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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
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Sistem Monitoring Dan Visualisasi Data Konsumsi Energi Listrik Rumah Berbasis IoT Dengan Aplikasi Blynk Setiawan, Pratama Wahyu; Hananto, April Lia; Novalia, Elfina; Hananto, Agustia
Jutisi : Jurnal Ilmiah Teknik Informatika dan Sistem Informasi Vol 14, No 1: April 2025
Publisher : STMIK Banjarbaru

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35889/jutisi.v14i1.2675

Abstract

Household electricity consumption continues to increase, but monitoring of electricity use is still limited to the KwH meter which only shows the total usage without real-time details. This research aims to design an Internet of Things (IoT)-based electrical energy consumption monitoring system with the Blynk application as a data visualization medium. The system is designed using a PZEM-004T sensor to measure voltage, current, and power, as well as a ESP8266 NodeMCU microcontroller to transmit data to the Blynk application over a WiFi connection. System testing is carried out using the black box method to evaluate the functionality of each feature without looking at internal processes. The test results showed that the system can display electricity consumption data in real-time, work stably, and allow remote monitoring via smartphone. The system also helps users recognize electricity usage patterns, supports decision-making in energy savings, and provides historical data for long-term usage evaluation.Keywords: Internet Of Things; Monitoring Listrik; NodeMCU ESP8266; Blynk; PZEM-004T AbstrakKonsumsi energi listrik rumah tangga terus meningkat, namun pemantauan penggunaan listrik masih terbatas pada KwH meter yang hanya menunjukkan total pemakaian tanpa detail real-time. Penelitian ini bertujuan merancang sistem monitoring konsumsi energi listrik berbasis Internet of Things (IoT) dengan aplikasi Blynk sebagai media visualisasi data. Sistem dirancang menggunakan sensor PZEM-004T untuk mengukur tegangan, arus, dan daya, serta mikrokontroler NodeMCU ESP8266 untuk mengirimkan data ke aplikasi Blynk melalui koneksi WiFi. Pengujian sistem dilakukan dengan metode Black box untuk mengevaluasi fungsionalitas tiap fitur tanpa melihat proses internal. Hasil pengujian menunjukkan bahwa sistem dapat menampilkan data konsumsi listrik secara real-time, bekerja dengan stabil, dan memungkinkan pemantauan jarak jauh melalui smartphone. Sistem ini juga membantu pengguna mengenali pola penggunaan listrik, mendukung pengambilan keputusan dalam penghematan energi, serta menyediakan data historis untuk evaluasi penggunaan jangka panjang. 
Analisis Sentimen Aplikasi Bank Digital Pada Google Play Store Menggunakan Algoritma Naive Bayes Arkan Hilman Hakim; Hananto, April Lia; Nurapriani, Fitria; Huda, Baenil
Journal of Informatics and Communication Technology (JICT) Vol. 7 No. 1 (2025)
Publisher : PPM Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52661/jict.v7i1.405

Abstract

Pesatnya perkembangan teknologi perbankan digital telah mendorong munculnya beragam aplikasi perbankan yang tersedia di Google Play Store. Ulasan pengguna terhadap aplikasi-aplikasi ini menjadi sumber informasi yang berharga untuk menilai tingkat kepuasan mereka, yang kemudian dapat dianalisis melalui pendekatan sentiment analysis. Penelitian ini dilakukan untuk mengkaji kecenderungan sentimen pengguna terhadap beberapa aplikasi bank digital dengan memanfaatkan algoritma Naïve Bayes. Data yang dianalisis berasal dari 1.000 ulasan pengguna untuk masing-masing aplikasi, yaitu Seabank, Krom Bank, Bank Jago, Blu by BCA, dan Bank Saqu. Seluruh proses analisis dan pengolahan data dilakukan menggunakan platform Google Colab, dengan menerapkan metode Multinomial Naïve Bayes (MNB) untuk mengklasifikasikan sentimen ke dalam dua kategori, yaitu positif dan negatif. Hasil penelitian mengungkapkan bahwa Seabank menunjukkan performa tertinggi, dengan accuracy sebesar 94%, precision 93%, recall 100%, dan F1-score 97%, serta total 945 ulasan positif dan 55 ulasan negatif. Temuan ini memperlihatkan bahwa analisis sentimen dapat memberikan masukan yang bernilai bagi pengembang untuk meningkatkan kualitas aplikasi, sekaligus menjadi panduan bagi pengguna dalam memilih layanan perbankan digital yang sesuai dengan preferensi kebutuhan.
KLASIFIKASI DAN PREDIKSI ULASAN APLIKASI DANA PADA GOOGLE PLAY STORE MENGGUNAKAN ALGORITMA NAÏVE BAYES Hayati, Cucu; Tukino; Hilabi, Shofa Shofiah; Hananto, April Lia
Jurnal Informatika Teknologi dan Sains (Jinteks) Vol 7 No 2 (2025): EDISI 24
Publisher : Program Studi Informatika Universitas Teknologi Sumbawa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51401/jinteks.v7i2.5691

Abstract

Di era digital saat ini, kemajuan teknologi yang pesat telah mendorong masyarakat beralih ke transaksi digital melalui financial technology (Fintech), salah satu inovasi fintech yaitu aplikasi DANA. Penelitian ini bertujuan untuk mengklasifikasi dan prediksi ulasan aplikasi DANA menggunakan Naïve Bayes. Dengan jumlah data 1.500 ulasan kemudian dilabeli berdasarkan kategori transaksi, keamanan, kinerja Aplikasi, pelayanan, serta aktivasi dan verifikasi. Tahapan penelitian ini dilakukan mulai dari pengumpulan data, pelabelan manual , preprocessing , pembobotan kata, model Naïve Bayes , dan evaluasi. Berdasarkan hasil analisis, tingkat akurasi yang diperoleh adalah sebesar 87%, dengan presisi mencapai 88%, recall sebesar 84%, dan f1-score sebesar 85%. Akurasi mengacu pada persentase prediksi yang benar dari keseluruhan data. Presisi menunjukkan seberapa tepat model dalam memprediksi suatu kelas tertentu, recall mengukur kemampuan model dalam menemukan seluruh data termasuk dalam suatu kelas tertentu, dan f1-score menggambarkan keseimbangan antara presisi dan recall. Maka, dapat disimpulkan model bawah pada penelitian ini mampu dalam mengklasifikasikan seluruh kategori dan dapat memberikan prediksi yang akurat, meskipun terdapat perbedaan nilai presisi, recall , dan f1-score . Diharapkan penelitian ini dapat bermanfaat bagi pengembang aplikasi DANA, dan juga dapat memberikan informasi mengenai efisiensi dan efektivitas algoritma Naïve Bayes dalam klasifikasi dan prediksi.
Penerapan Software Testing Life Cycle Pada Pengujian Otomatisasi Platform Dzikra Ruliansyah, Ruliansyah; Tukino; Baenil Huda; April Lia Hananto
CSRID (Computer Science Research and Its Development Journal) Vol. 15 No. 1: February 2023
Publisher : LPPM Universitas Potensi Utama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22303/csrid-.15.1.2023.01-11

Abstract

PT Bejana Investidata Globalindo (BIGIO), as an IT consultant and software development company, develops an in-house product called Dzikra which is a platform to help users build good habits in worship. In order to develop this system, the company requires a daily worship content management system known as the Dzikra web admin. The Software Development Life Cycle (SDLC) has several stages, one of the important stages is the testing stage which has the goal of evaluating whether the software has been created in accordance with the specifications and detects bugs or errors. Black box testing automation with Robot Framework can provide good testing documentation and can reduce human errors during the testing process. The implementation of the Software Testing Life Cycle (STLC) in the testing process can also make the testing flow more structured and provide a better focus on each testing stage. The results of the testing show that of the six features tested, they have run as expected. It is hoped that this research will provide support to PT Bejana Investidata Globalindo (BIGIO) in automating software testing process.
Analisis Sentimen Aplikasi Bank Digital Pada Google Play Store Menggunakan Algoritma Naive Bayes Arkan Hilman Hakim; Hananto, April Lia; Nurapriani, Fitria; Huda, Baenil
Journal of Informatics and Communication Technology (JICT) Vol. 7 No. 1 (2025)
Publisher : PPM Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52661/jict.v7i1.405

Abstract

Pesatnya perkembangan teknologi perbankan digital telah mendorong munculnya beragam aplikasi perbankan yang tersedia di Google Play Store. Ulasan pengguna terhadap aplikasi-aplikasi ini menjadi sumber informasi yang berharga untuk menilai tingkat kepuasan mereka, yang kemudian dapat dianalisis melalui pendekatan sentiment analysis. Penelitian ini dilakukan untuk mengkaji kecenderungan sentimen pengguna terhadap beberapa aplikasi bank digital dengan memanfaatkan algoritma Naïve Bayes. Data yang dianalisis berasal dari 1.000 ulasan pengguna untuk masing-masing aplikasi, yaitu Seabank, Krom Bank, Bank Jago, Blu by BCA, dan Bank Saqu. Seluruh proses analisis dan pengolahan data dilakukan menggunakan platform Google Colab, dengan menerapkan metode Multinomial Naïve Bayes (MNB) untuk mengklasifikasikan sentimen ke dalam dua kategori, yaitu positif dan negatif. Hasil penelitian mengungkapkan bahwa Seabank menunjukkan performa tertinggi, dengan accuracy sebesar 94%, precision 93%, recall 100%, dan F1-score 97%, serta total 945 ulasan positif dan 55 ulasan negatif. Temuan ini memperlihatkan bahwa analisis sentimen dapat memberikan masukan yang bernilai bagi pengembang untuk meningkatkan kualitas aplikasi, sekaligus menjadi panduan bagi pengguna dalam memilih layanan perbankan digital yang sesuai dengan preferensi kebutuhan.
User Experience Design Analysis of the Karawang Job Vacancy Website using the User-Centered Design Method and System Usability Scale Sopian, Jajang; Huda, Baenil; Novalia, Elfina; Hananto, April Lia
Sistemasi: Jurnal Sistem Informasi Vol 14, No 4 (2025): 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.v14i4.5303

Abstract

An optimized User Experience (UX) design plays a significant role in creating a comfortable browsing experience, ensuring good accessibility, and enhancing user satisfaction. This study analyzes the UX design of the Info Loker Karawang website by applying the User-Centered Design (UCD) method and evaluating the resulting prototype using the System Usability Scale (SUS) to assess the website’s ease of use. The UCD method was selected because it places the user at the center of the design process, enabling the development of solutions that align closely with users’ needs, expectations, and characteristics. This approach has proven effective in producing relevant and intuitive interfaces through stages of analysis, design, and evaluation involving active user participation. Following the design phase, the prototype was tested using the SUS instrument to measure how well the design solution met usability and user satisfaction criteria. The evaluation results indicate that applying UCD in website design significantly improves usability, achieving a SUS score of 72.5, which falls into Grade B and is categorized as “Good” on the adjective rating scale. This research provides insights into the importance of user-centered approaches in website development and demonstrates the effectiveness of SUS in evaluating and measuring the success of UX design outcomes.
Penerapan Algoritma Apriori Dalam Menentukan Pola Pergerakan Kebutuhan Distribusi Pada PT. Satria Teknik Indonesia Yoviyardi, Rama; Lia Hananto, April; Nurapriani, Nurapriani; Huda, Huda
Jurnal PROCESSOR Vol 20 No 1 (2025): Jurnal Processor
Publisher : LPPM Universitas Dinamika Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33998/processor.2025.20.1.2207

Abstract

In an increasingly competitive business environment, companies are required to make more precise strategic decisions to enhance operational efficiency. The shift in customer demand trends has become a major challenge faced by PT Satria Teknik Indonesia, a goods distribution company. To address this challenge, the company can leverage transaction data to analyze customer purchasing patterns. By utilizing the results of this analysis, PT Satria Teknik Indonesia can improve the accuracy of customer demand predictions, accelerate data-driven decision-making, and optimize inventory management. One effective method for this analysis is the Apriori algorithm. The data used were obtained from the company's transaction recording system during the period from January 2023 to October 2024 and were analyzed to discover association rules in large datasets and identify relationships between products that are frequently purchased together. The results of this study reveal two items that are prioritized for ordering: Back Support and Safety Shoes Cheetah. If customers purchase Back Support, they are highly likely to also purchase Safety Shoes Cheetah, with a support value of 20.22% and a confidence level of 100%. Conversely, if customers purchase Safety Shoes Cheetah, they tend to also buy Back Support, with a support value of 20% and a confidence level of 94.74%. This study identifies a strong purchasing association pattern between Back Support products and Safety Shoes Cheetah, providing empirical evidence of the benefits of implementing data mining techniques to improve inventory management effectiveness and better respond to customer needs
Klasifikasi Sentimen Komentar Pengguna pada Aplikasi Ruangguru Menggunakan Algoritma Naive Bayes Yovika Aprianti; Tukino; Hananto, April Lia; Hilabi, Shofa Shofiah
METIK JURNAL (AKREDITASI SINTA 3) Vol. 9 No. 1 (2025): METIK Jurnal
Publisher : LPPM Universitas Mulia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47002/metik.v9i1.1023

Abstract

The advancement of digital technology has encouraged the increasing use of online learning applications such as Ruangguru, while simultaneously fostering various innovations in the field of education. Ruangguru, as one of the most popular educational applications in Indonesia, receives thousands of user comments that can be analyzed to reflect user satisfaction and perception. This study aims to automatically classify user comments based on the sentiments they contain using the Naïve Bayes Classifier algorithm. This approach is expected to help Ruangguru developers better understand user needs and preferences, thereby improving service quality. The dataset was obtained from the Google Play Store platform, consisting of approximately 5,000 comments collected during the period from October 28 to December 31, using the google-play-scraper tool. The application of the Multinomial Naïve Bayes algorithm with TF-IDF weighting was employed to analyze the data, resulting in four sentiment categories: Baik Sekali, Baik, Cukup Baik, and Kurang Baik. Evaluation of the model was conducted using accuracy, precision, recall, and F1-score metrics. With an accuracy rate of 84.83%, the model correctly predicted the actual labels in approximately 85% of the test data. The model also achieved an F1-score of 85%, a precision of 86%, and a recall of 85%. The classification results revealed that the “Baik” category dominated with a proportion of 28.3%, followed by “Baik Sekali” at 24.3%, “Cukup Baik” at 24.0%, and “Kurang Baik” at 23.4%. These findings indicate that the model maintains a reasonable balance between sensitivity and accuracy in sentiment classification. Therefore, the Naïve Bayes Classifier method is capable of automatically identifying user opinions and has the potential to serve as a valuable tool in sentiment analysis for online learning services.
Klasterisasi Supplier Berdasarkan Kinerja Menggunakan Algoritma K-Means Afra, Alfina Fadhilah; Hananto, April Lia; Hananto, Agustia; Priyatna, Bayu
Jurnal Teknologi Dan Sistem Informasi Bisnis Vol 7 No 2 (2025): April 2025
Publisher : Prodi Sistem Informasi Universitas Dharma Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47233/jteksis.v7i2.1935

Abstract

Untuk memastikan efisiensi operasional dan kualitas produk, evaluasi kinerja supplier sangat berperan penting dalam bidang perindustrian. PT Percetakan masih menggunakan penilaian subjektif dalam menilai kinerja supplier. Variabel dalam data ini yaitu Supplier, Jumlah Pesanan, Harga Satuan dan Rentang Pengiriman yang dapat dianalisis untuk meningkatkan penilaian kinerja supplier. Penelitian ini menggunakan algoritma K-Means untuk mengklasterisasikan supplier berdasarkan kinerja. Algoritma K-Means dipilih karena dapat mengolah data dalam jumlah besar dan efisien, hasil yang didapat lebih objektif dibanding pendekatan subjektif. Hasil Penelitian ini diharapkan dapat memberikan kontribusi dan solusi yang praktis bagi PT Percetakan untuk menentukan mitra kerja sama melalui penerapan algoritma K-Means. Hasil klasterisasi menunjukkan bahwa terdapat perbedaan yang signifikan antara supplier dalam setiap klaster. Supplier dengan performa terbaik (Klaster 1) cenderung memiliki jumlah pesanan yang tinggi, harga satuan lebih kompetitif, dan waktu pengiriman lebih cepat. Sementara itu, supplier dengan performa rendah (Klaster 3) memiliki harga lebih tinggi dan rentang pengiriman yang lama, yang dapat mempengaruhi efisiensi operasional perusahaan.
Development of Geolocation-Based Employee Attendance Application on Android Mobile Kurnia, Nisa; Hananto, April Lia; Tukino, Tukino; Hilabi, Shofa Shofiah
J-INTECH ( Journal of Information and Technology) Vol 13 No 01 (2025): 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.v13i01.1890

Abstract

The development of mobile-based systems in Indonesia has provided innovative solutions to improve the efficiency of conventional administrative processes, especially in employee attendance. This research aims to develop an Android-based employee attendance application that is integrated with geolocation technology to enable accurate and real-time attendance monitoring. This system is built using the Waterfall method, which includes the stages of needs analysis, system design, implementation using Flutter and Dart programming language, and testing using black box testing techniques. Black-box testing was conducted on six main functions, resulting in a 94% overall success rate. Most functions achieved a 100% pass rate, but two test cases for attendance check in/out failed due to GPS location inaccuracies, highlighting the impact of device and environmental factors. The average response time was 1.28 seconds, and the average GPS delay was 2.1 seconds. The implementation of real-time notifications and admin verification improved transparency and minimized attendance fraud. The results demonstrate that the application provides an effective and efficient solution for employee attendance management. Future work should focus on enhancing location accuracy, conducting non-functional testing, and expanding features to ensure broader adoption and system 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