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All Journal Dinamik GEMA TEKNOLOGI Techno.Com: Jurnal Teknologi Informasi Jurnal Simetris Syntax Jurnal Informatika Elkom: Jurnal Elektronika dan Komputer Jurnal Ilmiah Mahasiswa FEB Prosiding SNATIF Jurnal Teknologi Informasi dan Ilmu Komputer Jurnal Berkala Epidemiologi Seminar Nasional Informatika (SEMNASIF) CESS (Journal of Computer Engineering, System and Science) E-Dimas: Jurnal Pengabdian kepada Masyarakat JOIN (Jurnal Online Informatika) Sinkron : Jurnal dan Penelitian Teknik Informatika Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) SISFOTENIKA Journal of Information Technology and Computer Science (JOINTECS) JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Jurnal Ilmiah FIFO Jurnal Pilar Nusa Mandiri InComTech: Jurnal Telekomunikasi dan Komputer Prosiding Seminar Nasional Teknoka JRST (Jurnal Riset Sains dan Teknologi) JOURNAL OF APPLIED INFORMATICS AND COMPUTING SINTECH (Science and Information Technology) Journal JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI Jurnal Sisfokom (Sistem Informasi dan Komputer) Jiko (Jurnal Informatika dan komputer) Explore IT : Jurnal Keilmuan dan Aplikasi Teknik Informatika Jurnal Telematika STRING (Satuan Tulisan Riset dan Inovasi Teknologi) CCIT (Creative Communication and Innovative Technology) Journal Jurnal Ilmiah Ilmu Komputer Fakultas Ilmu Komputer Universitas Al Asyariah Mandar Journal of Electronics, Electromedical Engineering, and Medical Informatics Jurnal Ilmu Komputer dan Bisnis Syntax Idea Techno Xplore : Jurnal Ilmu Komputer dan Teknologi Informasi Jurnal Sistem informasi dan informatika (SIMIKA) Jurnal Mnemonic Jurnal Asiimetrik: Jurnal Ilmiah Rekayasa Dan Inovasi Journal of Computer Science and Engineering (JCSE) SKANIKA: Sistem Komputer dan Teknik Informatika Media Gizi Kesmas Jurnal Teknik Informatika (JUTIF) Jurnal Pewarta Indonesia JURNAL KOMUNIKASI DAN BISNIS Ascarya: Journal of Islamic Science, Culture and Social Studies Jurnal PkM (Pengabdian kepada Masyarakat) Humantech : Jurnal Ilmiah Multidisiplin Indonesia Media Publikasi Promosi Kesehatan Indonesia (MPPKI) Bit (Fakultas Teknologi Informasi Universitas Budi Luhur) Journal Of Human And Education (JAHE) Prosiding Seminar Nasional Sisfotek (Sistem Informasi dan Teknologi Informasi) Jurnal Algoritma Jurnal Ticom: Technology of Information and Communication Berita Kedokteran Masyarakat Journal of Systems Engineering and Information Technology J-Icon : Jurnal Komputer dan Informatika Jurnal Teknik Indonesia Research Horizon Jurnal Relawan dan Pengabdian Masyarakat REDI Jurnal Pengabdian Masyarakat Nasional Health Dynamics Jurnal Ticom: Technology of Information and Communication The Indonesian Journal of Computer Science Seminar Nasional Riset dan Teknologi (SEMNAS RISTEK) Prosiding SeNTIK STI&K Journal of Medical and Health Science Jurnal Ilmu Kesehatan Immanuel Jurnal Analogi Hukum

Arief Wibowo

Universitas Budi Luhur

Author-ID : 414407

Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Immunology & microbiology Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Medicine & Pharmacology Nursing Public Health Social Sciences Transportation Veterinary Other

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ANALISIS SENTIMEN PELANGGAN TOKO ONLINE JD.ID MENGGUNAKAN METODE NAÏVE BAYES CLASSIFIER BERBASIS KONVERSI IKON EMOSI Fransiska Vina Sari; Arief Wibowo
Simetris: Jurnal Teknik Mesin, Elektro dan Ilmu Komputer Vol 10, No 2 (2019): JURNAL SIMETRIS VOLUME 10 NO 2 TAHUN 2019
Publisher : Universitas Muria Kudus

Analisis Sentimen adalah suatu teknik mengekstrak data teks untuk mendapatkan informasi tentang sentimen bernilai positif, netral maupun negatif. Analisis sentimen diberikan oleh pengguna internet pada media sosial untuk memberikan suatu penilaian atau opini pribadi. Salah satu toko online Indonesia yang sering mendapatkan sentimen pengguna melalui media sosial adalah JD.id. Adanya sentimen opini dari konsumen tentang JD.id dapat dianalisis dan dimanfaatkan untuk mendapatkan informasi yang berguna bagi pelanggan lain maupun pihak toko. Dengan menggunakan teknik Text Mining metode klasifikasi, akan diketahui suatu sentimen bernilai positif, netral atau negatif. Salah satu algoritme yang banyak digunakan dalam analisis sentimen adalah metode klasifikasi Naïve Bayes. Penelitian ini menggunakan metode Naïve Bayes Classifier (NBC) dengan pembobotan tf-idf disertai penambahan fitur konversi ikon emosi (emoticon) untuk mengetahui kelas sentimen yang ada dari tweet tentang toko JD.id. Hasil penelitian menunjukkan bahwa metode Naïve Bayes tanpa penambahan fitur mampu mengklasifikasi sentimen dengan nilai akurasi sebesar 96,44%, sementara jika ditambahkan fitur pembobotan tf-idf disertai konversi ikon emosi mampu meningkatkan nilai akurasi menjadi 98%.

IMPLEMENTASI ALGORITMA NAIVE BAYES UNTUK MEMPREDIKSI FREKUENSI TUNAI PADA MESIN ATM DI MASA TRANSISI PEMBATASAN SOSIAL BERSKALA BESAR (PSBB) PANDEMI COVID-19 Saptari Wijaya Mulia; Sujiharno Sujiharno; Arief Wibowo
SINTECH (Science and Information Technology) Journal Vol. 4 No. 1 (2021): SINTECH Journal Edition April 2021
Publisher : LPPM STMIK STIKOM Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31598/sintechjournal.v4i1.622

Determining the need of money for ATM is usually different, that is one of the problems in managing money allocation of ATM. Some seasonal factors such as holidays and the implementation of transition large-scale social restrictions related to the covid-19 pandemic that can affect fluctuations in cash transactions. In this paper aims to determine the frequency of cash withdrawals at ATM since the enactment of transition large-scale social restrictions in Jakarta using the naive bayes algorithm so it can be identified which ATM require more allocation money or not. Providing the right money allocation can improve the quality of service to customers and minimize unused money in ATM. Results of analysis using a Naive Bayes algorithm to predict cash withdrawals frequencies at ATM that show a prediction accuracy up to 81%

Media Sosial Sebagai Solusi Pemasaran Umkm Yang Adaptif Di Masa Pandemi Covid-19 Arief Wibowo; Widi Wahyudi; Dyah Retno Utari
Jurnal PkM Pengabdian kepada Masyarakat Vol 4, No 6 (2021): Jurnal PkM : Pengabdian kepada Masyarakat
Publisher : Universitas Indraprasta PGRI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30998/jurnalpkm.v4i6.8148

Pandemi COVID-19 yang terjadi di Indonesia telah membuat perlambatan ekonomi di berbagai sektor, mulai dari pengusaha hingga masyarakat. Berbagai elemen masyarakat mengalami dampak psikis, sosial dan ekonomi yang berimbas satu sama lainnya. Dalam masa pandemi yang disertai dengan kebijakan pembatasan sosial berskala besar, telah menimbulkan kesulitan tersendiri di masyarakat, terutama praktisi usaha kecil dan menengah. Di tengah daya beli yang menurun, strategi melakukan bisnis pun mengalami perubahan, sehingga diperlukan strategi pemasaran yang adaptif di masa pendemi Covid-19. Suku Dinas Pemberdayaan, Perlindungan Anak dan Pengendalian Penduduk (Sudin PPAPP) Kota Administrasi Jakarta Barat Provinsi DKI Jakarta bekerja dengan sivitas akademika telah mengadakan pelatihan kolaborasi untuk merespon dan memberi solusi atas permasalahan yang dirasakan pelaku UMKM. Kegiatan pengabdian masyarakat yang telah dilakukan, berupa seminar daring disertai workshop singkat tentang media sosial sebagai solusi pemasaran yang adaptif di masa pandemi Covid-19. Sasaran dari kegiatan ini adalah dipahaminya pengetahuan tentang media sosial yang dapat menjadi solusi pemasaran yang bisa dipraktikkan menjelang masa kebiasaan baru. Kegiatan abdimas ini telah diterima dengan baik oleh masyarakat sasaran, terlihat dari indikator bahwa mayoritas peserta sebanyak 95,1% telah memberikan rasa setuju akan manfaat kegiatan ini serta motivasi yang tinggi dan persepsi pemahaman yang sangat baik terhadap materi yang diberikan

Implementasi Web Service pada Perusahaan Logistik menggunakan JSON Web Token dan Algoritma Kriptografi RC4 Mochammad Rizky Royani; Arief Wibowo
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 4 No 3 (2020): Juni 2020
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

The development of e-commerce in Indonesia in the last five years has significantly increased the growth for logistics service companies. The Indonesian Logistics and Forwarders Association (ALFI) has predicted the growth potential of the logistics business in Indonesia to reach more than 30% by 2020. One of the efforts of logistics business companies to improve services in the logistics services business competition is to implement web service technology on mobile platforms, to easy access to services for customers. This research aims to build a web service with a RESTful approach. The REST architecture has limitations in the form of no authentication mechanism, so users can access and modify data. To improve its services, JSON Web Token (JWT) technology is needed in the authentication process and security of access rights. In terms of data storage and transmission security, a cryptographic algorithm is also needed to encrypt and maintain confidentiality in the database. RC4 algorithm is a cryptographic algorithm that is famous for its speed in the encoding process. RC4 encryption results are processed with the Base64 Algorithm so that encrypted messages can be stored in a database. The combination of the RC4 method with the Base64 method has strengthened aspects of database security. This research resulted in a prototype application that was built with a combination of web service methods, JWT and cryptographic techniques. The test results show that the web service application at the logistics service company that was created can run well with relatively fast access time, which is an average of 176 ms. With this access time, the process of managing data and information becomes more efficient because before making this application the process of handling a transaction takes up to 20 minutes.

99 / 5000 Hasil terjemahan JWT Implementation in Attendance Applications with Fingerprint Validation, Geotagging and Device Checker Arief Umarjati; Arief Wibowo
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 4 No 6 (2020): Desember 2020
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

During the Covid-19 pandemic the government implement the imposition of Large-Scale Social Restrictions (PSBB). This PSBB also has an impact on companies in Jabodetabek including PT Akses Digital Indonesia. In order to comply with regulations given by the government, PT Akses Digital Indonesia has implemented a Work From Home (WFH) policy for its employees. During the implementation of the WFH policy, had difficulty monitoring the performance of its employees. Attendance is one measure of the level of performance, especially employee discipline. Based on the identification of the problem, an employee presence web service application is needed. Of course, this application should be as effective as conventional fingerprint machines in offices. This application is accompanied by a validation feature using geotagging, fingerprint and device checkers to minimize fraud when employees make attendance. This study implements the RESTful API security feature on web services using JSON Web Token (JWT) based on the HMAC SHA-256 algorithm. All implementation stages are tested using the Black Box method and show that JWT can secure the authentication process and secure data. The validation feature is able to provide attendance data with an accuracy of 90,9%.

Penentuan Klaster Koridor TransJakarta dengan Metode Majority Voting pada Algoritma Data Mining Arief Wibowo; Moh Makruf; Inge Virdyna; Farah Chikita Venna
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 5 No 3 (2021): Juni 2021
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

The Covid-19 pandemic has made many changes in the patterns of community activity. Large-Scale Social Restrictions were implemented to reduce the number of transmission of the virus. This clearly affects the mode of transportation. The mode of transportation makes new regulations to reduce the number of passenger capacities in each fleet, for example, TransJakarta services. This study will categorize the TransJakarta corridors before and during the Covid-19 pandemic. The clustering method of K-Means and K-Medoids is used to obtain accurate calculation results. The calculations are performed using Microsoft Excel, Rapid Miner, and Python programming language. The clustering results obtained that using K-Means algorithm before Covid-19 pandemic, an optimum number of clusters is 3 clusters with DBI (Davies Bouldin Index) value is 0.184, and during Covid-19 pandemic, the optimum number of clusters is 2 clusters with DBI value is 0.188. Meanwhile, when using the K-Medoids algorithm before the Covid-19 pandemic, an optimum number of clusters is 3 clusters with the DBI value is 0.200, and during the Covid-19 pandemic, an optimum number of clusters is 4 clusters with the DBI value is 0.190. The final cluster is determined using the majority voting approach from all the tools used.

Perbandingan Kinerja Algoritma Support Vector Machine dan K-Nearest Neighbor Terhadap Analisis Sentimen Kebijakan New Normal Didin Muhidin; Arief Wibowo
STRING (Satuan Tulisan Riset dan Inovasi Teknologi) Vol 5, No 2 (2020)
Publisher : Universitas Indraprasta PGRI Jakarta

Twitter is one of the popular microblogging sites among internet users, so that many people use Twitter to convey their positive and negative sentiments towards the new normal policy. The pandemic period raises much public sentiment towards the policy of adapting to the new normal. This study aims to classify sentiment tweets into positive and negative classes. The classification algorithms used are k-NN and SVM. The test results show that the k-NN algorithm is better than SVM in solving this sentiment case with an accuracy of 72.96%.

Komparasi Pengelompokan Pemeringkatan Sertifikasi Travel Umrah Berizin dengan Algoritma Klasterisasi K-Means dan K-Medoids Muhammad Risky; Arief Wibowo; Zakaria Anshori
InComTech : Jurnal Telekomunikasi dan Komputer Vol 12, No 1 (2022)
Publisher : Department of Electrical Engineering

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/incomtech.v12i1.14528

Dengan Terbitnya Undang-Undang Nomor 11 Tahun 2020 tentang Cipta Kerja yang merevisi beberapa pasal dalam Undang-Undang Nomor 8 Tahun 2019 tentang Penyelenggaraan Haji dan Umrah, Kementerian Agama harus melakukan pembahasan tentang peraturan turunankedua Undang-Undang tersebut. Di antara peraturan turunan yang diterbitkan adalah Keputusan Menteri Agama (KMA) Nomor 1251 Tahun 2021 tentang Skema dan Kriteria Akreditasi serta Sertifikasi Usaha Penyelenggaraan Ibadah Umrah dan Penyelenggaraan Haji Khusus. Dalam KMA ini, Kementerian Agama melaksanakan pengaturan berkenaan dengan pemeringkatan PPIU dan juga PIHK, yang dibagi pemeringkatan menjadi 3 kelompok yaitu A, B C. Penelitian ini bertujuan untuk menganalisa dengan pembanding atau referensi lain menggunakan metode penambangan (mining). Penambangan (mining) yang dipergunakan pada penelitian ini adalah terhadap data. Dataset akan di proses dengan algoritma yang ditemukan oleh Lloyd dan kawan-kawan, yakni K-Means. Selain itu, dataset juga akan diproses dengan salah satu algoritma lain untuk pengelompokan data, dalam hal ini peneliti memilih K-Medoids. Dataset terdiri dari 5.000 baris data sesuasi dengan penilaian indikator dominan dan ko-dominan. Hasil Penelitian menunjukkan bahwa metode K-Means dengan dua kelompok dengan maksimize tanpa normalize memiliki Davies-Bouldin Index (DBI) 0,234. Sedangkan metode K-Means dengan 2 kelompok serta melakukan normalize maka Davies-Bouldin Index (DBI) adalah 0,005. K-Means adalah yang paling optimal dibanding K-Medoids pada penelitian ini.

Penentuan Dosen Terbaik Menggunakan Metode Analytical Hierarchy Process (AHP) dan Technique For Order By Similarity To Ideal Solution (TOPSIS): Studi Kasus Akademi Teknologi Bogor Istiqoomatun Nisaa; Arief Wibowo

Publisher : Program Studi Teknik Informatika, Fakultas Teknik, Universitas Yudharta Pasuruan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35891/explorit.v12i2.2288

Akademi Teknologi Bogor yang berdiri sejak tahun1997, berlokasi di Kota Bogor. Didukung 40 staf dosen. Dosen mempunyai kedudukan sebagai tenaga professional pada jenjang pendidikan tinggi yang diangkat sesuai dengan peraturan perundang-undangan. Dosen adalah tenaga pendidik yang memberikan sejumlah ilmu pengetahuan kepada anak didik di Perguruan Tinggi. Sistem penentuan dosen terbaik digunakan untuk mendukung kegiatan belajar dan mengajar dikampus agar terciptanya mahasiswa yang berkualitas dan kompeten di bidangnya. Hal ini untuk memenuhi kriteria dosen untuk memutuskan dosen yang dianggap terbaik. Proses penentuan dosen terbaik pada sistem yang berjalan saat ini masih memiliki kekurangan yaitu membutuhkan waktu yang lama untuk memproses data hasil kuesioner, sehingga keputusan yang didapat belum valid. Pada penelitian ini akan dibuat sebuah Sistem Pendukung Keputusan (SPK) dimana sistem ini dapat membantu seseorang mengambil keputusan yang akurat dan tepat sasaran. Adapun metode yang digunakan yaitu metode Analytical Hierarchy Process (AHP) untuk menghitung bobot setiap kriteria dan Technique For Order By Similarity To Ideal Solution (TOPSIS) untuk merangking alternatif berdasarkan setiap kriteria. Hasil penelitian ini adalah sebuah sistem yang mampu menghasilkan urutan perangkingan dalam penentuan dosen terbaik di Akademi Teknologi Bogor.

SEGMENTASI PELANGGAN MENGGUNAKAN METODE K-MEANS CLUSTERING BERDASARKAN MODEL QRF PADA PERUSAHAAN RINTISAN PENYEDIA TENAGA KERJA Sari Anggar Kusuma Melati; Arief Wibowo
JURNAL ILMU KOMPUTER Vol 6 No 2 (2020): Edisi September
Publisher : LPPM Universitas Al Asyariah Mandar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35329/jiik.v6i2.138

The difficulty of getting a job that is in accordance with the interests and specialization of a worker, as well as the difficulty of the company getting a worker who suits the needs of the company causes the mushrooming of consulting firms or labor providers in Indonesia today. With the increasing number of companies providing labor, of course the competitiveness of the business industry in the human resources is increasingly high. So it needs to be analyzed to determine the right business strategy, such as determining the company's promotion goals. One of them is analyzing the segmentation of customers who have worked together. This research successfully modeled customer segmentation based on data mining clustering techniques using the K-Means data mining algorithm. The QRF (Quantity, Recency, Frequency) modeling process is analyzing the customer's behavior from the number of requests in each transaction carried out within a certain timeframe, as well as recency as the identification of the time span of the last transaction, as well as the number of transactions made within a certain time period. Researchers conducted a period of data for one year by analyzing customer activity in start-up providers of labor during 2019, on 86 active customers. Based on the analysis results obtained, customer segmentation in two clusters with QRF (Quantity, Recency, Frequency) modeling using Davies Bouldin Index (DBI) evaluation scored -0,482, while customer segmentation in three clusters using QRF (Quantity, Recency, Frequency) evaluation using Davies Bouldin Index (DBI) evaluation to obtain -0.469, and customer segmentation in four clusters with QRF (Quantity, Recency, Frequency) modeling using Davies BouldinIndex (DBI) evaluation to obtain -0,526. Keywords— pelanggan, clustering, algoritma k-means, DBI, QRF

Co-Authors - Arientawati - Sumardianto Adita, Ita Afifah Khaerani Afifatussalamah, Rizka Ahmad Sururi Ahmad Sururi Akbar, Ahmad Aldizar Al Fatach, M Khabib Anggraini, Julaiha Probo Anita Diana Anugrah Sandy Yudhasti Apriati Suryani Ardhianto, Angga Ardianah, Eva Ari Wibowo Arief Umarjati Asep Permana Atik Ariesta Bayu Sadewo Bayu Satria Pratama Binarto, Antonius Jonet Boerhan Hidayat, Boerhan Danar Wido Seno Darki, Ni Wayan Yustika Agustin Diah Indriani Didik Hariyadi Raharjo Didin Muhidin Dwi Kristanto Dwi Yulianti Dyah Retno Utari Dyah Retno Utari, Dyah Retno Endah Sarah Wanty Fajar Siddik Chaniago Farah Chikita Venna Farid Setiawan Farid Setiawan, Farid Febrilliani, Jihan Sastri Fenny Irawati Fernando, Donny Firman Noor Hasan Firmanty Mustofa, Vina Fitri Nur Masruriyah, Anis Fitri Rachmilah Fadmi Fitriadi, Rifqi Fitriani, Netty Fransiska Vina Sari Frenda Farahdinna Fried Sinlae Ghapur, Abdul Gurdani Yogisutanti Hadidtyo Wisnu Wardani Hananto, Agustia Handoko, Andy Rio Hanindita, Meta Herdiana Hari Basuki Notobroto Haris Achadi, Abdul HARIYANTO HARIYANTO Harun Nasrullah Hayatul Khairul Rahmat Henry Henry Hidayat, Manarul Hidayat, Sarifudlin Huda, Ratu Najmil I MADE MINGGU WIDYANTARA, I MADE MINGGU Indah Rizky Mahartika Inge Virdyna Irfan Hadi Irfan Nurdiansyah Istiqoomatun Nisaa Iwan Irawan Jasmine, Meuthia Joko Sutrisno Jovansgha Avegad Jumaryadi, Yuwan Kanasfi, Kanasfi Karma, Ni Made Sukaryati Karyaningsih, Dentik Kresno Yulianto KRESNO YULIANTO KUNTORO Kuntoro Kuntoro Kurnia Setiawan Kutanto, Haronas Larasati, Pamela Linda Lingga Desyanita Luthfi Akbar Ramadhan Mahmudah Mahmudah Mailana, Agus Maria Adiningsih Marlina, Hesti Maskur A, Moch Riyadi Megananda Hervita Permata Sari Megawati, Rina Miftahul Arifin Miftahul Arifin Mochammad Rizky Royani Moh Makruf Muhamad Fadel Muhammad Febrian Rachmadhan Amri Muhammad Risky Mulyati Mulyati Nendi, Nendi Ningrum, Yogi Ajeng Nugroho, Angelika Pratiwi Widya Nur Aisiyah Widjaja, Nur Aisiyah Nur Rohman Nurcahya, Gelar Nurfidaus, Yasmine Nursyi, Muhamad Pattipeilohy, William Frado Pattipeilohy, William Frado Pebriaini, Prisma Andita Poppy Ruliana Pradiptha, Anindya Putri Probo Anggraini, Julaiha Purwadi Purwadi Putra, Andi Agung Putra, Rinaldi Febryatna Duriat Rachmah Indawati Rahman, Reza Rahmawati, Nur Anisah Rakhman, Abdulah Rakhmat Rakhmat Rakhmat Rakhmat RAMAYU, I Made Satrya Rangkuti, Muhammad Yusuf Rizqon Ratna Ayu Sekarwati Ratna Ayu Sekarwati Relawanto, Bowo Ria Puspitasari Rika Nurhayati Riki Ramdani Saputra Rina Megawati Ririh Yudhastuti Risaychi, Diva Ajeng Brillian Ristiana, Ina Riza, Yeni Rizkiyanto, Muhamad Ardiansyah Roedi Irawan Rojakul, Rojakul Rosita Dewi, Erni Ruliana, Poppy Rusdah Ryo Tanaka Sabirin, Sahril Sadewo, Bayu Santoso, Febrina Mustika Saptari Wijaya Mulia Sari Anggar Kusuma Melati Sari, Fransiska Vina Sasongko, Raden Satiri Satiri, Satiri Selly Rahmawati Selly Rahmawati Septian Firman S Sodiq Septiani, Riska Setya Haksama Setyowati, Erlin Shofinurdin Shofinurdin Siddik Chaniago, Fajar Sigit Ari Saputro Sigit Budi Nugroho Siregar, Sutan Syahdinullah SITI NURUL HIDAYATI Sitti Aliyah Azzahra Soenarnatalina Melaniani Sudewo, Andika Hasbigumdi Sugiyarta, Ahmad Sujiharno Sujiharno Sumarna, Presma Dana Scendi Suntoro, Dimas Fahmi Tiaharyadini, Rizka TRISNAWATI, WULAN Tulus Yuniasih Umam, Mohamad Hafidhul Vasthu Imaniar Ivanoti Wahyu Cesar Wahyu Desena Wahyudi, Widi Wahyuni, Chatarina Unggul Wangsajaya, Yosia Heartha Dhalasta Wasis Budiarto Wibiyanto, Alif Dewan Daru Widiyaningrum, Diyah Kiki Widyanto, Tetrian Windhu Purnomo Yahya Darmawan Yudanto, Satyo Zakaria Anshori Zaqi Kurniawan

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