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All Journal International Journal of Electrical and Computer Engineering Jurnal Ilmu Komputer dan Informasi Lontar Komputer: Jurnal Ilmiah Teknologi Informasi Jurnal Neutrino : jurnal fisika dan aplikasinya Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic Jurnal Ilmiah Kursor Jurnal Mahasiswa Jurusan Arsitektur Jurnal Teknologi Informasi dan Ilmu Komputer Journal of Information Systems Engineering and Business Intelligence Jurnal Teknologi dan Sistem Komputer JOIV : International Journal on Informatics Visualization Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) International Journal of Artificial Intelligence Research Journal of Information Technology and Computer Science Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Jurnal Nasional Teknik Elektro dan Teknologi Informasi Journal of Management Research and Studies Lontar Komputer: Jurnal Ilmiah Teknologi Informasi
Fitra Abdurrachman Bachtiar
Fakultas Ilmu Komputer - Universitas Brawijaya
Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Library & Information Science Physics Social Sciences

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Perbandingan Holt's dan Winter's Exponential Smoothing untuk Peramalan Indeks Harga Konsumen Kelompok Transportasi, Komunikasi dan Jasa Keuangan Achmad Fahlevi; Fitra Abdurrachman Bachtiar; Budi Darma Setiawan
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 12 (2018): Desember 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Consumer Price Index (CPI) is one of the most commonly used indicators in measuring the inflation rate. CPI's group of Transportation, Communication and Financial Services have the second largest proportion on living cost with 19.15%. As the group who categorize as administered price (the price are ruled by the government), forcasting this group would help some parties involved in taking neccessery decision and avoiding significant inflation rate. In this research, forecasting were performed using two Exponential Smoothing method which is, Holt's Exponential Smoothing and Winters Exponential Smoothing. This method was evaluated by calculating average error rate using Mean Absolute Percentage Error (MAPE) method. There will be 120 data from January 2017 until December 2017 that used which taken from Bank Indonesia official websites. The results of the test was the best parameter value for Holt's Exponential Smoothing which is 𝛼 = 0.7 dan β = 0.1 and for Winters Exponential Smoothing 𝛼 = 0.1, β = 0.4 dan γ = 0.8. And from this parameter's value, MAPE's value obtained for Holt's Exponential Smoothing which 0.474% and for Winters Exponential Smoothing is 1.503%. Both of them got MAPE value under 10% that can be categorize as very good on forcasting CPI group of Transportation, Communication and Financial Services. And can be conclude either that Holt's Exponential Smoothing have better accuration rather than Winters Exponential Smoothing in Cosumer Price Index's group of Transportation, Communication and Financial Services.
Prediksi Kredit Macet Berdasarkan Preferensi Nasabah Menggunakan Metode Klasifikasi C4.5 pada Koperasi Simpan Pinjam Mitra Raya Wates Iqbal Taufiq Ahmad Nur; Nanang Yudi Setiawan; Fitra Abdurrachman Bachtiar
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 12 (2018): Desember 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Bad credit is the main problem that faced by financial institutions, especially cooperatives in Indonesia. This problem is also happened in KSP Mitra Raya Wates that does not use credit analyst and the decision making process is using an intuitive approach and based on existing experience that owned by KSP Leader. The survey process conducted at KSP Mitra Raya Wates also cannot guarantee that the loans made by customers are free from credit risk, considering there are customers who have bad credit from a total of all customers who have received loans. KSP Mitra Raya Wates needs a system that capable of supporting decision to detect credit quality early on. C4.5 method can be used to predict customers' credit quality by generating rule in form of decision tree. The results of confusion matrix have accuracy of 94.5946. While based on the ROC curve, it generated AUC value of 0.9689. The level of usability generated by utilizing SUS is 82.5. The output is dashboard visualization with several graphs containing the percentage, time-series and trend of total submissions that have been made and also forms that can be used by KSP Mitra Raya Wates to make predictions of customer credit application and also dataset entry into the system.
Analisis Sentimen Opini Pelanggan Terhadap Aspek Pariwisata Pantai Malang Selatan Menggunakan TF-IDF dan Support Vector Machine Yoga Tika Pratama; Fitra Abdurrachman Bachtiar; Nanang Yudi Setiawan
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 12 (2018): Desember 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Department of Tourism and Culture (Disparbud) of Malang Regency requires the customer's perspective in the process of monitoring and evaluation of management and development activities of South Malang beach tourism. But Disparbud neither have the data about the customer's opinion, nor the application of technology on data processing and data analysis that capable of providing information about customer's perspective on aspects of South Malang beach tourism. The customer's perspective can be obtained from customer's opinions in the form of review that available on the web platform. Web Scraping is a method for extraction of customer's opinion data sourced from the web platform. To get the information about customer's perspective on aspects of South Malang beach tourism could be done by performing Aspect Level Sentiment Analysis on the customer's opinion data. One of many classification methods is the Support Vector Machine, which can be used to classify sentiments in sentiment analysis process. This research managed to get 674 customer's opinion data in Bahasa Indonesia ranged from 2013 to 2018 for 43 tourist attractions of South Malang beach tourism sourced from TripAdvisor. The tests that have been conducted on the results of the sentiment classification for all aspects resulted good results in an average of 85% on accuracy, 85% on precision, 87% on recall, and 85% on F1-Score. The output of this research is in form of data visualization in the form of Dashboard consisted of 4 Dashboards which contains results from the process of sentiment analysis on the customer opinions to aspects of South Malang beach tourism.
Evaluasi dan Rekomendasi Tampilan Website E-Complaint Universitas Brawijaya Pada Perangkat Bergerak Menggunakan Metode Heuristic Evaluation Wahyu Satriyo Wibowo; Hanifah Muslimah Az-Zahra; Fitra Abdurrachman Bachtiar
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 2 No 12 (2018): Desember 2018
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Usability issues of Brawijaya University's E-Complaint website, particularly any of those issues faced by mobile device users due to less responsive display, receive considerable attention because they affect user's perspective on the website. Thus, a usability evaluation was done by applying heuristic evaluation method to fix the issue faced by the users. These experts relied on provided 13 heuristic mobile checklists to conduct the evaluation. Usability assessment was also conducted on the user's side by utilizing System Usability Scale (SUS) and it was complemented with interview with 8 respondents who were categorized into 2 groups: Brawijaya's scholars and general public. The heuristic evaluation highlighted 66 issues in total which were then summarized into 27 issues including issues found during interview with the respondents. Those results were then used for revision. UB's E-Complaint website display improvement was based on the collected guidelines, expert solutions, and user feedback. This improvement lowered the number of issues found by the experts, from 66 into 29 issues with average severity rating of 1,80 (it was previously 2,84). User satisfaction was also improved from SUS score of 44.38 into 72.5 and was supported by positive responses received from the interviews. SUS score indicated that there were some improvements in adjective rating from “OK” to “Good”, in grade scale from “F” to “C”, and in acceptability from “not acceptable” into “acceptable”.
Peringkasan Multi-Dokumen Berbasis Clustering pada Sistem Temu Kembali Berita Online Menggunakan Metode K-Means Amalia Kusuma Akaresti; Mochammad Ali Fauzi; Fitra Abdurrachman Bachtiar
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 1 (2019): Januari 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

The growing number of online news sites resulted in an explosion of information and information redundancy occurred. On this issue it takes the search engine to make it easier for users to find information, but users still have to read it one by one, therefore it needs also a summary system. Therefore a summary system is required to facilitate Internet users avoid getting the same information from different sources. In this study, multi-document clustering based on online news retrieval system using K-Means method. The process of searching system using Cosine Similarity method and on the summary using K-Means Clustering method. The results show that the optimum results in the recall system are Recall 71%, Presicion 65.82%, F-Measure 66.35% and on Recall system of Recall 37.3%, Presicion 18%, F-Measure 19.2%.
Evaluasi Kualitas Website Terhadap Kepuasan Masyarakat Menggunakan Metode Webqual 4.0 dan Importance Performance Analysis (IPA) (Studi Kasus pada Website disperkim.malangkota.go.id Dinas Perumahan dan Kawasan Permukiman Kota Malang) Ikrom Septian Hadi; Satrio Hadi Wijoyo; Fitra Abdurrachman Bachtiar
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 1 (2019): Januari 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

The purpose of this study to obtain results of the evaluation of website use WebQual disprekim.malangkota.go.id 4.0 and get advice on website disperkim.malangkota.go.id using the guidelines and methods of science. The method used in the evaluation of the Department of Housing and Settlement website Malang was that WebQual 4.0 to 3 dimensions as well as methods lmportance and Performance Analysis (LPA), which consists of a conformance level analysis, gap analysis, and analysis of LPA quadrant. The results of the analysis of the quality of Website Department of Housing and Settlement Region Malang shows that the website has a concordance rate of <100% is equal to 94.53%, means that the Website performance level Department of Housing and Settlement Region Malang is still below the level of interest or not in accordance with user expectations. Average Average value gap (GAP) on the Website of Housing and Settlement Region Malang were negative (<0) is equal to -0.24, the results showed that the level of performance Website Department of Housing and Settlement Region Malang is still lacking and has not met expectations users
Segmentasi Pelanggan Menggunakan Metode Fuzzy C-Means Clustering Berdasarkan LRFM Model Pada Toko Sepatu (Studi Kasus: Ride Inc Kota Malang) Muhammad Taufik Dharmawan; Nanang Yudi Setiawan; Fitra Abdurrachman Bachtiar
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 2 (2019): Februari 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Ride Inc. is a leather shoe store established in 2012 in the city of Malang. Customer data owned has not been utilized to obtain values that are able to help Ride Inc. in creating business strategies to gain and retain customers. Customer segmentation is groups of customers who have a similarity of characteristics that able to provide information. The characteristics of customers can be seen by applying LRFM (Length, Recency, Frequency, and Monetary) model. Methods used in grouping customers are Fuzzy C-Means clustering. Elbow method used to help the process of determining the best number of clusters iteratively. The data used from the Ride Inc. are 522 customers data in the period of July 2017 until March 2018. The results shows that there are two and three clusters that formed based on elbow method that are then implemented into the Fuzzy C-Means. Customer segment analysis based on the LRFM model formed in the rank of profitable customer group based on the highest value of L, F, and also M and the lowest R. Dashboard visualization become the output of the research based on the value of the given LRFM to Ride Inc. The average score of usability testing from 2 respondents is 65. This means that Ride Inc. receive the dashboard visualization.
Analisis Segmentasi Pelanggan Dengan RFM Model Pada Pt. Arthamas Citra Mandiri Menggunakan Metode Fuzzy C-Means Clustering Wiratama Ahsani Taqwim; Nanang Yudi Setiawan; Fitra Abdurrachman Bachtiar
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 2 (2019): Februari 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

PT. Arthamas Citra Mandiri is a money changer company. The company has not applied CRM (Customer Relationship Management) so that company still applying the same service to all customers. Some customers often have transactions, but on the other sides, some customers are rarely. The data used in this research is the transaction history from January 2017 until December 2017 and it including 981 transactions. Segmentation is a process to identify customers so it can help us to know the profitable customers for the company. The characteristics of the customers could be seen from RFM (Recency, Frequency, Monetary) which means Recency (the last customer transaction), Frequency (the number of transactions), and Monetary (the amount of money spend). One of the clustering methods that can be used in this research is Fuzzy C-Means. Elbow method is used to help the researcher determine the best cluster for Fuzzy C-Means. Partition Coefficient and Euclidean Distance are validation methods to knowing the best cluster. In this research, cluster 3 is the best results. Cluster results are visualized by the dashboard with some graphics which contains segmentation customer based on RFM value of PT. Arthamas Citra Mandiri customers transactions. Dashboard visualization is given to the company and researcher doing usability testing to know the effectiveness of the dashboard visualization. The results of the usability testings are 77.5. It means the dashboard is an acceptable categorized or can be accepted by the company.
Pengembangan Aplikasi E-Learning Dengan Menerapkan Metode Gamification Irwan Suprianto; Fajar Pradana; Fitra Abdurrachman Bachtiar
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 2 (2019): Februari 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Online learning platform, also known as e-learning is a very popular media for education these days. the lack of interest from the students to the media used by the school are the main cause for the ineffective of the e-learning. interest and student satisfaction are influenced by some factor such as the feature and content does not help the student finishes their assignment so they decided not to use the application again. in order to combat these problems, a new e-learning app are developed implementing game method for the feature and content. This method are called Gamification. interest is the main target for gamification
Peringkasan Teks Untuk Deteksi Kejadian Pada Dokumen Twitter Berbahasa Indonesia Dengan Metode Affinity Propagation Rezky Dermawan; Fitra A. Bachtiar; Putra Pandu Adikara
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 3 No 3 (2019): Maret 2019
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Twitter is on of many social medias where the user often tell about events that are happenings around them, ranging from insignificant to important things. Twitter's qualities where the user could make a tweet anywhere in a brief time frame, make it feasible for critical information to appear before the media even report it. However, it is difficult to comprehend what relevant events are occuring in a specific region because of the sheer size of scale and diverse sort of tweets. Accordingly, there is a need of a framework that could do pertinent event detection and give a summary about that event. In light of the reason expressed over, this research center around text summarization for event detection of Indonesian Twitter archive utilizing Affinity Propagation. Through the process of clustering, the resulting clusters become the representation of events occuring in a specific place and time period. Two kinds of data are used for assessment, first is themathic which has spesific kind of event happening in the time frame of the tweet and second is generic where the tweet are taken from an arbitary time frame. In order to get the best resulting cluster, parametesr of Affinity Propagation are evaluated reuslting in preference of quartile 3 dan minimum, damping factor of 0,3 and 0,5, changed limit of 1 and 2, iteration maximum of 250 as the best parameters for the thematic and generic data. The result of tweet summary from the clustering process are then compared with a specialist's summary to be evaluated by ROGUE-N method, scoring 0,459 and 0,4009 respectively on two kinds of data.
Co-Authors AA Sudharmawan, AA Abidatul Izzah Abu Wildan Mucholladin Achmad Arwan Achmad Basuki Achmad Basuki Achmad Fahlevi Achmad Firmansyah Sulaeman Achmad Hanim Nur Wahid Achmad Ridok Adam Hendra Brata Adam Syarif Hidayatullah Adhia, Nabila Nur Fajri Adinugroho, Sigit Aditya Rachmadi Aditya Rachmadi, Aditya Admaja Dwi Herlambang, Admaja Dwi Afida, Latansa Nurry Izza Afifurrijal Afifurrijal Agus Wahyu Widodo Ahmad Afif Supianto Ahmad Afif Supianto Ahmad Afif Supianto Ahmad Afif Supianto Ahmad Fairuzabadi Aisyah Awalina Aisyatul Maulidah Akhmad Lazuardi Al Ikhsan, Mochammad Dearifaldi Alaikal Fajri Nur Alfian Aldi Fianda Putra Aldo, Muhammad Alfi Nur Rusydi Alfian, Kharis Alfin Taufiqurrahman Alfirsa Damasyifa Fauzulhaq Alhasyimi, Dana Mustofa Amadea, Karina Amalia Kusuma Akaresti Amrillah, Muhammad Ifa Andi Alifsyah Dyasham Anggit Chalilur Rahman Anita Rizky Agustina Anita Rizky Agustina Anjasari, Ni Luh Made Beathris Anjumi Kholifatu Rahmatika Annuranda, Ramansyah Eka Apriyanti -, Apriyanti Ardi Wicaksono ari kusyanti Arieftia Wicaksono Arifien, Zainal Aulia Dewi Savitri Aulia Nurrahma Rosanti Paidja Aulia Septi Pertiwi Awalina, Aisyah Azhar Izzannada Elbachtiar Azizah, Rizky Adinda Azzam Syawqi Aziz Azzam, Ja'far Shidqul Baharudin Yusuf Widiyanto Barlian Henryranu Prasetio Bayu Aji Firmansyah Bayu Priyambadha Benni A. Nugroho Bere, Stevania Biabdillah, Fajerin Bianca Pingkan Nevista Bintang Fajrianti Budi Darma Setiawan Budi Setiawan Cahya, Reiza Adi Cinthia Vairra Hudiyanti Dariswan Janweri Perangin-Angin Darmawan, Riski Dary Ardiansyah Haryono Dea Zakia Nathania Dedi Romario Delpiero, Rangga Raditya Desy Setya Rositasari Dewi, Elok Nuraida Kusuma Dian Eka Ratnawati Dika Imantika Dimas Angga Nazaruddin Dinda Adimanggala Dito William Hamonangan Gultom Diva Fardiana Risa Djoko Pramono Dona Adittia Dyah Ayu Wulandari Dyah Ayu Wulandari Dyah Ayu Wulandari Dzar Romaita Eka Devi Prasetiya Eka Yuni Darmayanti Eko Laksono Eko Setiawan Fabiansyah Cahyo Kuncoro Pradipta Fahrezy, Ahmad Faizatul Amalia Fajar Pradana Faranisa, Puspa Ayu Fardan Ainul Yaqiin Farhan Setya Dhitama Farhansyah, Brahma Hanif Farid Syauqi Nirwan Fasya Ghassani Hadiyan Fatwa Ramdani, Fatwa Ferdian Maulana Akbar Ferry Ardianto Rismawan Ficry Agam Fathurrachman Fikar Mukamal Gandhi Ramadhona Gembong Edhi Setyawan Giga Setiawan Gregorius Dhanasatya Pudyakinarya Gultom, Dito William Hamonangan Gunawan, Alifi Haikal, Raihan Hanif Prasetyo Maulidina Hanifah Khoirunnisak Hanifah Muslimah Az-Zahra Hanifah Muslimah Az-Zahra, Hanifah Muslimah Haryowinoto Rizqul Aktsar Hasyir Daffa Ibrahim Hayashi, Yusuke Herman Tolle Heryana, Ana Hidayatullah, Adam Syarif Hirashima, Tsukasa Holiyanda Husada Hutamaputra, William Ihza Razan Alghifari Ikhsan Putra Arisandi Ikrom Septian Hadi Ilham Pambudi Imam Cholissodin Imam Cholissodin Indra Kurniawan Syahputra Indriati Indriati Indriati Indriati Indriati Indriati Indriati Intan Yusuf Habibie Iqbal Taufiq Ahmad Nur Irfani, Ilham Irma Nurvianti Irwan Suprianto Irwanto, M. Sofyan Issa Arwani Istanto, Raga Saputra Heri Ivqonnada Al Mufarrih Joseph Ananda Sugihdharma Joseph Ananda Sugihdharma Julia Ferlin Kartiko, Erik Yohan Katrina Puspita Kevin Gusti Farras Fari&#039; Utomo Kharis Alfian Khoirullah, Habib Bahari Kresna Hafizh Muhaimin Krisnabayu, Rifky Yunus Krisnandi, Dikdik Kuncahyo Setyo Nugroho Kurnia Fakhrul Izza Kurniawan, Rafi Athallah Kusumo, R. Budiarianto Suryo Lailil Muflikhah Larasati, Sza Sza Amulya Lathania, Laela Salma Ludgerus Darell Perwara Luthfi Afrizal Ardhani M Reza Syahputra A M. Ali Fauzi M. Khusnul Azhari M. Raabith Rifqi Mar'i, Farhanna Marji Marvel Timothy Raphael Manullang Maulidah, Aisyatul Mawarni, Marrisaeka Moch Irfan Prayudha Adhianto Mochamad Chandra Saputra Mochamad Havid Albar Purnomo Mochammad Dearifaldi Al Ikhsan Moh Iqbal Yusron Mufidatun Nuha Muh. Edo Aprillia Andilala Muhammad Ferdyandi Muhammad Tanzil Furqon Muhammad Taufik Dharmawan Muhammad Wafi Muhammad Zulfikarrahman Nabila Leksana Putri Nabila Lubna Irbakanisa Nadifa, Rahajeng Mufti Nainggolan, Cesilia Natasya Nanang Yudi Setiawan Nanang Yudi Setiawan Nanang Yudi Setyawan Nanda Ajeng Kartini Nanda Samsu Dhuha Nasita Ratih Damayanti Nevista, Bianca Pingkan Nourman Hajar Novanto Yudistira Novi Sunu Sri Giriwati Novianti, Siska Nur Wahyu Melliano Hariyanto Nur, Iqbal Taufiq Ahmad Nurafifah Alya Farahisya Nurkhoyri, Ageng Nurul Hidayat Oddy Aulia Rahman Nugroho Okta Dwi Ariska Pamungkas, Gilang Alif Pangestu, Gusti Pradana , Fajar Priyambadha, Bayu Pryono, Muhammad Adam Puras Handharmahua Purnomo, Fawwaz Anrico Putra Pandu Adikara Rafif Taqiuddin Rafif Taqiuddin Rafly, Andi Rahman, Rafli Rahmat Adi Setiawan Ramadhan, Muhammad Fitrah Ramadhianti, Fatiha Randy Cahya Wihandika Randy Cahya Wihandika Ratih Kartika Dewi Refi Fadholi Rekyan Regasari Mardi Putri, Rekyan Regasari Mardi Renavitasari, Ivenulut Rizki Diaz Retno Indah Rokhmawati Retno Indah Rokhmawati, Retno Indah Revanza, Muhammad Nugraha Delta Reza Syahputra Rezka Aditya Nugraha Hasan Rezky Dermawan Rhobith, Muhammad Rian Nugroho Ridwan Adi Setiabudi Risa, Diva Fardiana Riski Darmawan Riza Setiawan Soetedjo Rizal Setya Perdana Rizkey Wijayanto Rizkia Desi Yudiari Rizky Adinda Azizah Rizky Muhammad Faris Prakoso Robi Dwi Setiawan Rochmawanti, Ovy Rona Salsabila Said Atharillah Alifka Alhabsyi Salsabila, Rona Samuel Arthur Satrio Agung Wicaksono Satrio Agung Wicaksono Satrio Hadi Wijoyo Satrio Hadi Wijoyo Satyawan Agung Nugroho Satyawan Agung Nugroho Shinta Aprilisia Sifaunnufus Ms, Fi Imanur Sigit Adinugroho Sinana, Admi Rut Sintiya, Karena Siswahyudi, Puad Siti Mutdilah Sofyanda, Erika Yussi Sri Wulan Utami Vitandy Sueddi Sihotang Sugihdharma, Joseph Ananda Sulandri, Sulandri Sutawijaya, Bayu Syahidi, Aulia Akhrian Syahputra, Indra K. Taufik Hidayat Timothy Julian Tirana Noor Fatyanosa, Tirana Noor Titus Christian Ubaydillah, Achmad Afif Utaminingrum, Fitri Vasha Farisi Sarwan Halim Very Sugiarto, Very Vivy Junita Wafi, Muhammad Wahyu Ardiansyah, Mohammad Wahyu Satriyo Wibowo Wahyudi, Hafif Bustani Wayan F. Mahmudy Wayan Firdaus Mahmudy Welly Purnomo Whita Parasati Wicaksono, Satrio A. Wicky Prabowo Juliastoro Windy Adira Istiqhfarani Wiratama Ahsani Taqwim Wirdhayanti Paulina Yoga Tika Pratama Yudi Muliawan Yuita Arum Sari Zayn, Afta Ramadhan Zulfikarrahman, Muhammad