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All Journal Jurnal Sains dan Teknologi Jurnal Teknologi Informasi dan Ilmu Komputer International Journal of Advances in Intelligent Informatics Jurnas Nasional Teknologi dan Sistem Informasi ANDHARUPA Jurnal Informatika Jurnal Pilar Nusa Mandiri CogITo Smart Journal Indonesian Journal of Artificial Intelligence and Data Mining JITK (Jurnal Ilmu Pengetahuan dan Komputer) JMM (Jurnal Masyarakat Mandiri) JTAM (Jurnal Teori dan Aplikasi Matematika) SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan ILKOM Jurnal Ilmiah DoubleClick : Journal of Computer and Information Technology MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer JURTEKSI JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Jurnal Pengabdian Kepada Masyarakat MEMBANGUN NEGERI Building of Informatics, Technology and Science Infotekmesin Jurnal Teknologi Informasi dan Multimedia Seminar Nasional Teknologi Informasi Komunikasi dan Administrasi [SEMINASTIKA] Scientific Journal of Informatics JOURNAL OF INFORMATION SYSTEM MANAGEMENT (JOISM) JTIULM (Jurnal Teknologi Informasi Universitas Lambung Mangkurat) IJIIS: International Journal of Informatics and Information Systems Indonesian Journal of Data and Science JPMB: Jurnal Pemberdayaan Masyarakat Berkarakter Journal of Computer Networks, Architecture and High Performance Computing Jurnal Teknik Informatika (JUTIF) Teknika Society : Jurnal Pengabdian dan Pemberdayaan Masyarakat Journal of Technology and Informatics (JoTI) TIERS Information Technology Journal Decode: Jurnal Pendidikan Teknologi Informasi Indonesian Journal of Innovation Studies Jurnal Pengabdian Kepada Masyarakat Abdi Nusa Jurnal Ilmiah IT CIDA : Diseminasi Teknologi Informasi Jurnal Ilmiah Teknik Mesin, Elektro dan Komputer (JURITEK) Jurnal Pengabdian Mitra Masyarakat (JPMM) JOMPA ABDI: Jurnal Pengabdian Masyarakat Digital Transformation Technology (Digitech) ABDINE Jurnal Pengabdian Masyarakat Jurnal Krisnadana Bulletin of Social Informatics Theory and Application Jurnal Pengabdian Kepada Masyarakat Ceria Jurnal Medika: Medika Jurnal Pengabdian Kepada Masyarakat Bersinergi Inovatif Prosiding Seminar Nasional Pemberdayaan Masyarakat (SENDAMAS) TECHNOVATE Edu Komputika Journal Jurnal Informatika
Pungkas Subarkah
Universitas Amikom Purwokerto
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DESIGNING UI/UX FOR ELEMENTARY SCHOOL E-LEARNING USING DESIGN THINKING METHOD Anshari, Muhammad Rifqi; Kuncoro, Adam Prayogo; Subarkah, Pungkas
JURTEKSI (jurnal Teknologi dan Sistem Informasi) Vol. 10 No. 3 (2024): Juni 2024
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) STMIK Royal Kisaran

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33330/jurteksi.v10i3.3177

Abstract

Abstract: Advances in technology and the internet have an impact on various daily activities, including the teaching and learning process. E-learning facilitates flexible learning without being constrained by space and time constraints. With e-learning, subject matter can be delivered consistently and more standardly than conventional learning which depends on the conditions of the teacher or instructor. One school in Banjarnegara Regency faced problems with students who had difficulty in learning, especially English. The learning media owned is limited to package books only. Therefore, schools need to have media that can support the learning process to be more optimal. This study aims to design and test UI/UX e-learning designs that suit the needs of the school using the design thinking method. This UI/UX design is expected to be an effective solution to overcome the limitations of learning media and improve the quality of student learning. Before the UI/UX design is implemented into the system, this study also conducts testing of the UI/UX design to assess its feasibility. Testing using the SUS (System Usability Scale) method resulted in a value of 82 with grade B, so it can be concluded that the design developed in this study is feasible to be deployed into the system and further developed.             Keywords: E-learning; design thinking; system usability scale; UI/UX Abstrak: Kemajuan teknologi dan internet berdampak pada berbagai aktivitas sehari-hari, termasuk proses belajar-mengajar. E-learning memfasilitasi pembelajaran yang fleksibel tanpa terkendala oleh batasan ruang dan waktu. Dengan e-learning, materi pelajaran dapat disampaikan secara konsisten dan lebih standar dibandingkan pembelajaran konvensional yang bergantung pada kondisi guru atau instruktur. Salah satu sekolah di Kabupaten Banjarnegara menghadapi permasalahan dengan peserta didik yang kesulitan dalam pembelajaran, khususnya bahasa Inggris. Media pembelajaran yang dimiliki terbatas hanya pada buku paket saja. Oleh karena itu, sekolah perlu memiliki media yang dapat menunjang proses pembelajaran agar lebih optimal. Penelitian ini bertujuan untuk merancang dan menguji desain UI/UX e-learning yang sesuai dengan kebutuhan sekolah tersebut menggunakan metode design thinking. Desain UI/UX ini diharapkan dapat menjadi solusi efektif untuk mengatasi keterbatasan media pembelajaran dan meningkatkan kualitas belajar siswa. Sebelum desain UI/UX diterapkan ke dalam sistem, penelitian ini juga melakukan pengujian terhadap desain UI/UX untuk menilai kelayakannya. Pengujian menggunakan metode SUS (System Usability Scale) menghasilkan nilai 82 dengan grade B, sehingga dapat disimpulkan bahwa desain yang dikembangkan dalam penelitian ini layak untuk dideploy ke dalam sistem dan dikembangkan lebih lanjut. Kata kunci: E-learning; design thinking; system usability scale; UI/UX 
OPTIMIZATION OF CART ALGORITHM BASED ON ANT BE COLONY FEATURE SELECTION FOR STUNTING DIAGNOSIS Subarkah, Pungkas; Ikhsan, Ali Nur; Wahyudi, Rizki; Rofiqoh, Dayana
JURTEKSI (jurnal Teknologi dan Sistem Informasi) Vol. 11 No. 2 (2025): Maret 2025
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) STMIK Royal Kisaran

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33330/jurteksi.v11i2.3579

Abstract

Abstract: One of the main health problems in children is stunting which is one of the concerns in the Sustainable Development Goals (SDGs). Specifically in Indonesia, the prevalence of stunting in 2024 is 21.6%. This figure is still relatively high, because the target prevalence of stunting is 14%. This study aims to implement machine learning knowledge through the Classification And Regression Trees (CART) algorithm based on Ant Be Colony (ABC) feature selection which aims to determine the increase in accuracy in analyzing stunting datasets. The data used comes from Kaggle which consists of 16500 datasets. The dataset consists of gender, age, birth length, birth weight, body length, body weight, breastfeeding and stunting status. The research methods used are data collection, data preprocessing, classification, and evaluation using K-fold cross validation. The results obtained in this research are the implementation of the CART algorithm obtained a value of 89.86% and the results of CART with Ant Be Colony (ABC) feature selection, which obtained an accuracy value of 93.65%. This shows that there is an increase in the accuracy value in the use of CART algorithm optimization and Ant Be Colony (ABC) feature selection by 3.76%. With the research results that have been obtained, it can be categorized as excellent accuracy value excellent. It is hoped that further research can be carried out by adding other classification algorithms or adding feature selection.            Keywords: classification; feature selection; optimazation; stunting Abstrak: Salah satu masalah kesehatan utama pada anak adalah stunting yang menjadi salah satu perhatian dalam Sustainable Development Goals (SDGs). Khusus di Indonesia angka Pravelensi stunting pada tahun 2024 di angka 21.6%. Angka ini masih tergolong tinggi, karena target angka pravelensi stunting ialah 14%. Penelitian ini bertujuan untuk mengimplementasikan pengetahuan machine learning melalui algoritma Classification And Regression Trees (CART) berbasis seleksi fitur Ant Be Colony (ABC) yang bertujuan untuk mengetahui peningkatan akurasi dalam menganalisis dataset stunting. Data yang digunakan bersumber dari Kaggle yang terdiri dari 16500 dataset. Dataset terdiri dari jenis kelamin, usia, panjang lahir, berat lahir, panjangg badan, berat badan, menyusui dan status stunting.  Metode penelitian yang digunakan adalah pengumpulan data, preprocessing data, klasifikasi, dan evaluasi menggunakan K-fold cross validation. Hasil yang diperoleh pada penelitian ini adalah Implementasi algoritma CART memperoleh nilai sebesar 89,86% dan hasil seleksi fitur CART dengan Ant Be Colony (ABC) memperoleh nilai akurasi sebesar 93,65%. Hal ini menunjukkan adanya peningkatan nilai akurasi pada penggunaan optimasi algoritma CART dan pemilihan fitur Ant Be Colony (ABC) sebesar 3,76%. Dengan hasil penelitian yang telah diperoleh dapat dikategorikan nilai akurasi yang diperoleh sangat baik. Diharapkan dapat dilakukan penelitian selanjutnya dengan menambahkan algoritma klasifikasi lain atau menambahkan seleksi fitur. Kata kunci: klasifikasi; optimalisasi; seleksi fitur; stunting
Sentiment Perspective of Government's Free Nutritious Meal Policy on Social Media X using Indo-BERT and Bi-LTSM Subarkah, Pungkas; Ikhsan, Ali Nur; Anggraeni, Epri; Sabaniyah, Arbangi Puput
Journal of Technology and Informatics (JoTI) Vol. 7 No. 2 (2025): Vol. 7 N. 2 (2025)
Publisher : Universitas Dinamika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37802/joti.v7i2.1065

Abstract

This research has the potential to make an important contribution to the development of computationally-based sentiment analysis, especially in the context of government policies regarding the Free Meal Program that will be implemented throughout Indonesia. This research was conducted using Indo-BERT and Bi-LSTM algorithms. These approaches were used to categorize emotions into three groups: neutral, negative, and positive. Data is obtained from posts on social media X, then after processing the data, it will be applied to both algorithms, namely Indo-BERT and Bi-LSTM. The research findings show that the model's performance in determining the public sentiment of government policies. Validation and valuation were conducted using the f1 score, recall, and precision metrics. The evaluation findings show that the Indo-BERT algorithm is better than the Bi-LSTM algorithm with an accuracy value of 80% for Indo-BERT and 78% for the accuracy value of the Bi-LSTM algorithm, and the Indo-BERT accuracy value is included in the good classification accuracy value. The sentiment analysis results are also represented by word clouds for each positive, negative and neutral class, providing an intuitive picture of the words frequently used in public discourse on free nutritious meals.
Perancangan Aplikasi Bimbingan Karir Berbasis Website Job Journey Untuk Membantu Peserta Didik Merencanakan Karir Awali, Uston; Subarkah, Pungkas; Riyanto, Riyanto
Digital Transformation Technology Vol. 4 No. 1 (2024): Periode Maret 2024
Publisher : Information Technology and Science(ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/digitech.v4i1.3898

Abstract

Penelitian ini bertujuan untuk merancang fitur-fitur baru pada aplikasi bimbingan karir berbasis website, Job Journey, yang belum ada pada aplikasi bimbingan karir sebelumnya. Aplikasi ini diharapkan membantu siswa SMA dalam merencanakan karir mereka dengan lebih baik. Metode penelitian yang digunakan adalah model waterfall, yang meliputi tahapan analisis, desain, implementasi, pengujian, dan pemeliharaan. Fitur-fitur baru yang dikembangkan meliputi layanan konsultasi, mentoring, webinar, kelas online, informasi lowongan kerja, dan tes psikologi. Pengujian sistem dilakukan dengan metode Blackbox Testing untuk memastikan validitas dan kinerja sistem. Hasil pengujian menunjukkan bahwa fitur-fitur aplikasi berfungsi dengan baik sesuai dengan harapan. Aplikasi Job Journey berhasil memfasilitasi siswa dalam merencanakan karir mereka melalui interaksi langsung dengan profesional, memberikan wawasan dan nasihat dari para ahli, serta meningkatkan kesiapan mereka untuk memasuki dunia kerja. Selain itu, aplikasi ini memudahkan administrator dalam mengelola data pengguna, pembayaran, artikel, serta memantau perkembangan siswa dalam menggunakan layanan aplikasi. Kesimpulannya, Aplikasi Job Journey efektif dalam memenuhi kebutuhan perencanaan karir siswa dan memudahkan pengelolaan serta pemantauan layanan oleh administrator
ANALYSIS OF THE ACCEPTANCE OF THE SINAGA ATTENDANCE APPLICATION AT SMA NEGERI 1 JATILAWANG USING THE TECHNOLOGY ACCEPTANCE MODEL (TAM) Sabaniyah, Arbangi Puput; Yunita, Ika Romadhoni; Subarkah, Pungkas
JURTEKSI (jurnal Teknologi dan Sistem Informasi) Vol. 12 No. 1 (2025): Desember 2025
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) STMIK Royal Kisaran

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33330/jurteksi.v12i1.4205

Abstract

This study analyzes the acceptance of teachers and ASN employees of the SINAGA (Sistem Informasi Layanan Kepegawaian) attendance application at SMA Negeri 1 Jatilawang using a modified Technology Acceptance Model (TAM). The model was extended by incorporating two external variables: Information Quality and Complexity. This explanatory quantitative research employed the Structural Equation Modeling–Partial Least Square (SEM-PLS) method involving 60 respondents who are civil servants, consisting of teachers and administrative staff. The results reveal that Information Quality has a positive and significant influence on both Perceived Usefulness (PU) and Perceived Ease of Use (PEOU), while Complexity does not show a significant effect on either variable. Furthermore, PEOU and PU have a positive impact on Attitude Toward Use (ATU), which subsequently affects Behavioral Intention to Use (BIU). Behavioral intention, in turn, strongly influences Actual Use (AU). These findings indicate that teachers’ acceptance of the SINAGA digital attendance system in educational settings is primarily driven by information quality and users’ positive attitudes rather than by system complexity. Theoretically, this study contributes to the expansion of TAM application in the educational context. Practically, it provides valuable insights for improving the effectiveness of SINAGA implementation through better information quality and enhanced user experience.
Comparison of Naive Bayes and SVM in Public Opinion Sentiment Analysis on Platform X Salma Ngarifatul Khofiyah; Pungkas Subarkah
Jurnal Teknologi Informasi Universitas Lambung Mangkurat (JTIULM) Vol. 10 No. 2 (2025)
Publisher : Fakultas Teknik Universitas Lambung Mangkurat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20527/jtiulm.v10i2.478

Abstract

The growth of social media has made it the primary means for the general public to express their opinions, including on political and legal issues in Indonesia. One topic that has been widely discussed is the abolition of Tom Lembong and the amnesty granted to Hasto Kristiyanto by President Prabowo Subianto, which has garnered mixed public reactions on the X platform. The purpose of this study is to analyze public sentiment regarding current issues and compare the performance of two machine learning algorithms, Naïve Bayes and Support Vector Machine (SVM), to classify public opinion. Data was obtained through a crawling process of 3,003 tweets, followed by a preprocessing stage that included cleaning, case folding, slang normalization, tokenizing, stopword removal, and stemming. Next, a suitability analysis using the TF-IDF method was conducted before the data was processed by the two algorithms. The results showed that, of the 2,998 valid tweets, 78.6% of public opinion was negative and only 21.4% was positive, indicating a predominance of criticism of the issues discussed. When comparing the algorithms, SVM provided more accurate results with an accuracy rate of 78.66%, while Naïve Bayes only achieved 58%. This shows that SVM is more flexible in analyzing text data with a high level of complexity compared to Naïve Bayes.
Enhancing Waste Classification with MobileNetV2: Adding a Plastic Sachets Class for Sustainable Management Pritama, Argiyan Dwi; Sandy Kusuma, Velizha; Baihaqi, Wiga Maulana; Subarkah, Pungkas
Edu Komputika Journal Vol. 12 No. 1 (2025): Edu Komputika Journal
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/edukom.v12i1.18931

Abstract

The issue of waste management remains a critical concern due to its adverse impact on the environment. This research enhances a deep learning-based waste classification model by introducing a new class, namely plastic sachets, to broaden the classification scope and increase the model's relevance to waste types commonly found in the community. The dataset used is an extended version of a previous open-source dataset, comprising 2,968 images divided into seven classes. Data preprocessing steps include stratified data splitting, data augmentation to increase image diversity, and pixel normalization. The model adopts the MobileNetV2 architecture through a transfer learning approach, utilizing 2D Global Average Pooling and Dense layers with softmax activation for multi-class classification. Evaluation using precision, recall, and F1-score demonstrated strong performance, with an overall accuracy of 97%. While the model performs well across most classes, further improvement is needed for minority classes such as plastic sachets. This study highlights the promising potential of deep learning in supporting automated waste sorting to promote sustainable waste management practices in Indonesia.
Comparative Performance of Retrieval Augmented Generation Tourism Chatbots: Kinerja Komparatif Retrieval Augmented Generation pada Chatbot Pariwisata Farizi, Amar Al; Arsi, Primandani; Subarkah, Pungkas
Indonesian Journal of Innovation Studies Vol. 27 No. 1 (2026): January
Publisher : Universitas Muhammadiyah Sidoarjo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21070/ijins.v27i1.1836

Abstract

General Background: The rapid adoption of artificial intelligence in smart tourism has increased the use of contextual chatbots to deliver destination information efficiently. Specific Background: However, tourism chatbots based on Large Language Models frequently encounter information hallucination, reducing reliability when handling dynamic and local tourism data. Knowledge Gap: Existing studies mainly focus on rule-based or single-model chatbot implementations and provide limited comparative evaluation of Retrieval Augmented Generation configurations combining embedding models and Large Language Models. Aims: This study aims to comparatively evaluate multiple Retrieval Augmented Generation configurations to identify the most suitable combination for contextual tourism chatbots and to analyze differences between large multilingual and small monolingual embedding models using a local tourism dataset. Results: Experimental evaluation using data from 49 tourist destinations in Banyumas Regency shows that the Multilingual-E5-Large embedding model consistently achieves perfect Precision, Recall, and F1-Score across all tested Large Language Models. The combination of Multilingual-E5-Large and GPT-4.1-Mini demonstrates the most balanced performance, achieving a BERTScore F1 of 0.7515 with an average response time of 1.555 seconds. Novelty: This research provides a systematic comparative assessment of embedding capacity and Large Language Model selection within a unified Retrieval Augmented Generation framework for tourism chatbots. Implications: The findings offer practical guidance for selecting model configurations that ensure accurate retrieval, high-quality responses, and efficient system performance in contextual tourism information services. Highlights • Multilingual embedding models deliver consistently higher retrieval accuracy across all tested configurations• GPT-4.1-Mini produces the most balanced generative quality and response latency• Embedding model selection plays a more decisive role than language model variation Keywords Retrieval Augmented Generation; Tourism Chatbot; Large Language Model; Embedding Model; Comparative Evaluation
Analisis Kepuasan Pengguna Aplikasi Kehadiran Panda menggunakan Metode System Usability Scale (Studi Kasus: PT. Puskomedia Indonesia Kreatif) Damayanti, Aulia Shafira Tri; Yunita, Ika Romadoni; Subarkah, Pungkas
Jurnal Teknologi Informasi dan Multimedia Vol. 7 No. 4 (2025): November
Publisher : Sekawan Institut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35746/jtim.v7i4.511

Abstract

PT Puskomedia Indonesia Kreatif has developed the Panda Attendance Application, a digital technology system for village administration with a focus on the smooth flow of employee infor-mation. This application utilizes QR codes and GPS technology for the attendance or absence of village employees at registered coordinates. One of the issues at PT Puskomedia is that village operators face challenges such as needing to contact the PT Puskomedia system operator for manual attendance tracking, leading to a decline in users. Currently, there are various challenges in the use of the Panda Attendance Application by village government institutions. Several com-plaints have been raised by users regarding technical issues and unsatisfactory user experience. The purpose of this study is to evaluate the level of user acceptance of the Panda application. The method used to analyze user satisfaction is the System Usability Scale (SUS) method. The results of this study yielded a SUS score of 46.22, indicating a low category (Grade E), with a percentile rank of 10%, and classified as poor (Grade E). The nature (adjective) of the application falls into the “Poor” category, and the score of 46.22 places the application in the “Not Acceptable” catego-ry according to the level of acceptance. Recommendations for improvement from this analysis in-clude enhancing system stability and technical improvements such as accelerating the QR code reading process. Responding to user feedback and implementing these improvements is expected to enable the Panda attendance application to achieve a higher level of usability and gain better acceptance from users.
Analisis Perbandingan Metode TAM dan Metode UTAUT 2 dalam Mengukur Kesuksesan Penerapan SIMRS pada Rumah Sakit Wijaya Kusuma DKT Purwokerto Fiby Nur Afiana; Pungkas Subarkah; A. Kholil Hidayat
MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Vol. 19 No. 1 (2019)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/matrik.v19i1.432

Abstract

Guidelines regarding the development of health services by the community indirectly require the management and executors of health services to provide services in an optimal and professional manner. With the help of information systems, it is expected to help management to achieve improved health services. This study aims to analyze the success of the application of the Hospital Management Information System (SIMRS), especially the medical record information system applied at Wijaya Kusuma Hospital, DKT Purwokerto. The TAM and UTAUT 2 methods are used by several researchers to measure the success of the application of information systems based on the wishes of users / consumers in using information systems. The TAM method was developed to explain the behavior of information system users. Placing attitude factors and each user behavior with the construct. UTAUT 2 is a development of the previous method which aims to help companies / organizations to understand how the use of information technology in supporting company / organizational performance Comparison of the final results of both methods is done to determine the extent to which the success of information systems can be explained by the two analysis results. produced. The final result stated that a better method was used in the success of the hospital management information system at Wijaya Kusuma Hospital, DKT Purwokerto, namely the UTAUT 2 method because the UTAUT method was able to measure 2,109 while the TAM method only measured 1,782.
Co-Authors A. Kholil Hidayat Abdallah, Muhammad Marshal Adam Prayogo Kuncoro Adam Prayogo Kuncoro Adam Prayogo Kuncoro Adhimah, Laily Farkhah Aditya Permana, Reza Afifah, Erika Luthfi Akhmad Mustolih Ali Nur Ikhsan Alif Nur Fadilah Alifah Dafa Iftinani Alifian , Raditya Sani Alya Khansa Dzakkiyah Amin, M. Syaiful Amira Aida Rashifa Anggi Tri Dewi Septiani Anggraeni, Eling Sekar Anggraeni, Epri Anggraini, Nova Anshari, Muhammad Rifqi Anunggilarso, Luky Rafi Arbangi Puput Sabaniyah Arief Rachman Hakim Arsi, Primandani Astrida, Deuis Nur Aunillah, Puteri Johar Awal Rozaq, Hasri Akbar Awali, Uston Azhar Andika Putra Azhari Shouni Barkah Azizan Nurhakim Azzahra, Delia Oktaviana Bagus Adhi Kusuma Bagus Adhi Kusuma Baihaqi, Wiga Maulana Bryan Jerremia Katiandhago Budi Utami, Dias Ayu Busyro, Muhammad Chendri Irawan Satrio Nugroho Chyntia Raras Ajeng Widiawati Cindy Magnolia Damayanti, Aulia Shafira Tri Damayanti, Wenti Risma Darmo, Cahyo Pambudi Dava Patria Utama Dermawan, Riky Dimas Desi Riyanti Dewi Fortuna Dhanar Intan Surya Saputra Dias Ayu Budi Utami Dias Ayu Budi Utami, Dias Ayu Budi Didit Suhartono Dwi Krisbiantoro, Dwi Dwi Putra, Ruly Niko Elistiana, Khoerotul Melina Enggar Pri Pambudi Fadilah, Alif Nur Fandy Setyo Utomo Faridatun Nida Farizi, Amar Al Fiby Nur Afiana Fiby Nur Afiana Firmanda, Reza Arief Fitriya Maharani, Lulu Amnah Gina Cahya Utami Harun Alrasyid Hellik Hermawan Hendra Marcos Hendra Marcos, Hendra Hidayah, Debby Ummul hidayatulloh, hanif Ikhsan, Ali Nur Ilham, Fatah Iphang Prayoga Irfan Santiko Irma Damayanti Irma Darmayanti Isnaini, Khairunnisak Nur Isnaini, Khairunnisak Nur Jali Suhaman Katiandhago, Bryan Jerremia Khoerida, Nur Isnaeni Khofiyah, Salma Ngarifatul Kholifah Dwi Prasetyo Kartika, Nur Kisma, Atmaja Jalu Narendra Kusuma, Bagus Adhi Kusuma, Velizha Sandy Latifah Adi Triana Lestari, Tri Endah Widi Lestari, Vika Febri Luki Rafi Anuggilarso Maharani Kusuma Dewi Marlita, Reva Merliani, Nanda Nurisya Mohammad Imron Mohd Sanusi Azmi Muflikhatun, Siti Muhammad Marshal Abdallah Muhammad Ma’ruf Muhammad Rifqi Anshari Mustolih, Akhmad Nanda Nurisya Merliani Nandang Hermanto Nandang Hermanto Nasar Ghanim, Nadif Neta Tri Widiawati Nikmah Trinarsih Nur Hidayah, Septi Oktaviani Nur Isnaeni Khoerida Nuraini , Rema Sekar Nurul Hidayati Pramudya, Reyvaldo Shiva Prasetya, Eko Budi Prasetyo Kartika, Nur Kholifah Dwi Prastyadi Wibawa Rahayu Prastyadi Wibawa Rahayu Prayoga, Iphang Primandani Arsi Primandani Arsi Pritama, Argiyan Dwi Purba, Mariana Purwadi Ragil Wilujeng Ramadani, Nevita Cahaya Ranggi Praharaningtyas Aji Ratih Anggraeni Rayinda Maya Anjani Reza Aditya Permana Reza Aditya Permana Reza Arief Firmanda Riandini, Dini Riyanto Riyanto Riyanto Riyanto Riyanto Riyanto Rizki Sadewo Rizki Wahyudi Rofiqoh, Dayana Rohman, M. Abdul Romadoni, Nova Salma Rosana Fadilla Sari Rujianto Eko Saputro Sabaniyah, Arbangi Puput Sadewo, Rizki Salma Ngarifatul Khofiyah Salsabiela, Ayuni Sandy Kusuma, Velizha Saputra, Dhanar Sari, Rida Purnama Sarmini Sarmini Satrio Nugroho, Chendri Irawan Sekhudin Sekhudin Selamat, Siti Rahayu Septi Oktaviani Nur Hidayah Septi Oktaviani Nur Hidayah Septiana Putri, Refida Sholikhatin, Siti Alvi SITI ALVI SHOLIKHATIN Siti Alvi Solikhatin Siti Alvi Solikhatin Sugiarti Sugiarti Suhaman, Jali Susanto, Wachyu Dwi Syabani, Amin Syamsiar, Syamsiar Tarwoto, Tarwoto Tri Astuti Trian Damai Triana, Latifah Adi Tripustikasari, Eka Tripustikasari Umma, Rofiqul Utami, Melida Ratna Utomo, Anwar Tri V, Jay Wachyu Dwi Susanto Wahyu, Herta Tri Wanda Fitrianingsih Wenti Risma Damayanti Wenti Risma Damayanti Widiawati, Neta Tri Yuli Purwati Yunita, Ika Romadhoni Yunita, Ika Romadoni