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All Journal MATICS : Jurnal Ilmu Komputer dan Teknologi Informasi (Journal of Computer Science and Information Technology) TELKOMNIKA (Telecommunication Computing Electronics and Control) Jurnal Teknologi Journal of Innovation and Applied Technology Journal of Environmental Engineering and Sustainable Technology Jurnal Teknologi Informasi dan Ilmu Komputer Habitat Jurnal Edukasi dan Penelitian Informatika (JEPIN) SMATIKA Journal of Information Technology and Computer Science Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer JAST : Jurnal Aplikasi Sains dan Teknologi Indonesian Journal of Applied Informatics International Journal of Engineering, Science and Information Technology J-Intech (Journal of Information and Technology) Journal of Innovative and Creativity IMPACTS: International Journal of Empowerment and Community Services Journal of Information Technology Jurnal Pengabdian Masyarakat Teknologi Informasi dan Informatika
Arief Andy Soebroto
Fakultas Ilmu Komputer , Universitas Brawijaya
Astronomy Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Social Sciences Transportation Other

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Sistem Informasi Profil Kelompok Pertanian Terpadu Berbasis Web dengan Integrated Farming (Studi Kasus: Desa Dawuhan, Malang) Arief Andy Soebroto; Nurul Hidayat; Rizal Setya Perdana; Indriati Indriati; Hendra Darmawan; Raihan Fikri Brilliansyach; Mohammad Ibnu; Nadhira Nurannisa; M Azka Obila Vasya
J-INTECH ( Journal of Information and Technology) Vol 12 No 02 (2024): J-Intech : Journal of Information and Technology
Publisher : LPPM STIKI MALANG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32664/j-intech.v12i02.1501

Abstract

Dawuhan Village in Poncokusumo District, Malang Regency, is an evolving village with significant potential in the livestock sector. However, livestock data management in this village is still done manually, facing various challenges such as limited access, data integrity issues, and time-consuming processes. To address these issues, this research aims to develop a Web-Based Integrated Livestock Group Profile Information System. The primary objectives of this study are to improve accessibility, streamline the livestock data management process, and enhance data accuracy and security. The system is designed using the Next.js framework, chosen for its ease of use and security in implementing authentication and authorization, as well as its capability for future integration. The research results show that the developed system functions according to the requirements, providing a more efficient platform, reducing errors, and enhancing the user experience for farmers involved in data management. The implementation of this system is expected to improve operational efficiency and livestock data management in Dawuhan Village comprehensively.
The Poncokusumo Village Information System In The Context Of Moving Towards A Digital Village Arief Andy Soebroto; Agi Putra Kharisma; Diva Kurnianingtyas; Syakirah Dwi Anisa; Charles Eugene; Annisa Indah Fitriani
Journal of Innovative and Creativity Vol. 6 No. 1 (2026)
Publisher : Fakultas Ilmu Pendidikan Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/joecy.v6i1.4956

Abstract

Manual administrative processes in Poncokusumo Village have long been a source of inefficiency, resulting in common problems such as service delays, restricted public access to information, and difficulties with data archiving. To tackle these issues, this study set out to analyze the impact of the Sistem Informasi Manajemen Desa/Kelurahan (SIMDEK) on the effectiveness of village administration. The research employed the Community-Based Participatory Action Research (CBPAR) method, utilizing a combination of questionnaires and the Wilcoxon test to assess the understanding of the SIMDEK website among village officials and residents. The primary goal was to see if the system could genuinely improve administrative efficiency and transparency. The findings from the data analysis were compelling. The study's results demonstrated that the SIMDEK training had a significant positive effect on improving the understanding of village residents. This was statistically confirmed by an Asymp. Sig (2-tailed) value that was smaller than the significance level α, which is the standard measure for statistical significance. Based on these outcomes, the conclusion is clear: the implementation of SIMDEK can markedly improve the speed of services, the accuracy of data processing, and the transparency of information within Poncokusumo Village. This study holds significant implications, providing a strong case for village governments to expand the use of SIMDEK. Doing so is not just a technological upgrade; it represents a strategic and necessary step toward the broader digital transformation of public services, ensuring a more responsive and accountable local government for the community.
An Expert System for Early Risk Diagnosis of Breast Cancer Using Fuzzy Mamdani and Case-Based Reasoning Rumahorbo, Cicilia Angelica; Arief Andy Soebroto; Putra Pandu Adikara; Diah Prabawati Retnani
Journal of Information Technology and Computer Science Vol. 10 No. 3: Desember 2025
Publisher : Faculty of Computer Science (FILKOM) Brawijaya University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jitecs.2025103854

Abstract

Breast cancer remains one of the leading causes of morbidity and mortality among women worldwide, making early detection essential to improve treatment outcomes. However, early-stage breast cancer symptoms are often subjective and non-specific, which complicates initial risk assessment. This study proposes an expert system for early breast cancer risk diagnosis by integrating Fuzzy Mamdani and Case-Based Reasoning (CBR). The Fuzzy Mamdani method is employed as the primary inference mechanism to model uncertainty in symptoms and risk factors using linguistic rules, while CBR is utilized as a decision support component by leveraging similarities with previously validated clinical cases. The dataset consists of 150 patient records, of which 123 cases are used as the case base and 27 cases are employed for system evaluation. Experimental results show that the proposed system achieves an accuracy of 92.59% compared to expert judgments. These findings indicate that the integration of Fuzzy Mamdani and Case-Based Reasoning provides an interpretable and adaptive approach for early breast cancer risk assessment and has potential as a screening support tool.  
Social Media-Based Nature Tourism Village Marketing Management Training Setiawan, Ari; Endah Emiarti; Pretty Diawati; Vera Selviana Adoe; Arief Andy Soebroto; Romanda Annas Amrullah; Farida Mony; Bioni Sena; Nurasiah; Alfry Aristo Jansen Sinlae
IMPACTS: International Journal of Empowerment and Community Services Vol. 4 No. 1 (2025)
Publisher : Faculty of Economics Universitas Sarjanawiyata Tamansiswa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30738/impacts.v4i1.21184

Abstract

ABSTRACT Purpose ­ Ngudal Tourism Village in Tawangmangu, Central Java, possesses high potential for nature-based tourism due to its scenic landscapes and cultural richness. However, its digital presence and promotional strategies remain limited. This community service program aimed to enhance the digital marketing capacity of local tourism stakeholders through social media-based training. Methods - Fifteen participants—including homestay owners, youth representatives, culinary business actors, and village officials—were trained in content creation, platform management, audience engagement, and digital branding. The training adopted a participatory approach involving workshops, simulations, and mentoring. Result and discussions - As a result, participants demonstrated significant improvements in digital literacy, with post-training assessments showing a 47% increase in knowledge. The village launched official Instagram, Facebook, and YouTube accounts, achieving over 300 organic followers and substantial content engagement within one month. Economic impacts included increased homestay bookings and product inquiries via social media. A digital task force was formed to ensure sustainability. Conclusion - This program illustrates the potential of social media as a transformative tool for rural tourism promotion and recommends replicating such models in other under-promoted villages to foster inclusive digital development.
Implementasi Algoritma Random Forest Untuk Prediksi Churn Pada Pelanggan Retail Online Anam, Muhammad Haris Khoirul; Kurnianingtyas, Diva; Soebroto, Arief Andy
Jurnal Pengembangan Teknologi dan Ilmu Komputer Vol 10 No 4 (2026): April 2026
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Studi ini menganalisis prediksi pelanggan yang akan berhenti berlangganan (churn) di ritel online untuk membantu perusahaan mengembangkan strategi retensi yang lebih tepat sasaran. Data yang digunakan adalah dataset berisi 1.000 catatan pelanggan ritel online dengan 14 variabel prediktor dan 1 variabel target (Target_Churn). Untuk memastikan data siap untuk pemodelan, dilakukan langkah pra-pemrosesan, termasuk pengecekan kualitas data, transformasi fitur kategorikal dengan one-hot encoding, dan standardisasi fitur numerik. Dataset kemudian dibagi menjadi data pelatihan dan pengujian dengan rasio 70:30 menggunakan pengambilan stratified sampling. Model klasifikasi dibangun menggunakan algoritma Random Forest, dan optimasi hyperparameter dilakukan menggunakan GridSearchCV dengan validasi silang 5-fold untuk mendapatkan konfigurasi terbaik. Hasil pengujian menunjukkan bahwa model mencapai akurasi 48,33% dan nilai AUC-ROC 0,4825, yang menunjukkan bahwa kemampuannya untuk membedakan antara kelas churn dan non-churn masih rendah pada dataset yang digunakan. Namun, analisis kepentingan fitur mengungkapkan bahwa faktor-faktor yang terkait dengan transaksi dan kepuasan pelanggan cenderung memiliki dampak yang lebih besar daripada karakteristik demografis. Kesimpulan dari penelitian ini adalah bahwa model Random Forest belum dapat memberikan prediksi churn yang andal pada dataset ini, dan oleh karena itu, diperlukan data yang lebih representatif, penyertaan karakteristik perilaku, atau pengujian metode lain untuk meningkatkan kinerja.
Penerapan Model Arsitektur UNet untuk Peningkatan Resolusi Spasial Curah Hujan di Wilayah Pulau Jawa Berbasis Data MSWEP Putri, Nurulita Purnama; Saputro, Adhi Harmoko; Prasetya, Ratih; Soebroto, Arief Andy
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 13 No 1: Februari 2026
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jtiik.2026131

Abstract

Pemodelan curah hujan dengan resolusi tinggi sangat penting untuk berbagai aplikasi meteorologi dan hidrologi, termasuk peringatan dini bencana, manajemen sumber daya air, dan perubahan iklim. Namun, data curah hujan dengan resolusi tinggi sering kali tidak tersedia atau terbatas dalam cakupan wilayah dan periode waktu tertentu. Oleh karena itu, metode downscaling berbasis deep learning dapat menjadi solusi untuk meningkatkan resolusi data curah hujan dengan akurasi yang lebih baik. Penelitian ini berfokus pada evaluasi arsitektur Convolutional Neural Network (CNN) yaitu U-Net dalam melakukan downscaling data curah hujan Multi-Source Weighted-Ensemble Precipitation (MSWEP) untuk wilayah Pulau Jawa. Tujuannya adalah untuk mengevaluasi efektivitas model U-Net dalam meningkatkan resolusi data curah hujan dari 0.2° ke 0.1°. Hasil evaluasi pada data testing menunjukkan bahwa U-Net memiliki performa lebih baik jika dibandingkan ResNet. U-Net menghasilkan RMSE 0.0168, MAE 0.0107, MSE 0.00028, dan R² 0.9919, sementara ResNet memiliki RMSE 0.0188, MAE 0.0122, MSE 0.00035, dan R² 0.9899. Dengan nilai kesalahan yang lebih kecil dan akurasi lebih tinggi, U-Net terbukti lebih unggul dalam menangkap pola data curah hujan. Penelitian ini menyimpulkan bahwa U-Net lebih unggul dalam meningkatkan resolusi data curah hujan dan lebih efisien dalam menangkap pola data, menjadikannya pilihan yang lebih baik untuk aplikasi downscaling curah hujan wilayah Pulau Jawa.   Abstract High-resolution rainfall modeling is crucial for various meteorological and hydrological applications, including disaster early warning systems, water resource management, and climate change analysis. However, high-resolution rainfall data are often unavailable or limited in spatial coverage and time periods. Therefore, deep learning-based downscaling methods can serve as a promising solution to enhance the resolution of rainfall data with improved accuracy. This study focuses on evaluating the performance of a Convolutional Neural Network (CNN) architecture, specifically U-Net, for downscaling Multi-Source Weighted-Ensemble Precipitation (MSWEP) data over the island of Java. The objective is to assess the effectiveness of the U-Net model in increasing the spatial resolution of rainfall data from 0.2° to 0.1°. Evaluation on the testing dataset shows that U-Net outperforms the ResNet model, achieving an RMSE of 0.0168, MAE of 0.0107, MSE of 0.00028, and R² of 0.9919, compared to ResNet’s RMSE of 0.0188, MAE of 0.0122, MSE of 0.00035, and R² of 0.9899. With lower error values and higher accuracy, U-Net demonstrates superior capability in capturing rainfall patterns. The findings of this study conclude that U-Net is more effective in enhancing rainfall data resolution and more efficient in learning spatial patterns, making it a better choice for rainfall downscaling applications over the Java region.
Performance Evaluation of Machine Learning and Deep Learning for Rainfall Forecasting Arief Andy Soebroto; Lily Montarcih Limantara; Wayan Firdaus Mahmudy; Moh. Sholichin; Nurul Hidayat; Agi Putra Kharisma
International Journal of Engineering, Science and Information Technology Vol 5, No 4 (2025)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v5i4.1179

Abstract

Climate change is a significant challenge for both humans and the environment, with its impacts increasingly felt across various regions of the world. The most evident consequence is the alteration of extreme weather patterns, which often lead to destructive and life-threatening natural disasters. Among these, extreme rainfall was the most damaging factor, frequently triggering floods. However, the increasing occurrence of related events outlined the urgent need for developing more accurate rainfall forecasting systems as a strategic measure for disaster risk reduction. This research adopted daily rainfall data from Samarinda City, collected between 2004 and 2012, to conduct prediction using both machine and deep learning methods. The implementation of machine learning methods, such as Support Vector Regression (SVR), enabled the model to learn from historical data and uncover complex patterns, resulting in accurate forecasts and improved adaptability to climate variability. Meanwhile, deep learning models, including Recurrent Neural Networks (RNN) and Long Short-Term Memory (LSTM), enhanced prediction performance by capturing more intricate and abstract data relationships. Performance evaluations conducted using Mean Absolute Error (MAE) and Mean Squared Error (MSE) showed that deep learning outperformed machine learning in accuracy. The LSTM model achieved the best performance, with loss values of 0.0482 and 0.0527 for MSE and MAE, respectively. The advantage of deep learning lies in its ability to build more complex models for handling non-linear problems and to learn data representations at various levels of abstraction, which has led to more accurate results. Furthermore, LSTM surpassed RNN by effectively overcoming the vanishing gradient issue, allowing for more stable and efficient training that led to superior predictive performance.
Pengembangan Sistem Investasi Pemasaran Budidaya Ternak Domba Berbasis Penguatan Managemen Peternakan Dengan Kearifan Lokal Soebroto, Arief Andy; Suryadi, Nanang; Surjowardojo, Puguh; Tarno, Hagus
DIMASLOKA: Jurnal Pengabdian Masyarakat Teknologi Informasi dan Informatika Vol 2 No 2 (2023): Juli
Publisher : Fakultas Ilmu Komputer Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/dimasloka.v2i2.21

Abstract

Salah satu tantangan peternak adalah rendahnya akses ke pembiayaan yang mudah dan murah. Seperti diketahui bahwa rasio kredit UMKM terhadap total kredit perbankan kurang dari 20 persen. Penyerapan KUR masih didominasi oleh sektor perdagangan (44,4%) sedangkan sektor pertanian, perternakan, perburuan, dan kehutanan di posisi kedua yaitu 30,1%. Selain problematika permodalan, maka juga perlu strategi lainnya dalam memperkuat UMKM, yaitu ada 5 pondasi. Lima pondasi adaptasi yang telah dijalankan di Tahun 2022 diantaranya, kemudahan akses pembiayaan, perluasan pasar dan digitalisasi, kemitraan, pendataan dan reformasi birokrasi. Modal, kemitraan dan pemarasan sangat memegang peranan penting dalam penguatan perekonomian UMKM. Hal ini sejalan dengan SDGs Indonesia 2030 dimana peningkatan kesejahteraan masyarakat desa untuk mengurangi kemiskinan, pekerjaan yang layak dan pertumbuhan ekonomi, infrastruktur, industri dan inovasi dan kemitraan untuk mencapai tujuan adalah empat (4) dari tujuh belas (17) kesepakatan bersama dalam Sustainable Development Goals (SDGs) pada tahun 2015. Desa Bumirejo Kecamatan Dampit Kabupaten Malang yang memiliki BUMDESA dan 700 peternak (farm) mempunyai prgram pemberdayaan UMKM sehingga perlu didukung dengan sistem permodalan dan pemasaran untuk meningkatkan kapasistas dan kualitas produksi. Salah satu solusi yang ditawarkan adalah melalui pengembangan sistem investasi pemasaran budidaya ternak domba berbasis penguatan managemen peternakan dengan kearifan lokal. Berbasis kearifan lokal karena budaya beternak dan budidaya hijauan pakan ternak sudah tersedia di lingkungan masyarakat desa. Sistem ini dikembangkan berbasis aplikasi web dengan pengguna adalah administrator dan umum. Peran administrator memberikan informasi terkini sedangkan umum adalah mengakses aplikasi untuk membaca informasi peluang investasi dan pemasaran yang ditawarkan.   Abstract One of the challenges for breeders is the lack of access to easy and inexpensive financing. As it is known that the ratio of MSME credit to total bank credit is less than 20 percent. KUR absorption was still dominated by the trade sector (44.4%) while the agriculture, livestock, hunting and disposal sectors were in second place at 30.1%. In addition to capital problems, other strategies are also needed to strengthen MSMEs, namely there are 5 ways. Five demanding conditions that have been implemented in 2022 include easy access to financing, market expansion and digitalization, partnerships, data collection and bureaucratic reform. Capital, partnerships and marketing play an important role in strengthening the MSME economy. This is in line with Indonesia's SDGs 2030 where increasing the welfare of rural communities to reduce poverty, decent work and economic growth, infrastructure, industry and innovation and partnerships to achieve goals are four (4) out of seventeen (17) mutual agreements in the   Sustainable Development Goals (SDGs) in 2015. Bumirejo Village, Dampit District, Malang Regency which has BUMDESA and 700 breeders (farms) has an MSME empowerment program so it needs to be supported with a capital and marketing system to increase production capacity and quality. One of the solutions offered is through the development of a marketing investment system for sheep farming based on strengthening livestock management with local wisdom. Based on local wisdom because the culture of raising livestock and forage cultivation is already available in the village community. This system is developed based on a web application with users as administrators and general public. The role of the administrator provides up-to-date information while the general is to access the application to read the investment and marketing opportunity information offered.
Pembangunan Aplikasi Farm Record Tanaman Buah Berkayu Di Kecamatan Poncokusumo Kab Malang Dalam Rangka Mendukung Ketahanan Pangan Soebroto, Arief Andy
DIMASLOKA: Jurnal Pengabdian Masyarakat Teknologi Informasi dan Informatika Vol 4 No 1 (2025): Januari
Publisher : Fakultas Ilmu Komputer Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/dimasloka.v4i1.31

Abstract

Sudah jamak bahwa diketahui petani tanaman buah berkayu gagal dalam panen karena produktivitas dan kualitas produksi hasil pertanian turun. Dampak dari turunya produktivitas dan kualitas produksi hasil pertanian turun berdampak pada ketahanan pangan petani. Gangguan hama, penyakit, kesalahan proses budidaya dan lain hal selama ini tidak tercatat dengan baik sehingga petani jika ada masalah maka yang memberikan solusi dari permasalahannya berdasarkan informasi sesama petani dan trial and error. Berdasarkan hal tersebut maka perlu diberikan solusi berupa aplikasi farm recording tanaman buah berkayu dengan batasan di Kecamatan Poncokusumo Kabupaten Malang dalam rangka mendukung ketahanan pangan. Dari permasalahan tersebut dibutuhkan pendekatan teknologi informasi dalam me-nyelesaikan satu kasus berkaitan dengan budidaya pertanian tanaman buah berkayu. Mitra kegiatan pengabdian kepada masyarakat ini melibatkan dua petani pada Ke-lompok Tani Hutan-KTH Rahayu yang berlokasi di RT 22/RW 5 Dusun Lesti Desa Dawuhan Kecamatan Poncokusumo Kabupaten Malang. Aplikasi yang telah dikembangkan diberikan nama InFarm. InFarm ke depan akan dikembangkan menjadi suatu aplikasi Integrated Farming yang meliputi perkebunan, pertanian, perikanan darat dan peternakan. Pengguna ada dua yaitu administrator dan petani. Petani perkebunan buah berkayu dapat memasukan data kataegori tanaman yaitu tanaman berkayu dan tanaman non berkayu. Tiap kategori dibagi diberikan isian jenis tanaman yang meliputi nama dan jenis tanaman. Petani dapat memasukkan catatan tanaman tersebut untuk semua perlakuan pada sebuah tanaman seperti memberikan pupuk, obat dan perlakuan lainnya seperti pruning. Harapanya dengan adanya catatan perkebunan atau farm recording petani dapat membaca histori kegiatan yang dilakukan sebagai dasar untuk melakukan perlakuan selanjutnya.
Implementation of IoT-Based Flood Emergency Application System (SADARI) for Real-Time Monitoring and Early Warning System in Dringu Probolinggo District Afrikhatul Maulidiyah; Muhammad Imron Rosadi; Muhammad Faishol Amrulloh; Arief Andy Soebroto
Jurnal Teknologi Vol. 18 No. 2 (2026): Jurnal Teknologi
Publisher : Faculty of Engineering Universitas Muhammadiyah Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24853/jurtek.18.2.205-212

Abstract

Floods are hydrometeorological disasters that often occur in urban areas due to limited drainage capacity and high rainfall intensity. Delay in information on water conditions is one of the main factors in low preparedness for potential floods. This research aims to implement the Internet of Things (IoT)-based Flood Emergency Application System (SADARI) as a real-time monitoring and early warning system in Dringu District, Probolinggo Regency. The developed system integrates water level sensors and rainfall sensors, data loggers, and GSM-based communication modules for continuous data transmission. The research method uses a Research and Development (R&D) approach which includes the design, implementation, and testing stages of the system. The results of the implementation show that the system is able to monitor water levels in real-time and classify conditions into safe, alert, and hazard statuses. In field tests, the system successfully detected variations in water levels from normal (±16 cm) to dangerous conditions (±181 cm) and sent automatic notifications via Telegram Bot in a timely manner. In addition, the system is supported by an independent power supply so that it can operate sustainably in the field. Thus, the SADARI system can be an effective solution in supporting flood mitigation, improving community preparedness, and providing information on environmental conditions quickly and accurately.
Co-Authors Achmad Arwan Achmad Ridok Adam Hendra Brata Ade Wija Nugraha Adhi Harmoko Saputro Adi Setyo Nugroho Admaja Dwi Herlambang Afrikhatul Maulidiyah Agi Putra Kharisma Agus Wahyu Widodo, Agus Wahyu Ahmad Afif Supianto Ahmad Mustafirudin Ahmad Shofi Nurur Rizal Aizul Faiz Iswafaza Alfarisi, Muhammad Asnin Alfry Aristo Jansen Sinlae Ali Akbar Alysha Ghea Arliana Amira Ibtisama Ana Kusuma Ardani Anam, Muhammad Haris Khoirul Andreas Tommy Christiawan Andri Wijaya Kusuma Annisa Indah Fitriani Anto Satriyo Nugroho Ari Setiawan Asrul Syawal Asrul, Divanda Arya Inasta Asus Maizar Suryanto H Austenita Pasca Aisyah Baghaz, Renanda DSP Bambang Gunadi Bioni Sena Brilliansyach, Raihan Fikri Caesar, Canny Amerilyse Candra Dewi Candra Dewi Catur Ari Setianto Charles Eugene Dama Yuliana Deby Putri Indraswari Denny Sagita Rusdianto Destyana Ellingga Pratiwi Destyana Ellingga Pratiwi Dhea Azahria Mawarni Dian Eka Ratnawati Diva Kurnianingtyas Divanda Arya Inasta Asrul Djoko Pramono Dwi Cindy Herta Turnip Dwi Puri Cemani Dzikrullah, Muhammad Aulia Fachruz Edy Santoso Eka Miyahil Uyun Eko Ari Setijono Marhendraputro Eko Arisetijono Elza Fadli Hadimulyo Endah Emiarti Enggar Septrinas Enggarsita Auliasin Eugenius Yosep Korsan N Evi Irhamillah Azza Faisal Roufa Rohman Faizatul Amalia Fajar Pradana Farida Mony Fauziah Mayasari Iskandar Febrianita Indah Perwitasari Fendy Yulianto Ferdy Wahyurianto Fildzah Amalia Galuh Mazenda Guruh Prayogi Willis Putra Habib Yafi Ardi Hagus Tarno Hanafi, Andy Hastian Bayu Hendra Darmawan Hendra Darmawan Herman Syantoso Himawan Sutanto I Gede Adi Brahman Nugraha I Putu Bagus Arya Pradnyana Ibnu, Mohammad Ibrahim Kusuma Imam Cholissodin Imam Cholissodin Imam Cholissodin Imam Cholissodin Imam Cholissodin Indra Ekaristio P Indriana Candra Dewi Indriati Indriati Indriati Indriati Indriati Indriati Ishak Panangian Sinaga Ismiarta Aknuranda Issa Arwani Issa Arwani Karmia Larissa Br Pandia Khoifah Inda Maula Khrisna Widhi Dewanto Krisna Wahyu Aji Kusuma Kurnianingtyas, Diva Lailatul Rizqi Ramadhani Lailil Muflikhah Laode Muhamad Fauzan Latifah Hanum Lily Montarcih Limantara M Azka Obila Vasya Mahdi Fiqia Hafis Maria Tenika Frestantiya Maria Tenika Frestantiya, Maria Tenika Maya Febrianita Moh. Sholichin Mohammad Ibnu Mohammad Imron Maulana Muh. Arif Rahman Muhammad Faishol Amrulloh Muhammad Imron Rosadi Muhammad Iqbal Kurniawan Muhammad Rois Al Haqq Muhammad Rouzikin Annur Muhammad Tanzil Furqon Muhammad Taruna Praja Utama Mutia Ayu Sabrina Nadhira Nurannisa Nadya Rahmasari Nadya Sylviani Nainggolan, Yohana Beatrice Nanang Suryadi Niftah Fatiha Armin Niken Hendrakusma Wardani Nizar Rahman Kusworo Nurannisa, Nadhira Nurasiah Nuriya Fadilah Nurudin Santoso Nurul Faizah Nurul Faridah, Nurul Nurul Hidayat Nurul Hidayat Nurul Hidayat Nurul Hidayat Nurul Hidayat Odhia Yustika Putri Pretty Diawati Priyambadha, Bayu Puguh Surjowardojo Putra Pandu Adikara Putri, Nurulita Purnama Raihan Fikri Brilliansyach Randy Cahya Wihandika Ratih Prasetya, Ratih Raymond Gunito Farandy Junior Rekyan Regasari Rekyan Regasari Mardi Putri Restia Dwi Oktavianing Tyas Retnani, Diah Prabawati Reynald Daffa Pahlevi Ridwan Fajar Widodo Rio Andika Dwiki Adhi Putra Rio Arifando Risda Nur Ainum Riski Ida Agustiyan Risqi Nur Ifansyah Rivaldy Raihan Syams Rizal Setya Perdana Rizal Setya Perdana Rizal Setya Perdana Romanda Annas Amrullah Rumahorbo, Cicilia Angelica Saiful Kirom, Muhammad Ihsan Santoso, Nurudin Sativandi Putra Satrio Agung Wicaksono Sitepu, Yosua Christiansen Stefan Levianto Sukamto, Anjas Pramono Surya Wirawan SUTRISNO Sutrisno Sutrisno Sutrisno, Sutrisno Syakirah Dwi Anisa Teddy Syach Pratama Thareq Ibrahim Tiara Rossa Diassananda Tryse Rezza Biantong Vasya, M Azka Obila Vera Selviana Adoe Vicky Virdus Vivien Fathuroya, Vivien Wayan Firdaus Mahmudy Wayan Firdaus Mahmudy Welly Purnomo Wijaya, Aldi Rahman Wildan Ziaulhaq Wildan Ziaulhaq Wildansyah Maulana Rahmat Yearra Taufan Ardy Rinaldy Yusril Iszha Eginata Zaien Bin Umar Alaydrus Ziya El Arief Ziya El Arief, Ziya El