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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 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 RESIPROKAL: Jurnal Riset Sosiologi Progresif Aktual Community Service Journal of Indonesia Journal of Robotics and Control (JRC) INSPIRASI: Jurnal Kajian dan Penelitian Pendidikan Islam 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 Dharmas Education Journal (DE_Journal) MANAJERIAL: Jurnal Inovasi Manajemen dan Supervisi Pendidikan COMMUNITY : Jurnal Pengabdian Kepada Masyarakat 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 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 Jurnal Cendekia Ilmiah Aspirasi: Jurnal Ilmiah Administrasi Negara Jurnal Indonesia Mengabdi
Syaiful Anam
School of Political Science and International Studies, Queensland University, Australia
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OPTIMIZING HEART ATTACK DIAGNOSIS USING RANDOM FOREST WITH BAT ALGORITHM AND GREEDY CROSSOVER TECHNIQUE Ardiyansa, Safrizal Ardana; Maharani, Natasha Clarissa; Anam, Syaiful; Julianto, Eric
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 18 No 2 (2024): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol18iss2pp1053-1066

Abstract

Cardiovascular disease stands as one of the primary contributors to global mortality, with the World Health Organization (WHO) reporting approximately 17.9 million deaths annually. Swift and accurate diagnosis of heart attacks is crucial to ensure timely and specialized intervention for patients afflicted by this ailment. A machine learning algorithm that can be employed for addressing such issues is the Random Forest algorithm. However, the efficacy of the model is significantly influenced by the features selected during the training phase. To mitigate this, the Binary Bat Algorithm (BBA) with greedy crossover has been utilized to enhance feature selection within the model. This approach is particularly adept at preventing convergence issues often associated with local minima. The optimal parameters for BBA with greedy crossover are determined to be , , , and . With these parameters, the proposed algorithm identifies the most relevant features, including age, gender, cp, chol, thalach, oldpeak, slope, and ca, achieving an accuracy of 94.19% on the training data and 91.8% on the test data. Furthermore, the precision and recall values for both classes range from 0.87 to 0.96, contributing to an approximate -score of 0.92. The proposed method has increased its -score by 0.05 if compared with the regular Random Forest model. These results underscore the effectiveness of the proposed algorithm in providing accurate and reliable predictions for heart disease diagnosis. As such, this model makes diagnosing heart attack more convenient and effective because it does not require too much medical features or patient data. Hopefully, the results of this research help medical practitioners make better and timely decisions in the diagnosis and treatment of heart attacks, as well as assist in planning more effective public health programs for heart attack prevention.
An Enhanced Particle Swarm Optimization with Mutation for Mean-Value-at-Risk Portfolio Optimization in the Indonesian Banking Sector Anam, Syaiful; Bukhori, Hilmi Aziz; Maulana, Avin; Maulana, M. Idam; Rasikhun, Hady
Jurnal Teknik Informatika (Jutif) Vol. 6 No. 4 (2025): JUTIF Volume 6, Number 4, Agustus 2025
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2025.6.4.5191

Abstract

Portfolio optimization in emerging markets is challenging because high volatility and non-normal return distributions reduce the effectiveness of traditional mean–variance models, which tend to underestimate downside risk. This study aims to develop and evaluate an Enhanced Particle Swarm Optimization with Mutation (PSO with Mutation) for portfolio optimization under the Mean-Value-at-Risk (Mean-VaR) framework in the Indonesian banking sector. The novelty of this approach lies in integrating a mutation operator into standard PSO to maintain population diversity, prevent premature convergence, and improve exploration of the solution space. To evaluate the method, daily adjusted closing prices of 31 Indonesian bank stocks from January 2020 to July 2025 were collected. Preprocessing included removing tickers with incomplete data and computing daily returns. The optimization problem was formulated using Mean-VaR as the risk measure, with portfolio weight constraints. The proposed PSO with Mutation was benchmarked against standard PSO, Genetic Algorithm (GA), Bat Algorithm (BA), BA with Mutation, and classical models (Markowitz and Monte Carlo–based VaR). Performance was assessed using expected return, Mean-VaR, risk-adjusted return, Sharpe ratio, execution time, and stability across 25 independent runs. The results show that PSO with Mutation achieved a competitive expected return (0.0020), the lowest Mean-VaR (0.0311), the highest risk-adjusted return (0.0650), and the lowest variability across runs, while maintaining acceptable execution time. These findings confirm that mutation-enhanced PSO provides a robust, balanced, and efficient solution for portfolio optimization, making it highly relevant for investors in volatile emerging markets and advancing research on hybrid metaheuristics in financial optimization.
GWO-Enhanced Hybrid Deep Learning with SHAP for Explainable TLKM.JK Stock Forecasting Bukhori, Hilmi Aziz; Bukhori, Saiful; Anam, Syaiful; Yusuf, Feby Indriana; Sari, Meylita
Jurnal Teknik Informatika (Jutif) Vol. 6 No. 4 (2025): JUTIF Volume 6, Number 4, Agustus 2025
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2025.6.4.5205

Abstract

This study presents an innovative Grey Wolf Optimization (GWO)-enhanced hybrid deep learning model integrating Convolutional Neural Networks (CNN), Bidirectional Long Short-Term Memory (BiLSTM), and Transformer, combined with SHAP for interpretable stock price forecasting of TLKM.JK from July 29, 2024, to July 29, 2025. Addressing non-linear market dynamics, the model evaluates seven experimental cases, with the GWO-optimized configuration (Case 2) achieving superior performance, with a Root Mean Squared Error (RMSE) of 75.23, Mean Absolute Error (MAE) of 58.14, and Directional Accuracy (DA) of 76.2%, surpassing the baseline by 17.4% in RMSE and 8.1% in DA. Notably, Case 2 excels during the April 2025 surge (11.8% increase, MAE 53, DA 82%) and the high-volume day of May 28, 2025 (531,309,500 shares, MAE 48), leveraging Volume (SHAP 0.45) and RSI (0.28) as key predictors. With a 4-hour convergence time on an NVIDIA RTX 3060 GPU, the model ensures computational efficiency and interpretability, making it a robust tool for traders. Despite limitations in single-stock focus and GPU dependency, this framework advances AI-driven financial forecasting by offering transparent, high-accuracy predictions, paving the way for multi-stock applications and real-time SHAP updates.
Improving Lateral-Movement Intrusion Detection in Virtualized Networks using SHAP Feature Selection, SMOTE, and a Voting Ensemble Classifier Maulana, Avin; Anam, Syaiful; Aziz Bukhori, Hilmi
Jurnal Teknik Informatika (Jutif) Vol. 6 No. 4 (2025): JUTIF Volume 6, Number 4, Agustus 2025
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2025.6.4.5233

Abstract

Modern virtualized networks, such as those using VXLAN (Virtual eXtensible LAN), generate heavy east–west traffic, which can conceal the lateral movement of attackers. Detecting such infiltration attacks is challenging due to overlay encapsulation (e.g., VXLAN) and flat subnet architectures create blind spots for traditional IDS.  This study aims to evaluate a robust methodology for addressing class imbalance in intrusion detection by integrating SHAP-driven feature selection with SMOTE in a voting ensemble. We conducted an ablation study on the CICIDS2017 Thursday-WorkingHours-Afternoon-Infiltration subset, which is highly imbalanced (36 infiltration flows vs. 288,566 benign flows), varying SHAP feature sets (Top-5 vs. Top-30), classification thresholds , and SMOTE (Synthetic Minority Over-sampling Technique) balancing. The ensemble combined XGBoost, Random Forest, and Logistic Regression, and was evaluated with ROC-AUC, precision, recall, and F1-score. Results indicate that using more SHAP‑important features improves ROC‑AUC and recall, while SMOTE substantially enhances minority‑class detection. The best configuration is Top‑30 SHAP features with SMOTE at , achieved ROC‑AUC = 0.976 and F1‑score = 0.78, whereas using fewer features or omitting SMOTE significantly reduced recall and F1‑score. This synergy of interpretable feature selection and synthetic oversampling establishes a practical methodology for intrusion detection in highly imbalanced, modern virtualized environments. The novelty lies in demonstrating that SHAP + SMOTE integration yields both transparency and resilience, directly addressing encapsulation challenges in detecting stealthy lateral movement.
IMPROVING SUPPORT VECTOR MACHINE PERFORMANCE WITH BINARY GAUSSIAN IMPROVED WHALE OPTIMIZATION ALGORITHM: A CASE STUDY ON DIABETES DATA Fajri, Haidar Ahmad; Ardiyansa, Safrizal Ardana; Anam, Syaiful; Maharani, Natasha Clarrisa; Julianto, Eric
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 19 No 4 (2025): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol19iss4pp2531-2542

Abstract

Diabetes mellitus is a chronic condition with high blood sugar that can cause severe organ damage, affecting all ages globally. Early diagnosis is crucial for improving patients' quality of life, and machine learning offers a promising approach. The Support Vector Machine (SVM) is effective for classification, but feature selection is essential to enhance the relevance of features. The Whale Optimization Algorithm (WOA) is an optimal method for global feature selection, but it has a drawback-premature convergence, which can lead to suboptimal results. This issue should be addressed by modifying mutation operations, convergence factors, and population initialization, resulting in Binary Gaussian IWOA (BGIWOA). This research focuses on feature selection using BGIWOA, comparing it with Variance Inflation Factor (VIF) using SVM. The result show that BGIWOA is better than VIF and the best configuration BGIWOA’s parameter is with linear kernel. This configuration produces the best accuracy of 95.00%. BGIWOA-SVM demonstrates better accuracy with stable consistency compared to VIF-SVM. The best SVM model achieves average accuracy of 95.62% for training data and 95.58% for validation data, with an accuracy of 93.85% for the test data. This model also yields an average precision of 94.00%, a recall of 91.00%, and an -score of 92.00%. The model was also better than SVM without optimization, which only achieved a training accuracy of 84.25% and a testing accuracy of 81.30%. This model can assist in diagnosing diabetes with accurate and consistent predictions for new data. The results are specific to the diabetes dataset used in this research, so further testing on other binary datasets is necessary to confirm the model's effectiveness and generalizability across different domains and types of data.
Strategies of Islamic Religious Education in Shaping the Religious Character of Students at Pondok Pesantren Ruqoba Al-Atsary Anam, Syaiful; Sofia Mendez
International Journal of Post Axial: Futuristic Teaching and Learning Vol. 3 No. 4 December 2025: International Journal of Post-Axial
Publisher : Yayasan Azhar Amanaa Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59944/postaxial.v3i4.520

Abstract

Islamic religious education in pesantren plays a crucial role in shaping the religious character of students. This study aims to analyze the strategies of Islamic religious education implemented at Pondok Pesantren Ruqoba Al-Atsary in fostering students’ religious character. The research employed a descriptive qualitative method with data collected through observation, interviews, and documentation. The findings reveal that the applied strategies include classical Islamic text (kitab kuning) learning, reinforcement of Qur’an memorization (tahfidzul Qur’an), habituation of daily worship, role modeling by kyai and teachers, as well as disciplinary supervision. These strategies effectively nurture religious values such as faith, obedience in worship, noble character, and social responsibility among students. Furthermore, the study highlights the relevance of these strategies in addressing contemporary challenges posed by globalization and digital culture, which often undermine the moral foundations of youth. The results also contribute to the theoretical discourse on Islamic education by emphasizing the integration of knowledge, practice, and values. Practically, they provide a model for pesantren and other Islamic educational institutions to strengthen religious character formation. Thus, Islamic religious education strategies at Pondok Pesantren Ruqoba Al-Atsary serve not only to preserve tradition but also to respond adaptively to modern challenges in building a pious and responsible Muslim generation.
Analisis Pemberdayaan Kelompok Tani Sejati Bersatu Desa Sejati dalam Perspektif Ekonomi Islam Anam, Syaiful; Nurdiana, Titin; Ani, Ani; Aziz, Abd.
IQTISODINA Vol. 8 No. 1 (2025): Juni
Publisher : LPPM IAI Nazhatut Thullab

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

This research aims to understand the empowerment of farmer groups in Sejati Village, Camplong District, Sampang Regency from the perspective of Islamic economics. This study is a qualitative descriptive analysis. The research was conducted in Bunut hamlet, Sejati Village, Camplong District, Sampang Regency. The subjects of this study are the Sejati Bersatu farmer group in Sejati Village. The informants for this research include Mr. Muhammad as the head of the Sejati Bersatu farmer group, farmers, and the community of Bunut Hamlet. Data collection was done using methods of observation, interviews, and documentation. Tancehe results of the study indicate that the management of tobacco and chili in Sejati Village, Camplong District, Sampang Regency is in accordance with the perspective of Islamic economics In accordance with the perspective of Islamic economics which includes the principle of monotheism, the principle of maslahah, the principle of mutual assistance, and the principle of working and productivity.
Norms without Power? Evaluating ASEAN Outlook on the Indo-Pacific’s Role in Shaping the Indo-Pacific Anam, Syaiful; Asyidiqi, Hasbi; Rizki, Kurnia Zulhandayani; Munir, Ahmad Mubarak
Indonesian Journal of Global Discourse Vol. 7 No. 2 (2025): July-December 2025
Publisher : The Department of International Relations Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/ijgd.v7i2.172

Abstract

ABSTRAK Tulisan ini mengkaji secara kritis ASEAN Outlook on the Indo-Pacific (AOIP) sebagai kerangka normatif yang merumuskan visi ASEAN terhadap tatanan kawasan yang inklusif, berbasis aturan, dan kooperatif di tengah memanasnya rivalitas kekuatan besar. Dengan menggunakan teori konstruktivisme dan model norm life cycle yang dikembangkan oleh Finnemore dan Sikkink, studi ini menilai peran AOIP sebagai bentuk norm entrepreneurship serta stagnasinya dalam fase awal kemunculan norma. Melalui analisis konten dan wacana terhadap dokumen AOIP, deklarasi KTT, dan respons negara anggota, makalah ini menunjukkan bahwa berbagai keterbatasan struktural ASEAN, seperti pengambilan keputusan berbasis konsensus, kelemahan institusional, dan perbedaan politik internal, menghambat operasionalisasi prinsip-prinsip AOIP. Meskipun mendapatkan dukungan retoris dari ASEAN dan mitra eksternal, AOIP tidak memiliki mekanisme penegakan yang efektif, landasan institusional yang kuat, maupun kemauan politik kolektif, sehingga menjadikannya sebagai “norma tanpa kekuatan.” Tulisan ini berargumen bahwa agar AOIP dapat berkembang menjadi kerangka kerja yang lebih berdampak, ASEAN perlu mengadopsi pendekatan institusionalisasi secara bertahap, memberdayakan norm entrepreneurs, dan membangun kemitraan strategis dengan aktor eksternal yang sejalan. Pada akhirnya, riset ini menyoroti janji sekaligus keterbatasan dari agensi normatif dalam tata kelola kawasan, serta menekankan tantangan ASEAN dalam menavigasi antara wacana aspiratif dan realitas geopolitik. Kata kunci: ASEAN, Indo-Pasifik, AOIP, konstruktivisme, norm entrepreneurship, tatanan kawasan, norm life cycle, institusionalisasi, kekuatan normatif.
Peningkatan Kapasitas Disabilitas Gunakan Polimer Dalam Penangkaran Jahe Merah Berbasis Inklusi Ratri, Dian Kusumaning; Safitri, Anisa Dewi; Rosid, Muchamad; Puspito, Bayu; Anam, Syaiful; Widyantoro, Didik
Prosiding University Research Colloquium Proceeding of The 10th University Research Colloquium 2019: Bidang Pengabdian Masyarakat
Publisher : Konsorsium Lembaga Penelitian dan Pengabdian kepada Masyarakat Perguruan Tinggi Muhammadiyah 'Aisyiyah (PTMA) Koordinator Wilayah Jawa Tengah - DIY

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Penyandang disabilitas menjadi kelompok yang rentan terjeratkemiskinan dan rawan mengalami permasalahan ekonomi dan sosiallainnya. Salah satu bentuk pendampingan yang dapat dilakukanuntuk penyandang disabilitas adalah peningkatan kapasitas (pentas)dalam berwirausaha mandiri melalui penangkaran jahe merahdengan media pot limbah merang (polimer). Kegiatan pengabdianmasyarakat ini dilaksanakan di kelompok disabilitas kelurahanCangkrep Lor kecamatan Purworejo kabupaten Purworejo.Tujuan program ini adalah 1) kelompok disabilitas memperolehpengetahuan baru tentang peluang usaha penangkaran jahe merahdengan menggunakan pot limbah merang; (2) kelompok disabilitasdapat mengetahui pemanfaatan limbah merang sebagai penggantipolibag; (3) kelompok disabilitas mempunyai keterampilan usahapenangkaran jahe merah dengan menggunakan pot limbah merang.Metode yang digunakan yaitu (1) perencanaan; (2) sosialisasi; (3)pelatihan; (4) evaluasi dan pendampingan.Hasil yang dicapai antara lain (1) penandatanganan kerja samadengan mitra tentang keberlanjutan program; (2) pelaksanaansosialisasi program; (3) kegiatan pelatihan proses pembuatan rumahpenangkaran jahe; pembuatan pot limbah merang (polimer);penangkaran jahe dan perawatan; (4) pendampingan dilakukanuntuk mengembangkan keterampilan anggota kelompok disabilitasagar dapat berwirausaha secara mandiri; (5) pembuatan modulpenangkaran jahe merah dan pembuatan polimer.
Hibridisasi Algoritma Genetika Dengan Variable Neighborhood Search (VNS) Pada Optimasi Biaya Distribusi Rahmi, Asyrofa; Mahmudy, Wayan Firdaus; Anam, Syaiful
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 4 No 2: Juni 2017
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (987.611 KB) | DOI: 10.25126/jtiik.201742287

Abstract

AbstrakProses distribusi dianggap sangat penting bagi perusahaan karena menjadi salah satu faktor yang mempengaruhi perolehan keuntungan. Besarnya biaya yang dikeluarkan serta kompleksnya permasalahan dalam proses distribusi menjadikan permasalahan distribusi sebagai topik yang perlu diteliti lebih mendalam lagi. Karena algoritma genetika (AG) sudah terbukti mampu memberikan solusi terbaik pada berbagai macam permasalahan optimasi dan kombinatorial, maka algoritma ini digunakan untuk menyelesaikan permasalahan distribusi pada penelitian ini. Namun, penerapan GA klasik memiliki kekurangan yaitu belum mencapai titik optimum global sehingga perlu dihibridisasi menggunakan algoritma variable neighborhood search (VNS). Algoritma ini dipilih karena selain mencari solusi secara global, algoritma ini juga mencari solusi secara lokal sehingga mampu menutupi kekurangan dari GA. Dengan menggunakan hibridisasi GA dengan VNS maka biaya yang diperoleh adalah 32392960 yang dibuktikan dengan penghematan biaya sebesar 323190 jika dibandingkan dengan GA klasik yaitu 32716150. Namun, dilihat dari waktu komputasi, GA-VNS membutuhkan waktu yang relatif sama dengan GA klasik yaitu 279332 ms (milisecond) dan 265091 ms.Kata kunci: distribusi, algoritma genetika, variable neighborhood searchAbstractThe distribution process is considered importantly for the company as one of the factors that affects profitability. The costs incurred as well as the complexity of the distribution problems makes the distribution problems as a topic that need to be examined more deeply. Since the wide range of combinatorial and optimization problems have been ever solved by using genetic algorithm (GA) well then it is used to resolve the distribution problems in this study. However, the implementation of classical GA has the disadvantage that has not yet reached the global optimum so that needs to be hybridized by using variable neighborhood search (VNS) algorithm. The VNS algorithm has been chosen because its ability either to search the global solutions or local solutions. The local search of VNS algorithm is able to cover the shortage of the GA. By using hibridization of GA with VNS, the cost accrued is 32392960 as evidenced by cost savings of 323190 in comparison with the classical GA is 32716150. However, the computational time of GA-VNS is equal to its classical GA relatively.Keywords: distribution, genetic algorithm, variable neighborhood search
Co-Authors A.Mirza Fauzan Gazali, A.Mirza Fauzan Abd. Aziz Abdul Bari Abdul Rouf Alghofari Achmad Noor Fatirul Achmad Taufik Adella Novita Aeri Rachmad Agus Suryanto Ahmad Afif Supianto Ahmad Mubarak Munir Aji, Kurniawan Akhmad Khumaidi Akhodiyah, Sulistina Alfian Hidayat Alifiobono, Adeva Amar, Siti Salama Anam, Afdolul Andi Kurniawan Andreas Andriani , Fitri ani ani Antariksa Sudikno Ardiyansa, Safrizal Ardana Aris Munandar Asyidiqi, Hasbi Asyrofa Rahmi, Asyrofa Ayu Dwi Lestari, Cynthia Ayudaning D , Pamungkas Aziz Bukhori, Hilmi Baehaqi Bukhori, Hilmi Aziz Bustamin, Syamsumar Choa, Yeshua Austin Harvey Deny Tisna Amijaya, Fidia Devita Sari, Nindy Dian Eka Ratnawati Dian Sisinggih Dian Sisingih, Dian Dwi Mifta Mahanani, Dwi Mifta Edi Satriyanto Fahrul Riza Fajri, Haidar Ahmad Fauzi, Rahman Ali Feby Indriana Yusuf Feny Rita Fiantika Fery Widhiatmoko Fisnia Pratami Fitriah, Zuraidah Guci, Abdi Negara Gustiningsih Hapsani, Anggi Habibi, Nur Syakherul Hadi Wijoyo, Satrio Hady Rasikhun Hamdani, Ibnu Mansyur Hamiduddin, Hamiduddin Hanayanti, Citra Siwi Handayani, Nilam Hasbullah Hasbullah Hdayat, Alfian Helen Yuliana Angmalisang Husni , Valencia Ikhwanudin, Tedy Ilyas, Muhaimin Imam Nurhadi Purwanto Indah Yanti Irma Noervadila Isnani Darti Judijanto, Loso Julianto, Eric 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 Mala Mardialina Mar'atun, Chairanil Marjono Marjono Marsum Marsum Maulana, Avin Maulana, M. Idam Maulana, Zacki Ibnu Miftahus Surur, Miftahus Mila Kurniawaty Muhammad Rivai Muharini Kusumawinahyu, Wuryansari Muhtashor, Imam 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 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 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 Wuryasari Muharini Kusumawinahyu Yuli Kartika Dewi Yunanto, Fredy Zabadi, Fairus Zulkarnain Zulkarnain