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All Journal Semantik TELKOMNIKA (Telecommunication Computing Electronics and Control) Jurnal Ilmiah Kursor Jurnal Teknologi Informasi dan Ilmu Komputer Pro Bisnis Telematika Sistemasi: Jurnal Sistem Informasi JOIV : International Journal on Informatics Visualization Jurnal Pilar Nusa Mandiri JITK (Jurnal Ilmu Pengetahuan dan Komputer) SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan ILKOM Jurnal Ilmiah Jurnal Tekno Insentif JURTEKSI Jurnal Teknologi Terpadu Building of Informatics, Technology and Science Indonesian Journal of Electrical Engineering and Computer Science Jurnal Teknik Informatika (JUTIF) JURPIKAT (Jurnal Pengabdian Kepada Masyarakat) Journal of Applied Data Sciences Jurnal Pendidikan dan Teknologi Indonesia JUSTIN (Jurnal Sistem dan Teknologi Informasi) Jurnal Algoritma Electronic Journal of Education, Social Economics and Technology Jurnal Informatika: Jurnal Pengembangan IT Journal of Informatics and Interactive Technology (JIITE) INJECT Interdisciplinary Journal of Communication Journal of Digital Market and Digital Currency
Fandy Setyo Utomo
Universitas AMIKOM Purwokerto
Religion Agriculture, Biological Sciences & Forestry Arts Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Medicine & Pharmacology Nursing Public Health Social Sciences Veterinary Other

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Comparative Analysis of ArUco Marker Detection Techniques Using Adaptive Thresholding, CLAHE, and Kalman Filter for Smart Cane Applications Yulianto, Koko Edy; Saputro, Rujianto Eko; Utomo, Fandy Setyo
Jurnal Teknik Informatika (Jutif) Vol. 6 No. 4 (2025): JUTIF Volume 6, Number 4, Agustus 2025
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2025.6.4.4883

Abstract

This study aims to analyze and compare the effectiveness of three image processing techniques  Adaptive Thresholding, CLAHE, and Kalman Filter in enhancing the performance of ArUco marker detection for a smart cane system designed for visually impaired individuals at SLB Kuncup Mas Banyumas. The evaluation method includes detection accuracy, marker position precision, and computational time required by each technique under two different lighting conditions: daytime and nighttime. The results show that all three image processing techniques successfully achieved a 100% detection accuracy for ArUco markers. However, significant differences were observed in computational time, with Kalman Filter demonstrating the fastest processing speed, making it the most efficient option for real-time applications requiring quick response. CLAHE and Adaptive Thresholding performed better in uneven lighting conditions, although they required longer computational times. Kalman Filter is therefore recommended for marker-based navigation systems in environments demanding fast response times, while CLAHE and Adaptive Thresholding are better suited for settings with variable lighting intensities. The implications of these findings open opportunities for developing adaptive navigation systems capable of dynamically adjusting image preprocessing methods based on real-time environmental conditions. This study contributes practically to the advancement of assistive navigation technologies for visually impaired individuals, particularly in the development of visual marker-based detection systems. The results also provide a useful guideline for selecting appropriate image processing techniques according to environmental characteristics, thereby improving the accuracy and adaptability of navigation systems across diverse lighting conditions and operational environments.
Lightweight Visual Detection System for Object Identification with ArUco Markers in Resource-Constrained Environments Yulianto, Koko Edy; Saputro, Rujianto Eko; Utomo, Fandy Setyo
Electronic Journal of Education, Social Economics and Technology Vol 6, No 2 (2025)
Publisher : SAINTIS Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33122/ejeset.v6i2.757

Abstract

Object detection is a fundamental task in computer vision systems used in robotics, automation, and real-time tracking applications. However, implementing accurate and responsive detection on low-cost embedded hardware presents significant challenges due to limited processing power and environmental variability. This study aims to evaluate the performance of an object detection system utilizing ArUco markers on a Raspberry Pi-based platform. The research investigates the system’s ability to detect and identify three types of physical objects a plastic bottle, a flower pot, and a glass cup as well as the performance when all three objects are present simultaneously. The system was tested under controlled static conditions using a camera to capture real-time video streams. Detection time, computation time, and accuracy were measured across five consecutive frames for each scenario. Results show that the system achieved consistent detection and processing times below 0.14 seconds per frame, meeting real-time performance criteria. Detection accuracy across all individual object scenarios exceeded 91%, with the highest accuracy recorded in the multi-object scenario at 93.44%. No detection failures occurred during the experiments, and frame-by-frame analysis confirmed temporal stability. These findings indicate that marker-based detection is a reliable and efficient approach for real-time applications in structured environments. The study provides a foundation for extending the system to more dynamic conditions in future research.
Enhancing Customer Purchase Behavior Prediction Using PSO-Tuned Ensemble Machine Learning Models Kafilla, Princess Iqlima; Utomo, Fandy Setyo; Karyono, Giat
Jurnal Teknik Informatika (Jutif) Vol. 6 No. 5 (2025): JUTIF Volume 6, Number 5, Oktober 2025
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2025.6.5.4952

Abstract

Predicting customer purchase behavior remains a significant challenge in e-commerce and marketing analytics due to its complex and nonlinear patterns. This study introduces a machine learning framework that integrates ensemble learning models with Particle Swarm Optimization (PSO) for hyperparameter tuning to improve classification accuracy and class discrimination. Several ensemble algorithms, including CatBoost, XGBoost, LightGBM, AdaBoost, and Gradient Boosting, were compared against a baseline Logistic Regression model, both with default and PSO-optimized configurations. Experiments on a real-world e-commerce dataset containing behavioral and demographic variables showed that ensemble methods substantially outperformed traditional models across accuracy, F1-score, and ROC AUC metrics. Notably, the PSO-tuned Gradient Boosting model achieved the highest ROC AUC of 0.9547, improving the AUC by approximately 0.0076 compared to its default configuration, while CatBoost obtained the highest overall accuracy and F1-score. PSO optimization was especially effective in enhancing simpler models such as Logistic Regression but showed marginal gains and some convergence instability in more complex ensemble models. Feature importance analyses consistently identified variables such as time spent on the website, discounts availed, age, and income as key drivers of purchase intent. These findings demonstrate the benefit of combining ensemble learning with metaheuristic optimization, offering actionable insights for developing robust, data-driven marketing strategies.
Optimasi Klasifikasi Gaya Belajar Mahasiswa Inklusif Berdasarkan Model VAK dengan Stratified Split dan Multilayer Perceptron Kusuma, Velizha Sandy; Setyo Utomo, Fandy; Baihaqi, Wiga Maulana; Subarkah, Pungkas
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 12 No 5: Oktober 2025
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jtiik.2025125

Abstract

Identifikasi gaya belajar mahasiswa dengan mempertimbangkan fitur disabilitas memiliki peran penting dalam menciptakan pengalaman belajar yang inklusif dan personal. Namun, ketidakseimbangan data dalam kategori gaya belajar dan disabilitas menimbulkan tantangan yang signifikan bagi model klasifikasi. Penelitian ini bertujuan mengatasi tantangan tersebut dengan menerapkan teknik stratified split untuk menjaga keseimbangan distribusi kelas, khususnya pada variabel disabilitas dan gaya belajar. Algoritma Random Forest dan Multilayer Perceptron (MLP) digunakan untuk mengklasifikasikan gaya belajar mahasiswa berdasarkan model Visual, Auditory, dan Kinesthetic (VAK). Data yang digunakan berasal dari Open University Learning Analytics Dataset (OULAD), yang diproses melalui penggabungan data, pengkodean label, dan transformasi fitur untuk meningkatkan kinerja model. Evaluasi model dilakukan menggunakan metrik akurasi, presisi, recall, dan F1-score. Hasil penelitian menunjukkan bahwa model MLP mencapai kinerja sempurna dengan skor 100% pada semua metrik, sementara Random Forest menunjukkan performa sangat baik dengan skor 99%. Implementasi stratified split terbukti efektif dalam menjaga keseimbangan distribusi data, memastikan representasi yang memadai untuk semua kelas, termasuk mahasiswa dengan disabilitas. Penelitian ini memberikan kontribusi penting dalam mengembangkan model klasifikasi gaya belajar yang lebih akurat dan mendukung pendekatan pembelajaran yang lebih inklusif.   Abstract Identifying students' learning styles by considering disability features plays an important role in creating an inclusive and personalized learning experience. However, the imbalance of data in learning style and disability categories poses significant challenges for classification models. This research aims to overcome these challenges by applying a stratified split technique to maintain a balanced class distribution, especially in the disability and learning style variables. Random Forest and Multilayer Perceptron (MLP) algorithms are used to classify student learning styles based on the Visual, Auditory, and Kinesthetic (VAK) model. The data used comes from the Open University Learning Analytics Dataset (OULAD), which is processed through data merging, label coding, and feature transformation to improve model performance. Model evaluation was conducted using accuracy, precision, recall, and F1-score metrics. The results showed that the MLP model achieved perfect performance with a score of 100% on all metrics, while Random Forest showed excellent performance with a score of 99%. The implementation of stratified split proved effective in maintaining the balance of data distribution, ensuring adequate representation for all classes, including students with disabilities. This research makes an important contribution in developing more accurate learning style classification models and supporting more inclusive learning approaches.
Implementasi Simple Additive Weighting dan Weighted Product pada Sistem Pendukung Keputusan untuk Rekomendasi Penerima Beras Sejahtera Berlilana, Berlilana; Prayoga, Fandhi Dhuga; Utomo, Fandy Setyo
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 5 No 4: Agustus 2018
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (2428.333 KB) | DOI: 10.25126/jtiik.201854768

Abstract

Salah satu upaya pemerintah untuk mengatasi masalah kemiskinan di Indonesia yaitu membuat program beras sejahtera (RASTRA). RASTRA merupakan program dari pemerintah berupa bantuan beras bersubsidi untuk membantu masyarakat yang berpenghasilan rendah. Permasalahan yang terjadi yakni banyaknya kriteria penilaian yang digunakan dalam pedoman RASTRA dan penduduk miskin di suatu area/wilayah seringkali menyulitkan proses penentuan Keluarga Penerima Manfaat yang berhak menerima RASTRA pada Musyawarah desa/kecamatan. Tujuan penelitian ini adalah merancang dan mengembangkan sistem penunjang keputusan menggunakan model matematika Simple Additive Weighting (SAW) dan Weighted Product (WP) untuk memberikan rekomendasi penerima RASTRA. Terdapat empat tahapan penelitian yang digunakan untuk mencapai tujuan penelitian, yaitu analisis kebutuhan perangkat lunak, desain perangkat lunak, pengembangan, dan pengujian perangkat lunak. Berdasarkan hasil pengujian, hasil perhitungan nilai preferensi SAW memiliki performa yang lebih baik daripada WP karena SAW mampu meminimalisir nilai preferensi alternatif yang sama. Hal ini tampak dari perankingan alternatif berdasarkan hasil perhitungan SAW sejumlah 13 peringkat, dan WP sejumlah 10 peringkat. AbstractOne of the government's efforts to overcome the poverty problem in Indonesia is to make the program "Beras Sejahtera" (RASTRA). RASTRA is a government program of subsidised rice to help low-income communities. The problems which occur are the number of assessment criteria used in the RASTRA guidelines and the poor in an area/region often complicate the process of determining the Beneficiary Family who are eligible to receive RASTRA at the village/sub-district deliberation. The purpose of this research is to design and develop decision support system using Simple Additive Weighting (SAW) and Weighted Product (WP) mathematical model to give the recommendation of RASTRA recipient. There are four research stages to achieve the research objectives, namely software requirements analysis, software design, development, and software testing. Based on the test results, the calculation of SAW preference values has better performance than WP because SAW can minimise the value of the same alternative preferences. This can be seen from the alternative ranking based on the calculation of SAW of 13 ranks, and WP 10 rank number.
Pengembangan Media Pembelajaran Tata Surya berbasis Virtual Reality untuk Siswa Kelas 6 Sekolah Dasar dengan Evaluasi Kepuasan Pengguna terhadap Elemen Multimedia Purwati, Yuli; Sagita, Selvi; Utomo, Fandy Setyo; Baihaqi, Wiga Maulana
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 7 No 2: April 2020
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jtiik.2020701894

Abstract

Dalam studi ini, kami mengembangkan aplikasi virtual reality untuk mempelajari tata surya di tingkat sekolah dasar. Tujuan pembuatan aplikasi ini untuk menyediakan media pembelajaran berbasis multimedia bagi siswa agar dapat memahami konsep tata surya. Multimedia Development Life Cycle (MDLC) adalah tahap pengembangan sistem yang digunakan untuk membangun aplikasi virtual reality. MDLC terdiri dari tahapan konsep manufaktur, desain, pengumpulan bahan, perakitan, pengujian, dan distribusi. Hasil tes penerimaan pengguna yang dilakukan oleh satu orang guru pengampu menunjukkan hasil 81,25%, sedangkan yang dilakukan oleh 26 siswa menunjukkan hasil 88,63%. Berdasarkan hasil tes penerimaan oleh guru diperoleh saran perbaikan aplikasi pada sisi interaktifitas pengguna. Evaluasi kepuasan pengguna terhadap aplikasi dilakukan dengan kuesioner berdasarkan empat elemen multimedia: teks, interaktivitas, animasi, dan gambar grafis. Hasil evaluasi penggunaan teks memiliki nilai 3,57, grafik bernilai 3,52, animasi bernilai 3,54, dan interaktivitas memiliki nilai 3,51. Berdasarkan hasil tes, dapat disimpulkan bahwa responden puas dengan penggunaan elemen multimedia pada aplikasi tersebut, dan aplikasi tersebut dapat membantu mereka untuk memahami topik pembelajaran lebih baik daripada metode pembelajaran dan pengajaran konvensional. AbstractIn this study, we developed a virtual reality application for learning the solar system at the elementary school. The purpose of making this application is to provide multimedia-based learning media for students to be able to understand the concept of the solar system. Multimedia Development Life Cycle is a development stage of the system used to build virtual reality applications. MDLC consists of stages of the manufacturing concept, design, material collecting, assembly, testing, and distribution. Results of user acceptance test conducted by one teacher show the results of 81.25%, while that is done by 26 student shows the results of 88.63%. Based on the acceptance test results by the teacher, there are suggestions to improve the application on the user interactivity aspect. Evaluation of user satisfaction of the applications is done by a questionnaire based on the four elements of multimedia: text, interactivity, animation, and a graphical image. The result of the evaluation of the use of text has a value of 3.57, the graphic has a value of 3.52, animation has a value of 3.54, and interactivity has a value of 3.51. Based on the test results, it can be concluded that the respondents are satisfied with the use of multimedia elements on the application, and the application can help them to understand the learning topic better than conventional methods of learning dan teaching.
Windows Communication Foundation untuk Audiobook Dongeng bagi Anak Penyandang Tunanetra Purwati, Yuli; Utomo, Dadang Wahyu; Utomo, Fandy Setyo; Baihaqi, Wiga Maulana
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 7 No 2: April 2020
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jtiik.2020721943

Abstract

Anak penyandang tunanetra memiliki keterbatasan dalam mengakses informasi, hiburan, dan hal lain yang bisa diakses anak normal. Salah satu keterbatasan yang tidak mampu dilakukan oleh anak tersebut yakni membaca dongeng. Buku dongeng adalah salah satu yang dibutuhkan oleh anak untuk mengasah daya imajinasi dan kreatifitasnya. Buku dongeng biasanya dilengkapi dengan ilustrasi yang menarik untuk anak. Bagi anak penyandang tunanetra hal tersebut tidak bisa dilakukan. Mereka tidak dapat melihat gambar maupun tulisan di dalam buku dongeng. Namun mereka masih dapat mendengar cerita dongeng dari orang lain. Membaca dongeng membutuhkan ketrampilan khusus karena tidak hanya sekedar membaca tapi juga mengilustrasikan gambar dan teks di buku dongeng sesuai cerita dan karakter dari tokoh-tokoh yang ada di dalam buku sehingga anak seolah-olah masuk dalam cerita di buku tersebut meskipun mereka tidak melihat gambar yang ada di buku. Penelitian ini bertujuan merancang dan membangun Windows Communication Foundation untuk aplikasi Audiobook dongeng agar dapat dimanfaatkan oleh anak penyandang tunanetra. Penelitian ini dilakukan dengan 3 tahapan, yaitu analisis sistem, desain sistem, serta implementasi dan pengujian sistem. Hasil riset ini adalah perangkat lunak Windows Communication Foundation dengan 3 layanan, yakni layanan untuk menambah data audio dongeng, layanan untuk memilih dan memutar audio dongeng, dan layanan untuk melihat daftar audio dongeng. Berdasarkan hasil pengujian terhadap Windows Communication Foundation, seluruh layanan tersebut telah berfungsi dengan baik. AbstractChildren with visual impairments have limitations in accessing information, entertainment, and other things that can be accessed by normal children. One of the limits that cannot be done by the child is reading a fairy tale. A fairy tale book is one that is needed by children to hone their usability and creativity. A fairy tale book that is usually equipped with exciting illustrations for children. For children with visual impairments, this cannot be done. They cannot see pictures or writings in fairy tales books. But they can still hear tales from other people. Reading a fairy tale needs special skills such as how to read it aloud and how to illustrate pictures and texts in a fairytale book according to the stories and characters in it. Children might feel that they are involved in the story even though they could not see the picture given. The purpose of the research is to design and to develop Windows Communication Foundation for the fairytale Audiobook application to be used by children with visual impairments. This research was conducted in 3 stages, namely system analysis, system design, and system implementation and testing. The results of this study are Windows Communication Foundation software with three services, namely services to add audio data tales, services to select and play tale audio, and services to view a list of fairy tales audio. To conclude, the result of testing of the Windows Communication Foundation shows that all these services have been well equipped.
Sales Data Visualization to Determine Business Insight Using Metabase in a Global Retail Company Utomo, Fandy Setyo; Lubna, Zuhriyatul
Sistemasi: Jurnal Sistem Informasi Vol 13, No 4 (2024): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v13i4.3870

Abstract

In the era of dynamic business globalization, sales data analysis and visualization are key to strategic decision making. The application of Metabase as the main tool for visualization and analysis of sales data in the context of global retail companies, especially in the online sales sector. XYZ Company became the subject of research with complex challenges in managing extensive and diverse sales data. Metabase was adopted as a solution to deal with this complexity, enabling the company to gain deep insights into sales trends, consumer preferences, and hidden growth opportunities. Data visualization, through Metabase, plays a key role in transforming complex information into easy-to-understand visual representations, helping analysts and business stakeholders spot important patterns and trends. Research results reveal patterns of concurrent product purchases, providing opportunities to increase sales through promotions or product bundling. The identification of product categories that customers are interested in within a single transaction provides important insights for stock management and marketing strategies. Analysis of customer gender preferences opens up opportunities to direct more specific marketing strategies, focusing on the majority of a particular gender. The resulting recommendations include increased promotion or bundling of frequently purchased products together, as well as implementation of more focused marketing strategies based on product category preferences and customer gender. This article aims to contribute to the scientific literature on the practical application of data visualization in the context of sales analysis, with a focus on developing effective business decisions and marketing strategies.
ALGORITMA NAÏVE BAYES UNTUK ANALISIS SENTIMENT REVIEW BLIBLI.COM DI GOOGLE PLAY STORE Fadhilah, Siti Nur; Utomo, Fandy Setyo
Sistemasi: Jurnal Sistem Informasi Vol 13, No 2 (2024): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v13i2.3887

Abstract

Currently, there are approximately 354 million active mobile phones in Indonesia, placing the country fourth globally in terms of the highest number of mobile phone users. E-Commerce, as a form of online transaction, enables the digital exchange of goods and services to meet daily needs. This research aims to implement sentiment analysis using the Naive Bayes classification algorithm as a method to gather user opinions. Thus, the study not only provides insights into customer satisfaction with Blibli.com but also serves as a basis for potential improvements in services or feature development to enhance the online shopping experience. Overall, the Naive Bayes algorithm successfully achieved an accuracy of around 84%, demonstrating its proficiency in categorizing sentiment in reviews. When focusing on negative data, the Naive Bayes algorithm exhibited a precision of approximately 79%, recall of around 95%, and an f1-score of about 86%, indicating its success in identifying and classifying negative reviews with high precision and sensitivity. On the positive side, the Naive Bayes algorithm achieved a precision of about 91%, recall of around 83%, and an f1-score of about 87%.
Spearman Rank Correlation Analysis to Assess Satisfaction with Study Locations at Tadika CERIA Octavia, Annisa Suci; Utomo, Fandy Setyo
Sistemasi: Jurnal Sistem Informasi Vol 13, No 5 (2024): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v13i5.4375

Abstract

One of the activities that is routinely held during the learning process is filling out questionnaires by parents to determine the quality of Tadika CERIA education and services. The results of this questionnaire were then analyzed using the Spearman Rank Correlation method. This study aims to apply correlation analysis using Python to evaluate student satisfaction with the learning location at Tadika CERIA. Utilizing a dataset of survey responses that includes variables such as cleanliness, quality of teaching, and communication, analysis was conducted to identify key factors influencing student satisfaction. This approach not only shows the practical application of Python in data processing and statistical analysis, but also provides valuable insights for school administrators in improving the quality of the learning environment. The results show a positive correlation between certain aspects and student satisfaction, underscoring the importance of a deep understanding of student preferences and needs in the development of a conducive learning environment. This research makes an important contribution in the context of early childhood education, offering a foundation for further research in an effort to improve the holistic educational experience.
Co-Authors Adiya, Az Zahra Dwi Nur Afit Ajis Solihin Aisha Hukama Setyowati Aji Saeful Aji Septa, Adrian Ajis Solihin, Afit Amar Al Farizi Anas Nur Khafid Anggini, Melisa Anggraeni, Mutia Dwi Anggraini, Nova Anggriani, Epri Anies Indah Hariyanti Azhari Shouni Barkah Azmi, Mohd Sanusi Bagus Adhi Kusuma Bahari, Aris Ridky Setiya Baihaqi, Wiga Maulana Balit, Muhamad Naufal Burhanuddin Berlilana Berlilana Berlilana Burhanuddin Balit, Muhamad Naufal Churil Aeni, Agustina Chyntia Raras Ajeng Widiawati Chyntia Raras Ajeng Widiawati Darmono Dedi Purwanto, Dedi Didi Prasetyo Dwi Krisbiantoro, Dwi Dzaky Candy Fahrezy Fadhilah, Siti Nur Febriansyah Husni Adiatma Giat Karyono Giat Karyono Hanif Hidayatulloh Hendra Marcos, Hendra hidayatulloh, hanif Ilham, Rifqi Arifin Imam Tahyudin Indriyani, Ria Jamie Mayliana Alyza Kafilla, Princess Iqlima Kusuma, Bagus Adhi Kusuma, Velizha Sandy Lasmedi Afuan Lubna, Zuhriyatul Lukita, Dita Maulana Baihaqi, Wiga Mohd Fairuz Iskandar Othman Mohd Nazrin Muhammad Mohd Sanusi Azmi Muaziz, Imam Muhamad Naufal Burhanuddin Balit Muhtyas Yugi Murtiyoso Murtiyoso Nandang Hermanto Nanna Suryana Nikmah Trinarsih Nugroho, Khabib Adi Nur Cholis Romadhon Octavia, Annisa Suci Prayoga, Fandhi Dhuga Pungkas Subarkah Purbo, Yevi Septiray Purwidiantoro, Moch. Hari Pyawai, Hero Galuh R. Vitto Mahendra Putranto Ramadhan, Aziz Ramadhan, Rio Fadly Rifqi Arifin Ilham RR. Ella Evrita Hestiandari Rujianto Eko Saputro Sagita, Selvi Samsul Arifin Sarmini - Sarmini Sarmini Sarmini Sekhudin Sekhudin Setiabudi, Rizki Setiawan, Ito Shafira, Lulu Shendy Filanzi Slamet Widodo Sofa, Nur Sri Hartini Subarkah, Pungkas Sugianto, Dwi Suryana, Nanna Taqwa Hariguna Titi Safitri Maharani Trinarsih, Nikmah Turino, Turino Utomo, Dadang Wahyu Wahid, Arif Mu'amar Wibisono, Arif Cahyo Wiga Maulana Baihaqi Yuli Purwat Yuli Purwati Yuli Purwati Yulianto, Koko Edy