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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) EXPERT: Jurnal Manajemen Sistem Informasi dan Teknologi Jurnal Teknologi Informasi dan Ilmu Komputer Panrita Abdi - Jurnal Pengabdian pada Masyarakat Sistemasi: Jurnal Sistem Informasi JOIV : International Journal on Informatics Visualization International Journal of Artificial Intelligence Research Journal of Information Technology and Computer Science (JOINTECS) Jurnal Ilmiah FIFO PROCESSOR Jurnal Ilmiah Sistem Informasi, Teknologi Informasi dan Sistem Komputer JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI Conference on Innovation and Application of Science and Technology (CIASTECH) JURTEKSI METIK JURNAL Jutisi: Jurnal Ilmiah Teknik Informatika dan Sistem Informasi Jusikom: Jurnal Sistem Informasi Ilmu Komputer Systematics Techno Xplore : Jurnal Ilmu Komputer dan Teknologi Informasi Jurnal Teknologi Dan Sistem Informasi Bisnis Jurnal Informasi dan Teknologi Buana Information Technology and Computer Sciences (BIT and CS) JATI (Jurnal Mahasiswa Teknik Informatika) REMIK : Riset dan E-Jurnal Manajemen Informatika Komputer Indonesian Journal of Electrical Engineering and Computer Science Abdimas Galuh: Jurnal Pengabdian Kepada Masyarakat JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) JIKA (Jurnal Informatika) Jurnal Sistem Komputer dan Informatika (JSON) Infotek : Jurnal Informatika dan Teknologi Journal of Applied Data Sciences Jurnal Cahaya Mandalika Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer) Djtechno: Jurnal Teknologi Informasi Bulletin of Computer Science Research KLIK: Kajian Ilmiah Informatika dan Komputer Jurnal Mandiri IT Mechanical Engineering for Society and Industry Dirgamaya: Jurnal Manajemen dan Sistem Informasi J-Intech (Journal of Information and Technology) Automotive Experiences Journal of Informatics and Communication Technology (JICT) Jurnal Sistem Informasi Triguna Dharma (JURSI TGD) Jurnal Informatika Teknologi dan Sains (Jinteks) Abdimas Journal International of Lingua and Technology Jurnal Komtekinfo Jurnal Buana Pengabdian Jurnal Ilmiah Sistem Informasi dan Ilmu Komputer Innovative: Journal Of Social Science Research JIM: Jurnal Ilmiah Mahasiswa Pendidikan Sejarah Jurnal Accounting Information System (AIMS) INTERNAL (Information System Journal) Jurnal Polimesin Journal of Informatics and Communication Technology (JICT) CSRID Jurnal SINTA: Sistem Informasi dan Teknologi Komputasi Jurnal PETISI (Pendidikan Teknologi Informasi) Journal of Information Technology Jurnal Abdimas Mahakam
April Lia Hananto
Universitas Buana Perjuangan Karawang, Indonesia
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Pendekatan Data Mining Dengan Algoritma K-Means Untuk Klasterisasi Faktor Perceraian Di Jawa Barat Andini, Vina; Hananto, April Lia; Priyatna, Bayu; Hananto, Agustia
JURNAL PETISI (Pendidikan Teknologi Informasi) Vol. 7 No. 2 (2026): JURNAL PETISI (Pendidikan Teknologi Informasi)
Publisher : Universitas Pendidikan Muhammadiyah Sorong

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36232/jurnalpetisi.v7i2.5560

Abstract

Abstrak: Penelitian ini dilatarbelakangi oleh tingginya angka perceraian di Provinsi Jawa Barat yang menunjukkan variasi faktor penyebab antarwilayah, sehingga diperlukan analisis kuantitatif berbasis data untuk mengidentifikasi pola pengelompokan determinannya. Tujuan penelitian ini adalah menganalisis konfigurasi klaster faktor penyebab perceraian serta mengidentifikasi faktor dominan pada masing-masing kelompok wilayah menggunakan pendekatan data mining. Metode yang digunakan adalah K-Means Clustering berbasis unsupervised learning terhadap data sekunder Open Data Jabar periode 2017–2024, dengan enam variabel utama yaitu ekonomi, KDRT, kawin paksa, zina, madat, dan cacat badan. Penentuan jumlah klaster dilakukan menggunakan Elbow Method, evaluasi model menggunakan Silhouette Coefficient, serta visualisasi pola dilakukan melalui Principal Component Analysis (PCA). Hasil penelitian menunjukkan terbentuknya tiga klaster dengan nilai Silhouette sebesar 0,61 yang mengindikasikan kualitas pemisahan klaster yang baik. Cluster pertama didominasi faktor ekonomi, cluster kedua menonjol pada faktor zina dan madat, sedangkan cluster ketiga menunjukkan kombinasi tekanan ekonomi, KDRT, dan kawin paksa. Temuan ini menegaskan bahwa perceraian di Jawa Barat dipengaruhi oleh pola determinan yang berbeda antarwilayah. Penelitian ini menyimpulkan bahwa pendekatan K-Means efektif dalam mengidentifikasi struktur laten faktor perceraian dan merekomendasikan kebijakan pencegahan yang disesuaikan dengan karakteristik klaster serta pengayaan variabel dan metode pada penelitian selanjutnya
Klasterisasi Siswa Berdasarkan Profil Akademik dan Karakteristik Belajar Menggunakan Algoritma K-Means untuk Mendukung Pembelajaran Faiharani, Attaya; Huda, Baenil; Nurapriani, Fitria; Hananto, April Lia
Journal of Information System Research (JOSH) Vol 7 No 3 (2026): April 2026
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v7i3.9572

Abstract

Grouping students based on academic and non-academic characteristics is important to support the development of more targeted educational guidance strategies in schools. The main problem addressed in this study is the absence of objective data-based student mapping, which causes development programs to remain general and less targeted. This study aims to classify students using the K-Means clustering algorithm based on academic profiles and other supporting variables, and to evaluate cluster quality using the silhouette coefficient method. The research stages include data preprocessing, determining the optimal number of clusters, clustering using K-Means, and evaluating the clustering result. The results showed that four clusters were selected as the final configuration with a silhouette score of 0,1093, with cluster membership distributed into 12, 4, 2, and 2 students. Visualization using principal component analysis shows that most clusters are sufficiently well separeted. This study contributes a data-driven student grouping model that can be used as a basis for recommending student potential development according to the characteristics of each group.
KLASIFIKASI DAERAH RAWAN PENYAKIT HEWAN MENULAR STRATEGIS MENGGUNAKAN ALGORITMA DECISION TREE C4.5 Hasibuan, Nadya Susanti; Huda, Baenil; Hilabi, Shofa Shofiah; Hananto, April Lia
Djtechno: Jurnal Teknologi Informasi Vol 7, No 1 (2026): April
Publisher : Universitas Dharmawangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46576/djtechno.v7i1.8543

Abstract

Penelitian ini memiliki tujuan untuk mengklasifikasikan tingkat kerawanan daerah berdasarkan kasus penyakit hewan menular di wilayah kabupaten atau kota Provinsi Nusa Tenggara Barat dengan memanfaatkan teknik data mining. Dalam penelitian ini, metode yang diterapkan adalah algoritma Decision Tree C4.5 dengan menggunakan teknik evaluasi 5-fold cross validation sebagai penilaian efektivitas model. Dataset yang digunakan merupakan data sekunder periode 2020–2024 yang melalui tahapan preprocessing meliputi data cleaning, agregasi, feature engineering, dan pelabelan menjadi tiga kategori kerawanan: rendah, sedang, dan tinggi. Temuan dari penelitian ini menunjukkan bahwa variabel rata-rata kasus menjadi faktor utama dalam menentukan tingkat wilayah kerawanan. Model yang dibangun mampu menghasilkan klasifikasi dengan performa yang baik, ditunjukkan oleh akurasi rata-rata sebesar 94% dan nilai tinggi untuk presisi, recall, serta F1-score di setiap kategori. Selain itu, model memiliki kemampuan interpretasi yang jelas melalui struktur pohon keputusan yang dihasilkan. Dengan demikian, pendekatan yang digunakan terbukti efektif dalam identifikasi wilayah berisiko dan dapat mendukung pengambilan keputusan dalam upaya pengendalian penyakit hewan menular dengan strategi yang lebih tepat dan berbasis data.
Design of an Enterprise Architecture for Monitoring IT Services and Infrastructure Using TOGAF ADM at PT Fratama Kencana Gemilang Karina; Hananto, April Lia; Priyatna, Bayu; Hananto, Agustia
J-INTECH ( Journal of Information and Technology) Vol 14 No 01 (2026): Journal of Information and Technology
Publisher : LPPM Universitas Bhinneka Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32664/j-intech.v14i01.2275

Abstract

The management of information technology infrastructure at PT Fratama Kencana Gemilang currently faces significant operational challenges in its day-to-day operations. This is due to the device monitoring mechanisms currently in place, which remain manual and fragmented across units, resulting in the IT team often only becoming aware of technical issues after receiving user complaints. This reactive approach inevitably hinders company productivity, particularly regarding server services that form the core of the business. Therefore, this study aims to design a more proactive, automated, and integrated enterprise system monitoring architecture using the TOGAF ADM (The Open Group Architecture Framework Architecture Development Method) framework. Through this approach, it is expected that all of the company’s technology assets can be centrally monitored and aligned with long-term strategic business objectives. This research employs a qualitative descriptive approach conducted through direct observation of the existing system infrastructure and in-depth architectural modeling. This design process covers various key domains in a structured manner, ranging from the vision domain, business architecture, information system architecture, to the supporting technology infrastructure. The research results indicate that the proposed open-source-based monitoring system design has successfully met the company’s functional and technical requirements comprehensively. This is evidenced by the results of the expert validation process (expert review), which yielded an average score of 4.5 out of 5.0. These results confirm that the designed system is highly effective in providing real-time and accurate visibility into infrastructure performance. This study concludes that the proposed architecture and resulting blueprint are highly suitable to serve as the primary reference for company management in enhancing the reliability of their IT services. The implementation of this design is expected to accelerate the troubleshooting process and minimize the risk of future system failures.
Prioritizing micro, small, and medium enterprises assistance areas in West Java using analytical hierarchy process Lestari, Renita; Huda, Baenil; Novalia, Elfina; Hananto, April Lia
Jurnal Mandiri IT Vol. 14 No. 4 (2026): April: Computer Science and Field.
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/mandiri.v14i4.527

Abstract

This study aims to develop a Decision Support System (DSS) to prioritize areas for receiving assistance for Micro, Small, and Medium Enterprises (MSMEs) in West Java Province using the Analytical Hierarchy Process (AHP) and Simple Additive Weighting (SAW) methods. The AHP method is used to determine the importance weight of each criterion based on its priority level, while the SAW method is used to carry out the normalization process, calculate preference values, and rank alternative areas. The criteria used include the number of MSMEs, workforce, financial stability ratio, legality ratio, BPP ratio, digital ratio, and innovation ratio. The results of the study indicate that the system built is able to produce an objective and consistent ranking of priority areas for MSME assistance, as evidenced by the agreement between the results of manual calculations using Microsoft Excel and the results of calculations in the system. Thus, this system is expected to assist relevant parties in making decisions regarding the distribution of MSME assistance in a more targeted and structured manner and rank 27 administrative regions in West Java Province. The results show that the highest-ranked region achieved a preference value of 0.8573, indicating its highest priority for MSME assistance, while the lowest-ranked region obtained a value of 0.5129. These results demonstrate the system’s capability to generate consistent and objective rankings. In addition, this study contributes by applying a combined AHP–SAW approach at a regional (macro) level, which is still limited in previous studies, thereby providing a more comprehensive framework for data-driven policy decision-making.
ANALISIS INTERAKTIF KASUS KEKERASAN ANAK DI INDONESIA MENGGUNAKAN DASHBOARD POWER BI Bilqis Amalia Utari; April Lia Hananto; Agustia Hananto
Jurnal Informatika Teknologi dan Sains (Jinteks) Vol 8 No 2 (2026): EDISI 28
Publisher : Program Studi Informatika Universitas Teknologi Sumbawa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51401/jinteks.v8i2.7346

Abstract

Kekerasan terhadap anak merupakan permasalahan serius di Indonesia yang berdampak pada perkembangan fisik, psikologis, dan sosial anak. Penelitian ini bertujuan untuk menganalisis data kasus kekerasan terhadap anak di Indonesia serta mengimplementasikan dashboard interaktif berbasis Microsoft Power BI sebagai media visualisasi dan eksplorasi data. Data yang digunakan bersumber dari Sistem Informasi Gender dan Anak (SIGA). Metode penelitian meliputi pengumpulan data, pre-processing, analisis distribusi kasus, pengembangan dashboard interaktif, serta evaluasi menggunakan System Usability Scale (SUS). Hasil penelitian menunjukkan bahwa kekerasan seksual merupakan jenis kekerasan yang paling dominan dengan persentase sebesar 46,05%. Dashboard yang dikembangkan mampu menyajikan informasi secara visual dan interaktif sehingga memudahkan pengguna dalam memahami distribusi kasus berdasarkan wilayah dan jenis kekerasan. Hasil evaluasi terhadap 35 responden menunjukkan skor SUS sebesar 80,2 yang termasuk dalam kategori “Good”. Dengan demikian, dashboard interaktif yang dikembangkan dapat membantu memahami pola distribusi kasus serta mendukung pengambilan keputusan berbasis data dalam upaya pencegahan dan penanganan kekerasan terhadap anak di Indonesia.
DIGITALISASI LAYANAN TOKO LARIS MOTOR DENGAN TEKNOLOGI CHATBOT OTOMATIS BERBASIS AI Gefira Rahmaifha; April Lia Hananto; Elfina Novalia; Baenil Huda
Jurnal Informatika Teknologi dan Sains (Jinteks) Vol 8 No 2 (2026): EDISI 28
Publisher : Program Studi Informatika Universitas Teknologi Sumbawa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51401/jinteks.v8i2.7374

Abstract

Penelitian ini bertujuan untuk merancang dan mengimplementasikan sistem chatbot otomatis berbasis Artificial Intelligence (AI) menggunakan workflow automation N8N sebagai solusi digitalisasi layanan pelanggan pada Toko Laris Motor. Permasalahan yang dihadapi meliputi keterlambatan respons, penumpukan pesan WhatsApp, serta ketidakkonsistenan informasi akibat proses pelayanan yang masih dilakukan secara manual. Penelitian ini menggunakan pendekatan Research and Development (R&D) yang mencakup tahapan analisis kebutuhan, perancangan sistem, pengembangan, pengujian, dan evaluasi. Sistem chatbot dikembangkan dengan memanfaatkan AI Agent untuk memahami konteks percakapan, serta diintegrasikan dengan WhatsApp API dan Google Sheets guna menyediakan informasi produk, harga, dan ketersediaan stok secara real-time. Proses pengujian sistem dilakukan menggunakan metode Blackbox Testing untuk memastikan setiap fungsi sistem berjalan sesuai dengan kebutuhan pengguna tanpa melihat struktur kode program. Hasil pengujian menunjukkan bahwa sistem mampu meningkatkan kecepatan respons layanan, menjaga konsistensi informasi, serta mengurangi beban kerja administratif. Implementasi chatbot ini mendukung transformasi digital pada sektor UMKM ritel otomotif dan menunjukkan bahwa otomatisasi layanan berbasis AI dapat meningkatkan efektivitas operasional serta kualitas interaksi pelanggan secara berkelanjutan.
Improved Hybrid GoogLeNet-Based Deep Learning Optimization for Standardized Straw Mushroom Quality Classification in Indonesia Bayu Priyatna; Titik Khawa Abdurahman; Muhammad Fahmi Miskon; April Lia Hananto; Agustia Tia Hananto; Aviv Yuniar Rahman
Journal of Applied Data Sciences Vol 7, No 2: May 2026
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v7i2.1206

Abstract

Deep learning plays a crucial role in modern computer vision due to its ability to automatically extract hierarchical features from large-scale image data. Among various architectures, Convolutional Neural Networks (CNNs) have been extensively utilized for image pattern interpretation, including in agricultural product inspection. Straw mushrooms (Volvariella volvacea) are important agro-industrial commodities in Indonesia; however, their quality assessment still relies on subjective manual evaluation based on the Indonesian National Standard (SNI:01-6945-2003), leading to inconsistency in grading results. To address this limitation, this research proposes an Improved Hybrid GoogLeNet model integrated with a YOLO-based detection framework and hybrid preprocessing to enhance feature clarity and classification robustness. The system is capable of conducting object detection, 3-class morphological quality classification (Pure White, Oval, and Black Spot/Defect), and automatic diameter measurement using calibrated pixel-to-centimeter conversion. Performance evaluation is carried out by benchmarking the proposed model against several popular deep learning architectures including YOLOv5, LeNet, AlexNet, VGGNet, and ResNet. Experimental results demonstrate that the Improved Hybrid GoogLeNet achieves the highest performance with precision of 97.99%, recall of 96.07%, and F1-score of 96.98%, along with low misclassification rates across all classes. These results indicate that the proposed method provides accurate, reliable, and efficient quality assessment that supports standardized automated grading in industrial applications. Therefore, this study contributes to the advancement of intelligent computer vision solutions for digital transformation in the Indonesian mushroom agro-industry.
Web-Based Warehouse Inventory System Using the Waterfall Method: A Case Study at Satria Wholesale Mart Melisa; Tukino; Agustia Hananto; April Lia Hananto
Jurnal Informasi dan Teknologi 2025, Vol. 7, No. 1
Publisher : SEULANGA SYSTEM PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60083/jidt.vi0.610

Abstract

In the digital era, manual warehouse inventory management is still challenging for many business people, including Satria Wholesale Mart. The main problems also faced are irregularities in recording incoming and outgoing goods, low accuracy of stock data, delays in reporting, and difficulties in tracking stock in real time. This finding aims to design and build an efficient and effective web-based warehouse inventory system using the Waterfall method. The finding method used is applied findings with a descriptive qualitative approach, which also aims to describe in detail and systematically the phenomena that also occur in the field and how new systems can be developed to solve these problems. The findings show that applying the waterfall method in developing a web-based inventory information system at PT Herso Ticep Indonesia has also yielded satisfactory results. The system that has also been developed has succeeded in meeting the needs of companies in inventory management, improving operational efficiency, and optimizing inventory management. These findings imply that companies can improve their operational efficiency and optimize inventory management by implementing this information system. The findings could also guide other companies that want to develop similar systems.
SISTEM INFORMASI MANAJEMEN STOK OBAT BERBASIS WEB PADA APOTEK BIMA FARMA Irsyadul I'bad; Tukino Tukino; April Lia Hananto; Baenil Huda; Fitria Nurapriani
EXPERT: Jurnal Manajemen Sistem Informasi dan Teknologi Vol 16, No 1 (2026): Juni
Publisher : Universitas Bandar Lampung (UBL)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36448/expert.v16i1.4801

Abstract

Manajemen stok obat di Apotek Bima Farma masih dilakukan secara manual, sehingga menyebabkan selisih data stok mencapai 8%–12% dan memperlambat proses pencarian serta pelaporan hingga sekitar 3 jam. Penelitian ini bertujuan membuat sistem informasi manajemen stok obat yang berbasis web agar bisa mempercepat dan membuat lebih tepat dalam mengolah data, serta mengurangi perbedaan stok hingga di bawah 2%. Sistem tersebut dibuat dengan menggunakan metode Waterfall, dan dalam pembuatan nya dilakukan perancangan menggunakan UML serta ERD. Sistem ini kemudian diimplementasikan dengan menggunakan framework CodeIgniter 3 yang berbasis PHP dan MySQL, serta menerapkan arsitektur MVC. Uji coba dilakukan dengan metode Black Box terhadap 12 skenario dan berhasil mencapai tingkat keberhasilan 100%. Selain itu, juga dilakukan pengujian dengan metode White Box dan diperoleh nilai kompleksitas siklomatis V(G) = 2. Hasil menunjukkan bahwa sistem berhasil mengotomatisasi proses pencatatan transaksi, memberikan informasi stok secara langsung dan segera, serta menghemat waktu dalam pembuatan laporan dari sekitar 3 jam menjadi kurang dari 30 menit. Selain itu, perbedaan antara stok yang ada dan yang diperlukan berhasil dikurangi hingga di bawah 2%. Dengan demikian, sistem yang dikembangkan efektif dalam meningkatkan efisiensi dan akurasi pengelolaan stok obat serta layak diterapkan pada apotek skala kecil hingga menengah
Co-Authors - Faqih AA Sudharmawan, AA Abdullah Abdullah Abdullahi Tanko Mohammed Abdullahi Tanko Mohammed Adittia Agustian Afra, Alfina Fadhilah Agneresa Agneresa Agustia Tia Hananto Ahmed Sule Ahnaf, Naufal Zubdi Ajie, Prasetyo Alparizi, Muhamad Iqbal Alpian, Yayan alzahra, alika aziza Andini, Vina Anthony Chukwunonso Opia Aprilia Putri Nardilasari Arkan Hilman Hakim Asep Haris Atmaja, Rashelin Zahra Aulia, Aldi Aviv Yuniar Rahman Aviv Yuniar Rahman Aviv Yuniar Rahman Aviv Yuniar Rahman Aviv Yuniar Rahman Baenil Huda Baenil Huda Baenil Huda Baenil Huda Bagus Setyawan Baihaqi, Kiki Ahmad Bayu Priyatna Bayu Priyatna Bayu Priyatna Berkah*, Kamila Bilqis Amalia Utari Candra Zonyfar Catur Nugroho Danny Manongga Dean Ariesta Aziz Deddy Prihadi Detrie Noviani Dhany Hermansyah Dien Noviany Rahmatika Edrina Christine, Natalie Eichler, Luiz Eko Pramono Eko Sediyono Esam Abu Baker Ali Fadli, Muhammad Abil Faiharani, Attaya Fatlun, Aulia Fatmanisa Mumpuni Delta Maharani Fauzi Ahmad Muda Firdaus, Mohamad Ricky Firman Nurdiansyah Firman Nurdiyansyah Fitri Nur Masruriyah, Anis Fitri Nurapriani Fitria Nur Apriani Fitria Nurapriani Fuad anwar yuwono Gefira Rahmaifha Guntur, Muhamad Hananto, Agustia Hanny Hikmayanti Handayani Hasibuan, Nadya Susanti Hayati, Cucu Hendry Henry Adam Hibatullah, Muhammad Hafizh Hilabi, Shofa Shofia Hilabi, Shofa Shofiah Hilabi, Shofa Shofiah Hindriyanto Dwi Purnomo Huda Huda Huda, Baenil Ihsan, Mohammad Maftuh Ihwan Ghazali Ilman Kadori Indra Kurniawan Indri Oktapiani Irawan, Bei Harira Irsyadul I'bad Irwan Sembiring Istiadi Isyanto, H. Puji Iwan Setiawan Iwan Setyawan Joko Purwanto Kamila Berkah* Karina Kurnia, Nisa Lestari, Renita Lutfiah, Siti Mega Tri Kurnia Melisa Miswadi Miswadi Moh Hasan Basri Mohamad Ricky Firdaus Mubarok, Piky Muhamad Djaka Permana Muhammad Fahmi Miskon Muhammad Idris Muhammad Idris Muhammad Idris Muhammad Nova Muhammad Zacky Asy'ari Muthia Nur Rizky Fitriani Nisa Kurnia Novalia, Elfina Novia Cahya Utami Nur ‘Azah Nurapriani, Fitria Nurapriani, Nurapriani Nurfajria, Dera Paryono, Tukino Permana Andi Paristiawan Permana Andi Paristiawan Pradana Rizki Maulana Prasetya, Rafli Pratama, Daffa Agung Priatna, Bayu Priyatna , Bayu Priyatna, Bayu Purnomo, Hendryanto Dwi Putri Indraswari Ramadanti, Anita Khansa Reformasi, Era Rieke Retnosary Rosalina, Elsa Rukmanta Jayawiguna Ruliansyah Ruliansyah Ruliansyah Ruliansyah, Ruliansyah Saepul Aripiyanto Safarudin Gazali Herawan Sari, Nurnilam Sarina Sulaiman Sarina Sulaiman Setiawan, Feddy Wanditya Setiawan, Pratama Wahyu Shofa Shofia Hilabi Shofa Shofia Hilabi Shofa Shofia Hilabi Shofa Shofiah Hilabi Shofa Shofiah Hilabi Shofa Shofiah Hilabi Shofa Sofiah Hilabi Shofiah Hilabi, Shofa Shuaibu Alani Balogun Sigit Widiyanto Silva, Tiago Siti Masruroh Soleman, Soleman Sopian, Jajang Sri Mumpuni Ngesti Rahaju Sudrajat, Deden Renhad Suhada, Karya Surala, Lyvia Susilawati, Agnes Dwita Syah Alam Tita Puspita Sari Titik Khawa Abdurahman Tukino Tukino Tukino Tukino Tukino Tukino Tukino, Tukino Tukino, Tukino Wahiddin, Deden Yazid, Muhammad Abi Yovika Aprianti Yoviyardi, Rama