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All Journal Jurnal Informatika Jurnal sistem informasi, Teknologi informasi dan komputer Jurnal Teknologi Informasi dan Ilmu Komputer Journal of Animation & Games Studies Fountain of Informatics Journal Jurnal Ilmiah KOMPUTASI Jurnal Pengabdian UntukMu NegeRI JOIV : International Journal on Informatics Visualization Journal of Information Technology and Computer Science Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Jurnal Eksplora Informatika JURTEKSI JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) PrimaryEdu - Journal of Primary Education Building of Informatics, Technology and Science Jutisi: Jurnal Ilmiah Teknik Informatika dan Sistem Informasi Jurnal Informatika dan Rekayasa Elektronik JATI (Jurnal Mahasiswa Teknik Informatika) JIKA (Jurnal Informatika) Infotek : Jurnal Informatika dan Teknologi Indonesian Journal of Cultural and Community Development Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Jurnal Teknik Informatika (JUTIF) Indonesian Journal of Innovation Studies Jurnal Nasional Teknik Elektro dan Teknologi Informasi Prosiding Seminar Nasional Teknik Elektro, Sistem Informasi, dan Teknik Informatika (SNESTIK) PELS (Procedia of Engineering and Life Science) Proceedings of The ICECRS Procedia of Social Sciences and Humanities Publikasi Pengabdian Masyarakat Komputer dan Teknologi (PUNDIMASKOT) JOINCS (Journal of Informatics, Network, and Computer Science) Jurnal Sistem Informasi Prosiding SEMNAS INOTEK (Seminar Nasional Inovasi Teknologi) Indonesian Journal of Applied Technology Journal of Technology and System Information Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen) Journal of Electrical Engineering Smatika Jurnal : STIKI Informatika Jurnal Academia Open
Yulian Findawati
Universitas Muhammadiyah Sidoarjo
Religion Arts Humanities Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Public Health Social Sciences Transportation

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Multi-label Aspect Dangerous Speech Classification Using Keyword-Driven Ensemble Classifier on Imbalanced Data Findawati, Yulian; Budi Raharjo, Agus; Adni Navastara, Dini; Yonathan, Vincent; Yatestha, Anak Agung; Purwitasari, Diana
JOIV : International Journal on Informatics Visualization Vol 9, No 4 (2025)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.9.4.3129

Abstract

This study aims to detect various aspects of dangerous speech on social media, particularly Twitter, which has the potential to incite violence and increase prejudice against specific communities. The research dataset includes tweets containing dangerous speech related to the Indonesian government from 2019 to 2022. Researchers manually labeled the data based on seven aspects of hazardous speech, including social and historical context, dehumanization, accusations in the mirror, threats against women/children, questioning in-group loyalty, and threats against groups. The study employs a multi-label classification method to handle these aspects, which appear simultaneously in a single text. The main challenges include data imbalance, ambiguity, and the informal language frequently appearing in tweets. This study introduces a Keyword-Driven Ensemble Classifier (KDEC), a new ensemble model that leverages the strengths of SVC, Logistic Regression, IndoBERTweet, and specific keyword lists for each label. Researchers designed KDEC based on the best results from machine learning and deep learning methods tested in this study. The research team tested the model on small and large datasets, conducting trials involving seven and four-label classifications. The results show that KDEC, with label reduction and keyword support, effectively addresses data imbalance, resolves label overlap, and achieves 92% accuracy for seven-label classification and 88% for four-label classification. The findings of this research are highly relevant for hate speech analysis across various platforms and languages, particularly in understanding context and conveyed messages. Additionally, this study provides valuable insights into managing harmful content in online government-related discussions. This method identifies dangerous speech on a larger scale and supports data-driven social media content regulation decision-making.
Implementasi Aplikasi Perpustakaan Mini Mandiri At-Taqwa Urangagung Sidoarjo Rahmawati, Yunianita; Findawati, Yulian; Indahyanti, Uce; Fitroni, Arif Senja
Jurnal Pengabdian UntukMu NegeRI Vol. 7 No. 1 (2023): Pengabdian Untuk Mu negeRI
Publisher : LPPM UMRI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/jpumri.v7i1.4830

Abstract

Perpustakaan Mini Mandiri At-Taqwa didirikan untuk memberikan bahan bacaan pada warga perumahan Bhayangkara pada khususnya dan warga sekitar perumahan pada umumnya. Pendataan buku dan anggota dilakukan secara manual sehingga dibutuhkan suatu aplikasi pendataan buku secara otomatis sehingga dibuatlah aplikasi Perpustakaan Mini Mandiri At-Taqwa. Fitur aplikasi ini diantaranya Input Kategori Buku, Input Data Buku, Input Data Anggota, Input Data Petugas, Cari Data Buku, dan Laporan Buku. Aplikasi ini dapat membantu pencatatan dan pencarian data buku, anggota, dan petugas secara otomatis.
Game Simulasi Wirausaha Berbasis Model Pembelajaran Eksperiensial Sebagai Alternatif Media Pembelajaran Di SMK Kelas XI Findawati, Yulian; ., Suprianto; Sumarmi, Wiwik
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 2 No 1: April 2015
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (890.461 KB) | DOI: 10.25126/jtiik.201521131

Abstract

AbstrakSalah satu model pembelajaran yang menarik dan kreatif yaitu model pembelajaran Game. Adapun game yang dimaksud adalah game  simulasi yang  disesuaikan dengan mata pelajaran kewirausahaan pada SMK kelas XI. Game simulasi wirausaha yang dibuat berupa  game berbasis model pembelajaran eksperiensial dimana game ini memberikan pengalaman bagi pemain game sebagai wirausahawan muda yang ingin mengembangkan usaha. Di dalam game ini  juga  disesuaikan dengan kurikulum SMK  kelas XI pada mata pelajaran kewirausahaan, dimana yang disimulasikan berupa pengalaman perijinan usaha, manajemen produksi , manajemen pemasaran, pencatatan transaksi keuangan dan pelayanan pelanggan. Pengujian  validasi  game simulasi dilakukan oleh ahli media ,ahli materi dan siswa menggunakan kuisioner. Dari pengujian yang dilakukan oleh ahli media, game simulasi ini  memiliki nilai sangat bagus pada keterbacaan tulisan teks, ketepatan ukuran huruf, ketepatan warna huruf, ketepatan jenis huruf, kejelasan tata letak gambar, kesesuaian tampilan, penempatan konten, ketepatan penggunaan tema, dan kualitas tampilan desain. Sedangkan berdasar   pengujian yang dilakukan oleh  ahli materi maka yang memiliki nilai baik yaitu pada poin kebenaran materi, kemenarikan materi, keruntutan materi, cakupan materi..Berdasarkan uji kelayakan yang diujikan kepada siswa maka Game simulasi ini mampu menarik siswa sebagai pengguna Game simulasi wirausaha di dalam memahami pembelajaran kewirausahaan pada SMK kelas XI.Kata Kunci : Game Simulasi, Wirausaha, Media pembelajaranAbstractOne model of learning interesting and creative the model of learning games. As for the game in question is a simulation game that is tailored to the subjects of entrepreneurship in vocational class XI. Entrepreneurial simulation game that is made in the form of experiential learning model based games where the game provides an experience for gamers as young entrepreneurs who want to develop business. Also in the game adapted to class XI vocational curriculum in the subjects of entrepreneurship, where a simulated form of experience in licensing, production management, marketing management, recording of financial transactions and customer service. Validation testing simulation games conducted by media experts, subject matter experts and students using a questionnaire. From the testing conducted by media experts, game simulation makes the value very good in readable text, the accuracy of the size of the font, color accuracy letters, accuracy typeface, clarity of image layout, the suitability of view, the placement of the content, the accuracy of the use of themes, and display quality design. While based on tests performed by the subject matter experts who have good grades, namely the truth of the material points, the attractiveness of the material, the material keruntutan, materi..Berdasarkan coverage feasibility test students tested in the simulation game is able to attract students as entrepreneurial simulation game users in understand entrepreneurial learning in vocational class XI.Keywords: Simulation Game, Entrepreneur, Media LearningAbstrakSalah satu model pembelajaran yang menarik dan kreatif yaitu model pembelajaran Game. Adapun game yang dimaksud adalah game  simulasi yang  disesuaikan dengan mata pelajaran kewirausahaan pada SMK kelas XI. Game simulasi wirausaha yang dibuat berupa  game berbasis model pembelajaran eksperiensial dimana game ini memberikan pengalaman bagi pemain game sebagai wirausahawan muda yang ingin mengembangkan usaha. Di dalam game ini  juga  disesuaikan dengan kurikulum SMK  kelas XI pada mata pelajaran kewirausahaan, dimana yang disimulasikan berupa pengalaman perijinan usaha, manajemen produksi , manajemen pemasaran, pencatatan transaksi keuangan dan pelayanan pelanggan. Pengujian  validasi  game simulasi dilakukan oleh ahli media ,ahli materi dan siswa menggunakan kuisioner. Dari pengujian yang dilakukan oleh ahli media, game simulasi ini  memiliki nilai sangat bagus pada keterbacaan tulisan teks, ketepatan ukuran huruf, ketepatan warna huruf, ketepatan jenis huruf, kejelasan tata letak gambar, kesesuaian tampilan, penempatan konten, ketepatan penggunaan tema, dan kualitas tampilan desain. Sedangkan berdasar   pengujian yang dilakukan oleh  ahli materi maka yang memiliki nilai baik yaitu pada poin kebenaran materi, kemenarikan materi, keruntutan materi, cakupan materi..Berdasarkan uji kelayakan yang diujikan kepada siswa maka Game simulasi ini mampu menarik siswa sebagai pengguna Game simulasi wirausaha di dalam memahami pembelajaran kewirausahaan pada SMK kelas XI.Kata Kunci : Game Simulasi, Wirausaha, Media pembelajaran AbstractOne model of learning interesting and creative the model of learning games. As for the game in question is a simulation game that is tailored to the subjects of entrepreneurship in vocational class XI. Entrepreneurial simulation game that is made in the form of experiential learning model based games where the game provides an experience for gamers as young entrepreneurs who want to develop business. Also in the game adapted to class XI vocational curriculum in the subjects of entrepreneurship, where a simulated form of experience in licensing, production management, marketing management, recording of financial transactions and customer service. Validation testing simulation games conducted by media experts, subject matter experts and students using a questionnaire. From the testing conducted by media experts, game simulation makes the value very good in readable text, the accuracy of the size of the font, color accuracy letters, accuracy typeface, clarity of image layout, the suitability of view, the placement of the content, the accuracy of the use of themes, and display quality design. While based on tests performed by the subject matter experts who have good grades, namely the truth of the material points, the attractiveness of the material, the material keruntutan, materi..Berdasarkan coverage feasibility test students tested in the simulation game is able to attract students as entrepreneurial simulation game users in understand entrepreneurial learning in vocational class XI.Keywords: Simulation Game, Entrepreneur, Media Learning
SENTIMENT ANALYSIS OF POST-COVID-19 INFLATION BASED ON TWITTER USING THE K-NEAREST NEIGHBOR AND SUPPORT VECTOR MACHINE CLASSIFICATION METHODS Ratih Puspitasari; Findawati, Yulian; Rosid, Mochamad Alfan
Jurnal Teknik Informatika (Jutif) Vol. 4 No. 4 (2023): JUTIF Volume 4, Number 4, August 2023
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2023.4.4.801

Abstract

The COVID-19 pandemic caused a crisis in global economic growth. The impact of injuries due to the COVID-19 pandemic has also caused price increases and an increase in the inflation rate. Inflation is a price increase caused by a certain factor so that it has an impact on the prices of nearby goods which increase the circulation of money in society to increase. Many people expressed their various opinions or criticisms of the post-COVID-19 price increase policy on social media, one of which was via Twitter. Sentiment analysis was carried out to see how public sentiment is towards the price increase policy after the COVID-19 pandemic, and these sentiments are combined into multiclasses, namely positive, negative and neutral sentiments. So that this sentiment can later be used as material for evaluation regarding the post-COVID-19 price increase policy. This study aims to see and compare the accuracy of the two classification methods, namely K-Nearest Neighbor (K-NN) and Support Vector Machine (SVM) in the sentiment classification process. The data used was 5989 tweets with the keywords ""Stuffets Go Up Post-Pandemic", "Fuel Goes Up", "Inflation 2022", "Covid19 Inflation", "Inflation Post-Pandemic" with a data collection period from August to October 2022. The data obtained then enter the text preprocessing stage before later entering the classification stage. The results obtained after carrying out the classification using the K-Nearest Neighbor (K-NN) and Support Vector Machine (SVM) methods show that the Support Vector Machine (SVM) method has a higher accuracy of 79%, while the K-Nearest Neighbor (K -NN) has an accuracy of 54%.
CLASSIFICATION OF VOCATIONAL HIGH SCHOOL GRADUATES' ABILITY IN INDUSTRY USING EXTREME GRADIENT BOOSTING (XGBOOST), RANDOM FOREST, AND LOGISTIC REGRESSION Agustiningsih, Afikah; Findawati, Yulian; Alnarus Kautsar, Irwan
Jurnal Teknik Informatika (Jutif) Vol. 4 No. 4 (2023): JUTIF Volume 4, Number 4, August 2023
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2023.4.4.945

Abstract

The education world is one of the main sources in producing Human Resources. Vocational High School (SMK) is one level of school that presents various majors that are ready to compete in the industrial world. Therefore, a school institution needs to have a system to determine the quality of education provided to students so that they can compete in the industrial world. This study designs a system that is capable of classifying SMK student graduates as an evaluation for the school institution. The goal is to enable the school to devise strategies for producing better student quality in the following year. There are four classes in this study, namely those who work, those who are not working yet, those who are in college, and those who are entrepreneurs. There are several stages in building the classification system, including pre-processing, processing, and evaluation. This research uses three machine learning algorithms, namely XGBoost, Random Forest, and Logistic Regression. The results of the three methods obtained a training score of 91.70%, a test score of 66.88%, and an accuracy score of 67% generated by the XGBoost algorithm. The Random Forest algorithm produced a training score of 97.36%, a test score of 68.71%, and an accuracy score of 67%. Meanwhile, Logistic Regression produced a training score of 51.14%, a test score of 50.43%, and an accuracy score of 50%.
TOPIC MODELING IN COVID-19 VACCINATION REFUSAL CASES USING LATENT DIRICHLET ALLOCATION AND LATENT SEMANTIC ANALYSIS Malihatin S, Ulfah; Findawati, Yulian; Indahyanti, Uce
Jurnal Teknik Informatika (Jutif) Vol. 4 No. 5 (2023): JUTIF Volume 4, Number 5, October 2023
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2023.4.5.951

Abstract

COVID -19 vaccination is a program provided by the Indonesian government to minimize the spread of the virus. The COVID-19 vaccination program in Indonesia goes hand in hand with issues that are circulating, causing controversy and rejection of vaccination on social media, especially Twitter. There are many factors that influence vaccine rejection on Twitter, to summarize frequently discussed topics and find out hidden topics, this study uses the Latent Dirichlet Allocation (LDA) and Latent Semantic Analysis (LSA) methods from 1797 Twitter scrapping data. Both models require a set of words that have been converted into a matrix, so before conducting LDA topic modeling, the dataset will undergo a bag of word (BOW) calculation. Meanwhile, in LSA topic modeling, the existing dataset will undergo word weighting of frequently occurring words using Term Frequency - Inverse Document Frequency (TF-IDF). This study was conducted to find and summarize hidden information in the form of frequently discussed topics, thus understanding public opinions related to the COVID -19 vaccination refusal case. LDA and LSA methods will display topics based on the probability and mathematical calculations of word occurrences in each topic in the document. The topics that appear will be further analyzed through coherence score by applying a limit of 20 topics to display the best value. Further modeling experiments are carried out to display topics through LDA and LSA models, this study takes 6 topics with the highest coherence values including the right of individuals to choose whether to be vaccinated or not (0.484607), the Ribka Tjiptaning controversy (0.473368), rejection of the COVID-19 vaccine by groups represented by public figures (0.463631), punishment for non-compliance in the form of fines (0.324924), and halal certification (0.312521).
Sarcasm Detection in News Headline Dataset with Ensemble Deep Learning Method: Deteksi Sarkasme Pada Dataset News Headline Dengan Metode Ensemble Deep Learning Mochamad Alfan Rosid; Siti Nur Haliza; Yulian Findawati; Uce Indahyanti
JOINCS (Journal of Informatics, Network, and Computer Science) Vol. 6 No. 2 (2023): November
Publisher : Universitas Muhammadiyah Sidoarjo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21070/joincs.v6i2.1628

Abstract

Sarcasm, a prevalent linguistic device, is frequently used in public discourse, often causing offence and distress to the listener. The complexity inherent in detecting sarcasm is a significant and ongoing challenge in the field of sentiment analysis research. The widespread use of this phenomenon in diverse conversational contexts further complicates its identification in data sets full of human interactions. Deficiencies in methodologies for distinguishing such statements adversely affect the performance of sentiment analysis, especially in distinguishing negative, positive or neutral sentiments. Inaccuracies in sarcasm detection can affect the classification results of sentiment analysis. Therefore, sentiment analysis seeks to categorise sarcastic sentences that, despite appearing positive, actually contain negative meanings. This research aims to build a deep learning ensemble stack model. The basic deep learning methods used are Bidirectional Gated Recurrent Unit (BiGRU) and Convolutional Neural Network (CNN). LightGBM is used to perform stack ensemble of deep learning methods. The dataset used comes from the Kaggle website and consists of English headlines. The findings show that the stack ensemble method outperforms BiGRU and CNN, evidenced by an accuracy rate of 91.2% and an F1 score of 90.2%. Therefore, from the above discussion, it can be concluded that the LightGBM method emerges as the optimal solution for sarcasm detection
Design of WEB Based Information System for Correspondence and Community Complaint Services [Perancangan Sistem Informasi Layanan Surat Menyurat dan Pengaduan Masyarakat Berbasis WEB] Dwi Cahyono, Qitfirul; Eviyanti, Ade; Intan Mauliana, Metatia; Findawati, Yulian
Journal of Technology and System Information Vol. 1 No. 1 (2024): January
Publisher : Indonesian Journal Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47134/jtsi.v1i1.2153

Abstract

Public services are very important for the government to see how much success it has in carrying out services to the community. Correspondence is very important in a village government, because it is a separate necessity for the community in managing files and also complaints which are activities that can help in realizing prosperity in a village. In this study the authors developed an information system to assist the community in managing letters to the government and making complaints so that the community does not need to come to the village government office. The author uses the CodeIgniter framework, the PHP programming language and the MySQL database in designing a correspondence information system. To carry out work on this article using the waterfall method because this method has structured stages in the design of this information system. This method begins with a needs analysis, system design, implementation, testing, maintenance.The result obtained in the user acceptance test get a total percentage of 73%.
Aplikasi IT Support Work Orders Berbasis Web Dalam Rangka Menuju Sidoarjo Smart City Aljunza, Marshal Sheva; Findawati, Yulian; Fitrani, Arif Senja; Kautsar, Irwan Alnarus
Infotek: Jurnal Informatika dan Teknologi Vol. 7 No. 1 (2024): Infotek : Jurnal Informatika dan Teknologi
Publisher : Fakultas Teknik Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/jit.v7i1.23920

Abstract

One important aspect in supporting the smart city concept is adequate information technology infrastructure. The Sidoarjo district government has made many innovations in making this happen, one of which is the construction of an intranet and internet network using fiber optics which is centered in the Data Center and managed by the Sidoarjo District Communication and Information Center. As a work unit in the field of ICT infrastructure and security at the Sidoarjo Regency Diskominfo, it is responsible for serving reports from the OPD (Regional Apparatus Organization) regarding intranet and internet network problems in the Sidoarjo regency environment. However, the reporting system used is still very simple and manual. The aim of this research is to design and build a web-based system that functions as a complaint, documenting work, and reporting handling related to intranet and internet network problems at the OPD in Sidoarjo Regency. In collecting data, this research used qualitative methods. Meanwhile, system development uses the System Development Life Cycle (SDLC) method with waterfall model, and uses Unified Modeling Language (UML) and Entity Relationship Diagram (ERD) as system modeling. This application was built using PHP with the CodeIgniter framework and MySQL. The results of this research show that the system makes it easier for related parties to make complaints, document work, and report handling.
Pengenalan Bahasa Isyarat Indonesia Dengan Algoritma YOLOv8 Berbasis Mobile Hidayah, Firmansyah Nur; Rahmawati, Yunianita; Findawati, Yulian; Azizah, Nuril Lutvi
Infotek: Jurnal Informatika dan Teknologi Vol. 8 No. 2 (2025): Infotek : Jurnal Informatika dan Teknologi
Publisher : Fakultas Teknik Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/jit.v8i2.30189

Abstract

Indonesian Sign Language (BISINDO) is the primary means of communication for deaf people in Indonesia, but the general public's understanding of BISINDO is still limited, thus hampering inclusive social interaction. To overcome this obstacle, the development of an artificial intelligence-based BISINDO detection system is a promising solution. One of the latest approaches is the utilization of the YOLOv8 algorithm, which is known to have advantages in real-time object detection with high accuracy and better model efficiency compared to previous versions. The BISINDO detection system using YOLOv8 is trained with image and video datasets of Hand gestures, so that it is able to recognize various BISINDO gestures in various lighting conditions and backgrounds. The main challenge in developing this system is the limited variety of datasets and image quality, so that more diverse data collection and optimization of model parameters are needed. Integration of supporting Augmented Reality (AR) and Transfer Learning technologies also has the potential to improve the learning experience and detection accuracy. Thus, the BISINDO detection system based on YOLOv8 is expected to expand communication access, increase public awareness of BISINDO, and support the realization of a more friendly and inclusive social environment for deaf people in Indonesia
Co-Authors A.A. Ketut Agung Cahyawan W Ade Eviyanti Ade Eviyanti Aditya Kurniawan Adni Navastara, Dini Agustiningsih, Afikah Ahmad Rizqi Efendi Aji, Bagas Prakoso Aldio Nur Samsi Alim, Kholqi Aljunza, Marshal Sheva Alnarus Kautsar, Irwan ardhi pradana Ari Setiawan Arif Senja Fitrani Arif Senja Fitroni Astutik, Ika Ratna Indra Budi Raharjo, Agus Cindy Cahyaning Astuti Diana Purwitasari Dwi Cahyono, Qitfirul Eni Fariyatul Fahyuni Erfina, Idha Maharani Ericka Sukma Putri Wilujeng Ericka Sukma Putri Wilujeng, Ericka Sukma Putri Firdausi Usqi Salsabilah Fitroni, Arif Senja Ganang Ganindra Aulia Akbar Hanafi, Rizal Hidayah, Firmansyah Nur Hindarto Ida Rindaningsih Ida Rindaningsih, Ida Idha Maharani Erfina Ika Ratna Indra Astutik Imron Hidayat Intan Mauliana, Metatia Irwan A. Kautsar Irwan Alnarus Kautsar Irwan Alnarus Kautsar Islam Al-Hazmi, Auliansyah Jihaan Anisa Mukti Kautsar, Irwan Alnanrus Khubro, Jamaluddin Jumadil Maghfiroh, Alfiah Malihatin S, Ulfah Malna, Intan Afriza Mardhatillah, Radhita Fitra Maulana, Mahardika Rafi maulana, Metatia intan Mauliana, Metatia Intan Mochamad Alfan Rosid Moh. Attar Jibran Mohammad Fadli Zaka Mohammad Suryawinata Muhamad Alfin Firdiansyah Muhammad Alfin Firdiansyah Muhammad Choir Ridho Azizi Muhammad Fedy Rifki Muhammad Hilal Hamdi Muhammad Sayyi Syeh Putradifa Muhammad Syafri Romadhon Nahariqi, Muhammad Iqbal Ni'matu Zahroh Nuril Lutvi Azizah Nurwijayanti Pangestu, Krisna Aji Pratama, Chandra Hary Puspitasari, Anastasya Nadia Putri, Dewi Melisa Ramadhan, Aldo Reghan Ratih Puspitasari Ratih Puspitasari Rizaldy, Moch Dimas Fahmi Rizky Fajar Ryandi Rohman Dijaya Rosid, Muhammad Alfan Saputra, Abhirama Senja Fitrani, Arif Septian Dwi Pratama Septian Dwi Pratama Setiawan Bagus Rustianto Setyaningsih, Yuni Siska Dyah Pertiwi Siti Nur Haliza Steven Owen Purnawan Suhendro Busono Sumarno , Sumarno Sumarno . Suprianto Supriyanto - Suryani, Siti Dwi Sutarman Taurusta, Cindy Uce Indahyanti Wiwik Dwi Hastuti Wiwik Sumarmi Yasinta, Aulia Nur Yatestha, Anak Agung Yonathan, Vincent Yunianita Rahmawati Yunianita Rahmawati, Yunianita Zaka, Mohammad Fadli