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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 Lontar Komputer: Jurnal Ilmiah Teknologi Informasi 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 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 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 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
Anita Desiani
Universitas Sriwijaya, Palembang, Indonesia
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Simple Data Augmentation and U-Net CNN for Neclui Binary Segmentation on Pap Smear Images Desiani, Anita; Irmeilyana; Zayanti, Des Alwine; Utama, Yadi; Arhami, Muhammad; Affandi, Azhar Kholiq; Sasongko, Muhammad Aditya; Ramayanti, Indri
Journal of Electronics, Electromedical Engineering, and Medical Informatics Vol 6 No 3 (2024): July
Publisher : Department of Electromedical Engineering, POLTEKKES KEMENKES SURABAYA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35882/jeeemi.v6i3.442

Abstract

The nuclei and cytoplasm can be detected through Pap smear images. The image consists of cytoplasm and nuclei. In Pap smear image, nuclei are the most critical cell components and undergo significant changes in cervical cancer disorders. To help women avoid cervical cancer, early detection of nuclei abnormalities can be done in various ways, one of which is by separating the nuclei from the non-nucleis part by image segmentation it. In this study, segmentation of the separation of nuclei with other parts of the Pap smear image is carried out by applying the U-Net CNN architecture. The amount of pap smear image data is limited. The limiter data can cause overfitting on U-Net CNN model. Meanwhile, U-Net CNN needs a large amount of training data to get great performance results for classification. One technique to increase data is augmentation. Simple techniques for augmentation are flip and rotation. The result of the application of U-Net CNN architecture and augmentation is a binary image consisting of two parts, namely the background and the nuclei. Performance evaluation of combination U-Net CNN and augmentation technique is accuracy, sensitivity, specificity, and F1-score. The results performance of the method for accuracy, sensitivity, and F1-score values are greater than 90%, while the specificity is still below 80%. From these performance results, it shows that the U-Net CNN combine augmentation technique is excellent to detect nuclei in compared to detect non nuclei cell on pap smear image.
Sistem Pakar Diagnosa Penyakit Katarak dengan Metode Certainty Factor Mortara, Alda Amalia; Anita Desiani
JURNAL AMPLIFIER : JURNAL ILMIAH BIDANG TEKNIK ELEKTRO DAN KOMPUTER Vol. 13 No. 1 (2023): Amplifier Mei Vol. 13, No. 1 2023
Publisher : UNIB Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33369/jamplifier.v13i1.27265

Abstract

The eye is one of the most vital parts of the human body, which of course must be maintained. Unhealthy eyes will have a bad impact on the sufferer because it can interfere with the sufferer's activity process. One of the simplest and most common eye diseases suffered by humans is cataracts. Symptoms of cataracts occur painlessly so that many sufferers do not realize that they have cataracts. In Indonesia, the main cause of visual impairment and blindness is cataracts. Cases of blindness caused by cataracts occur due to a condition where the lens of the eye becomes cloudy and cataracts do not only occur at an early age but at all ages even though cataracts are a type of blindness that can be avoided and can be cured through treatment. Therefore an expert system is needed to help diagnose cataracts so that prevention can be done as much as possible. One method that can be used by expert systems is the assurance factor method. The advantage of the assurance factor method is that it can provide settlement solutions with the value of disease symptoms given by experts. With the superiority of the assurance factor method, this study will discuss the application of the assurance factor in the diagnosis of cataracts. To diagnose cataracts, there are 18 symptoms with 3 types of disease, namely congenital, juvenile, and traumatic cataracts. This study used 5 data tests based on the symptoms felt by people with cataracts to produce accurate predictions for each type of cataract where 86.0762% congenital cataracts in the first test data, 94.0595% juvenile cataracts in the second test data, 92.5128% traumatic cataracts in the third test data, 92.2440 % juvenile cataracts in the fourth test data, and 90.2080% juvenile cataracts in the fifth test data.
BLOOD VESSEL SEGMENTATION IN RETINAL IMAGES USING RESVNET ARCHITECTURE Ramadhani, Syafira Dian; Erwin, Erwin; Desiani, Anita; Bella Agustina, Sinta
Jurnal Teknik Informatika (Jutif) Vol. 5 No. 4 (2024): JUTIF Volume 5, Number 4, August 2024
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2024.5.4.2637

Abstract

The U-Net architecture is often used in medical blood vessel segmentation due to its ability to produce good segmentation. However, U-Net has high complexity due to the presence of the bridge part, which increases the parameters and training time. To overcome this, this research modifies U-Net by removing the bridge part, resulting in V-Net architecture. V-Net architecture faces challenges in capturing deep and complex features. This research proposes modifying V-Net with ResNet architecture in the encoder part, resulting in ResVNet architecture. ResNet, with residual connections, enables the training of very deep networks with more stability and effectiveness in capturing complex features. At the encoder, ResNet is used for more effective training of deep networks and capturing complex features. While at the decoder, U-Net is used to preserve the high resolution and spatial information of the image in segmentation. This study aims to determine the performance evaluation results of the ResVNet architecture. The evaluation measures used are accuracy, sensitivity, precision and Jaccard score. Tests were conducted on the DRIVE and STARE datasets. The measurement results of blood vessel segmentation using ResVNet on the DRIVE dataset resulted in accuracy 96.57%, sensitivity 82.28%, precision 79.57%, and Jaccard score 67.61%. On the STARE dataset, the accuracy results are 96.71%, sensitivity 79.44%, precission 79.44%, and Jaccard score 65.05%. The sensitivity results on the STARE dataset as well as the precision and Jaccard score values on the two datasets produced are still low, in the future this research will make improvements to the ResVNet architecture used.
Pemberdayaan Masyarakat Melalui Bimbingan Teknis Pengembangan Budidaya Ikan Lokal Sumatera Selatan di Indralaya Raya, Kabupaten Ogan Ilir Yonarta, Danang; Muslim, Muslim; Desiani, Anita; Syaifudin, Mochamad; Taqwa, Ferdinand Hukama
Jurdimas (Jurnal Pengabdian Kepada Masyarakat) Royal Vol 7, No 1 (2024): Januari 2024
Publisher : STMIK Royal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33330/jurdimas.v7i1.2735

Abstract

Indralaya Raya memiliki jumlah penduduk laki-laki sebanyak 7.079 jiwa dan perempuan 3.617 jiwa. Masyarakat Indralaya Raya sebagian besar berprofesi sebagai pedagang. Hal ini berdasarkan lokasi Indralaya Raya yang dekat dengan Pasar Indralaya yang hanya berjarak 3 km dengan waktu tempuh ± 5 menit. Indralaya Raya dialiri oleh Sungai Kelekar. Sungai Kelekar banyak dihuni oleh ikan-ikan lokal salah satunya ikan tambakan. Produksi ikan tambakan dari kegiatan budidaya masih sangat terbatas sehingga perlu dorongan agar masyarakat dapat membudidayakan ikan ini. Salah satu solusi yang dapat dilakukan adalah dengan melakukan pendampingan terhadap masyarakat mengenai teknis budidaya ikan tambakan mulai dari pemeliharaan induk hingga pemeliharaan larva hingga ukuran benih. Kegiatan pengabdian terhadap masyarakat dapat menjadi jembatan yang menghubungkan dengan masyarakat. Melalui kegiatan penyuluhan dan pendampingan mengenai produksi ikan tambakan masyarakat dapat mandiri secara ekonomi.
Development of An Expert System for The Diagnosis of Kidney Disease Using the Certainty Factor Method Refky Maulana; Anita Desiani
Majalah Bisnis & IPTEK Vol. 16 No. 1 (2023): Majalah Bisnis & IPTEK
Publisher : Pusat Penelitian dan Pengabdian Pada Masyarakat (P3M) STIE Pasundan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55208/hrc47w79

Abstract

Kidney disease is a prevalent health issue affecting millions of people globally. Early and accurate diagnosis of kidney diseases can help in the timely and effective management of the condition. Expert systems, such as those using the Certainty Factor (CF) method, can provide doctors with valuable assistance in diagnosing kidney diseases more efficiently and accurately. This study aims to develop a kidney disease diagnosis expert system using the CF method. The developed system consists of data collection, data storage, and data processing components, with the CF method used to calculate diagnostic confidence levels and decision-making based on predetermined rules. The knowledge acquisition process was carried out by interviewing three nephrologists to obtain rules for diagnosing kidney diseases. The expert system's evaluation is conducted by comparing the system's diagnostic accuracy with a specialist doctors. The results show that the developed expert system has an accuracy rate of 85.7% in diagnosing kidney diseases. The system also has a user-friendly interface, which allows doctors to input symptoms and obtain a diagnosis quickly and accurately. The developed system has several advantages over traditional diagnosis methods. It can diagnose multiple kidney diseases simultaneously and provide a differential diagnosis, allowing doctors to choose the most appropriate treatment plan for their patients. The system also has the potential to reduce diagnostic errors and improve patient outcomes.
PERBANDINGAN ALGORITMA SUPPORT VECTOR MACHINE (SVM) DAN LOGISTIC REGRESSION DALAM KLASIFIKASI KANKER PAYUDARA Desiani, Anita; Zayanti, Des Alwine; Ramayanti, Indri; Ramadhan, Faishal Fitra; Giovillando
Jurnal Kecerdasan Buatan dan Teknologi Informasi Vol. 4 No. 1 (2025): January 2025
Publisher : Ninety Media Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69916/jkbti.v4i1.191

Abstract

Kanker payudara memberikan dampak fisik dan dampak psikologis pada pasien. Deteksi dini terhadap kanker payudara dibutuhkan pada pengidap yang berisiko mengidap kanker payudara. Salah satu solusi yang bisa dilakukan untuk deteksi dini penyakit kanker payudara yaitu dengan melakukan klasifikasi menggunakan pendekatan data mining menggunakan algoritma Support Vector Machine (SVM) dan Algoritma Logistik Regresi (ALR) dengan teknik pengujian Precentage Split dan K-Fold Cross Validation. Penelitian ini bertujuan untuk mendapatkan hasil klasifikasi terbaik untuk mendeteksi penyakit kanker payudara dengan membandingkan kedua algoritma tersebut. Hasil Akurasi yang dihasilkan dari penelitian ini yaitu pada algoritma SVM diperoleh 96% pada metode Precentage Split dan 98% pada metode K-Fold Cross Validation. Sementara pada algoritma Logistic Regression didapat hasil akurasi sebesar 96% pada metode Precentage Split dan 97% untuk metode K-Fold Cross Validation. Berdasarkan hasil akurasi, algoritma SVM metode K-Fold Cross Validation merupakan algoritma terbaik dalam mengklasifikasi penyakit kanker payudara. Namun, hasil akurasi dari ALR masih bisa dikatakan sangat baik karena lebih dari 90%.
Pelatihan Aplikasi Desain Grafis Sebagai Peluang Usaha Ekonomi Produktif (UEP) Bagi Karang Taruna di Desa Limbang Jaya Suprihatin, Bambang; Desiani, Anita; Maiyanti, Sri Indra; Primartha, Rifkie; Salamah, Fitri; Sari, Puspa; Fadilah, Nadiyah
Kontribusi: Jurnal Penelitian dan Pengabdian Kepada Masyarakat Vol. 5 No. 1 (2024): November 2024
Publisher : Cipta Media Harmoni

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53624/kontribusi.v5i1.429

Abstract

Latar Belakang: Desa Limbang Jaya, terletak di Kecamatan Tanjung Batu, Kabupaten Ogan Ilir, Sumatera Selatan, memiliki kelompok Karang Taruna yang terdiri dari para pemuda-pemudi. Meskipun kelompok ini produktif dengan banyak kegiatan kepemudaan, mereka belum terorganisir dengan baik. Pandemi COVID-19 selama tiga tahun terakhir menyebabkan kegiatan mereka terhenti, dan banyak pemuda terkena Pemutusan Hubungan Kerja (PHK). Tujuan: Kegiatan ini bertujuan untuk mengetahui efektivitas pelatihan pemanfaatan aplikasi Canva dalam mengembangkan Usaha Ekonomi Produktif (UEP)di kalangan pemuda Karang Taruna Desa Limbang Jaya. Metode: Metode yang digunakan adalah survei kualitatif dan kuantitatif, yang melibatkan tahapan survei, persiapan kegiatan, penyampaian materi, dan evaluasi kegiatan. Hasil: Hasil kegiatan menunjukkan bahwa peserta pelatihan memahami materi tentang pemanfaatan aplikasi Canva dengan baik. Kesimpulan: Pelatihan pemanfaatan aplikasi Canva berhasil meningkatkan pemahaman dan keterampilan peserta dalam bidang desain grafis, yang berpotensi dikembangkan menjadi UEP. Langkah selanjutnya adalah melakukan pelatihan lanjutan dan memperluas cakupan program untuk mencapai dampak yang lebih besar. 
Klasifikasi Pengambilan Keputusan Tindakan Operasi Sesar Menggunakan Algoritma Classification and Regression Trees fildzah daniela, nyayu audy; desiani, anita; Irmeilyana, Irmeilyana
KOMPUTEK Vol 8, No 2 (2024): Oktober
Publisher : Universitas Muhammadiyah Ponorogo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24269/jkt.v8i2.2399

Abstract

Data mining adalah sebuah metode yang dapat digunakan untuk melihat pola pada kumpulan data yang hasilnya dapat digunakan untuk pengambilan keputusan. Salah satu metode dari proses data mining adalah klasifikasi. Untuk membuat klasifikasi data mining ada salah satu algoritma yang dapat digunakan yaitu Classification and Regression Trees (CART). Penelitian ini bertujuan untuk mengklasifikasikan pengambilan keputusan tindakan operasi sesar menggunakan algoritma Classification and Regression Trees (CART). Dari 80 data tindakan operasi sesar di dataset UCI dilakukan pengujian data dengan membagi data menjadi data latih dan data uji. Persentase split dataset yang digunakan antara lain 90% data latih 10% data uji, 80% data latih 20% data uji, 70% data latih 30%, 60% data latih 40% data uji, 50% data latih 50% data uji dan 85% data latih dan 15% data uji. Diperoleh hasil bahwa implementasi algoritma CART untuk klasifikasi dataset caesarean menghasilkan akurasi tertinggi 75%. Hasil tersebut menunjukkan bahwa algoritma CART dapat digunakan untuk klasifikasi  pengambilan keputusan tindakan operasi sesar.
Weather Forecasting Using Neural Networks with Backpropagation and ADAM Optimizer for city of Lhokseumawe Arhami, Muhammad; Aulia, Annisa Rizka; Salahuddin, Salahuddin; Desiani, Anita; Yassir, Yassir
ABEC Indonesia Vol. 12 (2024): 12th Applied Business and Engineering Conference
Publisher : Politeknik Negeri Bengkalis

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

Abstract

Weather forecasting in Lhokseumawe is crucial due to its diverse climate and impact on community activities.It serves as an operational responsibility of the Meteorology, Climatology and Geophysics Agency (BMKG) worldwide.The method of forecasting currently employed by the BMKG involves meteorological teams observing and analyzingstatistics based on principles of mechanics and physics. Artificial Neural Networks (ANN) can be utilized to forecastlong-term weather conditions, with the backpropagation algorithm being an ANN algorithm employed for short-termweather prediction. This involves training the backpropagation architecture data, which includes an input layer with asize of 6 using Relu activation, one hidden layer with a size of 64 using Relu activation, and an output layer with a size of3 using softmax activation. We also apply the ADAM optimizer, loss sparse categorical crossentropy, and accuracymetrics. However, the backpropagation algorithm displays weaknesses, including slow convergence, overfitting, andsusceptibility to local minima, which can be addressed by utilizing the ADAM optimization algorithm. The researchutilizes Artificial Neural Network (ANN) with the backpropagation algorithm and ADAM optimization to predictweather conditions in Lhokseumawe City with high accuracy. The research methods comprise of data collection,preprocessing, division, model building, and evaluation. The study outcomes present the weather conditions as sunny,cloudy, or rainy with an algorithm accuracy of 72%.
Klasifikasi Penyakit Kanker Paru-Paru Menggunakan Algoritma Naïve Bayes dan Iterative Dichotomizer 3 (ID3) Pratiwi, Putri; Dwifa, Dima; Desiani, Anita; Amran, Ali; Suprihatin, Bambang
Electrician : Jurnal Rekayasa dan Teknologi Elektro Vol. 18 No. 1 (2024)
Publisher : Department of Electrical Engineering, Faculty of Engineering, Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/elc.v18n1.2519

Abstract

Kanker paru-paru merupakan penyakit yang disebabkan oleh keganasan tumor dari bronkus. Pada tahun 2020 terdapat kasus kematian mencapai 30.843 jiwa. Agar menghambat angka kematian akibat kanker paru-paru, diperlukan alat untuk deteksi dini akibat kanker paru-paru. Pada penelitian ini menggunakan dataset kanker paru-paru yang memiliki 309 data. Teknik uji yang digunakan pada dataset kanker paru-paru ini adalah percentage split dan k-fold cross validation dengan algoritma naive bayes dan iterative dichotomizer 3 (ID3). Parameter penilaian yang digunakan untuk menentukan algoritma terbaik adalah akurasi, presisi dan recall. Hasil penelitian yang menggunakan teknik uji percentage split, diperoleh nilai akurasi, presisi dan recall tertinggi pada algoritma naive bayes yaitu akurasi sebesar 87%, presisi sebesar 91% dan recall sebesar 94% untuk kelas YES (positif lung cancer). Penelitian yang dilakukan dengan teknik uji menggunakan k-fold cross validation memberikan nilai terbaik pada algoritma ID3 dengan nilai akurasi 92%, presisi sebesar 94% dan recall sebesar 97% untuk kelas YES (positif lung cancer). Dengan demikian, penelitian yang dilakukan dengan metode k-fold cross validation memiliki nilai yang lebih tinggi dibandingkan nilai menggunakan teknik uji percentage split. Hal tersebut memberikan kesimpulan bahwa pada penelitian ini, diperoleh algoritma terbaik yaitu ID3 dengan teknik uji k-fold cross validation pada dataset kanker paru-paru.
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 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 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 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 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 Ira Rayyani Irmeilyana Irmeilyana Irmeilyana Irvan Andrian Kanda Januar Miraswan Karina Kartila Kartila Kerenila Agustin 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 Muhammad Akbar Muhammad Akmal Shidqi Muhammad Awaludin Djohar Muhammad Awaludin Djohar Muhammad Azwar Annas Muhammad Gibran Al-Filambany 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 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 Permatasari, Mitta Pertiwi, Citra Prabudifa, Muhammad Yusuf Pranata, Teddi Pratiwi, Ananda Puspa Sari Puspa Sari, Puspa Putra Bahtera Jaya Bangun, Putra Bahtera Jaya Putri Bella Nusantara Putri Pratiwi Putri, Ajeng Islamia Rahmadita, Suristhia Rahmat Dwian Ramadhan, Faishal Fitra Ramadhan, Raihan Ramadhani, Syafira Dian Ramayanti, Indri Rana Sania 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, 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 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