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All Journal Jurnal Penelitian Saintek Teika Jurnal Buana Informatika JSI: Jurnal Sistem Informasi (E-Journal) JUTI: Jurnal Ilmiah Teknologi Informasi Jurnal Edukasi dan Penelitian Informatika (JEPIN) Jurnas Nasional Teknologi dan Sistem Informasi Annual Research Seminar ANDHARUPA CESS (Journal of Computer Engineering, System and Science) Jurnal Ilmiah KOMPUTASI Sistemasi: Jurnal Sistem Informasi Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) RABIT: Jurnal Teknologi dan Sistem Informasi Univrab JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Information System for Educators and Professionals : Journal of Information System MBR (Management and Business Review) JOURNAL OF APPLIED INFORMATICS AND COMPUTING SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi J I M P - Jurnal Informatika Merdeka Pasuruan Jurnal Sisfokom (Sistem Informasi dan Komputer) KACANEGARA Jurnal Pengabdian pada Masyarakat Jiko (Jurnal Informatika dan komputer) Jurnal ULTIMA InfoSys Jurnal Teknologi Sistem Informasi dan Aplikasi Jurnal Ilmiah Media Sisfo The IJICS (International Journal of Informatics and Computer Science) JURIKOM (Jurnal Riset Komputer) JURTEKSI Jurnal Riset Informatika JOISIE (Journal Of Information Systems And Informatics Engineering) CCIT (Creative Communication and Innovative Technology) Journal JUSIM (Jurnal Sistem Informasi Musirawas) INFOMATEK: Jurnal Informatika, Manajemen dan Teknologi Building of Informatics, Technology and Science Journal of Information Systems and Informatics Jurnal Teknologi Dan Sistem Informasi Bisnis Zonasi: Jurnal Sistem Informasi Jurnal Pengabdian Masyarakat Bumi Raflesia JATI (Jurnal Mahasiswa Teknik Informatika) JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) SOSIOEDUKASI : JURNAL ILMIAH ILMU PENDIDIKAN DAN SOSIAL Jurnal Sistem Komputer dan Informatika (JSON) Teknomatika (Jurnal Teknologi dan Informatika) REKA ELKOMIKA: Jurnal Pengabdian kepada Masyarakat KLIK: Kajian Ilmiah Informatika dan Komputer Decode: Jurnal Pendidikan Teknologi Informasi JUSTIN (Jurnal Sistem dan Teknologi Informasi) Konstelasi: Konvergensi Teknologi dan Sistem Informasi Jurnal Algoritma Malcom: Indonesian Journal of Machine Learning and Computer Science Jurnal Masyarakat Madani Indonesia SmartComp Jurnal Informatika: Jurnal Pengembangan IT The Indonesian Journal of Computer Science JuTISI (Jurnal Teknik Informatika dan Sistem Informasi) Jurnal Komtika (Komputasi dan Informatika)
Allsela Meiriza, Allsela
Universitas Sriwijaya
Agriculture, Biological Sciences & Forestry Arts Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mechanical Engineering Medicine & Pharmacology Nursing Public Health Social Sciences Other

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User Experience Evaluation of YouTube Website Using Eye Tracking Method Larasati, Salsabila; Putra, Pacu; Oktadini, Nabila Rizky; Meiriza, Allsela; Sevtiyuni, Putri Eka
Journal of Applied Informatics and Computing Vol. 9 No. 1 (2025): February 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i1.8743

Abstract

YouTube is one of the most popular social media in Indonesia, with one of its features being the Clip Feature, which allows users to share 5-60 seconds video snippets, but many users still experience difficulty in accessing this feature. Based on a survey of more than 130 respondents, 60% were unaware of the Clip Feature, 85% had never used it, and 75% had difficulty finding its location in the YouTube interface. This research aims to evaluate the user experience in accessing the Clip Feature on the YouTube website using the Eye Tracking method, as well as analyzing user attention patterns. Through the RealEye.io tool, the results show that the quality of the test data is very good, with an average E-T data integrity value of 90.33% and gaze on screen of 89.73%. Heatmaps and gaze plot analysis show that respondents' attention patterns tend to show confusion, especially when looking for the Clip feature. This is supported by the results of the attention & emotion graphs analysis, which overall show that the average attention level of respondents is at 0.318, with an increase in the emotion of surprise experienced by respondents more than the emotion of happy. Although the Clip Feature offers significant benefits, users still experience difficulties in accessing it, which results in a decreased user experience. This research is expected to provide new recommendations in improving the user experience of YouTube website, specifically to make the Clip feature more accessible and effective to use.
Knowledge Extraction Using Aspect-Based Sentiment Analysis and Classification Method Inayah, Anna Fadilla; Tania, Ken Ditha; Wedhasmara, Ari; Meiriza, Allsela
JEPIN (Jurnal Edukasi dan Penelitian Informatika) Vol 10, No 3 (2024): Volume 10 No 3
Publisher : Program Studi Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26418/jp.v10i3.83389

Abstract

In this modern era, the use of technology in various fields of life is growing, especially in the financial sector such as digital payments. Digital payments are transactions made via the internet with various forms or electronic payment applications. This research utilizes one of the e-wallet applications, namely the DANA Application. As one of the digital payment applications, DANA's service quality is an important factor in competing with various e-wallet applications or other competitive digital payment applications, sentiment analysis of massive amounts of incoming review data is needed to understand user perceptions and satisfaction levels in order to help companies in decision making. This research analyzes 69632 user review data from May 1 to June 28, 2024, then classifies reviews into positive, negative, and neutral reviews based on aspects to find out the dominant aspects in the review data, as for the aspects determined in this study are mobile applications, interfaces, service performance, and security. This research compares various classification method algorithms to determine the performance of the model, the comparison results show that the Random Forest algorithm has the best performance of other algorithms studied based on evaluation metrics with accuracy 0.82, precision 0.82, recall 0.82, f1_score 0.82, AUC-ROC 0.92, and Cross Validation Mean Accuracy 0.822. This research is expected to produce useful and computerized knowledge extraction and provide perceptual understanding, user satisfaction, and insight into the most effective algorithms which can then help companies in making decisions in the future.
Evaluation of the Maturity Level of the RS SIM System using the Cobit 5 Framework in the Evaluation Direct and Monitoring Domain Rezeki, Yunika Tri; Oktadini, Nabila Rizky; Putra, Pacu; Sevtiyuni, Putri Eka; Meiriza, Allsela
Sistemasi: Jurnal Sistem Informasi Vol 14, No 1 (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.v14i1.4889

Abstract

The purpose of using the COBIT 5 framework in the Evaluate, Direct, and Monitor (EDM) domain in this study is to assess the maturity level of the Hospital Information Management System (HIMS) at the Primaya Hospital Laboratory. The evaluation process focuses on three main aspects: EDM01 (Governance Framework Setting and Maintenance), EDM02 (Ensuring Risk Optimization), and EDM05 (Ensuring Transparency). Data were collected by involving the hospital’s IT team through questionnaires and interviews. Based on the analysis, the current maturity level of the HIMS ranges from level 2 to level 4, with a target of achieving level 4 (Predictable Process). A GAP analysis was conducted to compare the current system condition (as-is) with the desired condition (to-be). This study provides improvement recommendations, including the optimization of system governance and the enhancement of IT performance transparency. These recommendations are expected to support increased efficiency, effectiveness, and the strategic value of the Hospital Information Management System (HIMS) at Primaya Hospital.
Increasing Farmer Groups Capacity in Cempaka District through the Utilization of Mobile-Based Knowledge Management and Strengthening Digital Literacy Putra, Pacu; Oktadini, Nabila Rizky; Irmawati, Irmawati; Meiriza, Allsela; Sevtiyuni, Putri Eka
REKA ELKOMIKA: Jurnal Pengabdian kepada Masyarakat Vol 6, No 1 (2025): Reka Elkomika
Publisher : Institut Teknologi Nasional, Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26760/rekaelkomika.v6i1.76-87

Abstract

Kelompok Tani (Poktan) Hidup Baru is located in Cempaka District, East Ogan Komering Ulu (OKU) Regency, 123 km away from Sriwijaya University. Poktan Hidup Baru was established in 2020 by farmers in Cempaka District and is led by Ali Fauzan. With 29 members, most of them are rice and fruit farmers. The limited technology and literacy of the farmers means that they are not able to innovate. Therefore, the main problem in the Community Partnership Empowerment Programme is the lack of digital literacy and agricultural knowledge management skills. Therefore, this PKM programme aims to introduce knowledge management and improve farmers' skills in using the internet and mobile-based agricultural applications. In addition, this PKM programme also aims to support the transformation of higher education through the production of scientific publications and audio-visual works.Service activities are carried out in five stages: first, preparation; second, production of materials; third, advice; fourth, support; and fifth, monitoring.  The team provides advice and training on the culture of knowledge sharing and the use of agricultural applications such as Plantix. This application can help solve agricultural problems in identifying pests and plant diseases, irrigation and marketing agricultural products. The positive response from the Hidup Baru farmer group indicates the need for similar training in the future to improve farmers' knowledge and skills.
Comparison of Rating-based and Inset Lexicon-based Labeling in Sentiment Analysis using SVM (Case Study: GoBiz Application Reviews on Google Play Store) Firda, Hiliah; Putra, Pacu; Oktadini, Nabila Rizky; Sevtiyuni, Putri Eka; Meiriza, Allsela
Sistemasi: Jurnal Sistem Informasi Vol 14, No 2 (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.v14i2.4795

Abstract

Digital transformation has impacted various sectors, including Micro, Small, and Medium Enterprises (MSMEs). GoBiz, a partner platform for Gojek's GoFood service, plays a crucial role in supporting MSME digitalization, making it essential to understand user perceptions of the application. This study conducts sentiment analysis on 5,000 GoBiz user reviews from the Google Play Store. It compares two labeling methods—Rating-Based and Inset Lexicon—and evaluates them using the Support Vector Machine (SVM) algorithm. The analysis process includes data selection, text preprocessing, data transformation using TF-IDF, SVM implementation with 10-fold cross-validation, and result visualization through word clouds. The findings indicate that the Rating-Based labeling method achieved an accuracy of 87%, with a precision of 86.7%, recall of 87.1%, and an F1-score of 86.8%. Meanwhile, the Inset Lexicon labeling method outperformed it, achieving an accuracy of 89.7%, precision of 89%, recall of 89.8%, and an F1-score of 89.3%. These results suggest that the combination of the Inset Lexicon labeling method and the SVM algorithm is more effective in classifying user sentiment and providing a more accurate understanding of user perceptions regarding the GoBiz application. Sentiment analysis results indicate that users appreciate GoBiz’s ease of operation but face challenges with driver services and advertisement features, highlighting areas for improvement to enhance user satisfaction.
Penerapan Metode Simple Multi Attribute Rating Technique Pada Pemberian Bonus Tahunan Karyawan Sari Andriani; Allsela Meiriza
Jurnal Teknik Informatika dan Sistem Informasi Vol 7 No 3 (2021): JuTISI
Publisher : Maranatha University Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28932/jutisi.v7i3.4079

Abstract

Employees are one of the most important aspects of a company. Quality employees will improve the quality of the company. To encourage employees to give their best to the company, companies can give bonuses to their employees. PT Budi Gema Gempita (BGG) is one of the companies that provides annual bonuses to its employees. In determining which employees will receive bonuses, PT Budi Gema Gempita (BGG) still uses paper to make an assessment. a decission support system is needed which can help Budi Gema Gempita (BGG), especially Human Resource Development (HRD) and division heads in the process of giving bonuses. The Simple Multi Attribute Rating Technique (SMART) method will be used because of its simplicity at responding to the needs of decision makers and how it responds. SMART is a multi-criteria decision method and a linear additive model to predict the value of each option. The use of SMART method is expected to provide the best recomendations for leaders to provide bonuses to employees
Prediksi Harga Emas Indonesia Menggunakan Model CNN-LSTM Septiana, Rika; Putri, Adetya Rielisa; Maharani, Wardah Shifa; Gultom, Gina Destia; Simanullang, Eka Darmayanti; Tania, Ken Dhita; Meiriza, Allsela; Rifai, Ahmad
INFOMATEK Vol 27 No 1 (2025): Juni 2025
Publisher : Fakultas Teknik, Universitas Pasundan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23969/infomatek.v27i1.24417

Abstract

Harga emas memiliki volatilitas tinggi yang menjadikannya menarik untuk dianalisis secara prediktif. Penelitian ini bertujuan untuk memprediksi harga emas Indonesia dengan kombinasi model Convolutional Neural Network dan Long Short-Term Memory (CNN-LSTM) berdasarkan data historis yang berjumlah 4.434 data dari PT Antam Tbk dari periode 2010 sampai 2025. Model ini dibangun menggunakan lapisan Conv1D (satu dimensi) untuk ekstraksi fitur dan dua lapisan LSTM untuk memahami pola waktu. Pengujian dilakukan dengan tiga variasi jumlah epoch pelatihan, yaitu 50, 100, dan 150, lalu hasilnya dievaluasi menggunakan metrik Root Mean Square Error (RMSE). Model terbaik ditemukan pada epoch 100 dengan nilai RMSE data pelatihan sebesar 5.811,51 dan data uji sebesar 13.236,10. Hasil ini menunjukkan bahwa model CNN-LSTM mampu mengenali pola harga emas lebih baik dibandingkan skenario lain. Dengan demikian, penelitian ini dapat dimanfaatkan untuk membantu para investor dalam mengambil keputusan investasi dan sebagai dasar pengembangan sistem prediksi harga komoditas lainnya.
Pengembangan Game Android Pada Anak Menggunakan Pendekatan User Centered Design Dan Evaluasi Usability Think Aloud Alvico, Alvico; Kurniawan, Dedy; Meiriza, Allsela; Syahbani, Muhammad Husni; Firnando, Ricy
The Indonesian Journal of Computer Science Vol. 14 No. 3 (2025): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v14i3.4396

Abstract

Technology, especially handheld devices, has become an integral part of modern life. The use of handheld devices among children aged 12-15 years reaches 99.61%. Despite the potential to cause dependency, these devices can be utilized positively, for example through learning with educational games. One of them is a titungan game that aims to increase user motivation and skills. However, the development of this game must also consider user needs. This research applies the User Centered Design method to improve the experience and comfort of playing, and the Think Aloud method as an evaluation. This study involved 8 participants consisting of children with an age range of 10-14 years. The results showed that the developed application has met the needs of users, with only two problems identified from 64 total evaluation scenarios with a percentage of 96.87% using the Think Aloud method.
PENDEKATAN KLASIFIKASI DALAM KNOWLEDGE DISCOVERY UNTUK ANALISIS SENTIMEN BERBASIS ASPEK PADA ULASAN BANDARA SULTAN MAHMUD BADARUDDIN II DI GOOGLE MAPS Nachwa, Syakillah; Khoiriyah Harahap, Dayana; Theresia Pardede, Eva; Nashiroh Ramadhani, Muthia; Anindya Putri, Salsa; Rositiani, Ely; Ditha Tania, Ken; Meiriza, Allsela
JATI (Jurnal Mahasiswa Teknik Informatika) Vol. 9 No. 3 (2025): JATI Vol. 9 No. 3
Publisher : Institut Teknologi Nasional Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36040/jati.v9i3.13776

Abstract

Sultan Mahmud Badaruddin II (SMB II) merupakan bandara utama di Sumatera Selatan yang berperan krusial untuk mobilitas regional. Kepuasan penumpang terhadap layanan bandara dapat dievaluasi melalui ulasan pengguna di Google Maps. Namun, volume ulasan yang besar menghadirkan tantangan dalam mengekstrak informasi yang bermakna. Studi ini menggunakan Aspect-Based Sentiment Analysis (ABSA) untuk melihat opini publik terhadap layanan Bandara SMB II menggunakan pendekatan klasifikasi dengan enam aspek yang dianalisis, yaitu check-in, keamanan, kenyamanan, lingkungan bandara, fasilitas dasar, dan mobilitas. Sebanyak 1.018 ulasan diperoleh dan diproses melalui tahapan preprocessing, data labeling, penyeimbangan data dengan SMOTE, ekstraksi fitur (TF-IDF), serta klasifikasi menggunakan algoritma Naïve Bayes, Support Vector Machine (SVM), dan Random Forest dengan skenario pembagian data 70:30, 80:20, dan 90:10. Hasil evaluasi menunjukkan bahwa skenario terbaik diperoleh pada perbandingan 90:10, yaitu model SVM mencapai kinerja terbaik dengan nilai accuracy sebesar 0.857, precision 0.839, recall 0.883, dan F1-score 0.860 melampaui Naïve Bayes dan Random Forest. Analisis sentimen telah menunjukkan bahwa aspek lingkungan bandara menerima sentimen positif tertinggi, tetapi aspek fasilitas dasar cenderung menerima ulasan negatif. Pengetahuan ini bisa menjadi dasar bagi pengelola Bandara SMB II untuk meningkatkan layanan mereka berdasarkan aspek-aspek yang paling berpengaruh terhadap pengalaman penumpang.
KOMPARASI RIDGE REGRESSION, RANDOM FOREST, DAN GRADIENT BOOSTING UNTUK PREDIKSI CURAH HUJAN HARIAN DI SUMATRA SELATAN BERBASIS TIME SERIES CROSS-VALIDATION Alvines, Mahendi; Ravi Wijayanto, Muhammad; Archi Daffa Danendra, Muhammad; Rizky Herdiansyah, Muhammad; Karimsyah Lubis, Muhammad; Ichsan Farel Rachmad, Muhammad; Ditha Tania, Ken; Meiriza, Allsela
JATI (Jurnal Mahasiswa Teknik Informatika) Vol. 9 No. 4 (2025): JATI Vol. 9 No. 4
Publisher : Institut Teknologi Nasional Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36040/jati.v9i4.13915

Abstract

Penelitian ini menganalisis pendekatan komparatif model regresi linear dan non-linear untuk prediksi curah hujan di Sumatera Selatan, Indonesia, menggunakan data klimatologi BMKG tahun 2024. Hal tersebut didasarkan pada perubahan iklim yang meningkatkan ketidakpastian pola curah hujan di Sumatera Selatan, mengancam sektor pertanian dan pengelolaan air. Komparasi ini bertujuan untuk membandingkan kinerja model regresi linear dan non-linear untuk prediksi curah hujan harian di Sumatera Selatan, serta mengidentifikasi prediktor utama yang memengaruhi curah hujan. Metodologi penelitian mengadopsi kerangka Knowledge Discovery in Database (KDD) dengan tahapan pengumpulan data, pra-pemrosesan, transformasi, pemodelan, dan evaluasi. Lima model machine learning dibandingkan: Linear Regression, Ridge Regression, Lasso Regression, Random Forest, dan Gradient Boosting, dengan validasi menggunakan TimeSeriesSplit untuk mempertahankan struktur temporal data. Hasil analisis menunjukkan Ridge Regression sebagai model terbaik dengan RMSE 14.62 mm, meskipun nilai R² negatif (-0.69) mengindikasikan keterbatasan model dalam menangkap variabilitas penuh data. Analisis koefisien regresi Ridge menunjukkan bahwa RR_LAG_1 juga berkontribusi signifikan (koefisien: 0.45). Konsistensi prediktor antar model memperkuat validitas temuan, sedangkan model secara konsisten mengalami kesulitan memprediksi kejadian curah hujan ekstrem (>50 mm). Pendekatan berbasis ensemble (Random Forest/Gradient Boosting) menunjukkan stabilitas prediksi lebih tinggi dengan deviasi RMSE <5 mm. Penelitian ini dapat memberikan masukan bagi pengembangan model prediksi curah hujan yang dapat mendukung sektor pertanian, pengelolaan sumber daya air, dan mitigasi bencana di Sumatera Selatan. Studi lanjutan dengan model hybrid dan dataset yang lebih lengkap disarankan untuk validasi lebih lanjut.
Co-Authors Abdurahman, Gibral Adhiyasa, Chandra Julian Adriansyah, Rizki Ahmad Rifai Ahmad Rifai Ahmad Rifai Ahmad Rifai Aisyah Fatimah Akbar Alzaini Akbar Alzaini Al Fachrozi, Muhammad Al-Farisy, M Hadi Alfarizi, M. Alfitrah, Intan Aidita Ali Ibrahim Alinda, Yelli Nur Alvico, Alvico Alvines, Mahendi Alya Zalfa Chairunnisa Alzaini, Akbar Amanda, Bella Rizkia Anadia, Qothrunnada Wafi Ananda Khoirunnisa Andini Bahri, Cheisya Andriani, Sari Ani Nidia Listianti, Ani Nidia Anindya Putri, Salsa Anna Dwi Marjusalinah Annisa Tri Ning Tyas Apriansyah Putra Archi Daffa Danendra, Muhammad Ari Wedhasmara Ariyani, Ishlah Putri Ariyanti, Putri Arnan, Sefian Arvhi Randita Setia Athallah Ubaid, Deni Ayu, Nabila Riska Ayuningtiyas, Pratiwi Az-Zahra, Nanda Salsabila Azera Pramesty Bayu Wijaya Putra Beriadi Agung Nur Rezqe Billan, Angel Caroline Cahyo Adi Nugraha Chandra Julian Adhiyasa Cindy Dinata Cynthia Sherina Fadeli Danendra, Devano Dedy Kurniawan Deni Lidianti Desty Rodiah Devano Danendra Dinda Lestarini Dinna Yunika Hardiyanti Dinna Yunika Hardiyanti Dinna Yunika Herdiyanti Dwi Rosa Indah Endang Lestari Ruskan Endang Lestari Ruskan Epriyanti, Nadia Ermatita - Fahren Affandi Faizah, Ovie Nur Fathoni - Fathoni - Fatimah Salsabila Firda, Hiliah Frans Nicko Apriansyah Gabriel Sebastian Santoso Gultom, Gina Destia Gusti Barata Hakim, Adzka Fahmi Aulia Hardini Novianti Hardini Novianti Hardini Novianti Hardini Novianty Ichsan Farel Rachmad, Muhammad Idpal, Idpal Imam Akbar Inayah, Anna Fadilla Intan Aidita Alfitrah Irmawati Irmawati Irwansyah, Muhammad Aziiz Izzan Fieldi, Muhammad Jackson Imanuel Manurung Jaidan Jauhari Jambak, Muhammad Ihsan Jefven Fernando Jeremiah Alwin Siahaan Jonathan Pakpahan Juliyanti, Tamara Karima, Dzakiah Aulia Karimsyah Lubis, Muhammad Karisa Anjani Fakhri Ken Dhita Tania Ken Dhita Tania Ken Dhita Tania, Ken Dhita Ken Ditha Tania Ken Ditha Tania Khairani, Annisa Khoiriyah Harahap, Dayana Khoirusy Syafaat Lailla Syal Syabilla Larasati, Salsabila Lifiano Jamot Munthe, Gabriel Luh Sri Mulia Eni M Naufal Hisyam M Rifki Ali M, Nys Marliza Tiara M. Ilham Fahlevi M. Rudi Sanjaya M. Thoriqul Fadli Maharani, Wardah Shifa Maretta, Aulia Maretta, Aulia Pinkan Mariska, Inneke Via Marpaung, Xenia Clarissa Valencia Mei Intan Natasyah Meiriza, Viola Meitiana Audya Merizka Azzahra Mira Afrina Mohd Rizky Putra Pratama Muhamad Edric Rasyid Muhammad Aidil Fitri Syah Muhammad Ali Buchari Muhammad Azmi Zaky Muhammad Dzaky Hasyim Muhammad Husni Syahbani Muhammad Ihsan Muhammad Imam Riadillah Muhammad Wahyu Hikmalsyah Mulyadi Mulyadi Munaspin, Zahra Diva Putri Nabila Oktadini Nabila Riska Ayu Nabila Rizki Oktadini Nabilaputri, Silvia Nachwa, Syakillah Nadia Ayu Safitri Naretha Kawadha Pasemah Gumay Nashiroh Ramadhani, Muthia Nawirah Athqiyah Novitia Chinoi Nurul Izmy Nur’Aini, Risma Nyimas Silvia Oktadini, Nabila Oktadini, Nabila Rizky Onkky Alexander Pacu Putra Pacu Putra Padlefi, Muhamad Riza Pakpahan, Jonathan Paulus Paskah Lino Susilo Perdani, Tharisa Antya Pinkasari, Aulia Putri Ariyanti Putri Eka Sevtiyuni Putri Eka Sevtiyuni Putri Eka Sevtyuni Putri Mutiara Arinie Putri Setiyawati Putri, Adetya Rielisa Putri, Meiyin Monica Amilia Putri, Nyayu Dwi Tarisa RA Aliffyaa Ramadhani Rafika Octaria Ningsih Rafli Maulana, Muhammad Rahmat Izwan Heroza Ramadhan Putra Pratama, Muhammad Ramadhan, Kumara Aditya Ramadhan, Muhammad Gilang Rangga Aderiyana, Fakih Rani Mardiah Ravi Wijayanto, Muhammad Rezeki, Yunika Tri Rezqe, Beriadi Agung Nur Ricy Firnando Rido Zulfahmi Rika Septiana Riska Yunita Risma Nur Aini Rizka Dhini Kurnia Rizka Dhini Kurnia Rizka Rahmadhani Rizki Kurniati Rizky Herdiansyah, Muhammad Rizky Sawitri Rizkyllah, Anabel Fiorenza Rizqi, Ahmad Fadhil Rositiani, Ely Royan Dwi Saputra RR. Ella Evrita Hestiandari Salsabila, Fatimah Sanjaya, M. Rudi Saputri, Sonia Dwi Sari Andriani Sarifah Putr Raflesia Sarifah Putri Raflesia Sasmita, Ruth Mei Sawitri, Rizky Sella Juniastia Marsya Saputri Septhia Charenda Putri Sevtiyuni, Putri Eka Simanullang, Eka Darmayanti Susanti, Helen Susilo, Paulus Paskah Lino Syahbani, Muhammad Husni Syarief Albani, Muhammad Tharisa Antya Perdani Theresia Pardede, Eva Titiana, Nuke Merisca Tri Mutiara Illahi Tri Zafira, Zahra Tsabitah, Laila Vanisa Amalia Putri Via Mariska, Inneke Wahyudi, Muhammad Iqbal Wulan Dari, Atikah Yadi Utama Yadi Utama Yasir Alghifari, Muhammad Yasyfi Imran, Athallah Yelli Nur Alinda Yoga Fradana Yunika Hardiyanti, Dinna Yunita Yunita Zaki, Imam Syahputra Zaqqi Yamani Zwesty Quatra