Article Per Year (5 Year)
p-Index From 2021 - 2026
6.566
P-Index
This Author published in this journals
All Journal International Journal of Electrical and Computer Engineering Seminar Nasional Aplikasi Teknologi Informasi (SNATI) Jurnal Teknologi Informasi dan Ilmu Komputer International Journal of Advances in Intelligent Informatics Journal of Information Systems Engineering and Business Intelligence Indonesia Symposium on Computing Indonesian Journal on Computing (Indo-JC) JOIV : International Journal on Informatics Visualization Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) JURNAL MEDIA INFORMATIKA BUDIDARMA Jurnal Sisfokom (Sistem Informasi dan Komputer) KOMIK (Konferensi Nasional Teknologi Informasi dan Komputer) JURIKOM (Jurnal Riset Komputer) YUME : Journal of Management TEKNOLOGIA TEKTRIKA - Jurnal Penelitian dan Pengembangan Telekomunikasi, Kendali, Komputer, Elektrik, dan Elektronika Building of Informatics, Technology and Science JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Journal of Data Science and Its Applications Jurnal Sistem Komputer dan Informatika (JSON) Journal of Innovation in Educational and Cultural Research Journal of Applied Data Sciences Mosharafa: Jurnal Pendidikan Matematika Indonesian Journal of Social Science Research Jurnal Pengabdian Masyarakat Open Science and Technology eProceedings of Engineering Innovative: Journal Of Social Science Research AMMA : Jurnal Pengabdian Masyarakat Jurnal INFOTEL
Adiwijaya
Universitas Telkom
Agriculture, Biological Sciences & Forestry Humanities Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Mathematics Mechanical Engineering Nursing Public Health Social Sciences Other

Published : 178 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 178 Documents
Search

 14   15   16   17   18 
KMS Digital: Sistem Monitoring Tumbuh Kembang Balita Di Desa Lebakwangi Satria Mandala; Adiwijaya; Endro Ariyanto; Eko Darwiyanto
AMMA : Jurnal Pengabdian Masyarakat Vol. 4 No. 9 : Oktober (2025): AMMA : Jurnal Pengabdian Masyarakat
Publisher : CV. Multi Kreasi Media

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

Abstract

This community service program aims to develop a monitoring system for toddler growth and development through Digital KMS in Lebakwangi Village, Arjasari District, Bandung Regency, by integrating digital technology, improving digital literacy, encouraging active community participation, and utilizing local potential. This program is designed as a response to the limitations of the manual recording system that has been used so far, which often causes data input errors, delays in monitoring, and difficulties in early detection of growth disorders and nutritional problems in toddlers. Through an integrated approach, the activity began with the development of a Digital KMS system that included in-depth needs analysis with all stakeholders—from posyandu cadres and health workers to parents—to identify the constraints of traditional recording and determine the main features that must be included, such as automatic data input, notifications, and an interactive forum dashboard that displays data in real time. The stages of system development include needs analysis, user-friendly interface design, development of reporting and analytics modules, pilot testing in several strategic posyandu, and full implementation integrated with the local health system. This digital KMS application was built using Laravel tools for the backend and React for the frontend. Furthermore, the program improves digital literacy through workshops and technical training held at health centers and facilities, the creation of educational modules in the form of video tutorials, written guides, and interactive materials, as well as ongoing assistance with the formation of a technical support team that is ready to provide assistance in the field. A participatory approach is implemented through community discussion forums and the involvement of community leaders as agents of change to optimize system usage, enhance a sense of ownership, and empower the community to actively participate in system evaluation and improvement. In addition, data-based monitoring and evaluation are carried out by activating interactive dashboards for periodic monitoring, data collection and analysis for early risk identification, and periodic evaluation through surveys and questionnaires to compile evaluation reports as a basis for system improvement. Synergy among partners, involving local governments, educational institutions such as Telkom University, and local communities, strengthens the ecosystem supporting this program through strategic collaboration that ensures policy support, material development, and ongoing assistance. By utilizing existing geographical and infrastructure potential as well as the cultural value of mutual cooperation, this program has successfully implemented and socialized a digital KMS application that is expected to not only improve the accuracy and effectiveness of health monitoring for toddlers, but also empower the community through increased digital literacy and sustainable digital transformation, thereby generating a long-term positive impact on the quality of health services and the quality of life of children in Lebakwangi Village.
Integrating Digital Media-Based Local Wisdom to Enhance National Insight: The Role of Digital Readiness Yoyo Zakaria Ansori; Adiwijaya Adiwijaya; Mohd Razif Idris; Mohamad Gilar Jatisunda; Dede Salim Nahdi
Journal of Innovation in Educational and Cultural Research Vol 7, No 3 (2026)
Publisher : Yayasan Keluarga Guru Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46843/jiecr.v7i3.3000

Abstract

This study examined the effect of local wisdom–based digital learning media on elementary students' national insight while controlling for digital readiness. A quasi-experimental matching-only pretest–posttest control group design was employed. Participants were selected through purposive sampling from one public primary school, yielding 54 Grade V students. To reduce selection bias, students were matched on pretest national insight scores, prior academic achievement, and gender distribution, yielding equivalent experimental (n = 27) and control (n = 27) groups. Data were collected using a 20-item National Insight Test (? .80) and an 18-item Digital Readiness Scale assessing technological competence, attitudes, and self-efficacy (? .80). The intervention lasted four weeks, with the experimental group receiving culturally grounded digital instruction and the control group receiving conventional instruction. Data were analyzed using Analysis of Covariance (ANCOVA), with posttest national insight as the dependent variable and digital readiness as a covariate. Assumption tests were satisfied (p .05). The overall model was statistically significant, F(2, 51) = 14.87, p .001, explaining 37% of variance in posttest scores (R² = .37). Digital readiness significantly predicted national insight, F(1, 51) = 18.42, p .001, partial ?² = .27, while instructional condition showed a smaller but significant effect, F(1, 51) = 4.36, p = .041, partial ?² = .08. The findings suggest that although culturally grounded digital media enhances national insight, students' digital readiness plays a more substantial role in determining learning outcomes.
Transformasi Digital Tata Kelola Pemakaman Bersejarah melalui Implementasi TIMGRAVID di Yayasan Sajarah Timbanganten Bandung Nungki Selviandro; Angel Metanosa Afinda; Iga Narendra Pramawijaya; Nur Ghaniaviyanto Ramadhan; Adiwijaya; Indah Novitasari Dwi Saputro; Bayu Satrio Wibowo
Jurnal Pengabdian Masyarakat - PIMAS Vol. 5 No. 3 (2026): Agustus
Publisher : LPPM Universitas Harapan Bangsa Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35960/pimas.v5i3.2568

Abstract

Yayasan Sajarah Timbanganten Bandung merupakan pengelola kawasan pemakaman bersejarah yang memiliki nilai budaya dan historis bagi masyarakat Kota Bandung. Namun, proses administrasi pemakaman masih dilakukan secara manual sehingga menimbulkan berbagai kendala, seperti kesulitan pengelolaan data, monitoring makam, pencatatan pembayaran, dan penyediaan informasi kepada masyarakat. Kegiatan pengabdian kepada masyarakat ini bertujuan mengembangkan dan mengimplementasikan TIMGRAVID (Timbanganten Grave Digital Information), yaitu sistem informasi manajemen pemakaman berbasis web untuk mendukung digitalisasi tata kelola dan peningkatan kualitas layanan yayasan. Metode yang digunakan adalah Participatory Action Research (PAR) dan User-Centered Design (UCD) melalui tahapan identifikasi kebutuhan, pengembangan sistem, implementasi, pelatihan, pendampingan, dan evaluasi. Sistem yang dikembangkan mengintegrasikan pengelolaan data jenazah, data penanggung jawab, relasi keluarga, pengelolaan blok makam, administrasi pembayaran, monitoring masa berlaku hak penggunaan makam, serta penyediaan informasi publik. Hasil implementasi menunjukkan bahwa TIMGRAVID mampu meningkatkan efektivitas administrasi, mempermudah pencarian data, meningkatkan transparansi pengelolaan pembayaran, serta mendukung monitoring status makam secara lebih terstruktur. Hasil evaluasi dari sembilan responden menunjukkan tingkat kepuasan mitra yang tinggi, dengan nilai 4,89 untuk kesesuaian materi, 4,44 untuk waktu pelaksanaan, 4,78 untuk kejelasan materi, 5,00 untuk pelayanan tim pelaksana, dan 5,00 untuk keberlanjutan program, dengan rata-rata keseluruhan sebesar 4,82. Selain mendukung pengelolaan administrasi, sistem juga berkontribusi terhadap pelestarian digital data sejarah dan genealogis pada kawasan pemakaman bersejarah Timbanganten Bandung.
Schema-Guided Prompt Strategies for Text-to-SQL over Relational Databases Using Local LLMs Nurjayanti Nurjayanti; Adiwijaya Adiwijaya; Ade Romadhony; Alfian Akbar Gozali
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 10 No 4 (2026): August 2026
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v10i4.6966

Abstract

Text-to-SQL systems translate natural language questions into executable SQL queries, allowing users without SQL expertise to access structured data stored in relational databases. Although Large Language Models (LLMs) have substantially improved SQL generation capabilities, many state-of-the-art Text-to-SQL approaches continue to rely on cloud-based models with high computational requirements. Such dependence limits their deployment in environments with limited computing resources. This study addresses this limitation by proposing schema-guided prompting strategies for Text-to-SQL generation using local LLMs. A chat-based application was developed using the Django Web Framework, while model inference was performed through the Ollama platform to enable the deployment of local LLMs. The proposed framework incorporates database schema information, including table structures and column attributes, into structured prompts to improve the alignment between natural language questions and SQL generation. Experiment results across multiple databases demonstrate that schema-guided prompting significantly improves Text-to-SQL performance. The highest accuracy was achieved by LLaMA 3 (8B) with objective-aware prompting, reaching an Exact Matching (EM) accuracy of 71.96%. These findings suggest that structured prompt engineering provides a practical alternative to model fine-tuning for locally deployed LLMs, offering an effective balance between SQL generation accuracy, computational efficiency, and data privacy. Future work will investigate fine-tuning strategies, example selection methods, and cross-domain evaluation to enhance SQL generation.
Benchmarking Transformer Architectures for Chest X-ray Classification Joshua Pinem; Widi Astuti; Adiwijaya
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 10 No 1 (2026): February 2026
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v10i1.7132

Abstract

Lung diseases remain a major global health concern, necessitating accurate and timely diagnosis. Chest X-ray (CXR) imaging is widely used but challenging to interpret due to overlapping radiographic features and subjective variability among radiologists. Deep learning approaches, particularly Convolutional Neural Networks (CNNs), have shown promise but are limited in capturing global spatial dependencies. Vision Transformers (ViTs) overcome this limitation through self-attention, making them increasingly attractive for medical image analysis. This study systematically evaluates 13 Transformer-based architectures across three CXR datasets with distinct tasks: Pneumonia (3-class: Normal, Bacterial, Viral), COVID-QU-Ex (3-class: Normal, Non-COVID Pneumonia, COVID-19), and Tuberculosis (2-class: Normal, Tuberculosis). All models were trained under a unified setup with consistent preprocessing, augmentation, and evaluation protocols. To improve robustness, a soft voting ensemble of the top five models was also implemented. Results demonstrate that Transformer-based models provide highly competitive performance. On the Pneumonia dataset, the ensemble achieved an accuracy of 0.8743 and F1-score of 0.8615, surpassing several single models such as DeiT-Base (F1 = 0.8725). On COVID-QU-Ex, the ensemble soft voting obtained 0.9593 accuracy and 0.9582 F1-score, effectively balancing precision and recall. On Tuberculosis, ViT-B/16 and MobileViT-S achieved perfect performance (F1 = 1.0), likely influenced by dataset imbalance. These findings highlight the clinical potential of Transformer-based models, particularly when combined through ensembles, for robust and accurate CXR classification.
Assessing Large Language Models for Zero-Shot Dynamic Question Generation and Automated Leadership Competency Assessment I Gusti Bagus Yogiswara Gheartha; Adiwijaya Adiwijaya; Ade Romadhony; Yusfi Ardiansyah
Journal of Applied Data Sciences Vol 7, No 1: January 2026
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v7i1.970

Abstract

Automated interview systems powered by artificial intelligence often rely on fine-tuned models and annotated datasets, limiting their adaptability to new leadership competency frameworks. Large language models have shown potential for generating questions and assessing answers, yet their zero-shot performance, operating without task-specific retraining remains underexplored in leadership assessment. This study examines the zero-shot capability of two models, Qwen 32B and GPT-4o-mini, within a multi-turn self-interview framework. Both models dynamically generated questions, interpreted responses, and assigned scores across ten leadership competencies. Professionals representing the role of Digital Marketing and Account Manager participated, each completing two AI-led interview sessions. Model outputs were evaluated by certified experts using a structured rubric across three dimensions: quality of behavioral insights, relevance of follow-up questions, and fit of assigned scores. Results indicate that Qwen 32B generated richer insights than GPT-4o-mini (mean = 2.86 vs. 2.62; p less than 0.01) and provided more differentiated assessments across competencies. GPT-4o-mini produced more consistent follow-up questions but lacked depth in interpretation, often yielding generic outputs. Both models struggled with accurate scoring of candidate responses, reflected in low answer score ratings (Qwen mean = 2.35; GPT mean = 2.21). These findings suggest a trade-off between insight richness and scoring stability, with both models demonstrating limited ability to fully capture nuanced leadership behaviors. This study offers one of the first empirical benchmarks of zero-shot model performance in leadership interviews. It underscores both the promise and current limitations of deploying such systems for scalable assessment. Future research should explore competency-specific prompt strategies, fairness evaluation across demographic groups, and domain-adapted fine-tuning to improve accuracy, reliability, and ethical alignment in high-stakes recruitment contexts.
Impact of Speckle Reduction Filters on Machine Learning-Based Detection of Polycystic Ovary Syndrome from Ovarian Ultrasound Images Fazrol Rozi; Syafrizal Sy; Adiwijaya; Admi Nazra; Primawati
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 10 No 4 (2026): August 2026
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v10i4.7658

Abstract

Polycystic Ovary Syndrome (PCOS) is commonly assessed with ovarian ultrasonography, but speckle can conceal follicular margins and reduce the robustness of automated interpretation. Although automated PCOS studies increasingly employ machine learning, the contribution of conventional despeckling to subsequent segmentation and classification has not been examined consistently. This study compares five classical filters - Mean, Median, Lee, Frost, and Kuan - within an interpretable machine-learning pipeline for ovarian ultrasound analysis. From a public collection of 12,680 images, a balanced sample of 300 scans (150 PCOS and 150 non-PCOS) was selected. Two radiologists produced follicle annotations, and disagreements were resolved with a third expert to obtain consensus masks. Each filtered image was segmented by adaptive thresholding with morphological refinement, after which geometric and intensity descriptors were extracted. Support Vector Machine (SVM), Random Forest (RF), k-Nearest Neighbors (k-NN), and Logistic Regression (LR) were trained using a stratified 70/30 train-test split with cross-validated hyperparameter tuning. The Kuan-LR configuration yielded the strongest result, reaching 94.44% accuracy and an AUC of 0.98, together with the best edge-preservation score and segmentation agreement. The results indicate that preprocessing materially affects the reliability of an interpretable PCOS detection pipeline and provide quantitative guidance for selecting a speckle-reduction strategy before segmentation and classification.
SCL LEAD to Improve quality of Student-Centered Learning Process in the Class of Discrete Mathematics Adiwijaya Adiwijaya; Irma Palupi
Mosharafa: Jurnal Pendidikan Matematika Vol. 13 No. 2 (2024): April
Publisher : Department of Mathematics Education Program IPI Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31980/mosharafa.v13i2.1947

Abstract

Semakin banyak mahasiswa yang kurang tertarik pada beberapa mata kuliah di universitas, terutama matematika. Studi ini meneliti dampak pendekatan Student-Centered Learning (SCL) dalam pembelajaran Matematika Diskrit. Kami memperkenalkan metode SCL - Lecture’s Encouragement, Assistance, and Stimulating-Deliverance (SCL LEAD) untuk meningkatkan keterampilan belajar dengan mendorong interaksi dan kerja sama mahasiswa. Penelitian ini menggunakan pendekatan kuantitatif melalui pre-test dan post-test untuk mengukur keterlibatan dan kinerja mahasiswa. Data dikumpulkan melalui observasi terstruktur, jaminan kesiapan, dan diskusi kelompok, kemudian dianalisis untuk menilai dampaknya terhadap keterampilan kognitif dan kolaboratif mahasiswa. Perbandingan antara ujian tengah dan akhir semester digunakan untuk mengukur efektivitas SCL LEAD, dengan statistik deskriptif dan inferensial untuk mengidentifikasi perubahan keterampilan dan pencapaian. Temuan menunjukkan bahwa SCL LEAD memotivasi mahasiswa untuk berpartisipasi aktif serta meningkatkan kompetensi dan kinerja dalam Matematika Diskrit, memberi wawasan berharga bagi pengembangan strategi pembelajaran berpusat pada mahasiswa di pendidikan matematika. The increasing disengagement of students in certain university courses, particularly in mathematics, is a growing concern. This study investigates the impact of the Student-Centered Learning (SCL) approach on the learning process for Discrete Mathematics. We introduce the Student-Centered Learning - Lecture’s Encouragement, Assistance, and Stimulating-Deliverance (SCL LEAD) method to enhance learning skills by fostering increased student interaction and cooperation. The study employs a quantitative approach, using pre-tests and post-tests to measure students’ engagement and performance. Data were gathered through structured observations, readiness assurance processes, and group discussions, all of which were documented and analyzed to assess their impact on students’ cognitive and collaborative skills. Comparative metrics between mid-term and final exams were used to determine the effectiveness of the SCL LEAD model, with descriptive and inferential statistics applied to identify changes in students' skills and achievements following the implementation of SCL LEAD. The findings suggest that SCL LEAD motivates active participation and enhances both competence and performance in Discrete Mathematics, offering valuable insights for advancing student-centered strategies in mathematics education.
Co-Authors - Primawati A Rakha Ahmad Taufiq Abu Bakar, Muhammad Yuslan Ade Iriani Sapitri Ade Romadhony Ade Sumiahadi Adhitia Wiraguna Adhitia Wiraguna Aditya Arya Mahesa Admi Nazra Adnan Imam Hidayat Adwin Rahmanto Afrian Hanafi Al Faraby, Said Al Mira Khonsa Izzaty Alfian Akbar Gozali Alvi Syah Amalya Citra Pradana Amir Andi Ahmad Irfa ANDI FUTRI HAFSAH MUNZIR Andina Kusumaningrum Andri Saputra Andrian Fakhri Andriyan B Suksmono Angel Metanosa Afinda Anggitha Yohana Clara Aniq Atiqi Aniq Atiqi Rohmawati Anisa Salama Annas Wahyu Ramadhan Annisa Adistania Annisa Aditsania Antika Putri Permata Wardani Aras Teguh Prakasa Ardiansyah, Yusfi Astrid Frillya Septiany Astrima Manik Aziz, Muhammad Maulidan Azmi Hafizha Rahman Zainal Arifin Bambang Riyanto T. Bayu Julianto Bayu Munajat Bayu Munajat Bayu Rahmat Setiaji Bayu Satrio Wibowo Bernadus Seno Aji Bernadus Seno Aji Bintang Peryoga Bisma Pradana Brama Hendra Mahendra Chiara Janetra Cakravania Clarisa Hasya Yutika D. R. Suryandari Dana Sulistiyo Kusumo Danang Triantoro Danang Triantoro Murdiansyah Daniel Tanta Christopher Sirait Dany Dwi Prayoga Dany Dwi Prayoga Dede Salim Nahdi Della Alfarydy Akbar Deni Saepudin Denny Alriza Pratama Desi Sitompul Dewangga, Dhiya Ulhaq Dian Chusnul Hidayati Didi Rosiyadi Didit Adytia Dinda Karlia Destiani Dody Qori Utama Dody Qory Utama Dwi Yanita Apriliyana Dwi Yanita Apriliyana Dwifebri, Mahendra Eko Darwiyanto Eliza Jasin Elza Oktaviana Elza Oktaviana Endro Ariyanto Ergon Rizky Perdana Purba F. A. Yulianto Fachri Pane, Syafrial Fahmi Salman Nurfikri Faris Alfa Mauludy Faris Alfa Mauludy Farudi Erwanda Farudi Erwanda Fathur Rohman Fathurrohman Elkusnandi Fazrol Rozi, Fazrol Fhira Nhita Fikri Rozan Imadudin Firda A. Ma’ruf Firdausi Nuzula Zamzami Firly Juanita Surahman Fuad Ash Shiddiq Gde Agung Brahmana Suryanegara Ghozy Ghulamul Afif Gia Septiana Gia Septiana Gia Septiana Gilang Rachman Perdana Gilang Rachman Perdana Gilang Titah Ramadhani Grace Tika Guntoro Guntoro Guntoro Guntoro Guntoro Guntoro Hadyan Arif Hafidudin . Hafizh Fauzan Hafizh Fauzan Hendro Prasetyo Henri Tantyoko Honakan Honakan I Gusti Bagus Yogiswara Gheartha I Kadek Haddy W. I Made Riartha Prawira I.G.N.P.Vasu Geramona Iga Narendra Pramawijaya Ilham Kurnia Syuriadi Ilham Yunirakhman Imadudin, Fikri Rozan Imam Prayoga Indah Novitasari Dwi Saputro Indriani Indriani Irene Yulietha Irma Irma Irma Palupi Irwinda Famesa Iyon Priyono Jendral Muhamad Yusuf Zia Ul Haq Jenepte Wisudawati Simanullang Joshua Pinem K, Kasnaeny Kamal Hasan Mahmud Kemas Muslim Lhaksmana Kemas Rahmat Saleh Raharja Kemas Rahmat Saleh Wiharja Kurnia C Widiastuti Kurniawan W. Handito Laila Putri Lalu Gias Irham Lisa Marianah Lisa Marianah Luke Manuel Daely Mahendra Dwifebri P Mahendra Dwifebri Purbolaksono Mahmud Dwi Sulistiyo Melanida Tagari Melanida Tagari Michael Sianturi Milah Sarmilah Moc. Arif Bijaksana Mochamad Agusta Naofal Hakim Mochammad Naufal Rizaldi Mohamad Gilar Jatisunda Mohamad Irwan Afandi Mohamad Mubarok Mohamad Syahrul Mubarok Mohamad Syahrul Mubarok Mohamad Syahrul Mubarok Mohammad Syahrul Mubarok Mohd Razif Idris Monica Triyani Muhammad Afianto Muhammad Enzi Muzakki Muhammad Fauzan Muhammad Feridiansyah Muhammad Ghufran Muhammad Irvan Tantowi Muhammad Kenzi Muhammad Mubarok Muhammad Mujaddid Muhammad Naufal Mukhbit Amrullah Muhammad Nurjaman Muhammad Shiddiq Azis Muhammad Shiddiq Azis Muhammad Surya Asriadie Muhammad Syahrul Mubarok Muhammad Yuslan Abu Bakar Nanda Prayuga Nida Mujahidah Azzahra Nida Mujahidah Azzahra Niken Dwi Wahyu Cahyani Novelty Octaviani Faomasi Daeli Novia Russelia Wassi Nuklianggraita, Tita Nurul Nungki Selviandro Nur Ghaniaviyanto Ramadhan Nurjayanti Nurjayanti Oscar Ramadhan Pinem, Joshua Pratama Dwi Nugraha Preddy Desmon Purbalaksono, Mahendra Dwifebri Putri, Dinda Rahma Putri, Dita Julaika Raihana Salsabila Darma Wijaya Rendi Kustiawan Reynaldi Ananda Pane Riche Julianti Wibowo Rifqi Abdul Aziz Riko Bintang Purnomoputra Riska Chairunisa Rizki Syafaat Amardita Rizky Pujianto Rizma Nurviarelda Roberd Saragih et al., Roberd Rosyadi, Ramadhana Said Faraby Satria Mandala Sekar Kinasih Semeidi Husrin Sheila Annisa Shidqi Aqil Naufal Shuni’atul Ma’wa Sigit Bagus Setiawan St.Sukmawati S. Sugeng Hadi Wirasna Suriyanti Suriyanti Syafrial Fachri Pane, Syafrial Fachri Syafrizal Sy Syahrizal Rizkiana Rusamsi Syam, Mukhlisah Syifa Khairunnisa Talitha Kayla Amory Tati LR Mengko Tesha Tasmalaila Hanif Timami Hertza Putrisanni Tita Nurul Nuklianggraita Triyani, Monica Try Moloharto Untari Novia Wisesty Untari Wisesty Untari. N. Wisesty Untary Novia Wisesty Vina Mutiara Purnama Warih Maharani Widi Astuti Widi Astuti Widi Astuti Winda Christina Widyaningtyas Wisnu Adhi Pradana Yana Meinitra Wati Yoga Widi Pamungkas Yoyo Zakaria Ansori Yuliant Sibaroni Zahra Putri Agusta Zakia Firdha Razak Zulfikar Fauzi