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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Natural Science: Journal of Science and Technology The Journal of Experimental Life Sciences (JELS) CAUCHY: Jurnal Matematika Murni dan Aplikasi Bulletin of Electrical Engineering and Informatics JAS (Journal of ASEAN Studies) Jurnal Teknologi Informasi dan Ilmu Komputer Jurnal Teknik Pengairan: Journal of Water Resources Engineering Dauliyah Journal of Islamic and International Affairs JOIV : International Journal on Informatics Visualization Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Electro Luceat BAREKENG: Jurnal Ilmu Matematika dan Terapan Kuttab: Jurnal Ilmu Pendidikan Islam Edukasi Islami: Jurnal Pendidikan Islam Jurnal al-Ulum : Jurnal Pemikiran dan penelitian ke-Islaman Jurnal Sisfokom (Sistem Informasi dan Komputer) LINGUISTIK : Jurnal Bahasa dan Sastra Nation State : Journal of International Studies Justisia Ekonomika Journal of Electronics, Electromedical Engineering, and Medical Informatics Ulumuna: Jurnal Studi Keislaman Value: Jurnal Manajemen dan Akuntansi RESIPROKAL: Jurnal Riset Sosiologi Progresif Aktual Community Service Journal of Indonesia Journal of Robotics and Control (JRC) INSPIRASI: Jurnal Kajian dan Penelitian Pendidikan Islam Islam Universalia : International Journal of Islamic Studies and Social Sciences Jurnal Pendidikan dan Kewirausahaan Indonesian Journal of Electrical Engineering and Computer Science Community Development Journal: Jurnal Pengabdian Masyarakat Journal of Management - Small and Medium Enterprises (SME's) Al Ghazali: Jurnal Kajian Pendidikan Islam dan Studi Islam Jurnal Teknik Informatika (JUTIF) Ulumuna Jurnal Teknologi Pendidikan : Jurnal Penelitian dan Pengembangan Pembelajaran At Turots: Jurnal Pendidikan Islam Dharmas Education Journal (DE_Journal) MANAJERIAL: Jurnal Inovasi Manajemen dan Supervisi Pendidikan COMMUNITY : Jurnal Pengabdian Kepada Masyarakat An-Nuha : Jurnal Pendidikan Islam Journal Corner of Education, Linguistics, and Literature Indonesian Journal of Peace and Security Studies PAKDEMAS : Jurnal Pengabdian Kepada Masyarakat Jurnal Teknik Sumber Daya Air Indonesian Journal of Global Discourse Tanfidziya: Journal of Arabic Education JURNAL ILMU PENDIDIKAN Qawanin: Journal of Economic Syaria Law Prosiding University Research Colloquium POACE: Jurnal Program Studi Administrasi Pendidikan Jurnal Ekonomi Syariah dan Hukum Islam Prosiding Konferensi Nasional Penelitian Matematika dan Pembelajarannya Journal Research of Social Science, Economics, and Management KOLONI Innovative: Journal Of Social Science Research Jurnal Pengabdian Masyarakat Bangsa Pengabdian Pendidikan Indonesia (PPI) Indonesian Journal of Mathematics and Applications International Journal of Post-Axial: Futuristic Teaching and Learning Jurnal Kebijakan Pembangunan Daerah (JKPD) Alamtana Aspirasi: Jurnal Ilmiah Administrasi Negara Jurnal Indonesia Mengabdi
Syaiful Anam
School of Political Science and International Studies, Queensland University, Australia
Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities Astronomy Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Immunology & microbiology Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Neuroscience Nursing Physics Public Health Social Sciences Transportation Veterinary Other

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New perspective in enhancing Papanicolaou-smear image using CLAHE and spider monkey optimization Khozaimi, Ach; Muharini Kusumawinahyu, Wuryansari; Darti, Isnani; Anam, Syaiful; Nahdhiyah, Ulfatun
Bulletin of Electrical Engineering and Informatics Vol 14, No 6: December 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v14i6.10250

Abstract

High-quality Papanicolaou (Pap) smear images are essential for reliable early detection of cervical cancer, yet low contrast and noise often hinder accurate interpretation. This study introduces spider monkey optimization (SMO)-contrast-limited adaptive histogram equalization (CLAHE), an optimized CLAHE framework guided by the SMO algorithm. A novel signal contrast (SC) objective function is proposed, combining perceptual enhancement contrast enhancement-based image quality (CEIQ) with fidelity preservation peak signal-to-noise ratio (PSNR) to adaptively tune CLAHE parameters. Experiments on the publicly available SIPaKMeD and Mendeley LBC datasets demonstrate that SMO-CLAHE consistently outperforms manual settings and flower pollination algorithm (FPA)-based optimization, and achieves performance comparable to pelican optimization algorithm (POA) across key quality metrics including entropy, structural similarity index (SSIM), PSNR, enhancement measure estimation (EME), root mean square contrast (RMSC), standard deviation (STD-DEV), and CEIQ. Furthermore, downstream evaluation using a MobileNetV3-S classifier shows that the enhanced images lead to improved cervical cancer classification performance. These results highlight SMO-CLAHE as a robust and clinically relevant preprocessing framework, offering a new perspective for Pap smear image enhancement and diagnostic support.
Triple-Mutation Bat Algorithm–Optimized Extreme Learning Machine for Fetal Health Classification Wisnumurti, Prabowo; Anam, Syaiful; Muslikh, Mohammad
CAUCHY: Jurnal Matematika Murni dan Aplikasi Vol 11, No 1 (2026): CAUCHY: JURNAL MATEMATIKA MURNI DAN APLIKASI
Publisher : Mathematics Department, Universitas Islam Negeri Maulana Malik Ibrahim Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18860/cauchy.v11i1.37525

Abstract

Fetal health assessment is essential for preventing perinatal complications, yet manual interpretation of cardiotocography (CTG) signals is prone to variability and diagnostic delays. This study introduces TMBA–ELM, a hybrid intelligent model that optimizes Extreme Learning Machine (ELM) parameters using the Triple Mutation Bat Algorithm (TMBA). The novelty of this work lies in extending TMBA—originally designed for continuous optimization—into a mixed-variable optimization framework that simultaneously tunes the hidden-node size and the activation function. This is achieved through the integrated use of Cauchy, Gaussian, and time-based mutation strategies, representing the first adaptation of TMBA for ELM parameter optimization and its first application to CTG-based fetal health classification. The model was evaluated on an imbalanced CTG dataset comprising 2,126 samples and benchmarked against BA-ELM, EMD-FA-ELM, and PSO-EM-ELM. TMBA-ELM achieved 89.23% ± 0.44% accuracy, outperforming BA-ELM (ELM models with parameters tunned by ELM) with accuracy 87.37%±0.63%, PSO-EM-ELM (Error-minimizaed-ELM parameters tunned with particle swarm optimization) with accuracy 82.76% ± 1.83%, and EMD-FA-ELM (ELM parameters tunned with firefly algorithm and data decompositioned by empirical decomposition) with accuracy 87.76% ± 1.95%. However, TMBA-ELM required 164.23 ± 12.76 seconds of computation time, which is substantially higher than BA-ELM and PSO-EM-ELM with computing time 60.9 ± 10.24 seconds and 59.69 ± 5 seconds, respectively. Overall, TMBA-ELM provides improved accuracy compared with existing ELM-based models, while its increased computational cost represents a limitation for time-constrained applications.
HETEROGENEOUS GRAPH NEURAL NETWORKS FOR STOCK PRICE PREDICTION: MODELING TEMPORAL AND CROSS-STOCK DEPENDENCIES Bukhori, Hilmi Aziz; Aruchunan, Elayaraja; Anam, Syaiful; Bukhori, Saiful; Maulana, Avin
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 20 No 2 (2026): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol20iss2pp0981-1000

Abstract

Stock price prediction remains a challenging task due to the complex interplay of temporal trends and relational dependencies within financial markets. This study proposes the GNN-LSTM Hybrid model, a novel framework that integrates Graph Neural Networks (GNNs) with Long Short-Term Memory (LSTM) units to simultaneously capture heterogeneous graph structures and temporal dynamics in stock data, leveraging GNNs to model relational dependencies and LSTMs to address long-term temporal patterns, with graph construction based on stock correlation and temporal edge features. Using a dataset covering 1,270 trading days from March 2015 to April 2020, we evaluate the model against traditional methods (ARIMA, LSTM) and modern graph-based approaches (T-GCN, GAT, Transformer-TS, Base GraphSAGE, SAGE-IS). The GNN-LSTM Hybrid achieves superior performance, with a Mean Absolute Error (MAE) of 0.740 (±0.13), Root Mean Squared Error (RMSE) of 1.100 (±0.21), Mean Absolute Percentage Error (MAPE) of 4.92% (±1.16), and Directional Accuracy (DA) of 67.0% (±2.7), and significantly outperforms all baselines, as confirmed by paired t-tests (p < 0.05). Hyperparameter analysis reveals that a configuration of 6 GNN layers and a hidden dimension size of 128 optimizes predictive accuracy, balancing computational efficiency (training time: 16.0 ± 0.7 s) and performance. Validation across 100 training epochs further confirms the model’s robust convergence across all metrics. With an inference time of 20.0 ± 1.0 ms, which is competitive compared to baselines like ARIMA (23.5 ± 1.1 ms) and GAT (20.5 ± 1.0 ms), the GNN-LSTM Hybrid demonstrates strong potential for practical financial forecasting, offering a scalable and accurate solution for capturing the multifaceted dynamics of stock markets, with implications for real-time applications and broader economic modeling.
ENHANCING CERVICAL CANCER IMAGES QUALITY: HYBRID SMO-PMD FILTER FOR NOISE REDUCTION Khozaimi, Ach; Darti, Isnani; Anam, Syaiful; Kusumawinahyu, Wuryansari Muharini
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 20 No 2 (2026): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol20iss2pp1437-1452

Abstract

This study presents an image denoising method for cervical cancer images using the Perona–Malik Diffusion (PMD) filter optimized with the Spider Monkey Optimization (SMO) algorithm. The BRISQUE is proposed as the new objective function. The method was simulated on three datasets: SIPaKMeD, Herlev, and Mendeley Liquid-Based Cytology (LBC). Enhanced image quality was evaluated using MSE, SSIM, PSNR, and Entropy. On the SIPaKMeD dataset, the SMO-PMD filter achieved an average MSE of 0.0454, SSIM of 0.9984, PSNR of 62.27 dB, and Entropy of 5.425. The Mendeley dataset recorded an MSE of 0.3991, SSIM of 0.9994, PSNR of 53.08 dB, and Entropy of 5.489. The Herlev dataset achieved an MSE of 8.1191, SSIM of 0.9688, PSNR of 55.77 dB, and Entropy of 5.203. The SMO algorithm was compared with Particle Swarm Optimization (PSO) and Genetic Algorithm (GA). SMO showed better results across all metrics. The proposed method produces images with lower noise, higher structural similarity, and improved visual quality. The stable entropy values across the datasets indicate that essential diagnostic information was preserved. These findings provide a new perspective for enhancing cervical cancer images using a hybrid SMO-PMD filter. A limitation of this study is that experiments were limited to three datasets, and SMO’s reliance on extreme κ values might reduce stability in other contexts
Pengaruh LMX Terhadap Kinerja Pegawai dengan Loyalitas dan LOC Sebagai Mediasi Anam, Syaiful; Wahyu Utomo, Kabul; Handriyono
Value : Jurnal Manajemen dan Akuntansi Vol. 20 No. 3 (2025): September - Desember 2025
Publisher : Program Studi Manajemen, Fakultas Ekonomi dan Bisnis Universitas Muhammadiyah Cirebon

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32534/jv.v20i3.8164

Abstract

Employee performance is the driving force behind organizational performance improvement. Developing an effective HR development program requires empirical evidence on how LMX, loyalty, and locus of control play a role in shaping employee performance. The research aims to explain how relational leadership shapes behavioural and psychological mechanisms that determine performance outcomes. A quantitative survey was administered to academic and administrative staff at a private university, and data were analysed using Structural Equation Modelling–Partial Least Squares. Findings show that high-quality LMX directly enhances employee performance and significantly strengthens both loyalty and internal locus of control. Loyalty functions as an emotional mechanism that reinforces commitment, whereas internal locus of control emerges as the strongest mediator, indicating that psychological empowerment plays a critical role in sustaining high performance. The results highlight the importance of supportive leadership, professional recognition, and participatory work environments in improving organisational outcomes. This study contributes to the literature by integrating relational and psychological constructs within one predictive model and by extending the application of relational leadership theories in higher education institutions. The findings offer practical insights for university management in designing leadership development, employee engagement initiatives, and performance enhancement strategies.
IMPROVING MADRASAH TEACHERS' COMPETENCIES IN ARTIFICIAL INTELLIGENCE-BASED LEARNING DATA PROCESSING IN BATU CITY Anam, Syaiful; Aziz Bukhori, Hilmi; Maulana, Avin; Yanti, Indah; Gustiningsih Hapsani, Anggi
Community Service Journal of Indonesia Vol. 7 No. 2 (2025): Community Service Journal of Indonesia
Publisher : Institute for Research and Community Service, Health Polytechnic of Kerta Cendekia, Sidoarjo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36720/csji.v7i2.813

Abstract

Teacher competence is a crucial factor in improving the quality of education..This community service program aimed to enhance the professional competence of madrasah teachers in processing learning data using artificial intelligence (AI)-based tools. Conducted through a one-day intensive workshop in Batu City, the program involved 18 teachers from five madrasahs at the Madrasah Aliyah and Madrasah Tsanawiyah levels. The training adopted the ADDIE instructional design model, covering needs analysis, AI-assisted data processing with Google Sheets and ChatGPT/OpenAI, reinforcement of AI ethics, and infographic creation. Quantitative evaluation showed a significant improvement in participants’ competencies, with average scores increasing from 60.3 (pre-test) to 86.3 (post-test). The most notable progress was observed in logical operations (IF function mastery) and ethical awareness in AI use, while 88% of participants reported high satisfaction with the training content and delivery. The program effectively integrated digital literacy, ethical reflection, and practical application to foster teacher professionalism. Beyond individual competence, this initiative contributed to building a sustainable collaborative network through the Subject Teachers’ Working Group (MGMP) and provided a replicable model for technology-based professional development in Islamic education.
Implementasi Pendidikan Agama Islam Berbasis Al-Quran Dan Sunnah Menurut Pemahaman Salafus Shalih Usman, Arif; Bahresy, Fiqqi Assidieq; Romadhon, Wahyu Rizky; Afrizon, Afrizon; Anam, Syaiful; Jumadi, Jumadi
An-Nuha Vol 6 No 1 (2026): Islamic Education
Publisher : Prodi Pendidikan Keagamaan Islam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/annuha.v6i1.779

Abstract

This study aims to analyze the implementation of Islamic Religious Education (PAI) based on the Quran and Sunnah according to the understanding of Salafus Shalih at Pondok Pesantren Ihya' As-Sunnah Singkut, Jambi. In the midst of modern educational challenges, the Salafiyah model offers a return to the purity of Islamic teachings (Tasfiyah) and authentic upbringing (Tarbiyah). This research uses a qualitative descriptive case study approach with data collected through learning observations, in-depth interviews with administrators and teachers (Ustadz), and curriculum documentation. The findings show that: (1) The curriculum integrates the National and Pesantren Curriculum with emphasis on Aqidah Tauhid, Tahfidz Al-Quran, and Arabic; (2) Learning methods prioritize talaqqi, memorization, and practicing sunnah; (3) Educational orientation places Adab (manners) before Ilm (knowledge). The implication is the formation of students with strong religious identity, skills, and noble character following the guidance of Prophet Muhammad Shalallahu ‘alaihi wasallam.
KAPITAL SOSIAL DALAM PEMBANGUNAN DESA: KRITIK TERHADAP PROGRAM TRADE AND DISTRIBUTION CENTER (BUMDES) DI WILAYAH LOMBOK BARAT-PROVINSI NTB Anam, Syaiful; Hdayat, Alfian; Zulkarnain, Zulkarnain
Jurnal Kebijakan Pembangunan Daerah Vol 7 No 1 (2023): Juni 2023
Publisher : Badan Perencanaan Pembangunan Daerah Provinsi Banten

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56945/jkpd.v7i1.227

Abstract

Development agendas related to improving welfare in developing countries often face failure. In post-authoritarian Indonesia, the development and policy model patterns are still very elite, centralistic, and clientelist. It even often negates the value of local wisdom as one of the failure’s root causes. This study examines how development programs integrate noble values or social capital as the Development Engine. In the context of village development in NTB, to achieve the vision contained in Governor’s NTB Gemilang Program, the village (Trade and Distribution Center) TDC program is designed, namely the distribution program and Trade Center in the village through the Village-owned Enterprise (BUMDes-Badan Usaha Milik Desa) business scheme. This scheme aims to modernize and digitize the village by fulfilling the basic needs of the village population. This program also is expected to contribute to the village’s domestic income (PADes). However, in the development of BUMDes in Indonesia, this policy model is often distorted for political and development interests that are partial and short-term. This study examines and critically studies the loss of social capital in implementing the TDC program. Modernization and digitalization in the village development agenda, in general, have a good purpose. But it will also damage the values of village Wisdom when development removes an important aspect of existing social capital. Through an exploratory qualitative approach, this study focuses on the pilot project TDC in West Lombok NTB, which implicitly found that social capital is not reproduced in the development agenda because it is deemed as entirely political and elite both in the making and implementation.
The Effect of Price Discount and Electronic Word of Mouth on Purchase Intention with Brand Image as a Mediator (A Case Study of Generation Z Coffee Consumers in Surabaya) Anam, Syaiful; Daniel, Joseph Robert
Journal Research of Social Science, Economics, and Management Vol. 5 No. 7 (2026): Journal Research of Social Science, Economics, and Management
Publisher : Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59141/jrssem.v5i7.1308

Abstract

The rapid growth of social media and digital platforms has transformed consumer behavior, particularly among Generation Z, who increasingly rely on online information and promotional offers when making purchasing decisions. In Indonesia, TikTok has emerged as a key marketing channel, with local brands like Kopi Kenangan leveraging discounts and electronic word of mouth (e-WOM) to engage young consumers. However, the interplay between price incentives, digital recommendations, and brand perception remains underexplored in the context of coffee consumption. The purpose of this research is to determine the effect of price discounts and e-WOM on buying interest through the mediating role of brand image. The data source for this study is primary data. The sampling technique used was purposive sampling, with a total of 400 Generation Z respondents in the city of Surabaya. Data collection was conducted through the distribution of questionnaires. This study employs the SEM-PLS analysis method using the SmartPLS version 4.0 data processing tool. The results indicate that price discounts and e-WOM have a significant effect on brand image. In addition, price discounts, e-WOM, and brand image have also been proven to significantly influence buying interest. The findings further reveal that brand image mediates the influence of price discounts and e-WOM on buying interest.
The Artificial Bee Colony (ABC) Algorithm for Estimating Parameter of Epidemic Influenza Model Nirmalasari, Ririn; Suryanto, Agus; Anam, Syaiful
The Journal of Experimental Life Science Vol. 10 No. 1 (2020)
Publisher : Graduate School, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1048.636 KB) | DOI: 10.21776/ub.jels.2019.010.01.06

Abstract

The Artificial Bee Colony (ABC) is one of the stochastic algorithms that can be applied to solve many real-world optimization problems. In this paper, The ABC algorithm was used to estimate the parameter of the epidemic influenza model. This model consists of a differential system represented by variations of Susceptible (S), Exposed (E), Recovered (R), and Infected (I). The ABC processes explore the minimum value of the mean square error function in the current iteration to estimate the unknown parameters of the model. Estimating parameters were made using participation data containing influenza disease in Australia, 2017. The best parameter chosen from the ABC process matched the dynamical behavior of the influenza epidemic field data used. Graphical analysis was used to validate the model. The result shows that the ABC algorithm is efficient for estimating the parameter of the epidemic influenza model. Keywords: ABC, Epidemic, Estimate, Influenza, Parameter.
Co-Authors A.Mirza Fauzan Gazali, A.Mirza Fauzan Abd. Aziz Abdul Bari Abdul Rouf Alghofari Achmad Taufik Adella Novita Aeri Rachmad AFRIZON AFRIZON, AFRIZON Agus Supriyadi Agus Suryanto Ahmad Afif Supianto Aji, Kurniawan Akhmad Khumaidi Akhodiyah, Sulistina Alfian Hidayat Alifiobono, Adeva Amalia Amar, Siti Salama Anam, Afdolul Andreas Andriani , Fitri Angga Rizky, Agus ani ani Ardiyansa, Safrizal Ardana Arif Usman Arifin Arifin Aris Munandar Aruchunan, Elayaraja Asyidiqi, Hasbi Asyrofa Rahmi, Asyrofa Ayu Dwi Lestari, Cynthia Ayudaning D , Pamungkas Aziz Bukhori, Hilmi Baehaqi bahresy, fiqqi assidieq Bukhori, Hilmi Aziz Bustamin, Syamsumar Choa, Yeshua Austin Harvey Daniel, Joseph Robert Deny Tisna Amijaya, Fidia Devita Sari, Nindy Dian Eka Ratnawati Dian Sisinggih Dian Sisingih, Dian Dwi Mifta Mahanani, Dwi Mifta Dwi Ratnasari Edi Satriyanto Fahrul Riza Fajri, Haidar Ahmad Fatirul, Achmad Noor Fauzi, Rahman Ali Feby Indriana Yusuf Fery Widhiatmoko Fiantika, Feny Rita Fisnia Pratami Fitriah, Zuraidah Guci, Abdi Negara Gustiningsih Hapsani, Anggi Habibatul Islamiyah, Ummi Habibi, Nur Syakherul Hadi Wijoyo, Satrio Hady Rasikhun Hamdani, Ibnu Mansyur Hamiduddin, Hamiduddin Hanayanti, Citra Siwi Handayani, Nilam Handriyono Hasbullah Hasbullah Hdayat, Alfian Helen Yuliana Angmalisang Husni , Valencia Ikhwanudin, Tedy Ilyas, Muhaimin Imadoeddin, Imadoeddin Imam Nurhadi Purwanto Indah Yanti Irma Noervadila Isnani Darti Jayanti, Luh Putu Dharma Judijanto, Loso Julianto, Eric Jumadi Jumadi Kabul Wahyu Utomo Karjaya, Lalu Puttrawandi Karsim, Karsim Kasanova, Ria Kasyful Amron Khafid Ismail Khairurrizki, Khairurrizki Khozaimi, Ach. Kurniadi, Harso Kusumawinahyu, Wuryansari M Kusumo, R. Budiarianto Suryo Lailatul Jannah, Noor Lestari, Baiq Ulfa Septi Lestari, Cynthia Ayu Dwi Lestari, Silvya Anggun Lina, Roidah Maharani, Natasha Clarissa Maharani, Natasha Clarrisa mahmudy, wayan f Mar'atun, Chairanil Mardialina, Mala Marsudi Marsudi Marsum Marsum Maulana, Avin Maulana, M. Idam Maulana, Zacki Ibnu Maulida, Ghina Rahmah Miftahus Surur, Miftahus Mila Kurniawaty Mohammad Muslikh Muhammad Rivai Muharini Kusumawinahyu, Wuryansari Muhtashor, Imam Munir, Ahmad Mubarak Muzaky, Ahmad Nagib, Rima Abdul Mujib Nahdhiyah, Ulfatun Nalasari , Lista Tri Nanang Rifa'i, Muhamad Ni Wayan Surya Wardhani Nirmalasari, Ririn Nono Hery Yoenanto Noor Hidayat, Noor NUR HAMID Nur Shofianah Nurdiana, Titin Pardede, Hilman Ferdinandus Prasetyo, Onky Puspito, Bayu Putra, M. Rafael Andika R. Suhaimi Rahmawati Rifa'i, Dhila Silvia Rahmawati, Reny Rosalina Ramdani, Ahmad Ratri, Dian Kusumaning Rifa'i, Muhamad Nanang Rifa’i , Muhamad Nanang Rini Aristin, Rini RINI RINI Rizki, Kurnia Zulhandayani robbaniyah, qiyadah Romadhon, Wahyu Rizky Ronaldo, Reza Rosi, Muhammad Fathur Rosid, Muchamad Rosulana, Ahmad Rudiyanto, Mohammad Sabilla, Kinanti Rizsa Safitri, Anisa Dewi Saiful Bukhori Saputri, Levia Sari, Meylita Sa’adah, Umu Shofianah, Nur Siska Siska Sofia Mendez Suhaimi Suhaimi Sukma Umbara Tirta Firdaus, Sukma Umbara Tirta Sukowati, Laila Sundari Sundari Suryani Suryani Syaiful . Syarifatul Azaliyah, Syarifatul Trisilowati Trisilowati, Trisilowati Tuloli, Mohamad Handri Tuminem, Hannan Azka Umbara, Sukma Utomo, M. Chandra Cahyo Utomo, Yudo Bismo Uyun, Nazdrotul Very Dermawan Vicky Zilvan, Vicky Wahada, Listiatul Wayan Firdaus Mahmudy Widiyanto Widiyanto Widyantoro, Didik Wijaya, Komang Agus Arta Wisnumurti, Prabowo Wuryasari Muharini Kusumawinahyu Yuli Kartika Dewi Yunanto, Fredy Zabadi, Fairus Zulkarnain Zulkarnain