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All Journal International Journal of Electrical and Computer Engineering Seminar Nasional Aplikasi Teknologi Informasi (SNATI) Jurnal Ilmu Komputer dan Informasi Lontar Komputer: Jurnal Ilmiah Teknologi Informasi Majalah Ilmiah Teknologi Elektro Jurnal Teknik ITS IPTEK The Journal for Technology and Science Semantik TELKOMNIKA (Telecommunication Computing Electronics and Control) Bulletin of Electrical Engineering and Informatics Jurnal Ilmiah Kursor Jurnal Teknologi Informasi dan Ilmu Komputer Setrum : Sistem Kendali-Tenaga-elektronika-telekomunikasi-komputer agriTECH Scientific Journal of Informatics Seminar Nasional Informatika (SEMNASIF) EMITTER International Journal of Engineering Technology Proceeding of the Electrical Engineering Computer Science and Informatics JOIV : International Journal on Informatics Visualization Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Journal of Information Technology and Computer Science Jurnal Sains Dan Teknologi (SAINTEKBU) Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Jurnal Inotera Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI) CCIT (Creative Communication and Innovative Technology) Journal JAVA Journal of Electrical and Electronics Engineering JAREE (Journal on Advanced Research in Electrical Engineering) Jurnal Nasional Teknik Elektro dan Teknologi Informasi Makara Journal of Technology Jurnal Rekayasa elektrika Majalah Ilmiah Teknologi Elektro
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EKSTRAKSI FITUR SECARA OTOMATIS UNTUK PENGENALAN POLA GERAKAN MATA Eka Dwi Nurcahya; I Ketut Eddy Purnama; Mauridhi Hery Purnomo
Seminar Nasional Informatika (SEMNASIF) Vol 1, No 1 (2012): Computation And Instrumentation
Publisher : Jurusan Teknik Informatika

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Abstract

Mata manusia menyimpan berbagai informasi, termasuk isyarat dari gerakan mata. Mata manusia digerakkan oleh otot mata (ocular muscle) yang diatur oleh syaraf motorik. Ada beberapa jenis pergerakan mata antar lain pergerakan mata cepat atau tiba-tiba yang disebut gerakan saccadic dan fixation yaitu kontrol mata yang terfokus pada objek yang diam dapat digunakan sebagai penentu pola pergerakan mata. Pola pergerakan mata didapatkan dari perubahan titik tengah mata. Video gerakan mata dengan durasi 6 detik menghasilkan 150 frame sebanyak 72,8% berhasil mengidentifikasi area pupil sebagai titik tengah mata. Pola pergerakan mata yang didapatkan untuk dijadikan fitur adalah saccadic latency, durasi saccadic, kecepatan puncak dan tingkat kecepatan atau deviasi.
Estimator Parameter Tegangan Jaringan Tiga Fasa Berbasis D-SOGI PLL Iwan Setiawan; Mochammad Facta; Ardyono Priyadi; Mauridhi Hery Purnomo
Jurnal Teknologi Elektro Vol 16 No 2 (2017): (May - Agustus) Majalah Ilmiah Teknologi Elektro
Publisher : Universitas Udayana

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (228.417 KB) | DOI: 10.24843/MITE.2017.v16i02p15

Abstract

Phase locked loop (PLL) adalah sebuah sistem umpan balik yang memegang peran penting dalam sistem-sistem konverter terkoneksi jaringan listrik. Fungsi utama PLL adalah mendapatkan beragam informasi parameter jaringan yaitu seperti phase dan magnitude tegangan. Informasi-informasi tersebut selanjutnya digunakan sebagai dasar proses sinkronisasi peralatan dengan jaringan listrik. Tujuan utama paper ini adalah memodelkan sekaligus membandingkan unjuk kerja salah satu jenis PLL yang dikenal dengan nama Dual Second Order Generalized Integrator Phase-Locked Loop dengan SRF-PLL yaitu sebuah PLL yang relatif standar. Berdasarkan hasil simulasi, unjuk kerja D-SOGI PLL dalam keadaan tunaknya lebih unggul dibandingkan SRF-PLL terutama untuk kondisi jaringan listrik tiga phase tidak seimbang.
SUPERRESOLUTION USING PAPOULIS-GERCHBERG ALGORITHM BASED PHASE BASED IMAGE MATCHING Budi Setiyono; Mochamad Hariadi; Mauridhi Hery Purnomo
Jurnal Ilmiah Kursor Vol 6 No 3 (2012)
Publisher : Universitas Trunojoyo Madura

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Citra resolusi tinggi (High Resolution Image) akan memberikan informasi yang lebih detail, sehingga analisis terhadap citra tersebut menjadi lebih akurat. Banyak bidang memerlukan citra resolusi tinggi antara lain adalah medical, penginderaan satelite, citra dari teleskop serta pengenalan pola.Pada penelitian ini dilakukan proses untuk mendapatkan citra resolusi tinggi, yang dikenal dengan superresolution. Sebagai citra referensi, digunakan lebih dari satu citra, namun demikian, citra-citra tersebut berada pada scene yang sama. Dua tahap utama dalam superresolution adalah registrasi dan rekonstruksi. Registrasi yang akurat diperlukan untuk mendapatkan hasil rekonstruksi yang baik. Phase-Based Image Matching (PBIM) digunakan untuk estimasi translasi pada tahap registrasi. Hanya translasi sampai ketelitian sub pixel yang berkontribusi dalam rekonstruksi. Untuk mendapatkan translasi sampai level sub pixel, dilakukan fitting disekitar puncak. Sedangkan untuk rekonstruksi ke dalam Grid Resolusi tinggi digunakan algoritma Papoulis-Gerchberg. Penulis melakukan kolaborasi antara registrasi dengan PBIM dan rekonstruksi menggunakan algoritma PapoulisGerchberg. Uji coba dilakukan penulis dengan obyek serangkaian citra dengan banyak tekstur dan sedikit tekstur. Dari hasil uji coba, citra dengan banyak tekstur akan menghasilkan Peak Signal to Noise Ratio (PSNR) rata-rata 21,62. Sedangkan untuk citra yang kurang mengandung tekstur 19,54. Kata kunci: Superresolution, Registrasi, Rekonstruksi, Phased Based Image Matching. Abstract High Resolution Image provide more detail information, so that it obtain more accurate image analysis. Many areas require high resolution image, such as medical, sensing satellite, image of the telescope and pattern recognition. This research make a process to obtain high resolution images, known as superresolution. This superresolution using a series of images in the same scene as the reference image. Two main stages in the super resolution are the registration and reconstruction. An accurate registration is required to obtain a great reconstruction results. Phase-Based Image Matching (PBIM) will be used to estimate pixels translation at the registration stage. Only sub-pixels translation which contribute to the reconstruction phase. We used the function fitting around the peak point, to obtain sub pixel accurate shift. While reconstruct a high-resolution image use Papoulis-Gerchberg algorithm. The author collaborate registration and reconstruction. Registration using PBIM and reconstruction using Papoulis-Gerchberg algorithm. Experiments have been done with a series of images that contain much texture and less texture. The experimental results with images contain much texture produces an average Peak Signal to Noise Ratio (PSNR) 21.62. While image contain less texture produces PSNR 19.54.
POINT CORRESPONDENCE CORRECTION BASED ON SURFACE CURVATURE FEATURES Eko Mulyanto Yuniarno; Mochamad Hariadi; Mauridhi Hery Purnomo
Jurnal Ilmiah Kursor Vol 6 No 4 (2012)
Publisher : Universitas Trunojoyo Madura

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Abstract

3D computer model of a real object has been widely used in various applications such as motion capture, computer vision and computer graphics. To build a 3D computer model, multiview data point cloud of real object from different view point that obtained from a 3D scanner must be registered to placing the multiview data point cloud into a common coordinate system. Correspondence to find pair point matching is an important step in registration. False correspondence will affected to the registration quality.A novel technique of point correspondence correction between two point clouds is presented in this paper. The correspondence technique is started by selecting pair point matching candidate base on two reference point constraint then followed by correspondence correction using surface curvature feature. We tested the technique by applying thecorrespondence correction technique into three registration algorithm registration which is ICP, ICP-AIF and ICP-SCF then compare it with the original registration algorithm The result shows that registration algorithm using correspondence correction 63% faster, 23% more accurate and to find 530% more correct pair matching point than the original registration algorithm.
QUALITY IMPROVEMENT OF OBJECT EXTRACTION FOR KEYFRAME DEVELOPMENT BASED ON CLOSED-FORM SOLUTION USING FUZZY CMEANS AND DCT-2D Ruri Suko Basuki; Mochamad Hariadi; Mauridhi Hery Purnomo
Jurnal Ilmiah Kursor Vol 7 No 2 (2013)
Publisher : Universitas Trunojoyo Madura

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QUALITY IMPROVEMENT OF OBJECT EXTRACTION FOR KEYFRAME DEVELOPMENT BASED ON CLOSED-FORM SOLUTION USING FUZZY CMEANS AND DCT-2D aRuri Suko Basuki, bMochamad Hariadi, cMauridhi Hery Purnomo a,b,cFaculty of Industrial Technology, Dept. of Electrical Engineering Institut Teknologi Sepuluh Nopember, Kampus ITS Keputih, Sukolilo, Surabaya, Jawa Timur, Indonesia a Faculty of Computer Science, Dian Nuswantoro University Jalan Imam Bonjol, Semarang, Indonesia E-mail: a rurisb@research.dinus.ac.id Abstrak Penelitian ini bertujuan untuk meningkatkan kualitas ekstraksi obyek pada citra tunggal hasil pemecahan frame dari video sekuensial yang terkompresi. Kualitas hasil ekstraksi obyek dengan algoritma closed-form solution menurun karena adanya beberapa perubahan nilai intensitas pada channel RGB. Sehingga di sekitar batas tepi obyek hasil ekstraksi terlihat kasar baik secara visual maupun hasil pengukuran dengan Mean Squared Error (MSE) antara obyek hasil ekstraksi dengan ground truth. Untuk meningkatkan kualitas hasil ekstraksi objek, nilai threshold pada unknown region ditentukan melalui adaptive threshold yang diperoleh dengan mengaplikasikan algoritma Fuzzy C-Means (FCM). Pemilihan algoritma FCM karena dalam penelitian sebelumnya algoritma ini menunjukkan hasil yang lebih robust dibandingkan algoritma Otsu untuk mendapatkan nilai threshold yang optimal. Sedangkan untuk menghaluskan obyek di sekitar daerah batas tepi digunakan filter Discrete Cosine Transform (DCT) – 2D. Dari 10 obyek yang digunakan dan dievaluasi dengan MSE menunjukkan peningkatan rata-rata sebesar 31.55%. Namun pendekatan ini tidak begitu robust pada citra yang memiliki kemiripan warna. Penggabungan pendekatan ini dengan optimasi cost function dalam alpha region pada basis spectrum diharapkan mampu meningkatkan kinerja algoritma ekstraksi obyek pada penelitian selanjutnya. Kata kunci: Closed-form Solution, Algoritma Fuzzy C-Means, Discrete Cosine Transform-2D. Abstract The research is aimed to improve the quality of the extraction of the object in a single image resulted from frame’s fragmentation of sequential compressed video. The quality of the extracted objects with closed-form solution algorithm decreased due to some changes in the intensity values on the RGB channel. Thus, the extraction result around the boundary edges of objects visually seemed to be rough and when it was measured with the Mean Squared Error (MSE) beween the object extraction results with ground truth. To improve the quality of the extracted object, the threshold value on unknown region was determined by adaptive threshold obtained by applying the Fuzzy C-Means algorithm (FCM). FCM algorithm is chosen since in the previous research this algorithm gives more robust results than Otsu algorithm to obtain the optimal threshold value. Meanwhile, to eliminate noise around the border area, this research applies Discrete Cosine Transform (DCT) - 2D filters. The result of 10 objects used and evaluated with the MSE showed an average increase of 31.55%. However, this approach is not so robust to images having similar color. Combination of this approach with optimization of the cost function on the alpha region based on spectrum is expected improving the performance of object extraction algorithm for the next research. Key words: Closed-form Solution, Fuzzy C-Means Algorithm, Discrete Cosine Transform-2D
DESIGN OPTIMIZATION OF MICRO HYDRO TURBINE USING ARTIFICIAL PARTICLE SWARM OPTIMIZATION AND ARTIFICIAL NEURAL NETWORK Lie Jasa; Ratna Ika Putri; Ardyono Priyadi; Mauridhi Hery Purnomo
Jurnal Ilmiah Kursor Vol 7 No 3 (2014)
Publisher : Universitas Trunojoyo Madura

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DESIGN OPTIMIZATION OF MICRO HYDRO TURBINE USING ARTIFICIAL PARTICLE SWARM OPTIMIZATION AND ARTIFICIAL NEURAL NETWORK aLie Jasa, bRatna Ika Putri, cArdyono Priyadi, dMauridhi Hery Purnomo a,b,c,d Instrumentation, Measurement, and Power Systems Identification Laboratory Electrical Engineering Department, Institut Teknologi Sepuluh Nopember, Surabaya, Indonesia a Electrical Engineering Department, Udayana University, Bali, Indonesia b Electrical Engineering Department, Politeknik Negeri Malang, Malang, Indonesia. Email: liejasa@unud.ac.id Abstrak Turbin digunakan mengkonversi energy potensial menjadi energy kinetik. Kapasitas Energy yang dihasilkan dipengaruhi oleh sudu-sudu turbin yang dipasang pada tepi. Sudu turbin dirancang seorang ahli dengan sudut kelengkungan tertentu. Efisiensi dari turbin dipengaruhi oleh besarnya sudut, jumlah dan bentuk sudu. Algoritma PSO dapat digunakan untuk komputasi dan optimasi dari design turbin mikro hidro. Penelitian ini dilakukan dengan; Pertama, Formula design turbin dioptimasi dengan PSO. Kedua, Data hasil optimasi PSO diinputkan kedalam jaringan ANN. Ketiga, training dan testing terhadap simulasi jaringan ANN. Dan yang terakhir, Analisa kesalahanr dari jaringan ANN. Data PSO sebanyak 180 record, 144 digunakan untuk training dan sisanya 40 untuk testing. Hasil penelitian ini adalah MAE= 0.4237, MSE=0.3826, dan SSE=165.2654. Error training terendah didapatkan dengan algoritma pembelajaran trainlm. Kondisi ini membuktikan bahwa jaringan ANN mampu menghasilkan desain turbin yang optimal. Kata kunci: Turbin, PSO, ANN, Energi Abstract Turbines are used to convert potential energy into kinetic energy. The blades installed on the turbine edge influence the amount of energy generated. Turbine blades are designed expertly with specific curvature angles. The number, shape, and angle of the blades influence the turbine efficiency. The particle swarm optimization (PSO) algorithm can be used to design and optimize micro-hydro turbines. In this study, we first optimized the formula for turbine using PSO. Second, we input the PSO optimization data into an artificial neural network (ANN). Third, we performed ANN network simulation testing and training. Finally, we conducted ANN network error analysis. From the 180 PSO data records, 144 were used for training, and the remaining 40 were used for testing. The results of this study are as follows: MAE = 0.4237, MSE = 0.3826, and SSE = 165.2654. The lowest training error was achieved when using the trainlm learning algorithm. The results prove that the ANN network can be used for optimizing turbine designs. Keywords: Turbine, PSO, ANN, Energy
ADVANCE OPTIMIZATION OF ECONOMIC EMISSION DISPATCH BY PARTICLE SWARM OPTIMIZATION (PSO) USING CUBIC CRITERION FUNCTIONS AND VARIOUS PRICE PENALTY FACTORS Joko Pitono; Adi Soepriyanto; Mauridhi Hery Purnomo
Jurnal Ilmiah Kursor Vol 7 No 3 (2014)
Publisher : Universitas Trunojoyo Madura

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ADVANCE OPTIMIZATION OF ECONOMIC EMISSION DISPATCH BY PARTICLE SWARM OPTIMIZATION (PSO) USING CUBIC CRITERION FUNCTIONS AND VARIOUS PRICE PENALTY FACTORS a Joko Pitono, bAdi Soepriyanto, cMauridhi Hery Purnomo aDepartment of Electrical Engineering, PPPPTK/VEDC Malang b,cDepartment of Electrical Engineering, Sepuluh Nopember Institute of Technology, Surabaya Email: j_pitono@yahoo.com Abstract The classical economic dispatch problem could be solved based on single objective function of power system operation by minimizing the fuel cost. However, the single objective function is not sustainable because the environmental issues arise from the emissions generated by fossil-fueled thermal electric power plants. Various pollutants such as sulfur dioxide (SO2), nitrogen oxides (NOX) and carbon dioxide (CO2) affect environmental issues. The economy-environment dispatch problem has been generally solved by considering each objective separately or by applying Weighted Sum Method on both objectives. This paper formulates the solution of dispatch PSO method that considers the impact of various pollutants and various factors such as the price penalty Min-Max, MaxMax, and Average in solving multi-objective problems using cubic criterion function for the cost of fuel and emission values. Multi-objective functions method proposed in this research was validated using IEEE 30-bus systems with six generating units. The results of simulation using Min-Max penalty factor indicated less total fuel cost value compared to the simulation using Max-Max and Average penalty factor. In general, the comparison of Min-Max type= 100%, Max-Max type= 266.9%, and Average type= 191.8%; Max-Max penalty factor provided less emission value with comparison to Min-Max and Average penalty factors. In general, the comparison Max-Max type= 100%, Min-Max type= 102%, and Average type= 100.2% to ETSO while for ETNO and ETCO is not significantly different; Average penalty factor provided less fuel cost value compared to Max-Max and Average penalty factor. In general, the comparison of Average type= 100%, Min-Max type= 101.8%, and Max-Max type= 100.3%. Keywords: Economic-Emission Dispatch, Multi-Objective, Cubic Criterion Function, Price Penalty Factors, Particle Swarm Optimization.
IDENTIFIKASI SINYAL ELEKTRODE ENCHEPALO GRAPH UNTUK MENGGERAKKAN KURSOR MENGGUNAKAN TEKNIK SAMPLING DAN JARINGAN SYARAF TIRUAN Hindarto -; Moch. Hariadi; Mauridhi Hery Purnomo
Jurnal Ilmiah Kursor Vol 6 No 1 (2011)
Publisher : Universitas Trunojoyo Madura

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Abstract

This paper describe the application of backpropagation neural networks as classification and sampling technique (ST) for the extraction of features from the signal wave Electro Encephalo Graph (EEG). This research aims to develop a system that can recognize the EEG signal that is used to move the cursor. The data used is the EEG data which is IIIA dataset of BCI competition III (BCI Competition III 2003). This data contains data from three subjects: K3b, K6b and L1b. In this study, EEG signal data separated by the imagination of movement to the left, right, leg movements and tongue movements. Decision making has been carried out in two stages. In the first stage, TS is used to extract features from EEG signal data. This feature is as basic inputs in back propagation neural networks as a process of learning. This research used Back Propagation (20-20-10-5-1) and 90 data files EEG signal for the training process. During the identification process into four classes of EEG signal data files data files plus 60 into 150 EEG signal so that the EEG signal data file. The results obtained for the classification of these signals is 80% of the 150 files examined data signal to the process of mapping.
HIDDEN MARKOV MODELS BASED INDONESIAN VISEME MODEL FOR NATURAL SPEECH WITH AFFECTION Endang Setyati; Mauridhi Hery Purnomo; Surya Sumpeno; Joan Santoso
Jurnal Ilmiah Kursor Vol 8 No 3 (2016)
Publisher : Universitas Trunojoyo Madura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28961/kursor.v8i3.61

Abstract

In a communication using texts input, viseme (visual phonemes) is derived from a group of phonemes having similar visual appearances. Hidden Markov model (HMM) has been a popular mathematical approach for sequence classification such as speech recognition. For speech emotion recognition, a HMM is trained for each emotion and an unknown sample is classified according to the model which illustrate the derived feature sequence best. Viterbi algorithm, HMM is used for guessing the most possible state sequence of observable states. In this work, first stage, we defined system of an Indonesian viseme set and the associated mouth shapes, namely system of text input segmentation. The second stage, we defined a choice of one of affection type as input in the system. The last stage, we experimentally using Trigram HMMs for generating the viseme sequence to be used for synchronized mouth shape and lip movements. The whole system is interconnected in a sequence. The final system produced a viseme sequence for natural speech of Indonesian sentences with affection. We show through various experiments that the proposed, the results in about 82,19% relative improvement in classification accuracy.
CHAOTIC OSCILLATIONOFA THREE-BUS POWER SYSTEM MODEL USING ELMANNEURAL NETWORK I Made Ginarsa; Adi Soeprijanto; Mauridhi Hery Purnomo
Lontar Komputer : Jurnal Ilmiah Teknologi Informasi Vol. 4, No. 2 Agustus 2013
Publisher : Institute for Research and Community Services, Udayana University

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Abstract

Paper ini meneliti dan membahas secara mendalam mengenai osilasi chaotic pada sistem tenaga listrik.Dengan menggunakan sebuah three-bus pada sistem tenaga listrik, rute mungkin menyebabkan unjuk kerja chaotic sehingga dievaluasi, digambarkan serta dibahas dalam penelitian ini. Osilasi chaotic ini dimodelkan menggunakan Elmanneural network karena bentuknya yang sederhana dan juga melibatkan algoritmabackpropagation dengan adaptive learning rate dan momentumnya.Unjuk kerja learning rate dan momentumnya lebih baik dibandingkan jika tanpa momentumnya. Unjuk kerja chaotic dalam sistem tenaga listrik muncul karena sistem ini dioperasikan dalam mode critical. Unjuk kerja chaotic ini terdeteksi dengan munculnya sebuahchaotic attractordalam phase-plane trajectory.
Co-Authors Abdillah, Abid Famasya Adhi Dharma Wibawa Adhi Dharma Wibawa Adhi Dharma Wibawa, Adhi Dharma Adhi Kusmantoro Adi Soeprijanto Adi Soeprijanto Adi Soepriyanto Adi Sutanto Adri Gabriel Sooai Adriel Ferdianto Afandi, Acxel Derian Affan, Lazuardi Yaqub Agung Dewa Bagus Soetiono Agung Mega Iswara Agung Wicaksono Agus Dharma Agustinus Bimo Gumelar Ahmad Muslich Al Kindhi, Berlian Alamsyah Alamsyah - Alfiyan Alfiyan, Alfiyan Ali Sofyan Kholimi Amirullah Amirullah Amrul Faruq Ananto Mukti Wibowo Andi Setiawan Andreas Agung Kristanto, Andreas Agung Ardyono Pribadi Ardyono Priyadi Ardyono Priyadi Arham Arham, Arham Arif Muntasa Arifin Arifin Arik Kurniawati Aris Nasuha Aris Widayati Arman Jaya Arraziqi, Dwi Aryo Nugroho Atris Suyantohadi Atris Suyantohadi Atyanta Nika Rumaksari Atyanta. N. Rumaksari Bambang Purwahyudi Bambang Sujanarko Bambang Suprianto . Bandung Arry Sanjoyo Basuki, Setio Berlian Al Kindhi Bernaridho Hutabarat, Bernaridho Budi Setiyono Budiarti, Rizqi Putri Nourma Cahyadi, Billy Kelvianto Chastine Fatichah Choirina, Priska Darma Setiawan Putra Dedid Cahya Happyanto Dewi Nurdiyah Diah Puspito Wulandari Diana Purwitasari Djoko Purwanto Dwi F. Suyatno Eddy Satriyanto Effendy Hadi Sutanto Eka Dwi Nurcahya Eko M. Yuniarno Eko Mulyanto Eko Mulyanto Yuniarno Eko Mulyanto Yuniarno Elly Purwanti Endang Setyati Endang Sri Rahayu Endi Permata Era Purwanto Esther Irawati Setiawan Evi Septiana Pane Evi Septiana Pane, Evi Septiana F.X. Ferdinandus Fahmi Amiq Fanani, Nurul Zainal Farah Zakiyah Rahmanti Fath, Nifty Feby Artwodini Muqtadiroh Fendik Eko P Fujisawa, Kimiya Gigih Prabowo Glanny M.Christiaan Mangindaan Gregorius Satio Budhi Gunawan Gunawan Gunawan Gunawan H. Hammad, Jehad A. Hans Juwiantho Hardianto Wibowo Hasti Afianti Hendra Kusuma Hermawan, Norma Herti Miawarni Hidayatillah, Rumaisah Hindarto Husna, Farida Amila Hutama Harsono, Nathanael I Ketut Eddy Purnama I Ketut Edy Purnama I Made Gede Sunarya I Made Ginarsa I Nyoman Budiastra Ima Kurniastuti Imam Robandi Iman Fahruzi Indah Agustien Sirajudin Indar Sugiarto Ingrid Nurtanio Isa Hafidz Iwan Setiawan Jehad A. H. Hammad Joan Santoso Joko Pitono Joko Priambodo Juanita, Safitri Ketut Eddy Purnama Khairuddin Karim Khamid Khamid Khamid Khamid Kristian, Yosi Lailatul Husniah Laksana, Eka Purwa Lie Jasa Lilik Anifah Lukman Zaman Lystianingrum, Vita Makoto Chiba Margareta Rinastiti Margo Pujiantara Marselin Jamlaay Marsetio Pramono Meidhy Panginda Saputra Moch Hariadi Moch. Hariadi Moch. Iskandar Riansyah Mochamad Ashari Mochamad Hariadi Mochammad Facta Mochammad Hariadi Moh. Aries Syufagi Mohammad Arie Reza Muhamad Ashari Muhamad Haddin Muhammad Nur Alamsyah Muhammad Reza Pahlawan Muhammad Rivai Muhtadin Mukhammad Aris Muldi Yuhendri Mulyanto, Edy Nazarrudin, Ahmad Ricky Nova Eka Budiyanta Nova Rijati Nugroho, Supeno Nugroho, Supeno Mardi S. Nur Kasan, Nur Nurul Fadillah Nurul Zainal Fanani Oddy Virgantara Putra Ontoseno Penangsang Pratama, Afis Asryullah Priambodo, Joko Prima Kristalina Purnawan, I Ketut Adi Purwadi Agus Darwito Putra Wisnu AS R Dimas Adityo Rachmad Setiawan Radi Radi Rafly Azmi Ulya, Amik Rahmat Rahmat Rahmat Syam Raihan, Muhammad Ratna Ika Putri Rika Rokhana Rima Tri Wahyuningrum Rima Tri Wahyuningrum Riris Diana Rachmayanti Rokhana, Rika Rumaisah Hidayatillah Ruri Suko Basuki Rusmono Yulianto Saidah Saidah Saputra, Daniel Gamaliel Sartana, Bruri Trya SATO Yukihiko Setiawan, Esther Setijadi, Eko Sidharta, Bayu Adjie Sihombing, Drigo Alexander Sirait, Rummi Santi Rama Siti Rochimah Soebagio Soebagio Soebagio Soebagio Soebagio Soebagio Soebagio Soebagio Soetiono, Agung Dewa Bagus Subagio subagio Subuh Isnur Haryudo Sugiyanto - Sujono Sujono Sujono Sulistyono, Marcelinus Yosep Teguh Sumadi, Fauzi Dwi Setiawan Supeno M. S. Nugroho Supeno Mardi Supeno Mardi S. Nugroho Supeno Mardi Susiki Nugroho, Supeno Mardi Surya Sumpeno Sutedjo Sutedjo Syafaah, Lailis Syaiful Imron Tita Karlita Tita Karlita Tri Arief Sardjono Tsuyoshi Usagawa, Tsuyoshi Ulla Delfana Rosiani Umar Umar Vita Lystianingrum Widodo Budiharto Wijayanti . Wiratmoko Yuwono Wiwik Anggraeni Wridhasari Hayuningtyas Yani Prabowo Yodik Iwan Herlambang Yosi Kristian Yoyon Kusnendar Suprapto Yuhana, Umi Laili Yulianto Tejo Putranto Yuni Yamasari Yuniarno, Eko M. Yusron rijal Zaimah Permatasari Zaman, Lukman