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All Journal TEKNIK INFORMATIKA Dinamik SEGMEN Jurnal Manajemen dan Bisnis GEMA TEKNOLOGI Techno.Com: Jurnal Teknologi Informasi Jurnal Simetris Syntax Jurnal Informatika Elkom: Jurnal Elektronika dan Komputer Jurnal Ilmiah Mahasiswa FEB Prosiding SNATIF Jurnal Ketahanan Nasional Jurnal Teknologi Informasi dan Ilmu Komputer Jurnal Berkala Epidemiologi Seminar Nasional Informatika (SEMNASIF) CESS (Journal of Computer Engineering, System and Science) E-Dimas: Jurnal Pengabdian kepada Masyarakat JOIN (Jurnal Online Informatika) Sinkron : Jurnal dan Penelitian Teknik Informatika Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) SISFOTENIKA Journal of Information Technology and Computer Science (JOINTECS) JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Jurnal Ilmiah FIFO Jurnal Pilar Nusa Mandiri InComTech: Jurnal Telekomunikasi dan Komputer Prosiding Seminar Nasional Teknoka JRST (Jurnal Riset Sains dan Teknologi) JOURNAL OF APPLIED INFORMATICS AND COMPUTING SINTECH (Science and Information Technology) Journal JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI Jurnal Sisfokom (Sistem Informasi dan Komputer) JURNAL EDUCATION AND DEVELOPMENT Jiko (Jurnal Informatika dan komputer) JSiI (Jurnal Sistem Informasi) Explore IT : Jurnal Keilmuan dan Aplikasi Teknik Informatika JURIKOM (Jurnal Riset Komputer) Jurnal Telematika JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) STRING (Satuan Tulisan Riset dan Inovasi Teknologi) CCIT (Creative Communication and Innovative Technology) Journal Journal of Information System, Applied, Management, Accounting and Research Jurnal Ilmiah Ilmu Komputer Fakultas Ilmu Komputer Universitas Al Asyariah Mandar Journal of Electronics, Electromedical Engineering, and Medical Informatics Jurnal Ilmu Komputer dan Bisnis Syntax Idea Techno Xplore : Jurnal Ilmu Komputer dan Teknologi Informasi Jurnal Informatika dan Rekayasa Perangkat Lunak Jurnal Mnemonic Jurnal Asiimetrik: Jurnal Ilmiah Rekayasa Dan Inovasi International Journal of Advances in Data and Information Systems Journal of Computer Science and Engineering (JCSE) SKANIKA: Sistem Komputer dan Teknik Informatika Jurnal Teknik Informatika (JUTIF) Jurnal Pewarta Indonesia JURNAL KOMUNIKASI DAN BISNIS Ascarya: Journal of Islamic Science, Culture and Social Studies Jurnal PkM (Pengabdian kepada Masyarakat) Humantech : Jurnal Ilmiah Multidisiplin Indonesia Media Publikasi Promosi Kesehatan Indonesia (MPPKI) Bit (Fakultas Teknologi Informasi Universitas Budi Luhur) Journal Of Human And Education (JAHE) Prosiding Seminar Nasional Sisfotek (Sistem Informasi dan Teknologi Informasi) Economic Reviews Journal Jurnal Algoritma Jurnal Ticom: Technology of Information and Communication Berita Kedokteran Masyarakat Jurnal Hasil Pengabdian Masyarakat (JURIBMAS) Journal of Systems Engineering and Information Technology J-Icon : Jurnal Komputer dan Informatika Jurnal Teknik Indonesia Research Horizon IIJSE Jurnal Relawan dan Pengabdian Masyarakat REDI Jurnal Pengabdian Masyarakat Nasional Health Dynamics Jurnal Ticom: Technology of Information and Communication The Indonesian Journal of Computer Science Seminar Nasional Riset dan Teknologi (SEMNAS RISTEK) Prosiding SeNTIK STI&K Journal of Medical and Health Science Jurnal Ilmu Kesehatan Immanuel Jurnal Ekonomi, Manajemen, Akuntansi dan Keuangan
Arief Wibowo
Universitas Budi Luhur
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THE INFLUENCE OF SOCIAL INTERACTION, KNOWLEDGE SHARING, AND PERCEPTIONS OF WORKLOAD ON TEACHER'S READINESS FOR CHANGE AT SMA XYZ-NORTH JAKARTA Wibowo, Arief; Rakhman, Abdulah
Jurnal Komunikasi dan Bisnis Vol. 11 No. 1 (2023): May
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat Institut Bisnis dan Informatika Kwik Kian Gie

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46806/jkb.v11i1.927

Abstract

This study aimed to examine the influence of the variables of social interaction, knowledge sharing, and perceived workload on readiness for change among teachers at SMA XYZ in North Jakarta. The research method used is a quantitative research method. The number of respondents in this study were 38 teachers. The sample used is all teachers who are currently working at SMA XYZ in North Jakarta. The sampling technique is based on nonprobability sampling using the questionnaire method, namely by providing a list of questions directly to the respondents. The analysis method uses Structural Equation Modeling - Partial Least Square (SEM-PLS) with the WarpPLS 7.0 program. The conclusion of this study is that Social Interaction has a negative and significant effect on Readiness for change, Knowledge Sharing has a positive and significant effect on Readiness for change, and Workload Perception has a positive and significant effect on Readiness for Change for teachers at SMA XYZ in North Jakarta.
Analisis Ekspor Kopi Menggunakan Clustering K-Means dan Davies-Bouldin Index Irawati, Fenny; Nugroho, Angelika Pratiwi Widya; Wibowo, Arief
Jurnal Ilmiah FIFO Vol 17, No 2 (2025)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/fifo.2025.v17i2.006

Abstract

Indonesia merupakan salah satu produsen kopi terbesar di dunia, sehingga sektor ekspor menjadi pilar penting dalam perekonomian nasional. Aktivitas ekspor berperan dalam meningkatkan keuntungan, memperluas pangsa pasar, serta menjaga kestabilan harga komoditas dan nilai tukar. Penelitian ini mengkaji penerapan metode K-Means Clustering untuk menganalisis kinerja ekspor kopi berdasarkan negara tujuan. Data penelitian diperoleh dari catatan ekspor perusahaan Café Coffee pada periode 2023–2024, mencakup 40 negara tujuan beserta total kuantitas ekspor. Pengolahan data dilakukan melalui teknik data mining clustering dengan ukuran jarak Euclidean Distance. Hasil analisis menunjukkan bahwa algoritma K-Means berhasil mengelompokkan laba ekspor ke dalam tiga kategori, yaitu laba rendah, sedang, dan tinggi. Validasi model dilakukan menggunakan Davies-Bouldin Index (DBI) dengan nilai 0,422, yang mengindikasikan kualitas klaster yang baik dan dapat diterima.
Deteksi Emosi Teks X Berbahasa Indonesia Menggunakan Bi-LSTM dengan Seleksi Fitur Chi-Square Wangsajaya, Yosia Heartha Dhalasta; Setyowati, Erlin; Wibowo, Arief
Jurnal Algoritma Vol 22 No 2 (2025): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.22-2.2658

Abstract

Emotions are an important indicator in understanding public responses on social media, particularly X, which is the main medium for public expression. This study aims to develop a classification model for the emotions of Indonesian-speaking X users using a Bidirectional Long Short-Term Memory (Bi-LSTM) approach combined with data mining-based feature selection techniques. A dataset of approximately 6,000 tweets was collected through X scraping based on keywords and hashtags representing six main emotions: anger, sadness, fear, happiness, love, and surprise, from January 2024 to March 2025. The obtained data was processed through text normalization, stop word removal, and tokenization stages. Features were extracted using TF-IDF and selected using the Chi-Square method to improve classification performance. Tweets were labeled with emotions manually and semi-automatically. The Bi-LSTM model was trained and tested using accuracy, precision, recall, and F1-score metrics. Initial test results showed an accuracy of 86.3%, with the best performance on the emotions “happy” and “angry.” This study shows that the integration of deep learning and data mining can improve the accuracy of automatic emotion detection in Indonesian text. The main contribution of this study is the integration of Chi-Square feature selection with Bi-LSTM for Indonesian text, which has not been widely explored before.
Random Forest and Artificial Neural Network Data Mining for Environmental and Public Health Risk Modeling in Flood-Prone Urban Areas of Indonesia Mahdiana, Deni; Ebine, Masato; Wibowo, Arief
Jurnal Teknik Informatika (Jutif) Vol. 6 No. 6 (2025): JUTIF Volume 6, Number 6, Desember 2025
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2025.6.6.5387

Abstract

Floods in urban Indonesia pose severe environmental and public health challenges, exacerbating water contamination, vector proliferation, and disease outbreaks. Rapid urbanization, inadequate drainage systems, and climate change have intensified these impacts, emphasizing the need for integrated predictive frameworks. This study aims to develop a Data Mining (DM)-based modeling approach that combines environmental and health indicators to predict flood-related disease risks. Random Forest (RF) and Artificial Neural Network (ANN) algorithms were applied to multi-domain datasets from 30 flood-prone urban sub-districts between 2018 and 2023, encompassing rainfall, drainage density, land use, and water quality variables, integrated with disease incidence data such as diarrhea, dengue, and leptospirosis. The ANN model achieved superior predictive performance (93% accuracy, AUC 0.93) compared to RF (90% accuracy, AUC 0.90), identifying rainfall intensity, drainage density, and coliform contamination as the most influential predictors. These results demonstrate the capability of AI-driven DM techniques to capture complex interdependencies between environmental and health systems. The developed framework contributes to the field of informatics by providing a scalable, data-driven early warning tool for flood-related health risks, supporting evidence-based decision-making in disaster risk management and enhancing public health resilience in rapidly urbanizing regions.
Kearifan Lokal sebagai Fondasi Ketahanan Masyarakat Pesisir Menghadapi Ancaman Tsunami di Pesisir Kabupaten Bantul, Daerah Istimewa Yogyakarta Rahman, Fathin Aulia; Wibowo, Arief; Achadi, Abdul Haris
Jurnal Ketahanan Nasional Vol 31, No 3 (2025)
Publisher : Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/jkn.112955

Abstract

Penelitian ini bertujuan untuk menganalisis peran kearifan lokal sebagai fondasi ketahanan masyarakat pesisir Kabupaten Bantul dalam menghadapi ancaman tsunami. Latar belakang penelitian ini berasal dari tingginya ancaman bencana Tsunami di wilayah pesisir selatan Yogyakarta yang menuntut strategi mitigasi berbasis nilai lokal dan sosial budaya. Metode penelitian menggunakan pendekatan kuantitatif dengan membagikan kuesioner kepada 179 responden masyarakat pesisir serta didukung oleh analisis deskriptif dan interpretatif terhadap variabel pengetahuan lokal, keyakinan masyarakat, praktik adat, pola komunikasi, dan kepekaan lingkungan. Hasil penelitian menunjukkan bahwa variabel Keyakinan Masyarakat menjadi aspek paling dominan dengan nilai rerata indeks 4,13, khususnya indikator dorongan budaya/agama untuk gotong royong saat bencana (4,31) yang memperlihatkan kekuatan solidaritas sosial. Sementara itu, indikator kemampuan mengamati tanda-tanda alam (2,61) merupakan aspek terendah yang menandakan menurunnya pengetahuan ekologis tradisional. Temuan ini mengindikasikan bahwa nilai budaya dan spiritualitas masih menjadi kekuatan utama dalam membangun ketahanan sosial, namun perlu diimbangi dengan revitalisasi pengetahuan lokal dan penguatan sistem peringatan dini. Kesimpulannya, sinergi antara kearifan lokal dan teknologi modern menjadi kunci penting dalam membangun resiliensi masyarakat pesisir terhadap ancaman tsunami. 
PERENCANAAN STRATEGIS SISTEM INFORMASI KLINIK KECANTIKAN MENGGUNAKAN PENDEKATAN WARD AND PEPPARD (Studi Kasus PT Visi Putri Pramudhita Visi Beauty Clinic) Monica, Silvi; Wibowo, Arief
Journal of Information System, Applied, Management, Accounting and Research Vol 10 No 1 (2026): JISAMAR (February 2026)
Publisher : Sekolah Tinggi Manajemen Informatika dan Komputer Jayakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52362/jisamar.v10i1.2221

Abstract

The development of information technology requires every organization, including beauty clinics, to have an information system that is well-planned, integrated, and aligned with business strategy. This study aims to develop a strategic information system plan for Visi Beauty Clinic using the Ward and Peppard model as the main approach. The model is used to analyze the internal and external business environment, the internal and external IS/IT environment, as well as to formulate IS/IT management strategies. Various analytical techniques are applied, including Value Chain, SWOT, PEST, Five Forces, and the McFarlan Strategic Grid to comprehensively map application needs. The results show that Visi Beauty Clinic faces intense industry competition, increasing customer bargaining power, and demands for technology-based services. On the other hand, the clinic has opportunities to enhance its competitive advantage through service innovation, data integration, and strengthened information systems. Based on these findings, this study proposes an application portfolio that includes an electronic medical record system, health service system, executive information system, supply chain management, financial system, pharmacy application, human resource system, and an integrated distributed database. The resulting IS/IT strategic blueprint provides direction for application development based on strategic, operational, and potential priorities. Overall, the formulated IS/IT strategic plan supports business process efficiency, improves service quality, and strengthens the competitive position of Visi Beauty Clinic in the beauty industry. The implementation of these recommendations is expected to create added value and support the achievement of the company’s long-term vision.
Analisis Segmentasi Pelanggan dengan Algoritma K-Means pada Data Penjualan Nazihah, Fasya; Danniswara, Ahmad; Wibowo, Arief
Jurnal Algoritma Vol 22 No 2 (2025): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.22-2.2489

Abstract

Competition in the world of sales is becoming increasingly fierce, so store owners need the right strategy to understand customer behavior patterns and increase sales. One of the most widely used data analysis methods is K-Means Clustering, which can be used to find patterns and trends in sales data. This study was conducted with the aim of determining customer segmentation based on sales transaction data in order to obtain customer groups with similar characteristics. The method applied in this study was the K-Means algorithm on a sales dataset with a total of 1,289 customer data. Cluster quality was evaluated using the Davies-Bouldin index (DBI), with a DBI result of 0.077, indicating excellent cluster quality. The analysis resulted in three customer clusters, namely: the first cluster (C1) consisting of loyal buyers with 562 customers, the second cluster (C2) consisting of occasional buyers with 279 customers, and the third cluster (C3) consisting of buyers with an average purchase of 448 customers. The implication of these research results is that management can develop more appropriate marketing strategies, such as providing a personal approach to loyal customers and designing specific strategies to attract occasional buyers to become more loyal. Thus, these research results can serve as a basis for more effective marketing decision-making.
ANALISIS PENGELOMPOKKAN DISTRIBUSI FASILITAS PENDIDIKAN DI INDONESIA DENGAN METODE KLASTERISASI Nurfadhiilah, Annisa; Martens, Brigitta Griselda; Wibowo, Arief
Jurnal Education and Development Vol 14 No 1 (2026): Vol 14 No 1 Januari 2026
Publisher : Institut Pendidikan Tapanuli Selatan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37081/ed.v14i1.7598

Abstract

Penelitian ini bertujuan untuk menganalisis sebaran fasilitas pendidikan di seluruh wilayah provinsi di Indonesia pada tahun 2024, mencakup jenjang mulai dari Sekolah Dasar/Madrasah Ibtidaiyah hingga tingkat Perguruan Tinggi. Sumber data berasal dari Sakernas tahun 2024 yang dirilis oleh BPS sebagai sumber data utama. Dalam penelitian ini, digunakan pendekatan statistik deskriptif untuk melihat pola distribusi fasilitas pendidikan, serta memanfaatkan metode K-Means clustering guna membagi provinsi ke dalam kategori berdasarkan tingkat ketersediaan fasilitas tersebut. Hasil evaluasi menggunakan Davies-Bouldin Index mengindikasikan bahwa pemodelan dengan dua klaster memiliki tingkat pemisahan terbaik dengan nilai indeks 0,083, sementara model lima klaster memberikan pembagian wilayah yang lebih rinci dengan skor indek sebesar 0,088. Hasil analisis menunjukkan ketimpangan signifikan dalam akses pendidikan antarprovinsi dan antarjenjang, dengan fasilitas cenderung berkurang pada jenjang pendidikan yang lebih tinggi. Provinsi di Pulau Jawa menunjukkan dominasi dalam jumlah fasilitas, sedangkan provinsi di Indonesia bagian timur masih menghadapi kekurangan. Penelitian ini memberikan dasar bagi perumusan kebijakan pemerataan pendidikan di Indonesia.
Pemodelan Tren Kasus Hiv dan Klasterisasi Wilayah menggunakan Algoritma K-Means dan Decision Tree - Studi Kasus di Kabupaten Bogor Bintang, Bagus; Triantoro, Ery; Wibowo, Arief
Dinamik Vol 31 No 1 (2026)
Publisher : Universitas Stikubank

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35315/dinamik.v31i1.10310

Abstract

Infectious diseases remain a dynamic and evolving public health threat, requiring data-driven approaches for early detection and targeted policy planning. This study aims to model spatio-temporal trends and clustering patterns of HIV transmission in Bogor Regency during the period 2020–2023 by utilizing a combination of unsupervised and supervised machine learning techniques. The dataset was obtained from the Bogor Regency Health Office and includes annual data on the number of HIV cases across 40 sub-districts. The research methodology consists of data preprocessing stages, clustering using the K-Means algorithm, and classification using a Decision Tree model. The preprocessing steps include data integration, attribute selection, temporal aggregation, handling of missing data, and normalization using Z-score. K-Means clustering is applied to identify hidden patterns in the development of HIV cases, resulting in three distinct clusters based on multi-year trends. The resulting cluster labels are then used as target classes in the supervised classification process. The Decision Tree classification model demonstrates high accuracy in predicting cluster membership, indicating a strong relationship between the temporal patterns of HIV cases and cluster identity. The integration of clustering and classification techniques provides a robust analytical framework for understanding the dynamics of HIV transmission, while also supporting the formulation of more precise, evidence-based, and region-specific public health interventions.
ANALISIS PREDIKTIF TREN WABAH DEMAM BERDARAH MENGGUNAKAN MODEL PEMBELAJARAN MESIN BERBASIS RAPIDMINER Herriyawan, Herriyawan; Timur, Muhammad Bagus Bintang; Wibowo, Arief
Dinamik Vol 31 No 1 (2026)
Publisher : Universitas Stikubank

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35315/dinamik.v31i1.10356

Abstract

Demam berdarah dengue merupakan tantangan kesehatan masyarakat yang terus berulang di wilayah tropis, termasuk Indonesia. Penelitian ini bertujuan untuk memprediksi jumlah kasus tahunan dengan memanfaatkan lima algoritma pembelajaran mesin, yaitu Regresi Linier, Decision Tree, Random Forest, Support Vector Machine (SVM), dan Neural Network. Data historis tahun 2017–2024 diolah menggunakan teknik windowing deret waktu untuk menghasilkan fitur lag yang sesuai bagi pembelajaran terawasi. Evaluasi kinerja dilakukan melalui metrik Mean Absolute Error (MAE), Mean Squared Error (MSE), Root Mean Squared Error (RMSE), serta koefisien determinasi (R²). Model Decision Tree menunjukkan performa paling unggul pada sebagian besar indikator. Prediksi untuk tahun 2025 mengindikasikan adanya peningkatan moderat jumlah kasus. Namun, rendahnya nilai R² pada seluruh model mengisyaratkan perlunya pendekatan multivariat yang lebih kompleks dengan mempertimbangkan faktor iklim, lingkungan, dan demografi. Hasil penelitian ini menegaskan pentingnya kualitas data dan pemilihan fitur yang tepat dalam peramalan epidemiologis guna mendukung perencanaan kesehatan yang lebih efektif.
Co-Authors - Arientawati - Sumardianto Abdul Rachman Achadi, Abdul Haris Adita, Ita Afifah Khaerani Afifatussalamah, Rizka Ahmad Sururi Ahmad Sururi Akbar, Ahmad Aldizar Al Fatach, M Khabib Anggraini, Julaiha Probo Anita Anita Diana Antika Zahrotul Kamalia Anugrah Sandy Yudhasti Anuqman Fitriadi Apriati Suryani Ardhianto, Angga Ardianah, Eva Ari Wibowo Arief Umarjati Asep Permana Atik Ariesta Bayu Sadewo Bayu Satria Pratama Binarto, Antonius Jonet Bintang, Bagus Boerhan Hidayat, Boerhan Chairul Rizal Chintya Paramitha Danar Wido Seno Danniswara, Ahmad Deni Mahdiana Diah Indriani Didik Hariyadi Raharjo Didin Muhidin Dwi Kristanto Dwi Yulianti Dyah Retno Utari Dyah Retno Utari, Dyah Retno Ebine, Masato Efendi, Irman Eko Aji Putra Endah Sarah Wanty Fajar Siddik Chaniago Farah Chikita Venna Farid Setiawan Farid Setiawan, Farid Febrilliani, Jihan Sastri Fenny Irawati Ferdian, Sevtian Fernando, Donny Firman Noor Hasan Firmanty Mustofa, Vina Fitri Nur Masruriyah, Anis Fitri Rachmilah Fadmi Fitriadi, Rifqi Fitriani, Netty Fransiska Vina Sari Frenda Farahdinna Fried Sinlae Ghapur, Abdul Gurdani Yogisutanti Hadidtyo Wisnu Wardani Hananto, Agustia Handoko, Andy Rio Hanindita, Meta Herdiana Hari Basuki Notobroto Haris Achadi, Abdul HARIYANTO HARIYANTO Harun Nasrullah Hassan, Shiza Hayatul Khairul Rahmat Henry Henry Herriyawan, Herriyawan Hidayat, Manarul Hidayat, Sarifudlin Huda, Ratu Najmil Ida Ariyani Hasanah Indah Rizky Mahartika Indra Indra Inge Virdyna Irfan Hadi Irfan Nurdiansyah Istiqoomatun Nisaa Jasmine, Meuthia Joko Sutrisno Jovansgha Avegad Jumaryadi, Yuwan Kanasfi, Kanasfi Karyaningsih, Dentik KRESNO YULIANTO Kresno Yulianto KUNTORO Kuntoro Kuntoro Kurnia Setiawan Kutanto, Haronas Larasati, Pamela Linda Lingga Desyanita Luthfi Akbar Ramadhan Mahmudah Mahmudah Mailana, Agus Manurung, Ridho Parmonangan Maria Adiningsih Marlina, Hesti Martens, Brigitta Griselda Maskur A, Moch Riyadi Megananda Hervita Permata Sari Megawati, Rina Miechael, Miechael Miftahul Arifin Miftahul Arifin Mochammad Rizky Royani Moh Makruf Monica, Silvi Muhamad Fadel Muhammad Bagus Bintang Timur, Muhammad Bagus Bintang Muhammad Febrian Rachmadhan Amri Muhammad Noor Hasan Siregar Muhammad Risky Mulyati Mulyati Nazihah, Fasya Nendi, Nendi Ningrum, Yogi Ajeng Nugroho, Angelika Pratiwi Widya Nur Aisiyah Widjaja, Nur Aisiyah Nur Rohman Nurcahya, Gelar Nurfadhiilah, Annisa Nurfidaus, Yasmine Nursyi, Muhamad Pattipeilohy, William Frado Pattipeilohy, William Frado Pebriaini, Prisma Andita Popalia, Qamarullah Poppy Ruliana Pradiptha, Anindya Putri Prastiyo, Krisna Probo Anggraini, Julaiha Purwadi Purwadi Putra, Andi Agung Putra, Rinaldi Febryatna Duriat Rachmah Indawati Rahman, Fathin Aulia Rahmawati, Nur Anisah Rakhman, Abdulah Rakhmat Rakhmat Rakhmat Rakhmat RAMAYU, I Made Satrya Rangkuti, Muhammad Yusuf Rizqon Ratna Ayu Sekarwati Ratna Ayu Sekarwati Relawanto, Bowo Ria Puspitasari Riama Simanjuntak Ridho Dwi Maulida Rika Nurhayati Riki Ramdani Saputra Rina Megawati Ririh Yudhastuti Risaychi, Diva Ajeng Brillian Ristiana, Ina Riza, Yeni Rizkiyanto, Muhamad Ardiansyah Roedi Irawan Rojakul, Rojakul Rosita Dewi, Erni Ruliana, Poppy Rusdah Ruwirohi, Jan Everhard Ryo Tanaka Sabirin, Sahril Sadewo, Bayu Santoso, Febrina Mustika Saptari Wijaya Mulia Sari Anggar Kusuma Melati Sari, Fransiska Vina Sari, Wulan Novita Sasongko, Raden Satiri Satiri, Satiri Selamet Riyadi Selly Rahmawati Selly Rahmawati Septian Firman S Sodiq Septiani, Riska Setya Haksama Setyowati, Erlin Shofinurdin Shofinurdin Siddik Chaniago, Fajar Sigit Ari Saputro Sigit Budi Nugroho Siregar, Sutan Syahdinullah SITI NURUL HIDAYATI Sitti Aliyah Azzahra Soenarnatalina Melaniani Sudewo, Andika Hasbigumdi Sugiyarta, Ahmad Sujiharno Sujiharno Sumarna, Presma Dana Scendi Suntoro, Dimas Fahmi Supiyandi Supiyandi Syahirah, Afifah Tarmudzi, Rizky Tarwan Tiaharyadini, Rizka Triantoro, Ery TRISNAWATI, WULAN Tulus Yuniasih Umam, Mohamad Hafidhul Vasthu Imaniar Ivanoti Wahyu Cesar Wahyu Desena Wahyudi, Widi Wahyuni, Chatarina Unggul Wangsajaya, Yosia Heartha Dhalasta Wasis Budiarto Wibiyanto, Alif Dewan Daru Widiyaningrum, Diyah Kiki Widyanto, Tetrian Windhu Purnomo Yahya Darmawan Yudanto, Satyo Zakaria Anshori Zaqi Kurniawan