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All Journal Jurnal Bisnis dan Manajemen Journal of Innovation and Applied Technology Jurnal Teknologi Informasi dan Ilmu Komputer Jurnal POINTER Jurnal Pengabdian Kepada Masyarakat (Indonesian Journal of Community Engagement) Sinkron : Jurnal dan Penelitian Teknik Informatika Journal of Information Technology and Computer Science Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Seminar Nasional Teknologi Informasi Komunikasi dan Industri DIKEMAS (Jurnal Pengabdian Kepada Masyarakat) JPKMI (Jurnal Pengabdian Kepada Masyarakat Indonesia) Jurnal Sistem Informasi, Teknologi Informasi, dan Edukasi Sistem Informasi (JUST-SI) Bulletin of Social Informatics Theory and Application
Bayu Rahayudi
Fakultas Ilmu Komputer - Universitas Brawijaya
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Mathematics Public Health Social Sciences

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Perbandingan Algoritma Naive Bayes dan Support Vector Machine untuk Analisis Sentimen terhadap Review Produk Aster Kosmetik Malang Marketplace Shopee Dhiva Mustikananda; Dian Eka Ratnawati; Bayu Rahayudi
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 6 No 7 (2022): Juli 2022
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Aster Cosmetics Malang is a popular beauty shop in Malang City. Aster Cosmetics uses the Shopee online shopping platform as a product promotion medium. Online shopping provides many conveniences in the midst of the COVID-19 pandemic. On the online shopping platform there is a feature to add product reviews, where product reviews can be used as a consideration for potential buyers in making decisions. Shopee is used as a data source for sentiment analysis on Aster Cosmetics Malang product reviews. The review data are classified into positive, negative, and neutral categories. Classification is done by comparing the Naive Bayes algorithm and Support Vector Machine. This study uses 300 data for the classification of 3 sentiments, namely positive, negative, and neutral, then 200 data for the classification of 2 sentiments, namely positive and negative. Testing by comparing the two methods using the same test parameters, namely the percentage of training data and test data 80%:20% and cv=10. The classification results get the highest accuracy value of the Support Vector Machine method in the classification of 2 sentiments with an accuracy value of 87.56%, precision 88.81%, recall 86.76% and f-measure 86.85%, the highest accuracy results in the classification of 3 sentiments using the Support Vector Machine method with an accuracy value of 79.71%. , precision 81.56%, recall 79.56% and f-measure 79.36%.
Prediksi Hasil Panen Udang Vaname menggunakan Algoritme Backpropagation Neural Network Harris Imam Fathoni; Bayu Rahayudi; Dian Eka Ratnawati
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 6 No 8 (2022): Agustus 2022
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Shrimp (Caridea) is one of the commodities that are often exported every year. In cultivation, to maintain the productivity of shrimp harvests, there are several parameters that must be seen every day. Forecasting is used to help farmers to be used as a reference in terms of shrimp maintenance until the final harvest. This research used shrimp cultivation for four years from 2016 until 2019 as data inputs Then normalization of data is carried out which will then be processed using the backpropagation method to find the forecasting value for vaname shrimp yields. The final results were denormalized again and then evaluated using the MAPE (Mean Absolute Percentage Error) method and obtained in this study the optimal value with a minimum MAPE of 3.65% using the hidden neuron parameter = 1, the epoch value = 1000 and the initial random weight range value from -1 up to 1.
Analisis Sentimen Data Ulasan Pengguna Aplikasi TIX ID di Indonesia pada Google Play Store menggunakan Support Vector Machine Muhammad Razan Nadhif; Dwija Wisnu Brata; Bayu Rahayudi
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 6 No 8 (2022): Agustus 2022
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Review on the Google Play Store is one of the features used to provide an assessment of an application. TIX ID is an online cinema ticket booking service or application company made by PT Nusantara Elang Sejahtera. This application provides services such as ordering movie tickets from your favorite cinema, choosing online movies to buy or rent, and buying vouchers to watch streaming movies online. However, the rating accompanied by various reviews does not mean that the wishes or problems of users are fulfilled and stop evaluating in improving services to users. For this reason, sentiment analysis is needed that can classify reviews as user sentiment. In this study, the scraping stage was carried out for collecting application user review data, followed by the text preprocessing stage to process data by selecting data and turning it into more structured data. The data from text preprocessing were word weighted using the Term Frequency - Inverse Document Frequency (TF-IDF) method. Then sentiment classification is carried out using the Support Vector Machine (SVM) algorithm. The best results obtained with the SVM algorithm for sentiment testing of 2 classes with unbalanced data with positive data 274 and negative data 100 using training data values and test data 90%:10%, total data with 374 data, using parameter value C = 10, cross validation experiment K=10 and use of linear kernel. The results obtained for the average value of 91% accuracy, 94% precision, 83% recall and 86% f-measure. The best results obtained with the SVM algorithm for testing sentiment of 2 classes with balanced data with positive data 150 and negative data 150 using training data values and test data 90%:10%, total data with 300 data, using parameter value C = 0.5, experiment cross validation K=10 and use of linear kernel. The test results on balanced data get the highest accuracy results, namely 94%, precision 94%, recall 94% and f-measure 94% in the Support Vector Machine method with 2 sentiment classification.
Analisis Sentimen Objek Wisata Danau Toba berdasarkan Ulasan Pengunjung menggunakan Algoritma Support Vector Machine Immanuel Tri Putra Sihaloho; Dian Eka Ratnawati; Bayu Rahayudi
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 6 No 9 (2022): September 2022
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Lake Toba is one of the tourist destinations in Indonesia and is designated as one of the five developments of the National Tourism Strategic Area which is the government's super priority program in tourism development in Indonesia. Therefore, Lake Toba tourism managers need to know the perspective of visitors as evaluation material. Data acquisition of visitor reviews of Lake Toba attractions can be easily obtained through the Tripadvisor website using web scraping techniques. Reviews from Tripadvisor will be categorized into three classes, namely positive, neutral and negative. Before doing the classification, do text preprocessing to process the data into more structured data for research needs and carry out word weighting using the Term Frequency - Inverse Document method. Then the classification is carried out using the Support vector Machine algorithm. The best results in testing using the Support vector Machine algorithm are testing on 2 sentiment classes with a total of 220 data, using a linear kernel and a C value of 100. Accuracy, precision, recall, and f1-score values ​​in this machine learning model are successively were 83%, 84%, 83%, and 83%.
Analisis Sentimen Ulasan Aplikasi PeduliLindungi dengan Metode Random Forest Muhammad Reza Utama Pulungan; Dian Eka Ratnawati; Bayu Rahayudi
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 6 No 9 (2022): September 2022
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

PeduliLindung is an application developed by the Ministry of Communication and Information (KOMINFO) in collaboration with the Covid-19 Handling Committee. This application is useful for tracing user activities to places visited, getting vaccination info, and also notification of regulations that apply in Indonesia during the Covid-19 pandemic. The PeduliLindung application is used by more than Fifty million users based on information on the total downloads available on the Playstore platform. With many PeduliLindung users during the pandemic, there are often positive, negative and neutral reviews of the PeduliLindung application, especially on the App Store platform. This PeduliLindung application review data will be a data source for analysis and also classifying the sentiment. The PeduliLindung application review data will be obtained using the Scrapping technique where this process can extract data from website pages. The classification method used is Random Forest by testing the depth of the tree and the number of trees. The evaluation methods used are Confusion Matrix. The results of the study with a tree depth of 65 and the number of trees 400 got the best values, namely precision 71%, recall 71%, F1-Score 71% and accuracy 72% with a ratio of 90% training data and 10% test data.
Pengembangan Sistem Informasi Biro Perjalanan Wisata berbasis Web menggunakan Payment Gateway dan Booking Paket Wisata (Studi Kasus: CV. Maha Cipta Wisata) Adi Maulana Rifa'i; Bayu Rahayudi; Dwija Wisnu Brata
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 6 No 9 (2022): September 2022
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Tourism is a field that has bright business prospects, this can be seen by the increasing number of foreign and domestic tourists visiting many tourist objects in Indonesia. CV. Maha Cipta Wisata is a company engaged in tour & travel. provides various types of tourism packages, industrial visits, family gatherings, hotels, and buses. However, conventional hotel sales and marketing method is by ordering and paying via whatsapp. The transaction creates a loophole, because it can allow errors in uploading payments and must be checked for validation first by the admin. Based on the existing problems, a dynamic web-based tour package booking information system is needed that has payment gateways. It is hoped that with this integration, consumers can choose many payment method options and can increase consumer confidence because facilitator in making payments. Method of developing an information system using prototype is a development that saves time and costs without compromising product quality. While at the implementation stage using Laravel framework. Results of the development of a web-based travel agency information system using payment gateways and booking tour packages (case : CV. Maha Cipta Wisata) can help manage sales such as hotels and tour packages, in addition to the existence of a payment gateway providing various payment methods so that consumers get freedom in choosing payment methods. And black box testing is 100% valid. while compatibility using the sortsite works well.
Penerapan Rest API dalam Pengembangan Sistem Informasi Sayur Online Kediri berbasis Web dan Mobile (Studi Kasus: Sayuraya Kediri) Sandi Dewo Rahmadianto; Bayu Rahayudi; Buce Trias Hanggara
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 6 No 10 (2022): Oktober 2022
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Sayuraya is a startup located in Kediri City that provides online kitchen needs. There are several problems with Sayuraya's operations. The first is that the transaction recording process is still done manually so that it is possible for human errors to occur in the recording process. The second problem is that the management system is still done manually which takes a long time and is at risk of errors. The information system to be developed uses the RAD (Rapid Application Development) method. The study begins with a needs analysis interview with the vegetable owner. Furthermore, a design will be carried out based on a needs analysis. After the design is approved, it is then implemented in the form of coding. In the implementation process, a management web was created that would be used for the vegetable company, as well as a mobile application that would be used for the vegetable customer. And use the REST API for communication between mobile applications with the server. The last stage is testing. The first test is black-box testing, in this test, 18 functional requirements have been made, and the results are all functions run correctly. The second test was carried out using the Usability method by using the System Usability Scale, in this test the questionnaire was distributed to 6 respondents, 5 were customers and 1 was the vegetable owner. from the test results get a value of 77.08.
Pengembangan Aplikasi Ekstraksi KTP dan Reverse Geocoding pada Perangkat Bergerak untuk Verifikasi dan Validasi Data Pendaftar Data Terpadu Kesejahteraan Sosial (DTKS) RE. Miracle Panjaitan; Bayu Rahayudi; Dian Eka Ratnawati
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 6 No 12 (2022): Desember 2022
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Based on the 1945 Constitution of the Republic of Indonesia, the state is responsible for caring for the poor to meet the basic needs of humanity. The resources of social welfare in villages, assist the process of collecting data and verifying and validating the data of the poor. The results of the verification and validation are reported to the regent/mayor, then submitted to the governor, then forwarded to the Minister. Data that has been verified and validated must be based on information technology and integrated under the responsibility of the Minister. Integrated data belonging to the Ministry of Social Affairs is called the Integrated Data on Social Welfare (DTKS) and is used as a reference for the provision of Social Assistance (BANSOS). In fact, many recipients of Social Assistance (BANSOS) were found who should not be the target of this work program of the Ministry of Social Affairs. Researchers developed an ID card extraction and reverse geocoding application to help the verification and validation process, namely by matching the address obtained from the KTP extraction results with the location of the reverse geocoding results when taking photos of the ID card. This address matching is done by utilizing the Google Vision and Geocoder libraries. If the addresses match, then the DTKS registrant verification process can continue. If the addresses do not match, the DTKS registrant verification process cannot continue. This system was tested 10 times, with 5 experiments at the exact location with the ID card address and 5 at different locations with the ID card address. The success rate of this system trial is 95,7%.
Pembelajaran Mesin untuk Pembuatan Dokumen Karya Sastra Indonesia Secara Otomatis menggunakan Metode Modified Long Short Term Memory (LSTM) berbasis Extreme Learning Machine (ELM) Gusti Reza Maulana; Imam Cholissodin; Bayu Rahayudi
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 6 No 12 (2022): Desember 2022
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Documents as important and make it easy for human work. one type of document is a literary work. Literary work is a series of writings or an idea and thought conveyed with aesthetic purposes. The literary works used in this research are words of wisdom, poetry and rhymes. All this time making literary works are written manually. This is why many of these literary works took too long to produce. The focus of this research is to apply a literary work made from the program so that it does not take a long time to make it. This study uses a Modified Long Short Term Memory algorithm based on Extreme Learning Machine for the creation of the literary work. The process of making the literary work is preprocessing, dividing training data and test data, training phase, testing phase, calculating MAPE and calculating the accuracy of the BLEU Score. In testing the number of context neurons and hidden neurons, optimal results were obtained, namely as many as 5 and 800 for the three literary works. Calculation using the BLEU Score with a value of N = 4 produces an average accuracy for words of wisdom 74.66%, poetry of 14.49% and rhymes of 73.76%.
Pembangunan Sistem Reservasi Kamar Hotel berbasis Web dengan memanfaatkan Teknologi Payment Gateway (Studi Kasus: Hotel Asri) Muhammad Syahputra; Bayu Rahayudi; Welly Purnomo
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 7 No 1 (2023): Januari 2023
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Asri Hotel is located in Banyuwangi regency, East Java. The process of renting a room or reservation at this hotel is still written in the ledger. Customers must come in person or call-in advance to make a reservation, so there are often mistakes that harm customers and Asri Hotel. Currently, Hotel Asri also experiences problems in booking rooms due to a shortage of employees, so employees who have duties on the front end or reception are not always there. So, the step that can be taken to facilitate room reservations at Hotel Asri is to build a hotel room reservation system. The system to be built is web-based that is integrated with Midtrans's payment gateway so that guests can make room reservations and hotels in confirming room reservations. The research methodology used is the waterfall, starting from the analysis of needs in obtaining functional needs and non-functional needs of the system. Designing applications using Unified Modelling Language (UML). Functional testing of the system is performed by BlackBox testing the acquisition of 100% valid values. Non-functional testing was carried out using compatibility testing and the results of the system running in various browsers without any problems. System Usability Scale (SUS) testing was carried out on seven respondents and an average final score of 86% was obtained which based on the SUS score, the system built was accepted with the Acceptability Ranges assessment the system got an "ACCEPTABLE" score, in the Grade Scale assessment the system got a B grade and the system Adjective Ratings score got an "EXCELLENT" score.
Co-Authors Abdullah Harits Abdurrahim, Ahmad Azmi Abhiram, Muhammad Tegar Achmad Choirur Roziqin Achmad Ridok Adam Hendra Brata Ade Wahyu Muntizar Adi Mashabbi Maksun Adi Maulana Rifa'i Adi, Tri Adinda Putri, Lintang Gladyza Adinugroho, Sigit Aditya Septadaya Aditya, Nathanael Chandra Afif Ridhwan Ageng Wibowo Agus Wahyu Widodo Agus Wahyu Widodo, Agus Wahyu Ahmad Afif Supianto Ahmada Bastomi Wijaya Aldi Bagus Sasmita Aldous Elpizochari Alfarisi, Raihan Alfian Reza Pahlevi Alip Setiawan Allifira Andara Hasna Alvian Akmal Nabhan Amaliah Gusfadilah Andhi Surya Wicaksana Andro Subagio Angga Wahyudi Kurniawan Pratama Anggi Novita Sari Anne Diane Rachmadani Arif Indra Kurnia Arina Rufaida Aristides, Joy Vianoktya Arjun Nurdiansyah Arsan, Danish Alif Arsti Syadzwina Fauziah Audia Refanda Permatasari Ayezha Halidar Putri Irwanda Ayuda Dhira Pramadhari Bachtiar, Harsya Bafagih, Novel Bagas Laksono Bastian Dolly Sapuhtra Basuki, Akbar Lucky Bisma Anassuka Brillian Aristyo Rahadian Buce Trias Hanggara Budi Darma Setiawan Cahyo Gusti Indrayanto Candra Dewi Candra Dewi Chandra, Ardhya Khrisna Christina Sri Ratnaningsih Cindy Cynthia Nurkholis Dahnial Syauqy Daniel Agara Siregar Dany Primanita Kartika Sari Dany Primanita Kartikasari Davia Werdiastu Dedy Surya Pradana Dese Narfa Firmansyah Devi Nazhifa Nur Husnina Dhaifa Farah Zhafira Dhimas Wida Syahputra Dhiva Mustikananda Diamanta, Ananda Dian Eka Ratnawati Dian Ratnawati Dian Sisinggih Dimas Adi Syahbani Achmad Putra Djoko Pramono Djoko Pramono Dloifur Rohman Alghifari Dwi H Sulistyarini Dwija Wisnu Brata Dwija Wisnu Brata Dwija Wisnu Brata Dzulkarnain, Tsania Dzulkarnain, Tsania - Edgar Maulana Thoriq Edy Santoso Eko Wahyu Hidayat Ellita Nuryandhani Ananti Ema Rosalina Eni Hartika Harahap Fadilah Islamawan, Adam Faiz Abiyandani Faizatul Amalia Fajar Pangestu Faradila Puspa Wardani Faris Febrianto Farizky Novanda Pramuditya Fauzia, Sri Febrina Sarito Sinaga Ferina Kusuma Anjani Ferry Jiwandhono Fitria Yesisca Gagas Budi Waluyo Gani Kharisma Wardana Gilang Pratama Gusti Reza Maulana Haidar Azmi Rabbani Hanggara , Buce Trias Hardyan Zalfi Harris Imam Fathoni Haryuni Siahaan Hayunanda, alanela ganagisarama Heryadi Mochamad Ramdani Hidayati, Chofifa Hilmy Ramadhan, Achmad Zhafran Huda Minhajur Rosyidin Husalie, Levin Vinnu Imam Cholisoddin Imam Cholissodin Imam Cholissodin Immanuel Tri Putra Sihaloho Indriati Indriati Indriati Indriati Indriati, Indriati - Intan Sartika Eris Maghfiroh Irany Windhyastiti Irwan Shofwan Issa Arwani Issa Arwani Ivan Agustinus Jasico Da Comoro Aruan Jefri Hendra Prasetyo Jonemaro, Eriq Muhammad Adams Jumerlyanti Mase K., Anggraeni Dwi Kautsar, Ahmad Izzan Kevin Nastatur Chatriavandi Khairul Rizal Krishna Febianda Ksatria, Willyan Eka Kurnianingtyas, Diva Laila Diana Khulyati Lailil Muflikhah Liwenki Jus'ma Olivia M. Ali Fauzi M. Ali Fauzi M. Attala Reza Syahputra Made Tri Ganesha Madjid, Marchenda Fayza Marji Marji Marpaung, Veronika Oktafia Marwa Mudrikatussalamah Maulana Syahril Ramadhan Hardiono Maulana, M. Ighfar Maulidhia, Abrilian Meriza Nadhira Atika Surya Michael Eggi Bastian Mochammad Ilman Asnada Mohammad Aditya Noviansyah Mohammad Setya Adi Fauzi Mohammad Zahrul Muttaqin Muh. Arif Rahman Muhammad Ferian Rizky Akbari Muhammad Hidayat Muhammad Ikhsan Nur Muhammad Jibril Alqarni Muhammad Kevin Sandryan Muhammad Nadzir Muhammad Nurhuda Rusardi Muhammad Razan Nadhif Muhammad Reza Utama Pulungan Muhammad Shidqi Fadlilah Muhammad Syahputra Muhammad Tanzil Furqon Mukhtar Darma Hidayat, Alif Ahmad Muthia Maharani Muzayyani, Muhammad Farid Nadiah Nur Fadillah Ramadhani Najihah, Siti Waheeda Nanang Yudi Setiawan Nanang Yudi Setiawan Nanda Alifiya Santoso Putri Nashihul Ibad Al Amin Niken Hendrakusuma Wardani, Niken Hendrakusuma Nilna Fadhila Ganies Novanto Yudistira Nur M. F. Dinia Nurfadhilah, Rakhmad Giffari Nuril Haq, Muhammad Nurizal Dwi Priandani Nurul Hidayat Nurul Ihsani Fadilah Obed Manuel Silalahi Panjaitan, RE. Miracle Pascad Wijanata, Ida Bagus Prakosa, Wira Zeta Pramudita, Julina Larasati Primayuda, Averil Priscillia Vinda Gunawan Purnomo, Welly Putra Pandu Adikara Putranto, Rezky Donny Putri Ratna Sari Putri, Firda Qhafari, Abi Al Qoid A Fadhlurrahman Rafli, Mohammad Ali Rahinda, Muhammad Abiyyi Ramadhani, T. Zalfa Randy Cahya Wihandika Rani Metivianis Rasif Nidaan Khofia Ahmadah RE. Miracle Panjaitan Reinaldi Guista Pradana Ismail Reiza Adi Cahya Renaldi Muhammad Revan Yosua Cornelius Sianturi Reyhan Dzickrillah Laksmana Reza Aprilliana Fauzi Rheza Raditya Andrianto Rifwan Hamidi Riswan Septriayadi Sianturi Riza Rizqiana Perdana Putri Rizky Ardiawan Rizky Nuansa Nanda Permana Rohimatus Sholihah Roisul Setiawan Roma Akbar Iswara Rudianto Raharjo Safa S Istafada Saifurrijaal, Muchammad Salsabila, Dhea Rani Sandi Dewo Rahmadianto Satrio Agung Wicaksono Sekeon, Yerobal Gustaf Setiana, Maya Setiawan, Roisul Shafira Eka Aulia Putri Slamet Thohari Sofi Hidyah Anggraini Sugeng Santoso Sugiarto S Sugiono Sugiono Sukmawati, Annisa Sultan Saladdin Sultan, Muhammad Attharsyah Firdaus Supraptoa Supraptoa Tanica Rakasiwi Tasya Agiyola Teri Kincowati Tri Astoto Kurniawan Trias Hanggara, Buce Trio Pamujo Wicaksono Ulva Febriana Umar Basher, Nizar Umu Khouroh Vivilia Putri Agustin Wahyu Bimantara Wayan Firdaus Mahmudy Welly Purnomo Welly Purnomo Weni Agustina Wenny Ramadha Putri Wibowo, Dhimas Bagus Bimasena Wicaksono, Satrio A. Widhy Hayuhardhika Nugraha Putra Widhy Hayuhardika Nugraha Putra Widodo, Ibnu Sam Widyadhana, Fawwaz Kumudani Wiku Galindra Wardhana Wisnu Brata, Dwija Yahya, Faiz Yesaya Sergio Vito Putranta Yudi Setiawan, Nanang Yuita Arum Sari Yusuf Afandi Zhafira, Dhaifa Farah