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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) ComEngApp : Computer Engineering and Applications Journal TEKNIK INFORMATIKA Jurnal Pendidikan Matematika Media Informatika JSI: Jurnal Sistem Informasi (E-Journal) Jurnal Simantec Jurnal Teknologi Informasi dan Ilmu Komputer Jurnal Edukasi dan Penelitian Informatika (JEPIN) International Journal of Advances in Intelligent Informatics Jurnal Informatika dan Teknik Elektro Terapan POSITIF Annual Research Seminar KLIK (Kumpulan jurnaL Ilmu Komputer) (e-Journal) Proceeding of the Electrical Engineering Computer Science and Informatics Science and Technology Indonesia Demography Journal of Sriwijaya Format : Jurnal Imiah Teknik Informatika Sistemasi: Jurnal Sistem Informasi Jurnal Penelitian Sains JST ( Jurnal Sains Terapan ) JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING AKSIOLOGIYA : Jurnal Pengabdian Kepada Masyarakat BAREKENG: Jurnal Ilmu Matematika dan Terapan Dinamisia: Jurnal Pengabdian Kepada Masyarakat PROCESSOR Jurnal Ilmiah Sistem Informasi, Teknologi Informasi dan Sistem Komputer JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI Jurnal Infomedia KACANEGARA Jurnal Pengabdian pada Masyarakat MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer Riau Journal of Empowerment Jurnal Inovasi Hasil Pengabdian Masyarakat (JIPEMAS) Jurnal Penelitian dan Pengabdian Kepada Masyarakat UNSIQ Jurnal Kreativitas PKM Jurdimas (Jurnal Pengabdian Kepada Masyarakat) Royal KOMPUTEK Indonesian Journal of Applied Informatics KOMPUTIKA - Jurnal Sistem Komputer Jurnal Teknologi dan Informasi JKPM (Jurnal Kajian Pendidikan Matematika) Energy : Jurnal Ilmiah Ilmu-Ilmu Teknik Jurnal Teknologi Terapan Journal of Electronics, Electromedical Engineering, and Medical Informatics Jurnal Teknologi Informasi : Jurnal Keilmuan dan Aplikasi Bidang Teknik Informatika Jurnal Vokasi Jurnal Teknik Elektro dan Komputasi (ELKOM) Jurnal ABDINUS : Jurnal Pengabdian Nusantara Scientific Journal of Informatics Jurnal Teknik Elektro Uniba (JTE Uniba) Square : Journal of Mathematics and Mathematics Education BERNAS: Jurnal Pengabdian Kepada Masyarakat JOINT (Journal of Information Technology Idealis : Indonesia Journal Information System Jurnal Sistem Informasi dan Sistem Komputer Jurnal Teknik Informatika (JUTIF) Jurnal AbdiMas Nusa Mandiri Jurnal Amplifier: Jurnal Ilmiah Bidang Teknik Elektro dan Komputer JAGROS : Jurnal Agroteknologi dan Sains (Journal of Agrotechnology Science) Jurnal Ilmu Komputer dan Informatika Kontribusi: Jurnal Penelitian dan Pengabdian Kepada Masyarakat Jurnal Rekayasa Elektro Sriwijaya Jurnal Teknologi BAKTI : Jurnal Pengabdian Kepada Masyarakat Pattimura International Journal of Mathematics (PIJMath) Proceeding Applied Business and Engineering Conference Technology and Informatics Insight Journal Electrician : Jurnal Rekayasa dan Teknologi Elektro COREAI: Jurnal Kecerdasan Buatan, Komputasi dan Teknologi Informasi "JAMASTIKA" Jurnal Mahasiswa Teknik Informatika Journal Medical Informatics Technology Journal Of Artificial Intelligence And Software Engineering Jurnal INFOTEL Jurnal Informatika Polinema (JIP) Kreano, Jurnal Matematika Kreatif Inovatif Jurnal Kecerdasan Buatan dan Teknologi Informasi Majalah Bisnis & IPTEK JuTISI (Jurnal Teknik Informatika dan Sistem Informasi)

Anita Desiani

Universitas Sriwijaya, Palembang, Indonesia

Author-ID : 5654817

Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities Automotive Engineering Biochemistry, Genetics & Molecular Biology 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 Energy Engineering Environmental Science Health Professions Immunology & microbiology Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Neuroscience Nursing Physics Public Health Social Sciences Transportation Veterinary Other

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Penerapan Metode Multi Objective Optimization on the Basis of Ratio Analysis (MOORA) Sebagai Pendukung Keputusan Pemilihan Penerima Program Mahasiswa Wirausaha (Studi Kasus : Universitas Sriwijaya) Rahmat Dwian; Anita Desiani; Sugandi Yahdin
Jurnal Teknologi Vol 21, No 2 (2021): Oktober 2021
Publisher : Politeknik Negeri Lhokseumawe

Program Mahasiswa Wirausaha (PMW) of Sriwijaya University is one of the facilities for Sriwijaya University students who have an interest in entrepreneurship. There are 5 criteria in selecting PMW proposals based on Sriwijaya University, namely product innovation and originality, market potential/market opportunities, production processes, organization, and investment plans. In PMW 2019, there were 304 proposals submitted and 146 proposals were approved for funding. The proposal selection process by Sriwijaya University only accumulates the judges' scores for each criterion manually. In this study, the MOORA method was applied as decision support which proposals were eligible to fund. Starting from weighting the criteria, calculating the normalized matrix, multiplying each criterion weight by the normalized matrix, and sorting the product from highest to lowest. In the calculation results, there is a data similarity of 92.97% in the results of the MOORA method with the results from Sriwijaya University. This shows that the MOORA method can be used as a consideration in selecting PMW proposals for the following year.

Liver Segmentation Using Convolutional Neural Network Method with U-Net Architecture Muhammad Awaludin Djohar; Anita Desiani; Ali Amran; Sugandi Yahdin; Dewi Lestari Dwi Putri; Des Alwine Zayanti; Novi Rustiana Dewi
JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Vol 6, No 1 (2022): Issues July 2022
Publisher : Universitas Medan Area

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31289/jite.v6i1.6751

Abnormalities in the liver can be used to identify the occurrence of disorders of the liver, one of which is called liver cancer. To detect abnormalities in the liver, segmentation is needed to take part of the liver that is affected. Segmentation of the liver is usually done manually with x-rays. . This manual detection is quite time consuming to get the results of the analysis. Segmentation is a technique in the image processing process that allocates images into objects and backgrounds. Deep learning applications can be used to help segment medical images. One of the deep learning methods that is widely used for segmentation is U-Net CNN. U-Net CNN has two parts encoder and decoder which are used for image segmentation. This research applies U-Net CNN to segment the liver data image. The performance results of the application of U-Net CNN on the liver image are very goodAccuracy performance obtained is 99%, sensitivity is 99%. The specificity is 99%, the F1-Score is 98%, the Jacard coefficient is 96.46% and the DSC is 98%. The performance achieved from the application of U-Net CNN on average is above 95%, it can be concluded that the application of U-Net CNN is very good and robust in segmenting abnormalities in the liver. This study only discusses the segmentation of the liver image. The results obtained have not been applied to the classification of types of disorders that exist in the liver yet. Further research can apply the segmentation results from the application of U-Net CNN in the problem of classifying types of liver disorders.

Application of the Waterfall Method in Software Design on Android-Based Programming Language Course Applications Anita Desiani; Ali Amran; Nuni Gofar; Chairu Nisa Apriyani; Redina An Fadhila Chaniago
JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Vol 6, No 1 (2022): Issues July 2022
Publisher : Universitas Medan Area

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31289/jite.v6i1.6995

In this era of technology and information proliferating, programming skills are needed. Technology affects every area of life from industry, business, communication, transportation, health, and others. Everyone has the same opportunity to learn and master technology thus programming language courses are needed to provide education, innovation, and improvement of skills and abilities in the field of programming and data science to the public. Until now, programming language courses still use the conventional system, where everything is done manually, from class registration, class scheduling, teaching and learning process, and payment processing which results in many archives that must be stored for administrative purposes and require a relatively large amount of time for customers to come to the course location. Therefore, an information technology-based system is needed to fix the weaknesses of the old system. In this study, an Android-based programming language course application is designed to facilitate customers and course owners in teaching and learning activities and transactions. The design in this study uses the waterfall method, which consists of five stages, needs analysis, design, code, testing, and maintenance. The results obtained from testing applications using questionnaires on programming language course applications are 80% stated by course customers, where the application is easy to use, faster, and more practical in registering. In conclusion, this designed application can make it easier for customers to carry out teaching and learning activities and transact quickly and practically.

Segmentasi Citra Nukleus Sel Kanker Serviks Menggunakan Otsu Thresholding Dan Morfologi Closing Rifa Fadhila Nugrohoputri; Anita Desiani; Yogi Wahyudi; Muhammad Gibran Al-Filambany; Susanto Susanto; Sri Indra Maiyanti
Jurnal Sistem Informasi Vol 14, No 1 (2022)
Publisher : Universitas Sriwijaya

Kanker serviks dapat disembuhkan jika kelainan dan gejalanya dapat terdeteksi sedini mungkin. Pekerjaan diagnosa manual membutuhkan banyak waktu dan teknisi sitologi yang terampil. Sistem pengelolaan citra medis ini dihrapkan dapat mengurangi fakto-faktor subjektivitas dan kesalahan diagnosa kanker serviks. Penelitian ini menggunakan metode yang digunakan adalah Otsu Thresholding dan Morfologi Closing. Penelitian ini akan dilakukan dalam dua tahap utama, yaitu preprocessing dan dilanjutkan dengan segmentasi menggunakan metode yang diusulkan. Penelitian diukur menggunakan parameter yang terlibat untuk mengukur kinerja pendekatan yang diusulkan berdasarkan akurasi, sensitivitas, spesifisitas, F1-Score, dan IoU. Hasil penelitian dari 20 sampel gambar menunjukkan rata-rata metode yang diusulkan, yaitu Otsu Thresholding dan Morfologi Closing mampu melakukan perbaikan citra dan segmentasi citra nukleus sel kanker serviks dengan akurasi sebesar 0.8969, sensitivitas sebesar 0.8806, spesifisitas 0.9954, F1-Skor 0.9293, dan IoU sebesar 0.8740. Penelitian ini menyimpulkan bahwa metode Otsu Thresholding dan Morfologi Closing mampu menghasilkan perbaikan citra dan segmentasi nukleus sel kanker serviks dengan lebih baik dibandingkan dengan metode-metode lainnya dari penelitian lain.

Contrast Enhancement for Improved Blood Vessels Retinal Segmentation Using Top-Hat Transformation and Otsu Thresholding Muhammad Arhami; Anita Desiani; Sugandi Yahdin; Ajeng Islamia Putri; Rifkie Primartha; Husaini Husaini
International Journal of Advances in Intelligent Informatics Vol 8, No 2 (2022): July 2022
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar

Diabetic Retinopathy is a diabetes complication that usually results in abnormalities in the retinal blood vessels of the eye, resulting in blurry vision, including blurry vision and blindness. Automatic segmentation of blood vessels in retinal images can detect abnormalities in these blood vessels, actually resulting in faster and more accurate segmentation results. The paper proposed an automatic blood vessel segmentation method that combined Otsu Thresholding with image enhancement techniques, including Contrast Limited Adaptive Histogram Equalization (CLAHE) and Top-hat transformation for the retinal image. The retinal image data used in the study were the Digital Retinal Images for Vessel Extraction (DRIVE) dataset generated by the fundus camera. The CLAHE and Top-hat transformation methods were used to increase the contrast of the retinal image and reduce noise so that blood vessels could be highlighted appropriately and the segmentation process could be facilitated. Otsu Thresholding was used to distinguish between blood vessel pixels and background pixels. The performance evaluation measures of the methods used are accuracy, sensitivity, and specificity. The DRIVE dataset's study results showed that the average accuracy, sensitivity, and specificity values were 94.7%, 72.28%, and 96.87%, respectively, indicating that the proposed method was successful through blood vessels segmentation retinal images, especially for thick blood vessels.

Perbandingan Implementasi Algoritma Naïve Bayes dan K-Nearest Neighbor Pada Klasifikasi Penyakit Hati Anita Desiani
Jurnal Sistem Informasi dan Sistem Komputer Vol 7 No 2 (2022): Vol 7 No 2 - 2022
Publisher : STIMIK Bina Bangsa Kendari

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51717/simkom.v7i2.96

Hati adalah organ kelenjar terbesar dengan berat kira-kira 1200-1500 gram. Hati dapat terkena berbagai macam penyakit. Untuk mengetahui jumlah rerataan manusia yang terkena penyakit hati, maka kita dapat melakukan klasifikasi terhadap penyakit hati. Penelitian ini bertujuan untuk membandingkan kemudian menyimpulkan algoritma terbaik yang dapat digunakan dalam melakukan klasifikasi penyakit hati. Adapun algoritma yang dibandingkan adalah Naïve Bayes dan K-Nearest Neighbor (K-NN). Hasil dari penelitian ini menyatakan algoritma K-NN dan Naïve Bayes memperoleh nilai lebih dari 80% baik nilai akurasi, presisi maupun recall. Algoritma K-NN memberikan nilai akurasi, presisi, serta recall yang lebih tinggi dibandingkan dengan algoritma Naïve Bayes. Maka algoritma terbaik yang dapat digunakan adalah K-NN.

Implementasi Algoritma Naïve Bayes dan Support Vector Machine (SVM) Pada Klasifikasi Penyakit Kardiovaskular Anita Desiani; Muhammad Akbar; Irmeilyana Irmeilyana; Ali Amran
Jurnal Teknik Elektro dan Komputasi (ELKOM) Vol 4, No 2 (2022): ELKOM
Publisher : Universitas Muhammadiyah Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32528/elkom.v4i2.7691

Penyakit kardiovaskuler adalah penyakit yang diakibatkan penyempitan atau penyumbatan pembuluh darah di jantung penyakit ini disebabkan gangguan fungsi jantung dan pembuluh darah. Sistem kardiovaskular terdiri dari jantung dan pembuluh darahnya. Penelitian ini bertujuan melakukan klasifikasi penyakit kardiovaskular untuk memprediksi suatu pola. Pada penelitian ini akan menggunakan metode support vector machine dan naïve bayes dengan metode latih percentage split dan k-fold cross validation. Hasil akurasi pengolahan menggunakan Algoritma Naïve Bayes adalah sebesar 70% untuk metode latih percentage split dan 71% untuk metode latih k-fold cross validation. Kemudian dengan menggunakan algoritma support vector machine didapat akurasi 61% untuk metode latih percentage split dan 65% untuk metode latih k-fold validation. Hasil tersebut menunjukkan bahwa algoritma naïve bayes dengan metode latih k-fold validation cukup baik dalam melakukan klasifikasi penyakit kardiovaskular.

Segmentasi Paru-Paru Pada Citra Thorax Dada Dengan Menggunakan Metode Cnn U-Net Anisa Aulia Kusmareni; Anita Desiani; Sugandi Yahdin; Mutiara Saviera; Ajeng Islamia Putri; Des Alwine Zayanti
Jurnal Sistem Informasi Vol 14, No 2 (2022)
Publisher : Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36706/jsi.v14i2.16771

Paru-paru merupakan salah satu organ terpenting dari tubuh manusia. Apabila terjadi keabnormalan pada kinerja paru-paru, akan dapat menimbulkan penyakit pernafasan yang dapat membuat tubuh tidak dapat menjalankan kinerjanya dengan normal. Untuk mendeteksi keabnormalan pada paru-paru, dapat dilakukan dengan melihat ukuran dari paru-paru tersebut. Penelitian ini menyajikan metode untuk segmentasi paru-paru pada foto thorax dada pasien dengan metode CNN U-Net. Pada langkah awal pada metode CNN U-Net dilakukan resize lalu segmentasi menggunakan keras optimizer Nadam. Didapatkan nilai rata-rata akurasi sebesar 0.9632, sensitifitas sebesar 0.9586, dan spesifisitas sebesar 0.9675, F1-Skor sebesar 0.9920, dan koefisien Jaccard sebesar 0.9842.

Pemanfatan Lilin Dalam Pembelajaran Matematika Bangun Ruang Bagi Siswa Sekolah Dasar Sri Indra Maiyanti; Anita Desiani; Bambang Suprihatin
BERNAS: Jurnal Pengabdian Kepada Masyarakat Vol. 4 No. 1 (2023)
Publisher : Universitas Majalengka

Matematika merupakan mata pelajaran yang dianggap sulit oleh kebanyakan siswa sekolah dasar. Berbagai inovasi dalam pembelajaran Matematika dilakukan supaya materi pelajaran yang abstrak dapat dipahami dengan mudah dan melekat dalam ingatan siswa. Pengabdian kepada masyarakat ini bertujuan memberikan alternatif pembelajaran Matematika yang mudah dipahami, menarik dan menyenangkan dengan memanfaatkan media pembelajaran dalam bentuk lilin bangun ruang. Metode kegiatan dengan ceramah dan praktek pembuatan lilin berbentuk bangun ruang (kubus, balok, kerucut, prisma, limas, tabung dan bola). Hasil dari pengabdian ini adalah siswa dapat memahami materi bangun ruang melalui benda konkrit, selanjutnya dapat ditingkatkan ke pemahaman yang lebih abstrak. Siswa mengikuti kegiatan dengan antusias, bersemangat dan gembira. Sebelum kegiatan 80% siswa menganggap pelajaran bangun ruang “sulit” namun setelahnya hanya tinggal 33,3% siswa yang menganggap pelajaran bangun ruang sulit. Hampir semua siswa (93,3%) menganggap pembelajaran bangun ruang dengan media lilin bangun ruang “menyenangkan” dan mudah dilakukan. Nilai siswa setelah pembelajaran (Nilai rata-rata 67,5 post-test) lebih baik dibandingkan sebelumnya (rata-rata pre-test 50,7). Kata Kunci: Bangun Ruang; Lilin Bangun Ruang; Media Pembelajaran Matematika

Handling Missing Data Using Combination of Deletion Technique, Mean, Mode and Artificial Neural Network Imputation for Heart Disease Dataset Anita Desiani; Novi Rustiana Dewi; Annisa Nur Fauza; Naufal Rachmatullah; Muhammad Arhami; Muhammad Nawawi
Science and Technology Indonesia Vol. 6 No. 4 (2021): October
Publisher : Research Center of Inorganic Materials and Coordination Complexes, FMIPA Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26554/sti.2021.6.4.303-312

The University of California Irvine Heart disease dataset had missing data on several attributes. The missing data can loss the important information of the attributes, but it cannot be deleted immediately on dataset. To handle missing data, there are several ways including deletion, imputation by mean, mode, or with prediction methods. In this study, the missing data were handled by deletion technique if the attribute had more than 70% missing data. Otherwise, it were handled by mean and mode method to impute missing data that had missing data less or equal 1%. The artificial neural network was used to handle the attribute that had missing data more than 1%. The results of the techniques and methods used to handle missing data were measured based on the performance results of the classification method on data that has been handled the problem of missing data. In this study the classification method used is Artificial Neural Network, Naïve Bayes, Support Vector Machine, and K-Nearest Neighbor. The performance results of classification methods without handling missing data were compared with the performance results of classification methods after imputation missing data on dataset for accuracy, sensitivity, specificity and ROC. In addition, the comparison of the Mean Squared Error results was also used to see how close the predicted label in the classification was to the original label. The lowest Mean Squared Error wasobtained by Artificial Neural Network, which means that the Artificial Neural Network worked very well on dataset that has been handled missing data compared to other methods. The result of accuracy, specificity, sensitivity in each classification method showed that imputation missing data could increase the performance of classification, especially for the Artificial Neural Network method.

Co-Authors Adi Muzakir Adinda Ayu Lestari, Adinda Ayu Adzra Afiifah Nabila Affandi, Azhar Kholiq Agatha, Lucy Chania Agung Alamsyah Ajeng Islamia Putri Ajeng Islamia Putri Al-Ariq, M Al-Filambany, Muhammad Gibran Alamsyah, Agung albar Pratama Alga Mahida Ali Amran Ali Amran All Fajri, Muhammad Arya Ambarwati Ananda Pratiwi Andhini, Shania Putri Andika Cristian Lubis Andriani, Nur Avisa Calista Anggraini, Jeni Putri Anisa Aulia Kusmareni Annisa Aulia Lestari Annisa Kartikasari Annisa Nabila, Annisa Annisa Nur Fauza Annisa Nurba Iffah’da Apledaria Apledaria Arhami, Muhammad Arhami, Muhammad Arsyad. H, Muhammad Iqbal Arum Setiawan Aulia Salsabila Aulia, Annisa Rizka Ayuputri, Niken Azhar Kholiq Affandi Azzahra, Nur Devita Azzahra, Pasma Bambang Suprihatin Bambang Suprihatin Bambang Suprihatin Bambang Suprihatin Batubara, Gracia Mianda Caroline Bella Agustina, Sinta Betty Aprianah Betty Aprianah Budi Mulyono Calista, Nur Avisa Carolina Rahman Chairu Nisa Apriyani Chaya Gladys Zhafirah A Clarita Margo Uteh Des Alwine Zayanti Des Alwine Zayanti Des Alwine Zayanti, Des Alwine Desty Rodiah Dewi Lestari Dwi Putri Dewi Lestari Dwi Putri Dewi, Deshinta Arrova Dian Cahyawati Diana Dewi Sartika, Diana Dewi Dien Novita Dina Elly Yanti Dina Elly Yanti Dina Suzzete Sitorus Dite Geovani Dite Geovanni Dwi Ranti Dwi Septiani Dwifa, Dima Echa Alda Melinia Efriliyanti, Filda Endang Sri Kresnawati Endang Sri Kresnawati Endro Setyo Cahyono Endro Setyo Cahyono, Endro Setyo Enyta Yuniar Ermatita - Erwin Erwin Erwin, Erwin Fadhilah, Nadiyah Fadilah, Nadiyah Faishal Fitra Ramadhan Fathinah, Nadiva Azro Ferdi Setiawan Ferdinand Hukama Taqwa Filda Efriliyanti fildzah daniela, nyayu audy Firdaus Firdaus Fitri Salamah Fivalianda, Dido Geovani, Dite Geovanni, Dite Giovillando Hadi Tanuji Hasibuan, MS Henisaniyya, Nabila Herlina Hanum Herlina Hanum, Herlina Hermansyah Hermansyah Hermansyah Hermansyah Hermansyah Husaini Husaini Ilham Tri Wibowo Indah Verdya Alvionita Indra Maiyanti, Sri Indri Ramayanti Ira Rayyani Irmeilyana Irmeilyana Irmeilyana Irvan Andrian Kanda Januar Miraswan Karina Kartila Kartila Kerenila Agustin Kesuma, Lucky Indra Kurnia, M Kahfi Aldi Kurniawan, Rifki Kusmareni, Anisa Aulia Lizah Framesti Lubis, Andika Cristian Lucy Chania Agatha Makhalli, Siddiq Manoppo, Sania Marselina, Nyanyu Chika Maya Meilensa Maya Meilensa Mayangsari, Oki Sukma Mega Tiara Putri Mitta Permata Sari Mochamad Syaifudin, Mochamad Mortara, Alda Amalia MS Hasibuan Muchlas, Ally Muhammad Akbar Muhammad Akmal Shidqi Muhammad Awaludin Djohar Muhammad Awaludin Djohar Muhammad Azwar Annas Muhammad Gibran Al-Filambany Muhammad Ihsan Muhammad Naufal Rachmatullah Muhammad Nawawi Muhammad Nawawi Muhammad Syariful Irsyad Muhammad Wahyu Ilahi Muhammat Rio Halim Muslim Muslim Muslim Muslim Mustaqima, Dina Mutiara Saviera Muzakir, Adi Muzayyadah, Fathona Nur Nadya Riri Febiyanti Napitu, Michael Jackson Narti Narti, Narti Naturatama, Dicky Naufal Rachmatullah Ngudiantoro . Ning Eliyati Novi Rustiana Dewi Novi Rustiana Dewi Nugrohoputri, Rifa Fadhila NUNI GOFAR Nur Avisa Calista Nur Devita Azzahra Nyayu Chika Marselina Oki Dwipurwani Padhil, Azmi Muhammad Pasma Azzahra Permatasari, Mitta Pertiwi, Citra Prabudifa, Muhammad Yusuf Pranata, Teddi Pratiwi, Ananda Purwita Sari, Purwita Puspa Sari Puspa Sari, Puspa Putra Bahtera Jaya Bangun, Putra Bahtera Jaya Putri Bella Nusantara Putri Pratiwi Putri, Ajeng Islamia Putri, Tyara Hestyani Rahmadita, Suristhia Rahmat Dwian Ramadhan, Faishal Fitra Ramadhan, Raihan Ramadhani, Syafira Dian Ramayanti, Indri Rana Sania Ravisha Keyna Anduwi Rayani, Ira Redina An Fadhila Chaniago Redina An Fadhila Chaniago Refky Maulana Rifa Fadhila Nugrohoputri Rifki Kurniawan Rifkie Primartha Rifkie Primartha Rifkie Primartha Rio Halim, Muhammat Rizki, Fatur Salahuddin Salahuddin Salamah, Fitri Salsabila, Aulia Saputra, M Aldi Saputra, Tommy Sari Suryati Sasongko, Muhammad Aditya Savera, Mutiara Saviera, Mutiara Shania Putri Andhini Shidqi, Muhammad Akmal Shinta Octarina Siddiq Makhalli Sigit Priyanta Simamora, Valentino Sinta Bella Agustina Siti Husnul Hotimah, Siti Husnul Siti Nurhaliza Siti Rusdiana Puspa Dewi Sitorus, Dina Suzzete Sri Indra Maiyanti Sri Indra Maiyanti Sri Indra Maiyanti Sri Indra Maiyanti Suedarmin, Muhammad Sugandi Yahdin Sugandi Yahdin Sugandi Yahdin Suratama, Bintang Suryani Suryani Susanto Susanto Susanto Susanto Syafrina Lamin, Syafrina Syarifuddin, Fauzi Yusuf Teddi Pranata Titania Jeanni Charisa Titania Jeanni Charissa Tri Febriani Putri tri wahyuni Villando, Gio Waafiyah, Hilmiana Wahyudi, Yogi Yadi Utama Yassir Yassir Yogi Wahyudi Yonarta, Danang Yuli Andirani Yuli Andriani Yuli Andriani Yulia Resti Yuniar, Enyta Z, Des Alwine Zulhipni Reno Saputra Els

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