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Kusrini

Universitas Amikom Yogyakarta

Author-ID : 302666

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Data Ranking Optimization: Hybrid Fuzzy AHP-VIKOR with Information Gain Ratio Attribute Reduction Muzakir, Muhammad; Kusrini, Kusrini; Arief, Muhammad Rudyanto
KLIK- KUMPULAN JURNAL ILMU KOMPUTER Vol 11, No 2 (2024)
Publisher : Lambung Mangkurat University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20527/klik.v11i2.689

Poverty in Indonesia, including in Banjarmasin City, South Kalimantan Province, remains a significant issue despite the government's implementation of various mitigation programs. One of the primary challenges is the distribution of social assistance, which often fails to reach the intended beneficiaries. To address this problem, this study aims to apply the Hybrid Fuzzy Analytic Hierarchy Process (AHP) - Technique for Order Preference by Similarity to Ideal Solution (VIKOR) algorithm to the integrated social welfare data (DTKS) in Banjarmasin City. The hybrid Fuzzy AHP - VIKOR approach is employed in this study to rank social assistance recipients based on the available dataset, which consists of 2,879 records. Fuzzy AHP is utilized for the weighting and classification process, while VIKOR is applied to rank the alternatives. The combination of these two methods is expected to yield a more accurate ranking that aligns with the actual needs identified in the DTKS data for Banjarmasin City. The findings of this study demonstrate that the application of AHP and VIKOR methods produces more accurate rankings in accordance with the real data. These results have significant implications for enhancing the effectiveness of poverty alleviation programs and aiding the Banjarmasin City government in prioritizing the distribution of social assistance. By integrating the Fuzzy AHP and VIKOR methods, this study provides a deeper understanding of the more targeted distribution of social assistance, which is anticipated to improve the effectiveness of poverty alleviation programs in Banjarmasin City and beyond.

Metode Machine Learning dan Deep Learning dalam Prediksi Kinerja Siswa: Tinjauan Sistematis Desty Yani; Kusrini Kusrini
G-Tech: Jurnal Teknologi Terapan Vol 9 No 1 (2025): G-Tech, Vol. 9 No. 1 January 2025
Publisher : Universitas Islam Raden Rahmat, Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70609/gtech.v9i1.6501

Research on student performance prediction has advanced rapidly in recent years, driven by the increasing volume of educational data generated by digital learning platforms. This data can be analyzed using Machine Learning (ML) and Deep Learning (DL) techniques, integrated with feature management strategies tailored to specific needs. However, selecting the most relevant features and optimizing predictive models remain significant challenges. Different studies apply various feature selection and engineering techniques, leading to inconsistent results and limited generalizability. This study conducts as a Systematic Literature Review (SLR) to explore ML and DL approaches for student performance prediction, emphasizing their relationship with feature management techniques. The reviewed studies span publications from 2019 to 2024. This SLR aims to assist researchers in identifying effective strategies for predicting student performance, including the selection of methods, datasets, or feature management techniques. Most studies utilized publicly available datasets due to their accessibility and ease of use. Among ML methods, Random Forest emerged as the most frequently applied, achieving an F-measure of 99.5% integration of filter-based and wrapper-based feature selection techniques. Among DL approaches, the ANN-PCACSN model, employing Principal Component Analysis (PCA) for dimensionality reduction, achieved the highest accuracy of 99.32%. These findings highlight the importance of aligning preprocessing strategies with dataset properties and algorithm capabilities to enhance predictive performances.

Application of K-Means and Naïve Bayes Algorithms for Prediction Model of Student Interest Concentration (Case Study: Amikom University Yogyakarta) Danang Eko Prayogo; Kusrini Kusrini
G-Tech: Jurnal Teknologi Terapan Vol 9 No 1 (2025): G-Tech, Vol. 9 No. 1 January 2025
Publisher : Universitas Islam Raden Rahmat, Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70609/gtech.v9i1.6523

Amikom University Yogyakarta, has a Master of Informatics Engineering study program with three concentrations of specialization: Business Intelligence, Digital Information Intelligence, and Intelligence Animation. The choice of concentration by prospective students has been based on subjectivity, not on competence or work experience. To overcome this, this research proposes an algorithm-based concentration prediction and recommendation model to help prospective students choose the appropriate concentration. The dataset is obtained through questionnaires collected from active and inactive students. This research uses the K-Means algorithm for clustering raw data (unsupervised) in order to generate target classes, which are then classified using Naïve Bayes. The clustering process determines concentration labels such as Business Intelligence and others, while the SMOTE technique is used to balance the dataset to avoid data imbalance problems. This approach aims to produce more objective and accurate recommendations in determining student concentrations, reducing the tendency of subjectivity, and increasing the relevance of student competencies to the chosen field of specialization. From this research, the K-Means DBI score is 0.277 and the Naïve Bayes prediction accuracy score is 89%. This research aims to produce more objective and accurate recommendations in determining student concentrations, reducing subjectivity, and increasing the relevance of student competencies to the chosen field of specialization. The proposed model is expected to help universities in designing a more targeted admission strategy, as well as supporting students in making academic decisions that are in accordance with their abilities and interests, thereby increasing the effectiveness of the learning process and the suitability of graduates to the needs of the world of work.

ANALISIS PERBANDINGAN ALGORITMA KLASIFIKASI UNTUK IDENTIFIKASI DIABETES DENGAN MENGGUNAKAN METODE RANDOM FOREST DAN NAIVE BAYES Zuhri, Muhammad Rafli; Kusrini, Kusrini; Ariatmanto, Dhani
Jurnal Informatika Teknologi dan Sains (Jinteks) Vol 7 No 1 (2025): EDISI 23
Publisher : Program Studi Informatika Universitas Teknologi Sumbawa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51401/jinteks.v7i1.5146

Penanganan penyakit diabetes menjadi penting karena komplikasi yang dapat terjadi jika tidak ditanggulangi dengan benar. Klasifikasi merupakan salah satu metode yang dapat digunakan untuk mengidentifikasi diabetes. Algoritma klasifikasi ini dapat menganalisis data pasien, seperti usia, jenis kelamin, riwayat kesehatan, dan hasil tes, untuk memprediksi apakah pasien tersebut menderita diabetes. Random Forest dan Naïve Bayes merupakan dua algoritma klasifikasi yang populer. Random Forest adalah metode kompleks yang didasarkan pada penggabungan beberapa pohon keputusan untuk mendapatkan prediksi yang lebih akurat, sedangkan Naïve Bayes merupakan metode pengklasifikasian berdasarkan probabilitas sederhana dan dirancang agar dapat dimanfaatkan denegan asumsi antar variabel penjelas saling bebas (independen). Hasil penelitian menggunakan data sebanyak 70% sebagai data pelatihan dan 30% sebagai data pengujian dari keseluruhan 768 data. keseluruhan yang diperoleh bahwa metode random forest dapat memprediksi penyakit diabetes dengan tingkat persentase sebesar 94% dan tingkat persentase naïve bayes sebesar 78%. Berdasarkan hasil penelitian yang diperoleh metode random forest memiliki tingkat persentase lebih tinggi dibandingkan metode naïve bayes dengan tingkat persentase 94% sedangkan naïve bayes dengan tingkat persentase 78% sehingga dapat disimpulkan bahwa metode random forest merupakan metode terbaik dalam mengindentifikasi penyakit diabetes dibandingkan metode naïve bayes.

Optimasi Prediksi Harga Emas Menggunakan CNN-Bi-LSTM dengan Mekanisme Attention dan Bayesian Optimization Fitriyanto, Nur; Kusrini, Kusrini
Journal of Economic, Management, Accounting and Technology (JEMATech) Vol 8 No 1 (2025): Februari
Publisher : Fakultas Teknik dan Ilmu Komputer, Universitas Sains Al-Qur'an (UNSIQ) Wonosobo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32500/jematech.v8i1.8668

Prediksi harga emas merupakan aspek penting dalam investasi global karena volatilitasnya yang dipengaruhi oleh faktor ekonomi dan politik. Penelitian ini mengembangkan model hybrid CNN-Bi-LSTM dengan mekanisme Attention untuk menangkap pola data signifikan dan Bayesian Optimization untuk pencarian hyperparameter yang lebih efisien. Dataset yang digunakan mencakup harga emas harian dari 29 Desember 1978 hingga 4 Juni 2021, yang terbagi menjadi data pelatihan (70%), validasi (20%), dan pengujian (10%). Model yang dioptimasi menunjukkan hasil evaluasi dengan RMSE sebesar 17,98, MAE sebesar 10,93, RMAE sebesar 3,31, dan R² sebesar 1,00. Visualisasi hasil menunjukkan konvergensi stabil tanpa overfitting, distribusi residual yang mendekati normal, serta prediksi yang konsisten dengan data aktual. Integrasi mekanisme Attention dan Bayesian Optimization terbukti meningkatkan performa model secara signifikan. Penelitian ini membuka peluang pengembangan lebih lanjut dengan memasukkan variabel makroekonomi tambahan, seperti harga minyak mentah atau indeks saham, untuk memperluas cakupan prediksi.

Enhancing fire detection capabilities: Leveraging you only look once for swift and accurate prediction Nugroho, Agung; Agastya, I Made Artha; Kusrini, Kusrini
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 14, No 2: April 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v14.i2.pp1326-1334

Detecting fires is crucial to prevent potentially catastrophic outcomes. Traditional fire detection methods, relying on electronic, chemical, or mechanical sensors, often suffer from time delays in activation due to threshold parameters. An emerging alternative utilizes artificial intelligence, particularly image-based fire detection, using convolutional neural networks (CNNs). You only look once (YOLO) is a state-of-the-art object detection framework prized for speed and real-time capabilities. In our research, we conducted multiple training experiments employing various deep neural network (DNN) architectures as feature extractors for object detection within the YOLOv5 framework. These architectures included MobileNetV3, ResNet, and CSP-Darknet53. Among these configurations, YOLOv5 with CSP-Darknet53 (scale s) emerged as the most accurate, boasting mAP@50 of 0.88 and an impressive FPS of 73, with training model size of 14.50 MB. Furthermore, we integrated the selected model with the streamlit package to create a user-friendly web application interface for fire detection testing. The resulting model demonstrates remarkable efficiency, detecting fires within 0.01 seconds. This research represents a significant advancement in fire detection technology, offering both rapid detection and enhanced accuracy, with potential applications in various settings, from indoor facilities to outdoor environments.

Environmental Acoustic Features Robustness Analysis: A Multi-Aspecs Study Semma, Andi Bahtiar; Kusrini, Kusrini; Setyanto, Arif; da Silva, Bruno; Braeken, An
INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi Vol 9 No 1 (2025): February 2025
Publisher : Universitas Nusantara PGRI Kediri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29407/intensif.v9i1.23723

Abstract—Background: Acoustic signals are complex, with temporal, spectral, and amplitude variations. Their non-stationarity complicates analysis, as traditional methods often fail to capture their richness. Environmental factors like reflections, refractions, and noise further distort signals. While advanced techniques such as adaptive filtering and deep learning exist, comprehensive acoustic feature analysis remains limited. Objective: This study investigates which acoustic features maintain the highest robustness across diverse environments while preserving discriminative power. Methods: Audio samples were recorded in controlled environments (jungles, cafés, factories, streets) with varying noise levels. Standardized equipment captured 22050 Hz, 16-bit audio at multiple positions and distances. After amplitude standardization, various acoustic features were extracted and analyzed. Results: MFCCs demonstrated exceptional reliability, with correlation coefficients of 0.98819 and 0.98889 for closely positioned devices and a robustness score of 0.99. Across different acoustic scenes and sample lengths (1, 3, 5s), MFCCs maintained high correlation (≈0.978) and robustness (0.98), confirming their versatility. Conclusion: MFCCs proved highly effective for acoustic fingerprinting across settings. Despite limitations in tested environments (≤5m distance, ≤5s samples), their consistent performance validates the methodology. Future research should explore combining MFCCs with spectral features and expanding studies to broader environments and device types.

SISTEM KLASIFIKASI PENYAKIT JANTUNG BERBASIS PARTICLE SWARM OPTIMIZATION DAN NAÏVE BAYES DENGAN 5-FOLD CROSS VALIDATION Mufti Ari Bianto; Kusrini, Kusrini
Journal of Innovation Research and Knowledge Vol. 3 No. 8: Januari 2024
Publisher : Bajang Institute

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

Serangan Jantung adalah salah satu penyakit yang paling mematikan tercatat di dunia, terdapat jumlah kasus baru Penyakit Jantung sebanyak 1,5% serta jumlah kematian sebanyak 14,38%. Pada tahun 2022 jumlah penderita Penyakit Jantung di Indonesaia sejumlah 139.891 orang, pada umumnya jumlah penderita penyakit ini terus meningkat dikarenakan kurangnya pengetahuan atau informasi tentang penyakit jantung tersebut. Oleh karena itu dibutuhkan sebuah sistem yang dapat memberikan informasi serta klasifikasi penyakit secara dini yang dapat digunakan untuk klasifikasi apabila seseorang ingin mengetahui informasi ataupun gejala awal serangan jantung. Metode naïve bayes merupakan salah satu metode yang digunakan untuk melakukan klasifikasi berdasarkan probabilitas atau kemungkinan dari data sebelumnya, selain pendekatannya sederhana metode tersebut juga dapat melakukan klasifikasi secara baik. Mekanisme pengujiannya yaitu membagi 303 data kedalam 5 subset yang akan divalidasi dengan 5-fold cross validation. Hasil akhir dari penelitian ini adalah penerapan sistem klasifikasi dengan menggunakan metode naïve bayes yang akan menghasilkan nilai rata-rata akurasi sebesar 90,61%, presisi sebesar 87,44 %, dan recall sebesar 87,95%.

Prediksi Transaksi Minat Pembelian Online Menggunakan Kombinasi CNN Conv1D dan BiLSTM Herawati, Maimi; Kusrini, Kusrini
Journal Cerita: Creative Education of Research in Information Technology and Artificial Informatics Vol 11 No 1 (2025): Journal CERITA : Creative Education of Research in Information Technology and Ar
Publisher : UNIVERSITAS RAHARJA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/cerita.v11i1.3702

The rapid development of information technology has transformed consumer shopping behavior, particularly through e-commerce platforms. Online shopping has become a primary trend due to its convenience and the growing penetration of the internet. Understanding online purchase intention is therefore crucial for businesses in devising effective marketing strategies. Purchase intention is influenced by factors such as product quality, price, customer reviews, and platform usability. However, predicting purchase intention poses a significant challenge due to the large and complex nature of consumer data. Smote used for imbalance data. This study aims to combine CNN (Conv1D) and BiLSTM for high-accuracy purchase intention prediction. The research focuses on analyzing model accuracy and the effectiveness of the algorithms in handling imbalanced data. The results indicate that the combined CNN(Conv1D) + BiLSTM model achieves 97% accuracy with balanced evaluation metrics, although the True class recall (96%) is slightly lower than that of the False class (95%). Further optimization is needed to enhance overall model performance.

Rainfall Prediction in Jayapura City Area Using Long Short-Term Memory Azi, Amanda; Kusrini, Kusrini
Journal of Computer Networks, Architecture and High Performance Computing Vol. 7 No. 2 (2025): Forthcoming: Research Article, Volume 7 Issue 2 April, 2025
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v7i2.5506

Jayapura, one of Indonesia’s major fishing cities, relies heavily on accurate weather predictions to ensure the safety of its fishermen, particularly due to its significant tuna and skipjack production. This study aims to improve rainfall forecasting in Jayapura using a Long Short-Term Memory (LSTM) model, a type of artificial neural network designed for time series prediction. Accurate rainfall forecasts are crucial for reducing the risks fishermen face at sea due to sudden weather changes. Daily data from the Meteorological Station in Dok II Jayapura was collected and processed to train the LSTM model, incorporating variables such as TAVG (average temperature), RH_AVG (average relative humidity), FF_AVG (average wind speed), Pressure (air pressure), and Wind_Gust (wind gust). The model’s performance was evaluated using Mean Absolute Error (MAE) and Root Mean Squared Error (RMSE), yielding low values of 0.0542 and 0.0847, respectively, indicating high prediction accuracy. The MAE reflects the average magnitude of errors, while the RMSE highlights the model’s sensitivity to larger deviations, both supporting the reliability of the LSTM approach. The findings demonstrate that LSTM models can effectively forecast rainfall in Jayapura, providing valuable information that helps fishermen plan their activities more safely and efficiently. The study concludes that LSTM is a robust tool for rainfall prediction, and the inclusion of additional meteorological variables has proven to enhance accuracy. Further research is recommended to explore other factors to improve prediction reliability.

Co-Authors - Saifulloh A.A. Ketut Agung Cahyawan W AA Sudharmawan, AA 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 Adhani, Muhammad Azmi 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 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 Agustina, Nova 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 Amanullah, Raynaldi Fatih Amborowati, Armadyahah Amir Bagja Amir Fatah Amir Fatah Sofyan Amrina Rosyada anas, hasni Anastasia Meyliana Andayani Andayani Andhika Wisnu Widyatama 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 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 Suhartanto Ari Yuana, Kumara Arief Setyanto Arief Setyanto Arief Setyanto 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 Artha Agastya, I Made Arwendra Adi Putra Asnawi, Muhamad Fuat Asri, Saffinah Indah Asro Nasiri Asro Nasiri Asro Nasiri Asro Nasiri Asro Nasiri Asro Nasiri Asro Nasrini Assani, Moh. Yushi Atin Hasanah 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 Béjar, Rodrigo Martínez Bentar Candra P Bernadhed, Bernadhed Bimantyoso Hamdikatama Bisono, Hadi Hikmadyo Braeken, An Brenstein Mawene Buana, Yopy Tri 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 Darmawan, Eko Rahmad Darno - David Agustriawan David Junggu Manggala Pasaribu dayat subekti Dede - Sandi Dede Husen Dedi Gunawan Dema Matias L Tobing Dengen, Christin Nandari 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 Cahyani, Atika DWI ISKANDAR Dwi Utami Dwi Yuli Prasetyo Dwinda Etika Profesi Dwinda Etika Profesi Dzalfa Tsalsabila Rhamadiyanti Dzulhijjah, Dwi Ahmad 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 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 Ema Utami Emha T aufiq Luthfie Emha Taufik Luthf Emha Taufiq Luthfi EmhaTaufiq Lutfi, EmhaTaufiq Enni Lidrawati Erfan Tongalu Eri Sasmita Susanto Erwin Apriliyanto Erwin Apriliyanto Eva Oktaviani Fahma Inti Ilmawati Fahrullah, Fahrullah Fajar Dwi Insani Fajar Sodik Fajar Sudana Putra Fandli Supandi Fandli Supandi Fansuri, Muhammad Febrian Fareza Aditiyanto Nugroho 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 Fitriyandhi, Ari 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 hartanto, david budi Hartono, Anggit Dwi Haryo, Wasis Hasan, Nur Fitrianingsih Hasan, Nurul Rahmawati Hasim, Hasim As'ari Hasirun Hasirun Hasirun, Hasirun Hasnan Afif Helmawati, Nita Henderi Henderi . Hendriansyah Santosa Hendrik Hendrik Henri Kurniawan Henri Kurniawan Herawati, Maimi Heri Abijono Heri Abijono, Heri Heri Sismoro 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 Ilmi, M. Bahril Imam Listiono Indarto, Aan 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 Jumiati Jumiati Junaidi Junaidi Junaidi Sabtu Juwari Juwari Juwariyah, Siti Kaharuddin Kanafi Kanafi Kasman, Haris Saktiawan Kelik Sussolaikah Kemal Pasha Khoironi, Khoironi Khoirul Islam Khoirun Nisa Khomsatun Khomsatun Khusnawi Khusnawi Kristian, Taufik Aldri 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 La Aba 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. 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 Mardiana Mardiana marhalim, marhalim Marissa Utami Marta Ardiyanto Martínez-Béjar, Rodrigo Marwan Noor Fauzy MASRIYAH Masruri, Nizar Haris Masud, Ibnu Mat Sudir maulana, fahrizal Mawene, Brenstein Maykel Sonobe Maykel Sonobe Megantara, Muhamad Arldi MEI PARWANTO KURNIAWAN Metha, Halifa Sekar Miftachuddin, Achmad Agus Athok Mochamad Fadillah Abdullah Moenawar Kholil 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 Egy Pratama Muhammad Fahmi Muhammad Fajar Apriyanto Muhammad Fajrian Noor Muhammad Firdaus Abdi Muhammad Firdaus Abdi Muhammad Koprawi Muhammad Mariko Muhammad Nafi’Uddin Muhammad Resa Arif Yudianto Muhammad Riandi Widiyantoro Muhammad Riza Eko S Muhammad Rudyanto Arief Muhammad Rudyanto Arief Muhammad Rudyanto Arief Arief Muhammad Salimy Ahsan Muhirin Muktafin, Elik Hari Mukti Ali Mulia Sulistiyono Mulyaningtyas, Widya 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, Ni Nyoman Nibras Faiq Muhammad Nikko Listio Wicaksono NINIK TRI HARTANTI 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 Nurdianingsih, Neneng 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 Perdana, 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 Puri, Fiyas Mahananing 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 Riska Dwi Handayani Risna Sari Rita Wati Ritham Tuntun Riyan Abdul Aziz Rizal Khadarusman Rizal Sapta Dwi Harjo Rizkayati, Anisa Rizki Firdaus Mulya Rizki Mawan Rizky Aries Saputra Rizqi Sukma Kharisma Robi Wariyanto Abdullah 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 Sarawan, Tommy 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 Solikin, Arif Fajar Sri Handayani Sri Hartati Sri Lestari Rahayu Sri Wahyuningsih Sri Wulandari 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 Suhendri Sukasna . Sukasna, Sukasna Supraba, Laksmita Dewi Supriantara Supriantara Supriatin Supriatin Supriyati Supriyati 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 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 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 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 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, Risca 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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