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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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Analisis Sentimen Opini Publik pada Media Sosial Twitter terhadap Vaksin Covid-19 menggunakan Algoritma Support Vector Machine dan Term Frequency-Inverse Document Frequency Edgar Maulana Thoriq; Dian Eka Ratnawati; Bayu Rahayudi
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 5 No 12 (2021): Desember 2021
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Social media is a place for people to express their aspirations, ideas, and even their critics. One of the policies made recently by the government is the provision of COVID-19 vaccine. This policy has been widely discussed on Twitter and attracted a lot of diverse opinions in the society. Twitter is a social media that has a fairly large user base in Indonesia, where many users share their opinions regarding the provision of COVID-19 vaccine. Twitter can be a source of data that can be used to conduct sentiment analysis on government policies by classifying tweets (a term for content in Twitter) into positive or negative categories. The classification process is utilizing a classification algorithm, namely Support Vector Machine and term weighting namely Term Frequency - Inverse Document Frequency (TF-IDF) method. This study uses 450 tweets, then testing is carried out using the cross validation method with number of fold = 10. Best performance of the classification algorithm is 86% accuracy, 88% precision, 82% recall, and 85% f-measure. Value of the performance is obtained with value C of 1 and the maximum iteration of 300.
Optimasi Gizi Bahan Makanan pada Anak - Anak untuk Tumbuh Kembang menggunakan Algoritma Genetika (Studi Kasus : Dinas Kesehatan Kabupaten Kediri) Putri Ratna Sari; Imam Cholissodin; Bayu Rahayudi
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 5 No 12 (2021): Desember 2021
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Around 70% of parents in the Mojo district are still not familiar with foods that contain optimal nutrition for children. Nutrition that is not optimal will cause disease in children and make growth and development not perfect. In Kediri Regency itself, many children are overweight or often referred to as obese. The obesity rate in Kediri Regency reaches 80%. The problem of optimizing the nutrition of foodstuffs can be solved by an optimization algorithm, namely the Genetic Algorithm. A Genetic Algorithm is an algorithm that uses the basis of natural selection and evolution from biology and can combine sequences of structures with information in a random way. In this study, to determine the representation of the solution generated from the genetic algorithm, testing was carried out on the effect of the parameter values. Optimal parameter results, namely the generation of 1200, the value of Crossover Extended Intermediate of 0.5, the value of Reciprocal Exchange Mutation 0.9, and Popsize 60 by using the optimal parameters, the optimal category of food ingredients will be known, the price according to weight, and recommended nutrition for the patient. From the results of using optimal parameter testing, we get a package of food ingredients that match the need, differences, and price, in the test the difference in content between food ingredients and nutritional need is 6,1 % for Rp. 37.722,00 for patients with male gender and 5,4% for patients with female gender for Rp. 32.040,00.
Analisis Sentimen pada Twitter Bencana Alam di Kalimantan Selatan menggunakan Metode Naive Bayes Adi Mashabbi Maksun; Yuita Arum Sari; Bayu Rahayudi
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 5 No 12 (2021): Desember 2021
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

The great flood disaster that hit the South Kalimantan region caused conversation and debate among the community and government, especially on Twitter which was trending, and thousands of tweets appeared on Twitter with the hashtags #PrayForKalsel, and #KalselJugaIndonesia. The tweets of the public and the government clashed for their own defense of the truth and gave rise to many positive and negative opinions. Twitter is now a place to chat and complain about various groups. For this research, it is hoped that it can help and make it easier to conduct research using public opinion on Twitter that contains positive or negative opinions. The method used in this study is using Naive Bayes, the process of this system starts from the data preprocessing process which includes case folding, tokenization, filtering, normalization, and finally stemming then word weighting using Raw TF and the classification process used is Naive Bayes. The data used comes from twitter which is taken by crawling and scrapping using the hashtags #PrayForKalsel, and #KalselJugaIndonesia with a total of 520 data. The data was taken using the Twitter API. using the confusion matrix test from the 5 experiments, the average value reaches an accuracy of 0.81, a precision of 0.81, a recall of 0.81, and an f-measure of 0.81, and the highest test value is an accuracy of 0.88, a precision of 0.89, recall 0.87, and f-measure 0.87.
Pengenalan Citra Makanan Kue Tradisional menggunakan Ekstraksi Fitur HSV Color Moment dan Local Binary Pattern dengan K-Nearest Neighbour Gagas Budi Waluyo; Yuita Arum Sari; Bayu Rahayudi
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 5 No 12 (2021): Desember 2021
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Traditional cakes or market snacks are traditional foods that we need to preserve, these traditional cakes are very rarely found today, because many people do not know about these traditional cakes and are very rarely found in this modern era. Actually this traditional cake is a delicious food and there are many various types and certainly not too many preservatives in it. But over time traditional cakes have been shifted by modern food and a lot of food is imported into the country, therefore it is time to preserve it so that it does not become extinct and posterity can find out. So a system is needed to recognize traditional cakes using technology as it is today n this study, to recognize traditional cakes using Hue Saturation Value (HSV) color feature extraction and Local Binary Pattern (LBP) texture features and classified using the K-Nearest Neighbor (KNN) method. The color feature used is the color moment which produces three values, namely the mean, standard deviation, and skewness. While the LBP texture feature will produce a grayscale value as much as the number of neighbors used. After that, the obtained feature extraction is classified using K-Nearest Neighbor. The test results show that if you only use the HSV color feature method, you get an accuracy value of 75%. If only using the LBP texture feature method, the accuracy value is 72.5%. Meanwhile, if the two feature extraction methods are combined, the accuracy value is 75%.
Pengelompokan Topik Skripsi Mahasiswa Fakultas Ilmu Komputer Universitas Brawijaya berdasarkan Judul pada Periode 2015-2019 menggunakan Metode Semi Supervised K-Means Mochammad Ilman Asnada; Bayu Rahayudi; Achmad Ridok
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 6 No 1 (2022): Januari 2022
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

The title of the thesis is a sentence that briefly conveys some of the contents of the thesis itself. Every year the research or final project is always increasing, from the many titles used as the thesis it is possible that the topics discussed are almost the same or even the same. Based on this, in this study grouping the title of the thesis which is implemented in a program. The results of title grouping are displayed annually (2015 to 2019) in the form of a bar chart and then the number of data groups based on a predetermined topic or category will be seen. Extracting a collection of thesis titles using the flow of text mining which will be used as a dataset. Then the datasets are grouped using the semi-supervised k-means method, the method is the development of k-means. After that, the collection of thesis titles is preprocessed with the text mining method in which there are several stages, namely tokenization, filtering, stemming, term weighting. The initial stage of the semi-supervised k-means method is to label several datasets to determine the initial centroid, after which the data grouping process is carried out. Based on the results of tests carried out using the amount of test data that varies each year. From the test results every year (2015 to 2019) the silhoutte value is different and the largest silhoutte is in 2016 using the amount of 30% test data with a silhoutte of 0.0274024334, while the Davies Bouldin Index (DBI) value is optimal for testing 30% of the data. test in 2015 was 0.345362812. The results of grouping with the same amount of training data on each label also have a better silhouette value than the number of training data on each label that is not the same.
Pengelompokan Ulasan Produk HP pada Marketplace Tokopedia menggunakan Metode Semi Supervised K-Means Rizky Ardiawan; Yuita Arum Sari; Bayu Rahayudi
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 6 No 1 (2022): Januari 2022
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

The internet has grown rapidly in accordance with the changing times. It also changes shopping behavior that was originally face to face now can be done online. Cell phones or smartphones are the most sought after items today. To buy these items online, there are many marketplaces available in Indonesia, such as Tokopedia. A product review is rated as the main factor for consumers to buy goods. To perform analysis on reviews, a method is needed that can classify and group reviews into existing categories. By combining the two understandings between Supervised and unsupervised, one can create a grouping method based on training data consisting of labeled data. The method that is suitable for this case is the Semi Supervised K-Means method. From the results of this study, it was found that in 4 different experiments, the evaluation of the cluster value using Silhouette was 0.013647 which was the largest value using the Semi Supervised K-Means method. Which is very small, namely 3 clusters. However, the results of clustering the clusters produced in the same method proved to be better than the K-Means method in general with the review data according to the original label.
Optimasi Rute Pendistribusian Obat Pedagang Besar Farmasi di Apotek Kota Kediri menggunakan Algoritma K-Means dan Artificial Bee Colony (ABCKM) Cindy Cynthia Nurkholis; Imam Cholissodin; Bayu Rahayudi
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 6 No 2 (2022): Februari 2022
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Pharmaceutical wholesaler is a business that already has a license to distribute pharmaceutical products. In product distribution, there are pharmacies that are close by, no delivery is made, so the courier returns again and gets a larger total distance. Thus, pharmaceutical wholesalers need an optimal route for distributing pharmaceutical products. This problem is a Multi Traveling Salesman Problem (MTSP). The K-Means and Artificial Bee Colony algorithms were chosen to solve the MTSP problem because the K-Means algorithm can be used to share data with the best sources. The solution used in K-Means is the closest neighbor coordinate solution only. So that an artificial bee colony algorithm is needed to help avoid being trapped in the local optima. The artificial bee colony algorithm will be used in finding the optimal route in the problem of optimizing the distribution route of pharmaceutical products at the Kediri City Pharmacy. From the research conducted, it is proven that the ABCKM algorithm is proven to be better than the ABC algorithm and better than using the distribution route carried out by the current courier. From the research, the artificial bee colony algorithm achieves convergence in finding the best solution with a popsize of 70, a limit of 25, and a maximum iteration of 700. From the optimal parameters, the best fitness value is 0.012193.
Optimasi Rute Pendistribusian Produk Bebicare di Kabupaten Sidoarjo dengan Pendekatan Algoritma Genetika Ema Rosalina; Imam Cholissodin; Bayu Rahayudi
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 6 No 2 (2022): Februari 2022
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Distribution is the process of distributing products or services to other parties. Bebicare is an organic baby food product produced by PT. ANUGERAH JAYA MANDIRI. One of the branches of this company is Bebicare Sidoarjo branch. It has 25 outlets that sell products for two and a half hours every day. In the delivery process, there is often a delay in the arrival of products to outlets which results in switching customers to competing products and decreasing sales turnover. The purpose of this study was to find the optimal distribution route for Bebicare products. The method used in the process of finding the optimal distribution route for Bebicare products is to use a genetic algorithm. First, enter the distance data, then the data will be processed using a genetic algorithm, after which the results will be obtained in the form of a distribution route for the Bebicare product. From this study, optimal parameters were obtained in the form of a population of 190, a combination of Cr 0.6 Mr. 0.4, the generations 1150, and the shortest total distance of 118.25 kilometers. The program result route is more optimal than the original route because it has a shorter distance.
Pengembangan Aplikasi Manajemen Surat berbasis Web memanfaatkan Teknologi Integrasi Protokol IMAP Gmail (Studi Kasus: CV. Mandiri Nusantara) Rohimatus Sholihah; Bayu Rahayudi; Welly Purnomo
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 6 No 2 (2022): Februari 2022
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

The letter is a written communication medium to convey information to the intended party, either for individual or organizational purposes. Management of correspondence CV. Mandiri Nusantara is still done manually until now because the letters received and sent have various types and the number is not small as time goes by. If you still use conventional methods, you have a lot of risk of losing mail data, taking up a lot of space, making it difficult to get mail information, as well as correspondence management processes such as archiving, distributing, and making letters. In archiving there are incoming letters that are received directly in the form of physical documents, whereas some companies or agencies still send incoming letters in the form of physical documents to CVs. Mandiri Nusantara and incoming mail from Gmail. With the existing problems, it is necessary to develop a web-based mail management application to help manage correspondence. Between applications and Gmail can be integrated using the IMAP protocol, retrieve email messages every month from Gmail to be displayed on the application as a CV archive. Mandiri Nusantara. Using the Rapid Application Development (RAD) method in development even though it only requires a relatively fast and short time does not reduce product quality, only 60 - 90 days have maximum results. The results of the development of a web-based mail management application utilizing the IMAP Gmail protocol integration technology (Case Study: CV. Mandiri Nusantara) can assist in managing correspondence such as archiving, distributing, and creating letters and makes it easier to find mail information with 100% valid BlackBox testing results. and the test results for User Acceptance Testing (UAT) conducted by 3 examiners consisting of the director, finance, and the main manager of correspondence or administrators have 88% results, that the web-based mail management application has met the needs of users in managing CV correspondence. Mandiri Nusantara.
Optimasi Rute Distribusi Gas Lpg 3 Kg dengan Integrasi Algoritma K-Means dan Ant Colony Optimization pada Multiple Travelling Salesman Problem Liwenki Jus'ma Olivia; Bayu Rahayudi; Imam Cholissodin
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 6 No 2 (2022): Februari 2022
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Multiple Traveling Salesman Problem (TSP) is a development of the Traveling Salesman Problem in which the TSP only has one salesperson, while the M-TSP can have more than one salesperson With more than one sales, the distribution process will be faster and can reduce transportation costs. PT. Tegal Ombo Makmur is one of the companies that carry out distribution activities in which each salesperson will determine the route of the agent's address to be addressed and it is not uncommon to determine the route that is not efficient or not optimal so that it is a waste of time, energy, and costs. To solve the MTSP problem, this research proposes the use of the K-Means method and the Ant Colony Optimization (K-ACO) Algorithm. The K-Means method is used for optimal city division and then the shortest route will be searched using the ACO Algorithm. The best results were obtained with 4 salesmen and 91 points at the time of iteration at K-Means of 400, parameter NcMax or iterations is 3000, the value of is 1, the value of is 0.9,the value of is 0,9, and the value of is 0.04. Then the total distance generated by the system is 207.94 km, while the total route distance from the company is 466.45 km. Multiple Traveling Salesman Problem (TSP) is a development of the Traveling Salesman Problem in which the TSP only has one salesperson, while the M-TSP can have more than one salesperson With more than one sales, the distribution process will be faster and can reduce transportation costs. PT. Tegal Ombo Makmur is one of the companies that carry out distribution activities in which each salesperson will determine the route of the agent's address to be addressed and it is not uncommon to determine the route that is not efficient or not optimal so that it is a waste of time, energy, and costs. To solve the MTSP problem, this research proposes the use of the K-Means method and the Ant Colony Optimization (K-ACO) Algorithm. The K-Means method is used for optimal city division and then the shortest route will be searched using the ACO Algorithm. The best results were obtained with 4 salesmen and 91 points at the time of iteration at K-Means of 400, parameter NcMax or iterations is 3000, the value of is 1, the value of is 0.9,the value of is 0,9, and the value of is 0.04. Then the total distance generated by the system is 207.94 km, while the total route distance from the company is 466.45 km.
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