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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Jurnal Sains dan Teknologi TELKOMNIKA (Telecommunication Computing Electronics and Control) CESS (Journal of Computer Engineering, System and Science) Proceeding of the Electrical Engineering Computer Science and Informatics JOIN (Jurnal Online Informatika) SISFOTENIKA JURNAL MEDIA INFORMATIKA BUDIDARMA Jurnal Pilar Nusa Mandiri Jurnal Mantik Penusa JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI ILKOM Jurnal Ilmiah Jiko (Jurnal Informatika dan komputer) JSiI (Jurnal Sistem Informasi) Jurnal Pengembangan Riset dan Observasi Teknik Informatika JURIKOM (Jurnal Riset Komputer) Jurnal Riset Informatika JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) TELKA - Telekomunikasi, Elektronika, Komputasi dan Kontrol Building of Informatics, Technology and Science Jurnal Mantik Aisyah Journal of Informatics and Electrical Engineering INTI Nusa Mandiri Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) JATI (Jurnal Mahasiswa Teknik Informatika) Jurnal Teknik Informatika C.I.T. Medicom Journal of Intelligent Decision Support System (IDSS) JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Journal of Computer System and Informatics (JoSYC) Jurnal Sistem Komputer dan Informatika (JSON) Jurnal Teknik Informatika (JUTIF) Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer) RESOLUSI : REKAYASA TEKNIK INFORMATIKA DAN INFORMASI JPM: JURNAL PENGABDIAN MASYARAKAT Journal La Multiapp KLIK: Kajian Ilmiah Informatika dan Komputer International Journal of Basic and Applied Science JUSTIN (Jurnal Sistem dan Teknologi Informasi) PROSISKO : Jurnal Pengembangan Riset dan observasi Rekayasa Sistem Komputer SAGA: Journal of Technology and Information Systems Journal International Journal of Teaching and Learning (INJOTEL) INTERNATIONAL JOURNAL OF SOCIETY REVIEWS (INJOSER) Journal of Blockchain, Nfts and Metaverse Technology
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Penerapan Data Mining Untuk Mengukur Kepuasan Mahasiswa Terhadap Pembelajaran dengan Menggunakan Algoritma Naïve Bayes Agung Triayudi; Gatot Soepriyono
Journal of Computer System and Informatics (JoSYC) Vol 4 No 1 (2022): November 2022
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v4i1.2524

Abstract

Education is very important for life, with education can help in improving Human Resources (HR). Human Resources (HR) in universities are students. Increased competence in students carried out in higher education is carried out by learning. The process carried out in learning is very influential on the results obtained from learning both competencies and abilities possessed by students. Based on this, it is necessary to improve learning in higher education in order to support good results. Measuring the level of student satisfaction with learning can measure the extent to which the learning process has been carried out. The process of measuring the level of student satisfaction with learning is done first by collecting data. After collecting data, the data processing process is carried out to get the expected results. Errors in the data processing process, the results obtained are also not in accordance with the objectives carried out. Therefore, to solve the problem it is necessary to do it with the right process by using a separate method or technique where the method is data mining. Data mining is a method or technique used for data processing. The data processing process carried out in data mining is carried out on large data. The Naïve Bayes algorithm is an algorithm that is included in the classification of data mining techniques. Where the process in the nave Bayes algorithm is very dependent on the grouping process carried out on each attribute and also the target class of each object. The results of the study show that the probability value of PUAS is 0.034108116 and the probability value of NOT SATISFIED is 0. This indicates that the result of decision making is SATISFIED.
DATA MINING K-MEDOIDS DAN K-MEANS UNTUK PENGELOMPOKAN POTENSI PRODUKSI KELAPA SAWIT DI INDONESIA Faiq Husain Pratama; Agung Triayudi; Eri Mardiani
JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Vol 7, No 4 (2022)
Publisher : STKIP PGRI Tulungagung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29100/jipi.v7i4.3237

Abstract

Kelapa sawit merupakan tanaman golongan palma yang memiliki periode produksi setiap tahunnya. Penyebaran terbesar kelapa sawit berada di Indonesia. Indonesia memiliki luas perkebunan mencapai 17,32 juta hektar. Detailnya hasil produksi 26,57 ton dengan luas kebun 8,51 juta hektar. Menurut data USDA, pada tahun 2022 menurun karena berbagai faktor. Untuk itu perlu dilakukan klasifikasi potensi produksi kelapa sawit dan identifikasi peluang keberhasilan produksi disetiap lokasi perkebunan kelapa sawit. Dengan ini dilakukan penelitian pembuatan sistem clustering untuk melihat potensi produksi kelapa sawit dengan memakai kombinasi 2 metode yaitu K-Medoids dan K-Means. K-Medoids berfungsi untuk penentuan cluster sesuai dengan data variable yang paling rendah(Cluster 1) 18 wilayah, sedang (Cluster 2) 5 wilayah, dan tinggi (Cluster 3)/(Cemtroid) 2 wilayah pada potensi hasil Luas areal, produksi, dan produktivitas kelapa sawit. Algoritma K-Means berfungi untuk mengelompokkan rata rata luas tanah 514.885,72 Ha, produksi 1.931.882,84 Ton dan produktifitas 3.227,08 Kg/Ha, dengan pembagian potensi rendah, sedang dan tinggi. Kombinasi dari kedua algoritma berfungsi sangat baik karena masing masing memiliki peran tersendiri yang sesuai dengan kebutuan penelitian. Dari penggabungan 2 metode K-Medoids dan K-Means mendaptkan hasil ketiga klaster bahwa hasil produksi kelapa sawit yang memiliki potensi rendah 72% sedang 20%, tinggi 2%. Segmentasi ini disebabkan oleh kesamaan karakteristik perkebunan berdasarkan kesamaan dari luas, produksi, dan produktivitas. Yang memiliki potensi produksi tertinggi kelapa sawit ada 2 provinsi yaitu Kalimantan Barat dan Riau.
PENERAPAN METODE DESIGN THINKING DALAM RANCANG APLIKASI PENANGANAN LAPORAN PENCURIAN BARANG BERHARGA DI POLSEK SUKMAJAYA apiek maniek; Agung Triayudi; Albaar Rubhasy
JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Vol 6, No 2 (2021)
Publisher : STKIP PGRI Tulungagung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29100/jipi.v6i2.2026

Abstract

Instruksi Maraknya kasus pencurian di Indonesia masih terus melanda masyarakat sehingga perlu ditindak lanjuti dan diantisipasi. Secara umum motivasi pelaku kejahatan adalah untuk memenuhi kebutuhan yang relatif sulit, salah satunya adalah minimnya ketersediaan lapangan pekerjaan. Tidak sedikit masyarakat pernah mengalami kasus pencurian barang dan tidak mengetahui prosedur perlaporan perkara ke pihak berwajib. Pembuatan dan pengelolaan laporan polisi yang bersifat manual seringkali menjadi kendala bagi Pusat Pelayanan Polsek Sukmajaya, perlu sigap dan akurat dalam menangani laporan kepolisian, antara lain dalam memantau jumlah laporan. Di era digital ini, informasi yang terbatas ini dapat memudahkan masyarakat dalam menyampaikan laporan pencurian barang melalui aplikasi mobile smartphone dengan memanfaatkan pesatnya perkembangan teknologi informasi dan komunikasi. Perancangan ini menggunakan metode Design Thinking pada sistem aplikasi penangan laporan pencurian barang. Model desain aplikasi bertindak sebagai perantara, membantu memfasilitasi pertukaran informasi antara korban dan pihak berwenang.
PERBANDINGAN ALGORITMA K-MEANS DENGAN K-MEDOIDS PADA PENGELOMPOKAN ARMADA KENDARAAN TRUK BERDASARKAN PRODUKTIVITAS Aceng Supriyadi; Agung Triayudi; Ira Diana Sholihati
JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Vol 6, No 2 (2021)
Publisher : STKIP PGRI Tulungagung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29100/jipi.v6i2.2008

Abstract

Armada kendaraan truk merupakan salah satu aset utama dalam bisnis di bidang jasa transportasi. Evaluasi kinerja amada secara cepat dan akurat diperlukan untuk mendukung tercapainya produktivitas armada secara maksimal sehingga target perusahaan dapat mudah tercapai. Proses evaluasi kinerja armada yang masih dilakukan secara manual menyebabkan rumitnya proses pengolahan dan kurang akurat nya hasil evaluasi yang diperoleh, sehingga diperlukan suatu teknik pengolahan data secara cepat dan lebih akurat salah satunya dengan namun menerapkan teknik data mining menggunakan metode clustering. Metode Clustering akan digunakan untuk mengelompokkan setiap armada kendaraan berdasarkan produktivitas kinerjanya. Penelitian ini membandingkan penerapan Algoritma K-Means dan K-Medoids, yang kemudian dilakukan uji validitas terhadap hasil cluster yang terbentuk. Davies Bouldin Index sebagai metode dalam analisis klaster menghasilkan nilai validitas sebesar 0,67 untuk K-Means clustering dan 1,78 untuk K-Medoids. Berdasarkan nilai validitas yang dihasilkan Algoritma K-Means dipilih untuk diimplementasikan pada pembuatan aplikasi clustering armada kendaraan berbasis web karena paling relevan dengan nilai validitas DBI yang lebih rendah dari pada K-Medoids. Pengujian yang telah dilakukan terhadap hasil clustering pada aplikasi web didapatkan persentase kesesuaian sebesar 97 % baik dengan tool Rapidminer maupun dengan perhitungan secara manual
E – LIVING CO. SISTEM INFORMASI WEB PENYEWAAN RUMAH TINGGAL (KONTRAKAN/KOST) DI DAERAH JAKARTA SELATAN Ahmad Arief Fadila; Agung Triayudi; Eri Mardiani
JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Vol 7, No 4 (2022)
Publisher : STKIP PGRI Tulungagung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29100/jipi.v7i4.3227

Abstract

Dari penelitian yang dilakukan  penulis dapat disimpulkan bahwa permasalahan saat ini adalah merancang sebuah sistem informasi perumahan (pensiun/sewa) berbasis website dengan tujuan untuk mempermudah sistem kerja di E Living Co, karena sistem yang lama adalah masih berbasis sistem akuntansi, sehingga kurang akurat dalam pencatatan dan kurang efisien. Untuk keperluan penelitian ini, penulis bermaksud untuk membangun sebuah sistem informasi perumahan (akomodasi/sewa) berbasis website, sistem informasi ini akan dibangun dengan menggunakan metode waterfall, yaitu suatu metode yang menunjukkan pendekatan sekuensial dan sistematis. Dalam perancangan ini penulis menggunakan  bahasa pemrograman yang berbeda berupa  html, css, php dan my sql serta memanfaatkan use case diagram dan activity diagram dalam deskripsi cara kerja website. Pada pengujian sistem penulis menggunakan j-meter dengan lima kali percobaan terhadap 10.000 data, 20.000 data, 30.000 data, 40.000 data dan 50.000 data. Dan waktu respon yang paling besar ialah data yang berjumlah 50.000 data dengan ukuran 447 KB dengan waktu respon sistem 0.4 detik lalu sedangkan data yang 10.000 data dengan ukuran size 393 KB waktu responnya 0,3 detik
Diagnosa Kelainan Jantung dengan Pendekatan Fuzzy Logic Mamdani Sumiati Sumiati; Haris Triono Sigit; Agung Triayudi; Melisa Theresia
TELKA - Jurnal Telekomunikasi, Elektronika, Komputasi dan Kontrol Vol 8, No 2 (2022): TELKA
Publisher : Jurusan Teknik Elektro UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/telka.v8n2.149-157

Abstract

Penyakit jantung merupakan penyebab utama kematian yang menduduki peringkat satu di Indonesia. Oleh karena itu, dokter perlu mendeteksi sejak dini penyakit jantung pada pasien. Dalam mendiagnosa penyakit jantung diperlukan sebuah alat untuk mengetahui kondisi fisik jantung. Alat yang sering digunakan adalah Elektrokardiogram (EKG). Alat EKG ini dapat memantau aktivitas listrik jantung yang ditampilkan dalam bentuk grafik. Namun, alat EKG ini dinilai belum mampu mendeteksi secara otomatis keadaan jantung pasien. Oleh karena itu, pada penelitian ini dikembangkan sebuah aplikasi untuk mengidentifikasi kelainan jantung secara otomatis berbasis metode Fuzzy Mamdani dengan menggunakan 100 data hasil rekam medis Elektrokardiogram. Sistem yang dikembangkan mampu mengidentifikasi kondisi jantung pasien dalam dua kategori yaitu kondisi jantung yang normal dan kondisi jantung yang abnormal. Adanya sistem ini dapat membantu dokter dalam melakukan pemeriksaan kondisi jantung. Berdasarkan hasil pengujian sistem dengan pendekatan success rate mendapat nilai True positive 0,9%, nilai False Positive 0%, nilai success rate sebesar 95%, dan nilai error rate sebesar 0,05 %.Heart disease is the number one cause of death in Indonesia. Therefore, doctors need to detect early heart disease in patients. In diagnosing heart disease, a tool is needed to determine the physical condition of the heart. The tool often used is the electrocardiogram (EKG). This EKG tool can compile the heart's electrical activity, which is displayed in graphic form. However, this EKG tool cannot detect the patient's heart condition automatically. Therefore, this study developed a system to detect cardiac abnormalities using the Fuzzy Mamdani method using 100 electrocardiogram medical record data. The developed system can identify the patient's heart condition, namely normal heart and abnormal heart conditions. The existence of this system can assist doctors in examining heart conditions. Based on the results of system testing using the success rate approach, a True positive value of 0.9%, a False Positive value of 0%, a success rate of 95%, and an error rate of 0.05%.
Analisis Sentimen Vaksinasi Booster Berdasarkan Twitter Menggunakan Algoritma Naïve Bayes dan K-NN Afid Rozaqi; Agung Triayudi; Rima Tamara Aldisa
Jurnal Sistem Komputer dan Informatika (JSON) Vol 4, No 1 (2022): September 2022
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/json.v4i1.4907

Abstract

Covid-19 or the corona virus has spread throughout the world, one of which is Indonesia. There have been many problems due to this virus for 2 years in Indonesia, and various efforts and policies have been made by the government to control the impact that does not become worse by this corona virus, these efforts are vaccination actions against the Indonesian people, and in early 2022 the government started a new program, namely booster vaccination. Many people are pro and contra to the program on social media Twitter. This study was conducted with the aim of knowing the sentiment of Indonesians towards booster vaccination in Indonesia.The data obtained as many as 2000 tweets obtained from the keyword "booster vaccine" on Twitter. Then the data is divided into training data and test data (training) then made into three different portions, namely 60/40, 70/30, and 80/20. The test results are that the best performance is found in testing a portion of 80% of the training data 20% of the test data using the K-NN algorithm, the test produced the highest value results, namely 78.62% accuracy and AUC 0.845 and categorized as good classification. The results show that the K-NN algorithm model with an 80% portion of training data is the best in the classification of booster vaccination sentiment analysis. The sentiment results in the test data were positive with 303 tweet data and negative sentiment totaled 93 tweet data. The results of more positive sentiments show that booster vaccinations in Indonesia are acceptable and get a lot of support from the Indonesian people on social media Twitter.
Implementasi Klasifikasi Data Mining Untuk Penentuan Kelayakan Pemberian Kredit dengan Menggunakan Algoritma Naïve Bayes Agung Triayudi; Sumiati Sumiati
Jurnal Sistem Komputer dan Informatika (JSON) Vol 4, No 1 (2022): September 2022
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/json.v4i1.4653

Abstract

Credit today is very widely used in the transaction process. At first, lending was only done by banks, but with the development of time and also the increasing needs and purchases from the public, lending is not only done by banks. The granting of credit for financing goods by the company to the buyer is not done haphazardly, but must go through several selection processes. The process of granting credit must be carried out through detailed and strict stages. This causes the process to be lengthy and also lengthens the work of the selection team. Data mining is a data processing technique that is useful for obtaining important patterns from data sets. The Naïve Bayes algorithm is part of the data mining classification process. The process of the Naïve Bayes algorithm is based on the concept of the Bayes theorem. The result of the research is that the new alternative data is ACCEPTABLE for credit applications, it can be seen that the probability value of ACCEPTED is greater than the probability value of REJECTED, which is 0.011108
Pembangunan Smart Detection Absensi Berbasis Kartu RFID dan ESP 32 Fikri Fajar Asshiddiqi; Agung Triayudi; Rima Tamara Aldisa
Jurnal Sistem Komputer dan Informatika (JSON) Vol 4, No 1 (2022): September 2022
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/json.v4i1.4912

Abstract

In today's era with the rapid development of technology and the development of semiconductor technology, it is possible to create integrated circuits on an increasingly large scale and can integrate many different systems. One of the benefits of current technological developments in the attendance recording tool, whose data is integrated into the learning information system to replace the manual recording model. This tool is designed by integrating the work of a radio frequency identification (RFID) microcontroller into one system. The extracted data as a unique number from the RFID tag is used as student data. After the card is attached to the assessment device, student data will automatically be entered into the attendance database. By making this tool, it can facilitate the work and activities of students and lecturers in conducting lecture activities and also as learning for all in this period of rapid technological development
Implementation of the waste volume clustering method at company "x" to reduce the amount of waste using the k-medoids algorithm Agung Triayudi
International Journal of Basic and Applied Science Vol. 11 No. 2 (2022): Sep: Basic and Applied Science
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/ijobas.v11i2.73

Abstract

Garbage/waste is the residue of human daily activities or comes from natural processes in solid form. Some of the causes that affect the environment are the problems of managing and disposing of waste/household waste. Company "X" is a company engaged in waste transportation services and non-hazardous waste management for business sectors such as apartments, offices, hospitals, and hotels. In this problem, there is an increase in the cubication of household waste produced by the vendor company "X" every month. Data mining is the extraction of information. Identify hidden information from large amounts of data, leverage and promote knowledge in real-time applications. Clustering is a multidimensional statistic designed to collect similar individuals into homogeneous classes based on observations in variables. The resulting classes can be set according to various structures. This study will cluster data from the volume of levies issued by the Environmental Service from 2010 to 2021 into 3 clustering categories, namely Klassam_0 for low volume of waste generated, Klassam_1 for medium volume of waste generated, and Klassam_2 for the volume of waste generated is high. From the results of this study, there were 8 on Klassam_0, 88 on Klassam_1, and 48 on Klassam_2. The volume of organic and inorganic waste is very good because of the emphasis on the waste management process that occurs in 2021, from the results of the clustering in 1 year (12 months) in 2021 8 months or clusters that are included in klassam¬_0 which can be interpreted as volume of waste "low", and 4 months or clusters included in klassam_2 which can be interpreted as "high" volume of waste.
Co-Authors ., Hervian AAN SETIAWAN Abdul Azis Abdul Aziz Hasibuan Abdulah, Muhamad Biyan Aceng Supriyadi Achmad Syaifudin Rodhi Achmad Syirod Ade Muhammad Nur Fauzi Adi Firman Ari Saputra Adi Yulianto Aditya lutfi Irawan Afid Rozaqi Afiyan Nur Chafidin Afrasim Yusta Afriany, Joli Agung Rahmad Fadjar Agus Iskandar Agus Iskandar Agus Iskandar Ahmad Arief Fadila Ahmad Avivanto Ahmad Rizki Firdaus Aji Juliana Akhmad Primulyana Albaar Rubhasy Albaar Rubhasy Aldi Andres Ardiansah Aldya Bagas Prahastyo Alfian Muhharam Ali Rahman Alisa Fitriyani Alisya Mutia Mantika Alvian Nur Efendi Ananda Sustantiara Andarweni, Dhea Andreas Gerhard Simorangkir Andrianingsih Andrianingsih Andriansyah Utomo Anggita Putri Maharani Anhar Hawari Anharudin Anharudin apiek maniek Ardinsah Ardinsah Ardiyanto Wantudi Arie Gunawan Ariel Cahyono Arika Zuraidah Aris Gunaryati Artamevia, Zahrach Arya Dimas Setiadi Arya Sastranegara Astri Pertiwi Atikah Suhaimah Baldhan Difa Ben Rahman Benrahman Bernardito Jordan Cahya, Nilam Candra Kurniawan Chafidin, Afiyan Nur Chuy Mandala Putra Cintya Damayanti Dandi Putra Daud Iswandii Della Diniyati Deny Hidayatullah Dewi Janetta Az Zahra Dhea Andarweni Dhieka Avrilia Lantana Dian Yunita Sihombing Dicke Rifki Fajrin Dimas Aryanto Wijaya Diniyati, Della Diranisha, Virly Djamaludin, Muhammad Ariel Dwi Auditira Dwi Ifan Ramadhan Dwi Juliastuti Dwika Assrani Dwina Pri Indini Dwiyatno, Saleh Dzahabi Yunas, Rio Al E, Endah Tri Efendi, Alvian Nur Eka Febriyanto Riski Eka Permana Putra Endah Tri Eshti Handayani Endah Tri Esti Handayani Endah Tri Esti Handayani Eri Mardiani Eri Mardiani Eri Mardiani Fachid, Syakirah Fadhil Muhammad Supriyanto Fadillah, Rizkah Faiq Husain Pratama Faizal Kurniawan Fajar Setiawan Hidayat Fajhar Muhammad Fajrin, Dicke Rifki Faran, Jhiro Fardila Inastiana Fatha Alsidqi Husaini Fathiya Zahra, Hawra Ferina Gunawan Fifto Nugroho Fikar Wahyu Tyas Tono Fikri Fajar Asshiddiqi Fikrianzi Nindyo Kusumo Fildzah Fildzah Firzatullah, Raden Muhamad Flipo Hariski Frankly Sept Genius Zendrato Gatot Soepriyono Genius Zendrato, Frankly Sept Ghulam Prasetyo Utomo Hadi Ansyah Hakam, Muhammad Aulia Haris Triono Sigit Hasibuan, Abdul Aziz Hervian . Heryanto, Yayan Hidayat, Fajar Setiawan Hilman, Hilman Fikri Wijaya Hoga Saragih Ibnu Nur Khawarizmi Ikbal Danu Setiawan Iksal Iksal Iksal Iksal Imam Rizqi Imanuel Sinuraya Inastiana, Fardila indrawan indrawan ingsih, Andrian Ira Diana Sholihati Ira Diana Sholihati Ira Diana Solihati Ira Diana Solihati Iskandar Fitri Ismi Naili Qurrotul Aini Ismia Iwandini Jhiro Faran Juliana, Aji Jumpa Dorisman Rajagukguk Junior, Reza Phahlevi Kabeleke Melanesia L Kartika Salma Nadhiva Karyaningsih, Dentik Kiai Agus Priyaharto Mulia I Kodim Suparman Kusumaningtyas, Grasiella Yustika Rezka Talita Latif Arif Anggoro lia kamelia Lili Dwi Yulianto Listrina Turnip Ma'arif, Ridwan Ahmad Made Yoga Mahardika Mardiani, Eri Mauludani Muhammad Melati Indah Petiwi Melisa Theresia Mesran, Mesran Moh Dani Ariawan Muhamad Biyan Abdulah, Muhammad Andhika Maulana Muhammad Ariel Djamaludin Muhammad Aulia Hakam Muhammad Fadli Muhammad Faisal Abdillah Muhammad Faizal Muhammad Farhan Adistyra Muhammad Ilyas Sahputra Muhammad Jordy Muhammad Prabowo Chaniago Muhammad Rafi Fadhilah Muhammad Rizki Wardhana Muhammad Rizki Zidan Muhammad Rizky Hamdan Mutiara Mala Khairunnisa Nabilah Ananda Pratiwi Nadia Putri Ariyanti Nanda Fathi Rizky Nesha Putri Pratama Nifea Kusumawardhani Nofrisa, Dini Novi Dian Nathasia Novi Dian Nathasia Nur Hayati Nur Hayati Nur Hayati Nur Iskandar Zulkarnaen Nurfatanah Nurfatanah Nurfazriah Attamami Nurhadiyan, Thoha Oktaviani Oktaviani Oktaviani oktaviani Oky Triadi Sampurno Panjaitan, Fricia Oktaviani Penny Hendriyati Putra Dama Ramadhan Raffi Dima Sampurno Rafi Syahputra Rahmat Aji Santoso Raihan Abdi Negoro Rais Rabtsani, Muhamad Raka Alvianda Rama Setiawan Ramadhan, Duta Pramudya Ratih Mardianti Ratih Titi Komala Sari Ratih Titi Komalasari Repi, Viktor Vekky Ronald Resha Anjariansyah Reynaldo, Yohanes Reza Phahlevi Junior Riad Sahara Rian Aditia Rian Rasyidhi Rian Tineges Rian, Rian Hidayat Ricky Andri Widayat Riefand Fadhlurrohman Rifki Nur Apriyono Rima Tamara Aldisa Rima Tamara Aldisa Rima Tamara Aldisa Rio Al Dzahabi Yunas Ripin, Muhamad Riska Setiawati Riska Susilawati Rivaldi Okta Pratama Rizal Bagus Pambudi Rizal Toha, Muhammad Rizki Kurnia Rizky Setiawan Rodhi, Achmad Syaifudin Rosaima Situmorang Rosalina, Vidila Rudi Adityawan Sahputra, Muhammad Ilyas Sampurno, Raffi Dima Saragih, Nova Sari Ningsih Sawindri, Sawindri sawindri Seanand Sonia Shabrilianti Setiawan, Ikbal Danu Setiawati, Riska Setiono, Aji Shafira Shalehanny Shintia Mutiarani Sholihati, Ira Diana Simanjuntak, Handayani Simanungkalit, Racquel Terranova Singgih Yulianto Bastian Siti Nurhalizah Soepriyono, Gatot Solihati, Ira Diana Suginam Sugitha, I Kadek Agga Suhaimah, Atikah Suherman Suherman Sultana Namira Sumiati Sumiati Sumiati Sumiati Sumiati Sumiati Sumiati, Sumiati Suparman, Kodim Susilawati . Susilawati, Riska Sussolaikah, Kelik Syabana, Ulwi Syafrida Hafni Sahir Syavira Cahyaningsih Syirod, Achmad Thoha Nurhadiyan Titih Aji Kurniawan Titik Abdul Rahman Tiyas Asih Qurnia Putri Tobby Wiratama Putra Tyas Tono, Fikar Wahyu Untoroseto, Dedi Utami, Yulianti Pratiwi Vendy Blessing Gulo Vidila Rosalina Vivimaryati Vivimaryati Vivimaryati, Vivimaryati Wahid Al Jufri Wahyu Oktri Widyarto Wardhana, Muhammad Rizki Wibowo, Adhitya Eka WINARSIH Winarsih Winarsih Winarsih Winarsih Winarsih Winda Antika Putri Wiratama Putra, Tobby Wulan Kartika Murti Wulan Widhari Wulandari, Faras Tira Yana Tania Haryanto Yandi Makmur Yani Sugiyani Yanto Murnihati Waruwu Yohanes Reynaldo Yulianti Pratiwi Utami Yunan Fauzi Wijaya Zahrach Artamevia Zuraidah, Arika