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Aji Prasetya Wibawa

Univeristas Negeri Malang

Author-ID : 2489010

Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities Astronomy Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Neuroscience Physics Public Health Social Sciences Transportation Other

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Math Creativity Survey for Class 4 Elementary School Yasa, Arnelia Dwi; Chrisyarani, Denna Delawanti; Wadu, Ludovikus Boman; Wibawa, Aji Prasetya; Kuswandi, Dedy
Jurnal Ilmiah Sekolah Dasar Vol 5, No 4 (2021): November
Publisher : Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/jisd.v5i4.39479

The development of creativity among school students has received attention and has become a topic of discussion in education policy. The purpose of this study was to explore and describe the creativity of elementary school students in learning Mathematics. This research uses a descriptive approach in the form of a survey. This study involved 200 students from 11 elementary schools. The research instrument is a questionnaire based on 4 aspects, namely, flexibility, originality and elaboration. Descriptive approach was used to analyze the research data. The findings show that students' creativity differs in four aspects. The Fluency Aspect got a score of 3.07 in the medium category. The flexibility aspect got a score of 3,098 in the medium category. The originality aspect got a score of 2.37 in the medium category. The aspect elaboration got a score of 2.47 in the medium category. Based on the results of the study, it can be found that from the four aspects of student creativity in the medium category. The findings suggest that sub-indicators in every aspect of creativity need to be developed and improved.

Implementasi metode Fuzzy Tsukamoto untuk menentukan hasil tes kesehatan pada penerimaan peserta didik baru di Sekolah Menengah Kejuruan Lestari, Muqodimah Nur; Islami, Pio Arfianova Fitrizky; Moses, Kirya Mateeke; Wibawa, Aji Prasetya
Register: Jurnal Ilmiah Teknologi Sistem Informasi Vol 4, No 1 (2018): January
Publisher : Information Systems - Universitas Pesantren Tinggi Darul Ulum

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26594/register.v4i1.718

Sekolah Menengah Kejuruan (SMK) hendaknya mampu menciptakan siswa siap kerja, tidak hanya di sekolah saja dilakukan tes kesehatan. Pada saat memasuki dunia kerja, para siswa juga akan dites kesehatan oleh perusahaan untuk memastikan riwayat kesehatan calon tenaga kerja. Dalam hal ini, pihak sekolah tentunya tidak ingin jika para siswa tidak bisa masuk ke perusahaan karena terbentur dengan riwayat kesehatan. Oleh karena itu, pemeriksaan kesehatan merupakan salah satu persyaratan utama dalam menyeleksi calon siswa baru pada SMK. Dalam makalah ini akan dikembangkan sebuah sistem penentuan status kesehatan peserta didik SMK yang terkomputerisasi. Model yang digunakan dalam kajian ini adalah Fuzzy Tsukamoto. Metode Fuzzy Tsukamoto dilakukan yang pertama kali untuk menentukan fungsi keanggotaannya, kemudian menentukan rule, dan nantinya kategori akan diklasterisasi ke masing-masing kelompok sesuai dengan rule yang diterapkan. Metode Tsukamoto yang digunakan adalah metode defuzzikfikasi rata-rata terpusat (Center Average Defuzzifier). Kesimpulan yang didapat dari penelitian ini adalah penggunaan Logika Fuzzy dengan metode Tsukamoto dapat menentukan status kesehatan pada calon siswa SMK.Â Â Â Vocational High School should be able to prepare students for ready to work. Medical examination is the last step for recruitment process. It is conducted by the company to ascertain the medical history of the prospective workforce. In this case, the school certainly would not want the students can not get into the company because it collided with a medical history. Therefore, medical examination is one of the main requirements in selecting new students in vocational high school. In this paper, a computerized system for determining the health status of vocational high school student developed. The model used in this study is developed. Fuzzy Tsukamoto determines the membership function, then defines the rule, and the categories will be clustered in to different groups according rule applied. The Tsukamoto which was used hereÂ is the Center Average Defuzzifier method. The conclusion obtained from this research is the use of Fuzzy Logic with Tsukamoto method can determine health status in prospective students of vocational high school.

Single Exponential Smoothing-Multilayer Perceptron Untuk Peramalan Pengunjung Unik Jurnal Elektronik Ferdinand, Miftakhul Anggita Bima; Wibawa, Aji Prasetya; Zaeni, Ilham Ari Elbaith; Rosyid, Harits Ar
Mobile and Forensics Vol. 2 No. 2 (2020)
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/mf.v2i2.2034

Jumlah kunjungan rerata pengunjung unik per hari pada jurnal elektronik menunjukkan bahwa hasil terbitan karya ilmiah website tersebut menarik. Sehingga jumlah pengunjung unik dijadikan indikator penting dalam mengukur keberhasilan sebuah jurnal elektronik untuk memenuhi perluasan, penyebaran dan percepatan sistem akreditasi jurnal. Pengunjung Unik merupakan jumlah pengunjung per Internet Address (IP) yang mengakses sebuah jurnal elektronik dalam kurun waktu tertentu. Terdapat beberapa metode yang biasa digunakan untuk peramalan, diantaranya adalah Multilayer Perceptron (MLP). Kualitas data berpengaruh besar dalam membangun model MLP yang baik, karena sukses tidaknya permodelan pada MLP sangat dipengaruhi oleh data input. Salah satu cara untuk meningkatkan kualitas data adalah dengan melakukan smoothing pada data tersebut. Pada penelitian ini digunkan metode peramalan Multilayer Perceptron berdasarkan penelitian sebelumnya dengan kombinasi data training dan testing 80%-20% dengan asitektur 2-1-1 dan learning rate 0,4. Selanjutnya untuk meningkatkan kualitas data dilakukan smoothing dengan menerapkan metode Single Exponential Smoothing. Dari penelitian yang dilakukan diperoleh hasil terbaik menggunakan alpha 0.9 dengan hasil akurasi MSE 94.02% dan RMSE 75.54% dengan lama waktu eksekusi 580,27 detik. The number of visits by the average unique visitor per day on electronic journals shows that the published scientific papers on the website are interesting. So that the number of unique visitors is used as an important indicator in measuring the success of an electronic journal to meet the expansion, dissemination and acceleration of the journal accreditation system. Unique Visitors is the number of visitors per Internet Address (IP) who access an electronic journal within a certain period of time. There are several methods commonly used for forecasting, including the Multilayer Perceptron (MLP). Data quality has a big influence in building a good MLP model, because the success or failure of modeling in MLP is greatly influenced by the input data. One way to improve data quality is by smoothing the data. In this study, the Multilayer Perceptron forecasting method was used based on previous research with a combination of training data and testing 80% -20% with a 2-1-1 architecture and a learning rate of 0.4. Furthermore, to improve data quality, smoothing is done by applying the Single Exponential Smoothing method. From the research conducted, the best results were obtained using alpha 0.9 with MSE accuracy of 94.02% and RMSE 75.54% with a long execution time of 580.27 seconds.

Prediksi Lama Studi Mahasiswa Menggunakan Naïve Bayes Berdasarkan Aspek Sosial Ekonomi Mahasiwa Putri, Desy Pratiwi Ika; Anggreani, Desi; Wibawa, Aji Prasetya
Mobile and Forensics Vol. 2 No. 1 (2020)
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/mf.v2i1.2137

Perguruan tinggi merupakan satuan penyelenggara pendidikan tinggi sebagai tingkat lanjut jenjang pendidikan menengah di jalur pendidikan formal. Kualitas perguruan tinggi, khususnya perguruan tinggi di Indonesia diukur berdasarkan 9 standar utama. Salah satu aspek yang berpengaruh ialah mahasiswa dan lulusan. Ketepatan waktu studi mahasiswa adalah hal yang penting dalam perguruan tinggi. Ketepatan waktu mahasiswa dalam menyelesaikan studi menjadi salah satu penunjang penilaian kualitas perguruan tinggi. Metode Naïve Bayes dapat digunakan untuk memprediksi ketepatan lama studi. Klasifikasi Naïve Bayes dalam penelitian ini menggunakan beberapa variabel yang sangat erat kaitannya dalam menyelesaikan studi khususnya pada aspek sosial ekonomi mahasiswa. Adapun variable dari sisi sosial dan ekonomiÂ tersebut diantaranya jenis kelamin, nilai IPK, tempat lahir, tipe sekolah, jumlah keikutsertaan organisasi, tingkat ekonomi, dan dukungan orang tua. Pada penelitian ini, metode Naïve Bayes diimplementasikan pada kasus prediksi lama studi mahasiswa menggunakan 200 data set. Hasil penelitian menunjukkan tingkat rata-rata akurasi sebesar 80,5% dengan menggunakan K-Fold Cross Validation diperoleh standar deviasi 3,02%. Higher education is a higher education provider unit as an advanced level of secondary education in the formal education pathway. The quality of tertiary institutions, especially tertiary institutions in Indonesia, is measured according to 9 main standards. One influential aspect is students and graduates. Timeliness of student studies is important in higher education. Timeliness of students in completing their studies is one of the supports for assessing the quality of higher education. The Naïve Bayes method can be used to predict the accuracy of the study duration. Naïve Bayes classification in this study uses several variables that are very closely related in completing studies, especially on the social economic aspects of students. The social and economic variables include gender, GPA, birthplace, type of school, number of organizational participations, economic level, and parent support. In this study, the Naïve Bayes method is implemented in the case of prediction of student study duration using 200 data sets. The results showed an average level of accuracy of 80.5% using K-Fold Cross Validation obtained a standard deviation of 3.02%.

Pelabelan Kelas Kata Bahasa Jawa Menggunakan Hidden Markov Model Mursyit, Mohammad; Wibawa, Aji Prasetya; Zaeni, Ilham Ari Elbaith; Rosyid, Harits Ar
Mobile and Forensics Vol. 2 No. 2 (2020)
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/mf.v2i2.2450

Part of Speech Tagging atau POS Tagging adalah proses memberikan label pada setiap kata dalam sebuah kalimat secara otomatis. Penelitian ini menggunakan algoritma Hidden Markov Model (HMM) untuk proses POS Tagging. Perlakuan untuk unknown words menggunakan Most Probable POS-Tag. Dataset yang digunakan berupa 10 cerita pendek berbahasa Jawa terdiri dari 10.180 kata yang telah diberikan tagset Bahasa Jawa. Pada penelitian ini proses POS Tagging menggunakan dua skenario. Skenario pertama yaitu menggunakan algoritma Hidden Markov Model (HMM) tanpa menggunakan perlakuan untuk unknown words. Skenario yang kedua menggunakan HMM dan Most Probable POS-Tag untuk perlakuan unknown words. Hasil menunjukan skenario pertama menghasilkan akurasi sebesar 45.5% dan skenario kedua menghasilkan akurasi sebesar 70.78%. Most Probable POS-Tag dapat meningkatkan akurasi pada POS Tagging tetapi tidak selalu menunjukan hasil yang benar dalam pemberian label. Most Probable POS-Tag dapat menghilangkan probabilitas bernilai Nol dari POS Tagging Hidden Markov Model. Hasil penelitian ini menunjukan bahwa POS Tagging dengan menggunakan Hidden Markov Model dipengaruhi oleh perlakuan terhadap unknown words, perbendaharaan kata dan hubungan label kata pada dataset. Part of Speech Tagging or POS Tagging is the process of automatically giving labels to each word in a sentence. This study uses the Hidden Markov Model (HMM) algorithm for the POS Tagging process. Treatment for unknown words uses the Most Probable POS-Tag. The dataset used is in the form of 10 short stories in Javanese consisting of 10,180 words which have been given the Javanese tagset. In this study, the POS Tagging process uses two scenarios. The first scenario is using the Hidden Markov Model (HMM) algorithm without using treatment for unknown words. The second scenario uses HMM and Most Probable POS-Tag for treatment of unknown words. The results show that the first scenario produces an accuracy of 45.5% and the second scenario produces an accuracy of 70.78%. Most Probable POS-Tag can improve accuracy in POS Tagging but does not always produce correct labels. Most Probable POS-Tag can remove zero-value probability from POS Tagging Hidden Markov Model. The results of this study indicate that POS Tagging using the Hidden Markov Model is influenced by the treatment of unknown words, vocabulary and word label relationships in the dataset.

ANALISIS PENERAPAN APLIKASI MUSEUM VIRTUAL INDONESIA (SIMVONI) Suryanto, Tri Lathif Mardi; Wibowo, Nur Cahyo; Wibawa, Aji Prasetya; Nadhiroh, Baitun
Jurnal Sistem Informasi dan Bisnis Cerdas Vol 15, No 1 (2022): JURNAL SISTEM INFORMASI DAN BISNIS CERDAS (SIBC) FEBRUARI 2022
Publisher : Program Studi Sistem Informasi, Fakultas Ilmu Komputer, UPN "Veteran" Jawa Timur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33005/sibc.v15i1.2877

Penelitian ini mengggunakan metode deskriptif analisis dengan tujuan untuk mengetahui peran SIMVONI sebagai sistem informasi baru yang dapat mempermudah pengunjung museum dalam melakukan kunjungan sehingga dapat menjaga eksistensi kunjungan museum itu sendiri di tengah pandemi Covid-19. Teknologi tersebut dinamakan virtual tour, di tengah pandemic virtual tour menjadi primadona di berbagai sektor termasuk sektor pariwista. Pengembangan SIMVONI digunakan untuk menjaga eksistensi kunjungan museum ditengah segala keterbatasan yang ada. Dengan hasil kuesioner yang didapatkan menunjukkan terdapat gap yang sangat jauh terhadap minat pengguna, dimana pengunjung memiliki niat yang cukup besar untuk berkunjung secara langsung ke museum setelah melakukan tur di SIMVONI. Dari hasil tersebut menunjukkan bahwa saat atau setelah menerapkan SIMVONI di museum memberikan dampak yang positif. DOi : https://doi.org/10.33005/sibc.v15i1.2877

Enabling External Factors for Inflation Rate Forecasting Using Fuzzy Neural System Nadia Roosmalita Sari; Wayan Firdaus Mahmudy; Aji Prasetya Wibawa; Elta Sonalitha
International Journal of Electrical and Computer Engineering (IJECE) Vol 7, No 5: October 2017
Publisher : Institute of Advanced Engineering and Science

Inflation is the tendency of increasing prices of goods in general and happens continuously. Indonesia's economy will decline if inflation is not controlled properly. To control the inflation rate required an inflation rate forecasting in Indonesia. The forecasting result will be used as information to the government in order to keep the inflation rate stable. This study proposes Fuzzy Neural System (FNS) to forecast the inflation rate. This study uses historical data and external factors as the parameters. The external factor using in this study is very important, which inflation rate is not only affected by the historical data. External factor used are four external factors which each factor has two fuzzy set. While historical data is divided into three input variables with three fuzzy sets. The combination of three input variables and four external factors will generate too many rules. Generate of rules with too many amounts will less effective and have lower accuracy. The novelty is needed to minimalize the amount of rules by using two steps fuzzy. To evaluate the forecasting results, Root Means Square Error (RMSE) technique is used. Fuzzy Inference System Sugeno used as the comparison method. The study results show that FNS has a better performance than the comparison method with RMSE that is 1.81.

Illiteracy Classification Using K Means-NaÃ¯ve Bayes Algorithm Muhammad Firman Aji Saputra; Triyanna Widiyaningtyas; Aji Prasetya Wibawa
JOIV : International Journal on Informatics Visualization Vol 2, No 3 (2018)
Publisher : Society of Visual Informatics

Illiteracy is an inability to recognize characters, both in order to read and write. It is a significant problem for countries all around the world including Indonesia. In Indonesia, illiteracy rate is generally set as an indicator to see whether or not education in Indonesia is successful. If this problem is not going to be overcome, it will affect peopleâ€™s prosperity. One system that has been used to overcome this problem is prioritizing the treatment from areas with the highest illiteracy rate and followed by areas with lower illiteracy rate. The method is going to be a way easier to be applied if it is supported by classification process. Since the classification process needs a class, and there has not been any fine classification of illiteracy rate, there is needed a clustering process before classification process. This research is aimed to get optimal number of classes through clustering process and know the result of illiteracy classification process. The clustering process is conducted by using k means algorithm, and for the classification process is conducted by using NaÃ¯ve Bayes algorithm. The testing method used to assess the success of classification process is 10-fold method. Based on the research result, it can be concluded that the optimal illiteracy classes are three classes with the classification accuracy value of 96.4912% and error rate value of 3.5088%. Whereas the classification with two classes get the accuracy value of 93.8596% and error rate value of 6.1404%. And for the classification with five classes get the accuracy value of 90.3509% and error rate value of 9.6491%.

Journal Classification Using Cosine Similarity Method on Title and Abstract with Frequency-Based Stopword Removal Piska Dwi Nurfadila; Aji Prasetya Wibawa; Ilham Ari Elbaith Zaeni; Andrew Nafalski
International Journal of Artificial Intelligence Research Vol 3, No 2 (2019): December 2019
Publisher : STMIK Dharma Wacana

Classification of economic journal articles has been done using the VSM (Vector Space Model) approach and the Cosine Similarity method. The results of previous studies are considered to be less optimal because Stopword Removal was carried out by using a dictionary of basic words (tuning). Therefore, the omitted words limited to only basic words. This study shows the improved performance accuracy of the Cosine Similarity method using frequency-based Stopword Removal. The reason is because the term with a certain frequency is assumed to be an insignificant word and will give less relevant results. Performance testing of the Cosine Similarity method that had been added to frequency-based Stopword Removal was done by using K-fold Cross Validation. The method performance produced accuracy value for 64.28%, precision for 64.76 %, and recall for 65.26%. The execution time after pre-processing was 0, 05033 second.

Journal Unique Visitors Forecasting Based on Multivariate Attributes Using CNN Aderyan Reynaldi Fahrezza Dewandra; Aji Prasetya Wibawa; Utomo Pujianto; Agung Bella Putra Utama; Andrew Nafalski
International Journal of Artificial Intelligence Research Vol 6, No 2 (2022): Desember 2022
Publisher : International Journal of Artificial Intelligence Research

Forecasting is needed in various problems, one of which is forecasting electronic journals unique visitors. Although forecasting cannot produce very accurate predictions, using the proper method can reduce forecasting errors. In this research, forecasting is done using the Deep Learning method, which is often used to process two-dimensional data, namely convolutional neural network (CNN). One-dimensional CNN comes with 1D feature extraction suitable for forecasting 1D time-series problems. This study aims to determine the best architecture and increase the number of hidden layers and neurons on CNN forecasting results. In various architectural scenarios, CNN performance was measured using the root mean squared error (RMSE). Based on the study results, the best results were obtained with an RMSE value of 2.314 using an architecture of 2 hidden layers and 64 neurons in Model 1. Meanwhile, the significant effect of increasing the number of hidden layers on the RMSE value was only found in Model 1 using 64 or 256 neurons.

Co-Authors A.N. Afandi Abd. Rasyid Syamsuri Abdur Rohman Achmad Fanany Onnilita Gaffar Adaby, Resnu Wahyu Ade Kurnia Ganesh Akbari Aderyan Reynaldi Fahrezza Dewandra 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 Agung Bella Putra Utama Agus Purnomo 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 Alfiansyah Putra Pertama Triono Ali, Martina Alifah Diantebes Aindra Amro, Manar Y Anak Agung Istri Sri Wiadnyani 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 Anggreani, Desi Anik Nur Handayani Anton Prafanto Anusua Ghosh Anusua Ghosh, Anusua Ardiansyah, Mohammad Iqbal Firman Aripriharta - Arya Tandy Hermawan Ashar, Muhammad Astuti, Wistiani Atmaja, I Made Ari Dwi Suta Atmaja, Nimas Hadi 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 Cholisah Erman Hasihi Chong , Wan Ni Chuttur, Mohammad Yasser Citra Suardi Citra, Hana Rachma Collante, Leonel Hernandez Danang Arengga Wibowo Daniar Wahyu Darwis, Herdianti Dedi Kuswandi Dedy Kuswandi Denis Eka Cahyani Denna Delawanti Chrisyarani, Denna Delawanti Desi Anggreani 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 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 Fachrul Kurniawan Fachrul Kurniawan Fachrul Kurniawan Fadhilah, Farhan Fadhilla, Akhmad Fanny Fadhli Almu’iini Ahda Faidzin, Ilham Fajar Purnama Fajarwati, Erliana Faller, Erwin Faradini Usha Setyaputri Farid Miftahuddin Farida Nur Kumala Fauzan Cahya Arifin Fauzy Satrio Wibowo 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 Gianika Roman Sosa Graciello, Manuel Tanbica Gülsün Kurubacak Gunawan Gunawan Gwinny Tirza Rarastri Hammad, Jehad A. H. Hammad, Jehad A.H 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 Haviluddin Haviluddin Haviluddin, - Hendrawan, William Hartanto Herdianti Darwis Heri Pratikto Herman Herman 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 Ilham Mulya Putra Pradana Imansyah, Pranadya Bagus Imro’aturrozaniyah, Imro’aturrozaniyah Inggar Tri Agustin Mawarni Irsyada, Rahmat Islami, Pio Arfianova Fitrizky Islami, Pio Arfianova Fitrizky Islami, Pio Arfianova Fitrizky Ismail, Amelia Ritahani Istiqlal, Adib Izdihar, Zahra Nabila Jehad A. H. Hammad Jehad A.H. Hammad Jevri Tri Ardiansah Junoh, Ahmad Kadri Juwita Annisa Fauzi Juwita Annisa Fauzi Kaki, Gregorius Paulus Mario Laka Kasturi Kanchymalay, Kasturi Kelvin Wong Khafit Badrus Zaman Khen Dedes Khoiruddin Asfanie Khurin Nabila Kirya Mateeke Moses Kohei Arai Kurniawan, Fachrul Kurniawati, Fitriana Kuswandi, Dedy Laily Hidayah Langlang Gumilar Lauretta, Giovanny Cyntia Lazuardi Noorca Rachmadi Leonel Hernandez 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. Alfian Mizar M. Zainal Arifin 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 Ming F. Teng Ming Foey Teng Ming Foey Teng, Ming Foey Mochamad Hariadi 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 Nabila Izdihar, Zahra Nabila, Khurin Nada, Anita Qotrun Nadhiroh, Baitun Nadia Roosmalita Sari Nadia Roosmalita Sari Nafalski, Andrew Nastiti Susetyo Fanany Putri Naufal, Ayyub Naziro Nedic, Zorica Nida Jabari Ningsih, Eka Nurcahya Ningtyas, Yana Noorul Islam Novia Ratnasari Novian Candra Kurniawan Noviani, Erina Fika Nugraha, Agil Zaidan Nur Cahyo Wibowo Nur Hidayatullah Nurhalifah, Siti Nurroby Wahyu Saputra Nurul Falah Hashim Nurul Hidayat Oakley, Simon Okazaki Yasuhisa Oki Dwi Yuliana Omar, Saodah Osamu Fukuda Pakpahan, Herman Santoso Paramarta, Andien Khansa’a Iffat Paul Igunda Machumu Pio Arfianova Fitrizky Islami Piska Dwi Nurfadila 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 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 Riri Nada Devita Rizal Kholif Nurrohman Rizqini, Fajriwati Qoyyum Roni Herdianto Rosmin, Norzanah Rr. Poppy Puspitasari, Rr. Poppy Rully Charitas Indra Prahmana Ruth Ema Febrita Salahuddin, Lizawati Salsabila, Reni Fatrisna Santoso, Priyo Aji Saputra, Irzan Tri Sari, Nadia Roosmalita 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 Stamen Gadzhanov Subadra, ST. Ulfawanti Intan Sucahyo, Cornaldo Beliarding Sugiarto Cokrowibowo Sugiyanto - Suhiro Wongso Susilo Sujito Sujito 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 Tasrif Hasanuddin Trahutomo, Dinnuhoni 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 Vitrail Gloria Mairi 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, Nur Cahyo Widiharso, Prasetya Widiyanintyas, Triyanna Yandratama, Hengky Yasa, Arnelia Dwi Yingchi Mao Yongen Susman Yosi Kristian Yuliana, Oki Dwi Yuliawati, Pundhi Yuni Rahmawati Yusmanto, Yunan Zaeni, Ilham Ari Elbaith Zhou, Xiaofeng Zulkham Umar Rosyidin Zulkham Umar Rosyidin

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