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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 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 Adopsi Teknologi dan Sistem Informasi 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
Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Humanities Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Nursing Public Health Social Sciences Transportation Other

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Development of Health Mask Identification Using YOLOv5 Architecture Ahmad Fauzi; Prasetyo Ajie; Anis Fitri Nur Masruriyah; Deden Wahiddin; Hanny Hikmayanti; April Lia Hananto
International Journal of Artificial Intelligence Research Vol 6, No 1.1 (2022)
Publisher : Universitas Dharma Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29099/ijair.v6i1.1.573

Abstract

Coronavirus Disease 2019 (COVID-19) causes the state to suffer losses, especially in the health sector. WHO calls for controlling COVID-19 with health protocols that must be obeyed, one of which is wearing a mask. The use of masks can reduce the transmission of COVID-19. But there are still many people who ignore the protocol to use masks properly. So a system was created to detect the use of masks properly using the YOLOv5 architecture. Aiming to help regulate the use of masks in public areas or open places. The process of this research begins with data collection in the form of images. The collected image data will later be used as a dataset and model training will be carried out using the YOLOv5s model. The accuracy results obtained from this study reached 90.37%
Klasterisasi Siswa Berdasarkan Profil Akademik dan Karakteristik Belajar Menggunakan Algoritma K-Means untuk Mendukung Pembelajaran Attaya Faiharani; Baenil Huda; Fitria Nurapriani; April Lia Hananto
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 ULASAN APLIKASI KOPI KENANGAN PADA GOOGLE PLAYSTORE MENGGUNAKAN ALGORITMA NAIVE BAYES Muhammad Abil Fadli; Tukino tukino; Elfina Novalia; April Lia Hananto
Djtechno: Jurnal Teknologi Informasi Vol 6, No 2 (2025): Agustus
Publisher : Universitas Dharmawangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46576/djtechno.v6i2.7037

Abstract

Aplikasi Kopi Kenangan merupakan aplikasi yang digunakan untuk pemesanan minuman secara online milik perusahaan PT Bumi Berkah Boga. Selain hal tersebut aplikasi ini juga membantu perusahaan menerima ulasan terkait pengalaman pelanggan dalam menggunakan layanan aplikasi kopi kenangan. Namun ulasan pelanggan di Google Playstore memiliki jumlah data yang banyak sehingga sulit dianalisis secara manual. Tujuan penelitian ini melakukan klasifikasi ulasan pelanggan pada aplikasi Kopi Kenangan mempergunakan algoritma Naïve bayes. Metode penelitian ini meliputi pengumpulan data, preprocessing, pemodelan dan evaluasi. Data yang dipergunakan dalam penelitian ini yaitu sebesar 1000 data dengan lima kategori yaitu promo, pelayanan, performa aplikasi, transaksi dan kualitas produk. Hasil penelitian menunjukkan bahwa kategori ulasan terbanyak adalah tentang performa aplikasi dengan persentase 45% dari total 1000 data ulasan. Hasil akurasi penelitian yaitu sebesar 85% yang menunjukkan bahwa model dapat melakukan klasifikasi data kategori sentimen dengan cukup baik.
IMPLEMENTASI MACHINE LEARNING MELALUI PENDEKATAN ALGORITMA RANDOM FOREST DALAM PREDIKSI TINGKAT STRES BERDASARKAN POLA GAYA HIDUP Anita Khansa Ramadanti; April Lia Hananto; Bayu Priyatna; Agustia Hananto
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.v7i1.8457

Abstract

Stres yang tidak terkelola berisiko berkembang menjadi gangguan serius seperti depresi hingga risiko bunuh diri. Machine learning dapat dioptimalkan sebagai solusi deteksi dini berdasarkan kombinasi faktor gaya hidup. Penelitian ini bertujuan untuk mengembangkan model prediksi tingkat stres melalui pendekatan algoritma Random Forest dengan dataset yang diperoleh platform Kaggle. Tahapan penelitian meliputi data preprocessing, penanganan ketidakseimbangan kelas menggunakan SMOTE, hingga evaluasi dan integrasi model.  Hasil evaluasi menunjukkan bahwa model mencapai akurasi sebesar 0.80, dengan nilai precision, recall, dan F1-Score secara keseluruhan berada pada angka 0,80. Performa terbaik diperoleh pada klasifikasi tingkat stres kategori High dengan F1-Score sebesar 0.86. Model yang telah tervalidasi kemudian diintegrasikan ke dalam antarmuka melalui Streamlit, sehingga mampu memberikan hasil prediksi secara real-time berdasarkan input data pengguna. Penelitian ini membuktikan bahwa algoritma Random Forest efektif dalam mengidentifikasi tingkat stres, dan implementasinya dalam bentuk aplikasi web berpotensi menjadi alat bantu deteksi dini yang fungsional dan sederhana.
Pendekatan Data Mining Dengan Algoritma K-Means Untuk Klasterisasi Faktor Perceraian Di Jawa Barat Vina Andini; April Lia Hananto; Bayu Priyatna; Agustia Hananto
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
Audit Tata Kelola TI Pada Rapor Digital Madrasah (RDM) Berbasis Framework Cobit 2019 Domain DSS Nursyifa; Bayu Priyatna; Fitria Nurapriani; April Lia Hananto
JURNAL PETISI (Pendidikan Teknologi Informasi) Vol. 7 No. 3 (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.v7i3.5599

Abstract

Abstrak: Tujuan dari penelitian ini adalah untuk menilai tata kelola teknologi informasi pada aplikasi Rapor Digital Madrasah (RDM) di MI Al-Hidayah 04 dengan menggunakan pendekatan COBIT 2019. Domain Pengiriman, Layanan, dan Dukungan (DSS), yang terdiri dari subdomain DSS01, DSS02, dan DSS05, menjadi fokus audit. Data dikumpulkan dari lima belas responden, yang terdiri dari guru dan kepala sekolah, melalui observasi, wawancara, dan kuesioner. Hasil perhitungan menunjukkan bahwa tingkat kapabilitas rata-rata saat ini adalah 2,22, yang berada pada level proses manajemen. Sub-domain DSS01 memiliki celah terbesar, yaitu 1,15, diikuti oleh DSS05 dengan nilai 0,47, dan DSS02 telah melampaui target dengan nilai -0,28. Penguatan prosedur keamanan dan pencadangan data serta standarisasi dokumen operasional adalah fokus dari rekomendasi perbaikan.
Analisis Pola Penjualan Mobil Honda Menggunakan Pendekatan EDA dan Dashboard Visualisasi Tableau Sofia Ramadanti Az-Zahra; April Lia Hananto; Bayu Priyatna; Shofa Shofiah Hilabi
Jutisi : Jurnal Ilmiah Teknik Informatika dan Sistem Informasi Vol 15, No 3 (2026): Juni 2026
Publisher : STMIK Banjarbaru

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35889/jutisi.v15i3.3606

Abstract

Vehicle sales data, which continues to grow year after year, generates a significant amount of information, often challenging to analyze optimally when presented solely in static reports. This study aims to analyze Honda car sales patterns for the 2021–2025 period using an Exploratory Data Analysis (EDA) approach combined with a Tableau visualization dashboard. The method used is descriptive quantitative, utilizing Honda wholesale data obtained from GAIKINDO. The research process includes data collection, data cleansing, Exploratory Data Analysis (EDA), dashboard visualization, and usability evaluation using the System Usability Scale (SUS). The variables analyzed include annual sales trends, monthly growth, vehicle models, and vehicle categories. The results show that Honda sales peaked in 2023 before declining in the 2024–2025 period. The 4x2 category and the LCGC segment were listed as the main contributors to sales, while the usability evaluation obtained a SUS score of 68.3. These findings indicate that the developed dashboard is capable of presenting information effectively and is suitable for use as a data-driven decision-making support.Kata kunci: Exploratory Data Analysis; Wholesales Data; Data Visualization; Tableau. AbstrakData penjualan kendaraan yang terus bertambah dari tahun ke tahun menghasilkan volume informasi yang cukup besar dan sering kali tidak mudah dianalisis secara optimal apabila hanya disajikan dalam bentuk laporan statis. Penelitian ini bertujuan untuk menganalisis pola penjualan mobil Honda pada periode 2021–2025 melalui pendekatan Exploratory Data Analysis (EDA) yang dipadukan dengan dashboard visualisasi Tableau. Metode yang digunakan adalah deskriptif kuantitatif dengan memanfaatkan data wholesales Honda yang diperoleh dari GAIKINDO. Proses penelitian mencakup pengumpulan data, pembersihan data, EDA, visualisasi dashboard, serta evaluasi usability menggunakan System Usability Scale (SUS). Variabel yang dianalisis meliputi tren penjualan tahunan, pertumbuhan bulanan, model kendaraan, dan kategori kendaraan. Hasil penelitian menunjukkan bahwa penjualan Honda mencapai titik tertinggi pada tahun 2023 sebelum mengalami penurunan pada periode 2024–2025. Kategori 4x2 dan segmen LCGC tercatat sebagai kontributor utama penjualan, sementara hasil evaluasi usability memperoleh skor SUS sebesar 68,3. Temuan ini mengindikasikan bahwa dashboard yang dikembangkan mampu menyajikan informasi secara efektif dan layak digunakan sebagai pendukung pengambilan keputusan berbasis data. 
Analisis dan Pemodelan Proses Bisnis Katering pada UMKM Menggunakan BPMN April Lia Hananto; Elsa Rosalina; Agustia Hananto; Baenil Huda
INTERNAL (Information System Journal) Vol. 7 No. 1 (2024)
Publisher : Masoem University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32627/internal.v7i1.938

Abstract

Fafiras Kitchen is a family business that focuses on food catering services. This business involves three main operational stages, namely the ordering process, procurement of raw materials, and delivery of products to customers. From the results of observations and interviews, several problems were identified such as the absence of good records in the ordering process resulting in errors in order fulfillment and loss of customer data, dependence on one raw material supplier increases the risk of delays and disruptions in the supply chain and inefficient delivery management caused by human error and no real time tracking, so this has an impact on customer loyalty. This research aims to analyze and model the current business process and provide recommendations for improvement. Modeling is done using Business Process Model and Notation (BPMN) with a qualitative approach to investigate existing business processes. The results of this research can identify areas of improvement to increase the efficiency and effectiveness of MSMEs operations so that MSMEs can better understand, manage, and optimize their business processes. In addition, this research also conducted simulations using the Bizagi Modeler application to test the validity of the business process modeling that has been made. The simulation results show an increase in time in the implementation of business processes.
Arsitektur Enterprise Pengelolaan Masjid Al-Fatih Universitas Buana Perjuangan Karawang Berbasis Zachman Framework Shelly Nur Azizah; April Lia Hananto; Fitria Nurapriani; Baenil Huda
Adopsi Teknologi dan Sistem Informasi (ATASI) Vol. 5 No. 2 (2026): Adopsi Teknologi dan Sistem Informasi (ATASI)
Publisher : Mulawarman University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30872/atasi.v5i2.4579

Abstract

This research was conducted to design an Enterprise Architecture model to support the administrative management of the Al-Fatih Mosque at Buana Perjuangan University, Karawang, which is still done manually and not yet integrated. The main problems include separate financial records, activity management, and inventory, which hamper efficiency and transparency. The method used is the Zachman Framework as a conceptual framework to map organizational needs based on six main perspectives, namely data, function, network, people, time, and motivation. Research data was obtained through observation, interviews, and documentation. The results of the research are in the form of an Enterprise Architecture blueprint design that shows the relationship between organizational business processes and information system elements needed in mosque management. The resulting blueprint is expected to be used as a strategic guideline in developing an integrated information system so as to improve management efficiency, report transparency, and support the implementation of digital-based mosque governance.
Classification of Starling Images Using a Bayesian Network April Lia Hananto; Aviv Yuniar Rahman; Tukino Paryono; Bayu Priyatna; Agustia Hananto; Baenil Huda
Journal of Applied Data Sciences Vol 6, No 1: JANUARY 2025
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v6i1.423

Abstract

The classification of starling species is vital for biodiversity conservation, especially as some species are endangered. This research investigates the effectiveness of the Bayesian Network (BayesNet) for classifying starling species and compares its performance with Artificial Neural Networks (ANN) and Naive Bayes models. The dataset comprises 300 images of five starling species—Bali, Rio, Moon, Kebo, and Uret—captured under controlled conditions. Feature extraction focused on color, texture, and shape, while data augmentation through slight image rotations was applied to enhance model generalization. The BayesNet model achieved an accuracy of 96.29% using a 90:10 training-to-testing split, outperforming ANN (90.74%) and Naive Bayes variants. Precision, recall, F1-score, and AUC-ROC values further validated the robustness of the BayesNet model, with precision at 0.90, recall at 0.91, F1-score at 0.92, and AUC-ROC at 0.95. These results demonstrate the superior performance of multi-feature Bayesian Networks in starling classification compared to other machine learning models. The novelty of this study lies in its application of a probabilistic approach using Bayesian Networks, which enhances interpretability and performance, especially in scenarios with limited data. Future work may explore additional feature sets and advanced machine learning models to further improve classification accuracy and robustness.
Co-Authors - Faqih Abdullah Abdullah Abdullahi Tanko Mohammed Abdullahi Tanko Mohammed Adittia Agustian Afra, Alfina Fadhilah Agneresa Agneresa Agustia Tia Hananto Ahmad Fauzi Ahmed Sule Alparizi, Muhamad Iqbal Alpian, Yayan alzahra, alika aziza Anis Fitri Nur Masruriyah Anita Khansa Ramadanti Anthony Chukwunonso Opia Aprilia Putri Nardilasari Arkan Hilman Hakim Asep Haris Atmaja, Rashelin Zahra Attaya Faiharani 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 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 Deden Wahiddin Detrie Noviani Dhany Hermansyah Dien Noviany Rahmatika Edrina Christine, Natalie Eichler, Luiz Eko Pramono Eko Sediyono Elfina Novalia Elsa Rosalina Esam Abu Baker Ali Fatlun, Aulia Fatmanisa Mumpuni Delta Maharani Fauzi Ahmad Muda Firdaus, Mohamad Ricky Firman Nurdiansyah Firman Nurdiyansyah Fitri Nurapriani Fitria Nur Apriani Fitria Nurapriani Fitria Nurapriani Fuad anwar yuwono Gefira Rahmaifha Guntur, Muhamad Hananto, Agustia Hanny Hikmayanti Handayani 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* Kurnia, Nisa Lutfiah, Siti Mega Tri Kurnia Melisa Miswadi Miswadi Moh Hasan Basri Mohamad Ricky Firdaus Mubarok, Piky Muhamad Djaka Permana Muhammad Abil Fadli Muhammad Fahmi Miskon Muhammad Idris Muhammad Idris Muhammad Idris Muhammad Nova Muhammad Zacky Asy'ari Muthia Nur Rizky Fitriani Naufal Zubdi Ahnaf Nisa Kurnia Novalia, Elfina Novia Cahya Utami Nur ‘Azah Nurapriani, Fitria Nurapriani, Nurapriani Nurfajria, Dera Nursyifa Paryono, Tukino Permana Andi Paristiawan Permana Andi Paristiawan Pradana Rizki Maulana Prasetya, Rafli Prasetyo Ajie Pratama, Daffa Agung Priatna, Bayu Priyatna , Bayu Priyatna, Bayu Purnomo, Hendryanto Dwi Putri Indraswari Reformasi, Era Rieke Retnosary Rukmanta Jayawiguna Ruliansyah Ruliansyah Ruliansyah Ruliansyah, Ruliansyah Saepul Aripiyanto Safarudin Gazali Herawan Sari, Nurnilam Sarina Sulaiman Sarina Sulaiman Setiawan, Feddy Wanditya Setiawan, Pratama Wahyu Shelly Nur Azizah 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 Sofia Ramadanti Az-Zahra 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 Tukino, Tukino Vina Andini Yazid, Muhammad Abi Yovika Aprianti Yoviyardi, Rama