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Kusrini

Universitas Amikom Yogyakarta

Author-ID : 302666

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Benchmarking Hyperparameter Variations on Transfer Learning Models for Coral Reefs Classification: A Case Study on Efficientnetv2 and Mobilenetv2 Bimantyoso Hamdikatama; Dedi Gunawan; Kusrini Kusrini
Jurnal Nasional Komputasi dan Teknologi Informasi (JNKTI) Vol 8, No 1 (2025): Februari 2025
Publisher : Program Studi Teknik Komputer, Fakultas Teknik. Universitas Serambi Mekkah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32672/jnkti.v8i1.8792

Abstract - Coral reef recognition using transfer learning models is a critical area of research to enhance automated monitoring and conservation efforts. This study examines the impact of hyperparameter tuning on the performance of two models, EfficientNetV2 and MobileNetV2, in recognizing coral reef conditions such as bleaching, physical damage, and algae overgrowth. Bayesian Optimization is evaluated as an automated hyperparameter tuning method alongside Grid Search, Random Search, and Manual Trial-based approaches. The results reveal that Bayesian Optimization achieves competitive accuracy (up to 0.81) and balances computational efficiency with performance, requiring fewer trials compared to manual optimization. Notably, Bayesian Optimization reduces training time while maintaining high metrics such as Precision and Specificity. These findings highlight the effectiveness of Bayesian Optimization in improving model performance for coral reef recognition, offering a reliable and efficient solution to support conservation decision-making. This approach also demonstrates potential for broader applications in classification and regression tasks.Keywords: EfficientNetV2, MobileNetV2, Optimization, Coral Reefs Abstrak - Pengenalan terumbu karang menggunakan model pembelajaran transfer adalah bidang penelitian yang penting untuk meningkatkan upaya pemantauan dan konservasi otomatis. Penelitian ini menguji dampak penyetelan hyperparameter pada kinerja dua model, EfficientNetV2 dan MobileNetV2, dalam mengenali kondisi terumbu karang seperti pemutihan, kerusakan fisik, dan pertumbuhan berlebih alga. Bayesian Optimization dievaluasi sebagai metode penyetelan hiperparameter otomatis bersama dengan Pencarian Grid, Pencarian Acak, dan pendekatan berbasis Uji Coba Manual. Hasilnya menunjukkan bahwa Bayesian Optimization mencapai akurasi yang kompetitif (hingga 0,81) dan menyeimbangkan efisiensi komputasi dengan kinerja, sehingga membutuhkan lebih sedikit uji coba dibandingkan dengan pengoptimalan manual. Selain itu, Bayesian Optimization mengurangi waktu pelatihan dengan tetap mempertahankan metrik yang tinggi seperti Presisi dan Spesifisitas. Temuan ini menyoroti efektivitas Optimasi Bayesian dalam meningkatkan kinerja model untuk pengenalan terumbu karang, menawarkan solusi yang andal dan efisien untuk mendukung pengambilan keputusan konservasi. Pendekatan ini juga menunjukkan potensi untuk aplikasi yang lebih luas dalam tugas klasifikasi dan regresi.Kata kunci: EfisienNetV2, MobileNetV2, Optimasi, Terumbu Karang

Implementasi Pengembangan Sistem Model Water Fall Untuk Data Warehouse Akademik Sofan Tohir, Arik Sofan Tohir; Kusrini, Kusrini; Sudarmawan, Sudarmawan
INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi Vol 1 No 2 (2017): Vol. 1 No. 2 Agustus 2017
Publisher : Universitas Nusantara PGRI Kediri

Data warehouse is a concept and a technology to store transactional data from several sources that have been through the process of filtering and selection of data. By using the Ectract, Transform and Load (ETL) process in the data warehouse, OLTP data is processed to produce good data and ready for use for the analysis process. For the design of this warehouse data will be built by using the Nine Step Method from Kimbal, so that the resulting warhouse data can be as expected. For the development of life flow system (SDLC) with waterfall model. By using the wate fall model will be built a prototype to implement the data warehouse design results.

Yayak Kartika Sari Prediksi Customer Churn Berbasis Adaptive Neuro Fuzzy Inference System Sari, Yayak Kartika; Kusrini, Kusrini; Wibowo, Ferry Wahyu
Generation Journal Vol 2 No 1 (2018): Generation Journal
Publisher : Universitas Nusantara PGRI Kediri

Abstrak – Customer Churn adalah pelanggan yang berhenti berlangganan dan pindahpada perusahaan lain, karena berbagai faktor. Customer churn merupakan masalah yang sangatpenting yang harus dihadaapi oleh perusahaan karena berhentinya pelanggan akan berdampakpada retensi perusahaan. Oleh sebab itu, dibuatkan sistem prediksi customer churn untukmengetahui tingkat pelanggan yang churn, apabila customer churn dapat diketahui terlebih dahulu,maka akan menguntungkan bagi pihak CRM untuk mengatur strategi-strategi mencegah pelangganyang melakukan churn. Untuk menentukan prediksi customer churn menggunakan teknik datamining dengan algoritma ANFIS. Algoritma ANFIS merupakan gabungan antara jaringan syaraftiruan dengan fuzzy inference system. Model prediksi yang dibangun dengan metode ANFISmenggunakan pembelajaran alur maju dan pembelajaran alur mundur, sehingga untuk melakukanprediksi dibutuhkan nilai parameter fuzzy baru yang diperoleh dari proses pelatihan. Setelah nilaiparameter fuzzy baru didapatkan, maka akan dilakukan tahap pengujian. Pada tahap pengujiandilakukan dengan proses pembelajaran maju untuk mendapatkan nilai prediksinya, sehingga padaprosesnya nilai prediksi yang berupa angka dan status prediksi. Pelatihan dan pengujian ANFISuntuk semua produk menghasilkan perbandingan nilai error rata-rata pelatihan sebesar 8,316 %

Heri Abijono Analisis Perbandingan Metode Simple Additive Weighting dan Profile Matching dalam Sistem Pendukung Keputusan Abijono, Heri; Kusrini, Kusrini
Generation Journal Vol 2 No 2 (2018): Generation Journal
Publisher : Universitas Nusantara PGRI Kediri

Peneliti telah menerapkan sistem pendukung keputusan berupa suatu aplikasiuntuk mendistribusikan dana Bantuan Siswa Miskin (BSM) di tahun 2015 dengan menggunakanmetode Simple Additive Weighting. Peneliti kemudian mengembangkan sistem ini di tahun 2017dengan menambahkan ketentuan kepemilikan Kartu Perlindungan Sosial ataupun Surat KeteranganRumah Tangga Miskin untuk mempertimbangkan prioritas pemberian dana bantuan itu, selainmempertimbangkan empat macam kriteria yang telah ada pada sistem sebelumnya. Penelitian kaliini ditujukan untuk membandingkan algoritma dari dua metode, Simple Additive Weighting danProfile Matching, untuk menentukan metode mana yang cocok dipakai dalam pendistribusian danaBSM. Peneliti membuat analisis berupa perhitungan-perhitungan sesuai algoritma dari dua buahmetode yang diperbandingkan dengan menunjukkan cara kerja proses dari tiap-tiap metode yangdiperbandingkan. Keluaran sistem adalah berupa informasi perankingan prioritas siswa untukmemperoleh dana BSM.

Meningkatkan Keamanan Pesan Menggunakan Enkripsi Arnold Cat Map Dan Steganografi Pixel Value Differencing Masruri, Nizar Haris; Kusrini, Kusrini; Sunyoto, Andi
Prosiding SEMNAS INOTEK (Seminar Nasional Inovasi Teknologi) Vol. 3 No. 1 (2019): PROSIDING SEMNAS INOTEK Ke-III Tahun 2019
Publisher : Universitas Nusantara PGRI Kediri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29407/inotek.v3i1.522

Pesan tidak hanya berupa text, namun juga berbentuk gambar. Sebuah pesan gambar terkadang merupakan informasi yang sangat rahasia contohnya gambar informasi barang bukti. Untuk itu dibutuhkan teknik untuk melindungi pesan tersebut agar tidak diketahui oleh pihak lain. Pixel Value Differencing (PVD) merupakan salah satu teknik penyisipan pesan ke dalam data digital seperti gambar (citra) dengan kelebihan kapasitas penampung yang besar. PVD menghitung selisih nilai piksel dengan cara membagi piksel-piksel citra menjadi blok-blok yang terdiri dari dua buah piksel yang posisinya berdekatan yang digunakan sebagai tempat penyisipan pesan. Untuk meningkatkan keamanan, maka dilakukan enksripsi pada pesan citra agar konstruksi citra menjadi tidak beraturan sehingga tidak mudah untuk diketahui dan dimanipulasi oleh pihak lain. Paper ini akan menggabungkan steganografi PVD dan metode enskripsi Arnold Cap Map (ACM). Untuk mengetahui kualitas citra yang tersisipi pesan, maka dilakukan evaluasi kualitas citra dengan perhitungan nilai Mean Square Error (MSE) dan Peak Signal to Noise Ratio (PSNR). Hasil pengujian menunjukkan bahwa citra dengan resolusi 512x512 piksel menghasilkan nilai MSE : 0.36311 dan PSNR (db): 57.3356, sedangkan citra dengan resolusi 256x256 piksel menghasilkan nilai MSE : 11.1786 dan PSNR(db) : 42.4521.

Polarized Amplitude Time Spiral Encoding for Infant Cry Audio Augmentation and CNN Classification Nuk Ghurroh Setyoningrum; Ema Utami; Kusrini; Ferry Wahyu Wibowo
Journal of Innovation Information Technology and Application (JINITA) Vol 7 No 2 (2025): JINITA, December 2025
Publisher : Politeknik Negeri Cilacap

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35970/10.35970/jinita.v7i2.2960

Recognizing infant cries is essential for healthcare, yet conventional representations such as spectrograms and MFCC often fail to capture temporal dynamics, limiting classification performance. This study introduces Polarized Amplitude Time Spiral Encoding (PATSE), a novel transformation that encodes amplitude and time into spiral-based polar representations, enabling richer visual features for deep learning. To address data scarcity and imbalance, audio augmentation techniques time stretching, time shifting, pitch scaling, and polarity inversion were applied, expanding the dataset from 457 to 6855 samples. A Convolutional Neural Network (CNN) trained on PATSE images achieved notable improvements, with overall accuracy increasing from 80% before augmentation to 93% after augmentation. The model attained high performance on the dominant Hungry class (F1-score = 0.96) while also enhancing recognition of minority classes such as belly pain, burping, discomfort, and tired. These results confirm the effectiveness of PATSE in improving generalization and reducing bias, offering a distinctive advantage over linear representations. The proposed framework provides a foundation for intelligent infant cry monitoring and early detection systems in healthcare.

ANALISIS KOMPARATIF KLASIFIKASI SENTIMEN PENGGUNA APLIKASI INVESTASI MENGGUNAKAN ALGORITMA HYBRID CNN-LSTM, CNN-GRU DENGAN IMPLEMENTASI SMOTE I Putu Agus Ari Mahendra; Kusrini Kusrini
TEKNIMEDIA: Teknologi Informasi dan Multimedia Vol. 6 No. 1 (2025): Juni 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.v6i1.258

Sentiment analysis, a branch of Natural Language Processing (NLP), plays a crucial role in identifying and classifying opinions embedded in text. This study aims to compare the performance of hybrid CNN-LSTM and CNN-GRU models in sentiment analysis of user reviews for investment applications on Google Play Store, utilizing the Synthetic Minority Over-sampling Technique (SMOTE) to address data imbalance. A total of 15,000 user reviews were collected through web scraping, preprocessed using the TF-IDF method and various text cleaning techniques. The CNN-LSTM and CNN-GRU models were evaluated using an 80%-20% train-test split. The evaluation results showed that CNN-GRU outperformed in terms of precision (91.62%), F1 score (90.45%), and overall accuracy (87.60%), while CNN-LSTM excelled in recall (91.08%) for detecting positive reviews. CNN-GRU was deemed more balanced in detecting both positive and negative sentiments, making it a more reliable choice for sentiment analysis requiring uniform performance

KLASIFIKASI RANDOM FOREST TERHADAP DIAGNOSA PENYAKIT KANKER PAYUDARA BERDASARKAN STATUS KEGANASAN Yusrinnatul Jinana triadin; Kusrini Kusrini; Kusnawi Kusnawi
TEKNIMEDIA: Teknologi Informasi dan Multimedia Vol. 6 No. 1 (2025): Juni 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.v6i1.259

Breast cancer is one of the diseases with the highest mortality rate in the world. There are two types of breast cancer, namely malignant and benign. Identification of the type allows for prevention and appropriate treatment before it spreads to other organs. Therefore, a large amount of breast cancer data classification analysis is needed. Data mining techniques, such as random forest, can be used because they are able to provide accurate predictions with a low error rate. The results of this study indicate that *Random Forest is an effective and accurate method for breast cancer classification with an accuracy of 95% and an AUV-ROC value of 0.99 and a recall of 97% which shows the model's ability to distinguish the two types of breast cancer very well so that it can reduce the risk. The use of the 5-Fold Cross-Validation technique) ensures that the results obtained are stable and do not depend on certain data divisions, thereby increasing the generalization of the model. Experiments on various parameters (n_estimators, max_depth, training data size) show that the best configuration is n_estimators = 100 and max_depth = 10, which provides the optimal balance between accuracy and model complexity. This model can be applied in a **Medical Decision Support System* to assist doctors in *early detection of breast cancer*, thereby increasing the speed and accuracy of diagnosis.

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 CITRA DENGAN POHON KEPUTUSAN Kusrini Kusrini; Sri Hartati; Retantyo Wardoyo; Agus Harjoko
JUTI: Jurnal Ilmiah Teknologi Informasi Vol 7, No 2, Juli 2008
Publisher : Department of Informatics, Institut Teknologi Sepuluh Nopember

Image classification can be done by using attribute of text that come along with the image, such as file name, size, or creator. Image classification also can be done base on visual content of the image. In this research, we implement a image classification model base on image visual content. The image classification is based on decision tree method that adapt C4.5 algorithm. The decision variable used in the decision tree generation process is image visual features, i.e. color moment order-1, color moment order-2, color moment order-3, entropy, energy, contrast, and homogeneity. The result of this research is an application that can classified image base on the knowledge of the previous classification cases. Keywords: image classification, decision tree, C4.5 algorithm

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 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 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 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 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 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 Rizaldi, Rizaldi 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 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 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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