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All Journal International Journal of Electrical and Computer Engineering TEKNIK INFORMATIKA Seminar Nasional Aplikasi Teknologi Informasi (SNATI) ELKHA : Jurnal Teknik Elektro Proceedings of KNASTIK TELKOMNIKA (Telecommunication Computing Electronics and Control) JUTI: Jurnal Ilmiah Teknologi Informasi Jurnal Teknologi Informasi dan Ilmu Komputer Global Strategis Jurnal Teknologi dan Sistem Komputer Jurnal ELTIKOM : Jurnal Teknik Elektro, Teknologi Informasi dan Komputer JOIV : International Journal on Informatics Visualization Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) International Journal of Artificial Intelligence Research Jurnal Penelitian Politik Conference SENATIK STT Adisutjipto Yogyakarta Jurnal Pertahanan : Media Informasi tentang Kajian dan Strategi Pertahanan yang Mengedepankan Identity, Nasionalism dan Integrity JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI JITTER (Jurnal Ilmiah Teknologi Informasi Terapan) KACANEGARA Jurnal Pengabdian pada Masyarakat MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer Jurnal Mnemonic Abdimas Galuh: Jurnal Pengabdian Kepada Masyarakat Abdimasku : Jurnal Pengabdian Masyarakat Aiti: Jurnal Teknologi Informasi Jurnal Teknik Informatika (JUTIF) Journal of Applied Data Sciences Jurnal Pertahanan dan Bela Negara BHAKTI PERSADA Jurnal Aplikasi IPTEKS (Journal of Applied Sciences and Technology) ELPOSYS: Jurnal Sistem Kelistrikan Jurnal Elektrosista Jurnal Informatika Polinema (JIP) Jurnal TNI Angkatan Udara Jurnal Pengabdian Kepada Masyarakat Jurnal Ilmiah Tenaga Listrik.
Arwin Datumaya Wahyudi Sumari
Indonesian Defense University
Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities Automotive Engineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Mechanical Engineering Nursing Public Health Social Sciences Transportation Other

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The Internet-of-Things-based Fishpond Security System Using NodeMCU ESP32-CAM Microcontroller Sumari, Arwin Datumaya Wahyudi; Annurroni, Ilyas; Ayuningtyas, Astika
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 9 No 1 (2025): February 2025
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v9i1.6033

Abstract

Fish theft in ponds is a common problem, especially in freshwater fish farms. To solve this problem, a security system that can detect human movement and provide real-time notifications is needed. This research aims to design and implement an Internet of Things (IoT)-based fishpond security system using NodeMCU ESP32-CAM Microcontroller equipped with HB100 Radar Sensor to detect human entity movement with NodeMCU ESP32-CAM to take pictures of the approaching human entity, as well as Arduino Uno R3 to control system inputs and outputs. The system also sends real-time notifications and can be managed independently by a social media application. The results show that the system can detect human movement well, provide real-time notifications, and be handled easily. The test results show that the HB100 Radar Sensor can detect entities with a maximum distance of 9 meters with overall accuracy of 90%, the Buzzer performs well according to the human entity detected by the sensor, the Arduino Uno R3 successfully sends a trigger signal to NodeMCU ESP32-CAM to activate the OV2640 camera to capture the detected human entities with a maximum distance of up to 60 meters with an optimal distance between 1 to 9 meters. Integrated system test results show that all components of the fishpond security system
Improving the User Interface and Experience of a Student PortalThrough the Eight Golden Rules Sumari, Arwin Datumaya Wahyudi; Perdana, Fatiha Eros; Nugraheny, Dwi; Lovrencic, Sandra
MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Vol. 24 No. 3 (2025)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/matrik.v24i3.4542

Abstract

One of the crucial web-based academic service facilities in higher education is the Student Portal. Based on a survey of student users, the existing Student Portal at the Institut Teknologi Dirgantara Adisutjipto (Design A) is visually unappealing. It therefore requires improvement in terms of User Interface (UI) design. The purpose of this study is to enhance the UI and UX of the Student Portal. The method used involved applying the Eight Golden Rules method and the Maze tool to design the UI. The resulting new design (Design B) and the current one (Design A) were tested using A/B testing. This study involved a sample of 41 student users from the Informatics Study Program, as they were considered familiar with UI/UX, along with four staff users selected to represent the overall population of Student Portal users. The instrument that is used to evaluate both designs is the System Usability Scale (SUS). The test results show that Design A received an average score of 55.0, which falls into the ”OK” category with a grade of D. In contrast, Design B, which incorporates the Eight Golden Rules method, achieved an average score of 75.0, placing it in the ”GOOD” category with a grade of B. In conclusion, the application of the Eight Golden Rules method led to a 36.4% improvement inthe UI and UX of the Student Portal.
Preserving Indigenous Indonesian Batik Motif Using Machine Learning and Information Fusion Sumari, Arwin Datumaya Wahyudi; Aziza, Nadia Layra; Hani'ah, Mamluatul
JOIV : International Journal on Informatics Visualization Vol 9, No 5 (2025)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.9.5.3714

Abstract

Preserving Indonesia’s indigenous cultural heritage in the form of Batik with various motifs to maintain the nation’s continuity from generation to generation. Hundreds of Batik motifs are spread across multiple regions of Indonesia, along with their unique names and meanings, where each motif has a cultural and historical meaning behind it. The distinctive patterns of Batik motifs challenge the community to remember and distinguish them, so it is crucial to have an intelligent system. This study designed and implemented a Batik motif classification system based on machine learning’s Support Vector Machine (SVM) with a Radial Basis Function (RBF) kernel. The primary key to classifier performance is features. An assessment was carried out on the performance of two feature models: single features and fused features. The Gray Level Co-occurrence Matrix (GLCM) produces the texture features of the Batik motif, and the Moment Invariant (MI) is used to create the shape features of Batik motifs. The Union Fusion and XOR operators produce a single fused feature of the two features. The proposed combination of techniques, namely SVM and GLCM, outperforms the combination scenario of Multi Texton Histogram (MTH), Multi Texton Co-Occurrence Descriptor (MTCD), Multi Texton Co-occurrence Histogram (MTCH) with SVM, and the combination of GLCM with 1-NN as well as the combination techniques that employed information fusion. The experiment results showed that the proposed combination technique achieved an accuracy of 97%. It can be concluded that SVM (RBF) with GLCM yields the best Batik motif recognition system.
PERKEMBANGAN TERKINI PENGEMBANGAN DAN PENGAPLIKASIAN TEKNOLOGI COGNITIVE ARTIFICIAL INTELLIGENCE DI POLITEKNIK NEGERI MALANG Ika Noer Syamsiana; Arwin Datumaya Wahyudi Sumari
Jurnal Ilmiah Tenaga Listrik Vol. 1 No. 2 (2022): Jurnal Ilmiah Tenaga Listrik
Publisher : Politeknik Negeri Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51510/jitl.v1i2.736

Abstract

Cognitive Artificial Intelligence (CAI) merupakan teknologi AI yang ditujukan untuk mengemulasikan kemampuan kognitif otak manusia pada sistem berbasis komputer. Metode utama CAI adalah Knowledge Growing System (KGS) yang telah dibangun dan dikembangkan sejak tahun 2006 serta merupakan teknologi CAI asli Indonesia hasil karya anak bangsa. Dalam artikel ini disampaikan perkembangan terkini penelitian, pengembangan, dan pemanfaatan teknologi CAI di Politeknik Negeri Malang pada empat macam use-case yakni pada sistem dukungan pengambilan keputusan, cybersecurity, deteksi Covid-19 dari data-data gejala klinis, pengenalan objek, dan prediksi kesehatan peralatan elektronika dan listrik.
Penerapan Sistem Informasi Administratif Desa Ngijo Kabupaten Malang menggunakan OpenSID Rahmad, Cahya; Sumari, Arwin Datumaya Wahyudi; Kirana, Annisa Puspa; Abdullah, Moch Zawaruddin; Sukmana, Septian Enggar
Bhakti Persada Jurnal Aplikasi IPTEKS Vol. 8 No. 1 (2022): Bhakti Persada Jurnal Aplikasi IPTEKS
Publisher : Unit Publikasi Ilmiah, P3M, Politeknik Negeri Bali

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31940/bp.v8i1.1-8

Abstract

Administrasi kependudukan merupakan rangkaian kegiatan penataan dan penertiban dokumen dan data kependudukan serta pendayagunaan hasilnya untuk pelayanan publik dan pembangunan sektor lain. Desa Ngijo adalah salah satu desa unggulan yang ada di Kabupaten Malang. Kantor Desa Ngijo yang berada di Kabupaten Malang merupakan salah satu instansi pemerintah yang bergerak di bidang pelayanan masyarakat, namun dalam kinerja pelayanan masyarakat Balai Desa ini memiliki kendala dan permasalahan yaitu belum adanya ketersedian sistem informasi yang dapat menangani administrasi kependudukan. Desa Ngijo sebagai salah satu instansi pemerinatahan, memiliki peran yang penting yaitu sebagai pengelola data kependudukan di tingkat desa. Pengelolaan data kependudukan di Desa Ngijo saat ini masih belum memaksimalkan penggunaan teknologi informasi untuk pengelolaannya, sehingga masih terdapat beberapa kekurangan dan kendala yang dihadapi. Seperti masih terdapat kerangkapan data kependudukan, kesulitan dalam pencarian data, serta pembuatan laporan kependudukan. Sehingga pelayanan kepada masyarakat serta kerja dari perangkat desa menjadi kurang efektif dan efisien. Oleh karena itu dibutuhkan sebuah sistem informasi terkomputerisasi yang dapat digunakan untuk mengelola data tersebut. Metode yang digunakan untuk perancangan sistem administrasi kependudukan yaitu dengan metode prototyping. Dengan adanya sistem informasi administrasi kependudukan yang berbasiskan website ini, dapat memudahkan pengelolaan data kependudukan. Hal ini terwujud dalam persepsi dari 98% peserta pelatihan yang menyatakan bahwa sistem ini akan menjadi komponen layanan yang sangat bermanfaat bagi warga desa.
Pemilihan Daging Kelapa Bermutu Berdasarkan Warna dan Tekstur untuk Produksi Wingko Berkualitas Menggunakan Metode Support Vector Machine (SVM) dan Fusi Informasi Sumari, Arwin Datumaya Wahyudi; Alfian, Ahmad Alfian; Rahmad, Cahya
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 8 No 3: Juni 2021
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jtiik.2021834391

Abstract

Mutu daging kelapa adalah faktor utama yang menentukan kualitas produksi wingko baik yang berasal dari kelapa muda atau kelapa tua dari varietas genjah. Dalam upaya menjaga kualitas produksi wingko kelapa, diperlukan teknik dalam memilih daging kelapa yang bermutu tinggi secara konsisten dengan bantuan teknologi. Dalam penelitian ini telah dibangun sebuah sistem pencitraan digital berbasis Kecerdasan Artifisial untuk pemilihan daging kelapa bermutu. Pemilihan tersebut didasarkan pada warna dan tekstur dengan memanfaatkan Support Vector Machine (SVM) sebagai pengklasifikasi, dan fusi informasi. Pengolahan citra digital menggunakan kombinasi metode Hue, Saturation, Value (HSV) dan metode Gray-Level Co-Occurrence Matrix (GLCM) sebagai pengekstraksi fitur warna dan fitur energi. Kedua macam fiur tersebut difusikan menjadi fitur tunggal guna mempercepat klasifikasi oleh SVM sebagai landasan pemilihan daging kelapa. Dengan menggunakan sistem ini, pemilihan daging kelapa bermutu berhasil mencapai akurasi sebesar 50%. Dalam penelitian ini juga ditemukan bahwa ketidak tepatan pelabelan memberi dampak signifikan pada akurasi pemilihan daging kelapa.AbstractThe quality of coconut meat is a primary factor which determines the quality of wingko production whether that comes from young coconut or old one from Genjah variety. In the effort of maintaining the quality of coconut wingko production, a technique for selecting high quality of coconut meat in consistent way with the aid of technology is needed. In this research, an Artificial Intelligence-based digital imaging system for selecting quality coconut meat has been developed. The selection is based on color and texture by utilizing Support Vector Machine (SVM) as classifier and information fusion. The digital image processing uses the combination of Hue, Saturation, Value (HSV) and Gray-Level Co-Occurrence Matrix (GLCM) methods as color and energy feature extractors. Both features are fused to obtain single feature to accelerate SVM classification as the basis for selection the coconut meat. By using this system, the selection of quality coconut meat is successful to achieve the accuracy as much as 50%. In this research it was also found that incorrectly labeling gives significant impact to the accuracy of coconut meat selection.
Pengenalan Jenis Tanaman Mangga Berdasarkan Bentuk dan Tekstur Daun Menggunakan Kecerdasan Artifisial K-NearestNeighbor (KNN) dan Fusi Informasi Sumari, Arwin Datumaya Wahyudi; Syahbana, Muhammad Rifky; Mentari, Mustika
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 8 No 4: Agustus 2021
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jtiik.2021844392

Abstract

Memilih tanaman mangga yang sesuai dengan yang diinginkan menjadi sebuah tantangan dihadapkan pada tanaman marga Mangifera yang ada saat ini. Kesalahan pemilihan jenis tanaman mangga dapat menyebabkan kekecewaan pada pembeli dan menurunkan kepercayaan kepada penjual tanaman mangga karena dapat dianggap memberikan jenis tanaman yang salah. Permasalahannya adalah jenis tanaman mangga dapat diketahui setelah tanaman tersebut berbuah. Oleh karena itu, dalam upaya mereduksi kesalahan dalam pemilihan sebelum melakukan pembelian tanaman mangga, maka dirancang  dan dibangun sebuah sistem pencitraan digital untuk pengenalan jenis tanaman mangga berdasarkan bentuk dan tekstur daun menggunakan metode Kecerdasan Artifisial K-Nearest Neighbor (KNN) yang digabungkan dengan Fusi Informasi guna memperoleh hasil klasifikasi dengan akurasi yang lebih baik. Data citra daun empat macam daun tanaman mangga yakni jenis Gadung, Lalijiwo, Golek dan Irwin, diproses menggunakan metode Local Binary Pattern (LBP) dan Entropy untuk ekstraksi fitur tekstur, dan metode Rectangularity untuk ekstraksi fitur bentuk. Kedua macam fitur tersebut difusikan menjadi masukan bagi pengklasifikasi KNN. Berdasarkan dari hasil-hasil pengujian, K-NN berhasil mengenali keempat jenis tanaman mangga tersebut dengan akurasi tertinggi sebesar 70% pada nilai K = 5, K = 9, K = 10 dan K = 11. Dari hasil pengujian juga diperoleh hasil bahwa fusi informasi mampu mempercepat sistem mengenali jenis tanaman mangga sebesar 0,11 detik. AbstractChoosing the right desired Mango plant is a challenge faced with various types of the existing Mangifera clan plants. The wrong choice of Mango plant species can end up with buyer disappointment and reduce the trust to the seller because it can be considered as providing the wrong type of plant. This happened because the type of Mango plant can only be identified after it bears fruit. In the effort to reduce such error, a digital imaging system was designed and built for recognizing the  types of Mango plants based on the leaf shape and texture using Artificial Intelligence’s K-Nearest Neighbor (KNN) combined with Information Fusion to accelerate the classification with a consistent classification results. The image data consists of four kinds of Mango plant leaves, namely Gadung, Lalijiwo, Golek and Irwin. The leaf texture feature was extracted using the Local Binary Pattern (LBP) and Entropy methods, while the leaf shape feature was extracted using the Rectangularity method. The two features are fused as the input for the KNN classifier. Based on the test results, KNN was able to identify the four types of the Mango plant with the highest accuracy of 70% at values of K = 5, K = 9, K = 10, and K = 11. Besides that, it is also obtained a result that, the information fusion is able to speed up the recognition the types of Mango by 0.11 seconds.
Klasifikasi Mutu Telur Burung Puyuh Berdasarkan Warna dan Tekstur Menggunakan Metode K-Nearest Neighbor (KNN) dan Fusi Informasi Sumari, Arwin Datumaya Wahyudi; Mawarni, Putri Indah; Syulistyo, Arie Rachmad
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 8 No 5: Oktober 2021
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jtiik.2021854393

Abstract

Kualitas produk merupakan faktor utama untuk menjamin keberlangsungan satu usaha peternakan. Perusahaan telur puyuh yang memiliki ribuan burung Puyuh seperti CV. NS Quail Farm mampu memproduksi ribuan telur dalam sehari karena seekor burung Puyuh mampu menghasilkan 250-300 butir telur per tahun. Penyeleksian ribuan telur-telur tersebut dilakukan secara tradisional oleh para pekerja peternakan sehingga kualitas telur-telur hasil seleksi bergantung pada perspektif masing-masing pekerja. Guna memperoleh telur hasil seleksi dengan kualitas yang sama, maka dibangun sebuah sistem pencitraan digital untuk pemilihan telur burung Puyuh berdasarkan fitur warna dan tekstur kulit telur menggunakan metode klasifikasi K-Nearest Neighbor (KNN) yang dikombinasikan dengan fusi informasi. 300 data citra telur burung Puyuh diolah menggunakan normalisasi Red, Green, Blue (RGB) dan Otsu thresholding guna memperoleh fitur warna dan fitur tekstur yang kemudian difusikan menjadi fitur terfusi tunggal sebagai masukan pengklasifikasi KNN. Dari hasil-hasil penelitian, disimpulkan bahwa sistem berhasil mengklasifikasikan mutu telur Baik, Sedang, dan Buruk dengan akurasi rata-rata sebesar 77,78%. Disamping itu, klasifikasi dengan fusi informasi mampu mengungguli klasifikasi tanpa fusi informasi sebesar 11,11% pada nilai  yang sama yakni 7 dan fusi informasi juga mampu mempercepat proses klasifikasi sebesar 0,22 detik dibandingkan terhadap klasifikasi tanpa fusi informasi.AbstractThe quality of product us a primary factor to ensure the sustainability of a farm business. A company which has thousands of quail such as CV. NS Quail is capable of producing thousand quail eggs in a day because a quail is able to produce 250-300 eggs per year. The selection of the eggs is carried out traditionally by the farm workers so that the quality of the selected eggs are depended on the perspective of each worker. In order to obtain the same quality of the selected eggs, a digital imaging system for quail egg selection based on color feature and texture feature using K-Nearest Neighbor (KNN) combined with information fusion is developed. 300 image data of quail egg was processed using Red, Green, Blue (RGB) and Otsu thresholding to obtain color feature and texture feature which then were fused to become single fused feature as the input to KNN classifier. From the research results, it is concluded that the system was managed to classify egg quality as good, medium, and bad with an accuracy of 77,78%. In addition, the classification with information fusion was able to outperform the classification without information fusion by 11.11% at the same  value of 7 and information fusion is also able to accelerate classification process by 0.22 seconds compared to that of without information fusion.
Pelatihan sistem informasi catatan Bimbingan Konseling (BK) bagi guru bimbingan konseling SMA di Kabupaten Sleman Nuryatno, Edi Triono; Ayuningtyas, Astika; Wahyudi Sumari, Arwin Datumaya; Nugraheny, Dwi; Pamungkas, Dedi Bintang; Agustian, Harliyus; Sajati, Haruno; Sudaryanto, Sudaryanto; Aryanto, Salam; Astuti, Yenni
KACANEGARA Jurnal Pengabdian pada Masyarakat Vol 7, No 3 (2024): Agustus
Publisher : Institut Teknologi Dirgantara Adisutjipto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28989/kacanegara.v7i3.2227

Abstract

Guru Bimbingan Konseling (BK) yang tergabung dalam MGBK di wilayah Kabupaten Sleman membutuhkan perangkat lunak yang dapat membantu pekerjaan mereka dalam memberikan konseling kepada anak-anak Sekolah Menengah Atas (SMA) atau Sekolah Menengah Kejuruan (SMK). Dengan menggunakan perangkat lunak yang dapat diakses dimana saja akan sangat menguntungkan bagi Guru BK jika membutuhkan data di waktu apapun dan tempat manapun. Sehijngga para guru ini membutuhkan pelatihan untuk menggunakan perangkant lunak yang dapat diakses melalui halaman brower dengan Alamat catatanbk.com. Rata-rata nilai hasil pelatihan para peserta sejumlah 96,3.  Sebanyak 26 guru memiliki nilai diatas rata-rata dan 7 orang guru berada dibawah rata-rata.
Design and Implementation of 12-Bit Arithmetic Logic Unit with 8 Operation Codes to Field Programmable Gate Array Sumari, Arwin Datumaya Wahyudi; Hijriana, Sukriya; Dermawan, Denny
ELKHA : Jurnal Teknik Elektro Vol. 15 No.2 October 2023
Publisher : Faculty of Engineering, Universitas Tanjungpura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26418/elkha.v15i2.64041

Abstract

Digital system has been a part of human life since the invention of the computer with a microprocessor as the central brain. At the heart of a processor is an Arithmetic Logic Unit (ALU) that handles arithmetic and logic operations. The need for high-speed computation to handle complex computations demands microprocessors with higher performance. The existing 4-opcode 8-bit ALU cannot handle multiplication operations, so a solution is needed. In this research, while raising the appeal of beginners, a 12-bit ALU with eight operation codes (opcode) was designed and implemented in Xilinx"™s Field Programmable Gate Array using a schematic diagram approach through logic gates. The designed and implemented ALU provides addition, subtraction, multiplication, square, AND, OR, NAND, and XOR operations. The multiplication operation was tested by performing the computation to provided datasets to obtain the distance travelled by ten military aircraft based on their maximum speed and air travel duration to ensure its performance. The computation performance comparison with an 8-bit ALU with four opcodes was also done. The computation was done for air travel between 10 to 60 minutes with a 10-minute difference. It was found that the 12-bit ALU with eight opcodes outperformed its contender with computation differences between 130.815 ns and 1,468.214 ns. This high performance is supported by the multiply operation that does repeated addition at one time. Based on this finding, the 8-opcode 12-bit ALU is more efficient in the context of computation time, with consistent accuracy. Moreover, the computation time required to calculate military aircraft data with different maximum speeds and air travel duration is only 119.501 ns.
Co-Authors A.I. Wuryandari A.S. Ahmad Aciek Ida Wuryandari Adang Suwandi Ahmad Adang Suwandi Ahmad Adang Suwandi Ahmad Addin, Tri Nur Ade Ismail Adhika Febrianto Adinandra, Dimas Eka Affandi, Luqman Afifah Millatina Nugraheni Agustian, Harliyus Alfian, Ahmad Alfian Alvi Rahmadhani Anggraini Kusumaningrum, Anggraini Annisa Puspa Kirana Annurroni, Ilyas Anton Setiawan Honggowibowo Ardhia Rahmania, Diva Arie Rachmad Syulistyo Arya Septiawan Astika AyuningTyas, Astika Aziza, Nadia Layra Bachri, Karel Octavianus Bambang Anggoro Soedjarno Bambang Gastomo Bayu Anugerah Rahardjo Putra Benedictus Mardwianta, Benedictus Bima Gilang Lesmana Brian Adam Bhagaskara Catherine Olivia Sereati Chika Labita David Putra Setyawan David Putra Setyawan, David Putra Denny Dermawan Dhebys Suryani Hormansyah, Dhebys Suryani Dimas Rossiawan Hendra Putra Dimas Rossiawan Hendra Putra Djapri, Suparman Dwi Nugraheny, Dwi Dwiguspana, Edwin Emy Setyaningsih Farchan Agil, Mochammad Farel Putra Hidayat Farida Agustini Widjajati Febrianto, Adhika Firman Munthaha Hadi, Arijo Haruno Sajati Haryo Budi Rahmadi Hijriana, Sukriya Indrazno Siradjuddin Jaka Sembiring Jaka Sembiring Khayam, Umar Lovrencic, Sandra Luluk Mufida M. Ardli Aqdama Mamluatul Hani’ah Maulana Zinedin Zidane Mawarni, Putri Indah Moch Zawaruddin Abdullah Mochammad Syaifuddin Zuhri Muhammad Auful Kirom Muhammad Bisri Musthafa Muhammad Bisri Musthofa Muhammad Ifan Fanani Muhammad Oktoda Noorrohman Mustika Mentari Nabilah Hanun Nafisah, Nihayatun Naily Ikmalul Insiyah Ngat Mari Ngatmari Nugraheni, Afifah Milatina Nugroho, Sutopo Purwo Nuryatno, Edi Triono Odhitya Desta Triswidrananta Odhitya Desta Triswidrananta Pamungkas, Dedi Bintang Partono, Rani Perdana, Fatiha Eros Pramitarini, Yushintia Pranata, Aldi Surya Prihantoro, Mitro Pujiastuti, Asih Purwoko, Agus Rahmad, Cahya Rahman, Alex Firmansyah Rahmawati, Fajar Khanif Ricky Yulian Adi Pratama Rindu Alriavindra Funny Rokhimatul Wakhidah Rudy Laksmono Widayatno Salam Aryanto Sarwono Sutikno Satwika, Satriya Dipa Semmy Tyar Armandha Septafiansyah Dwi Putra Septian Enggar Sukmana Setiawan, Paulus Siswanto, Sela Aulia SUDARYANTO SUDARYANTO Sulistio, Andhika Syahbana, Muhammad Rifky Syamsiana, Ika Noer Syamsuri, Tresna Umar Trio Adiono Wahyudi, Moh Ari Wintolo, Hero Yenni Astuti, Yenni Yoda, Vincensius Arga Yohana, Puspa Ayu Yohana Yoppy Yunhasnawa Yushintia Pramitarini Yusuf Kurniawan Zaenal Abidin Zidan Shabira As Sidiq