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Fitur Length Of Edge Dan Moment Invarian Untuk Gesture Recognition Dengan Menggunakan Kinect Untuk Kontrol Lampu MP, Rekyan Regasari; Setiawan, Budi Darma; Arwani, Issa
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 2, No 1 (2015)
Publisher : Fakultas Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (805.673 KB)

Abstract

AbstrakTeknologi Kinect adalah teknologi yang dikembangkan untuk game. Kinect memungkinkan pemain game mengontrol permainan dengan menggunakan gerakan dan suara. Hal ini dikarenakan di dalam Kinect terdapat 3 hardware yang bekerja bersama-sama. Tiga hardware tersebut yaitu color VGA video camera, sensor kedalaman, dan multi array microphones. Karena itu, penelitian ini mencoba mengembangkan sensor Kinect untuk keperluan mendeteksi telapak tangan dan gesturnya untuk digunakan sebagai kontrol lampu. Hal ini dilakukan dengan menambahkan beberapa proses pengolahan citra. Pengenalan telapak tangan, menggunakan sensor VGA camera dan depth camera dalam Kinect. Ketika seorang pengguna menjulurkan tangannya kearah sensor, kemudian mengangkat jarinya maka program akan bereaksi. Jika 2 jari yang diangkat maka program akan mengaktifkan saklar padam. Sedangkan jika 5 jari yang diangkat, maka program akan mengaktifkan saklar hidup. Dalam penelitian ini ada 2 fitur yang digunakan dan dibandingkan hasilnya. Fitur yang digunakan adalah fitur Moment Invariant dan Length of Edge. Hasil lebih baik diberikan jika pengenalan dilakukan dengan menggunakan Length of Edge. Dari seluruh data uji yang dipakai, untuk pengenalan dengan menggunakan fitur Length of Edge, akurasi maksimal diperoleh sebesar 100%, sedangkan  dengan menggunakan fitur Moment Invariant, akurasi maksimal diperoleh sebesar 80%.Kata kunci: Moment Invarian, Length of Edge, gesture telapak tanganAbstractKinect is a technology developed for game. Kinect allows players to control game play by using movement and sound. This is because Kinect has 3 hardware that work together. The three hardware are VGA video camera, depth sensor and multi-array microphones. Therefore, this study attempts to use Kinect sensor for detecting the palms gestures and use them as a light control. This is done by adding some image processing technique. The palms gesture detection is done by using the VGA camera and depth camera in Kinect Sensor. When a user sticking his hand out and raise his fingers, then program will gives response. If 2 fingers are raised, program will activate off switch, while if 5 fingers are raised, program will activate on switch. There are two features are used in this study, and the results are compared. The features are Moment Invariant and Length of Edge. Better results given by recognition using the Length of Edge. From all the test data used, recognition using Length of Edge give 100% accuracy, while recognition using Moment Invariant features, give 80% in acuracy.Keywords: Moment Invarian, Length of Edge, palm gesture
Movie recommender systems using hybrid model based on graphs with co-rated, genre, and closed caption features Adikara, Putra Pandu; Sari, Yuita Arum; Adinugroho, Sigit; Setiawan, Budi Darma
Register: Jurnal Ilmiah Teknologi Sistem Informasi Vol 7, No 1 (2021): January
Publisher : Information Systems - Universitas Pesantren Tinggi Darul Ulum

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26594/register.v7i1.2081

Abstract

A movie recommendation is a long-standing challenge. Figuring out the viewer’s interest in movies is still a problem since a huge number of movies are released in no time. In the meantime, people cannot enjoy all available new releases or unseen movies due to their limited time. They also still need to choose which movies to watch when they have spare time. This situation is not good for the movie business too. In order to satisfy people in choosing what movies to watch and to boost movie sales, a system that can recommend suitable movies is required, either unseen in the past or new releases. This paper focuses on the hybrid approach, a combination of content-based and collaborative filtering, using a graph-based model. This hybrid approach is proposed to overcome the drawbacks of combination in the content-based and collaborative filtering. The graph database, Neo4j is used to store the collaborative features, such as movies with its genres, and ratings. Since the movie’s closed caption is rarely considered to be used in a recommendation, the proposed method evaluates the impact of using this syntactic feature. From the early test, the combination of collaborative filtering and content-based using closed caption gives a slightly better result than without closed caption, especially in finding similar movies such as sequel or prequel.
Design and Implementation of Earth Image Classification Using Unmanned Aerial Vehicle Barlian Henryranu Prasetio; Ahmad Afif Supianto; Gembong Edhi Setiawan; Budi Darma Setiawan; Imam Cholissodin; Sabriansyah Rizkiqa Akbar
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 13, No 3: September 2015
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v13i3.1786

Abstract

Research in the field of image classification has been widely applied and developed, especially in the field of satellite imagery. Image classification is the process of grouping the pixels in an image into a number of classes, so that each class can describe an entity with certain characteristics. The research aims to build software that can perform the classification of earth image results from UAV (Unmanned Aerial Vehicle) monitoring. The Image converted into YUV format then classified using Fuzzy Support Vector Machine (FSVM). This research designed elements that UAVs will be used for monitoring as follows: (1) the control station, which designed the software on a computer that is used to send or receive data, and display the data in graphical form, (2) payload, using the camera to capture images and send to the control station, (3) communication system using TCP/IP protocol, and (4) UAV, using X650 quadcopter products from xaircraft. All of data can be received if it is sent by several segmented package into smaller parts. The results of image classification, the image of the monitoring carried out on the UAV sized 256 x 256 pixels with a total number of 450 training data size. It is 16x16 pixel image data. Tests performed to classify the image into 3 classes, namely agricultural area, residential area, and water area. The highest accuracy value of 77.69% obtained by the number of training data as much as 375.
Extreme Learning Machine Weights Optimization Using Genetic Algorithm In Electrical Load Forecasting Vina Meilia; Budi Darma Setiawan; Nurudin Santoso
Journal of Information Technology and Computer Science Vol. 3 No. 1: June 2018
Publisher : Faculty of Computer Science (FILKOM) Brawijaya University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1812.596 KB) | DOI: 10.25126/jitecs.20183154

Abstract

The growth of electrical consumers in Indonesia continues to increases every year, but it is not matched by the provision of adequate infrastructure that available. This causes the available electrical capacity can't fulfill the demand for electricity.  In this study, a smart computing system is build to solves the problem. Electrical load data per hour is being used as an input to do the electrical load forecasting with Extreme Learning Machine method. Extreme Learning Machine method uses random input weight within range -1 to 1. Before the electric load prediction process runs, genetic algorithms first optimizing the input weight.  According to the test results with weight optimization, MAPE average error rate is 0.799% while without weight optimization the rate rise to 1.1807%. Thus this study implies that Extreme Learning Machine (ELM) method with weight optimization using Genetics Algorithm (GA) can be used in electrical load forecasting problem and give better prediction result
Comparative Evaluation of Usability between QWERTY-Based Arabic and Non-QWERTY-Based Arabic Keyboard Layout: Empirical Evidence Ismiarta Aknuranda; Almira Syawli; Budi Darma Setiawan
Journal of Information Technology and Computer Science Vol. 5 No. 2: August 2020
Publisher : Faculty of Computer Science (FILKOM) Brawijaya University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1422.696 KB) | DOI: 10.25126/jitecs.202052199

Abstract

QWERTY-based Arabic keyboard layouts have been in existence in order to assist QWERTY users in Arabic typing. However, there was lack of empirical evidence presenting the comparative usability of this layout and the common non-QWERTY-based Arabic keyboard layout. This study examined the usability of a QWERTY-based Arabic keyboard layout (QB) and the common non-QWERTY-based Arabic keyboard layout (NQB) from the perspective of QWERTY users, and compared the evaluation results between the two layouts. After experiments using within-subjects and between-subjects designs, the results showed that QB is significantly better in efficiency and learnability than NQB. QB also enabled more effective typing in almost all experiment designs, except in one between-subjects study. The relatively short interaction time of participants’ first encounter with Arabic keyboards possibly caused this exception. Most participants subjectively preferred QB to NQB in their overall usability.
IDENTIFICATION OF PATCHOULI PLANTS USING LANDSAT-8 SATELLITE IMAGERY AND IMPROVED K-MEANS METHOD Candra Dewi; Muhammad Syaifuddin Zuhri; Achmad Basuki; Budi Darma Setiawan
Journal of Environmental Engineering and Sustainable Technology Vol 3, No 2 (2016)
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (517.806 KB) | DOI: 10.21776/ub.jeest.2016.003.02.1

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To maintain the availability of the patchouli plants required monitoring the spread of patchouli plantation. This study performed the identification of patchouli plant through Landsat-8 satellite imagery and Improved K-Means method. Improved was done on this study include the process of determining the initial cluster by specifying the closeness between the data and the determination of the number of cluster (K) by using the histogram equalization technique. The result of internal criteria testing shows that determining the number of clusters using the histogram is less effective because it produces the lower value of the silhouette. On almost all image data test found the best value of the silhouette's coefficient is 75.089% at K=2 and data in February. Furthermore, based on the results of testing the external criteria known the highest purity value in February data with a number of cluster 5 is 0.6829268. The test results also show that the use of the Improved K-Means on the Landsat-8 image has not been able to recognize the difference patchouli plants with other crops due to the limited resolution of imagery data and also the minimum number and variation of test data. But, visually the patchouli plant cluster is found for February data while the age of the rice crop surrounding the patchouli is still in the early phase of planting.
Mendeteksi Jenis Burung Berdasarkan Pola Suaranya Budi Darma Setiawan; Imam Cholissodin; Rekyan Regasari Mardi Putri
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 3, No 2: Juni 2016
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1032.704 KB) | DOI: 10.25126/jtiik.201632183

Abstract

AbstrakIlmuwan biologi terutama di bidang biodifersitas, terus melakukan penelitian tentang spesies hewan yang ada di dunia. salah satu hewan yang spesiesnya memiliki banyak variasi adalah burung. Tiap jenis burung memiliki perbedaan-perbedaan, mulai dari bentuk anggota tubuhnya, prilakunya, makanannya hingga suaranya. Ilmuwan sering juga mengalami kesulitan untuk melakukan pengamatan di alam. Misalnya, untuk mengetahui spesies burung apa saja yang ada di suatu daerah, mereka harus hadir di suatu wilayah, dan menelusuri setiap pelosok. kadang kala kehadiran mereka di tempat tersebut dalam jangka waktu lama, malah mengusik burung yang ada, dan burung-burung malah pergi meninggalkan tempat, sebelum berhasil diamati. Salah satu cara untuk mendeteksi burung apa saja yang ada di suatu wilayah, tanpa harus mengusik keberadaan burung adalah dengan menggunakan alat bantu. Bisa dengan menggunakan kamera video untuk mengambil gambar lingkungan sekitar, atau dengan perekam suara, untuk merekam suara burung yang ada di sana. Untuk itu penelitian ini ditujukan untuk membuat sebuah pengklasifikasi suara burung secara otomatis. Fitur yang digunakan adalah rhythm, pitch, mean, varian, min, max, dan delta  dari suara burungnya. dari hasil klasifikasi 4 jenis burung, didapatkan hasil rata-rata akurasi terbaik sebesar 88.82%. Kata Kunci : suara burung, klasifikasi, rhythm, pitchAbstractMany of Biologi scientist, especially in the field of biodiversity, conduct research on the animal species that exist in the world. One of the animal which is largely diverse in species is bird. Each species of birds have differences, from the shape of his body, his behavior, his food to it's voice. Scientists often find it difficult to make observations in nature. For example, to determine which species of birds present in an area, they should be present in an area, and explore every corner. sometimes their presence in that place for a long time, even disturb the bird, and they leaving the place, before been observed. One way to detect any bird that is in an area, without having to disturb the presence of birds is to use the automatic tools. For example to use a video camera to take pictures of the surrounding environment, or with voice recorders to record the sound of the birds that were there. This study is aimed to create a classifier bird sound automatically. Features used are rhythm, pitch, mean, variance, min, max, and delta of the bird sound samples. of the results of the classification of four types of birds, showed the best average of accuracy is 88.82%. Key Word : bird song, classification, rhythm, pitch.
Registrasi Citra Dental Menggunakan Feature From Accelerated Segment Test dan Local Gabor Texture For Iterative Point Correspondence Ahmad Afif Supianto; Budi Darma Setiawan
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 4, No 4: Desember 2017
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (985.536 KB) | DOI: 10.25126/jtiik.201744503

Abstract

AbstrakRegistrasi citra di bidang periodontal telah dikembangkan untuk melakukan evaluasi terhadap tulang alveolar. Masalah yang disebabkan oleh kesalahan saat ekstraksi fitur atau oleh degradasi gambar bisa timbul pada proses pencocokan fitur. Selain itu, teknik registrasi citra yang didasarkan pada fitur seperti titik, identifikasi tepian (edges), kontur, atau fitur yang lain yang biasa digunakan untuk membandingkan gambar dan kemudian memetakannya merupakan teknik yang sangat sensitif terhadap keakuratan pada tahap ekstraksi fitur. Dari kedua argumen ini, maka diperlukan teknik ekstraksi fitur yang tangguh untuk mencegah terjadinya kesalahan pada proses pencocokan fitur sehingga mendapatkan hasil registrasi citra yang akurat. Pada penelitian ini, diusulkan metode baru untuk registrasi citra. Metode yang diusulkan menggunakan metode ekstraksi fitur yang efektif terhadap akurasi dan efisien terhadap waktu komputasi dengan menerapkan Learning Features, yaitu Feature from Accelerated Segment Test (FAST) sebagai metode ekstraksi fitur. Selain itu, akan dilakukan pengembangan terhadap proses pencocokan fitur dengan menerapkan Local Gabor Texture (LGT) pada algoritma Iterative Point Correspondence (IPC) untuk melakukan registrasi pada citra dental periapikal. Uji coba dilakukan terhadap 8 citra grayscale dental periapikal dan berhasil melakukan registrasi citra  pada citra dental periapikal dengan nilai akurasi rata-rata diatas 93% dengan jumlah iterasi minimal mulai dari 400 iterasi.Kata kunci: registrasi citra, learning feature, local gabor texture, iterative point correspondence, citra dental periapikalAbstractImage registration in the periodontal field has been developed to evaluate alveolar bones. Problems caused by errors during feature extraction or by image degradation can arise in feature matching process. In addition, image registration techniques that are based on features such as points, identification of edges, contours, or other features commonly used to compare images and map them are very sensitive techniques for accuracy at the feature extraction stage. From both of these arguments, a robust feature extraction technique is needed to prevent mistakes in the feature matching process to get image registration results accurately. In this study, a new method for image registration is proposed. The proposed method uses an effective feature extraction method for accuracy and efficient computing time by applying learning features, which is Feature from Accelerated Segment Test (FAST) as a feature extraction method. In addition, a feature-matching process will be developed by applying Local Gabor Texture (LGT) to the Iterative Point Correspondence (IPC) algorithm to register on the periapical dental images. The experiments were conducted on 8 grayscale dental periapical images and successfully registered the image in periapical dental image with an average accuracy more than 93% with a minimum iteration count starting from 400 iterations.Keywords: image registration, learning feature, local gabor texture, iterative point correspondence, dental periapical images
Fitur Length Of Edge Dan Moment Invarian Untuk Gesture Recognition Dengan Menggunakan Kinect Untuk Kontrol Lampu Rekyan Regasari MP; Budi Darma Setiawan; Issa Arwani
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 2, No 1: April 2015
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (805.673 KB) | DOI: 10.25126/jtiik.201521133

Abstract

AbstrakTeknologi Kinect adalah teknologi yang dikembangkan untuk game. Kinect memungkinkan pemain game mengontrol permainan dengan menggunakan gerakan dan suara. Hal ini dikarenakan di dalam Kinect terdapat 3 hardware yang bekerja bersama-sama. Tiga hardware tersebut yaitu color VGA video camera, sensor kedalaman, dan multi array microphones. Karena itu, penelitian ini mencoba mengembangkan sensor Kinect untuk keperluan mendeteksi telapak tangan dan gesturnya untuk digunakan sebagai kontrol lampu. Hal ini dilakukan dengan menambahkan beberapa proses pengolahan citra. Pengenalan telapak tangan, menggunakan sensor VGA camera dan depth camera dalam Kinect. Ketika seorang pengguna menjulurkan tangannya kearah sensor, kemudian mengangkat jarinya maka program akan bereaksi. Jika 2 jari yang diangkat maka program akan mengaktifkan saklar padam. Sedangkan jika 5 jari yang diangkat, maka program akan mengaktifkan saklar hidup. Dalam penelitian ini ada 2 fitur yang digunakan dan dibandingkan hasilnya. Fitur yang digunakan adalah fitur Moment Invariant dan Length of Edge. Hasil lebih baik diberikan jika pengenalan dilakukan dengan menggunakan Length of Edge. Dari seluruh data uji yang dipakai, untuk pengenalan dengan menggunakan fitur Length of Edge, akurasi maksimal diperoleh sebesar 100%, sedangkan  dengan menggunakan fitur Moment Invariant, akurasi maksimal diperoleh sebesar 80%.Kata kunci: Moment Invarian, Length of Edge, gesture telapak tanganAbstractKinect is a technology developed for game. Kinect allows players to control game play by using movement and sound. This is because Kinect has 3 hardware that work together. The three hardware are VGA video camera, depth sensor and multi-array microphones. Therefore, this study attempts to use Kinect sensor for detecting the palm's gestures and use them as a light control. This is done by adding some image processing technique. The palm's gesture detection is done by using the VGA camera and depth camera in Kinect Sensor. When a user sticking his hand out and raise his fingers, then program will gives response. If 2 fingers are raised, program will activate off switch, while if 5 fingers are raised, program will activate on switch. There are two features are used in this study, and the results are compared. The features are Moment Invariant and Length of Edge. Better results given by recognition using the Length of Edge. From all the test data used, recognition using Length of Edge give 100% accuracy, while recognition using Moment Invariant features, give 80% in acuracy.Keywords: Moment Invarian, Length of Edge, palm gesture
Pengembangan Aplikasi Kamus Istilah Ilmiah Dengan Bahasa Isyarat untuk Peningkatan Kualitas Belajar Siswa Tuna Rungu Budi Darma Setiawan; Fajar Pradana
Indonesian Journal of Disability Studies Vol. 4 No. 1 (2017)
Publisher : The Center for Disability Studies and Services Brawijaya University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (450.07 KB) | DOI: 10.21776/ub.IJDS.2017.004.01.4

Abstract

The government guarantees the absence of a difference for all Indonesian citizens to get education in higher education. Educational needs for every disability is different. Suppose the deaf students, to communicate highly dependent on writing and sign language. From the field observations problems found sign language that is used has a lot of variations, especially for scientific terms such as for example: cell, engineering, photosynthesis and others. This causes the communication becomes slower so that deaf students have difficulty understanding the material taught in the lectures. For that we need to make a media in the form of software to save the new terms as well as sign language. The media should also be accessible though many people (online). This way, if someone is having difficulty in finding a cue for a term, he can look for it on this media. From the results of tests performed, the application is able to enhance the understanding of the time three seconds faster than before using the app. On the usability and user acceptance testing, the application has largely met the expectations of the user.
Co-Authors Abdul Fatih Achmad Basuki Achmad Fahlevi Adinugroho, Sigit Aditya Chandra Nurhakim Aditya Kresna Bayu Arda Putra Agung Nurjaya Megantara Agus Wahyu Widodo Ahmad Afif Supianto Ahmad Afif Supianto Akhmad Eriq Ghozali Akmal Subakti Wicaksana Almira Syawli Amaliah Gusfadilah Andhi Surya Wicaksana Andika Harlan Angga Dwi Apria Rifandi Aria Bayu Elfajar Azmi Makarima Yattaqillah Barlian Henryranu Prasetio Bayu Rahayudi Budi Santoso Cahyo Adi Prasojo Candra Dewi Candra Dewi Chelsa Farah Virkhansa Cindy Inka Sari Cinthia Vairra Hudiyanti Deby Chintya Dellia Airyn Dhan Adhillah Mardhika Dian Eka Ratnawati Dwi Anggraeni Kuntjoro Dwi Ari Suryaningrum Dwi Damara Kartikasari Edo Fadila Sirat Eka Novita Shandra Eka Yuni Darmayanti Eti Setiawati Fadhlillah Ikhsan Fajar Nur Rohmat Fauzan Jaya Aziz Fajar Pradana, Fajar Fanny Aulia Dewi Fatwa Ramdani, Fatwa Febri Ramadhani Fikri Hilman Fitra A. Bachtiar Fitra Abdurrachman Bachtiar Gandhi Ramadhona Gembong Edhi Setiawan Gilang Ramadhan Hendra Pratama Budianto Husin Muhamad Imam Cholisoddin Imam Cholissodin Imam Cholissodin Imam Cholissodin Indah Larasati Indriati Indriati Irfan Aprison Irma Lailatul Khoiriyah Irma Nurvianti Irma Ramadanti Fitriyani Ismiarta Aknuranda Issa Arwani Issa Arwani Issa Arwani Karina Widyawati Kholifa'ul Khoirin Koko Pradityo M Kevin Pahlevi M. Ali Fauzi M. Raabith Rifqi M. Rikzal Humam Al Kholili M. Tanzil Furqon Mahendra Data Marji Marji Masayu Vidya Rosyidah Mayang Arinda Yudantiar Mimin Putri Raharyani Miracle Fachrunnisa Almas Moch. Khabibul Karim Mohamad Alfi Fauzan Muhammad Arif Hermawan Muhammad Dimas Setiawan Sanapiah Muhammad Khaerul Ardi Muhammad Rizkan Arif Muhammad Syaifuddin Zuhri Muhammad Tanzil Furqon Mustofa Robbani Muthia Azzahra Nadia Natasa Tresia Sitorus Nanda Agung Putra Nashrullah Nashrullah Nelli Nur Rahma Ni Luh Made Beathris Anjasari Ni'mah Firsta Cahya Susilo Nihru Nafi' Dzikrulloh Noval Dini Maulana Nur Intan Savitri Bromastuty Nurhana Rahmadani Nurudin Santoso Nurudin Santoso Nurul Hidayat Oky Krisdiantoro Olive Khoirul L.M.A. Pindo Bagus Adiatmaja Putra Pandu Adikara Radifah Radifah Rafely Chandra Rizkilillah Rahmat Faizal Raissa Arniantya Randy Cahya Wihandika Randy Cahya Wihandika Ratna Candra Ika Rekyan Regasari Mardi Putri, Rekyan Regasari Mardi Rekyan Regasari MP Rekyan Regasari MP, Rekyan Regasari Rendi Cahya Wihandika Retiana Fadma Pertiwi Sinaga Revinda Bertananda Reza Wahyu Wardani Ridho Agung Gumelar Rima Diah Wardhani Rinda Wahyuni Rizal Setya Perdana Rizki Agung Pambudi Rizky Haqmanullah Pambudi Robih Dini Rosi Afiqo Rudito Pujiarso Nugroho Rudy Usman Azzakky Ryan Mahaputra Krishnanda Sabriansyah Rizkiqa Akbar Satrio Hadi Wijoyo Shelly Puspa Ardina Sigit Adinugroho Siti Fatimah Al Uswah Siti Utami Fhylayli Sri Wahyuni Suryani Agustin Sutrisno Sutrisno Tahajuda Mandariansah Talitha Raissa Tibyani Tibyani Tri Afirianto Tria Melia Masdiana Safitri Ulfah Mutmainnah Vina Meilia Vina Meilia Wayan Firdaus Mahmudy Yerry Anggoro Yosendra Evriyantino Yuita Arum Sari Yuita Arum Sari Yulfa Hadi Wicaksono Zubaidah Al Ubaidah Sakti