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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Jurnal Pengajaran MIPA TELKOMNIKA (Telecommunication Computing Electronics and Control) Bulletin of Electrical Engineering and Informatics Jurnal Ilmu Komputer (JIK) Indonesian Journal of Disability Studies Jurnal Teknologi Informasi dan Ilmu Komputer Jurnal Sosioteknologi Journal of Engineering and Technological Sciences ELINVO (Electronics, Informatics, and Vocational Education) Jurnal Penelitian dan Pembelajaran IPA Indonesian Journal of Science and Technology Pedagogia: Jurnal Pendidikan QUANTUM: Jurnal Inovasi Pendidikan Sains JOIV : International Journal on Informatics Visualization Al Ishlah Jurnal Pendidikan Knowledge Engineering and Data Science Jurnal Penelitian Pendidikan IPA (JPPIPA) Momentum: Physics Education Journal MUST: Journal of Mathematics Education, Science and Technology Journal of Natural Science and Integration JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI JURNAL PENDIDIKAN TAMBUSAI Journal of Education Technology Jurnal Tekno Insentif Jurnal Sains Dirgantara Education and Human Development Journal Kappa Journal Jurnal Paedagogy Cendikia : Media Jurnal Ilmiah Pendidikan Journal Evaluation in Education (JEE) Brilliance: Research of Artificial Intelligence Jurnal Pengabdian Masyarakat untuk Negeri (UN-PENMAS) Jurnal Komputer Teknologi Informasi Sistem Komputer (JUKTISI) Digital Transformation Technology (Digitech) Journal of Coaching and Sports Science Bulletin of Social Informatics Theory and Application Jurnal Guru Komputer Journal of Deep Learning, Computer Vision and Digital Image Processing Journal of Computers for Society Cadika Journal. IJIES (International Journal of Innovation in Enterprise System) Curricula: Journal of Curriculum Development THABIEA : JOURNAL OF NATURAL SCIENCE TEACHING
Lala Septem Riza
Universitas Pendidikan Indonesia, Bandung, Indonesia
Agriculture, Biological Sciences & Forestry Humanities Astronomy Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Languange, Linguistic, Communication & Media Library & Information Science Materials Science & Nanotechnology Mathematics Physics Social Sciences Other

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Machine Learning-Based Clustering for Program Learning Outcomes in Higher Education: A Systematic Review W. Wahyudin; Lala Septem Riza; E. Erlangga; Dwi Novia Al Husaeni
Brilliance: Research of Artificial Intelligence Vol. 5 No. 1 (2025): Brilliance: Research of Artificial Intelligence, Article Research May 2025
Publisher : Yayasan Cita Cendekiawan Al Khwarizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/brilliance.v5i1.5953

Abstract

This study aims to systematically review the application of machine learning-based clustering algorithms in the evaluation of Graduate Learning Outcomes (CPL) in higher education. The review was conducted using the PRISMA approach on articles published in the Scopus database during the period 2020–2025. A total of 52 articles were analyzed to identify trends in the algorithms used, implementation challenges, and their contributions to curriculum development. The findings show that algorithms such as K-Means, Hierarchical Clustering, and Fuzzy C-Means are frequently used in mapping student competencies. However, their implementation in practice remains limited due to insufficient model validation, lack of justification for algorithm selection, and a disconnect between analytical results and academic decision-making. This situation reflects a broader issue in the integration of machine learning into educational contexts, where the technical potential of algorithms has not yet been fully translated into meaningful pedagogical impact. As a conceptual contribution, this study develops a machine learning-based computational model that includes the stages of CPL data collection, preprocessing, cluster modeling, result evaluation, and integration into curriculum policy. The proposed model is designed to enhance transparency, adaptability, and evidence-based decision-making in curriculum management systems. This study also highlights the need for the development of soft clustering techniques, integration with digital learning systems, and attention to the ethics and transparency of algorithms in data-based evaluation. Thus, this study emphasizes the importance of bridging the gap between algorithmic analysis and applicable educational strategies within higher education institutions.
Implementing the rasch model to assess the level of students' critical and reflective thinking skills on the photoelectric effect Tarpin Juandi; Ida Kaniawati; Achmad Samsudin; Lala Septem Riza
Momentum: Physics Education Journal Vol. 7 No. 2 (2023)
Publisher : Universitas PGRI Kanjuruhan Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21067/mpej.v7i2.8252

Abstract

This study aims to determine the level of students’ critical and reflective thinking skills on the topic of photoelectric effects. In this study, the cross-sectional survey approach was employed in conjunction with purposive sampling techniques.  The data collection instruments are questionnaires for critical thinking and reflective thinking skills, with 20 critical thinking items and 24 reflective thinking items. A total of 35 students, 6 males and 29 females, with an average age of 20 years, agreed to fill out the questionnaire that was distributed. The acquired quantitative data were evaluated using the Rasch model, with critical thinking skills showing that 11% of students were at a very low level, 49% were at a low level, 26% were at a high level, and 14% were at a very high level. Meanwhile, data analysis of reflective thinking skills revealed that 20% of pupils had low levels, 63% had moderate levels, and 17% had high levels. As a result, it is suggested that critical thinking and reflective thinking skills be continuously debriefed.
Mengevaluasi Tantangan Keamanan dalam Sistem Akses Digital untuk Pendidikan Kejuruan yang Didukung Teknologi: Tinjauan Literatur Sistematis Kennedy Barfi Yaw Agyeibi; Budi Mulyanti; Agus Setiawan; Lala Septem Riza; Ilhamdaniah Ilhamdaniah
Jurnal Sosioteknologi Vol. 25 No. 2 (2026): JULY 2026
Publisher : Fakultas Seni Rupa dan Desain ITB

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5614/sostek.itbj.2026.25.2.3

Abstract

The rapid expansion of technology-enabled vocational education has increased reliance on digital access systems that regulate entry to learning platforms, simulations, and assessment environments. This study examines how security challenges in these systems affect learning continuity in vocational education and identifies factors that intensify disruption risks. A systematic review of peer-reviewed studies published between 2020 and 2025 was conducted using five academic databases, applying predefined inclusion criteria and synthesizing findings through descriptive and thematic analysis. Results show that weaknesses in data confidentiality, integrity, and especially system availability frequently interrupt instructional activities, particularly practice-based learning dependent on digital laboratories and assessment tools. Disruptions are often amplified by misalignment between technical infrastructure, user practices, and institutional governance, with institutions lacking governance capacity and user training facing higher risks of learning interruption. Although technical and administrative mitigation strategies exist, they are often implemented without sufficient alignment to pedagogical needs. The study concludes that digital access security should be treated not merely as a technical concern but as a prerequisite for equitable and resilient vocational learning, calling for integrated socio-technical and pedagogically informed security strategies.
Comparison of Machine Learning Algorithms for Species Family Classification using DNA Barcode Riza, Lala Septem; Rahman, M Ammar Fadhlur; Prasetyo, Yudi; Zain, Muhammad Iqbal; Siregar, Herbert; Hidayat, Topik; Abu Samah, Khyrina Airin Fariza; Rosyda, Miftahurrahma
Knowledge Engineering and Data Science
Publisher : citeus

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

Abstract

Classifying plant species within the Liliaceae and Amaryllidaceae families presents inherent challenges due to the complex genetic diversity and overlapping morphological traits among species. This study explores the difficulties in accurate classification by comparing 11 supervised learning algorithms applied to DNA barcode data, aiming to enhance the precision of species family classification in these taxonomically intricate plant families. The ribulose-1,5-bisphosphate carboxylase-oxygenase large sub-unit (rbcL) gene, selected as a DNA barcode locus for plants, is used to represent species within the Amaryllidaceae and Liliaceae families. The experimental results demonstrate that nearly all tested models achieve accurate species classification into the appropriate families, with an accuracy rate exceeding 97%, except for the Naïve Bayes model. Regarding computational time, the Random Forest model requires significantly more time for training than other models. Regarding memory usage, the Least Squares Support Vector Machine with a polynomial kernel, and Regularized Logistic Regression consume more memory than other models. These machine learning models exhibit strong concordance with NCBI's classifications when predicting families using the test dataset, effectively categorizing species into the Amaryllidaceae and Liliaceae families.
ANALISIS PENERIMAAN PENGGUNA TERHADAP PEMBELAJARAN MULTIMEDIA PEMROGRAMAN BERORIENTASI OBJEK BERBASIS QR CODE PADA PENDIDIKAN VOKASI DENGAN PENDEKATAN TECHNOLOGY ACCEPTANCE MODEL (TAM) Dwi Fitria Al Husaeni; Mumu Komaro; Lala Septem Riza; Eka Fitrajaya Rahman; Erna Piantari; Amay Suherman
MUST: Journal of Mathematics Education, Science and Technology Vol 10 No 1 (2025): JULY
Publisher : Universitas Muhammadiyah Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30651/must.v10i1.25503

Abstract

The research objective is to analyze the Technology Acceptance Model (TAM) in measuring QR Code-based object-oriented programming learning multimedia in supporting vocational school students' learning on problem-based object-oriented programming (PBO) material. The TAM model variables used consist of Perceived Usefulness (PU), Perceived Ease of User (PEU), and User Acceptance of IT (UA-IT). The research respondents consisted of 35 students of SMK Negeri 1 Cimahi. The research stages consisted of familiarizing respondents with the use of multimedia, distributing TAM questionnaires, and testing the TAM model using SmartPLS software. The research results show that the average value of the user response questionnaire for QR Code-based PBO learning multimedia is 84.95% in the "Very Good" category. Based on the analysis of the relationship between TAM variables using PLS, it is known that the perceived ease of user variable has a positive influence on the acceptance of QR Code-based PBO learning multimedia, the perceived usage variable has a positive influence on the acceptance of QR Code-based PBO learning multimedia, and the variable perceived ease of use and perceived use. together they have a positive influence on the acceptance of QR Code-based PBO learning multimedia. This research is expected to provide an explanation regarding the use of TAM analysis in learning multimedia
Improving vocational students’ learning outcomes through problem-based learning with multimodal learning media Dwi Fitria Al Husaeni; Eka Fitrajaya Rahman; Budi Mulyanti; Amay Suherman; Ade Gafar Abdullah; Lala Septem Riza; Erna Piantari; Sabila Fauziyya; Eki Nugraha
Curricula: Journal of Curriculum Development Vol. 4 No. 2 (2025): Curricula: Journal of Curriculum Development
Publisher : Universitas Pendidikan Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17509/curricula.v4i2.91733

Abstract

Learning in vocational schools, particularly in database subjects, is still hampered by conventional methods that do not develop critical thinking skills and practical applications that meet industry needs. This study aims to assess the effect of using learning media in implementing the Problem-Based Learning (PBL) model on improving vocational students' learning outcomes, particularly in database materials. The research employed a three-cycle Classroom Action Research (CAR) method, conducted with 32 students of class XI RPL at SMKN 13 Bandung. The learning strategy in this study was designed using a PBL approach and integrated multimodal media, including PDF modules, PowerPoint presentations, and learning videos. The results showed a significant and consistent increase in student learning outcomes, with the average score rising from 66.30 in the first cycle to 81.84 in the third cycle. This finding confirms that the use of varied learning media in PBL can enhance conceptual understanding and increase students' active engagement in learning.   Abstrak Pembelajaran di SMK, khususnya pada mata pelajaran basis data masih terkendala oleh metode konvensional yang kurang mengembangkan keterampilan berpikir kritis dan penerapan praktis sesuai kebutuhan industri. Penelitian ini bertujuan untuk mengukur pengaruh penggunaan media pembelajaran dalam penerapan model Problem-Based Learning (PBL) terhadap peningkatan hasil belajar siswa SMK, khususnya pada materi basis data. Metode penelitian yang digunakan adalah Penelitian Tindakan Kelas (PTK) tiga siklus, yang dilaksanakan terhadap 32 siswa kelas XI RPL di SMKN 13 Bandung. Strategi pembelajaran dalam penelitian ini dirancang dengan pendekatan PBL yang diintegrasikan dengan media pembelajaran multimoda yang terdiri dari modul PDF, presentasi PowerPoint, dan video pembelajaran. Hasil penelitian menunjukkan peningkatan hasil belajar siswa yang signifikan dan stabil, dengan skor rata-rata meningkat dari 66,30 pada siklus I menjadi 81,84 pada siklus III. Temuan ini menegaskan bahwa penggunaan media pembelajaran yang bervariasi dalam konteks PBL dapat mendorong pemahaman konseptual yang lebih baik dan meningkatkan keterlibatan aktif siswa dalam pembelajaran. Kata Kunci: media pembelajaran; pembelajaran berbasis masalah; sekolah menengah kejuruan
Design of an Apperception Strategy to Activate Students’ Prior Knowledge Using Visual Block Programming Aria Sastra Wisesa; Jajang Kusnendar; Muhammad Rafi Valliansyah; Lala Septem Riza
Journal of Deep Learning, Computer Vision, and Digital Image Processing ARTICLE IN PRESS
Publisher : CV. Sakura Digital Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61255/decoding.v4i3.1633

Abstract

Purpose – This study aims to implement an Activating Prior Knowledge (APK) strategy supported by the OOPify visual block programming tool in Object-Oriented Programming (OOP) learning and to examine students' learning outcomes and learning responses following its implementation.Methods – The study employed the Research and Development (R&D) method, consisting of preliminary study, product development, implementation, and evaluation. Data were collected through observations, interviews, pretest–posttest assessments, and questionnaires. The data were analyzed using the Shapiro–Wilk normality test, the Wilcoxon Signed-Rank Test, Normalized Gain (N-Gain) analysis, and descriptive statistics.Findings – The Wilcoxon Signed-Rank Test showed a statistically significant difference between the pretest and posttest scores (Z = −3.346, p = 0.001). The N-Gain analysis indicated that students with low initial proficiency achieved the highest average N-Gain score of 0.493 (moderate category). In addition, the usability evaluation showed that OOPify obtained an overall usability score of 76.23%, indicating good usability and positive student perceptions. Research implications – These findings provide preliminary evidence that integrating an Activating Prior Knowledge strategy with the OOPify visual block programming platform may support students' conceptual understanding and learning experiences. Because this study employed a one-group pretest–posttest design, the observed differences should not be interpreted as definitive causal effects.Originality – This study integrates the Activating Prior Knowledge strategy through the Know–Want to Know–Learned (KWL) approach and brainstorming activities with the OOPify visual block programming tool to support more meaningful learning of Object-Oriented Programming concepts
Multi-stage hybrid YOLO-driven and MobileNetV2-CNN variants for robust fish freshness classification Raseeda Hamzah; Rosniza Roslan; Amni Munira Khidir; Lala Septem Riza
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 15, No 4: August 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v15.i4.pp3660-3671

Abstract

This study presents a multi-stage hybrid representation learning framework for robust fish freshness classification to address the critical challenge of reliable quality assessment in unpreserved food supply chains. The proposed pipeline operates in two stages: stage-1 employs you only look once (YOLO)v8n as feature-gated detector to validate inputs and eliminate non-fish images, while stage-2 leverages transfer-learned MobileNetV2 variants enhanced with convolutional neural network (CNN) layers, fine-tuning, adaptive learning rate schedulers, and expanded fully connected layers for hierarchical classification into three freshness classes i.e., highly fresh, fresh, and not fresh. The framework has been trained and evaluated on two curated datasets comprising 4,500 fish and non-fish images and 11,111 freshness-labeled including augmented dataset to increase diversity. The experimental results showed significant improvements. The best performance model transfer learning (TL)-MobileNetV2 + CNN + fine-tuning achieved 98.07% training accuracy and 67.72% validation accuracy on 80:20 split, and training accuracy of 97.57%, validation accuracy of 97.21% through 10-fold cross-validation. The comparative benchmarking confirmed that dual-stage design outperformed baseline MobileNetV2 and YOLOv5s models across precision, recall, and F1-score. The findings highlighted significant value of integrating detection-driven validation with transfer-learning classification, and propose new benchmark for intelligent freshness monitoring. For future work, this study aims to explore attention-based models, data integration, and species diversity.
Identifikasi Pola Risiko Akademik Dan Rekomendasi Peningkatan Kinerja Mahasiswa Menggunakan Metode Association Rules Mining Al Husaeni, Dwi Novia; Nabila, Ghina Firdha; Munir; Wahyudin, Asep; Wibisono, Yudi; Rasim; Riza, Lala Septem
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 13 No 4: Agustus 2026
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jtiik.134

Abstract

Penelitian ini dilatarbelakangi oleh kompleksitas faktor non-akademik, seperti gaya hidup dan kondisi sosial ekonomi, yang berpotensi memengaruhi capaian akademik mahasiswa namun belum sepenuhnya dieksplorasi secara sistematis berbasis data. Penelitian ini bertujuan mengidentifikasi pola asosiasi antara gaya hidup, latar belakang keluarga, dan kondisi pembelajaran terhadap status kerja paruh waktu mahasiswa serta dampaknya pada kinerja akademik. Penelitian ini menggunakan pendekatan data mining dengan metode Association Rules Mining (ARM) melalui algoritma Apriori untuk mengekstraksi pola hubungan antarvariabel dari data mahasiswa. Dataset yang digunakan merupakan hasil penggabungan dua dataset akademik dan kebiasaan belajar mahasiswa yang telah melalui proses seleksi variabel, diskretisasi data numerik, serta validasi oleh ahli dan responden. Dengan algoritma Apriori dan validasi holdout, ditemukan 44 aturan asosiasi yang memenuhi kriteria minimum support 0,05 dan confidence 0,8. Kualitas aturan dievaluasi menggunakan metrik support, confidence, dan lift pada data pelatihan dan data pengujian untuk memastikan stabilitas dan konsistensi pola yang dihasilkan. Hasil analisis menunjukkan bahwa mahasiswa yang tidak bekerja paruh waktu umumnya memiliki kualitas tidur yang baik, frekuensi olahraga yang teratur, dukungan ekonomi dari keluarga menengah ke atas, serta akses internet yang memadai, yang merupakan faktor-faktor yang berkorelasi positif dengan performa akademik. Hasil pengujian pada data uji menunjukkan nilai confidence rata-rata di atas 0,8 dan nilai lift lebih besar dari 1, yang mengindikasikan adanya hubungan asosiasi positif antarvariabel. Temuan ini selaras dengan literatur yang menyebut pekerjaan paruh waktu berpotensi mengganggu capaian belajar. Disarankan intervensi berupa beasiswa berbasis kebutuhan, edukasi pola hidup sehat, konseling manajemen waktu, dan peningkatan infrastruktur digital. Penelitian ini berkontribusi pada kebijakan berbasis data untuk mendukung kesejahteraan dan prestasi mahasiswa.   Abstract This study is motivated by the complexity of non-academic factors, such as lifestyle and socioeconomic conditions, which have the potential to influence students’ academic performance but have not yet been systematically explored using data-driven approaches. The study aims to identify association patterns between lifestyle, family background, and learning conditions in relation to students’ part-time employment status and its impact on academic performance. A data mining approach was employed using Association Rules Mining (ARM) with the Apriori algorithm to extract patterns of relationships among variables from student data. The dataset used was obtained from the integration of two academic and learning habit datasets, which underwent variable selection, numerical data discretization, and validation by experts and respondents. Using the Apriori algorithm with holdout validation, 44 association rules were identified that met the minimum criteria of 0.05 support and 0.8 confidence. The quality of the rules was evaluated using support, confidence, and lift metrics on both training and testing datasets to ensure the stability and consistency of the extracted patterns. The results indicate that students who do not engage in part-time work generally exhibit good sleep quality, regular physical activity, sufficient economic support from middle- to high-income families, and adequate internet access—factors that are positively associated with academic performance. Testing results show an average confidence value above 0.8 and lift values greater than 1, indicating positive association relationships among the analyzed variables. These findings are consistent with existing literature suggesting that part-time employment may interfere with academic achievement. Accordingly, interventions such as need-based scholarships, healthy lifestyle education, time management counseling, and improvements in digital infrastructure are recommended. This study contributes to data-driven policymaking to support student well-being and academic success.
Design and Development of Virtual Reality Media on Computer System Learning to Enhance Students' Cognitive Abilities Wahyudin; Anthonio Akbar; Eki Nugraha; Lala Septem Riza; Shah Nazir
Journal of Education Technology Vol. 9 No. 2 (2025): May
Publisher : Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/jet.v9i2.94553

Abstract

The quality of education in Indonesia remains a significant concern, as reflected in the PISA survey, which ranks Indonesia 72nd out of 77 participating countries. One contributing factor is the limited development of Higher Order Thinking Skills (HOTS) among students, particularly in cognitive, psychomotor, and affective domains. This study aims to design and develop Virtual Reality (VR) media integrated with a Self-Directed Learning (SDL) model to enhance students' cognitive abilities in computer system learning. Employing a Research and Development (R&D) approach with the ADDIE model, this experimental research involved 33 students and applied a One Group Pre-test Post-test design. Data were collected through cognitive tests and student response questionnaires, and analyzed using paired sample t-tests and N-Gain calculations. The results indicated a significant improvement in students' cognitive abilities, with overall conceptual gains categorized as moderate and positive student responses toward the VR media. These findings suggest that SDL-based VR media can effectively foster students’ cognitive development, encourage active, independent learning, and serve as an innovative instructional solution to address educational quality challenges. The study implies that immersive technology integration, when paired with appropriate learning models, holds substantial potential in enhancing students' higher-order thinking skills in the digital era.
Co-Authors Abdullah, Cep Ubad Abu Samah, Khyrina Airin Fariza Achmad Samsudin Ade Gafar Abdullah, Ade Gafar Ade Rohayati Ade Sobandi, Ade Adedokun-Shittu, Nafisat Afolake Adi Rahmat Agus Setiawan Ahmad Firdaus Ahmad Fadzil Ahmad Zainal Abidin Al Husaeni, Dwi Fitria Al Husaeni, Dwi Novia Aldi Zainafif Alejandro Rosales Pérez Alejandro Rosales-Pérez Amay Suherman Amirah Misdan, Nur Farhanah Amni Munira Khidir Andre Rangga Gintara Ani Anisyah Ani Anisyah anne Hafina, anne Anthonio Akbar Aqhbar Habib Aria Sastra Wisesa Arianti, Andini Setya Asep Bayu Dani Nandiyanto Asep Wahyudin Asep Wahyudin AZ Pranata Budi Mulyanti Budiana, Dian Cep Ubad Abdullah Dadang Lukman Hakim Destian, Rangga Dewini Dewini Dwi Novia Al Husaeni E. Erlangga Edy Soewono Eka Fitrajaya Rahman Eki Nugraha Eliyawati Eliyawati Enjang Ali Nurdin Enjun Junaeti Erna Piantari Faisal Syaiful Anwar Farhan Dhiyaa Pratama Fathimah, Nusuki Syari'ati Fatimah, Nusuki Syariati Ferry Mukharradi Simatupang Fidela Zhafirah Fuadillah, Erry Gerraldi, Alief Gunarso Hasanah , Lilik Nur Hasrol Jono, Mohd Nor Hajar Hayati , Nurlaila Herbert Siregar Homdijah, Oom Siti Husni Firmansyah Ida Kaniawati Ilhamdaniah Ilhamdaniah Irsyad Fauzan Nurdin ISKANDAR, AYSHA ALIA Isma Widiaty Jaja Kustija Jajang Kusnendar Judhistira Aria Utama Kafilli, Muhammad Fikri Kennedy Barfi Yaw Agyeibi Kenny David Kenny David Khairul Nurmazianna Ismail Khyrina Airin Fariza Abu Samah Khyrina Airin Fariza Abu Samah Kuntjoro Adji Sidarto Liliasari Mahmoud Fahsi Masnur Ali Mediayani, Melani Mohamad Faiz Dzulkalnine Mohd Nor Hajar Hasrol Jono Mohd Nor Hajar Hasrol Jono Muhamad Nabil Fahruddin Muhammad Afif Auliya Muhammad Alam Basallamah Muhammad Aziz Muhammad Azka Atqiya Muhammad Hazmi Zuhdi Muhammad Irfan Firmansyah Muhammad Rafi Valliansyah Muhammad Ramdan Pamungkas Muhammad Syafri Syamsudin Mumu Komaro Munir Munir Munir Munir Munir, Munir N. Nurjanah Nabila, Ghina Firdha Nanang Dwi Ardi Naufal Rabah Wahidin Nazir, Shah Nor Aiza Moketar Nor Intan Shafini Nasaruddin Novi Sofia Fitriasari Novitasari , Eka Fitri Novri Asri Nur Maisarah Nor Azharludin Nur Maisarah Nor Azharludin Nuraulia, Anti Nurhayati, Ai Siti Nurqueen Sayang Dinnie Wirakarnain Nusratullo, Samialloi Olyan, Warzuqni Parlindungan Sinaga Pérez, Alejandro Rosales Pertiwi, Anita Dyah Piantari, Erna Prabawa, Harsa Wara prasetyaningsih prasetyaningsih Prasetyaningsih, Prasetyaningsih Pratiwi Pratiwi Pudjo Sukarno Pudjo Sukarno Putri , Ananda Hafizhah Putri , Liandha Arieska Putri Amelia Solihah Putri, Iffa Ichwani Qobus, Muhammad Shofwan Rahman, M Ammar Fadhlur Raihah Aminuddin Rambari Apandi, Anjar Rani Megasari Raseeda Hamzah Raseeda Hamzah Rasim Rasim, Rasim Rena Zaen Rendi Adistya Rosdiyana Riandi Riandi Riezqa Andika Rika Rafikah Agustin Rizky Rachman Judie Rooseno Rahman Dewanto Rosa, Elisa Rosi Oktiani Rosniza Roslan Rosniza Roslan Rosyda, Miftahurrahma Sabila Fauziyya Safitri, Fibriyana Sahidin, M. Zaenal Iskandar Samah, Khyrina Airin Fariza Abu Sapiruddin, Sapiruddin Selvi Marcellia Shah Nazir Shah Nazir Shah Nazir Sigit Nugroho Siregar, Herbert Siregar, Nofi Marlina Solihat, Syifa Sugeng Rifqi Mubaroq Sulistiyono, Yakub Eriyanto Suratno Susilawati - Tarpin Juandi Tarpin Juandi Taufiq Hidayat Topik Hidayat Tutuka Ariadji Tyas Farrah Dhiba W. Wahyudin Wahyudin Wahyudin - Wahyudin Wahyudin Sanusi Rosada Wahyudin Wahyudin Wahyudin, W. Wawan Setiawan Wibisono, Yudi Wihardi, Yaya Yudi Prasetyo Zain, Muhammad Iqbal Zainab Othman Zsalzsa Puspa Alivia