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All Journal International Journal of Electrical and Computer Engineering IAES International Journal of Artificial Intelligence (IJ-AI) Lontar Komputer: Jurnal Ilmiah Teknologi Informasi JURNAL SISTEM INFORMASI BISNIS ELKHA : Jurnal Teknik Elektro Bulletin of Electrical Engineering and Informatics Jurnal Al Bayan: Jurnal Jurusan Pendidikan Bahasa Arab Jurnal Teknologi Informasi dan Ilmu Komputer Jurnal Edukasi dan Penelitian Informatika (JEPIN) Khazanah Informatika: Jurnal Ilmu Komputer dan Informatika Al-Jabar : Jurnal Pendidikan Matematika Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Jurnal Obsesi: Jurnal Pendidikan Anak Usia Dini Syntax Literate: Jurnal Ilmiah Indonesia Jurnal EDUTECH Undiksha JETL (Journal Of Education, Teaching and Learning) Jurnal Linguistik Komputasional Edunesia : jurnal Ilmiah Pendidikan ABSYARA: Jurnal Pengabdian Pada Masyarakat Journal of System and Computer Engineering JUSTIN (Jurnal Sistem dan Teknologi Informasi) Jurnal Nasional Teknik Elektro dan Teknologi Informasi Tanjungpura International Journal on Dynamics Economics, Social Sciences, and Agribusiness (TIJDESSA) Jurnal Teknik Indonesia Scientica: Jurnal Ilmiah Sains dan Teknologi Journal of Electrical Engineering, Energy, and Information Technology Jurnal Aplikasi dan Riset Informatika
Herry Sujaini
Universitas Tanjungpura
Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Social Sciences Transportation Other

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Perbandingan Algoritma Support Vector Machine (SVM) dan Naive Bayes pada Analisis Sentimen Bahasa Jawa dan Sunda Putri, Galuh Kusuma; Sujaini, Herry; Ulumi, Desepta Isna
JUSTIN (Jurnal Sistem dan Teknologi Informasi) Vol 13, No 2 (2025)
Publisher : Jurusan Informatika Universitas Tanjungpura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26418/justin.v13i2.88285

Abstract

Perbedaan  struktur  kalimat,  pilihan  kata, dan  tingkatkesopanan  dalam  Bahasa Jawa dan Sunda  dibandingkan  dengan  Bahasa Indonesia  membuat  analisis  sentimenmenjadi  lebih  kompleks.  Karakteristik  unik  kedua  bahasaini  sering  kali  sulit  dipahami,  terutama  bagi  bukan  penuturaslinya,  sehingga  metode  pemrosesan  teks  yang  umumdigunakan  untuk  Bahasa Indonesia  tidak  selalu  efektif.  Oleh  karena  itu,  diperlukan  pendekatan  yang  dapatmengklasifikasikan  sentimen  teks  berbahasa  daerah  ini,  apakah  bersifat  positif,  negatif,  atau  netral,  gunameningkatkan  pemahaman  terhadap  opini  masyarakat  sertamemperluas  aksesibilitas  informasi.  Mengingat  tantangantersebut,  penelitian  ini  berfokus  pada  eksplorasi  metodeklasifikasi  yang  dapat  secara  efektif  menanganikarakteristik  unik  dari  Bahasa Jawa dan Sunda  dalamanalisis  sentimen.  Untuk  itu,  penelitian  ini  bertujuanmelakukan  perbandingan  antara  algoritma  Support Vector Machine  (SVM) dan  Naive Bayes  guna  menentukanpendekatan  yang paling  sesuai  dalam  mengklasifikasikansentimen  teks  pada  kedua  bahasa  ini.  SVM  mencari  garis  pemisah  terbaik  untuk  mengklasifikasikan  data,  sedangkanNaive Bayes  menggunakan  perhitungan  probabilitasberdasarkan  pola  kata yang  muncul.  Dalam  penelitian  iniekstraksi  fitur  dilakukan  menggunakan  TF-IDF  dan  seleksifitur  menggunakan  Chi-Square. Data yang  digunakan  dariIndonesian NLP data catalogue  yang  terdata  mulai  daritahun  2020-2023.  Hasil  penelitian  menunjukkan  bahwametode  klasifikasi  Support Vector Machine  (SVM)  lebihbaik  dari  pada  Naive Bayes  di  kedua  bahasa.  SVM  mendapatkan  akurasi  pada Bahasa Jawa  sebesar  76% dan Bahasa Sunda  sebesar  80%  sedangkan  Naive Bayes  pada Bahasa Jawa  sebesar  73% dan Bahasa Sunda  sebesar  77%. SVM  menjadi  metode  terbaik  dalam  penelitian  ini  karenamenunjukkan  performa  yang  lebih  baik  pada  kedua  bahasadibandingkan  Naive Bayes.
Trubbish: Sebuah Implementasi Model Interaksi Gestur dalam Permainan Virtual Reality untuk Pembelajaran Pemilahan Sampah Perwitasari, Anggi; Gusman, Gusman; Sujaini, Herry
JUSTIN (Jurnal Sistem dan Teknologi Informasi) Vol 13, No 3 (2025)
Publisher : Jurusan Informatika Universitas Tanjungpura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26418/justin.v13i3.91361

Abstract

Peningkatan jumlah limbah yang dihasilkan setiap tahun di Indonesia menuntut solusi efektif dalam pengelolaannya. Salah satu pendekatan yang dapat dilakukan adalah dengan menanamkan kesadaran pemilahan sampah sejak dini melalui media pembelajaran interaktif. Penelitian ini mengembangkan permainan edukasi berbasis virtual reality yang dirancang untuk meningkatkan pemahaman anak-anak mengenai pemilahan sampah. Metode penelitian yang digunakan adalah Multimedia Development Life Cycle (MDLC) untuk memastikan pengembangan yang sistematis dan terstruktur. Teknologi virtual reality dipilih karena kemampuannya dalam memberikan pengalaman belajar yang imersif dan menarik. Hasil pengujian usability menunjukkan bahwa permainan ini memiliki kualitas yang sangat baik, dengan skor Likert sebesar 95,7%, yang mengindikasikan tingkat kepuasan pengguna yang tinggi. Temuan ini menunjukkan bahwa pendekatan virtual reality berbasis sensor gerak dapat menjadi metode pembelajaran yang efektif dalam meningkatkan kesadaran dan pemahaman anak-anak tentang pentingnya pemilahan sampah.
A deep learning-based adaptive e-module in mathematics: Design and evaluation for visual communication design vocational students Feriyadi, Deri; Yani T, Ahmad; Tiur Maria, Haratua; Aunurrahman; Sujaini, Herry
Al-Jabar: Jurnal Pendidikan Matematika Vol 16 No 2 (2025): Al-Jabar: Jurnal Pendidikan Matematika
Publisher : Universitas Islam Raden Intan Lampung, INDONESIA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24042/ajpm.v16i2.26718

Abstract

Purpose: This study aims to design, implement, and evaluate a deep learning-based adaptive e-module to teach mathematical concepts. Specifically, the topic of optimum value to tenth-grade vocational students in the Visual Communication Design (DKV) program. The goal is to determine the module's feasibility, practicality, and effectiveness in improving students' problem-solving skills and learning motivation.Method: The research employed the ADDIE development model, consisting of five stages: analysis, design, development, implementation, and evaluation. Validation was carried out by three experts in education and technology. The product was tested on 36 vocational students, using instruments such as expert validation forms, Likert-scale questionnaires, pre- and post-tests, interviews, and classroom observations.Findings: Expert evaluations indicated high feasibility with scores ranging from 4.2 to 4.6. The average student score increased from 57.97 (pre-test) to 69.44 (post-test), while the standard deviation decreased from 11.315 to 8.914. A low correlation between pre- and post-test scores (r = –0.022; p = 0.899) suggests that the module was equally effective for students across different ability levels. Feedback from both teachers and students confirmed the module’s high practicality and engaging nature.Significance: The findings demonstrate that a deep learning-based adaptive e-module can enhance visual and contextualized mathematics learning for vocational students. It promotes conceptual understanding, learning motivation, and problem-solving skills regardless of initial performance. This study highlights the transformative potential of integrating artificial intelligence into instructional design, especially for creative-industry-focused education programs.
Analisis Perbandingan Algoritma Naive Bayes dan K-Nearest Neighbor dalam Klasifikasi Gaya Bahasa pada Teks Berbahasa Indonesia. Tinanda, Fika Tsalsabila; Sujaini, Herry; Nasution, Helfi
Journal of System and Computer Engineering Vol 6 No 4 (2025): JSCE: October 2025
Publisher : Universitas Pancasakti

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61628/jsce.v6i4.2158

Abstract

In the digital era, Indonesian-language texts have rapidly proliferated across social media, online news, blogs, and digital documents, often containing various figurative language styles such as personification, metaphor, hyperbole, euphemism, and irony. Manual identification of these language styles is inefficient on a large scale, especially when class distribution is imbalanced. This study aims to compare the performance of the Naïve Bayes and K-Nearest Neighbor (KNN) algorithms in classifying figurative language styles in Indonesian texts, and to evaluate the impact of applying the Synthetic Minority Over-sampling Technique (SMOTE) and hyperparameter tuning on model accuracy. The dataset consists of 5,155 original samples and 6,240 samples after SMOTE application, with an 80:20 train-test split. Evaluation was conducted under four scenarios: without SMOTE and without tuning, with SMOTE without tuning, without SMOTE with tuning, and with both SMOTE and tuning. The results show that Naïve Bayes demonstrated stable performance with an accuracy of up to 93.19%, while KNN achieved its highest accuracy of 93.43% after applying SMOTE and tuning. The implementation of SMOTE and hyperparameter tuning proved effective in improving accuracy, particularly for KNN. This study highlights the significant contribution of data balancing and parameter optimization in enhancing the automatic classification of figurative language styles in Indonesian texts.
Peningkatan Akurasi Mesin Penerjemah Bahasa Inggris - Indonesia dengan Memaksimalkan Kualitas dan Kuantitas Korpus Paralel Sujaini, Herry
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 7 No 3: Juni 2020
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jtiik.2020732076

Abstract

Korpus paralel memiliki peran yang sangat penting dalam mesin penerjemah statistik (MPS). Korpus paralel yang diperoleh berbagai sumber biasanya memiliki kualitas yang kurang baik, sedangkan kuantitas korpus paralel merupakan tuntutan utama bagi hasil penerjemahan yang baik. Penelitian ini bertujuan untuk mengetahui efek ukuran dan kualitas korpus paralel di MPS. Penelitian ini menggunakan metode bilingual evaluation understudy (BLEU) untuk mengklasifikasikan pasangan kalimat paralel sebagai kalimat berkualitas tinggi atau buruk. Metode ini diterapkan ke korpus paralel yang berisi 1,5 M pasangan kalimat Inggris-Indonesia paralel dan memperoleh 900K pasangan kalimat paralel berkualitas tinggi. Beberapa sistem MPS dengan berbagai ukuran korpus paralel mentah dan korpus berkualitas tinggi yang difilter dilatih dengan MOSES dan dievaluasi kinerjanya. Hasil percobaan yang dilakukan menunjukkan bahwa ukuran korpus paralel merupakan  faktor utama dalam kinerja terjemahan. Selain itu, kinerja terjemahan yang  lebih baik dapat dicapai dengan korpus berkualitas tinggi yang lebih kecil menggunakan metode filter berkualitas. Hasil eksperimen pada MPS bahasa Inggris-Indonesia menunjukkan bahwa dengan menggunakan 60% kalimat yang kualitas terjemahannya baik, kualitas terjemahan dapat meningkat sebesar 7,31%. AbstractThe parallel corpus has a very important role in the statistical machine translator (SMT) system. The parallel corpus obtained by various sources usually has poor quality, while the quantity of parallel corpus is the main demand for good translation results. This study aims to determine the effect of the size and quality of parallel corpus at SMT. This study uses the bilingual evaluation understudy (BLEU) method to classify pairs of parallel sentences as high-quality or bad sentences. This method is applied to a parallel corpus containing 1.5 M parallel English-Indonesian sentence pairs and obtaining 900K pairs of high-quality parallel sentences. Some SMT systems with various sizes of raw parallel bodies and high-quality corpus filtered are trained with MOSES and evaluated for performance. The experimental results show that the size of the parallel corpus is a major factor in translation performance. In addition, better translation performance can be achieved with a smaller high-quality corpus using a quality filter method.The experimental results in the English-Indonesian SMT show that by using 60% of sentences whose translation quality is good, the quality of the translation can increase by 7.31%.
Meningkatkan efektivitas pembelajaran di era digital melalui pelatihan pengembangan video pembelajaran interaktif Ulumi, Desepta Isna; Sujaini, Herry; Perwitasari, Anggi; Novriando, Haried
ABSYARA: Jurnal Pengabdian Pada Masayarakat Vol 4 No 2 (2023): ABSYARA: Jurnal Pengabdian Pada Masyarakat
Publisher : Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/ab.v4i2.24251

Abstract

Effective teaching in the digital era poses a major challenge in education, especially in elementary schools. This study highlights the importance of interactive learning media in enhancing teaching quality. Utilizing methods of presentation, discussion, and mentoring, this training targeted 50 elementary school teachers at SDN 39 and SDN 08 Sungai Kakap. The main focus was on creating educational videos using Microsoft PowerPoint, a software commonly used by teachers. The training content included the definition of educational videos, steps in video creation, tips for making engaging videos, and using PowerPoint for educational purposes. Pre-tests and post-tests were conducted to measure participants' understanding before and after the training. Results showed a significant improvement in understanding and skills in creating educational videos, with average pre-test scores rising from 54 to 93 in post-tests. Participants realized that PowerPoint is not only for presentations but also an effective tool for creating engaging and efficient educational videos. This research affirms that technology-based interactive learning, such as PowerPoint educational videos, enhances teachers' enthusiasm and student engagement, and supports teaching effectiveness in elementary schools. The main conclusion is that educational technology training like this is crucial for enhancing teachers' creativity and the quality of learning in the digital era.
Robmanjar: Robot Teman Belajar Stimulator Literasi Anak Usia Dini Sulistyawati, Sulistyawati; Sujaini, Herry; Salam, Urai; Aunurrahman, Aunurrahman; Wicaksono, Luhur
Jurnal Obsesi : Jurnal Pendidikan Anak Usia Dini Vol. 8 No. 4 (2024)
Publisher : LPPM Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/obsesi.v8i4.5927

Abstract

Perkembangan teknologi digital membuka peluang baru dalam dunia pendidikan anak usia dini. Salah satu tantangan dalam pendidikan anak usia dini adalah bagaimana menstimulasi minat baca dan menulis sejak dini. Tujuan penelitian ini untuk mengembangkan media pembelajaran inovatif berbasis robot bernama Robmanjar dalam upaya meningkatkan kemampuan literasi anak. Penelitian ini menggunakan metode eksperimen dengan desain One-Group Pretest-Posttest Design. Subjek penelitian adalah 15 anak Kelompok Bermain SPNF SKB Kota Pontianak usia 5-6 tahun. Pengumpulan data dilakukan sebelum dan sesudah perlakuan menggunakan tes kemampuan literasi. Analisis data menggunakan uji-t berpasangan untuk membandingkan nilai rerata sebelum dan sesudah perlakuan. Hasil penelitian menunjukkan bahwa terdapat peningkatan yang signifikan pada kemampuan literasi baca dan tulis anak setelah menggunakan media pembelajaran Robmanjar. Penggunaan teknologi robot dalam pembelajaran dapat menjadi alternatif yang menarik dan efektif untuk meningkatkan minat belajar anak. Hasil penelitian ini memberikan kontribusi penting dalam pengembangan media pembelajaran berbasis teknologi untuk anak usia dini.
Application of Photovoltaic Panels as Producers of Electrical Energy With IoT Technology Based on Programmable Logic Controller Aryanto, Budi; Sanjaya, Bomo Wibowo; Sujaini, Herry; Panjaitan, Seno Darmawan; Yacoub, Redi Ratiandi; Miharja, Nata
ELKHA : Jurnal Teknik Elektro Vol. 16 No.1 April 2024
Publisher : Faculty of Engineering, Universitas Tanjungpura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26418/elkha.v16i1.76663

Abstract

The process of converting solar cell electrical energy is a form of utilizing environmentally friendly alternative energy sources (renewable energy). The conversion system is in the form of PV panels that are installed in a location exposed to sunlight and unobstructed. Monitoring is carried out when the sun shines from morning to evening. The location of the panel is in the vehicle parking lot of the engineering faculty, while monitoring is carried out in the Control Laboratory of the Tanjungpura University Engineering Faculty, which is 300 meters away. Factors that determine the quality of PV panels are the system and dimensions. This shows that fluctuations in current (I), voltage (V) and power (P) need to be controlled so that load distribution and reserves can prevent reduced energy generation. Observation and control using Long Range Area (LoRa) radio transmission media connections, Internet of Things (IoT) and Programmable Logical Control (PLC) in real-time. Observation and test results show that energy generation has experienced an increase in temperature which has an impact on reducing power. Meanwhile, the effect of the distance between the installed panels produces an average delay of 7 milliseconds (midday conditions). Meanwhile, the Signal to Noise Ratio (SNR) value for data transmission is 30 dBm at the device frequency of 868.125 MHz. Baud rate 2400-9600 bps with a speed of 0.3 bps "“ 62.5 Kbps. The application of this system is a research novelty because it can determine and control the generation of electrical energy at minimum, maximum and optimum conditions with a certain distance between the observer and the installed panel.
Development of Learning Videos on Computer Hardware Materials Herlinda, Romana; Sujaini, Herry; Suratman, Dede; Warneri, Warneri; Salam, Urai
Edunesia : Jurnal Ilmiah Pendidikan Vol. 6 No. 1 (2025)
Publisher : research, training and philanthropy institution Natural Aceh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51276/edu.v6i1.1035

Abstract

This study aimed to develop a learning video on computer hardware material at SMP Negeri 8 Jangkang using the ADDIE development method. This study involved 32 grade VII students as test subjects and six validators consisting of material, design, and media experts. Qualitative and quantitative data analysis showed that the developed learning video had a very high feasibility level, with an average percentage of 96% in the material, design, and media aspects. Empirical tests on 32 students showed similar results, with a feasibility level reaching 98% and positive responses from students to the learning media. Statistical tests using the Mann-Whitney method showed a significant difference between the experimental and control groups, with a substantial effect value of 5.44. These findings indicate that learning videos have a very considerable influence on student learning outcomes. Based on the study results, learning videos are categorized as very effective media and positively impact student learning outcomes on computer hardware material. In addition, student responses to the use of this media were very positive, which confirmed its effectiveness and usefulness in supporting a more interactive and enjoyable learning process.
Enhancing Arabic Listening Skills through the Development of Interactive Multimedia for High School Students Halisah, Atikah Nur; Sujaini, Herry; Salam, Urai; Aunurrahman, Aunurrahman; Yani, Ahmad; Queiroz, Carla
Jurnal Al Bayan : Jurnal Jurusan Pendidikan Bahasa Arab Vol 17 No 2 (2025): Jurnal Al Bayan: Jurnal Jurusan Pendidikan Bahasa Arab
Publisher : Universitas Islam Negeri Raden Intan Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24042/nhrkx202

Abstract

Listening comprehension is one of the most challenging skills for students learning Arabic. This research aimed to develop and evaluate an interactive multimedia learning product based on the Lectora Inspire application to enhance Arabic listening skills among high school students. Employing a research and development (R&D) design, the study followed a modified Borg & Gall model integrated with the ADDIE framework. Data were collected through interviews, observations, questionnaires, and pre- and post-tests, and analyzed using the Rasch model, N-Gain score, and Mann–Whitney U test. Validation results indicated very good feasibility across content, design, and interactivity aspects. In the experimental class (n = 32), the mean N-Gain score was 0.6272 (62.72%), categorized as medium-to-high according to Hake’s criteria, indicating substantial improvement in listening skills. Rasch analysis revealed significant increases in logit ability from pretest to posttest, with stable fit indices. The Mann–Whitney U test confirmed a significant difference between the experimental and control groups (p < 0.05). The findings of this study indicated that interactive multimedia developed with the Lectora Inspire application effectively enhances Arabic listening skills among high school students. The integration of text, audio, video, animation, and interactive quizzes created an engaging and multisensory learning experience that improved comprehension and motivation. These results implied that teachers can utilize Lectora Inspire–based multimedia as an innovative, student-centered tool to strengthen listening instruction, while the validated development model may serve as a reference for future multimedia-based Arabic learning materials.
Co-Authors Abang Wandi Syafutra, Abang Wandi Achmadi Achmadi Ade Elbani Ade Mirza Adesfiana, Zeny Novia Afriani Afriani Afrizal - Agustina Listiawati ahmad yani Ahmad Yani T Akbar, Khamsah Akbar, Khamsah Akmal, Wildan Aktris Nuryanti, Aktris Al-Abdaliah, Ulfat Alda Dwi Meilinda Aldi Setiawan, Aldi Alhadiansyah Aloysius Mering Andi Ihwan Andreas Christian Andri Hidayat, Andri Anggi Perwitasari Anggi Srimurdianti Sukamto, Anggi Srimurdianti Antonius Yonathan Ardiani, Lian Arif Bijaksana Putra Negara Arif Bijaksana Putra, Arif Bijaksana Asep Nursangaji Aswandi - Aunurrahman Aunurrahman Aunurrahman Ayusra, Nuraini Bijaksana Putra, Arif Bistari Bomo W. Sanjaya Budi Aryanto Darwis, Robby Darwis, Robby Dede Suratman Deni Ferliyansah, Deni Desepta Isna Ulumi Despitaria Despitaria, Despitaria Dharmawan, Eric Dian Prawira, Dian Doddi Aria Putra, Doddi Aria Dwi Zulfita Edy Suasono Elang Derdian Marindani Elly Suharlina Enda Esyudha Pratama Enriko Yudhistira Ramadhan Erni Djun Astuti Etsa, Muhammad Dwi Eva Dolorosa Eva Faja Ripanti Eva Faja Ripanti Faizal Feriyadi, Deri Fitri Imansyah Gerry Christofer, Gerry Gientry Rachma Ditami Glen Hizkia Oge Mangundap Gusman, Gusman Hadary, Ferry Hafiz Muhardi Halisah, Atikah Nur Hamdani - Haratua Tiur Maria Silitonga Haried Novriando Hariyadi, Firma Harry Luanda Sadewa, Harry Luanda Hartono, Seno Helen Sasty Pratiwi Helen Sasty Pratiwi, Helen Sasty Helen Sastypratiwi, Helen Helfi Nasution Hendra Robaintoro, Hendra Hendro Priyatman, Hendro Hengky Anra Heri Priyanto, Heri Herlinda, Romana Hermanus Herawan Ica Khamisah, Ica Imam Ghozali Indri Astuti Irwan Adhi Prasetya, Irwan Adhi Ismail Yusuf Ismail Yusuf, Ismail Ismawartati - Jada Ario Yustin, Jada Ario Januardi, Tri Jarob, Yosep Jemi Karlos, Jemi Juanda op, Juanda Kadek Yudhimas Septiyadi Putra, Kadek Yudhimas Septiyadi Kamel, Ahmad Khairiyah, Dian Khairul Hafidh Lo Bun San Luhur Wicaksono Madani Madani, Madani Mandau, M Yunus Mandira, Soni Mario Anggara, Mario Meiran Panggabean Memet Agustiar Mochammad Meddy Danial Muanuddin - Muhammad Azhar Irwansyah Muhammad Hasbiansyah, Muhammad Muhammad Saleh Muhammad Yusuf Muhsin Muhsin Mulyana Mulyana Mutammimah Mutammimah, Mutammimah Muthahari, Morteza Nata Miharja Niken Candraningrum Ninda Fitria Pratiwi, Ninda Fitria Ningsih, Kurnia Ningtyas, Della Widya Novi Safriadi Novi Safriadi Nurmainah - Pertiwi, Anggi Pratama, Ramananda Priyo Saptomo Purwaningsih - Purwoharjono Purwoharjono Purwoharjono Putri, Galuh Kusuma Queiroz, Carla Rachman Rohendi Rachmawati Rahmasari, Reza Rahmidiyani - Ramadhani Edo Saputra Ratna Herawatiningsih Redi R. Yacoub Ridho Prabowo Riduansyah - Rommy Patra Ronja, Ronja Rudy Dwi Nyoto Rudy Dwi Nyoto, Rudy Dwi Rudy Dwinyoto, Rudy Ryan Herwan Dwi Putra, Ryan Herwan Sanjaya, Bomo Wibowo Seno Darmawan Panjaitan Septiriana, Rina Setia Budi Setiawan, Sandra Permata Gea Sholva, Yus Silvia Uslianti Simanjuntak, Maya Salinka Siti Hadijah Siti Halidjah Sofhian Sofhian Stepanus Sahala Sitompul Stephanie Stephanie Steven Pragestu, Steven Sulistyawati Sulistyawati Surachman - Sy. Hasyim Azizurrahman Syaifurrahman Syaifurrahman Syamswisna , Syarifah Nurbaiti Tedy Rismawan Tinanda, Fika Tsalsabila Tri Apriani, Tri Try Wahyudinata, Try Tursina Tursina Tursina Tursina Tursina Tursina urai salam Uti Asikin Veithzal Rivai Zainal Venny Karolina Vivensius Mitra, Vivensius Vivi Bachtiar Wahyu Gunawan Wahyuni, Mirda Warneri . Wendy Windhu Putra Witarsa - Yohanes Gatot Sutapa Yulia Magdalena Yuline - Yulis Jamiah Zahra Nadira, Zahra Zubaidah R