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Evaluation of Creative Thinking Skills in the Development of Elementary Science Learning in Elementary Schools: A Mix Method Study Yasa, Arnelia Dwi; Kumala, Farida Nur; Wibawa, Aji Prasetya; Hidayah, Laily
Journal of Education Reseach and Evaluation Vol 7 No 4 (2023): November
Publisher : LPPM Undiksha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/jere.v7i4.68255

Abstract

Students' creative thinking abilities are still limited in science learning development lectures. Students are only able to answer questions at the concept application level (C1-C3 or lower order thinking skill). This is due to the lack of variety in learning methods, lecture material has not been linked to contextual problems. This research aim is to analyze the creative thinking abilities of elementary teacher education students in elementary science learning development courses. This study uses mixed method. Sampling was carried out using random sampling involving 233 students from 8 different campuses. The research instrument consists of a test that includes 12 questions related to indicators of creative thinking skills (fluency, flexibility, originality, and collaboration), semi-structured interviews with 10 respondents to explore the understanding behind the answers given, and documentation. Data analysis techniques are carried out through quantitative and qualitative data analysis which includes data reduction, data presentation, as well as drawing conclusions and verification. The research results show that of the four indicators of creative thinking, students are categorized as sufficient in the fluency aspect. However, the other three indicators, namely flexibility, originality, and elaboration are in the poor category. The interview results also revealed that the majority of respondents were unable to provide answers that were in accordance with the indicators of creative thinking achievement. The conclusion of this research is that three indicators of creative thinking, namely flexibility, originality and elaboration, need to be improved because they are categorized as lacking.
Patterns of Computational Thinking Skills for Elementary Prospectives Teacher in Science Learning: Gender Analysis Studies Kumala, Farida Nur; Dwi Yasa, Arnelia; Bin Haji Jait, Adam; Aji Prasetya Wibawa; Laily Hidayah
International Journal of Elementary Education Vol 7 No 4 (2023): November
Publisher : Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/ijee.v7i4.68611

Abstract

The PISA data results show that computational thinking abilities are still lacking. Computational thinking ability is influenced by gender. This research aims to analyze patterns of computational thinking skills of prospective elementary school teachers based on gender at 8 universities in Indonesia. In this research, the components of computational thinking skills analyzed are abstraction, algorithmic, decomposition, and pattern recognition. This research is a mix method research with research subjects as many as 234 prospective elementary school teachers at 8 higher educational institutions. The instruments used were test and interviews. The data analysis technique used is a quantitative data analysis technique using SEM PLS and for qualitative data analysis using miles and Huberman. The research results show that computational thinking skills are still low on the decomposition and pattern recognition components. Based on the SEM PLS test results, it shows that computational thinking abilities are related to gender. In general, the computational thinking ability of female students is slightly higher in all sub-indicators than men and there are differences in the pattern of computational thinking ability between male and female elementary school teacher prospective. The ability of prospective female elementary school teachers to answer in more detail and more structured, while the answers of male prospective teachers are shorter and less comprehensive. Recommendations for developing computational thinking skills by developing problem-based learning, contextual project-based learning and STEAM based learning.
Comparative Performance of Transformer Models for Cultural Heritage in NLP Tasks Tri Lathif Mardi Suryanto; Aji Prasetya Wibawa; Hariyono Hariyono; Andrew Nafalski
Advance Sustainable Science Engineering and Technology Vol. 7 No. 1 (2025): November-January
Publisher : Science and Technology Research Centre Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/asset.v7i1.1211

Abstract

AI and Machine Learning are crucial in advancing technology, especially for processing large, complex datasets. The transformer model, a primary approach in natural language processing (NLP), enables applications like translation, text summarization, and question-answer (QA) systems. This study compares two popular transformer models, FlanT5 and mT5, which are widely used yet often struggle to capture the specific context of the reference text. Using a unique Goddess Durga QA dataset with specialized cultural knowledge about Indonesia, this research tests how effectively each model can handle culturally specific QA tasks. The study involved data preparation, initial model training, ROUGE metric evaluation (ROUGE-1, ROUGE-2, ROUGE-L, and ROUGE-Lsum), and result analysis. Findings show that FlanT5 outperforms mT5 on multiple metrics, making it better at preserving cultural context. These results are impactful for NLP applications that rely on cultural insight, such as cultural preservation QA systems and context-based educational platforms.
Pemodelan Sistem Deteksi Kadar Unsur Hara Tanah Berdasarkan Nilai NPK Menggunakan Metode Fuzzy Mamdani Dityo Kreshna Argeshwara; Zulkham Umar Rosyidin; Aji Prasetya Wibawa; Anik Nur Handayani; Mokh. Sholihul Hadi
Jurnal Sains dan Informatika Vol. 9 No. 1 (2023): Jurnal Sains dan Informatika
Publisher : Teknik Informatika, Politeknik Negeri Tanah Laut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34128/jsi.v9i1.523

Abstract

Profil kesuburan tanah merupakan hal yang penting dalam pertanian karena merupakan media utama dalam bercocok tanam. Penggunaan pupuk kimia dan pestisida secara terus menerus dan berlebihan akan dapat menimbulkan perubahan sifat fisika dan kimia tanah yang pada akhirnya akan dapat menyebabkan tanah menjadi kritis. Hal ini akan berpengaruh pada produktivitas hasil panen para petani. Salah satu upaya untuk mengetahui tingkat kesuburan tanah adalah melalui diagnosa unsur hara dalam tanah. Tujuan penelitian ini adalah untuk membuat pemodelan sistem optimalisasi deteksi kadar unsur hara dalam tanah menggunakan fuzzy. Melalui simulasi ini akan didapatkan data kadar unsur hara tanah dengan parameter unsur hara N (Nitrogen), P (Fosfor) , K (Kalium) menggunakan labview. Berdasarkan parameter tersebut kemudian dihasilkan berapa nilai kadar unsur hara NPK dalam tanah apakah rendah, sedang atau tinggi.
Indonesian English learning preferences Lisa Ramadhani Harianti; Aji Prasetya Wibawa; Bety Masruroh; Vira Setia Ningrum; Eka Nurcahya Ningsih
International Journal of Education and Learning Vol 6, No 2 (2024): August
Publisher : Association for Scientific Computing Electrical and Engineering(ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/ijele.v6i2.1352

Abstract

This study examines the language learning preferences of Indonesians by comparing search trends for popular formal English courses and English learning applications using Google Trends data. The data is visualized and analyzed descriptively, revealing Ruang Guru as the most preferred English language institution in Indonesia. Its popularity is attributed to service promotions, user-friendly websites, and efficient marketing techniques. Simultaneously, Grammarly is observed as the most popular English learning application among Indonesian learners, emphasizing the importance of refining writing skills. A comparison of search results between Grammarly and Ruang Guru highlights Grammarly's dominance and the preference for self-directed and flexible learning options among Indonesians. These findings have significant implications for education policymakers, language application developers, and English course institution managers. The study suggests a need for the formulation of courses that align with the preferences of Indonesian learners, facilitating autonomous and flexible learning experiences. This insight can guide strategic decisions to enhance the effectiveness and relevance of English language education in Indonesia.
An enhanced pivot-based neural machine translation for low-resource languages Sulistyo, Danang Arbian; Wibawa, Aji Prasetya; Prasetya, Didik Dwi; Ahda, Fadhli Almuíini
International Journal of Advances in Intelligent Informatics Vol 11, No 2 (2025): May 2025
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/ijain.v11i2.2115

Abstract

This study examines the efficacy of employing Indonesian as an intermediary language to improve the quality of translations from Javanese to Madurese through a pivot-based approach utilizing neural machine translation (NMT). The principal objective of this research is to enhance translation precision and uniformity among these low-resource languages, hence advancing machine translation models for underrepresented languages. The data collecting approach entailed extracting parallel texts from internet sources, followed by pre-processing through tokenization, normalization, and stop-word elimination algorithms. The prepared datasets were utilized to train and assess the NMT models. An intermediary phase utilizing Indonesian is implemented in the translation process to enhance the accuracy and consistency of translations between Javanese and Madurese. Parallel text corpora were created by collecting and preprocessing data, thereafter, utilized to train and assess the NMT models. The pivot-based strategy regularly surpassed direct translation regarding BLEU scores for all n-grams (BLEU-1 to BLEU-4). The enhanced BLEU ratings signify increased precision in vocabulary selection, preservation of context, and overall comprehensibility. This study significantly enhances the current literature in machine translation and computational linguistics, especially for low-resource languages, by illustrating the practical effectiveness of a pivot-based method for augmenting translation precision. The method's dependability and efficacy in producing genuine translations were proved through numerous studies. The pivot-based technique enhances translation quality, although it possesses limitations, including the risk of error propagation and bias originating from the pivot language. Further research is necessary to examine the integration of named entity recognition (NER) to improve accuracy and optimize the intermediate translation process. This project advances the domains of machine translation and the preservation of low-resource languages, with practical implications for multilingual communities, language education resources, and cultural conservation.
Optimizing Indonesian-Sundanese Bilingual Translation with Adam-Based Neural Machine Translation Nada, Anita Qotrun; Wibawa, Aji Prasetya; Putri Syarifa, Dhea Fanny; Fajarwati, Erliana; Putri, Fadia Irsania
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 8 No 6 (2024): December 2024
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v8i6.6116

Abstract

This research seeks to construct an automatic translation between Indonesian and Sundanese languages based on the Neural Machine Translation (NMT) method. The model used in this study is the Long Short-Term Memory (LSTM) type, which carries out an encoder-decoder structure model learned with Bible data. The text translation here was conducted in different epochs to optimize the process, followed by the Adam optimization algorithm. Testing the Adam optimizer with different epoch settings yields a BLEU score for Indonesian to Sundanese translations of 0.991785, higher than the performance of the None optimizer. Experimental results demonstrate that Indonesian to Sundanese translation using Adam optimization with 1000 epochs consistently performed better in BLEU - Bilingual Evaluation Understudy - scoring than Sundanese to Indonesian translation. Limitations of the research were also put forth, particularly technical issues related to the collection of data and the Sundanese language’s complex grammatical features, that the model can only partially express, honorifics, and the problem of polysemy. Also, it must be mentioned that no special hyperparameter selection was performed, as parameters were chosen randomly. In future studies, transformer-based models can be investigated since these architectures will better deal with complex language via their self-attention mechanism.
MPPT Performance Analysis for PV Energy Harvesting Using Grey Wolf Optimization (GWO) Algorithm Aripriharta, Aripriharta; Syabani, Muhiban; Sendari, Siti; Wibawa, Aji Prasetya; Susilo, Suhiro Wongso; Bagaskoro, Muhammad Cahyo; Rosmin, Norzanah
ELKHA : Jurnal Teknik Elektro Vol. 17 No.1 April 2025
Publisher : Faculty of Engineering, Universitas Tanjungpura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26418/elkha.v17i1.91643

Abstract

Renewable energy is a key solution to meeting the growing demand for electricity while reducing reliance on non-renewable sources. Among various renewable technologies, photovoltaic (PV) systems are widely used in solar power plants (PLTS) to harness solar energy. However, PV efficiency is affected by environmental factors such as fluctuating solar irradiance and temperature, which cause instability in output voltage and power. To address these issues, Maximum Power Point Tracking (MPPT) techniques are applied to optimize power extraction. This study proposes the Grey Wolf Optimization (GWO) algorithm for MPPT and evaluates its performance through MATLAB/SIMULINK simulations under varying irradiance and temperature conditions. Inspired by the hunting behavior and social hierarchy of grey wolves, GWO dynamically adjusts the converter's duty cycle based on real-time voltage and current measurements to maximize output power. The study focuses on PV systems in Malang, Indonesia, and compares GWO with the Particle Swarm Optimization (PSO) method in terms of accuracy and stability. The results indicate that increased solar irradiance substantially enhances PV power output, while rising temperatures tend to reduce efficiency. The GWO algorithm achieves an average tracking accuracy of 94.5632%, slightly lower than the 96.9851% achieved by PSO. However, GWO demonstrates superior performance in terms of stability, with faster convergence and reduced oscillations during the tracking process. A comparison of system performance before and after applying the GWO method shows notable improvements in tracking consistency and power extraction efficiency, especially under dynamic environmental changes. The novelty of this study lies in its use of real-world environmental data collected over a 30-day period in a tropical setting, which is rarely addressed in previous GWO-based MPPT research. These findings highlight the potential of the GWO-based MPPT strategy to enhance PV system reliability and efficiency in real-time renewable energy applications.
A review of recent deep learning applications in wood surface defect identification Ali, Martina; Hashim, Ummi Raba’ah; Kanchymalay, Kasturi; Wibawa, Aji Prasetya; Salahuddin, Lizawati; Rahiddin, Rahillda Nadhirah Norizzaty
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 14, No 3: June 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v14.i3.pp1696-1707

Abstract

Wood is widely used in construction, art, and home applications due to its aesthetic appeal and favorable mechanical properties. However, environmental factors significantly affect the growth and preservation of wood, often leading to defects that can reduce its performance and ornamental value. Researchers have introduced machine vision and deep learning methods to address the challenges of high labor costs and inefficiencies in identifying wood defects. Deep learning has shown great success in image recognition tasks, yielding impressive results. This paper reviews previous work on deep-learning strategies for identifying wood surface defects. It also discusses data augmentation techniques to address limited defect data and explores transfer learning to enhance classification accuracy on small datasets. Finally, the paper examines the potential limitations of deep learning for defect identification and suggests future research directions.
Building a Narrative Event Dataset from Andersen’s Fairy Tales for Literary and Computational Analysis Daniati, Erna; Wibawa, Aji Prasetya; Irianto, Wahyu Sakti Gunawan
International Journal of Engineering, Science and Information Technology Vol 5, No 3 (2025)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v5i3.910

Abstract

This paper describes building a narrative event dataset for the entire set of 153 fairy tales written by Hans Christian Andersen as?a resource for literary analysis and computational research. The corpus is?built up through semi-automatic annotation for important narrative events: character actions, period transitions, causal communications, and story themes. Each event is augmented with? metadata such as event type, event participants, event temporality (order) and event thematic relevance. This computer-readable structured data is helpful for NLP applications like event detection and temporal reasoning. Still, it supports in-depth literary?studies of plot structures, moral themes and character archetypes in Andersen's stories. Linking the digital humanities with the domain of computational linguistics, the dataset can be jointly used in inter-disciplinary research, and has the potential to reveal new aspects of classical narrative forms and how these findings?and developments can be usefully integrated in AI-supported storytelling systems.
Co-Authors A.N. Afandi Abd. Rasyid Syamsuri Abdullah Sholum Abdur Rohman Achmad Fanany Onnilita Gaffar Adaby, Resnu Wahyu Ade Kurnia Ganesh Akbari Adil Zakaria Aditya Wahyu Setiawan Adjie Rosyidin Adnan, Adam Agung Bella Putra Utama Agung Bella Putra Utama Agung Bella Putra Utama Agung Bella Putra Utama Agung Bella Putra Utama Agung Bella Putra Utama Agustinus Noertjahyana Ahmad 'Ammar Musyaffa' Ahmad Munjin Nasih Ahmad Naim Che Pee Ahmad Taufiq Aindra, Alifah Diantebes Aji, Bayu Kuncoro Akbari, Ade Kurnia Ganesh Akhimullah Akmal Fattah Akhmad Fanny Fadhilla Akrom Tegar Khomeiny Alamsyah, David Satria Aldy Rahmat Yulianto Alfiansyah Putra Pertama Triono Ali, Martina Alifah Diantebes Aindra Amro, Manar Y Andien Khansa’a Iffat Paramarta Andika Dwiyanto, Felix Andini, Nurul Fajriah Andrew Nafalski Andrew Nafalski Andrew Nafalski Andrew Nafalski Andrew Nafalski Andrew Nafalski Andri Pranolo Andriansyah, Muhammad Rizal Angeline, Grace Anik Nur Handayani Anton Prafanto Anusua Ghosh Anusua Ghosh, Anusua Ardha Ardhana Putra Agustavada Ardiansyah, Mohammad Iqbal Firman Aripriharta - Arya Tandy Hermawan Ashar, Muhammad Astuti, Wistiani Atmaja, I Made Ari Dwi Suta Atmaja, Nimas Hadi Azizah, Desi Fatkhi Ba, Abdoul Fatakhou Bagaskoro, Muhammad Cahyo Bahalwan, Lugas Anegah Baitun Nadhiroh Bambang Widi Pratolo Bella Putra Utama, Agung Betty Masruroh Bety Masruroh Bin Abdul Hadi, Abdul Razak Bin Haji Jait, Adam Cahyo Prayogo, Cahyo Cengiz, Korhan Che Pee, Ahmad Naim Chong , Wan Ni Chuttur, Mohammad Yasser Citra Suardi Citra, Hana Rachma Collante, Leonel Hernandez Dafa Fadhilah Hilmi Danang Arbian Sulistyo Daniar Wahyu Darwis, Herdianti David Satria Alamsyah Dedes, Khen Dedi Kuswandi Dedy Kuswandi Denis Eka Cahyani Denna Delawanti Chrisyarani, Denna Delawanti Desi Anggreani Devi Dwi Purwanto Devita, Riri Nada Dewandra, Aderyan Reynaldi Fahrezza Dewi, Popy Maulida Dhani Wahyu Wijaya Dhani Wahyu Wijaya Dhaniyar Dhaniyar Didik Dwi Prasetya Didik Nurhadi Didik Suprayogo Dika Fikri L Dityo Kreshna Argeshwara Dityo Kreshna Argeshwara Drezewski, Rafał Dwi Jaelani, Mardian dwi yasa, arnelia Dwieb, Mohamed Dwiyanto, Felix Andika Dwiyanto, Felix Andika Dyah Lestari Edinar Valiant Hawali Eka Nurcahya Ningsih Elta Sonalitha Endah Setyo Wardani Erna Daniati Esther Irawati Setiawan Eva, Nur Fachrul Kurniawan Fachrul Kurniawan Fachrul Kurniawan Fadhilah, Farhan Fadhilla, Akhmad Fanny Fadhli Almu’iini Ahda Fadia Irsania Putri Faidzin, Ilham Fajar Purnama Fajarwati, Erliana Faller, Erwin Faradini Usha Setyaputri Farid Miftahuddin Farida Nur Kumala Fauzan Cahya Arifin Felix Andika Dwiyanto Felix Andika Dwiyanto Felix Andika Dwiyanto Felix Andika Dwiyanto Felix Andika Dwiyanto Ferdinand, Miftakhul Anggita Bima Ferina Ayu Pusparani Filby , Brilliant Filby, Brilliant Fitria, Nimas Dian Fitriana Kurniawati Fukuda, Osamu Gianika Roman Sosa Graciello, Manuel Tanbica Gülsün Kurubacak Gunawan Gunawan Gwinny Tirza Rarastri Hakkun Elmunsyah Hammad, Jehad A. H. Hammad, Jehad A.H Handayani , Anik Nur Hari Putranto Haris Anwar Syafrudie Harits Ar Rasyid Harits Ar Rosyid Hariyono Hariyono Hariyono Hariyono Hariyono Hariyono Hartono, Nickolas Hary Suswanto Hasanuddin, Tasrif Hashim, Ummi Raba’ah Hasihi, Cholisah Erman Haviluddin Haviluddin Haviluddin, - Hendrawan, William Hartanto Heri Pratikto Herman Herman Herman Santoso Pakpahan Herman Thuan To Saurik Heru Nurwarsito Heru Wahyu Herwanto Hery Widijanto Hidayah Kariima Fithri Hidayah, Laily Hidayatul Ma'rifah Hitipeuw, Emanuel Hong, Yeap Chi I Made Wirawan I Nyoman Gede Arya Astawa Idris Idris Ilham Mulya Putra Pradana Imansyah, Pranadya Bagus Imro’aturrozaniyah, Imro’aturrozaniyah Inggar Tri Agustin Mawarni Irsyada, Rahmat Islam, Noorul Islami, Pio Arfianova Fitrizky Islami, Pio Arfianova Fitrizky Islami, Pio Arfianova Fitrizky Ismail, Amelia Ritahani Istiqlal, Adib Izdihar, Zahra Nabila Jabari, Nida Jehad A. H. Hammad Jehad A.H. Hammad Jehad Hammad Jevri Tri Ardiansah Junoh, Ahmad Kadri Juwita Annisa Fauzi Juwita Annisa Fauzi Kaki, Gregorius Paulus Mario Laka Kartika Candra Kirana Kasturi Kanchymalay, Kasturi Kelvin Wong Khafit Badrus Zaman Khoiruddin Asfanie Khurin Nabila Kirya Mateeke Moses Kohei Arai Kurniawan, Fachrul Kurniawan, Novian Candra Kurniawati, Fitriana Kuswandi, Dedy Laily Hidayah Langlang Gumilar Lauretta, Giovanny Cyntia Lazuardi Noorca Rachmadi Leonel Hernandez Leonel Hernandez Leonel Hernandez, Leonel Lestari, Muqodimah Nur Lestari, Muqodimah Nur Lestari, Muqodimah Nur Liang, Yoeh Wen Lisa Ramadhani Harianti Lisa Ramadhani Harianti Ludovikus Boman Wadu Luther Latumakulita M Zainal Arifin, M Zainal M. Alfian Mizar M. Zainal Arifin Mairi, Vitrail Gloria Mansoor Abdul Hamid Mantony, Oslida Mao, Yingchi Marchena, Piedad Marida, Tyas Agung Cahyaning Marji Marji Markus Diantoro Masruroh, Bety Mazarina Devi Meiga Ayu Ariyanti Mhd. Irvan, Mhd. Irvan Mifta Dewayani Miftahul Qiki Winata Miladina Rizka Aziza Ming F. Teng Ming Foey Teng, Ming Foey Mochamad Hariadi Moh. Safii Moh. Zainul Falah Mohamad Rodhi Faiz Mokh Sholihul Hadi Moses, Kirya Mateeke Moses, Kirya Mateeke Moses, Kirya Mateeke Mudakir, Mudakir Muh. Aliyazid Mude Muhamad Arifin Muhammad Busthomi Arviansyah Muhammad Ferdyan Syach Muhammad Firman Aji Saputra Muhammad Iqbal Akbar Muhammad Jauharul Fuadi Muhammad Nu’man Hakim Muhammad, Abdullahi Uwaisu Muladi Munir Munir Muntholib Muqodimah Nur Lestari Mursyit, Mohammad Musyaffa', Ahmad 'Ammar Nabila Izdihar, Zahra Nabila, Khurin Nada, Anita Qotrun Nadhiroh, Baitun Nadia Roosmalita Sari Nafalski, Andrew Nastiti Susetyo Fanany Putri Naufal, Ayyub Naziro Nedic, Zorica Ningsih, Eka Nurcahya Ningtyas, Yana Novia Ratnasari Noviani, Erina Fika Novrindah Alvi Hasanah Nugraha, Agil Zaidan Nur Hidayat, Wahyu Nur Hidayatullah Nurfadila, Piska Dwi Nurhalifah, Siti Nuril Anwar, Nuril Nurroby Wahyu Saputra Nurul Falah Hashim Nurul Hidayat Nuryana, Zalik Oakley, Simon Okazaki Yasuhisa Oki Dwi Yuliana Omar, Saodah Osamu Fukuda Paramarta, Andien Khansa’a Iffat Paul Igunda Machumu Pio Arfianova Fitrizky Islami Praherdhiono, Hendy Prananda Anugrah Prasojo, Fadillah Pratama, Awanda Setya Sanfajar Puji Santoso Puji Santoso Puji Santoso Punaji Setyosari Pundhi Yuliawati Pundhi Yuliawati Purnawansyah Purnawansyah Purnomo Purnomo Purnomo Purnomo Purwatiningsih, Ayu Putra Utama, Agung Bella Putra, Agung Bella Utama Putri Syarifa, Dhea Fanny Putri, Desy Pratiwi Ika Putri, Fadia Irsania Putri, Nastiti Susetyo Fanany Qonita, Adiba Rahiddin, Rahillda Nadhirah Norizzaty Rahmadhani, Nur Aini Syafrina Raja, Roesman Ridwan Ratnasari, Novia Rendy Yani Susanto Resty Wulanningrum Ridho, Faiz Mohammad Ridwan Shalahuddin Ridwan Shalahuddin Riri Nada Devita Rizal Kholif Nurrohman Rizqini, Fajriwati Qoyyum Roni Herdianto Rosmin, Norzanah RR. Poppy Puspitasari Rully Charitas Indra Prahmana Ruth Ema Febrita Saifullah, Shoffan Salahuddin, Lizawati Salsabila, Reni Fatrisna Santoso, Priyo Aji Saputra, Anggie Wahyu Saputra, Irzan Tri Sarni Suhaila Rahim Seno Isbiyantoro Setiawan, Ariyono Setyadi, Hario Jati Setyaputri, Faradini Usha Setyawan P. Sakti Shahrul, Azzhan Shalahuddin, Ridwan Shiddiqy, Jabar Ash Shidiqi, Maulana Ahmad As Shili, Hechmi Sias, Quota Alief Simbolon, Triyanti Sisca Rahmadonna Siti Helmyati Siti Sendari Soenar Soekopitojo Soraya Norma Mustika Sri Rahmawati ST. Ulfawanti Intan Subadra Stamen Gadzhanov Sucahyo, Cornaldo Beliarding Sugiarto Cokrowibowo Sugiyanto - Suhiro Wongso Susilo Sujito Sujito Sularso Sularso, Sularso Sulistyo, Danang Arbian Sunu Jatmika, Sunu Supeno Mardi Susiki Nugroho, Supeno Mardi Supriadi Supriadi Supriyono Supriyono Suryani, Ani Wilujeng Susilo, Suhiro Wongso Suyono Suyono Suyono Suyono Syaad Patmantara Syaad Patmanthara Syabani, Muhiban Tantri Hari Mukti Trahutomo, Dinnuhoni Tri Andi, Tri Tri Kuncoro Tri Lathif Mardi Suryanto Tri Lathif Mardi Suryanto Tri Saputra, Irzan Tri Sutanti Tri Sutanti, Tri Triono, Alfiansyah Putra Pertama Triyanna Widiyaningtyas Triyanna Widyaningtyas Triyanna Widyaningtyas, Triyanna Tsukasa Hirashima Tuatul Mahfud Ummi Rabaah Hasyim Uriu, Wako Utama , Agung Bella Putra Utama, Agung Bella Putra Utomo Pujianto Vira Setia Ningrum Vira Setia Ningrum Voliansky, Roman Wadu, Ludovikus Boman Wahyu Arbianda Yudha Pratama Wahyu Sakti Gunawan Irianto Wahyu Tri Handoko Wako Uriu Wardani, Endah Setyo Wayan Firdaus Mahmudy Wibowo, Danang Arengga Wibowo, Fauzy Satrio Wibowo, Nur Cahyo Widiharso, Prasetya Widiyanintyas, Triyanna Yandratama, Hengky Yasa, Arnelia Dwi Yingchi Mao Yongen Susman Yosi Kristian Yuhefizar Yuhefizar Yuliana, Oki Dwi Yulianto, Aldy Rahmat Yuliawati, Pundhi Yuni Rahmawati Yusmanto, Yunan Zaeni, Ilham Ari Elbaith Zakaria, Adil Zhou, Xiaofeng Zulkham Umar Rosyidin Zulkham Umar Rosyidin