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All Journal International Journal of Power Electronics and Drive Systems (IJPEDS) JSI: Jurnal Sistem Informasi (E-Journal) Jurnal Pseudocode Jurnal Teknologi Informasi dan Ilmu Komputer INTEKNA POSITIF Journal of Information Systems Engineering and Business Intelligence Annual Research Seminar JPSriwijaya Jurnal Ilmiah KOMPUTASI Sistemasi: Jurnal Sistem Informasi Sinkron : Jurnal dan Penelitian Teknik Informatika Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) RABIT: Jurnal Teknologi dan Sistem Informasi Univrab JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING INTEGER: Journal of Information Technology Syntax Literate: Jurnal Ilmiah Indonesia Jurnal Sains dan Informatika JRMSI - Jurnal Riset Manajemen Sains Indonesia JITK (Jurnal Ilmu Pengetahuan dan Komputer) JOURNAL OF APPLIED INFORMATICS AND COMPUTING JURNAL PENDIDIKAN TAMBUSAI Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI) JURIKOM (Jurnal Riset Komputer) Jurnal Pemberdayaan: Publikasi Hasil Pengabdian Kepada Masyarakat Jurnal Riset Informatika JOISIE (Journal Of Information Systems And Informatics Engineering) Building of Informatics, Technology and Science Jutisi: Jurnal Ilmiah Teknik Informatika dan Sistem Informasi Journal of Information Systems and Informatics Zonasi: Jurnal Sistem Informasi Jurnal Pengabdian Masyarakat Bumi Raflesia Journal of Applied Engineering and Technological Science (JAETS) JATI (Jurnal Mahasiswa Teknik Informatika) Indonesian Journal of Electrical Engineering and Computer Science JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Jurnal Generic Jurnal Teknik Informatika (JUTIF) Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer) Jurnal Informatika dan Teknologi Komputer ( J-ICOM) KLIK: Kajian Ilmiah Informatika dan Komputer Jurnal Abdi Masyarakat Indonesia Jurnal Altifani Penelitian dan Pengabdian kepada Masyarakat Mejuajua Indonesian Journal of Innovation Studies Jurnal Puan Indonesia Jurnal Algoritma Jurnal Akuntansi, Keuangan dan Teknologi Informasi Akuntansi Malcom: Indonesian Journal of Machine Learning and Computer Science DEVOTE: Jurnal Pengabdian Masyarakat Global Jurnal Pengabdian Kolaborasi dan Inovasi IPTEKS Jurnal Abdimas Maduma Jurnal Pengabdian dan Pemberdayaan Masyarakat Indonesia Journal of Management and Innovation Entrepreneurship (JMIE) Jurnal Pengabdian Masyarakat Ilmu Komputer Jurnal Pengabdian Masyarakat Ekonomi dan Bisnis Digital The Indonesian Journal of Computer Science Buffer Informatika Jurnal PETISI (Pendidikan Teknologi Informasi) JUKEMAS : Jurnal Pengabdian Kepada Masyarakat
Ali Ibrahim
Universitas Sriwijaya, Indonesia
Religion Agriculture, Biological Sciences & Forestry Arts Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Neuroscience Nursing Public Health Social Sciences Other

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Analisis Integrasi Internet of Things (IoT) pada Sistem Informasi Manajemen untuk Peningkatan Produktivitas Ibrahim, Ali; Abdillah, Bimo Musthafa; Khaerullah, Muhammad; Amelia, Putri; Permana, Rizki Artinio; Nursodiq, Ahmad
Jurnal Pendidikan Tambusai Vol. 10 No. 1 (2026)
Publisher : LPPM Universitas Pahlawan Tuanku Tambusai, Riau, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/jptam.v10i1.36314

Abstract

Perkembangan teknologi Internet of Things (IoT) memberikan peluang signifikan dalam meningkatkan efisiensi operasional dan produktivitas organisasi. Integrasi IoT dengan Sistem Informasi Manajemen (SIM) memungkinkan akuisisi data secara real-time, pengambilan keputusan yang lebih cepat, serta otomasi proses bisnis. Penelitian ini bertujuan untuk menganalisis bagaimana integrasi IoT diterapkan pada Sistem Informasi Manajemen dan dampaknya terhadap peningkatan produktivitas. Metode penelitian yang digunakan adalah metode deskriptif dengan pendekatan kualitatif melalui studi literatur dan analisis dokumen terkait implementasi IoT dalam SIM. Hasil penelitian menunjukkan bahwa integrasi IoT dapat meningkatkan akurasi data, mempercepat alur informasi, mengurangi beban kerja manual, serta meningkatkan efektivitas pemantauan operasional. Namun, tantangan seperti keamanan data, biaya implementasi, dan kebutuhan infrastruktur digital masih menjadi hambatan utama. Penelitian ini memberikan gambaran menyeluruh mengenai peran IoT dalam memodernisasi Sistem Informasi Manajemen untuk meningkatkan produktivitas organisasi.
Pelatihan Pemanfaatan Teknologi Informasi dan Digital Marketing untuk Meningkatkan Daya Saing UMKM di Desa Sungai Rebo Ali Ibrahim; Endang Lestari Ruskan; Ermatita Ermatita; Fathoni Fathoni; Rizka Dhini Kurnia; Al farissi; Ahmad fali Oklilas; Yadi Utama; Purwita Sari; Naretha Kawadha Pasemah Gumay
Mejuajua: Jurnal Pengabdian pada Masyarakat Vol. 5 No. 3 (2026): April 2026
Publisher : Yayasan Penelitian dan Inovasi Sumatera (YPIS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52622/mejuajuajabdimas.v5i3.339

Abstract

UMKM memiliki peran strategis dalam mendorong pertumbuhan ekonomi lokal, termasuk di Desa Sungai Rebo, Kecamatan Banyuasin I, yang sebagian besar masyarakatnya menggantungkan penghasilan dari usaha kecil di sektor kuliner, kerajinan, dan perdagangan rumah tangga. Meskipun demikian, rendahnya pemanfaatan teknologi informasi serta keterbatasan kemampuan dalam pemasaran digital menyebabkan daya saing produk UMKM di desa tersebut belum berkembang secara optimal. Kondisi ini membuat jangkauan pemasaran produk masih terbatas pada pasar lokal dan belum mampu memanfaatkan peluang pasar yang lebih luas melalui media digital. Kegiatan pengabdian kepada masyarakat ini bertujuan untuk meningkatkan daya saing UMKM di Desa Sungai Rebo melalui penerapan teknologi informasi dan digital marketing sebagai strategi promosi produk secara berkelanjutan. Program ini dilaksanakan melalui pendekatan pelatihan dan pendampingan yang melibatkan pelaku UMKM sebagai mitra utama dalam setiap tahapan kegiatan, mulai dari identifikasi kebutuhan, pelatihan, hingga evaluasi hasil. Metode kegiatan meliputi asesmen awal untuk memetakan kemampuan digital pelaku UMKM, pelatihan penggunaan teknologi informasi dasar seperti pengelolaan perangkat digital dan aplikasi pengolahan foto produk, serta pelatihan digital marketing yang mencakup pembuatan konten promosi dan pemanfaatan media sosial. Selain itu, dilakukan pendampingan intensif dalam implementasi strategi digital marketing sesuai dengan karakteristik usaha masing-masing peserta. Hasil kegiatan menunjukkan adanya peningkatan kemampuan pelaku UMKM dalam memanfaatkan teknologi informasi untuk mendukung kegiatan usaha dan memperluas jangkauan pemasaran produk mereka. Hasil pre-test dan post-test menunjukkan adanya peningkatan signifikan pada pemahaman dasar teknologi informasi. Sebelum kegiatan, hanya 28% peserta yang memahami penggunaan perangkat digital untuk kegiatan bisnis; setelah pelatihan, tingkat pemahaman meningkat menjadi 78%.
Prediksi Lead Scoring untuk Optimasi Penjualan Menggunakan Random Forest dan Teknik SMOTE Pratama Putra, Daffa; Agil Kusuma, Dimas; Al Akbar, M. Rizki; Ibrahim, Ali; Fathoni, Fathoni
JURNAL FASILKOM Vol. 16 No. 1 (2026): Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer)
Publisher : Unversitas Muhammadiyah Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/jf.v16i1.11292

Abstract

Accurate lead scoring systems have become a strategic necessity for organizations operating in data-driven marketing environments, as they enable systematic identification of high-value customer prospects to maximize sales conversion efficiency. A fundamental challenge confronting conventional classification models is the class imbalance inherent in real-world marketing data, which induces majority-class bias and substantially reduces sensitivity toward minority-class prospects. This study proposes a Random Forest (RF)-based lead scoring prediction model integrated with the Synthetic Minority Over-sampling Technique (SMOTE) to address this limitation systematically. The dataset employed is the Lead Scoring Dataset from Kaggle, comprising 9,240 customer prospect records from an educational company with a class imbalance ratio of 1.59:1. Preprocessing included missing value treatment, removal of attributes exceeding 40% data loss, mode-based imputation, and categorical feature encoding. Following an 80:20 stratified split, SMOTE was applied exclusively to the training set to produce a balanced class distribution and prevent data leakage. The RF model was configured with n_estimators = 100, max_features = 'sqrt', and class_weight = 'balanced'. The proposed RF+SMOTE model achieved accuracy of 88.80%, precision of 86.44%, recall of 84.13%, F1-Score of 85.27%, and AUC-ROC of 0.9453, outperforming the baseline across four of five evaluation metrics. The most notable improvement was observed in recall, with a gain of 1.26 percentage points. Stratified 5-Fold Cross-Validation confirmed robust generalization capability, with AUC-ROC values consistently ranging between 94% and 95%. These findings demonstrate that the hybrid RF+SMOTE approach effectively enhances high-potential prospect detection while maintaining overall model stability for real-world Customer Relationship Management (CRM) deployment.
Identifikasi Pola Fraud pada Ekosistem Pembayaran Digital menggunakan Metode Isolation Forest Akbar, M. Willi; Kusuma Ningrum, Septiani; Afrina, Mira; Ibrahim, Ali
Jurnal Informatika dan Teknologi Komputer (J-ICOM) Vol 7 No 01 (2026): Jurnal Informatika dan Teknologi Komputer ( J-ICOM)
Publisher : E-Jurnal Universitas Samudra

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55377/j-icom.v7i01.13622

Abstract

Transformasi menuju ekonomi digital di Indonesia dihadapkan pada tantangan krusial berupa meningkatnya serangan fraud yang semakin canggih. Penelitian ini mengajukan sebuah pendekatan unsupervised learning untuk mengenali pola serangan fraud generasi baru sebagai dasar penguatan kapasitas supervisi institusional. Penelitian ini berfokus pada identifikasi anomali tanpa bergantung pada label historis yang ada dengan memanfaatkan algoritma ensemble Isolation Forest. Model berhasil memetakan karakteristik transaksi yang mencurigakan berkat penerapan rekayasa fitur yang mendalam, yang mencakup analisis perilaku, korelasi alamat, dan ekstraksi sinyal dari IP. Hasil evaluasi menunjukkan bahwa pendekatan unsupervised ini mampu mengidentifikasi 18% dari total kasus fraud yang telah dilabelkan, membuktikan relevansinya dalam menangkap sinyal serangan yang sesungguhnya. Lebih penting lagi, analisis kualitatif terhadap anomali yang ditemukan berhasil mengkarakterisasi sebuah Pola Serangan Senyap, yaitu kombinasi multi-faktor risiko yang berpotensi terlewatkan oleh sistem deteksi konvensional. Temuan ini menyajikan sebuah wawasan baru bagi institusi regulator untuk beralih dari supervisi reaktif ke penemuan ancaman proaktif, yang pada akhirnya mendukung terciptanya ekosistem keuangan digital yang aman dan berkelanjutan sejalan dengan Tujuan Pembangunan Berkelanjutan (SDGs).
Analisis Komparatif Algoritma Process Mining untuk Pemetaan Navigasi dan Deteksi Bottleneck E-Commerce Leiden Fauzi Yoka Surya; Lyvia Valentina; Zikri Firmansyah; Fathoni Fathoni; Ali Ibrahim
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.v15i3.3629

Abstract

E-commerce digitalization generates massive clickstream data, complicating customer journey mapping and bottleneck detection. The unstructured nature of web logs often leads to modeling failures. This study evaluates the performance of Alpha Miner, Heuristic Miner, and Inductive Miner algorithms in mapping user navigation routes and detecting interface inefficiencies using a public e-commerce clickstream dataset. Through Token-Based Replay evaluation, the research shows that Alpha Miner is inefficient for dynamic data and prone to Out of Memory errors. Conversely, Inductive Miner proved superior with a perfect fitness level (0.999), while Heuristic Miner was optimal in filtering noise (0.887). Further evaluations using the Performance Directly-Follows Graph localized the main bottleneck at the post-login transition to the shopping cart addition, which took the longest interface delay (42 minutes). These empirical findings provide a benchmark to optimize user interfaces and boost digital transaction conversions.Keywords: Bottleneck; Conformance Checking; Customer Journey; E-Commerce; Process Mining. AbstrakDigitalisasi e-commerce menghasilkan data clickstream masif yang menyulitkan pemetaan customer journey dan deteksi bottleneck. Sifat log web yang tidak terstruktur sering kali memicu kegagalan pemodelan. Penelitian ini mengevaluasi kinerja Alpha Miner, Heuristic Miner, dan Inductive Miner untuk memetakan navigasi pengguna serta mendeteksi inefisiensi antarmuka menggunakan dataset publik rekaman clickstream e-commerce. Melalui evaluasi Token-Based Replay, penelitian menunjukkan bahwa Alpha Miner tidak efisien untuk data dinamis dan rentan memicu Out of Memory. Sebaliknya, Inductive Miner terbukti paling unggul dengan tingkat kecocokan sempurna (0.999), sedangkan Heuristic Miner optimal dalam menyaring derau (0.887). Evaluasi lanjutan berbasis Performance Directly-Follows Graph melokalisasi bottleneck utama pada transisi pasca-login menuju penambahan keranjang belanja dengan jeda waktu antarmuka terlama (42 menit). Temuan empiris ini menjadi acuan untuk mengoptimalkan rekayasa antarmuka pengguna demi mendongkrak konversi transaksi digital. 
Segmentasi Pelanggan E-Commerce Berbasis Integrasi Text Mining dan RFM untuk Deteksi Dini Churn Violin Juneyla Nandita; Juseia Wulandari; Apriyadi Apriyadi; Ali Ibrahim; Fathoni Fathoni
Building of Informatics, Technology and Science (BITS) Vol 8 No 1 (2026): June 2026
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v8i1.9687

Abstract

The growth of transactions on e-commerce platforms generates a massive volume of unstructured customer review data. However, traditional Customer Relationship Management (CRM) models such as RFM often only focus on quantitative transaction data and ignore the emotional dimension contained in customer reviews. This study aims to analyze the relationship between purchase frequency and customer comment polarity through the integration of Text Mining and CRM Analytics approaches. The novelty offered is the development of a hybrid method that combines Lexicon Refinement-based sentiment extraction with the Random Forest algorithm to overcome rating bias in global e-commerce platform data (Kaggle). The proposed method includes the use of Natural Language Processing (NLP) techniques, topic modeling based on Latent Dirichlet Allocation (LDA), and sentiment analysis to extract polarity scores. The test results show that the initial lexicon model has limitations with an accuracy of 52.14% due to noise in neutral reviews (3-star rating). However, after optimization using the Random Forest algorithm and neutral data filtering, the classification accuracy increased significantly to 74.62%. These results prove that sentiment integration is able to provide more accurate loyalty mapping and help e-commerce management detect potential churn in the At-Risk customer segment.
Development of a Flask-based Application for Bank Customer Churn Prediction as a Decision Support Tool Suluh Arif Wibowo; Muhammad Rezky; Ali Ibrahim; Mira Afrina; Fathoni Fathoni
SISTEMASI Vol 15, No 4 (2026): Sistemasi: Jurnal Sistem Informasi
Publisher : Universitas Islam Indragiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v15i4.6257

Abstract

Customer churn prediction is a crucial aspect of the banking industry for maintaining customer loyalty and reducing the cost of acquiring new customers. This study aims to develop a web-based decision support system capable of predicting potential customer churn using the Gradient Boosting Machine (GBM) algorithm. The dataset used is the Bank Customer Churn Dataset, consisting of 10,000 customer records with 14 attributes. The research stages include exploratory data analysis and preprocessing, which involves data cleaning, categorical feature encoding, feature engineering (BalanceSalaryRatio, TenureByAge, CreditScoreGivenAge), and data balancing using SMOTE to address class imbalance. The GBM model was trained on the balanced dataset and evaluated using accuracy, precision, recall, and F1-score metrics. The evaluation results show that the model achieved an accuracy of 83.95%, with a recall of 67.32% for the churn class, indicating a strong capability in identifying customers at risk of churn. Feature importance analysis reveals that Age and NumOfProducts are the most dominant features, contributing approximately 77% to the prediction. The model was then implemented in a Flask-based web application with an HTML and CSS interface, enabling non-technical users to perform real-time churn predictions. This system is expected to assist banking institutions in designing more targeted and data-driven customer retention strategies.
TRAINING ON IMPROVING DIGITAL MARKETING SKILLS FOR THE PROMOTION OF FOOD PRODUCTS OF THE LIBERTI BERINGIN SAKTI FARMER GROUP OF PAGARALAM SELATAN Ahmad Fali Oklilas; Ali Ibrahim; Ricy Firnando; Yadi Utama
Devote: Jurnal Pengabdian Masyarakat Global Vol. 4 No. 1 (2025): Devote : Jurnal Pengabdian Masyarakat Global, Maret 2025
Publisher : LPPM Institut Pendidikan Nusantara Global

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55681/devote.v4i1.3717

Abstract

The training was designed to support the business sustainability of the Liberti Farmer Group located in Beringin Sakti Village, Ulu Rurah Village, Pagaralam Selatan Sub-district, Pagaralam City. The training included training to improve digital marketing skills to promote food products. This activity aims to provide a basic understanding of digital marketing and teach farmer group members how to use digital technology to promote their food products more efficiently and effectively. In this training, they will learn how to use social media as a marketing platform, create engaging content to promote goods, and increase market reach by using online marketplaces and advertisements. The hands-on practice-based method teaches participants how to create digital catalogs, manage social media accounts, and utilize SEO techniques to increase the visibility of their products. The training can improve the skills of farmer group members in utilizing digital technology for promotion, expanding the market for agricultural products, and increasing income.
Analisis Sentimen Ulasan Pengguna Pada Aplikasi M2U ID Menggunakan Metode Random Forest dan Support Vector Machine (SVM) Anadya Nisrina Salsabila; M. Rudi Sanjaya; Ali Ibrahim; Endang Lestari Ruskan
Jurnal Algoritma Vol 23 No 1 (2026): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.23-1.3375

Abstract

The M2U ID app is the primary digital banking platform of PT Bank Maybank Indonesia Tbk, serving as a crucial tool for supporting customers’ online transactions. The objective of this study is to analyze user review sentiment on the Google Play Store by comparing the performance of the Random Forest and Support Vector Machine (SVM) algorithms. A total of 16,270 review data points were collected via web scraping and processed through preprocessing stages and feature extraction using N-Gram-based TF-IDF with Chi-Square feature selection using the SelectKBest approach. Given the significant imbalance in data distribution, this study applied class weighting techniques as well as hyperparameter optimization using Grid Search and 5-Fold Cross-Validation. Testing on 3,254 test data points indicated that SVM performed more optimally with an accuracy rate of 82% and an F1-Macro score of 0.6344, compared to Random Forest, which yielded an accuracy of 73% and an F1-Macro score of 0.5832. The main contribution of this study is an in-depth analysis of classification errors in the minority (neutral) class, which has a low F1-score (0.16–0.17). The results of the error analysis show that the model’s limitations are caused by the ambiguity of technical features and the overlap of vocabulary in reviews with minimal emotional content.
Analisis Sentimen Ulasan Pengguna Pada Aplikasi Kitabisa: Donasi & Zakat Menggunakan Metode Support Vector Machine (SVM) dan Naive Bayes Nabilah Putri Maharani; M. Rudi Sanjaya; Ali Ibrahim; M. Husni Syahbani
Jurnal Algoritma Vol 23 No 1 (2026): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.23-1.3376

Abstract

The rapid advancement of digital technology has spurred the emergence of online philanthropy platforms like Kitabisa, which collect a large volume of user reviews. Reviews on the Google Play Store reflect both satisfaction levels and service issues, but their unstructured nature makes manual analysis difficult. This study evaluates user sentiment on the Kitabisa platform by comparing the Support Vector Machine (SVM) and Naive Bayes models. A dataset of 11,887 reviews was processed through preprocessing and word weighting using the TF-IDF approach. The evaluation results show that the Support Vector Machine outperformed Naive Bayes with an accuracy of 84.05% and an F1-score of 0.93, while Naive Bayes achieved an accuracy of 81.73% and an F1-score of 0.92. Theoretically, this study reinforces the literature regarding the superiority of Support Vector Machines for unstructured text data. Additionally, the results of this research produce an automated evaluation framework that can be used by application developers as a basis for improving service quality in accordance with user perceptions accurately.
Co-Authors . Apriansyah A Wendi Saputra AA Sudharmawan, AA Abdillah, Bimo Musthafa Adriani, Nadia Saphira Afif, Hasnan Agil Furgaan Agil Kusuma, Dimas Ahmad Fali Oklilas Ahmad Fali Oklilas Ahmad Fali Oklilas Ahmad Fali Oklilas Ahmad Fali Oklilas Ahmad Hiera Maldanop Ahmad Nursodiq Ahmad Rifai Ahmad Rifai Akbar Adiprama, Faris Akbar Alzaini Akbar Kurniawan, Iqbal Akbar, M. Willi Al Akbar, M. Rizki Al Farissi Albani, Muhammad Syarief Albert Amadeus Valentino Albukhori, M Rafli Alfitrah, Intan Aidita Ali Usman, Ali Alif Baidhawi Alif Mustaqim Alifa Putri Shahabiyah Alifayoezra, Muhammad Dzaky Alisia Silver Stone Aliya Faiza Allan Nugraha Allsela Meiriza Allsela Meiriza, Allsela Altahir, Ali Abdul Razzaq Alzaini, Akbar Amanda Ardhani, Dhita Amanda, Khansa Putri Amatullah, Shabrina Amelia, Putri Amerza, Rezki Anadia, Qothrunnada Wafi Anadya Nisrina Salsabila Ananda, Dea Tri Andin Sabilla Janna Andini Bahri, Cheisya Anggraini, Nadya Angie Silvanda Herman Anindya Putri, Salsa Annas Apreja Anne Trimaysella Annisa Turrahma Apriyadi Apriyadi Aqil Zidane, Muhammad Arafah, Siti Nur Ardhillah, Onky Ari Wedhasmara Arsita, Resi Arvhi Randita Setia Aryo De Wibowo Aslamiah, Iziah Astri Carolina Attika Putri, Shopi Audya, Meitiana Ayu Triana Ayuningtiyas, Pratiwi Azmi Zaky, Muhammad Baidhawi, Alif Barata, Gusti Basulina, Nur Annisa Bayu Wijaya Putra Beriadi Agung Nur Rezqe Beriadi Agung Nur Rezqeb Budi Astuti Cahya Aulia, Syifa Cantika Aulia Cendikiawan, Rizky Saputra Clark Peter Wijaya, Adley Damayanti, Risma Dea Tri Ananda Dedi Ramadhan Dedy Kurniawan Defiani, Nanda Dela Arum, Hestiana Delima, Rizki Della Audita Deni Agus Hendrawan Dessy yanti suryana Devi Indra Meytri Dhini Kurnia, Rizka Dian Febriansyah Dicha Pratiwi Duffin Dwi Rosa Indah Dytha Ananda Widhiarso Edhar, Zeter Eka Afrianti Eka Darmayanti Simanullang Eka Lusyanti Marpaung Eka Saputra Elisa, Felia Sonya Elsya Moriesta Endang Lestari Endang Lestari Ruskan Endang Lestari Ruskan Epriyanti, Nadia Erma Novita Satyariza Ermatita Ermatita - Ermatita Ermatita Eti Arini Fachrozi, Muhammad Al Fachry, Muammar Fadilah Nur Imani Fathoni Fathoni Fathoni - Fathoni - Fathoni, Fathoni Fatihaturrahmah, Aisyah Fatmayanis, Kiki Faza, Muhamamad Febriando Tambunan Felicia, Yohana Fernando, Jose Fitriani, Lesa Fraternesi Fraternesi Furgaan, Agil Garcia Krisnando Nathanael Gultom, Gina Destia Gumay, Naretha Kawadha Pasema Gumay, Naretha Kawadha Pasemah Gusti Barata Gusti Barata Gustiani, Sindy Gustin Saputri Hadiansyah Ma'sum Hafiiz Kresna Prasetya Haidar Afif Mufid, Muhammad Handayani Putri Wardanny Hanggara, Bryan haniyah faizah Hardini Novianti Hardini Novianti Hariza Marshella, Siti Hasbiallah, Muhammad Jidan Hedi Yunus Hedi Yunus Heliza Rahmania Hatta Hendra Wijaya Hendrawan, Deni Agus Hijriani, Nurul Hyoga Hara Kusuma Ifan Setiawan Ikhda Uswatun Khasanah Ikhwan Najatafani, Bintang Iman Saladin B. Azhar Imani, Fadilah Nur Iredho Fani Reza Iredho Fani Reza Irwansyah, Aziiz Islamiansyah, Wira Ispahan, Tarisha Jiwany, Larasathi Jodi Pratama, Muhammad Juseia Wulandari Karisa Anjani Fakhri Ken Ditha Tania Ken Ditha Tania Khaerullah, Muhammad Khailani, Kgs M Luthfi Khairani, Annisa Khairun Nisak, Novrinda Khalisatifa, Aida Khasanah, Ikhda Uswatun Khoiriyah Harahap, Dayana Khoirunnisa, Ananda Kodri, Lay Kurnia, Rizka Dhini  Kurniasari, R. Nyi Pipih Kurniawati, Junia kusmiarti, reni Kusuma Ningrum, Septiani Kusuma, Aisha Nuraini Lay Kodri Leiden Fauzi Yoka Surya Lenawati Asry Leonardi, Veronica Hertensia Lina Oktarina Lucky Hermanto, Muhammad Lukmanul Hakim Lyvia Valentina M Andika Saputra M Bintang Naufal Riansyah M. Husni Syahbani M. Rudi Sanjaya M. Rudi Sanjaya Madyus Randikai Maldanop, Ahmad Hiera mansyur abdul hamid Maretta, Aulia Pinkan Marini Mariska, Inneke Via Marjusalinah, Anna D. Maulindah, Rafika Maya Mardiana Meitiana Audya Meizalina, Mutiara Amalia Mgs Afriyan Firdaus Michelle Liu Miftahul Falah Miftahul Jannah Mila astuti Mira Afrina Monita, Tisa Muammar Fachry Muhammad Bayu Samudra Muhammad Dzaky Alifayoezra Muhammad Fadhil Rahman Muhammad Fakhri Nadrota Acta Muhammad Hidayat Mauluddin Muhammad Rafif AR Muhammad Rayhan Novello Muhammad Rezky Musdiono - Naberi Oktaria Nabila Hidayati Nabilah Putri Maharani Nachwa, Syakillah Nadia Saphira Adriani Nadya Angelia Naek Parulian Hutagalung Najwa Widasari, Yesya Nanda Defiani Napian, St Dhiah Raniah Naretha Kawadha Pasemah Gumay Nashiroh Ramadhani, Muthia Naufaldihanif, Rihan Ningsih, Rafika Octaria Nintyas, Vanda Ayu Novita Hamron Nugraha, Allan Nugrahani, Henny Saptatia Drajati Nur'Aini, Risma Nurharisyah Hasibuan Nurhidayati, Yossi Nurseptiani, Alya Nurul Hijriani Nurullah Marina Kelana Okllilas, Ahmad Fali Oktavio Theonady Olivia, Fanny Onkky Alexander Opi Hernayanti Pacu Putra Pakpahan, Jonathan Permana, Rizki Artinio Pradia Paramita Prasetia, Dika Prasetia Pratama Putra, Daffa Pratama, Muhammad Ramadhan Putra pratikto aditia wiguna Purwita dari Purwita Sari Purwita Sari, Purwita Putri Casanova, Musdalifa Putri Eka Sevtiyuni Putri Eka Sevtiyuni Putri Mutiara Arinie Putri, Amelia Rizki Putri, Septhia Charenda Rachmi Muti'ah Fadillah Rafif Nopyefa Rahmadini, Vira Putri Rahman, Abdul Ariga Rahmat Izwan Heroza Rahmat Izwan Heroza Raihana Putri, Naila Ramadhan, Dedi Ramadhan, Fitrah Ramadhani Maulizidan, Muammar Ramadhani, Muthia Randikai, Madyus Ratih Dewi Sari Resi resi Rezqe, Beriadi Agung Nur Riansyah, M Bintang Naufal Ricy Firnando Ricy Firnando Rielisa Putri, Adetya Rika Septiana Risma Damayanti Risyahputri, Aliyananda Ritonga, Torkis Rizka Dhini Kurnia Rizka Dhini Kurnia Rizka Dhini Kurnia Rizka Dhini Kurnia Rizka Mumtaz, Fadia Rizki, Raditya Dafa Rizkyllah, Anabel Fiorenza Rofiqul Rahman Ramadhan Rositiani, Ely Ruki, Taufik Rahman Rusdi Efendi Sabila, Amalia Sadjijo, Priyono Salsabila, Lulu Samsuryasi, Samsuryasi Sanjaya, M. Rudi Saputra, Marco Saputra, Yopis Sari, Ratih Dewi Sartika Sartika Sartika Sartika Sasmita, Ruth Mei Satria Alva Ardana Satyariza, Erma Novita Savero, Muhammad Juan Selviani Selviani Seprina, Iin Septiani Aulia Putri Setiawan, Ifan Sevtiyuni, Putri Eka Shabrina Amatullah Shifa Maharani, Wardah Siregar, Richi Nauli Juniarto Siswahyudianto Siti Raisah Adilah Sitorus, Herdiyanti Ratiningsih Situmorang, Ruth Christin Aprilia Sofita, Yunia Ruwanna St Dhiah Raniah Napian Suci Amalia Sulaiman , Ahmad Riski Suluh Arif Wibowo Supaidi, Ahmad Syafitri, Hidayah Syahbani, M. Husni Syahputra, M Fathan Aqilah Syalwa Salsabillah S Tamara Juliyanti Tammam, Bimmo Fathin Tanti Hidayah Tasya Permata Listi Tea Anggelah Theresia Pardede, Eva Therina Lakeisyah, Eka Thuraya, Zafira Tia Arlin Dita Tio Suhada Tisa Monita Tri Zafira, Zahra Turrahma, Annisa Umi Pertiwi Vanda Ayu Nintyas Vinolia Vinolia Viola Alfheny Violin Juneyla Nandita Windhi Tia Saputra Windhi Tia Saputra Winny Dea Monica Wirnanti, Rintan Wiwit Widhya Yadi Utama Yadi Utama Yadi Utama Yadi Utama Yadi Utama Yadi Utama Yelli Nur Alinda Yeremia Wiratama Yona Saymona Yopis Saputra Yossi Nurhidayati Yudha Pratomo Yunia Ruwanna Sofita Yunita Faujiyah Yunus, Hedi Yunus, Hedi Yusmaniarti Yusmaniarti Yusmaniarti Zahirah, Nabilah Zahran, Ahmad Hafizh Zaini, Akbar Al Zakirah Sabrina Putri Pasha Zefta Adetya Zhafiri, Muhammad Farisan Zikri Firmansyah Zufiyardi Zufiyardi Zulfadhli Syarif Zurfi, Ahmed