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All Journal JTEV (Jurnal Teknik Elektro dan Vokasional TELKOMNIKA (Telecommunication Computing Electronics and Control) Jurnal Ilmu Komputer dan Agri-Informatika Teknik dan Ilmu Komputer Journal Industrial Servicess Setrum : Sistem Kendali-Tenaga-elektronika-telekomunikasi-komputer ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika The Spirit of Society Journal : International Journal of Society Development and Engagement Techne : Jurnal Ilmiah Elektroteknika Jurnal Rekayasa Hijau MIND (Multimedia Artificial Intelligent Networking Database) Journal TESLA: Jurnal Teknik Elektro Jambura Journal of Electrical and Electronics Engineering Indonesian Journal of Electrical Engineering and Computer Science REKA ELKOMIKA: Jurnal Pengabdian kepada Masyarakat Community Empowerment Jurnal Pengabdian Teknologi Tepat Guna AKM: Aksi Kepada Masyarakat Jurnal Atma Inovasia Engagement: Jurnal Pengabdian Kepada Masyarakat JuTISI (Jurnal Teknik Informatika dan Sistem Informasi) SNTE Journal of Innovation and Community Engagement
Erwani Merry Sartika
Program Studi Teknik Elektro, Universitas Kristen Maranatha Bandung
Religion Agriculture, Biological Sciences & Forestry Arts Humanities Automotive Engineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Mechanical Engineering Public Health Social Sciences Transportation Other

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Perbandingan Deteksi Letak Polip pada Citra Colonoscopy menggunakan CNN dengan Arsitektur RetinaNet JONATHAN, RONALDO DAVE; HASUGIAN, MEILAN JIMMY; SARTIKA, ERWANI MERRY
ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika Vol 10, No 4: Published October 2022
Publisher : Institut Teknologi Nasional, Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26760/elkomika.v10i4.946

Abstract

ABSTRAKPenyakit kanker kolorektal diawali munculnya polip pada usus besar yang dapat berubah menjadi tumor ganas dan menimbulkan kanker. Sehingga diperlukan screening terhadap usus besar menggunakan colonoscopy. Menurut penelitian sekitar 26% polip terlewat saat prosedur colonoscopy. Pada penelitian ini dilakukan implementasi Convolutional Neural Network (CNN) dengan arsitektur RetinaNet untuk mendeteksi letak polip pada citra colonoscopy. Perbandingan dilakukan pada 3 jenis arsitektur yaitu ResNet-50, ResNet-101, dan ResNet-152 sebagai backbone pada arsitektur RetinaNet. Model yang terbaik berdasarkan metrik Intersection over Union (IoU) adalah model RetinaNet (Backbone = ResNet-50) tanpa data augmentation dengan nilai 0.8415. Sedangkan model yang terbaik berdasarkan metrik Average Precision (AP) adalah RetinaNet (Backbone = ResNet-101) dengan data augmentation dengan nilai AP25 = 0.9308, AP50 =0.9039, AP75 = 0.6985.Kata kunci: polip, colonoscopy, Convolutional Neural Network (CNN), RetinaNet ABSTRACTColorectal cancer always begins with the appearance of polyps in the colon which can turn into malignant tumors and cause cancer. Therefore, it is necessary to screen the large intestine using colonoscopy. However, according to studies, about 26% of polyps are missed during colonoscopy procedures. In this study, a Convolutional Neural Network (CNN) with RetinaNet architecture was implemented to detect the location of polyps in colonoscopy images. Comparisons were made on 3 types of architecture, namely ResNet-50, ResNet-101, and ResNet-152. From the evaluation results, the best model based on the Intersection over Union (IoU) metric is the RetinaNet model (Backbone = ResNet-50) without augmentation data with a value of 0.8415. While the best model based on the Average Precision (AP) metric is RetinaNet (Backbone = ResNet-101) with data augmentation with values AP25 = 0.9308, AP50 = 0.9039, AP75 = 0.6985.Keywords: polyp, colonoscopy, Convolutional Neural Network (CNN), RetinaNet
Simulasi Sistem Otomasi Load Shedding menggunakan Prediksi Beban SARTIKA, ERWANI MERRY; SARJONO, RUDI; RESTIANTO, REINALDO STEVEN
ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika Vol 7, No 1: Published January 2019
Publisher : Institut Teknologi Nasional, Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26760/elkomika.v7i1.180

Abstract

ABSTRAKSimulator penggunaan energi listrik sangat membantu dalam perencanaan pasokan listrik secara terus menerus atau perlu pemadaman bila terjadi gangguan. Agar kinerja pembangkit dapat kembali normal, bertahap, dan terencana akibat mengalami gangguan, maka digunakan metoda Load Shedding. Sistem otomasi dibutuhkan untuk merealisasikan metoda Load Shedding, dan melalui simulator dapat mengurangi resiko terhadap kerusakan bila langsung diimplementasikan. PLC digunakan untuk memprediksi beban saat load shedding, sedangkan SCADA digunakan untuk menampilkan prioritas dan status beban. Load shedding 1 adalah tindakan pelepasan beban bila pada salah satu genset mengalami gangguan, sedangkan Load shedding 2 bila pada kedua genset mengalami gangguan. Simulasi sistem load shedding 1 dan 2 berhasil dilakukan pelepasan beban secara otomatis. Setelah pelepasan beban, kapasitas beban yang ditanggung genset sesuai dengan prediksi dari PLC. Terdapat perbedaan hasil antara daya yang diprediksi secara perhitungan dan daya terukur, kemungkinan disebabkan beban masih belum steady saat data diambil.Kata kunci: Otomasi, Simulator, Sistem Load shedding, SCADA, PLC ABSTRACTSimulator of the use of electrical energy is very helpful in planning electricity supply continuously or needs to be suppressed if a disturbance occurs. In order for the generator performance to return to normal, gradual, and planned due to interference, the Load Shedding method is used. Automation systems are needed to realize the Load Shedding method, and through simulators can reduce the risk of damage if implemented immediately. PLC was used to predict load during load shedding, while SCADA was used to display priority and load status. Load shedding 1 was a load release action if one of the generator sets was disrupted, while Load shedding 2 if in both gensets were disrupted. Load system simulation of shedding 1 and 2 was successfully released by load automatically. After the load was released, the load capacity borne by the generator was in accordance with the predictions of the PLC., the load capacity borne by the generator was in accordance with the predictions of the PLC. There was a difference in results between the predicted power and measured power, possibly because the load was stillnot steady when the data was taken. Keywords: Automation, Simulator, Load Shedding System, SCADA, PLC
Pengontrolan Kecepatan Rotor BLDC UAV Berdasarkan Hasil Identifikasi menggunakan Metode Regresi SARTIKA,, ERWANI MERRY; MULIADY, MULIADY; SARJONO, RUDI; YUVENS, VINCENSIUS
ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika Vol 9, No 1: Published January 2021
Publisher : Institut Teknologi Nasional, Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26760/elkomika.v9i1.114

Abstract

ABSTRAKPenggunaan dan aplikasi motor Brushless DC cukup banyak di industri, namun masih cukup sulit untuk mengendalikannya. Pada penelitian sebelumnya telah dipelajari karakteristik parameter motor BLDC UAV menggunakan Metode Regresi untuk mengetahui hubungan antar parameter yang ada dalam sistem motor BLDC. Sinyal PWM merupakan salah satu yang menentukan kecepatan rotor dari BLDC. Pada penelitian ini identifikasi model motor BLDC hasil eksperimen digunakan untuk mengendalikan kecepatan rotor secara open loop dan closed loop. Pengendalian secara open loop menggunakan invers model hasil Metode Regresi menghasilkan kesalahan maksimal 3,77% untuk kecepatan rotor lebih dari 3500 rpm. Sedangkan pada pengendalian secara closed loop menggunakan model hasil Metode Regresi dan pengendali PI (Proportional Integral) dengan Kp = 1 dan Ki = 5, secara simulasi menghasilkan kecepatan rotor dengan settling time 1 detik.Kata kunci: motor BLDC, kecepatan rotor, identifikasi model, pengendalian ABSTRACTThe use and application of Brushless DC motors is quite a lot in the industry, but it is still quite difficult to control. In previous research the characteristics of UAV BLDC motor parameters using the regression method to determine the relation of the parameters in the BLDC motor system. The PWM signal is one that determines the rotor speed of the BLDC. In this study the identification of the BLDC motor model experimental results is used to control the rotor speed in open loop and closed loop. Control with open loop using the inverse model of the Regression Method produces a maximum error of 3.77% for rotor speeds of more than 3500 rpm. Whereas control with closed loop using the model of the Regression Method and PI (Proportional Integral) controller with Kp = 1 and Ki = 5, the simulation produces rotor speed with a settling time of 1 second.Keywords: BLDC motor, rotor speed, model identification, control
Implementasi Sensor IMU untuk mengetahui Sudut Elevasi Kendaraan menggunakan Metode Least Square SARTIKA, ERWANI MERRY; GANY, AUDYATI; YUVENS, VINCENSIUS
ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika Vol 8, No 2: Published May 2020
Publisher : Institut Teknologi Nasional, Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26760/elkomika.v8i2.301

Abstract

ABSTRAKKemiringan jalan menyebabkan pengendara sepeda motor lebih berhati-hati dalam mengendarai kendaraannya. Selain untuk keamanan, sudut elevasi jalan dapat mempengaruhi dalam pengendalian kendaraan sehingga dapat lebih menghemat energi. Pada paper ini sensor Inertial Measurement Unit (IMU) digunakan untuk mengetahui kemiringan kendaraan sepeda motor (naik/turun dan condong kiri/kanan). Dalam perancangannya beberapa data akselerasi dari sensor accelerometer IMU diolah dengan regresi sehingga diperoleh persamaan regresi yang kemudian digunakan untuk memperbanyak data sehingga data tersebut dapat digunakan untuk prediksi model antara 3 input nilai akselerasi dan 2 output nilai kemiringan sudut kendaraan. Prediksi model berhasil dengan indentifikasi menggunakan metode Least Square. Dari data pengamatan diperoleh bahwa rata-rata kesalahan absolut untuk kemiringan naik/turun dan condong kiri/kanan antara 5 o s/d 7 o, namun belum berhasil untuk sudut yang besar (70 o s/d 90 o).Kata kunci: IMU, accelerometer, sudut elevasi, Arduino, Least Square ABSTRACTThe slope of the road leads to awareness of motorcyclists ini riding their motorcycle addition to safety, the elevation angle of the road can affect vehicle control so that it can save more energy. In this paper the IMU sensor is used to determine the slope of a motorcycle (up / down and leaning left / right). In the design of some acceleration data from the IMU accelerometer sensor is processed so that the regression equation is obtained. The regression equation is used to generate the data to predict the model 3 input acceleration value and 2 output slope value of the vehicle. Model prediction was successful by identification using the Least Square method. Obtained from observational data that the average absolute error for the slope up / down and leaning left / right between 5 o to 7 o, but has not been successful for wide angles (70 o to 90 o).Keywords: IMU, accelerometer, elevation angle, Arduino, Least Square
Penerapan Algoritma Gradient Boosting pada Sinyal EEG sebagai Pengendali Kursi Roda DARMAWAN, GERARLDO INDRA; SARTIKA, ERWANI MERRY; CHANDRA, ERIC; BR. PASARIBU, NOVIE THERESIA; ANDRIANTO, HERI
ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika Vol 12, No 2: Published April 2024
Publisher : Institut Teknologi Nasional, Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26760/elkomika.v12i2.541

Abstract

ABSTRAKBerdasarkan data Badan Penduduk Statistik (BPS) tahun 2019, jumlah penduduk lanjut usia yaitu 23,4 juta dan 26,2% diantaranya mengalami keluhan kesehatan. Beberapa keluhan kesehatan yang dialami berkaitan dengan mobilitas. Kursi roda merupakan salah satu alat bantu yang kerap digunakan oleh penyandang disabilitas atau seseorang yang memiliki keterbatasan mobilitas. Brain-Computer Interface digunakan sebagai sistem kendali kursi roda menggunakan Raspberry Pi berdasarkan masukan berupa sinyal EEG. Sinyal EEG tersebut digunakan untuk memprediksi perintah otak dan rangsangan gerakan bola mata dengan menerapkan algoritma gradient boosting. Hasil prediksi machine learning merupakan set point untuk menjalankan motor DC sehingga kursi roda dapat bergerak berdasarkan hasil prediksi. Sistem BCI pada kursi roda telah dilakukan uji coba, integrasi BCI pada kursi roda berhasil diterapkan dengan persentase keberhasilan sebesar 60%.Kata kunci: BCI, Machine Learning, Wheelchair Control. ABSTRACTAccording to the Badan Penduduk Statistik 2019, the number of elderly population is 23.4 million, and 26.2% of them experience health complaints. Some of these complaints are related to mobility. Wheelchairs are one of the commonly used aids for people with disabilities or mobility limitations. The Brain-Computer Interface (BCI) is employed as a control system for a wheelchair, utilizing a Raspberry Pi, which operates based on input signals derived from EEG (Electroencephalogram) signals. These EEG signals are used to predict brain commands and stimulate eye movement through the application of gradient boosting algorithms. The machine learning prediction results are the set points to run the DC motor so that the wheelchair can move based on the prediction results. The BCI system for wheelchairs has been tested, and the integration of BCI into wheelchairs has been successfully applied with a 60% success rate.Keywords: BCI, Machine Learning, Wheelchair Control.
Kinerja Low-Cost Chlorophyll Meter pada Pengukuraan Indeks Klorofil Daun Srikaya Jumbo Hangkawidjaja, Aan Darmawan; Sartika, Erwani Merry; Andrianto, Heri; Pintu Batu, Michael Cladius Poltak
Jurnal Ilmu Komputer dan Agri-Informatika Vol. 12 No. 1 (2025)
Publisher : Sekolah Sains Data, Matematika, dan Informatika. Institut Pertanian Bogor

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/jika.12.1.13-24

Abstract

One of the factors affecting crop yields is the condition of nutrients in plants. The nutrient condition, particularly nitrogen, can be identified through the chlorophyll content in plant leaves, which can be measured using a chlorophyll meter. However, current chlorophyll meters are still expensive and have limitations such as limited data storage, with data being lost if there is no power supply. In this paper, an ESP32-based chlorophyll meter was developed to store chlorophyll content index (CCI) data in a memory module, enabling the data to be used for nitrogen status analysis. The plant used for chlorophyll measurement in this study was the jumbo sugar apple plant. The research methods included literature reviews from previous studies, design, implementation, and performance testing of the ESP32-based chlorophyll meter compared to the TYS-A chlorophyll meter in measuring the chlorophyll content of jumbo sugar apple leaves. The test results showed a determination coefficient (R²) of 0.9517 between the TYS-A values and those of the ESP32-based chlorophyll meter, indicating a significant correlation. The ESP32-based chlorophyll meter functioned effectively, being capable of measuring the chlorophyll index of jumbo sugar apple plant and storing the chlorophyll index data in a memory module. The ESP32-based chlorophyll meter can serve as an affordable alternative to the TYS-A chlorophyll meter.
Pemanfaatan Tools AI dalam Pembuatan Materi Pengajaran bagi Guru- Guru di BPPK Bandung Sartika, Erwani Merry; Ratnadewi; Heri Andrianto; Agus Prijono; Aan Darmawan; Yohana Susanthi; Anthonius Chandra
Jurnal Atma Inovasia Vol. 4 No. 4 (2024)
Publisher : Lembaga Penelitian dan Pengabdian pada Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24002/jai.v4i4.9399

Abstract

Pendidik seperti guru perlu mengikuti perkembangan teknologi, namun juga tetap menginspirasi siswa agar teknologi dapat digunakan untuk tujuan positif dan produktif. Teknologi kecerdasan buatan (AI) saat ini banyak digunakan untuk membantu pendidik dalam mengembangkan materi pembelajaran. Pendekatan metode partisipatif yaitu masyarakat terlibat aktif dalam mengidentifikasi dan menyelesaikan masalah berupa kebutuhan dari guru-guru di BPPK untuk dapat mengembangkan diri dengan mengikuti workshop tools AI ini. Hasil evaluasi menunjukkan bahwa 84% peserta dapat menyimak dan mengikuti pelatihan berupa workshop yang melibatkan peserta secara aktif dalam diskusi, praktik, dan pengembangan keterampilan secara langsung. Pengembangan metode pengabdian diperlukan sehingga guru-guru dapat mendapat mempelajari dan mempraktikkan materi yang diberikan dengan lebih baik.
PENINGKATAN KEMAMPUAN PEMBUATAN PRESENTASI MENGGUNAKAN GENERATIVE AI BAGI GURU-GURU DI BPPK BANDUNG Sartika, Erwani Merry; Novie Theresia Br. Pasaribu; Daniel Setiadikarunia; Judea Janoto Jarden; Riko Arlando Saragih; Herawati Yusuf; Elia Moses
Jurnal Atma Inovasia Vol. 4 No. 5 (2024)
Publisher : Lembaga Penelitian dan Pengabdian pada Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24002/jai.v4i5.9400

Abstract

Generative IA hasil dari ChatGPT digunakan untuk membuat presentasi menjadi semakin menarik dalam pengajaran guru-guru menjadi tujuan dari pengabdian ini. Peningkatan kemampuan pembuatan presentasi menggunakan metode service learning dengan dukungan asisten dirancang agar langkah-langkah generative AI yang harus dilakukan dapat terpantau dengan baik. dosen-dosen memperdalam empati, keterlibatan sosial, dan memberikan kontribusi yang bermakna bagi guru-guru. Selain itu pemanfaatan tools AI perlu divalidasi oleh guru-guru terkait kebenaran semua informasi yang diberikan oleh AI. Pelatihan lanjutan merupakan salah satu permintaan dari peserta dan tugas proyek menjadi tindak lanjut pengawasan penerapan materi pelatihan pemanfaatan tools AI bagi guru-guru BPPK.
Rancang Bangun Sistem Latihan Tekanan Lidah Pasaribu, Novie Theresia; Sartika, Erwani Merry; Darmanto, Christopher Prasetya; Renaldy, Derry; Lin, Che Wei; Setiawan, Febryan
Jambura Journal of Electrical and Electronics Engineering Vol 5, No 1 (2023): Januari - Juni 2023
Publisher : Electrical Engineering Department Faculty of Engineering State University of Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/jjeee.v5i1.17041

Abstract

Terapi gerakan lidah secara rutin dengan stimulasi ujung syaraf bisa digunakan sebagai alat bantu terapi bagi pasien untuk penyakit stroke, dysphasia dan sleep apnea. Pada penelitian awal ini akan didesain rancang bangun Sistem Latihan Tekanan Lidah (LTL) dengan menggunakan alat LTL yang dirancang dengan menggunakan sensor tekanan Force Sensing Resistor (FSR) untuk memfasilitasi gerakan latihan lidah yang terdiri dari Tongue Force, Tongue Slide, dan Tongue Press. Pilihan jenis gerakan latihan lidah, panduan dan hasil latihan gerakan lidah yang dilakukan akan ditampilkan pada aplikasi smartphone. Simpulan yang didapat dari penelitian ini adalah Sistem LTL telah berhasil direalisasikan dengan sensor FSR, dari pembacaan nilai sensor tekanan pada Arduino dan smartphone terdapat delay rata-rata 1 detik. Besar tekanan lidah pada gerakan Tongue Force, Tongue Slide, dan Tongue Press sebesar 0-730 Gram-force. Pada Gerakan Tongue Slide ada perubaan besaran tekanan pada Sensor-1 dan Sensor-2, dikarenakan ada gerakan lidah kearah belakang. Berbeda dengan gerakan Tongue Press dan Tounge Force yang hanya mempengaruhi pada Sensor-1 saja.Routine tongue movement therapy with nerve tip stimulation can be used as a therapeutic aid for patients for stroke, dysphasia and sleep apnea. In this initial research, the design of the Tongue Pressure Training System (LTL) will be designed using an LTL tool designed using a Force Sensing Resistor (FSR) pressure sensor to facilitate tongue exercise movements consisting of Tongue Force, Tongue Slide, and Tongue Press. A selection of types of tongue exercise movements, guides and results of tongue movement exercises performed will be displayed on the smartphone application. The results obtained from this study are the LTL system which is realized from the reading of the pressure sensor value on the smartphone display, there is an average delay of 1 second so that there is a large difference in pressure readings on Arduino and smartphones. The amount of tongue pressure when performing Tongue Force, Tongue Slide, and Tongue Press movements has a pressure reading value of 0-700 Gram-force. In the Tongue Slide Movement, there is a change in the amount of pressure on sensor-1 and sensor-2, because the movement requires the tongue to move. In contrast to the Tongue Press and Tounge Force movements which focus more on pressure in sensor-1.
Perancangan Aplikasi Monitoring Latihan Tekanan Lidah berbasis Android & Web Pasaribu, Novie Theresia; Renaldy, Derry; Sartika, Erwani Merry; Che, Wei Lin; Setiawan, Febryan
Jurnal Teknik Informatika dan Sistem Informasi Vol 10 No 2 (2024): JuTISI
Publisher : Maranatha University Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28932/jutisi.v10i2.8868

Abstract

The tongue is part of the muscular organs that are essential in the oral (mouth) and maxillofacial systems (jaw, neck, and face). By doing tongue movement exercises can help therapy patients with certain diseases, such as sleep apnea. This research will design and develop LTL applications based on Android and the Web using LTL tools that have been designed by Novie et al. Android-based applications are designed to help monitor the results of FSR sensor output from LTL devices from the user side, and Web-based applications are designed to monitor the progress of the LTL process that has been carried out from the side of medical personnel. The types of tongue exercise movements used in this research are Tongue Slide-1, Tongue Slide-2, and Tongue Press. The Android application will show patient identity data, tongue pressure reading data, and movement repetition data. The Android LTL application design that has been successfully realized presents features to monitor the results of tongue pressure exercise readings. The subjective test results of the appearance and ease of LTL android and LTL web applications get a good assessment because all assessments are in the index of 86.3%-92.5%. Meanwhile, the results of the experimental scenario for LTL System Testing show that the average tongue pressure of all respondents carried out in two experiments for tongue press movement, tongue slide-1 movement, and tongue slide-2 movement, above the set threshold limit of above 500 gf. Further research into experimental scenarios and the use of this application can be applied to real patients.
Co-Authors AAN DARMAWAN Aan Darmawan Aan Darmawan Hangkawidjaj Aan Darmawan Hangkawidjaja Agus Prijon Agus Prijono Agus Prijono Alfian Alfian Amadeus, Clarence Annisa Maizano Anthonius Chandra Arief Darmawan Ariesa Pandanwangi Arvin Ezekiel Denri Utama Arvin Ezekiel Denri Utama AUDYATI GANY Audyati Gany Audyati Gany Audyati Gany, Audyati Chandra, Eric Che, Wei Lin CHRISOPHRAS, HAZEL XARIS Clarence Amadeus Daniel Setiadikarunia Darmanto, Christopher Prasetya DARMAWAN, GERARLDO INDRA Dido Hardinanto Ginting Diki Dwi Saputra Dimitri Jeremy Dion Melvern Siswanto Elia Moses Elizabeth Wianto, Elizabeth Evan Adrian Adhi Giri Shaffaat AL Muttaqin GUNAWAN, REYNALDY FELICIUS HALIM, CHRISENDY Hangkawidjaja, Aan Darmawan HASUGIAN, MEILAN JIMMY Herawati Ys Herawati Yusuf Herawati Yusuf Herawati Yusuf Heri Andrianto I Nengah Agus Mulia Adnyana I Wayan Sukadana Ida Ida Ida, Ida Indra Maulidin JAYA, WILLIAM EKA Jeffrey Christopher Jeremy Jonathan Jeremy, Dimitri Jimmy Gozali JONATHAN, RONALDO DAVE Judea Janoto Jarden Lesmana, Cindrawati Lin, Che Wei LIN, CHE-WEI M, Kevin Reynaldo Markus Tanubrata Markus Tanubrata Markus Tanubrata Meilan Jimmy Hasugian Moses, Elia Muliady, Muliady Nathaniel Pius Winata Nicolaus Cornellius Novie Theresia Br. Pasaribu Novie Theresia Br. Pasaribu Nugroho, Vincensius Olga Catherina Pattipawaej Pasaribu, Novie Theresia Patrick Fellipe Army Pintu Batu, Michael Cladius Poltak Rainisa Maini Heryanto Ratnadewi Ratnadewi . Renaldy, Derry RESTIANTO, REINALDO STEVEN RESTIANTO, REINALDO STEVEN Reynaldy Felicius Gunawan Richard Setiawan Riko Arlando Riko Arlando Saragih Rudy Wawolumaja Santoso Santoso SARJONO, RUDI SARJONO, RUDI SETIAWAN, FEBRIAN Setiawan, Febryan Siti Zubaidah Sri Wahono T. Rudi Sarjono T. Rudi Sarjono T. Rudy Sarjono Tara Anggada Putra Tio Dewantho Sunoto Utama, Arvin Ezekiel Denri VIERI CANDHYA WIGAYHA Vieri Candhya Wigayha Vincensius Nugroho Vincent Utama Wahono, Sri Winda Halim Wulan Sallydri Santoso Yehuda Njuah Sectio Cibro Yeremia Timotius Yohana Susanthi Yulianti Talar YUVENS, VINCENSIUS Zefanya, Kevyn Vicy