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All Journal Tekno : Jurnal Teknologi Elektro dan Kejuruan EKSAKTA: Journal of Sciences and Data Analysis Jurnal Ilmiah Informatika Komputer Prosiding SNATIF Jurnal Informatika dan Teknik Elektro Terapan Journal of Information System Sistem : Jurnal Ilmu-Ilmu Teknik INTEGER: Journal of Information Technology JIKO (Jurnal Informatika dan Komputer) JEEMECS (Journal of Electrical Engineering, Mechatronic and Computer Science) JURNAL ILMIAH INFORMATIKA Jurnal Infomedia JURNAL PENDIDIKAN TAMBUSAI Jurnal Teknik Elektro dan Komputer TRIAC JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Jurnal Teknologi Terpadu JEECAE (Journal of Electrical, Electronics, Control, and Automotive Engineering) JASIEK (Jurnal Aplikasi Sains, Informasi, Elektronika dan Komputer) Jurnal Informatika dan Rekayasa Elektronik bit-Tech JE-Unisla ILKOMNIKA: Journal of Computer Science and Applied Informatics Generation Journal JATI (Jurnal Mahasiswa Teknik Informatika) CICES (Cyberpreneurship Innovative and Creative Exact and Social Science) Journal of Computer Networks, Architecture and High Performance Computing Jurnal Pengabdian kepada Masyarakat Nusantara Nusantara Science and Technology Proceedings Jurnal Restikom : Riset Teknik Informatika dan Komputer Jurnal Ilmiah Teknologi Informasi dan Robotika HOAQ (High Education of Organization Archive Quality) : Jurnal Teknologi Informasi Journal of Information System and Technology (JOINT) Jurnal Teknologi dan Manajemen TIERS Information Technology Journal Jurnal Informatika, Komputer dan Bisnis (JIKOBIS) International Journal Of Computer, Network Security and Information System (IJCONSIST) ALINIER: Journal of Artificial Intelligence & Applications MATHunesa: Jurnal Ilmiah Matematika Jurnal Sistem Informasi, Teknik Informatika dan Teknologi Pendidikan (JUSTIKPEN) Jurnal WIDYA LAKSMI (Jurnal Pengabdian Kepada Masyarakat) SinarFe7 Jurnal Informatika Software dan Network (JISN) Jurnal Ilmiah Sistem Informasi dan Ilmu Komputer VARIANSI: Journal of Statistics and Its Application on Teaching and Research STORAGE: Jurnal Ilmiah Teknik dan Ilmu Komputer Journal of Informatics and Electronics Engineering J-Icon : Jurnal Komputer dan Informatika TAMIKA: Jurnal Tugas Akhir Manajemen Informatika & Komputerisasi Akuntansi "JAMASTIKA" Jurnal Mahasiswa Teknik Informatika Jurnal Informatika Polinema (JIP) VISA: Journal of Vision and Ideas Journal of Innovative and Creativity Journal of Technology and System Information Journal of Software Engineering and Multimedia (JASMED) Jurnal Ilmiah Betrik : Besemah Teknologi Informasi dan Komputer Journal of Multidisciplinary Inquiry in Science, Technology and Educational Research Indonesian Journal of Electronics, Electromedical Engineering, and Medical Informatics Himpunan: Jurnal Ilmiah Mahasiswa Pendidikan Matematika Brilliant International Journal of Management and Tourism Jurnal Informatika Dan Tekonologi Komputer Jurnal Nasional Teknologi Informasi dan Aplikasinya Journal of Informatics and Vocational Education Journal of Advanced Informatics and Sustainable Intelligent Systems
Anggraini Puspita Sari
Unknown Affiliation
Agriculture, Biological Sciences & Forestry Humanities Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Public Health Social Sciences Other

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Inflation Convergence Modeling Using Binary Logistic Regression With SGD-Newton Raphson Optimization Methods in Indonesia Fatma Novalia Kussumarani; Istiqomah, Nerissabila Uswatun; Siva Ifin Azzahra; Anggraini Puspita Sari; Sischa Wahyuning Tyas
EKSAKTA: Journal of Sciences and Data Analysis VOLUME 7, ISSUE 1, April 2026
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20885/EKSAKTA.vol7.iss1.art9

Abstract

Global economic changes have necessitated the development of inflation models that can accurately describe Indonesia's economic dynamics. This study aims to compare two optimization methods, Newton Raphson and Stochastic Gradient Descent (SGD), in binary logistic regression modeling to analyze the effectiveness of monetary policy. This study contributes to evaluating the performance of both methods in terms of convergence speed and accuracy of inflation model parameter estimation. The results of the analysis show that the Newton Raphson method is more efficient in achieving convergence with an iteration value of 0.2933 compared to SGD, while both methods produce equivalent model quality based on the Akaike Information Criterion (AIC) values of 34.4008 and 34.4254. These findings emphasize the importance of selecting the right optimization method to support more efficient monetary policy analysis.
MODEL ESTIMASI WAKTU TEMPUH MENGGUNAKAN PENDEKATAN PEMODELAN MATEMATIS DAN OPTIMASI: TRAVEL TIME ESTIMATION MODEL USING MATHEMATICAL MODELING AND OPTIMIZATION APPROACHES Hamid, Aisyah Amalia; Shafara, Anindya Restu; Rachmawati, Siti Naia Hesti; Sari, Anggraini Puspita; Tyas, Sischa Wahyuning
HOAQ (High Education of Organization Archive Quality) : Jurnal Teknologi Informasi Vol. 17 No. 1 (2026): Jurnal HOAQ - Teknologi Informasi
Publisher : STIKOM Uyelindo Kupang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52972/hoaq.vol17no1.p140-154

Abstract

Estimasi waktu tempuh yang akurat sangat krusial bagi efisiensi sistem transportasi dan layanan logistik di perkotaan. Penelitian ini mengembangkan model estimasi waktu tempuh untuk wilayah Surabaya dengan mengintegrasikan metode interpolasi, regresi linear, dan teknik optimasi Newton-Raphson. Data yang digunakan bersumber dari rute OpenStreetMap serta variabel cuaca (curah hujan dan suhu) dari BMKG. Hasil analisis menunjukkan bahwa jarak tempuh, intensitas hujan, dan kondisi jam sibuk secara signifikan memengaruhi durasi perjalanan. Model ini memiliki tingkat akurasi yang tinggi dengan koefisien determinasi RSquare (???? 2 ) sebesar 0,92. Adapun tingkat kesalahan model diukur melalui Mean Absolute Error (MAE) sebesar 201,05 detik (sekitar 3,3 menit) dan Root Mean Squared Error (RMSE) sebesar 267,53 detik. Melalui simulasi optimasi rute, model ini mampu memberikan saran perjalanan yang 8–15% lebih cepat dibandingkan strategi pemilihan rute konvensional berbasis jarak terpendek. Dengan hasil tersebut, model ini dapat diimplementasikan pada sistem navigasi adaptif dan responsif terhadap perubahan kondisi lingkungan dan lalu lintas.   Accurate travel time estimates are crucial for the efficiency of transportation systems and logistics services in urban areas. This study developed a travel time estimation model for the Surabaya area by integrating interpolation, linear regression, and Newton-Raphson optimization techniques. The data used was sourced from OpenStreetMap routes and weather variables (rainfall and temperature) from the BMKG. The results of the analysis show that travel distance, rainfall intensity, and rush hour conditions significantly affect travel duration. This model has a high level of accuracy with a coefficient of determination R Square (R2 ) of 0.92. The model's error rate is measured by the Mean Absolute Error (MAE) of 201.05 seconds (approximately 3.3 minutes) and the Root Mean Squared Error (RMSE) of 267.53 seconds. Through route optimization simulations, this model is able to provide travel suggestions that are 8–15% faster than conventional route selection strategies based on the shortest distance. With these results, this model can be implemented in adaptive navigation and responsive systems that respond to changes in environmental and traffic conditions.
Prediksi Gangguan Kesehatan Mental pada Kalangan Mahasiswa Menggunakan Metode Pseudo-Labeling dan Algoritma Regresi Logistik Anggraini Puspita Sari; Dwi Arman Prasetya; Firza Prima Aditiawan; Muhammad Muharrom Al Haromainy
TAMIKA: Jurnal Tugas Akhir Manajemen Informatika & Komputerisasi Akuntansi Vol 4 No 2 (SEMNASTIK) (2024): TAMIKA: Jurnal Tugas Akhir Manajemen Informatika & Komputerisasi Akun
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/tamika.Vol4No2(SEMNASTIK).pp40-48

Abstract

Mental illness is a health condition that alters a person's thoughts, feelings, or behaviors, leading to distress and difficulty in maintaining a normal life. Mental health issues should not be taken lightly due to the challenges associated with diagnosis. Many students tend to experience mental health problems at various stages of their education, from diploma programs to doctoral studies. This situation becomes more critical as students approach the end of their studies and anticipate future prospects. This article explores the mental health status of students through symptoms, using logistic regression methods for prediction based on the dataset used. In this study, two types of data are employed: labeled dataset and unlabeled dataset, which are combined to create a semi-supervised learning approach. Labeled dataset is classified using a logistic regression algorithm, while unlabeled dataset employs the pseudo-labeling method. The analysis and modeling of the dataset indicate that the comparison between labeled and unlabeled dataset can significantly affect accuracy and processing time. Furthermore, the use of the pseudo-labeling method with the logistic regression algorithm is well-suited for the mental health case study, achieving an accuracy of 98% with a labeled to unlabeled dataset ratio of 1:2.
Sentiment Analysis of Presidential and Vice Presidential Candidates Using FastText CNN Fahri Izzuddin Zulkarnaen; Anggraini Puspita Sari
IJCONSIST JOURNALS Vol 6 No 1 (2024): September
Publisher : International Journal of Computer, Network Security and Information System

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33005/ijconsist.v6i1.121

Abstract

The Internet has become a platform for storing and accessing a wide range of public information. People tend to use social media to express opinions on products, political policies, and politicians, both as individuals and as parties. Sentiment analysis of presidential and vice-presidential candidates aims to understand public perspectives on each candidate. Based on sentiment analysis of the Indonesian public on social media, potential candidates for the presidential election, which is still over a year away, can be identified. This study categorizes sentiments into four classes: happy, love, sad, and angry. The model employs FastText embeddings with a Convolutional Neural Network (CNN). The best performance achieved was an F1-score of 0.9510. The findings indicate that Ganjar Pranowo leads as a presidential candidate, while Erick Thohir stands out as the leading vice-presidential candidate.
Prototype of Hydroponic Lettuce Cultivation: IoT-Based Automatic Irrigation System for Growth Enhancement and Sustainability Fina Amru Millati Millati; Anggraini Puspita Sari; Daniel Gloryo Nadirco; Norhaslinda Binti Hasim
IJCONSIST JOURNALS Vol 6 No 1 (2024): September
Publisher : International Journal of Computer, Network Security and Information System

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33005/ijconsist.v6i1.123

Abstract

Lettuce (Lactuca sativa) is a vegetable commonly grown in temperate and tropical climates. In organic cultivation, lettuce has high economic value due to its high mineral content, including iodine, copper, iron, phosphorus, and others. Hydroponics is an agricultural cultivation method that uses water as the planting medium. This method offers advantages such as space efficiency and more. Currently, monitoring water in hydroponic plant cultivation is conducted periodically by growers who physically visit the cultivation site, including the reservoir tank. This process can be quite inconvenient because growers cannot predict when moisture levels will drop. One solution to this problem is to implement remote, real-time water monitoring for hydroponic lettuce cultivation using Internet of Things (IoT) devices. Therefore, a system design for IoT-based remote monitoring of moisture levels is required, allowing growers to monitor the condition of hydroponic lettuce without needing to visit the cultivation site. The research findings indicate that when the moisture level is dry, the system will display a value of 100, prompting users to receive a notification for irrigation. If the value is below 100, the system indicates that the planting medium is sufficiently moist.
Deteksi Stres Mahasiswa Berdasarkan Komentar Media Sosial X Menggunakan TF-IDF dan Algoritma Logistic Regression Alvin Rama Saputra Alvin; Muhammad Wifaqul Azmi; Anggraini Puspita Sari
JOINS (Journal of Information System) Vol 11 No 1 (2026): Edisi (Desember 2025 - Mei 2026)
Publisher : Fakultas Ilmu Komputer, Universitas Dian Nuswantoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33633/joins.v11i1.14836

Abstract

Mental health issues, particularly stress among university students, are on the rise and require special attention. Students tend to express their psychological conditions implicitly through comments or posts on social media, especially on platform X, which provides valuable digital data for real-time and non-invasive emotional analysis. This study aims to develop a stress detection system for students by analyzing comments on social media platform X using the Term Frequency-Inverse Document Frequency (TF-IDF) method and the Logistic Regression algorithm. TF-IDF is applied to extract important linguistic features from student comments, while Logistic Regression is chosen for its ability to provide clear probabilistic interpretation and efficiency in processing high-dimensional text data. The model is trained using labeled student comment data and evaluated using accuracy, F1-score, precision, and recall metrics. The results indicate that the system developed can classify stress and non-stress comments with a high accuracy of 93%, demonstrating great potential in supporting early interventions for student mental health. The implication of this research is expected to serve as a foundation for the development of digital applications that are responsive, adaptive, and practical in promoting student mental well-being in Indonesia.
Analisis Variasi Daya Tarik Konsumen Menggunakan Metode Repeated Measures Anova Jonathan Teguh Samuel Kaeng; Danu Satrio; Anggraini Puspita Sari
Journal of Technology and System Information Vol. 3 No. 1 (2026): January
Publisher : Indonesian Journal Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47134/jtsi.v3i1.5384

Abstract

  Penelitian ini bertujuan untuk menganalisis pengaruh variasi jenis kemasan terhadap tingkat ketertarikan konsumen pada produk kebab mini. Penelitian ini menggunakan pendekatan kuantitatif dengan metode eksperimen semu dan desain within-subjects (repeated measures design). Pengumpulan data melalui survei menggunakan Google Form, di mana setiap responden memberikan penilaian berupa rating terhadap tiga jenis kemasan kebab mini, yaitu mika, styrofoam, dan craft box, dengan asumsi harga produk yang sama. Data yang terkumpul dianalisis menggunakan metode Repeated Measures ANOVA pada taraf signifikansi 0,05. Hasil penelitian  menunjukkan terdapat perbedaan pada tingkat ketertarikan konsumen berdasarkan jenis kemasan (p < 0,05). Berdasarkan hasil penelitian ini didapatkan bahwa jenis kemasan berpengaruh terhadap daya tarik konsumen pada produk kebab mini
PREDIKSI RISIKO BURNOUT KARYAWAN MENGGUNAKAN K-MEANS Muhamad Vicky Oktafrian; Raihan Ramadhan; Anggraini Puspita Sari
JATI (Jurnal Mahasiswa Teknik Informatika) Vol. 10 No. 2 (2026): JATI Vol. 10 No. 2
Publisher : Institut Teknologi Nasional Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36040/jati.v10i2.17738

Abstract

Burnout merupakan masalah serius dalam dunia kerja yang berdampak pada kesehatan mental karyawan serta kinerja organisasi. Tingginya beban kerja, lembur, dan rendahnya kualitas hubungan kerja menjadi faktor yang berkontribusi terhadap meningkatnya risiko burnout. Penelitian ini bertujuan untuk mengelompokkan tingkat risiko burnout karyawan menggunakan algoritma K-Means Clustering berdasarkan empat variabel utama, yaitu usia, jenis kelamin, riwayat lembur, dan kepuasan hubungan dengan rekan kerja. Metode penelitian meliputi pengumpulan data karyawan sebanyak 1.480 data, pra-pemrosesan data berupa encoding variabel kategorik dan normalisasi menggunakan Min-Max Scaler, serta pemodelan clustering menggunakan algoritma K-Means. Penentuan jumlah klaster optimal dilakukan dengan Elbow Method dan Silhouette Score. Hasil evaluasi menunjukkan bahwa jumlah klaster optimal adalah empat dengan nilai Silhouette Score sebesar 0,5472. Keempat klaster tersebut merepresentasikan tingkat risiko burnout yang berbeda, yaitu Non-Burnout, Low-Burnout, Medium-Burnout, dan High-Burnout. Hasil analisis menunjukkan bahwa karyawan yang sering lembur dan memiliki tingkat kepuasan hubungan kerja yang rendah cenderung berada pada kelompok risiko burnout yang lebih tinggi. Penelitian ini diharapkan dapat membantu organisasi dalam mendeteksi risiko burnout secara dini sebagai dasar pengambilan keputusan dan perancangan strategi intervensi yang lebih tepat sasaran.
Performance Evaluation of Support Vector Machine and Naïve Bayes Methods in Mining Sentiment from Shopee Application Reviews Dandi Azaidane; Muhammad Masrur Aji Dorojatun; Bisma Satrio Bimantoro; Anggraini Puspita Sari; Addien Haniefardy
Journal of Informatics and Vocational Education Vol. 9 No. 3 (2026): November 2026
Publisher : Informatics Education Department, Faculty of Teacher Training and Education, Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20961/joive.v9i3.3741

Abstract

Shopee is one of the most popular e-commerce platforms in Indonesia, with millions of individuals using it to buy and sell online. The number of user reviews on the Shopee app could be an essential metric in terms of the amount of consumer satisfaction with the services provided. The research intends to analyse the sentiment of Shopee’s customer reviews using the Naïve Bayes and Support Vector Machine (SVM) algorithms. In this work, the dataset used is the customer review data from Shopee app retrieved from Kaggle platform with a total of 9,561 reviews. The research process includes data selection, text pre-processing (Case Folding, Cleaning, Tokenising, Stopword Removal, Stemming), sentiment labelling based on rating into positive and negative class, data balancing with Synthetic Minority Over-sampling Technique (SMOTE), feature transformation using Term Frequency- Inverse Document Frequency (TF-IDF) and data splitting into training and testing set with 80:20 ratio. Naïve Bayes and Support Vector machine approaches were used to carry out the classification. Evaluation parameters used were accuracy, precision, recall, F1-score and confusion matrix.  The experimental results reveal that the Naive Bayes technique has an accuracy of 89.73%, a precision of 93.92%, a recall of 84.96% and an F1-score of 89.22%. However, SVM approach achieved 90.37% F1 score, 87.27% recall, 90.70% accuracy and 93.70% precision. The assessment result indicates that SVM technique is better than Naïve Bayes strategy in sentiment classification of customer reviews in Shopee. High accuracy and F1 score. The study result shows that the SVM method is better than the Naïve Bayes method in Shopee customer reviews sentiment categorisation.
Klasifikasi Penyakit Mata Menggunakan ResNet-50 Berdasarkan Citra Fundus Muh. Irsyad Dwi Kurniawan; Anggraini Puspita Sari; Achmad Junaidi
bit-Tech Vol. 8 No. 3 (2026): bit-Tech
Publisher : Komunitas Dosen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32877/bt.v8i3.3306

Abstract

Visual impairment from diabetic retinopathy, glaucoma, and cataracts remains a critical global health issue, emphasizing the need for early and accurate diagnosis to prevent permanent vision loss. This research presents an automated detection system utilizing ResNet-50, a deep learning architecture, to classify fundus images into multiple retinal disease categories. Unlike conventional convolutional neural networks used in prior studies, this approach leverages ResNet-50's residual learning mechanism to better identify complex retinal patterns. The study employed 4,184 fundus photographs from Kaggle, divided into four classes: cataract, diabetic retinopathy, glaucoma, and normal. Images were preprocessed through resizing to 224×224 pixels, normalized with ImageNet parameters, and augmented using random rotation and flipping techniques to enhance model generalization. Dataset splitting followed stratified sampling with an 80-20 train-test ratio, maintaining balanced class representation. Model training spanned 20 epochs using the Adam optimizer across three learning rates: 0.1, 0.01, and 0.001. The 0.001 learning rate produced optimal results with 90.35% accuracy, 90.28% precision, 90.18% recall, and 90.21% F1-score. The confusion matrix indicated strong performance in detecting diabetic retinopathy (219 correct predictions) and normal cases (189 correct predictions), though minor misclassifications occurred between glaucoma and normal categories. These findings validate ResNet-50's residual architecture as an effective tool for extracting discriminative retinal features, offering a computationally efficient solution for automated eye disease screening. Future work should incorporate explainability methods like Grad-CAM to enhance clinical interpretability and build trust among healthcare professionals in AI-assisted diagnostic systems.
Co-Authors Abd Rabi’ Achmad Junaidi Achmad Junaidi, Achmad Achmad Yusuf Yulestiono Addien Haniefardy Adhi Dwi Saputra Adiguna Yudhanto Adila, Mar’atul Adinda Putri Budi Saraswati Aditya, Wigananda Firdaus Putra Adiyatma, Hesel Faza Afandi, Rizki Baehtiar Agung Darmawansyah Agung Mustika Rizki, Agung Mustika Agussalim, Agussalim Agustiardani, Salsa Pramudhita Ahmad Nadhif Fikri Syahbana Ajeng Listya Devani Aji Paringga Jati Akbar, Fawwaz Ali Akbar, M.Azriel Yaqi Al-Ayyubi, Iqbal Alam, Fajar Indra Nur Aldito Restu Wintama Alfajr, Achmad Yuneda Alfi Hendri Alhamda, Denisa Septalian Alif Bayu Ammarizky Alif Ernanda Putra Alvin Rama Saputra Alvin Amelia Ananda Putri Lestari Amrullah, Ahmad Wildan Ana, Vika Rafi Ananda Ayu Puspitaningrum Andre Leto Andreas Nugroho Sihananto Andreas Nugroho Sihananto Anindhyta, Erisa Dwi Xena Aninidta, Sophia ANUGRAH PRASETYA, RAJAWALI SHAKTIKA Aprinia Salsabila Roiqoh Aqil Salim, Mas Muhammad Ar Rafi, Mohammad Hafiz Ardelia, Danika Najwa Ardiansyah, Muhammad Dafa Arhinza, Rayhan Saneval Ariando, Aldo Pradana Aries Boedi Setiawan Arif Nur Cahyo Arif Rahman Hakim Arif Widiasan Subagio Arifani, Kahpi Baiquni Arifin, Hilda Desfianty Arini, Andhini Putri Ariningtyas, Imelda Dwi Arryanto, Bahiskara Ananda Arthansa, Radendha Muhammad Aryananda, Rangga Laksana Atiqur Rozi Aurelia Krisnanti Wijaya Awang Mohammad Ziadhasya Rizqaarrafi AZMI, ANDRA HUSNUL Azzahra Adelia Sabrina Salsabila Azzahra Asti Khairunnisa Bagus Satrio Wicaksono Basuki Rahmat Masdi Siduppa Bayu Setiawan Belva Cynara Trana Putri, Prudencia Bhaswara, Maulana Muzakki Bimantoro, Ryan Bagus Bisma Satrio Bimantoro Budiman, Daniel cahyono, wahyu eko Cinta Ramayanti Citra Firdausi, Putri Aulia Daffa Athallah Fauzan Damai Arbaus, Damai Damayanti, Natasya Meryl Dandi Azaidane Daniel Gloryo Nadirco Danika Najwa Ardelia Daniswara, Sena Danu Satrio Dea Rajwa Zahra Athaya Dela Ayu Putri Mayona Dela Puspita Lasminingrum Delia Citra Kurniasari Deswita Choirun Nisa Devinka Marta Legawa Dewi, Shanty Kurnia Dian Maharani, Dian Dimas Satria Prayoga Dody Pintarko Dody Pintarko Dwi Arman Prasetya Dwi Arman Prasetya Dwi Arman Prasetya Dwi Arman Prasetya Eka Maurita Eka Prakarsa Mandyartha Ekawati, Anies Eko Kuncoro Eko Kuncoro EKO WAHYUDI Elizabeth, Caritta Endyarni, Regina Caeli Erlina Erlina Ayunda Cahyanti Eva Salsabilla Eva Yulia Puspaningrum Fabio Arayya Pratama Fahlefi, Muhammad Reza Fahri Izzuddin Zulkarnaen Fajrina, Nur Septia Farhans, Muhammad Izzudin Fatan Izzatur Rahman Fatchur Rozci Fatma Novalia Kussumarani Fauzan, Daffa Athallah Fina Amru Millati Millati Firdaus Putra Aditya, Wigananda Firmantara, Wahyu Firza Prima Aditiawan Firzannabeel Aqila Rafid Gatot Yulisianto Gatut Yulisusianto Hafiyan Fazagi Adnanto Hamid, Aisyah Amalia Hanin Fatma Soraya Hendri, Alfi Henni Endah Wahanani Hilda Desfianty Arifin Hilya ‘Zada Mardhatilla Al Haadiy Hiroshi Suzuki Icham, Maulana Izuddin Audadi idhom, Mohammad Intan Ni'matul Fitri Intan Putri Mansyur Pratama Iqbal Bagus Satriawan Irsyadi, Muhamad Haidir Irsyadi, Muhammad Haidir Irsyadi, Muhammad Rohman Irwansyah, Ferry Ishak Febrianto Ismail, Jefri Abdurrozak Istiqomah, Nerissabila Uswatun Jaka Subagja Jamaludin . Jeki Saputra Jibran, Kemal Fahreza Joko Lasmono Jonathan Teguh Samuel Kaeng Julastri, Bregsi Atingsari Kahpi Baiquni Arifani Kartika Sari Kartini Kartini Kartini Kartini KEZIA, KEZIA Khairul Anwar Khairunnisa Khairunnisa Khofifah, Nada Firda krisna krisnawati wati Krisnawati Kuncoro, Eko Ledjap, Adventus Michael Bala Leon Ddewandaru Pramudyo Letkol Arh Desyderius Minggu Lina Nurlaili, Afina Lisanthoni, Angela Listanto, Evan Adwitiya Dwi M Julius St M. Rafi Ardiansyah Made Hanindia Prami Swari Maharani, Ardiana Deka MAHARDIKA, NAUFAL INDRA Mahendra, Zenryo Yudi Arnava Darva Maisie Yunita Malva Makarim, Irsyad Fadhil Maliq Reynanda , Revano Marsanda, Dea Ayu Eka Masyhuri, Alif Syahda Adji Maulana, Hendra Maulana, M. Zaky Pria Maulida Shifa Annisa Maurisa Arimbi Putri Mayya, Kalfin Syah Kilau Minggu, Desi Derius Minggu, Desi Derius Mochammad Daffa Faiq Husin Syahputra Moh Avin Dharma Wijaya MOH MARIO SUBAGIO Moh. Misbahul Musthofah Mohammad Idhom Mohammad Quthbul Widad Mohammad, Bawazir Fadhil Muh. Irsyad Dwi Kurniawan Muhamad Vicky Oktafrian Muhammad Abdullah Hafizh Muhammad Hilmy Aziz Muhammad Lizamul Arsi Muhammad Masrur Aji Dorojatun Muhammad Muharrom Al Haromainy Muhammad Rohman Irsyadi Muhammad Rudmardiansyah Pratama Putra Muhammad Shaquille Syafiq Muhammad Wifaqul Azmi Mulyani Satya Bhakti Mulyo, Budi Mukhamad Nabila Anggita Luna Nachrowie, Nachrowie Nadia, Prasinta Hari Nafis Pratama Putra Nandana Wahyu Rizqullah Nicholas, Sandy Ninis Herawati Noor Imansyah Basoeki, Dandy Norhaslinda Binti Hasim Nur Rachman Nur Rachman Supadmana Muda Nurdiansyah, Titis Fajar Nurdianto, Muhammad Akbar Nurlaili, Afina Lina Nurul Hidajati Oktavia Nur Khasanah OKTAVIAN, JAGUAR DEVA NANGGALASAKTI OKTAVIAN Olivia Dewi Ramadhani Suryoningsih Panggih Santri Paramita, Maheswari Dian Pintarko, Dody Prakoso, Akbar Tri Pramudyo, Leon Ddewandaru Prapatoni, Velian Pratama Putra, Moch Aditya Pratama, Moch Nasikh Andhyka Prismahardi Aji Riyantoko Putra Dwi Wira Gardha Yuniahans Putra, Chrystia Aji Putri Salsabila, Belia Putri Wardhani, Lintang Sari Putricia Hendra, Ria Amelia Shinta Rachmawati, Siti Naia Hesti Rahman, Fatan Izzatur Rahman, Muhammad Fadhillah Rahmawati, Deisya Dzakiyyah Rahmawati. S, Abel Dwi Raihan Ramadhan Raissa Atha Febrianti Ramadhani, Aimee Natya Ramadhani, Neo Rendra Ardika Resti Indah Paramita Sari Revano Maliq Reynanda Riandi Zahra, Muhammad Alvin Ridho Fajar Fahturohman Riky Hermawan Ririn Wanandi Rizki, Agung Mustika Rizqullah Sandya Yossie Triwinanda Rochmawati, Febriyan Putri Rofiah, Muflichatur Romadhoni, Firman Rozi, Atiqur Ryan Bagus Bimantoro Sagita, Dhea Intan SALMAN ALFARIZI Samdono, Arif Sampurno Utomo, Moch Wahyu Sandy Nicholas Sanjaya, I Wayan Indra Sakti Sanjaya Santoso, Aries Satriya Yudha Saskia Rafika, Chesa Satrio Dharma Putra Satwika, I Kadek Susila Sena Daniswara Septyana, Dwitamara Setiawan, Aries Buedi Shafara, Anindya Restu Shintyadhita Wirawan Putri Siahaan, Renita Enjel Siharta, Niken Febrinikmah Silitonga, Paulenta Silvania Sischa Wahyuning Tyas Sischa Wahyuning Tyas Siti Sri Wahyuni Siva Ifin Azzahra Subairi Subairi SUGENG HARIANTO Sugeng Harianto Suherman Suherman Suryangga, Nova Suryantari, Putu Anggi Sutrisni, Erica Aprilia Syahbana, Ahmad Nadhif Fikri Syahrul Amin, Akhmad Syamjovanka, Revelin Putri Takahiro Kitajima Takashi Yasuno Tatipang, Angeline Riendra Torrilynn Farrell Zuriely Tresna Maulana Fahrudin Tsabita Safana Mustofa Ulummuddin, Ikhya Wardana, Nabila Sya’bani Wicaksono, Faris Hakim Widoretno, Astrini Aning Widya Indah Sujatmoko, Amanda Wisnu Murti, Hapsoro Yisti Vita Via Yogi Dwi Arsanti Yossie Triwinanda, Rizqullah Sandya Yunizar, Sri Fatmawati Zahran, Muhammad Sulthan Zidan, Ahmad Ziddan, Muhtasar