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All Journal JURNAL SISTEM INFORMASI BISNIS Ilmu Administrasi Publik Tadris: Jurnal keguruan dan Ilmu Tarbiyah ANDHARUPA Jurnal Humanitas: Katalisator Perubahan dan Inovator Pendidikan Jurnal Teori dan Praksis Pembelajaran IPS Jurnal Sosiologi Pendidikan Humanis JOIV : International Journal on Informatics Visualization PRISMA SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan Applied Information System and Management Martabe : Jurnal Pengabdian Kepada Masyarakat JURNAL PENDIDIKAN TAMBUSAI Ensiklopedia of Journal Minda Baharu JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Menara Ilmu International Journal for Educational and Vocational Studies Jurnal Studi Guru dan Pembelajaran Social, Humanities, and Educational Studies (SHEs): Conference Series Jurnal Menara Ekonomi : Penelitian dan Kajian Ilmiah Bidang Ekonomi Building of Informatics, Technology and Science The Indonesian Journal of Social Studies The Journal of Society and Media JURNAL GEOGRAFI Geografi dan Pengajarannya JOURNAL OF INFORMATION SYSTEM MANAGEMENT (JOISM) Journal of Herbal, Clinical and Pharmaceutical Science (HERCLIPS) Jurnal Partisipatoris IJIIS: International Journal of Informatics and Information Systems Abdimasku : Jurnal Pengabdian Masyarakat Suluah Bendang: Jurnal Ilmiah Pengabdian Kepada Masyarakat International Journal of Environmental, Sustainability, and Social Science Journal of Applied Data Sciences Jurnal Pengabdian Masyarakat Indonesia International Journal of Social Learning (IJSL) Journal La Lifesci International Journal of Social Science Indonesian Journal of Engagement, Community Services, Empowerment and Development (IJECSED) International Journal of Engagement and Empowerment (IJE2) SOCIAL : Jurnal Inovasi Pendidikan IPS Jurnal Pengabdian Kepada Masyarakat Jurnal Abdi Masyarakat Indonesia JUSTIN (Jurnal Sistem dan Teknologi Informasi) Jurnal Pengabdian Masyarakat untuk Negeri (UN-PENMAS) Jurnal Teknologi Sistem Informasi Jurnal Puan Indonesia Kajian Moral dan Kewarganegaraan Mudabbir: Journal Research and Education Studies Journal of Comprehensive Science Dedikasi: Jurnal Pengabdian Kepada Masyarakat Zona Manajerial: Program Studi Manajemen (S1) Universitas Batam Jurnal Pendidikan Indonesia (Japendi) Indonesian Research Journal on Education Innovative: Journal Of Social Science Research Jurnal Pengabdian Ibnu Sina International Journal of Emerging Research and Review Jurnal Manajerial dan Bisnis Tanjungpinang WASATHON Khidmat : Jurnal Pendidikan dan Ilmu Sosial Jurnal Pendekar Nusantara Zona Kebidanan : Program Studi Kebidanan Universitas Batam Jurnal Medika: Medika Society Jurnal Pengabdian Masyarakat Inovasi Indonesia Jurnal Dialektika Pendidikan IPS Edumaspul: Jurnal Pendidikan
Sarmini Sarmini
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Sistem Pendukung Keputusan Berbasis K-Means untuk Evaluasi Keberhasilan Bisnis dan Nilai Perusahaan Sarmini, Sarmini; Ma'arifah, Windiya; Tahyudin, Imam
Jurnal Sistem Informasi Bisnis Vol 14, No 4 (2024): Volume 14 Nomor 4 Tahun 2024
Publisher : Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21456/vol14iss4pp363-374

Abstract

Business development is in line with the development of increasingly sophisticated technology. This requires every company to compete and be motivated to increase its value as an indicator of success in managing the company so that investors are interested in investing. This study aims to design a K-means-based Decision Support System with a clustering approach to classify the growth rate of company value. Investment Opportunity Set (IOS) and profitability variables are the leading indicators of increasing company value. The problem formulation is how the design of this K-means-based decision support system can assist in classifying the growth rate of the company's value based on the IOS and profitability variables. This research aims to produce a decision support system that can organize the growth rate of company value using the K-means method. System testing is conducted to evaluate the effectiveness of the applied clustering method, focusing on the accuracy of the results. The weighting of IOS and profitability variables is based on the percentage of positive relationship to firm value, and the ultimate goal is to group companies with different growth rates. As a result, the K-means-based Decision Support System, or "Business Growth Prediction Decision Support System," successfully clustered the growth rate of firm value. With reasonable accuracy, measured using the silhouette coefficient, the calculation results show an overall mean silhouette coefficient of 0.684, close to the maximum value of 1. This result confirms that this decision support system can group companies in the L (Low), M (Medium), and H (High) categories based on the level of value growth, using the IOS and profitability variables as the leading indicators. Thus, this research supports decisions related to company growth strategies using K-means-based decision support systems.
Performa Random Forest dan XGBoost pada Deteksi Penipuan E-Commerce Menggunakan Augmentasi Data CGAN Sarmini, Sarmini; Sunardi, Sunardi; Fadlil, Abdul
Building of Informatics, Technology and Science (BITS) Vol 6 No 3 (2024): December 2024
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v6i3.6430

Abstract

Fraud detection in e-commerce faces great challenges due to data imbalance, where legitimate transactions far outnumber fraudulent transactions. This research explores the use of Conditional Generative Adversarial Network (CGAN) to generate synthetic fraudulent transaction data to address the imbalance problem. By increasing the amount of data in the minority class, this research aims to improve the performance of two widely used machine learning algorithms, namely Random Forest and XGBoost. The dataset used of 23,634 transactions with 22,412 non-fraud transactions and 1,222 fraudulent transactions. Accuracy, precision, recall, and F1-score metrics were conducted to assess the performance of the model in detecting fraud on the imbalanced and augmented datasets. The results show that augmentation of data with CGAN significantly improves the performance of both models, especially in improving recall for fraudulent transactions. On the original unbalanced dataset, Random Forest and XGBoost showed low recall (12.81% and 13.08%), with accuracy of 95.35% and 95.32% respectively. However, after augmentation, recall improved to 95.15% for Random Forest and 95.22% for XGBoost, with F1-score of 97.47% and 97.42% respectively, and accuracy of 97.50% for Random Forest and 97.42% for XGBoost. XGBoost showed a slight advantage in precision and recall over Random Forest, especially on the augmented dataset. These findings confirm the effectiveness of CGAN as a data augmentation method in improving fraud detection performance and offer a robust solution to address data imbalance in the financial sector.
Pengaruh Kualitas Pelayanan Proses Pembelajaran Guru IPS Terhadap Kepuasan Peserta Didik Kelas VIII di SMP Negeri 2 Sei Bamban Gomgom Samosir, Marinus; Turhan, Muhammad; Sarmini, Sarmini
MUDABBIR Journal Research and Education Studies Vol. 5 No. 1 (2025): Vol. 5 No. 1 Januari - Juni 2025
Publisher : Perkumpulan Manajer Pendidikan Islam Indonesia (PERMAPENDIS) Prov. Sumatera Utara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56832/mudabbir.v5i1.650

Abstract

Penelitian ini bertujuan untuk mendeskripsikan : (1). Bagaimana kualitas pelayanan pembelajaran guru IPS terhadap kepuasan peserta didik kelas VIII di SMP Negeri 2 Sei Bamban. (2) Apakah terdapat pengaruh kualitas pelayanan proses pembelajaran guru IPS di SMP Negeri 2 Sei Bamban terhadap peserta didik. Adapun jenis penelitian ini adalah kuantitatif menggunakan metode ex post facto. Populasi pada penelitian ini yaitu peserta didik kelas VIII dengan jumlah sampel sebanyak 62 responden/peserta didik. Teknik pengumpulan data yang digunakan dalam penelitian ini adalah observasi, kuesioner, dan studi dokumentasi.Hasil penelitian dengan pengujian secara parsial uji t membuktikan terdapat pengaruh kualitas pelayanan proses pembelajaran guru IPS terhadap kepuasan peserta didik dengan nilai thitung sebesar 3,385 dan nilai ttabel diketahui sebesar 1,999 yang berarti nilai thitung lebih besar dari ttabel (3,385 > 1,999), maka keputusan dalam penelitian ini adalah diterima. Selanjutnya berdasarkan hasil uji koefesien determinasi, menunjukkan tabel R Square sebesar 0,160 atau sama dengan 16,0%.
Pengembangan Edu-Ekowisata Batik Kabupaten Magetan untuk Penguatan Pendapatan Daerah menuju Green Economy Nasional Rahmadyanti, Erina; Susanti, Martini D.E; Sarmini, Sarmini; Mulyono, Agus Taufik; Supriyanto, Muhammad
UN PENMAS (Jurnal Pengabdian Masyarakat untuk Negeri) Vol 4 No 2 (2024): UN PENMAS Vol 4 No 2
Publisher : LPPM Universitas Narotama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29138/un-penmas.v4i2.2796

Abstract

Kegiatan ini bertujuan untuk mengembangkan pariwisata kreatif berbasis edu-ekowisata green industry batik di Desa Sidomukti. Metode yang digunakan meliputi edukasi dan sosialisasi, rancang bangun, serta pelatihan dan pendampingan. Hasil yang diperoleh adalah 1) peningkatan jumlah wisatawan rata-rata sebesar 7-10% per bulan; 2) introduksi peder batik mampu menghasilkan pewarnaan kain sebanyak 700 m/hari dengan jumlah pewarna sejumlah 30 gr/L untuk mencukupi 3,5 m kain mori dengan kecepatan pewarnaan 4,5 m per 10 menit; 3) instalasi pengolahan air limbah terbukti efisien untuk mengolah limbah cair batik Sidomukti karena memenuhi standar Peraturan Gubernur Jawa Timur No. 72 Tahun 2013 tentang baku mutu air limbah bagi industri tekstil. Hasil pengolahan menunjukkan kandungan TSS sebesar 14.9 mg/L, COD sebesar 6,4 mg/L, ammonia total (NH3-N) sebesar 0,037 mg/L; BOD5 sebesar 3 mg/L, dan chromium total sebesar 0,047 mg/L; 4) dukungan penguatan teknologi tepat guna (pelorod malam, penerangan, pemanenan air hujan), pengembangan sarana prasarana (booth makanan, spot foto, art shop, akomodasi, dan toilet umum bertema “batik”, serta penyelenggaraan kegiatan (events) bertema “batik” (lomba desain motif, fashion show , lomba mewarnai batik maupun mural batik) diperlukan untuk mendukung keberlanjutan pariwisata kreatif edu-ekowisata green industry batik Sidomukti.
Peran Akuntansi Menuju Ketahanan Bangsa Richmayati, Maya; Sandra, Elminaliya; Khadijah, Khadijah; Sarmini, Sarmini; Fauziah, Syifa
PUAN INDONESIA Vol. 6 No. 2 (2025): Jurnal Puan Indonesia Vol 6 No 2 Januari 2025
Publisher : ASOSIASI IDEBAHASA KEPRI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37296/jpi.v6i2.324

Abstract

Akuntansi adalah instrumen strategis untuk mendukung ketahanan bangsa dari berbagai dimensi, mulai dari manajemen keuangan, pembangunan ekonomi, hingga terciptanya keadilan sosial sesuai dengan sila kelima Pancasila. Dengan sistem akuntansi yang baik, bangsa dan negara dapat menghadapi tantangan ekonomi, politik, dan sosial dengan lebih tangguh. Identitas nasional sangat berharga karena dengan identitas nasional yang kuat, hal itu akan diakui oleh berbagai negara di seluruh dunia. Salah satu contohnya adalah produk-produk yang dihasilkan oleh UMKM dan dikonsumsi oleh seluruh penduduk Indonesia. Dengan mempercayai produk UMKM, bangsa Indonesia akan memperkuat persatuan Indonesia dan meningkatkan ketahanan bangsa dan negara, sehingga negara asing ragu untuk memasarkan produk mereka di dalam negeri. Akuntansi adalah "bahasa" yang akan dikomunikasikan kepada pengguna. Dalam akuntansi, ada empat laporan yang akan dihasilkan: laporan laba rugi, laporan arus kas, neraca, dan laporan perubahan ekuitas. Oleh karena itu, standar akuntansi keuangan (SAK) diperlukan dalam penyusunannya agar laporan keuangan yang dihasilkan berkualitas baik. Ini berlaku untuk perusahaan yang sudah terdaftar di bursa, karena mereka akan diaudit oleh auditor eksternal. Bagaimana pencatatan dilakukan oleh individu yang bukan berasal dari industri, khususnya individu pribadi yang tidak memahami akuntansi, maka pencatatan cukup dengan laporan laba rugi menggunakan konsep "pendapatan-biaya-biaya operasional."
Uji Aktivitas Antibakteri Deodorant Spray Tea Tree Oil (Melaleuca alternifolia) Terhadap Staphylococcus aureus Hidayati, Nurul; Budiman, Hendra; Sarmini, Sarmini
Journal of Herbal, Clinical and Pharmaceutical Science (HERCLIPS) Vol 6 No 01 (2024): HERCLIPS VOL 06 NO 01
Publisher : Universitas Muhammadiyah Gresik

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30587/herclips.v6i01.8244

Abstract

Deodorant spray adalah produk kosmetik yang digunakan untuk menyerap keringat, manutup bau badan, dan mengurangi bau badan. Deodorant yang beredar dan digunakan masyarakat sebagian besar berbahan dasar sintesis. Penggunaan deodorant berbahan sintesis secara terus-menerus berdampak buruk bagi tubuh. Solusinya adalah dengan mengembangkan formulasi deodorant spray dengan zat aktif alami. Tea tree oil efektif sebagai antibakteri, yang dapat mengendalikan bau ketiak. Tujuan penelitian ini adalah untuk mengetahui aktivitas antibakteri deodorant spray terhadap Staphylococcus aureus dan formula dengan konsentrasi tea tree oil yang dapat menghambat paling kuat. Metode penelitian ini eksperimental laboratorium. Formula deodorant menggunakan variasi konsentrasi tea tree oil yaitu 2% (F1), 3% (FII), dan 5% (FIII). Sediaan kemudian dilakukan evaluasi organoleptis, homogenitas, pH, viskositas, daya sebar, daya lekat, kejernihan, dan uji aktivitas antibakteri. Hasil penelitian menunjukkan ketiga formula dapat menghambat Staphylococcus aureus, dibuktikan dengan adanya zona hambat. Formula terbaik deodorant spray yaitu F3 dengan konsentrasi tea tree oil 5% dengan zona hambat paling kuat yaitu 24, 6 mm.
Novel Predictive Framework for Student Learning Styles Based on Felder-Silverman and Machine Learning Model Maulana Baihaqi, Wiga; Eko Saputro, Rujianto; Setyo Utomo, Fandy; Sarmini, Sarmini
Journal of Applied Data Sciences Vol 5, No 4: DECEMBER 2024
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v5i4.408

Abstract

This study analyzes data from the Open University Learning Analytics Dataset to evaluate how students' interactions with Virtual Learning Environment (VLE) materials influence their final outcomes. This research aims to formulate and build a novel predictive framework based on the Felder-Silverman and Machine Learning Model for student learning styles. Based on these objectives, this research provides novelty and contributions since it enhances student data analysis, uses a learning model using Felder-Silverman Learning Style Model (FSLSM) to give a more comprehensive understanding of students' learning styles, and improves prediction accuracy by introducing Artificial Neural Network (ANN) and feature selection using Random Forest. The data used includes 3 main files: vle.csv, which contains information about the materials and activities in the VLE; studentVle.csv, which records students' interactions with the materials; and studentInfo.csv, which provides demographic information of students and their final outcomes. The analysis process involved data merging and processing, including handling of missing values, data type conversion, as well as mapping activity types to learning style features based on the FSLSM. We use the Random Forest feature selection method, as well as data imbalance handling techniques such as oversampling, to improve model performance. The applied classification models include Logistic Regression, K-Nearest Neighbor, Random Forest, Support Vector Machine (SVM), and ANN. The analysis results showed that after tuning, the Random Forest model achieved 97% accuracy, while SVM achieved 97% accuracy as well, with better performance than previous studies. This research highlights the importance of comprehensive data integration and appropriate processing techniques in improving the accuracy of student learning style prediction. Based on the increase in accuracy results, it can be beneficial for more effective personalized learning and improve our understanding of students' learning style preferences. The research advances knowledge and provides practical applications for educators to tailor their teaching strategies.
Predicting Network Performance Degradation in Wireless and Ethernet Connections Using Gradient Boosting, Logistic Regression, and Multi-Layer Perceptron Models Widiawati, Chyntia Raras Ajeng; Sarmini, Sarmini; Yuliana, Dwi
Journal of Applied Data Sciences Vol 6, No 1: JANUARY 2025
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v6i1.519

Abstract

This study explores predicting network performance degradation in wireless and Ethernet connections using three machine learning algorithms: XGBoost, Logistic Regression, and Multi-Layer Perceptron (MLP). Key metrics, including accuracy, precision, recall, F1-score, and AUC-ROC, were employed to evaluate model performance. The MLP classifier achieved the highest accuracy (98.7%) and AUC-ROC (0.9998), with a precision of 1.0000 and recall of 0.8622, resulting in an F1-score of 0.9260. Logistic Regression provided reasonable baseline performance, with an accuracy of 93.67%, AUC-ROC of 0.9565, and an F1-score of 0.5992, but struggled with non-linear dependencies. XGBoost showed limited utility in detecting degradation events, achieving an F1-score of 0 despite a perfect AUC-ROC (1.0), indicating sensitivity to imbalanced data. Through hyperparameter tuning, MLP demonstrated robustness in capturing complex patterns in network latency metrics (local_avg and remote_avg), with remote_avg emerging as the most predictive feature for identifying degradation across both network types. Visualizations of latency dynamics demonstrate the higher predictive relevance of remote latency (remote_avg) in both network types, where spikes in this metric are closely associated with degradation. The findings underscore the effectiveness of using latency metrics and machine learning to anticipate network issues, suggesting that MLP is particularly well-suited for real-time, predictive network monitoring. Integrating such models could enhance network reliability by enabling proactive intervention, crucial for sectors reliant on continuous connectivity. Future work could expand on feature sets, explore adaptive thresholding, and implement these predictive models in live network environments for real-time monitoring and automated response.
Health and Socio-Demographic Risk Factors of Childhood Stunting: Assessing the Role of Factor Interactions Through the Development of an AI Predictive Model Hariguna, Taqwa; Sarmini, Sarmini; Azis, Abdul
Journal of Applied Data Sciences Vol 5, No 4: DECEMBER 2024
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v5i4.612

Abstract

Stunting is a significant global health problem, especially in developing countries such as Indonesia. This study aims to develop and evaluate an artificial intelligence (AI)-based predictive model to identify the risk of stunting in children using the CatBoost algorithm which is a combination of Weighted Apriori and XGBoost. This model is designed to utilize the advantages of each algorithm in handling data with variable weights to improve prediction accuracy. Feature analysis shows that "Height (cm) Age (months)" are the main indicators in classifying children's nutritional status. Model evaluation shows high accuracy of 94.85%, precision of 95%, recall of 94.85%, and F1 Score of 94.84%. Kappa Coefficient and Matthews Correlation Coefficient (MCC) reached 93.13% and 93.19%, respectively, while ROC-AUC reached 99.70%. These findings indicate that the CatBoost model can provide highly accurate results in detecting the risk of stunting and offer in-depth insights into risk factors that can improve the effectiveness of health interventions. This study fills the gap in the literature by integrating the Weighted Apriori and XGBoost algorithms, providing a significant contribution to early detection of stunting and supporting government efforts to reduce the prevalence of stunting in Indonesia and other regions.
PELAKSANAAN PROGRAM DZIKIR JAMA’I JUM’AT PAGI DAN TAUSIYAH SISWA SEBAGAI MANAJEMEN PENDIDIKAN KARAKTER DI SEKOLAH ISLAM NABILAH BATAM, KEPULAUAN RIAU Sarmini, Sarmini; Titik W, Diana; Ferdila, Ferdila; Mustika, Ita; Catra Y, Wayan
Martabe : Jurnal Pengabdian Kepada Masyarakat Vol 7, No 11 (2024): MARTABE : JURNAL PENGABDIAN MASYARAKAT
Publisher : Universitas Muhammadiyah Tapanuli Selatan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31604/jpm.v7i11.4513-4518

Abstract

Program Penguatan Pendidikan Karakter (PPK) yang tertuang dalam Perpres Nomor 87 Tahun 2017 merupakan bagian dari penyiapan generasi     mendatang     untuk     menghadapi tantangan dan tuntutan abad ke-21. Landasan hukum   pendidikan   karakter   di   Indonesia adalah  Pancasila  dan  UUD  1945  Konsensus tersebut    lebih    lanjut    ditegaskan    melalui Undang-Undang   Nomor   20   Tahun   2003 tentang Sistem Pendidikan Nasional (Saputro and  Murdiono,  2020).  Ada  empat  dimensi pendidikan   karakter   yang   tersurat   dalam tindakan yaitu:   perkembangan   intelektual, perkembangan    spiritual    dan    emosional, perkembangan    fisik,    dan    perkembangan kreativitas. Pengabdian yang dilakukan di Sekolah Islam Nabilah Batam bertujuan untuk mendukung dan memaksimalkan dalam pelaksanaan program Dzikir Jama’i serta Tausiyah Siswa yang sudah dilaksanakan sebagai salah satu Pendidikan Karakter. Dalam Pengabdian Masyarakat ini menggunakan metode Pelatihan dan menyampaian informasi serta penerapan dalam pelaksanaannya pada program Dzikir Jamai, dan Tausiyah Siswa sebagai Manajemen Pendidikan Karakter. Pelaksanaan Pengabdian di Sekolah Islam Nabilah dilaksanakan mulai dari 24 April s.d. 24 Mei 2024. Peserta dihadiri oleh siswa-siswi SMP dan SMA Islam Nabilah yang berjumlah kurang lebih 110 siswa. Pemberi materi 3 dosen dan 2 mahasiswa dari Universitas Batam dan Universitas Ibnu Sina, Batam.  
Co-Authors Abdul Azis Abdul Fadlil Abednego Dwi Septiadi Adiatma, Febriansyah Husni Aditiya, Eka Candra Rachmad Adiya, Az Zahra Dwi Nur Afianti, Nur Azizah Agung Dwi Bahtiar El Rizaq agung setiawan Agus Suprijono Agus Taufik Mulyono AHMAD MUZAKKI Ali Imron Amalia Fatma Pitaloka Amelia, Cevy Andhanie, Shafa Andi Hidayatul Fadlilah Andika Prasetya Nugraha Anindya, Salsa ANNA NOORDIA Arif Rahman Hakim Ariyanti Ariyanti Ariyanti Ariyanti Artono Artono, Artono Astri Wahyuningsih Aura Afan Shabrina Ayudya Nova Puspaningtyas BAYU SEGARA PUTRA, GEDE Bela, Sita Bonda Sisephaputra Budiarto, Mochamad Kamil Catra Y, Wayan Cevy Amelia Chyntia Raras Ajeng Widiawati Daniel Happy Putra Diah Ainin Budiarti DWI GATI, NITA Dwi Dwi Krisbiantoro, Dwi Dzakkiyah, Alya Khansa Dzikri, Muhammad Zulfikar Eka Tripustikasari, Eka Elminaliya Sandra Elsa Komala, Elsa Ervina Halit Fandi Fatoni Fandy Setyo Utomo Fauziyyah, Ulfah Febri Edward Febrianti, Diah Ratna Ferdila, Ferdila Filanzi, Shendy Fira, Choly Septa Fitriya, Ulthufna Kausarul FX Sri Sadewo Gading Gamaputra Galih Setyawan, Katon Gomgom Samosir, Marinus Gunawan, Dahlan Harmanto Harmanto Hendra Budiman Hidayati, Armawati hidayatulloh, hanif Ilham, Rifqi Arifin Imam Tahyudin Indriyani, Ria Irvani, Zendika Ita Mardiani Zain Jacky, M Katon Setyawan Ketut Prasetyo Khadijah Khadijah Kharisma, Marcellina Tiara Putri Khasanah, Fitrotul Khoerida, Nur Isnaeni Kristanti, Fania Putri Kurnia Imtichatus Sholichah Kusmanto, Hari Kusnul Khotimah Kusnul Khotimah Laila Vika Safitri Lailiyah, Faridatul Lediawati, Teni Siti Linayati Lestari, Linayati Listyaningsih Listyaningsih LUTFAIDAH, ANNA M. Jacky, M. Jacky M., Jacky Ma'arifah, Windiya Mahat, Hanifah Maulana Baihaqi, Wiga Maya Richmayati Mengkepe, Amy Dara Istikoma MUHAMMAD JACKY Muhammad Turhan Yani Mujahidin, Muhammad Diwanul Mulyadi Mulyadi Mustika, Ita Nabilah, Shafa Rizqi NAGALIMAN, Nagaliman Nanda, Risma Nasution Nasution Nasution Nasution Ngaliman, Ngaliman Ningrum, Diah Luckyta Niswatin Nuansa Bayu Segara Nugroho Hari Purnomo Nur Habibah Nurdewanti, Nilam Puspita Nurjanah, Rita Nurul Hidayati Oksiana Jatiningsih Pahlevi, Rahma Shintya Pambayun, Niken Lia Prihatiningtias Pamor Gunoto Prameswari, Karina Puspita Prastuti, Ajeng Eka Pratama, Cindy Arinda Diah Pratama, Irfan Pratama, Satrya Fajri Pratama, Wildan Razzaq Puspaningtyas, Ayudya Nova Putranto, R. Vitto Mahendra Rahmadyanti, Erina Rahmah, Anisa Aulia Rahmawati, Rizqi Rahmi Nurhaini, Rahmi Ramadhan, Rio Fadly Rasyid, Suparta Ratna Dewi Silalahi Rendianto, Fakrul Aldi Rini Elfina Risa Ayu Aktavia Riski Darma Santi Risnawati Risnawati Riswandhi Ismail Rujianto Eko Saputro Sabri Sabri Salma, Karina Salsabila, Firdausi Irma Sanuri, Ranti Saputra, Aina Aldi Saputri, Inka Sasmita Timur, Elshinta Agustin Satriawan, Bambang SEPTINA ALRIANINGRUM Setiyono, Rizal Setyawan, Katon Galih Silalahi, Ratna Dewi Siraj Siraj Siti Maizul Habibah Sri Hartini Sri Yanti Sriwahyuni, Tutik Subarkah, Pungkas Sugandi, Zain Arif Wildan SUGENG HARIANTO Suhaimi Suhaimi Sukartiningsih, Sri Sukma Perdana Prasetya Sumantri, Sumatri Sunardi Sunardi Sunarto Sunarto Supriyanto, Muhammad Susanti, Martini D.E Suyono Suyono Syahrizaldy, Hikmalul A'la Syawaldi, Rizky Bilal Syifa Fauziah Taqwa Hariguna Tarwoto, Tarwoto Turhan, Muhammad Ulthufna Kausarul Fitriya Uswatun Hasanah Wahid, Arif Mu'amar Wahyu, Herta Tri Waluyo, Retno Warsono Warsono Widiawati, Chyntia Windayati, Dian Titik Windayati, Diana Titik wisnu wisnu, wisnu Yahya, Saifudin Yenny Aryaneta Yi, Ding Yuanita FD Sidabutar Yuliana, Dwi Yuliarti, Agnes Pradini Yulvinda, Rossa Yuniar, Indhiawan Yunita, Ika Romadoni Zamzami, Mohammad Aqil Misbach Zein, Ita Mardiani