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Kusrini

Universitas Amikom Yogyakarta

Author-ID : 302666

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EMOGRAM-CNN: A Gram-Correlation Enhanced Multi-Kernel Convolutional Network for Text Emotion Recognition Marselina Endah Hiswati; Ema Utami; Kusrini Kusrini; Arief Setyanto
Journal of Innovation Information Technology and Application (JINITA) Vol 8 No 1 (2026): JINITA, June 2026
Publisher : Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/jinita.v8i1.3043

Deep neural architectures have demonstrated substantial capability for handling temporal and sequential data; however, most recurrent-based models, such as LSTM, BiLSTM, GRU, and BiGRU, remain computationally expensive and prone to overfitting. This study proposes and evaluates the EMOGRAM-CNN model, a convolutional neural architecture enhanced with Gram-matrix feature correlation, to improve feature representation in temporal classification tasks. Model performance was compared with conventional CNNs and recurrent architectures on a balanced six-class dataset comprising 17,967 samples. Experimental results show that EMOGRAM-CNN achieved the highest classification accuracy of 94.48%, outperforming CNN (94.00%), GRU (92.00%), BiGRU (91.00%), BiLSTM (91.00%), and LSTM (90.00%). The model converged faster, with smoother loss behavior and lower validation error, indicating superior stability and generalization. The Gram-based correlation layer effectively preserved second-order dependencies across feature maps, enabling the network to capture both local and global temporal relationships without recurrent connections. These findings confirm that EMOGRAM-CNN offers a robust, computationally efficient alternative to recurrent deep networks for sequence classification.

Evaluating Cross-Language Structural Generalization of the Unified Abstract Syntax Tree Mardi Utomo; Ema Utami; Kusrini; Arief Setyanto
Journal of Innovation Information Technology and Application (JINITA) Vol 8 No 1 (2026): JINITA, June 2026
Publisher : Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/jinita.v8i1.3191

Cross-language code analysis requires syntax-aware representations that can reduce language-specific syntactic variation while preserving comparable program structure. Although unified Abstract Syntax Tree (AST) representations have been proposed, empirical evidence on their representation-level structural behavior across datasets and programming languages remains limited. This paper evaluates the structural generalization of a Unified AST representation as a schema-level abstraction, not as a parser-free or full semantic equivalence mechanism. The Unified AST schema is constructed from the CodeXGLUE code-to-text dataset covering Python, PHP, Ruby, Java, JavaScript, and Go. Its generalization is then examined on function-level aligned benchmarks from CodeXGLUE code-to-code translation (Java-C#) and multilingual HumanEval (Java, JavaScript, Go, Python, C++, and Rust). Tree Edit Distance (TED) similarity is used as the primary structural metric, while cosine similarity, BLEU, compression ratio, and identifier precision-recall are treated as auxiliary indicators of lexical similarity, reconstruction fidelity, compactness, and identifier retention. The results show an average TED similarity of 0.77 on CodeXGLUE code-to-code translation and 0.60 on HumanEval. These findings indicate that the Unified AST can preserve cross-language structural patterns under aligned benchmark assumptions, although it does not prove behavioral equivalence and remains dependent on language-specific parsing during AST extraction

ANALISIS KOMPARATIF PENGGUNAAN AUGMENTASI DATA TERHADAP PERFORMA YOLO DALAM KLASIFIKASI INDIVIDU BERDASARKAN KEBERADAAN SENJATA: A COMPARATIVE ANALYSIS OF DATA AUGMENTATION TECHNIQUES ON YOLO PERFORMANCE IN CLASSIFYING INDIVIDUALS BASED ON WEAPON PRESENCE Nona Adinda Ariana Ariana; Kusrini
Rabit : Jurnal Teknologi dan Sistem Informasi Univrab Vol 11 No 2 (2026): Juli
Publisher : LPPM Universitas Abdurrab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36341/rabit.v11i2.8059

The increasing demand for security systems has encouraged the use of image processing technology to assist in identifying potential criminal activities. One important indicator in security surveillance is the presence of individuals carrying weapons. Therefore, this study aims to implement the YOLO11 deep learning algorithm to detect and classify individuals based on the presence of weapons in images. The dataset used consists of two classes, namely Person and Weapon, and four training scenarios were evaluated: the original dataset, the MixUp-augmented dataset, the CutMix-augmented dataset, and the combined MixUp-CutMix dataset. Model performance was evaluated using precision, recall, mAP50, and mAP50-95 metrics. The results show that the model trained on the original dataset achieved the highest recall of 0.84 and mAP50 of 0.92, while the model trained on the combined MixUp-CutMix dataset achieved the highest precision of 0.95 and mAP50-95 of 0.62. Among the augmentation methods applied, the combination of MixUp and CutMix produced the best performance, whereas MixUp yielded relatively lower performance than the other methods. The findings indicate that data augmentation can increase the diversity of training data; however, it does not always lead to better performance than the original dataset. Overall, the results demonstrate that YOLO11 has strong potential for application in computer vision-based surveillance systems to support the automatic detection of individuals carrying weapons.

Optimizing Acoustic Fingerprinting for Synchronized Audio Binary Matching Andi Bahtiar Semma; Kusrini Kusrini; Arief Setyanto; Bruno da Silva; An Braeken
Advance Sustainable Science Engineering and Technology Vol. 8 No. 3 (2026): May - July
Publisher : Science and Technology Research Centre Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/asset.v8i3.2744

As interconnected devices proliferate, secure and efficient pairing methods are critical. Environmental acoustic signals offer a promising solution, but their effectiveness depends on robust audio features that perform well across varying conditions. This study investigates optimal audio features for fingerprinting, focusing on synchronized audio in time-frequency domains. Six diverse datasets were collected across controlled environments to simulate real-world scenarios. Thirteen audio features were extracted and analyzed for robustness across distances, devices, scenes, and sample lengths. Cosine similarity assessed consistency, while the Youden index determined thresholds. The Mel Spectrogram, particularly with 5-second samples, achieved an AUC of 0.8758 and a J-statistic of 0.7278. Augmenting it with Tonnetz and spectral bandwidth yielded the highest performance (AUC: 0.9346, J-statistic: 0.7955, Accuracy: 0.8320, recall: 0.9648), demonstrating the potential of combining robust base features with complementary acoustic characteristics for reliable device pairing.

Pola Prestasi Akademik Mahasiswa Informatika Menggunakan K-Means Clustering Studi Kasus Universitas Hamzanwadi NTB Amanah Azzahra; Kusrini
Infotek: Jurnal Informatika dan Teknologi Vol. 9 No. 2 (2026): Infotek : Jurnal Informatika dan Teknologi
Publisher : Fakultas Teknik Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/jit.v9i2.33944

Analyzing students’ academic achievement patterns is important to support data-driven academic decision-making. This study aims to identify academic achievement patterns of Informatics students at Universitas Hamzanwadi using an unsupervised learning approach based on the K-Means algorithm. The main contribution of this research lies in conducting scenario-based experiments using several combinations of academic attributes and applying multi-metric evaluation to determine the most optimal clustering configuration for seventh-semester student data. The dataset includes the Semester Grade Point Average (IPS), Cumulative Grade Point Average (IPK), and the total accumulated credit units (SKS). After data cleaning and preprocessing, 382 student records were obtained for analysis. Data normalization was performed using Min–Max Scaling. The optimal number of clusters was determined using the Elbow method, resulting in three clusters. Cluster quality evaluation produced a Silhouette Score of 0.71, a Davies–Bouldin Index of 0.54, and a Calinski–Harabasz Index of 808.64, indicating good clustering quality. The results revealed three groups of students with high, medium, and low academic achievement characteristics. These findings confirm that the K-Means algorithm is effective in clustering student academic achievement patterns and can be used as a basis for academic evaluation and student development strategies. However, this study is limited to seventh-semester data and can be extended to other datasets or across study programs

Cyber intrusion detection model using deep learning based on augmented image-based feature construction Mauludil Asri M. Cane; Kusrini Kusrini; Melwin Syafrizal
Jurnal Pendidikan Informatika dan Sains Vol. 15 No. 1 (2026): Jurnal Pendidikan Informatika dan Sains
Publisher : Universitas PGRI Pontianak

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31571/saintek.v15i1.10499

Network intrusion detection remains a critical challenge in cybersecurity, particularly due to the increasing volume and complexity of network traffic. To address this issue, this study develops a deep learning framework that transforms tabular NSL-KDD data into image representations using the Lightweight Multi-feature Image Generator for Tabular Data (LM-IGTD). In addition, Homogeneous Noise Generation (HoNG) is applied to enrich feature diversity prior to processing. The transformed data are then classified using a Convolutional Neural Network (CNN) under a binary classification scheme to distinguish between normal and attack activities. Experimental results on the KDDTest+ dataset show that the proposed approach achieves an accuracy of 81.81%, an F1-score of 81.51%, and a ROC-AUC of 95.11%. The results indicate that LM-IGTD significantly contributes to improving the model’s ability to distinguish between classes, particularly in terms of ROC-AUC, while HoNG enhances classification performance in terms of accuracy and F1-score. However, a trade-off is observed between improved classification accuracy and the model’s probability ranking capability. Overall, these findings highlight that LM-IGTD provides an effective feature representation strategy, while HoNG offers a complementary contribution depending on the evaluation metric prioritized.

Performance comparison of Naive Bayes, PSO-Naive Bayes, and PCA-PSO-Naive Bayes for the classification of elementary school students' interests Endah Herminarimawati; Kusrini Kusrini
Jurnal Pendidikan Informatika dan Sains Vol. 15 No. 1 (2026): Jurnal Pendidikan Informatika dan Sains
Publisher : Universitas PGRI Pontianak

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31571/saintek.v15i1.10914

Identifying students’ interests at an early stage is a crucial process in education because it enables schools to direct students’ potential in a structured and objective manner. However, report card data typically contain many attributes, some of which are redundant or irrelevant, and this condition can degrade the performance of classification algorithms such as Naive Bayes. This study compared the classification performance of three models, namely pure Naive Bayes, a hybrid PSO-Naive Bayes model, and a hybrid PCA-PSO-Naive Bayes model, in classifying the interests of elementary school students into four categories: Academic, Arts, Sports, and ICT. The dataset combined cognitive data in the form of report card scores in nine subjects with affective data obtained from an interest questionnaire. Particle Swarm Optimization (PSO) was applied as a feature selection technique, while Principal Component Analysis (PCA) was applied as a dimensionality reduction technique before feature optimization. Model performance was evaluated using stratified 5-fold cross validation. The results showed that the PCA-PSO-Naive Bayes model achieved the highest mean accuracy of 98.92%, compared with 97.84% for pure Naive Bayes and 97.30% for PSO-Naive Bayes. The hybrid PCA-PSO-Naive Bayes model also produced the most stable accuracy across folds, with a range of 97.3% to 100%. These findings indicate that combining PCA-based dimensionality reduction with PSO-based component selection improves both the accuracy and the stability of Naive Bayes in classifying student interests based on academic and questionnaire data.

A comparative study of mango fruit pest and disease recognition Kusrini Kusrini; Suputa Suputa; Arief Setyanto; I Made Artha Agastya; Herlambang Priantoro; Sofyan Pariyasto
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 20, No 6: December 2022
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v20i6.21783

Mango is a popular fruit for local consumption and export commodity. Currently, Indonesian mango export at 37.8 M accounted for 0.115% of world consumption. Pest and disease are the common enemies of mango that degrade the quality of mango yield. Specialized treatment in export destinations such as gamma-ray in Australia, or hot water treatment in Korea, demands pest-free and high-quality products. Artificial intelligence helps to improve mango pest and disease control. This paper compares the deep learning model on mango fruit pests and disease recognition. This research compares Visual Geometry Group 16 (VGG16), residual neural network 50 (ResNet50), InceptionResNet-V2, Inception-V3, and DenseNet architectures to identify pests and diseases on mango fruit. We implement transfer learning, adopt all pre-trained weight parameters from all those architectures, and replace the final layer to adjust the output. All the architectures are re-train and validated using our dataset. The tropical mango dataset is collected and labeled by a subject matter expert. The VGG16 model achieves the top validation and testing accuracy at 89% and 90%, respectively. VGG16 is the shallowest model, with 16 layers; therefore, the model was the smallest size. The testing time is superior to the rest of the experiment at 2 seconds for 130 testing images.

PERBANDINGAN KINERJA ALGORITMA NAIVE BAYES DAN C4.5 DALAM PREDIKSI PENYAKIT JANTUNG Sri Wulandari; Kusrini Kusrini; Hanafi Hanafi
TEKNIMEDIA: Teknologi Informasi dan Multimedia Vol. 6 No. 2 (2025): Desember 2025
Publisher : Badan Penelitian dan Pengabdian Masyarakat (BP2M) STMIK Syaikh Zainuddin NW Anjani

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46764/teknimedia.v6i2.284

Information Technology is a data processing technology and is a variety of ways to produce high-quality information accurately and quickly, relevant to the needs of individuals and businesses. Strategic information about decision making. The development of information technology is one of the most important factors for the progress of time. There are several fields that are important for technological progress and affect the progress of the country, such as the education sector, the economic sector, the health sector, the government sector, and the socio-cultural sector. Basically, technology is developed to promote human work. Currently, technology is a great need for humanity. In fact, technology is used in all aspects of human life. Predicting heart disease accurately is essential to treat heart patients efficiently before a heart attack occurs. This goal can be achieved by using an optimal machine learning model with complete heart disease health data. Therefore, a comparison of the performance of the Naive Bayes algorithm and the C4.5 algorithm in predicting heart disease requires calculation so that the results obtained are more accurate. Before doing the calculation, it is necessary to check the feasibility of the data to be used, then the division of training and testing data. In the study, there were several scenarios for dividing training and testing data using a confusion matrix. This study resulted in a performance comparison of the Naïve Bayes and C4.5 algorithms in predicting heart disease, 6 experimental scenarios were carried out, each algorithm had 3 experiments with varying amounts of training data and testing data. The C4.5 algorithm performed 3 experimental scenarios, in the first experiment the Naïve Bayes algorithm, the first experiment 70:30 produced an accuracy of 83%. In the second experiment 80:20 produced an accuracy of 83%. In the third experiment 90:10 produced an accuracy of 85%. Then the C4.5 algorithm performed 3 experimental scenarios, in the first experiment 70:30 produced an accuracy of 98%. In the second experiment 80:20 produced an accuracy of 100% In the third experiment 90:10 produced an accuracy of 100%.

Klasifikasi Data Pariwisata Berkelanjutan Menggunakan Decision Tree dengan Equal Width dan Logaritma Binning : Decision Tree Classification Using Equal Width and Logarithmic Binning for Sustainable Tourism Data Fahri Alviansyah; Mukti Adi Azhari; Attar Raihan Nazhif; Suharto Suharto; Denny Saryanto; Kusrini Kusrini
MALCOM: Indonesian Journal of Machine Learning and Computer Science Vol. 6 No. 1 (2026): MALCOM January 2026
Publisher : Institut Riset dan Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57152/malcom.v6i1.2520

Pengelolaan data rekomendasi pariwisata memerlukan pemodelan prediktif yang akurat untuk mengklasifikasikan target rekomendasi berdasarkan perilaku wisatawan. Namun, variabel numerik seperti Rekomendasi Score seringkali memiliki distribusi data yang tidak merata (skewed), yang dapat memengaruhi performa algoritma pembelajaran mesin seperti Decision Tree. Penelitian ini bertujuan untuk membandingkan efektivitas dua teknik preprocessing dengan diskritisasi, yaitu Equal Width Binning (EWB) dan Logarithmic Binning (LB), dalam meningkatkan kinerja model klasifikasi. Metodologi penelitian ini mencakup beberapa tahapan preprocessing data, antara lain handling missing value, serta ekstraksi fitur temporal dari data tanggal perjalanan. Data kemudian diproses menggunakan dua skenario binning yang berbeda sebelum dilatih menggunakan algoritma Decision Tree. Hasil penelitian dievaluasi menggunakan metrik Akurasi, Presisi, Recall, dan F1-Score. Hasil perbandingan menunjukkan bahwa Equal Width Binning nilai akurasi sebesar 82 %, dan Logarithmic Binning memberikan nilai akurasi sebesar 90%. Diskritisasi melalui logaritma bining mampu mengurangi kedalaman pohon (tree depth) dan mencegah overfitting, sehingga menghasilkan model yang lebih tangguh dalam memprediksi target rekomendasi pariwisata.

Co-Authors - Saifulloh A.A. Ketut Agung Cahyawan W AA Sudharmawan, AA Aan Indarto ABADI Abda Abda Abdi Firdaus Abdillah, Yahya Auliya Abdul Haris Abdul Malik Zuhdi Abdul Ra'uf Alfansani Abdul Rokhim Abdullah Sukri, M Iqbal Abdullah, Mochamad Fadillah Achmad Agus Athok Miftachuddin Achmad Wazirul Hidayat Achmad Yusron Arif Adadilaga Arya Priwanegara Ade Pujianto, Ade Adhien Kenya Estetikha Adiatma, Biva Candra Lutfi Aditya Hastami Ruger Aflahah Apriliyani Afryansih, Nila Agam Saka Jati Agastya , I Made Artha Agastya I Made Artha Agastya, I Made Artha Agatha Deolika Agatstya, I Made Artha Agianto Syam Halim agung budi Agung Budi Agung Budi Prasetio Agung Budi Prasetyo Agung Jasuma Agung Jasuma Agung Nugroho Agus Harjoko AGUS PURWANTO Agus Sriyanto AGUS SULISTIYONO Agus Susilo Nugroho Agustina Rahmawati Ahmad Almas'ud ZD Ahmad Harmain Ahmad Sanusi Mashuri Ahmad Yusuf Ahmad Zarkasih Ahsan, Muhammad Salimy Aidina Ristyawan, Aidina Aiman Ayadi Aisha Alfani Aji Santoso, Bayu Aji Susanto Anom Purnomo Ajie Kusuma Wardhana Akhmad Syarif Akhmad Syarif Akrilvalerat Deainert Wierfi Alfahmi Muhammad Arif Alfatta, Hanif Ali Asgar Zainal Abidin Alva Hendi Muhammad Amanah Azzahra Amanullah, Raynaldi Fatih Amborowati, Armadyahah Amir Bagja Amir Fatah Amir Fatah Sofyan Amrina Rosyada An Braeken Anastasia Meyliana Andayani Andayani Andhika Wisnu Widyatama Andi Bahtiar Semma Andi Bahtiar Semma Andi Muhammad Irfan Andi Sunyoto Andi Suyoto Andi Syahrul Ramdana Andika, Roy Andri Rachmatullah Andri, Agung Andria Andria Andris Faesal Andriyan Dwi Putra Andriyanto, Rifki Angga Kurniawan Anggi Muhammad Rifa'i Anggit Dwi Hartanto Anggit Dwi Hartanto Anggit Dwi Hartanto, Anggit Dwi Anggit Hartanto Anggraeni, Meita Dwi Aninda Astuti Anjar Anjani Putra Anwar Sadad Aolia Ikhwanudin Aolia Ikhwanudin Apriliyani, Aflahah Aprison Wolla Gole Ardana, Wildan Muhammad Ardana, Wildan Muhammmad Ardiansyah, Fachri Arfiani Nur Khusna Arham Rahim Ari Ari Suhartanto Ari Fitriyandhi Ari Suhartanto Ari Yuana, Kumara Arief Setyanto Arief Setyanto Arief Tri Nugroho Arief, M Rudyanto Arief, M. Rudyanto Arief, Muh. Rudyanto Arief, Muhammad Rudyanto Arief, Rudyanto Ariel Yonatan Alin Arif Budiman Arif Fajar Solikin Arif Fajar Solikin Arif Fajar Solikin Arifuddin, Danang Arik Sofan Tohir Aris Subadi Arli Aditya Parikesit Armadyah Amborowati Armadyah Amborowati Armadyah Amborowati Arnap, Adam Arnila Sandi Arridho, Muhammad Noor Arwendra Adi Putra Asnawi, Muhamad Fuat Asri, Saffinah Indah Asro Nasiri Asro Nasiri Asro Nasiri Asro Nasiri Asro Nasiri Asro Nasrini Assani, Moh. Yushi Atika Dwi Cahyani Atin Hasanah Attar Raihan Nazhif Awaludin Abid Azi, Amanda Azib Widad Zuhaily Imam Azis Wahyudi Aziz Muslim Aziz Muzani, Ma'ruf Aziz, Moh Abdul Azkar, Azkar B, Isdayani B. R., Endah Bagas Dwi Novianto Bahrun Ghozali Banu Santoso Bayu Setiaji Bentar Candra P Bernadhed, Bernadhed Bhanu Sri Nugraha Bimantyoso Hamdikatama Bisono, Hadi Hikmadyo Braeken, An Brenstein Mawene Bruno da Silva Burhanudin Dwi Prakoso Candra Adipradana Candra Rusmana Candra, Kurnia Khoirul Choerun Asnawi Christian Budi Andrianto, Christian Budi Christin Nandari Dengen Christin Nandari Dengen Christin Nandari Dengen Christin Nandari Dengen D. Diffran Nur Cahyo da Silva, Bruno Danang Eko Prayogo Danang Wahyu Widodo Darno - David Agustriawan David Budi Hartanto David Junggu Manggala Pasaribu dayat subekti Dede - Sandi Dede Husen Dedi Gunawan Dema Matias L Tobing Dengen, Christin Nandari Denny Saryanto Desty Yani Destyanto, Febrian Devina Ninosari Dhani Ariatmanto Dhani Ariatmanto DHANI ARIATMANTO Dias Ayu Budi Utami Dibyo Sudarsono Didik Irawan Dimaz Arno Prasetio Dina Maulina Dina Maulina Dina Maulina Dina Maulina Djatmiko, Widdi Doni Briyan Wahyudi Donny Yulianto Dwi Astuti DWI ISKANDAR Dwi Utami Dwi Yuli Prasetyo Dwinda Etika Profesi Dwinda Etika Profesi Dzalfa Tsalsabila Rhamadiyanti Dzulhijjah, Dwi Ahmad Eddy Nurraharjo Eddy Nurraharjo Eka Wahyu Pujiharto Eka Wahyu Sholeha Eka Yulia Sari Ekastini Ekastini Ekastini Ekastini Eko Boedijanto Eko Pramono Eko Pramono Eko Pramono Eko Pramono Eko Pramono Eko Pramono Eko Purwanto Eko Purwanto Eko Purwanto Eko Rahmad Darmawan Eldas Puspitarini, Eldas Elfandry Bayunanda Elfrida Ratnawati Elik Hari Muktafin Elik Hari Muktafin Elik Hari Muktafin Eliza Staviana Elok Noor Farida, Elok Noor Elvis Pawan Elvis Pawan Ema Utami Ema Utami Ema Utami Emha T aufiq Luthfie Emha Taufik Luthf Emha Taufiq Luthfi EmhaTaufiq Lutfi, EmhaTaufiq Endah Herminarimawati Enni Lidrawati Erfan Tongalu Eri Sasmita Susanto Erwin Apriliyanto Erwin Apriliyanto Eva Oktaviani Fahma Inti Ilmawati Fahri Alviansyah Fahrullah, Fahrullah Fajar Dwi Insani Fajar Sodik Fajar Sudana Putra Fandli Supandi Fandli Supandi Fareza Aditiyanto Nugroho Fathoni Mahardika Fatkhurohman, Ari Fatkhurrochman, Fatkhurrochman Fauji Maulana Ramlan, Fauji Maulana Fauzi, Moch Farid Fauzy, Marwan Noor Febrianti, Winda Febriyanti, Nada Rizki Fendy Nugroho Fendy Prasetyo Nugroho Fendy Prasetyo Nugroho Fernandito, Durand Ferry Wahyu Wibowo Ferry Wahyu Wibowo Ferry Wahyu Wibowo Ferry Wahyu Wibowo Ferry Wahyu Wibowo Ferry Wahyu Wibowo Ferry Wahyu Wibowo Firman Sriyono Firmanda Fasya Firza Septian Fitriani Fitriani fitriyanto, nur Fitrony, Fachri Ayudi Fiyas Mahananing Puri Friden E Neno Fryda Fatmayati Gifari, Okta Ihza Gigih Setyaji Guido Adolfus Suni Gutama, Deden Hardan Hadi Sucipto Hadryan Eddy Hafidz Sanjaya, Hafidz Halimi, Ahmad Hamada Zein Hamdikatama, Bimantyoso Hanafi Hanafi Hanafi Handoko Adji Pangestu Hanif Al Fatta Hari Agustiyo Hari Muktafin, Elik Haris, Ruby Hartono, Anggit Dwi Haryo, Wasis Hasan, Nur Fitrianingsih Hasan, Nurul Rahmawati Hasim, Hasim As'ari Hasirun Hasirun Hasnan Afif Hasni Anas Henderi Henderi . Hendriansyah Santosa Hendrik Hendrik Henri Kurniawan Henri Kurniawan Herawati, Maimi Heri Abijono Heri Abijono, Heri Heri Sismoro Herlambang Priantoro Herlinawati, Noor Hery Nurmawan Hery Siswanto Hidayat, Fajar Maula Hidayatunnisa'i Hulvi, Alfajri I Made Adi Purwantara I Made Artha Agastya I Putu Agus Ari Mahendra I Wayan Pandu Ibnu Ickwantoro Ichsan Wasiso Ichsan Wasiso Idris Idris Ikhwan Baidlowi Sumafta Ikhwanudin, Aolia Ikmah Ikmah Ilham Aziz Rosadi Ilkham, Sundari Ilkham, Sundari Ilmawati, Fahma Inti Imam Listiono Indra Listiawan Iqbal Irfan Purwanto Irma Darmayanti Irwan Oyong Jangkung Tri Nugroho Jazi Eko Istiyanto Jeki Kuswanto Jeki Kuswanto Jemi Yohanis Babys Jhoanne Fredricka Jimmy H Moedjahedy Joang Ipmawati JOKO PRAYITNO José Ramón Martínez Salio Julia Kurniasih Jumaris Jumaris, Jumaris Junaidi Junaidi Junaidi Sabtu Juwari Juwari Juwariyah, Siti Kaharuddin Kanafi Kanafi Kasman, Haris Saktiawan Kelik Sussolaikah Kemal Pasha Khoironi, Khoironi Khoirul Islam Khoirun Nisa Kholil, Moenawar Khomsatun Khomsatun Khusnawi Khusnawi Kristina Vaher Kumara Ari Yuana Kumara Ari Yuana Kurni, Samuel Everth Andrias Kurniadi, Harso Kurniasari, Iin Kusnawi , Kusnawi Kusnawi Kusnawi Kusrini, Mashudi Kusuma Chandra Kirana Laka, Beatus Mendelson Lasimin Lewu, Retzi Y. Liana Trihardianingsih Lili Kartikawati Linda, Kumara Dewi Lisda Lisda Listyanto, Ahmad Wildan López, Alba Puelles Lukman Bachtiar Lutfan Lazuardi M rudyanto Arief M Rudyanto Arief M Vaizul Rahman M. Afriansyah M. BAHRIL ILMI M. Dedi Iskandar M. Idris Purwanto M. Ilham Arief M. Irwan Ukkas Irwan Ukkas Ukkas M. Nurul Wathani M. Rudiyanto Arief M. RUDYANTO ARIEF M. Rudyanto Arief M. Rudyanto Arief M. Rudyanto Arief M. Suyanto M. Suyanto, M. M. Syukri Mustafa M. Zainal Arifin M.Andi Rohmat Madhika, Yudha Randa Mahendra, Awanda Putra MAHMUDI Mahmudi Mahmudi Majid Rahardi Mangun, Syamsul Syahab Mansur Mansur Maradona, Maradona Mardi Utomo Mardiana Mardiana marhalim, marhalim Marissa Utami Marselina Endah Hiswati Marta Ardiyanto Martínez-Béjar, Rodrigo Marwan Noor Fauzy MASRIYAH Masruri, Nizar Haris Masud, Ibnu Mat Sudir maulana, fahrizal Mauludil Asri M. Cane Mawene, Brenstein Maykel Sonobe Maykel Sonobe Megantara, Muhamad Arldi MEI PARWANTO KURNIAWAN Melwin Syafrizal Metha, Halifa Sekar Miftachuddin, Achmad Agus Athok Mochamad Fadillah Abdullah Moh Er Kamim Moh Royandi Azka Moh. Badri Tamam Mohamad Firdaus, Mohamad Mohammad Diqi Mohammad Rezza Pahlevi Moningka, Nirwan Muahidin, Zumratul Muchamat Zainal Arifin Muflich, Alwie Mufti Ari Bianto Muh Saerozi Muh. Rudyanto Arief Muh. Rudyanto Arief Muhamad Fatahillah Z Muhamad Iksan, Muhamad Muhamad Kurniawan Muhamad Nanda Utama Muhamad Ryandy Ghonim Asgar Muhamad Yusuf Muhammad Agus Muljanto Muhammad Alfariz Muhammad Anwar Fauzi Muhammad Azmi Adhani Muhammad Egy Pratama Muhammad Fahmi Muhammad Fajar Apriyanto Muhammad Fajrian Noor Muhammad Febrian Fansuri Muhammad Firdaus Abdi Muhammad Firdaus Abdi Muhammad Koprawi Muhammad Mariko Muhammad Nafi’Uddin Muhammad Resa Arif Yudianto Muhammad Riandi Widiyantoro Muhammad Ricky Perdana Muhammad Riza Eko S Muhammad Rudyanto Arief Muhammad Rudyanto Arief Muhammad Rudyanto Arief Arief Muhammad Salimy Ahsan Muhammad Suyanto Muhirin Muktafin, Elik Hari Mukti Adi Azhari Mukti Ali Mulia Sulistiyono Muqorobin Muqorobin Muqorobin Muqorobin Muqorobin Muqorobin Muqorobin, Muqorobin Musa Hendri Janto Rahanra Muslihah, Isnawati Musthofa Galih Pradana Mutiara Dwi Anggraini Mutiara Dwi Anggraini Muzakir, Muhammad MZ, Reza Rafiq Nabawi, Isnan Nabila Payapo Nadea Cipta Laksmita Nafis Sururi Nanang Prasetiyantara Nasiri, Asro Neno, Friden Elefri Ngaeni, Nurus Sarifatul Ni Nyoman Utami Januhari Nibras Faiq Muhammad Nikko Listio Wicaksono NINIK TRI HARTANTI Nita Helmawati Nona Adinda Ariana Ariana Noor Abdul Haris Norhikmah Norhikmah Noto Narwanto Nova Agustina Noviyanti P Noviyanti P. Nugroho, Agung Nugroho, Hanantyo Sri Nugroho, Rakhmat Prasetyo Agung Nuk Ghurroh Setyoningrum Nuk Ghurroh Setyoningrum Nulngafan, Nulngafan Nur Hamid Sutanto Nurcahyo, Azriel Christian Nurita Evitarina Nurmalasari, Maulidya Dwi Nurwijayanti Oktafiqurahman, Andi Olajuwon, Sayyid Muh. Raziq Onde, Mitrakasih La ode Oscar Samaratungga Paiman Paiman Pamekas, Bondan Wahyu Pamoengkas, Muhamad Agoeng Pamungkas, Prima Giri Pamungkas, Sapto Paradise, Paradise Parsiyono Parsiyono Patmawati Hasan Pawit Srentiyono Perdana Putra, Muhammad Ricky Prabowo Budi Utomo Pradipta, Dody Prameswari, Sonia Anjani Pramono Pramono Pramudya Insan Prasetio, Agung Budi Prasetio, Dimaz Arno Prasetyo, Adi Prastowo, Wahit Desta Prastyo, Rahmat Pratama, Bayu Trisna Pratama, Muhammad Egy Profesi, Dwinda Etika Profesi, Dwinda Etika Pujianto, Ade Purnamasari, Resti Rachmawati Oktaria Mardiyanto Rachmawati Oktaria Mardiyanto Rahmat Saleh Sukur Rajnaparamitha Kusumastuti Rama Ashari Rama Saktriawindarta RAMADHAN, SYAIFUL Ramlan Ramlan Rantung , Tessa Rasyid, Magfirah Reflan Nuari Rendy Bagus Pratama Retantyo Wardoyo Retzi Yosia Lewu Ridlan Ahmad Riduan, Nor Ridwan Joko Purnomo Rifan Ferryawan Rifqi Hammad Rifqi Hammad Rini Wijayanti Rini, Rini Riovan Styx Roring Ripto Sudiyarno Ririn Putri Damaiyanti Risca Yunita Riska Dwi Handayani Risna Sari Rita Wati Ritham Tuntun Riyan Abdul Aziz Rizal Khadarusman Rizal Sapta Dwi Harjo Rizaldi, Rizaldi Rizkayati, Anisa Rizki Firdaus Mulya Rizki Mawan Rizky Aries Saputra Rizqi Sukma Kharisma Robi Wariyanto Abdullah Rodrigo Martínez Béjar Rohman, Arif Nur Rona Guines Purnasiwi Rooy Thaniket Rudyanto Arief S, Muhamad Rois S, Muhammad Sabri Safagi, Ardian Yuligar Sahirul Muklis Saifudin, Saifudin Saiful Bahri Saikin Saleh, Robby Febrianur Samponu, Yohakim Benedictus Samponu, Yohakim Benedictus Santosa, Hendriansyah SANTRI SANTRI Saputra, Mahmuda Saputra, Rizky Aries Saputro, Moh. Rizal Bayu Saputro, Uyock Anggoro Sari, Yayak Kartika Sari, Yunita Sartika Sarji, Sarji Selvy Megira, Selvy Semma, Andi Bahtiar Sentoso, Thedjo Sepriadi - Bumbungan Sepriadi Bumbungan Setianto, Yuni Ambar Setiawan, Moh. Arif Ma'ruf Setyanto, Arif Sewindu Putro Sigit Pambudi Simone Martin Marotta Siswo Utomo, Mardi Siti Delimasari Siti Fatonah Siti Hartinah Siti Maesaroh Siti Nurhayati Siti Rahayu Siti Rihastuti Siti Rokhmah Siti Solekhah Slamet Slamet Slamet Slamet Sobirin, Rahmat Sofyan Pariyasto Sofyan Pariyasto Solikin, Arif Fajar Sri Handayani Sri Hartati Sri Lestari Rahayu Sri Wahyuningsih Sri Wulandari Sri Wulandari Sri Yanto Qodarbaskoro Sriyati, Sriyati Sry Faslia Hamka Sudarmawan Sudarmawan Sudarmawan - Sudarmawan . Sudarmawan Sudarmawan Sudarmawan Sudarmawan Sudarmawan Sudarmawan Sudarmawan Sudarmawan Sudarmawan Sudarmawan Sudarmawan Sudarmawan Sudarmawan Sudarmawan Sudarmawan Sudarmawan Sudarmawan Sudarmawan Sudarmawan, Sudarmawan Sudarsono, Dibyo Sudarto Sudarto Sudiana Sudiana Sugi Harsono Sugihandono, Agus Suhardi Marli Suharto Suharto Suhendri Sukasna . Sukasna, Sukasna Supraba, Laksmita Dewi Supriantara Supriantara Supriatin Supriatin Supriyati Supriyati Suputa Suputa Surya Wibowo, Sapta Hary Suyono, Ayu Adelina Swardiana, I Wayan Pandu Swastikawati, Claudia Syafutra, Arif Dwi Syah, Firdiyan Syaiful Huda Syaiful Huda Syaiful Ramadhan Syamsu Hidayat Tala, WD. Syarni Tamaulina Br Sembiring Tampubolon, Jandri Tamuntuan, Virginia Taufik Aldri Kristian Teguh Arlovin Teguh Sri Pamungkas Theofanis Orphanoudakis Thiro Kabul Y, Yudhis Tika Dedy Prastyo Tito Prabowo Toifur, Tubagus Tolla, Yefta Tonny Hidayat TONNY HIDAYAT Tri Andi Tri Anggoro Tri Haryanti Tri Nugroho, Arief Tubagus Toifur Tukan, Ewaldus Ambrosius Turmuzi Tutik Maryana Tutut Dwi Prihatin Ula, M. Izul Umam Faqih Zubaedi Umdatur Rosyidah Utami Ema Uyock Anggoro Saputro Veny Cahya Hardita Vera Wati Victor Saputra Ginting Victor Saputra Ginting Vinnesa Patricia Carolina Wahyu Adie Saputro Wahyu Nugraha Wahyu Nur Alimyaningtias Wahyu Pujiharto, Eka Wahyu Sindu Prasetya Wahyu Wijaya Widiyanto Wahyudi, Alfian Cahyo Walidy Rahman Hakim Wangsa, Sabda Sastra Wariyanto Abdullah, Robi Wartono Wartono wati, Vera Wati, Vera Wauran, Alfrets Septy Wicaksono, Kurniawan Widdi Djatmiko Widiyanto, Wahyu Wijaya Widya Mulyaningtyas Widyanto, Agung Wijaya, Jodi Winarnie Winarto, Hendri Wira Dimuksa Wiwi Widayani Wiwi Widayani, Wiwi Wiwit Supriyanti Wulandari, Sri Y. P., Ryan Dwi Yanuargi, Bayu Yeyen Dwi Atma Yoga Handoko Agustin Yohanes Setyo Prabowo, Yohanes Setyo Yopy Tri Buana Yossy Ariyanto Yovita Kinanti Kumarahadi Yuana, Kumara Ari Yudha Chirstianto F Yuli Astuti Yuliana Yuliana, Yuliana Yuliani, Enie Yulita Fatma Andriani Yulius Nahak tetik Yuni Ambar S Yunita, Selviana Yusrinnatul Jinana triadin Yustian Servanda Yusuf Fadlila Rachman Yusuf Fadlila Rachman Yusuf Wahyu Setiya Putra Yuza, Adela Zaenul Amri Zakaria Zakaria Zenal Muttaqin Zeni Muhamad Noer Zuhri, Muhammad Rafli Zul Hisyam Zulkarnain, Imam Alfath Zulkarnain, Jefri Zulkipli Zulkipli Zulpan Hadi Zumarni, Zumarni

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