANSYAH Arief Hidayat Arief Rahman Aritonang, Ardelina Ariyanti Napitupulu, Pariang Aryandi, Aryandi Aryandi, Aryandi Aulia, Nadya Rahma Aulia, Riva Auvaria, Shinfi Wazna Ayuni, Novita Bekti, Joko Tigo Narimo BOBBY RAHMAN, BOBBY Budi Sulistiyo Nugroho Bustami Bustami Chandra Halim Chania, Veronicha Chaylaurent, Caren Chrisnajayantie, Raden Roro Brilianti Cut Ita Erliana Dahlan Abdullah Dahlan, Mukhtar Zaini Daud, Eva Darnila Deastuti, Francilia Defi Irwansyah Devita, Melindia Dewi, Hesti Puspita Donsu, Jenita Doli Tine Effan Fahrizal Efri, Efri Eko Gani PG Eva Darnila Ezwarsyah Ezwarsyah Fadlisyah Fadlisyah Fadlisyah Faizal, Kgs. M. Fajriana, Fajriana Fardiansyah, T. Fariski, Resta Fasim Hasibuan, Wilda Fatmariza Fatmariza Fauzan . Fauzi, Alfi Fauzi, Alfi Fazilah, Nura Fitri, Nurwijaya Fitria, Nurwijaya Fredinan Yulianda Fuadi, Wahyu Fuadi, Wahyu Gunawan Gunawan Hanan, Sahirah Shafa Alifiyah Handayani, Tri Widyastuti Hartono, Ali Haryanto, Darban Hasrul Hasrul, Hasrul Hayatun Nufus Hermain, Hermain Hidayatus Sholihah Hikalmi, Hikalmi Ikasari, Linda Ilham Kurniawan, Muhammad Ilyana, Anis Indah Permata Sari Indri, Nia Isfayani, Erna Isnayati, Isnayati Istifadah, Shovi Yatul Karyati, Atik Keumala, Cut Muftia Khasanah, Titik Fajriyati Nur Komariah Komariah Kurniawan, Nurhafid Kusumajaya, Hendra Lasmini Lasmini, Lasmini Lestari Wibowo Lestari, Indri Puji Lestari, Widia Ayuning Lifia, Reti Columba Lis Ayu Widari, Lis Ayu Listiana, Yeni Lucky Herawati LULUK ASMAWATI Lupita, Veronica M, Munawar M. Lutfi Al Fahmi Maisyuri, Maisyuri mardyanti , lelly Marhami, Marhami Masniah Masniah Maulidin, Maulidin Meilando, Rizky Melly Yani Melly Meriatna Meriatna Metty, Metty MISWAR MISWAR MMSI Irfan ,S. Kom Muhammad Arrayyan Muhammad Fadhil Muhammad Jihad Saputra Muhammad Muhammad Muhammad Zakaria Mukhlisuddin Ilyas muli ani Munawarah Munawarah, Munawarah Mursalin . Muthmainnah Muthmainnah Nadya Raudathul Sofa Najmuddin MA, Najmuddin Ndari, Wulan Nisfia, Laila Noamperani, Sapta Rahayu Nugroho, Arif Riyanto Budi Nurdin Nurdin Nurdin Nurdin Nurlitasari, Anggita Nurmiati Nurmiati Nurvinanda, Rezka Nuryanti, Rahma Oktalio, Oktalio Oktaningsih, khendy Oktarina, Rusmilda Oktavia, Tri Paloma, Ira Prameswari, Yuditia Purnomo, Fazrul Sandi Puspita, Ranti Putra, Septian Aditya Putri, Indah Hidayah Putri, Ninda Maulida Rahman*, Bobby Rahmani, Septi Ayu Rahmi, Hanifatul Ramadhanty, Helsy Riansyah, Riansyah Rianti, Lina Rini Meiyanti Rismaida, Rismaida Rochma, Izura Rosiani, Yessi Rozi Kesuma Dinata Rozzi Kesuma Dinata Rr Diah Nugraheni Setyowati, Rr Diah Nugraheni Rudini Rudini, Rudini Ruslan, Hermain Rustiyana, Rustiyana S. Padmini, Oktavia Sahputra, Ilham Said Fadlan Anshari Sanjaya, Arya Sari , Indah Permata Sari, Riska Kumala Sarita Oktorina Sepriadi Sepriadi Shalawati, Shalawati Sipangkar, Silvana Delima Siti Hajar Sofyan, Diana Khairani Soleha Soleha Subroto, Popo Sufyan Hakim Sujacka Retno Sumarwoto, S.H.I., M.H. Sumarwoto, S.H.I., M.H. Surya Surya Suryanef Suryanef Susanto, Abiyyu Naufal Suskandini Ratih Dirmawati Suwardi Suwardi Syafa, Luthfiani Syahnda, Aftri Syahrial Shaddiq Syibral Malasyi, Syibral Syukriah Syukriah, Syukriah Taufik, Nugraha Muhammad Taufiq Taufiq Tazrin, Cut Nisrina Trisna Trisna, Trisna Triyugo Winarko Ulfi Zahara Ulul Azmi Wahyu Fuadi Wahyu Fuadi Widiani, Lestari Wirayuda, Trisna Wulan Safitri, Wulan Wulandari Wulandari YANTI, HERA Yenni Carolina Yusuf Hanafi Zahara, Ulfi Zahraini Zahraini Zainul, Muhammad Zakaria, Zuraida Zara Yunizar Zarkasyi Zarkasyi Zularnaini, Zulkarnaini Zuraida Zuraida