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All Journal International Journal of Electrical and Computer Engineering IAES International Journal of Artificial Intelligence (IJ-AI) Jurnal Informatika Seminar Nasional Aplikasi Teknologi Informasi (SNATI) Jurnal Ilmu Komputer dan Informasi Jurnal Teknik ITS IPTEK Journal of Science IPTEK Journal of Proceedings Series IPTEK The Journal for Technology and Science Techno.Com: Jurnal Teknologi Informasi MATICS : Jurnal Ilmu Komputer dan Teknologi Informasi (Journal of Computer Science and Information Technology) Jurnal Buana Informatika TELKOMNIKA (Telecommunication Computing Electronics and Control) Bulletin of Electrical Engineering and Informatics JUTI: Jurnal Ilmiah Teknologi Informasi Jurnal Ilmiah Mikrotek Jurnal Simantec Jurnal Ilmiah Kursor Scan : Jurnal Teknologi Informasi dan Komunikasi Jurnal Teknologi Informasi dan Ilmu Komputer Jurnal Edukasi dan Penelitian Informatika (JEPIN) International Journal of Advances in Intelligent Informatics Scientific Journal of Informatics Journal of Information Systems Engineering and Business Intelligence Register: Jurnal Ilmiah Teknologi Sistem Informasi EMITTER International Journal of Engineering Technology Jurnal Inspiration Briliant: Jurnal Riset dan Konseptual Journal of Development Research Informatika Mulawarman: Jurnal Ilmiah Ilmu Komputer Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) International Journal of Artificial Intelligence Research Inform : Jurnal Ilmiah Bidang Teknologi Informasi dan Komunikasi INTEGER: Journal of Information Technology Seminar Nasional Teknologi Informasi Komunikasi dan Industri JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI Jurnal ULTIMATICS Explore IT : Jurnal Keilmuan dan Aplikasi Teknik Informatika Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI) CCIT (Creative Communication and Innovative Technology) Journal SPIRIT Progresif: Jurnal Ilmiah Komputer ILKOMNIKA: Journal of Computer Science and Applied Informatics Indonesian Journal of Electrical Engineering and Computer Science Journal of Intelligent Computing and Health Informatics (JICHI) Jurnal Teknik Informatika (JUTIF) Journal of Technology and Informatics (JoTI) Melek IT: Information Technology Journal Jurnal Nasional Teknik Elektro dan Teknologi Informasi Journal Research of Social Science, Economics, and Management Sewagati RESLAJ: Religion Education Social Laa Roiba Journal Jurnal Indonesia : Manajemen Informatika dan Komunikasi
Chastine Fatichah
Departemen Teknik Informatika Institut Teknologi Sepuluh Nopember Surabaya
Religion Arts Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Mathematics Mechanical Engineering Medicine & Pharmacology Public Health Social Sciences Other

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Exposure Fusion Framework in Deep Learning-Based Radiology Report Generator Hilya Tsaniya; Chastine Fatichah; Nanik Suciati
IPTEK The Journal for Technology and Science Vol 33, No 2 (2022)
Publisher : IPTEK, LPPM, Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j20882033.v33i2.13572

Abstract

Writing a radiology report is time-consuming and requires experienced radiologists. Hence a technology that could generate an automatic report would be beneficial. The key problem in developing an automated report-generating system is providing a coherent predictive text. To accomplish this, it is important to ensure the image has good quality so that the model can learn the parts of the image in interpreting, especially in medical images that tend to be noise-prone in the acquisition process. This research uses the Exposure Fusion Framework method to enhance the quality of medical images to increase the model performance in producing coherent predictive text. The model used is an encoder-decoder with visual feature extraction using a pre- trained ChexNet, Bidirectional Encoder Representation from Transformer (BERT) embedding for text feature, and Long-short Term Memory (LSTM) as a decoder. The model’s performance with EFF enhancement obtained a 7% better result than without enhancement processing using an evaluation value of Bilingual Evaluation Understudy (BLEU) with n-gram 4. It can be concluded that using the enhancement method effectively increases the model’s performance.
Feature Selection Using Hybrid Binary Grey Wolf Optimizer for Arabic Text Classification Muhammad Bahrul Subkhi; Chastine Fatichah; Agus Zainal Arifin
IPTEK The Journal for Technology and Science Vol 33, No 2 (2022)
Publisher : IPTEK, LPPM, Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j20882033.v33i2.13769

Abstract

Feature selection in Arabic text is a challenging task due to the complex and rich nature of Arabic. The feature selection requires solution quality, stability, conver- gence speed, and the ability to find the global optimal. This study proposes a feature selection method using the Hybrid Binary Gray Wolf Optimizer (HBGWO) for Ara- bic text classification. The HBGWO method combines the local search capabilities or exploratory of the BGWO and the search capabilities around the best solutions or exploits of the PSO. HBGWO method also combines SCA’s capabilities in finding global solutions. The data set used Arabic text from islambook.com, which consists of five Hadith books. The books selected five classes: Tauhid, Prayer, Zakat, Fasting, and Hajj. The results showed that the BGWO-PSO-SCA feature selection method with the fitness function search and classification method using SVM could per- form better on Arabic text classification problems. BGWO-PSO with fitness function and the classification method using SVM (C=1.0) gives a high accuracy value of 76.37% compared to without feature selection. The BGWO-PSO-SCA feature selec- tion method provides an accuracy value of 88.08%. This accuracy value is higher than the BGWO-PSO feature selection and other feature selection methods.
Modification of IDTCS Method for Touching Leukemia Cell Grouping Nenden Siti Fatonah; Chastine Fatichah; Handayani Tjandrasa
Journal Research of Social Science, Economics, and Management Vol. 1 No. 8 (2022): Journal Research of Social Science, Economics, and Management
Publisher : Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1955.032 KB) | DOI: 10.59141/jrssem.v1i8.136

Abstract

Morphological analysis and calculation of the number of white blood cells on microscopic images are stages in diagnosing leukemia. Constraints in developing a system for diagnosing leukemia are white blood cell segmentation and counting of the number single cells in touching cell. We propose to modify the Iterative Distance Transform For Convex Sets (IDTCS) method to separate the touching leukemia cells. The IDTCS method is used to determine markers for each cell in touching cells. The marker results from the IDTCS method are used as cell centroids and the next process is pixels clustering based on the nearest cell centroid using the euclidean distance function. The data used are microscopic images of Acute Lymphoblastic Leukemia (ALL). The experimental results show that using modified IDTCS method for clustering produces better accuracy compared to the K-Means clustering and Watershed methods.
Tajweed-YOLO: Object Detection Method for Tajweed by Applying HSV Color Model Augmentation on Mushaf Images Anisa Nur Azizah; Chastine Fatichah
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 7 No 2 (2023): April 2023
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v7i2.4739

Abstract

Tajweed is a basic knowledge of learning to read the Al-Qur’an correctly. Tajweed has many laws grouped into several parts so that only some people can memorize and implement Tajweed properly. Therefore, it is necessary to have an automatic detection system to facilitate the recognition of Tajweed, which can be used daily. This study presents Tajweed-YOLO, which applies the HSV color augmentation model to detect Tajweed objects in Mushaf images using YOLO. The contribution to this study was to compare the three versions of You Only Look Once (YOLO), i.e., YOLOv5, YOLOv6, and YOLOv7, and usage of the HSV color model augmentation to improve Tajweed detection performance. Comparing the three YOLO versions aims to solve problems in detecting small objects and recognizing various forms of Mushaf writing fonts in Tajweed detection. Meanwhile, the HSV color model aims to recognize Tajweed objects in various Mushaf and handle minority class problems. In this study, we collected four different Al-Qur’an mushaf with 10 Tajweed classes. The augmentation process can increase the detection performance by up to 85% compared to without augmentation 6th Class (Mad Jaiz Munfashil) using YOLOv6. The comparison of three YOLO versions concluded that YOLOv7 was better than YOLOv5 and YOLOv6, seen in data with augmentation and without augmentation. The evaluation results of mAP0.5 on 17 test data on the YOLOv7, YOLOv6, and YOLOv5 models are 80%, 69%, and 71%, respectively. These results prove that this research model’s results are suitable for the real-time detection of Tajweed.
Ultrasound Image Synthetic Generating Using Deep Convolution Generative Adversarial Network For Breast Cancer Identification Dina Zatusiva Haq; Chastine Fatichah
IPTEK The Journal for Technology and Science Vol 34, No 1 (2023)
Publisher : IPTEK, LPPM, Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j20882033.v34i1.14968

Abstract

Breast cancer is the leading cause of death in women worldwide; prevention of possible death from breast cancer can be decreased by early identification ultrasound image analysis by classifying ultrasound images into three classes (Normal, Benign, and Malignant), where the dataset used has imbalanced data. Imbalanced data cause the classification system only to recognize the majority class, so it is necessary to handle imbalanced data. In this study, imbalanced data can be handled by implementing the Deep Convolution Generative Adversarial Network (DCGAN) method as the addition of synthetic images to the training data. The DCGAN method generates synthetic images with feature learning on a Convolutional Neural Network (CNN), making DCGAN more stable than the basic generative adversarial network method. Synthetic and original images were further classified using the CNN GoogleNet method, which performs well in image classification and with reasonable computation cost. Synthetic ultrasound images were generated using a tuning hyperparameter in the DCGAN method to adjust the input size on GoogleNet for imbalanced data handling. From the experiment result, the implementation of DCGAN-GoogleNet has a higher accuracy in handling imbalanced data than conventional augmentation and other previous research, with an accuracy value reaching 91.61%, which is 1% to 4% higher than the accuracy value in the previous method.
Pemanfaatan E-commerce dan Media Sosial Guna Meningkatkan Ekonomi dan Proses Bisnis UMKM Koppontren NURILA Bangkalan Dini Adni Navastara; Nanik Suciati; Chastine Fatichah; Handayani Tjandrasa; Agus Zainal Arifin; Zakiya Azizah Cahyaningtyas; Yulia Niza; Evelyn Sierra; Daniel Sugianto; Kevin Christian Hadinata; Salim Bin Usman; Muhammad Fikri Sunandar; Fiqey Indriati Eka Sari
Sewagati Vol 6 No 4 (2022)
Publisher : Pusat Publikasi ITS

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (861.366 KB) | DOI: 10.12962/j26139960.v6i4.135

Abstract

Usaha Mikro, Kecil, dan Menengah (UMKM) memiliki peran yang besar dalam bidang industri dan ekonomi suatu negara. Di era digital ini, pemanfaatan teknologi untuk meningkatkan produktifitas UMKM sudah marak dilakukan. Sayangnya pemanfaatan tekonologi ini belum diterapkan pada UMKM dari Koperasi Pondok Pesantren Addimyathy Nurul Iman Labang (Koppontren NURILA). Tim pengabdi berinisiatif melaksanakan pelatihan untuk meningkatkan produktifitas UMKM Koppontren NURILA. Kegiatan terbagi menjadi empat tahap yaitu persiapan, pelatihan, pendampingan, dan evaluasi. Kegiatan ini mengangkat topik tentang pemanfaatan e-commerce dan media sosial untuk peningkatan ekonomi dan proses bisnis UMKM. Pelaksanaan pelatihan dan pendampingan dilakukan secara hybrid, yaitu daring dan luring di lokasi UMKM Koppontren NURILA. Berdasarkan hasil evaluasi, peserta kegiatan merasa puas terhadap kualitas materi dengan nilai 4.35 dari skala 5.
Pemanfaatan Platform Google Classroom untuk Pembelajaran Daring di Pondok Pesantren Miftahul Ulum Al-Islamy, Bangkalan, Madura Dini Adni Navastara; Nanik Suciati; Chastine Fatichah; Diana Purwitasari; Handayani Tjandrasa; Agus Zainal Arifin; Akwila Feliciano; Yulia Niza; Rangga Kusuma Dinata; Safhira Maharani; Ahmad Syauqi; Sherly Rosa Anggraeni; Fandy Kuncoro Adianto; Zakiya Azizah Cahyaningtyas; Salim Bin Usman; Kevin Christian Hadinata
Sewagati Vol 4 No 3 (2020)
Publisher : Pusat Publikasi ITS

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (269.198 KB)

Abstract

Proses pembelajaran daring menjadi hambatan tersendiri dalam bidang pendidikan, terlebih untuk pendidikan wajib yang harus dilakukan secara bertatap muka langsung antara pengajar dan pelajar. Di luar faktor permasalahan eksternal, permasalahan internal perlu diselesaikan terlebih dahulu, yaitu media pembelajaran. Salah satu platform digital yang tersedia sebagai media pembelajaran untuk menunjang pembelajaran secara daring adalah Google Classroom. Aplikasi Google Classroom berbasis web yang berbentuk pembelajaran asynchronous atau dapat dikatakan pemberian materi ajar dilakukan secara tidak langsung. Walaupun sebuah media daring sudah tersedia, masih ada yang belum mengenal atau memahami penggunaan aplikasi Google Classroom sebagai media ajar mereka. Oleh karena itu, kami mengadakan pengabdian masyarakat berupa pelatihan tentang penggunaan aplikasi Google Classroom bagi guru-guru di Pondok Pesantren Miftahul Ulum Al-Islamy, yang berada di Bangkalan, Madura. Selain itu, tim pengabdi juga melakukan pendampingan bagi guru-guru dalam mempraktikkan penggunaan Google Classroom sesuai dengan mata pelajaran yang diajar. Berdasarkan hasil survei, sebanyak 91% dari total peserta pelatihan menyebutkan bahwa pelatihan ini dapat meningkatkan pengetahuan dan kemampuan secara softskill dan hardskill para guru.
Framework Analysis Using The Rapid Evidence Assessment (REA) Method in Human Resources Information System Development Dhimas Pamungkas Wicaksono; Chastine Fatichah
IPTEK The Journal for Technology and Science Vol 34, No 1 (2023)
Publisher : IPTEK, LPPM, Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j20882033.v34i1.15740

Abstract

The framework application in the first phase of the Human Resources Information System (HRIS) development at X Company, which is a mining company, has so far been considered to have encountered many problems, with bugs and defects frequently being found that occurred when the project was deployed to a production environment. This happens due to frequent changes in project requirements in the middle of the development process, so many features become less relevant to business systems. So making decisions quickly and precisely before the first phase ends is necessary. The Rapid Evidence Assessment (REA) method was taken because it is a rapid review, which only a few weeks can decide based on field objective evidence. The use of a questionnaire involving project members was compared with the literature review results, namely that five aspects affected the time to develop: organizational aspects, process aspects, project aspects, people aspects, and technical aspects. The Scrum framework is a framework that is much more relevant to the current project conditions, with 3.6-point results and 3.1 points for the waterfall.
Combination of Cross Stage Partial Network and GhostNet with Spatial Pyramid Pooling on Yolov4 for Detection of Acute Lymphoblastic Leukemia Subtypes in Multi-Cell Blood Microscopic Image Mustaqim, Tanzilal; Fatichah, Chastine; Suciati, Nanik
Scientific Journal of Informatics Vol 9, No 2 (2022): November 2022
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v9i2.37350

Abstract

Purpose: Acute Lymphoblastic Leukemia (ALL) Detection with microscopic blood images can use a deep learning-based object detection model to localize and classify ALL cell subtypes. Previous studies only performed single cell-based detection objects or binary classification with leukemia and normal classes. Detection of ALL subtypes is crucial to support early diagnosis and treatment. Therefore, an object detection model is needed to detect ALL subtypes in multi-cell blood microscopic images.Methods: This study focuses on detecting the ALL subtype using YOLOV4 with a modified neck using Cross Stage Partial Network (CSPNet) and GhostNet. CSPNet is combined with Spatial Pyramid Pooling (SPP) to become SPPCSP to get various features map before the YOLOv4 final layer. Ghostnet was used to reduce the computation time of the modified YOLOV4 neck.Result: Experimental results show that YOLOv4 SPPCSP outperformed the recall value of 14.6%, the value of mAP@.5 0.8%, and reduced the computation time by 4.7 ms compared to the original YOLOv4.Novelty: The combination of CSPNet and GhostNet for YOLOV4 neck modification can increase the variety of features map and reduce computing time compared to the Original YOLOv4.
System of gender identification and age estimation from radiography: a review Nur Nafi’iyah; Chastine Fatichah; Darlis Herumurti; Eha Renwi Astuti; Ramadhan Hardani Putra; Esa Prakasa; Yosi Kristian
International Journal of Electrical and Computer Engineering (IJECE) Vol 13, No 5: October 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v13i5.pp5491-5500

Abstract

Under extreme conditions postmortem, dental radiography examinations can play an essential role in individual identification. In forensic odontology, individual identification traditionally compares antemortem dental records radiographs with those obtained on postmortem examination. As such, these traditional methods are vulnerable to oversights or mistakes in the individual identification of unidentified bodies. Digital technology can develop forensic odontology well. An automatic individual identification system is needed to support the forensic odontology process more easily and quickly because there are still opportunities to be created. We aimed to review the complete range of recent developments in identifying individuals from panoramic radiographs. We study methods in gender identification, age estimation, radiographic segmentation, performance analysis, and promising future directions.
Co-Authors Achmad Arwan Adhi Nurilham Aditya Bagusmulya Afrizal Laksita Akbar Agung Prasetya Agus Subhan Akbar, Agus Subhan Agus Zainal Arifin Agus Zainal Arifin Ahmad Hayam Brilian, Ahmad Hayam Ahmad Saikhu Ahmad Syauqi Ahmad Syauqi Aini, Nuru Ainul Mu'alif Akwila Feliciano Akwila Feliciano Al-Haddad, Abdullah Amalia Nurani Basyarah Amelia Devi Putri Ariyanto Amirullah Andi Bramantya Andika Pratama Andrea Bemantoro J Anisa Nur Azizah Anna Kholilah Anny Yuniarti Ardian Yusuf Wicaksono Ariana Yunita Arianto Wibowo Arif Sanjani, Lukman Arijal Ibnu Jati Ario Bagus Nugroho Arya Yudhi Wijaya Asmawati, Diah Avin Maulana Ayu Ismi Hanifah Benny Afandi Bilqis Amaliah Budi Pangestu Cahyaningtyas, Zakiya Azizah Daniel Oranova Siahaan Daniel Sugianto Daniel Swanjaya Darlis Heru Murti Darlis Herumurti Davin Masasih Deni Sutaji Desmin Tuwohingide Dhimas Pamungkas Wicaksono Diana Purwitasari Diana Purwitasari Diema Hernyka Satyareni Dimas Ari Setyawan Dimas Renggana, Christiant Dini Adni Navastara, Dini Adni Djoko Purwanto Dwi Kristianto Dwi Taufik Hidayat edy susanto Eha Renwi Astuti Eka Prakarsa Mandyartha Eka Prakarsa Mandyartha Eko Prasetyo Esa Prakasa Evan Tanuwijaya Evelyn Sierra Evy Kamilah Ratnasari Fachrul Pralienka Bani Muhamad Fachrul Pralienka Bani Muhamad Faizin, Muhammad 'Arif Fajar, Aziz Fajrin, Ahmad Miftah Fandy Kuncoro Adianto Fandy Kuncoro Adianto Faried Effendy Fatonah, Nenden Siti FATRA NONGGALA PUTRA Febri Liantoni Febri Liantoni, Febri Fiqey Indriati Eka Sari Furqan Aliyuddien Ginardi, R.V. Hari Ginardi, Raden Venantius Hari Gou Koutaki Hadziq Fabroyir Handayani Tjandrasa Haniefardy, Addien Haq, Dina Zatusiva Hardika Khusnuliawati Hardika Khusnuliawati Hari Ginardi Hendra Mesra hidayat, dwi taufik Hilya Tsaniya Hilya Tsaniya Hisyam Syarif, Hisyam I Ketut Eddy Purnama Ilmi, Akhmad Bakhrul Imam Artha Kusuma Imamah Imamah Irzal Ahmad Sabilla Isye Arieshanti Ivan Agung Pandapotan Jayanti Yusmah Sari Johan Varian Alfa Keiichi Uchimura Kevin Christian Hadinata Kevin Christian Hadinata Kinana Syah Sulanjari Kinana Syah Sulanjari Kusuma, Irnayanti Dwi Kusuma, Selvia Ferdiana Lukman Hakim M Rahmat Widyanto M. Rahmat Widyanto Machfud, M. Mughniy Mambaul Izzi Martini Dwi Endah Susanti Maulani, Irham Maulidiya, Erika Mauridhi Hery Purnomo Moch Zawaruddin Abdullah Mohamad Anwar Syaefudin Muhamad, Fachrul Pralienka Bani Muhammad Bahrul Subkhi Muhammad Fikri Sunandar Muhammad Jerino Gorter Muhammad Meftah Mafazy Muhammad Muharrom Al Haromainy Muhtadin Mustika Mentari Mutmainnah Muchtar Nafiiyah, Nur Nanik Suciati Nanik Suciati Narandha Arya Ranggianto Nazarrudin, Ahmad Ricky Nur Hayatin Nur Nafi’iyah Nur Nafi’iyah Nurilham, Adhi Nurina Indah Kemalasari Nursanti Novi Arisa Nursuci Putri Husain Nurwijayanti nuzula, Muhammad Iqbal firdaus Pradany, Latifa Nurrachma Priambodo, Anas Rachmadi Putra, Ramadhan Hardani R Dimas Adityo R. Dimas Adityo R. V. Hari Ginardi R.V Hari Ginardi R.V. Hari Ginardi Rachmad Abdullah Rahayu, Putri Nur Ramadhan Rosihadi Perdana Ramadhani, Muhammad Rafi' Rangga Kusuma Dinata Rangga Kusuma Dinata Ratih Kartika Dewi Rendra Dwi Lingga P. Riduwan, Muhammad Riyanarto Sarno Rizal A Saputra Rizal A Saputra, Rizal A Rizal Setya Perdana Rizka Wakhidatus Sholikah Rizka Wakhidatus Sholikah, Rizka Wakhidatus Rizqa Raaiqa Bintana Rozi, Fahrur RR. Ella Evrita Hestiandari Rully Soelaiman Safhira Maharani Safhira Maharani Sahmanbanta Sinulingga Salim Bin Usman Salim Bin Usman Sambodho, Kriyo Santoso, Bagus Jati Sarimuddin, Sarimuddin Septiyan Andika Isanta Sherly Rosa Anggraeni Sherly Rosa Anggraeni Shofiya Syidada Siti Mutrofin Siti Mutrofin Siti Rochimah Stefani Tasya Hallatu Subali, Made Agus Putra Subhan Nooriansyah Subkhi, M. Bahrul Sudianjaya, Nella Rosa Suhariyanto Suhariyanto Surya Sumpeno Syah Dia Putri Mustika Sari Sylvi Novita Dewi Tanzilal Mustaqim Tesa Eranti Putri Thoha Haq Tsaniya, Hilya Tuwohingide, Desmin Umi Laily Yuhana, Umi Laily Umy Rizqi Vit Zuraida Wahyu Saputra, Vriza Welly Setiawan Limantoro Wibowo, Prasetyo Wijoyo, Satrio Hadi Wilda Imama Sabilla Yoga Yustiawan Yosi Kristian Yudhi Purwananto Yuhana, Umi Laili Yuita Arum Sari Yulia Niza Yulia Niza Yunan Helmi Mahendra Yuslena Sari, Yuslena Yuwanda Purnamasari Pasrun Zaenal Arifin, Agus Zakiya Azizah Cahyaningtyas Zakiya Azizah Cahyaningtyas Zeng, Xinyou