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All Journal International Journal of Electrical and Computer Engineering IAES International Journal of Artificial Intelligence (IJ-AI) IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Rekam : Jurnal, Fotografi, Televisi Animasi SITEKIN: Jurnal Sains, Teknologi dan Industri Jurnal Teknologi Informasi dan Ilmu Komputer KLIK (Kumpulan jurnaL Ilmu Komputer) (e-Journal) Jurnal Bioedukasi JOIN (Jurnal Online Informatika) Sistemasi: Jurnal Sistem Informasi Jurnal ELTIKOM : Jurnal Teknik Elektro, Teknologi Informasi dan Komputer Informatika Mulawarman: Jurnal Ilmiah Ilmu Komputer Sinkron : Jurnal dan Penelitian Teknik Informatika Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) International Journal of Artificial Intelligence Research INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi Jurnal Sains Dan Teknologi (SAINTEKBU) CogITo Smart Journal Insect (Informatics and Security) : Jurnal Teknik Informatika JOURNAL OF APPLIED INFORMATICS AND COMPUTING JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI Applied Information System and Management ILKOM Jurnal Ilmiah Journal of Economic, Management, Accounting and Technology (JEMATech) KOMPUTIKA - Jurnal Sistem Komputer Jambura Journal of Informatics JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Bitnet: Jurnal Pendidikan Teknologi Informasi EDUMATIC: Jurnal Pendidikan Informatika METIK JURNAL Building of Informatics, Technology and Science Gema Wiralodra Indonesian Journal of Business Intelligence (IJUBI) Jurnal Tecnoscienza Generation Journal Jurnal Mnemonic Pangea : Wahana Informasi Pengembangan Profesi dan Ilmu Geografi Journal Cerita: Creative Education of Research in Information Technology and Artificial Informatics PRAJA: Jurnal Ilmiah Pemerintahan JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Journal of Computer System and Informatics (JoSYC) JIKA (Jurnal Informatika) Jurnal Sistem Komputer dan Informatika (JSON) Community Development Journal: Jurnal Pengabdian Masyarakat Jurnal Perangkat Lunak Jurnal Informa: Jurnal Penelitian dan Pengabdian Masyarakat Aiti: Jurnal Teknologi Informasi Jurnal TIKOMSIN (Teknologi Informasi dan Komunikasi Sinar Nusantara) Jurnal Teknologi Informatika dan Komputer Journal of Computer Networks, Architecture and High Performance Computing Jurnal Teknik Informatika (JUTIF) Jurnal Teknimedia: Teknologi Informasi dan Multimedia Journal of Electrical Engineering and Computer (JEECOM) JINAV: Journal of Information and Visualization International Journal of Artificial Intelligence and Robotics (IJAIR) Mitra Mahajana: Jurnal Pengabdian Masyarakat Jurnal Informatika dan Teknologi Komputer ( J-ICOM) DEVICE Djtechno: Jurnal Teknologi Informasi JTECS : Jurnal Sistem Telekomunikasi Elektronika Sistem Kontrol Power Sistem dan Komputer JURNAL STUDIA KOMUNIKA Jurnal Pengabdian Seni KLIK: Kajian Ilmiah Informatika dan Komputer Jurnal Saintekom : Sains, Teknologi, Komputer dan Manajemen Journal Computer Science and Informatic Systems : J-Cosys Jurnal Mandiri IT Sulawesi Tenggara Educational Journal JURNAL PAI: Jurnal Kajian Pendidikan Agama Islam Jurnal Sisfotek Global International Journal Artificial Intelligent and Informatics Jurnal Informatika Teknologi dan Sains (Jinteks) Journal of Innovation Research and Knowledge SENTRI: Jurnal Riset Ilmiah Malcom: Indonesian Journal of Machine Learning and Computer Science Nusantara of Engineering (NOE) Jurnal Bangkit Indonesia Jurnal Multidisiplin Sahombu COREAI: Jurnal Kecerdasan Buatan, Komputasi dan Teknologi Informasi JEC (Jurnal Edukasi Cendekia) Prosiding SEMNAS INOTEK (Seminar Nasional Inovasi Teknologi) SmartComp Jurnal Informatika Polinema (JIP) Jurnal Informatika: Jurnal Pengembangan IT Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen) Scientific Journal of Informatics Pengabdian Seni Jurnal Sistem Informasi Komputer dan Teknologi Informasi Jurnal TAM (Technology Acceptance Model) Jurnal Sistem Informasi dan Teknologi Informasi Jurnal Komtika (Komputasi dan Informatika)
Kusrini, Kusrini
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KLASIFIKASI PENGENALAN WAJAH SISWA PADA SISTEM KEHADIRAN DENGAN MENGGUNAKAN METODE CONVOLUTIONAL NEURAL NETWORK (CNN) Sarawan, Tommy; Kusrini, Kusrini
Djtechno: Jurnal Teknologi Informasi Vol 6, No 1 (2025): April
Publisher : Universitas Dharmawangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46576/djtechno.v6i1.6017

Abstract

Pengelolaan kehadiran yang konvensional sering kali memakan waktu dan rentan terhadap kesalahan manusia. Oleh karena itu, diperlukan suatu inovasi untuk meningkatkan sistem pengelolaan kehadiran yang lebih akurat, cepat, dan efisien. Pengenalan wajah telah menjadi salah satu teknologi yang semakin populer dalam berbagai aplikasi, termasuk dalam bidang pendidikan. Teknologi ini menawarkan solusi yang efisien dan inovatif untuk mengatasi tantangan dalam sistem kehadiran siswa. Artificial Intelligence, sebagai cabang dari ilmu komputer, bertujuan untuk menciptakan sistem yang mampu melakukan tugas-tugas yang biasanya membutuhkan kecerdasan manusia, seperti pengambilan keputusan, pengenalan pola, dan pembelajaran dari data. Salah satu algoritma yang dapat digunakan adalah Convolutional Neural Network (CNN) yang telah menunjukkan performa yang sangat baik dalam tugas pengenalan wajah, terutama dalam hal ekstraksi fitur dan klasifikasi gambar. Penelitian ini bertujuan untuk mengembangkan model klasifikasi pengenalan wajah siswa pada sistem kehadiran dengan menggunakan metode Convolutional Neural Network (CNN). Penelitian ini menyimpulkan bahwa melakukan retrain pada 50 layers akhir dan 4 layers custom dapat meningkatkan accuracy untuk arsitektur MobileNetV2 mencapai 25% sedangkan ResNetV2 mencapai 26%. Selain itu, skenario dua yang menggunakan arsitektur MobileNetV2 menghasilkan model terbaik dengan nilai precision 92%, recall 91% dan accuracy 91%.
Analisis Laporan Beban Kerja Dosen Pendidikan Agama Islam (PAI) pada Bidang Penelitian dengan menggunakan Metode Clustering Pratama, Muhammad Egy; Kusrini, Kusrini; Agastya, I Made Artha
JURNAL PAI: Jurnal Kajian Pendidikan Agama Islam Vol 4 No 1 (2025)
Publisher : Prodi Pendidikan Agama Islam IAINU Kebumen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33507/pai.v4i1.3150

Abstract

This study aims to classify research activities of Islamic Education lecturers based on Lecturer Workload Reports using the K-Means clustering method. The dataset includes research activities of PAI lecturers at UIN Sultan Aji Muhammad Idris Samarinda over the past three academic years. Classification was conducted by identifying publication types based on keywords and summarizing each lecturer’s activity. The results show variations in productivity, with many activities falling into the “others” category due to the lack of explicit publication descriptions. The K-Means method grouped lecturers into three clusters: Active, Moderately Active, and Less Active, based on the number of activities and total SKS. These findings can assist faculty leaders in formulating human resource development strategies and enhancing lecturers’ performance in supporting key performance indicators (KPI) and accreditation standards.
TESTING OF PIJAR SEKOLAH APPLICATION WITH LOAD TESTING METHOD USING LOCUST Prastyo, Rahmat; Kusrini, Kusrini; Kusnawi, Kusnawi
Jurnal TAM (Technology Acceptance Model) Vol 16, No 1 (2025): Jurnal TAM (Technology Acceptance Model)
Publisher : Institut Bakti Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56327/jurnaltam.v16i1.1790

Abstract

The Pijar Sekolah application is an application created to help the learning and teaching process. Pijar Sekolah has several features, such as attendance, assignments, exams, and grades. The feature that is widely accessed by users is the exam feature. Therefore, when many users use the application simultaneously, it is important to conduct performance test on the Pijar Sekolah application. This study purpose is to conduct performance test with the Load Testing method using Locust. Test was carried out with a gradually increasing number of users, the number of users as testers were 50, 100, 200, 400, and 800 with a ramp-up period of 1 second. The testing will be carried out in accordance with the examination process carried out using the Pijar Sekolah application by accessing Login, Login Status, Exam List, Start Exam, Question List, Exam Questions, and Submit Answers.  The results of the test show that the performance in terms of response time is stable when testing from 50 to 400, but in RPS (Request Per Second) the average value increases with the number of 800 users getting an average value of 33.83 RPS. However, the test with the number of 400 users get an error in submitting answers. When test with the number of users 800, the response time increases and there are several errors by getting responses of 502 and 422 for 0.033%. The results of this study can be used to determine which processes need to be improved in performance. So that the Pijar Sekolah application can be used by many schools in carrying out the exam process simultaneously.
Implementation of Blockchain for Integrated Civil Service Statistical Data (Case Study: Civil Service and Human Resource Development Agency of Madiun Regency, East Java Province) Huda, Syaiful; Kusrini, Kusrini; Kusnawi, Kusnawi
Journal of Electrical Engineering and Computer (JEECOM) Vol 7, No 2 (2025)
Publisher : Universitas Nurul Jadid

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33650/jeecom.v7i2.12170

Abstract

Digital transformation in personnel data management demands a transparent, secure, and integrated system to support data-driven decision-making and enhance accountability in personnel services. An integrated information system and personnel statistical data are necessary to assist leaders in analyzing staffing needs and making more accurate and efficient data-based policies, while also strengthening the principles of good governance through improved transparency and accountability. Therefore, the Personnel and Human Resource Development Agency of the Government of Madiun Regency, East Java, requires technology capable of effectively managing personnel information by offering security, transparency, and data integrity through a decentralized mechanism. Blockchain, as a distributed ledger technology, provides an innovative solution for maintaining data integrity and increasing public trust through permanent, encrypted, and validated transaction records within a decentralized network. The implementation of blockchain in the management of personnel statistical data remains limited, despite the technology’s ability to support real-time audit trails and reliable interactive data visualization. This study proposes a framework for integrating a relational database with smart contracts on the Ethereum network, by recording the hash of statistical data in the smart contract as proof of data authenticity. Data is retrieved from the database, hashed, and the hash is stored in the smart contract to ensure its integrity, with the results visualized in interactive charts. This framework is expected to improve transparency, accountability, and trust in personnel statistical data to support more accurate and efficient strategic decision-making.
Currency Exchange Rate Prediction Using Gated Recurrent Unit (GRU) with Historical Data and Economic Factor Adhani, Muhammad Azmi; Kusrini, Kusrini
Journal of Electrical Engineering and Computer (JEECOM) Vol 7, No 2 (2025)
Publisher : Universitas Nurul Jadid

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33650/jeecom.v7i2.12385

Abstract

This study presents a currency exchange rate prediction model using a Gated Recurrent Unit (GRU) with historical price data and selected economic factors. Historical data, including Open, High, Low, and Close (OHLC) prices, were obtained from Yahoo Finance. Economic factor data, including Non-Farm Payrolls (NFP), Gross Domestic Product (GDP), Purchasing Managers Index (PMI), Retail Sales, and Durable Goods Orders, were collected from Trading View. Data preprocessing involved chronological sorting, missing value handling, feature scaling, and sequence generation. Multiple experiment cases were evaluated: historical data alone, historical data combined with all economic factors, and historical data combined with each individual factor. The GRU model achieved its best performance when incorporating historical data with Durable Goods Orders, indicating that this economic indicator provides significant predictive value, as reflected by the lowest RMSE (0.0076) and MAPE (0.0054), and the highest R² (0.9764) indicating that this economic factor provides significant predictive value. These findings highlight the importance of integrating selected economic factors into exchange rate prediction models to enhance forecasting accuracy.
DEGREE: Development and Validation of a User Experience Model for Digital Educational Games Using Cronbach’s Alpha and Fuzzy Logic Kurniawan, Mei Parwanto; Suyanto, M.; Utami, Ema; Kusrini, Kusrini
Jurnal Teknik Informatika (Jutif) Vol. 6 No. 4 (2025): JUTIF Volume 6, Number 4, Agustus 2025
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2025.6.4.4942

Abstract

The rapid growth of digital educational games demands an evaluation model that accurately captures user experience and adopts a human-centred approach. This study introduces DEGREE (Digital Educational Game Review and Evaluation Engine), an enhanced model extending MEEGA+ by incorporating two previously underrepresented dimensions: Control and Feedback. Using a quantitative approach, questionnaires were distributed to high school students who actively use Minecraft and Duolingo, yielding 4800 responses.Reliability analysis via Cronbach’s Alpha revealed that the Player Experience + Control combination achieved the highest score (α = 0.914), while the inclusion of Feedback reduced reliability (α = 0.864), leading to its exclusion in the final model. The DEGREE model consists of two core domains: Usability (Aesthetics, Learnability, Operability, Accessibility) and Player Experience (Focused Attention, Fun, Challenge, Social Interaction, Confidence, Relevance, Satisfaction, Perceived Learning, User Error Protection, Control). Evaluation scores were calculated using the Fuzzy Weighted Average (FWA) method and Mean of Maximum (MoM) defuzzification. The Control dimension emerged as the most influential (0.2735), followed by Fun (0.2664) and Satisfaction (0.2516), highlighting the significance of user agency in digital learning environments. The DEGREE model offers a statistically robust and user-oriented framework for evaluating educational games, delivering actionable insights for developers and educators to design more effective and engaging digital learning experiences. This study contributes a new validated and generalizable evaluation framework that strengthens the theoretical foundation of user experience assessment in educational game design.
OPTIMASI HYPERPARAMETER MODEL LSTM DAN VARIANNYA UNTUK PERAMALAN PEMBELIAN BAHAN BAKU KARET ALAM Andika, Roy; Kusrini, Kusrini
JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Vol 10, No 3 (2025)
Publisher : STKIP PGRI Tulungagung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29100/jipi.v10i3.7567

Abstract

Penelitian ini mengkaji optimasi hyperparameter pada model peramalan deret waktu untuk memprediksi pembelian bahan baku karet alam. Tiga arsitektur model—LSTM, Bi-LSTM, dan Stacked LSTM—dieksekusi dengan menerapkan tiga metode tuning, yaitu Bayesian Optimization, Hyperband, dan Optuna. Proses tuning dilakukan dengan mengeksplorasi berbagai kombinasi parameter, seperti jumlah epoch, units, dropout rate, learning rate, batch size, dan units2, dengan model dikompilasi menggunakan fungsi loss MSE dan metrik MAE. Hasil penelitian menunjukkan bahwa learning rate dan dropout rate memiliki pengaruh signifikan terhadap penurunan error, sedangkan peningkatan units2 dapat meningkatkan risiko overfitting jika tidak diimbangi dengan strategi regularisasi yang tepat. Analisis mendalam mengungkap bahwa kombinasi Bayesian dengan Stacked LSTM menghasilkan performa terbaik pada subset data dengan score terendah, sedangkan Optuna menunjukkan konsistensi optimal untuk model LSTM. Menariknya, model Bi-LSTM tidak mencapai konfigurasi optimal, kemungkinan disebabkan oleh sensitivitas tuning yang lebih tinggi atau kompleksitas arsitektur yang tidak sesuai dengan karakteristik dataset yang digunakan. Temuan ini memberikan wawasan penting untuk pengembangan model peramalan yang lebih akurat dan efisien serta membuka peluang penelitian lanjutan dalam strategi optimasi hyperparameter yang adaptif dan robust.
Photography Strategies in the Challenges of Industry 4.0 and Society 5.0 Samaratungga, Oscar; Kusrini, Kusrini
Jurnal Multidisiplin Sahombu Vol. 5 No. 06 (2025): Jurnal Multidisiplin Sahombu, September - October (2025)
Publisher : Sean Institute

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

Abstract

Photography faced significant challenges during the COVID-19 pandemic due to restrictions on space for in-person meetings, while previous photo shoots required in-person meetings. During this period, technological and industrial developments began to be introduced in the era of Industry 4.0 and Society 5.0, but their popularity was overshadowed by information about COVID-19. This paper aims to determine the strategies of photographers in facing the challenges of Industry 4.0 and Society 5.0. The method used is qualitative, with data collection through archival/document studies and literature studies. Albert Joseph Toynbee's challenge and response theory is used to discuss these issues. COVID-19 has also influenced photography in finding strategies for professional photography practice. One of these is virtual photoshoots or remote photography. The challenges of photography have become increasingly complex with the emergence of Artificial Intelligence (AI). Photographers are also facing new challenges. This condition is addressed by considering the convenience offered by AI, namely, combining AI results with photography for photo functions used for promotions or business
Evaluation of E-Learning Usability Based on ISO 25010 with Hofstede's Cultural Dimensions as Moderation: A PLS-SEM Study in Higher Education Januhari, Ni Nyoman Utami; Setyanto, Arief; Kusrini, Kusrini; Utami, Ema; Béjar, Rodrigo Martínez
Applied Information System and Management (AISM) Vol. 8 No. 1 (2025): Applied Information System and Management (AISM)
Publisher : Depart. of Information Systems, FST, UIN Syarif Hidayatullah Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15408/aism.v8i1.45738

Abstract

Although e-learning has rapidly advanced in higher education, many platforms still fall short of meeting user needs due to a lack of integration between usability and cultural dimensions. This study explores how usability influences user satisfaction with e-learning platforms, with cultural dimensions based on Hofstede’s model examined as moderating variables. Usability Quality (QiU) is assessed using the ISO/IEC 25010 framework, which includes five key elements: effectiveness, efficiency, user satisfaction, risk avoidance, and contextual relevance. A total of 384 students from private universities in Bali participated in the study, representing a diverse range of academic disciplines. Using SmartPLS and Partial Least Squares Structural Equation Modeling (PLS-SEM), the analysis revealed that usability has a significant effect on user satisfaction (T=7.528, β=0.270), and cultural variables also play a substantial role (T=21.094, β=0.704). Although the moderating effect of culture was statistically significant (T=2.379, β=0.042), its impact was relatively modest compared to the direct effect of usability. Among the usability components, efficiency emerged as the most influential factor. Regarding cultural dimensions, individualism versus collectivism was found to have the strongest effect. These findings emphasize the importance of designing e-learning systems that are both usability-driven and culturally sensitive, ensuring alignment with user expectations and the educational context.  
Analisis Perbandingan Kinerja Web Humas Infrastruktur On-Premise dan Cloud Computing dengan Load Balancer Round Robin: Comparative Analysis of Public Relations Web Performance of On-Premise and Cloud Computing Infrastructure with Round Robin Load Balancer Saleh, Robby Febrianur; Kusrini, Kusrini
MALCOM: Indonesian Journal of Machine Learning and Computer Science Vol. 5 No. 3 (2025): MALCOM July 2025
Publisher : Institut Riset dan Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57152/malcom.v5i3.2182

Abstract

Penelitian ini menganalisis perbandingan kinerja web humas untuk pelayanan publik antara infrastruktur on-premise dan cloud computing dengan load balancer round robin di RSUD Ratu Aji Putri Botung. Era digitalisasi mendorong rumah sakit mengoptimalkan sistem informasi termasuk web humas sebagai platform komunikasi dengan masyarakat. Metode penelitian menggunakan pendekatan eksperimental komparatif dengan pengujian beban menggunakan Apache JMeter pada tiga skenario: 50, 200, dan 2000 concurrent users. Parameter yang dianalisis meliputi response time, throughput, CPU utilization, memory usage, dan availability. Hasil penelitian menunjukkan cloud computing dengan load balancer round robin memberikan performa superior dengan response time excellent (215-293 ms) untuk semua skenario vs on-premise yang mengalami performance collapse hingga 111,969 ms pada 2000 users. CPU utilization cloud computing optimal (78-90%) dengan distribusi beban merata, sedangkan on-premise under-utilized (6-49%). Network traffic cloud computing consistent (354-356K bytes/sec) menunjukkan throughput predictable, sementara on-premise erratic (45-551K bytes/sec). Load balancer round robin terbukti highly effective dengan perfect success rate (100%) vs on-premise (99.3%). Cloud computing menunjukkan excellent scalability dan 497.8x lebih cepat pada extreme load. Penelitian merekomendasikan implementasi cloud computing untuk web humas rumah sakit guna meningkatkan kualitas pelayanan publik significantly
Co-Authors AA Sudharmawan, AA Abdillah, Yahya Auliya Abdullah Sukri, M Iqbal Abdullah, Mochamad Fadillah Achmad Oddy Widyantoro Ade Pujianto, Ade Adhani, Muhammad Azmi Agastya, I Made Artha agung budi AGUS PURWANTO Ahmad Yusuf Aji Santoso, Bayu Aji Susanto Anom Purnomo Alfatta, Hanif Alva Hendi Muhammad anas, hasni Andi Muhammad Irfan Andi Sunyoto Andika, Roy Andriyanto, Rifki Angga Kurniawan Anggit Dwi Hartanto, Anggit Dwi Anggraeni, Meita Dwi Ardana, Wildan Muhammad Ardana, Wildan Muhammmad Ardiansyah, Fachri Ari Yuana, Kumara Arief Setyanto Arief, M Rudyanto Arief, Muhammad Rudyanto Arifuddin, Danang Arik Sofan Tohir Aris Subadi Arli Aditya Parikesit Asnawi, Muhamad Fuat Asri, Saffinah Indah Atin Hasanah Azi, Amanda Aziz Muzani, Ma'ruf Aziz, Moh Abdul Azkar, Azkar Bayu Setiaji Béjar, Rodrigo Martínez Bentar Candra P Bernadhed, Bernadhed Bisono, Hadi Hikmadyo Braeken, An Buana, Yopy Tri Candra, Kurnia Khoirul da Silva, Bruno Darmawan, Eko Rahmad David Agustriawan DHANI ARIATMANTO Dzulhijjah, Dwi Ahmad Eko Pramono Eko Purwanto Ema Utami Emha Taufiq Luthfi Fatkhurrochman, Fatkhurrochman Fauzi, Moch Farid Fauzy, Marwan Noor Febrianti, Winda Febriyanti, Nada Rizki Ferry Wahyu Wibowo fitriyanto, nur Gifari, Okta Ihza Halimi, Ahmad Hamdikatama, Bimantyoso Hanafi Hanafi Hanif Al Fatta Hari Muktafin, Elik Haris, Ruby hartanto, david budi Hartono, Anggit Dwi Haryo, Wasis Hasan, Nur Fitrianingsih Hasan, Nurul Rahmawati Hasirun, Hasirun Helmawati, Nita Herawati, Maimi Heri Abijono, Heri Herlinawati, Noor Hulvi, Alfajri I Made Adi Purwantara Ikhwanudin, Aolia Ilmawati, Fahma Inti Indarto, Aan Jeki Kuswanto Jumaris Jumaris, Jumaris Juwariyah, Siti Kasman, Haris Saktiawan Kharisma, Rizqi Sukma Kurniasari, Iin Kusnawi , Kusnawi Kusnawi Kusnawi Lewu, Retzi Y. Linda, Kumara Dewi Listyanto, Ahmad Wildan López, Alba Puelles Lukman Bachtiar M. RUDYANTO ARIEF M. Suyanto, M. Madhika, Yudha Randa Mahendra, Awanda Putra Majid Rahardi Mangun, Syamsul Syahab Maradona, Maradona Mardiana Mardiana Martínez-Béjar, Rodrigo Masruri, Nizar Haris Masud, Ibnu maulana, fahrizal Megantara, Muhamad Arldi MEI PARWANTO KURNIAWAN Metha, Halifa Sekar Miftachuddin, Achmad Agus Athok Mohamad Firdaus, Mohamad Mohammad Rezza Pahlevi Moningka, Nirwan Muflich, Alwie Mufti Ari Bianto Muhamad Iksan, Muhamad Muhammad Resa Arif Yudianto Muktafin, Elik Hari Mulia Sulistiyono Mulyaningtyas, Widya Muzakir, Muhammad MZ, Reza Rafiq Nasiri, Asro Ngaeni, Nurus Sarifatul Ni Nyoman Utami Januhari, Ni Nyoman Nugroho, Agung Nugroho, Hanantyo Sri Nuk Ghurroh Setyoningrum Nurmalasari, Maulidya Dwi Oktafiqurahman, Andi Olajuwon, Sayyid Muh. Raziq Onde, Mitrakasih La ode Oscar Samaratungga Pamoengkas, Muhamad Agoeng Pamungkas, Sapto Pradipta, Dody Prameswari, Sonia Anjani Prasetio, Agung Budi Prastyo, Rahmat Pratama, Muhammad Egy Puri, Fiyas Mahananing Purnamasari, Resti Putra, Andriyan Dwi Rachmawati Oktaria Mardiyanto RAMADHAN, SYAIFUL Rasyid, Magfirah Raynald Alfian Yudisetyanto Riduan, Nor Rizkayati, Anisa S, Muhamad Rois S, Muhammad Sabri Saleh, Robby Febrianur Samponu, Yohakim Benedictus Santosa, Hendriansyah SANTRI SANTRI Saputro, Moh. Rizal Bayu Saputro, Uyock Anggoro Sarawan, Tommy Sari, Yayak Kartika Selvy Megira, Selvy Semma, Andi Bahtiar Sentoso, Thedjo Setiawan, Moh. Arif Ma'ruf Setyanto, Arif Siswo Utomo, Mardi Slamet . Solikin, Arif Fajar Sudarmawan, Sudarmawan Sudarto Sudarto Swastikawati, Claudia Syafutra, Arif Dwi Syaiful Huda Tala, WD. Syarni Tampubolon, Jandri Tamuntuan, Virginia Toifur, Tubagus TONNY HIDAYAT Tri Nugroho, Arief Tukan, Ewaldus Ambrosius Ula, M. Izul Wahyu Pujiharto, Eka Wahyudi, Alfian Cahyo Wangsa, Sabda Sastra Wicaksono, Nikko Listio Wijaya, Jodi Wiwi Widayani, Wiwi Yanuargi, Bayu Yossy Ariyanto Yuana, Kumara Ari Yuza, Adela Zakaria Zakaria Zuhri, Muhammad Rafli Zulkarnain, Imam Alfath Zumarni, Zumarni