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All Journal Jurnal Edukasi dan Penelitian Informatika (JEPIN) JOIV : International Journal on Informatics Visualization Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) International Journal of Artificial Intelligence Research RABIT: Jurnal Teknologi dan Sistem Informasi Univrab JURNAL MEDIA INFORMATIKA BUDIDARMA PROCESSOR Jurnal Ilmiah Sistem Informasi, Teknologi Informasi dan Sistem Komputer JMM (Jurnal Masyarakat Mandiri) Sebatik JURNAL PENDIDIKAN TAMBUSAI Jurnal Ilmiah Media Sisfo Journal of Information Technology and Computer Engineering JURTEKSI Jurdimas (Jurnal Pengabdian Kepada Masyarakat) Royal JOURNAL OF SCIENCE AND SOCIAL RESEARCH EXPLORE Jurnal Review Pendidikan dan Pengajaran (JRPP) Jurnal Teknologi Informasi dan Pendidikan Jusikom: Jurnal Sistem Informasi Ilmu Komputer bit-Tech Jurnal Sistem Informasi dan Informatika (SIMIKA) JATI (Jurnal Mahasiswa Teknik Informatika) Indonesian Journal of Electrical Engineering and Computer Science JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Jurnal Infortech Jurnal Pendidikan Guru (JPG) Journal of Applied Data Sciences Jurnal Computer Science and Information Technology (CoSciTech) Majalah Ilmiah UPI YPTK Journal of Computer Scine and Information Technology Bulletin of Computer Science Research KLIK: Kajian Ilmiah Informatika dan Komputer Jurnal Ipteks Terapan : research of applied science and education Jurnal Pustaka Data : Pusat Akses Kajian Database, Analisa Teknologi, dan Arsitektur Komputer Jurnal Pustaka AI : Pusat Akses Kajian Teknologi Artificial Intelligence EXPLORE Jurnal Komtekinfo Journal of Computers and Digital Business SmartComp JOURNAL OF COMMUNITY SERVICE AND APPLICATION SCIENCE (JCSAS) Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen) Jurnal Pustaka Robot Sister
Sovia, Rini
Universitas Putra Indonesia YPTK Padang, Padang
Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities Astronomy 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 Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Health Professions Immunology & microbiology Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Neuroscience Nursing Physics Public Health Social Sciences Veterinary Other

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Pemanfaatan Aplikasi Untuk Memberikan Diagnosa Awal Penyakit Gigi Dan Mulut Pada Ins Dental Care Sovia, Rini; Ardiansyah, Ricki; Rani, Maha
Jurdimas (Jurnal Pengabdian Kepada Masyarakat) Royal Vol. 7 No. 2 (2024): April 2024
Publisher : STMIK Royal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33330/jurdimas.v7i2.3022

Abstract

Technological developments in various fields continue to increase, one of which is in the health sector, namely the use of applications to provide initial diagnoses of dental and oral diseases. Lack of public awareness and knowledge in maintaining oral health can give rise to various kinds of diseases, some of which can be cured with proper treatment. One way that can be done to prevent this disease is by providing education to the public by using a web-based application. The PKM team held activities at Ins Dental Care. The method used in this activity is training in the use of applications for early diagnosis of dental and oral diseases with the participants being doctors and nurses. The aim of this service activity is to provide knowledge to participants about applications that can be used by participants to provide initial diagnoses of dental and oral diseases so that later participants can easily obtain information about dental and oral diseases. With this application, Ins Dental Care can easily provide education to the public about dental health and reach local communities to provide education about dental health and dental disease. By utilizing a web application for early diagnosis of dental and oral diseases, people can obtain information on diagnosing dental diseases independently without having to come to the clinic.    Keywords: training; application; diagnosis; dental and oral diseases
Penerapan E-Commerce Model Business To Customer DSruput Cabang Lubuk Begalung Berbasis Web Lidya Adriani Darma; Rini Sovia; Heriyanto
Journal of Computers and Digital Business Vol. 1 No. 2 (2022)
Publisher : PT. Delitekno Media Madiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (833.969 KB) | DOI: 10.56427/jcbd.v1i2.14

Abstract

Perkembangan teknologi pada dunia digital dan internet berdampak kuat pada dunia pemasaran. Diciptakan teknologi E-Commerce sebagai salah satu strategi pemasaran yang mampu menjangkau jaringan masyarakat luas. Perancangan E-Commerce dalam penelitian ini di tujukan kepada “D’Sruput cabang Lubuk Begalung”. Permasalahan yang dihadapi oleh D’Sruput adalah minimnya strategi pengembangan usaha, yang masih menggunakan strategi tradisional marketing, sehingga pemasaran dan keterbatasan promosi jadi lebih sempit. Metode penelitian yang dilakukan adalah dengan menganalisa kebutuhan yang dapat menghasilkan pemodelan system pemasaran digital dengan menggunakan perancangan system UML (Unified Modelling Language). Penelitian ini menghasilkan sebuah analisa pengembangan E-Commerce berbasis web untuk D’Sruput yang diharapkan mampu menjangkau pasar yang lebih luas, jumlah konsumen meningkat karna adanya diskon-diskon yang disediakan serta kemudahan dalam pemesanan jenis-jenis minuman yang di inginkan.
Sistem Identifikasi Citra Huruf Aksara Minangkabau Berbasis Convolutional Neural Network Saputra, Riyan; Ramadhanu, Agung; Sovia, Rini
Jurnal Pustaka AI (Pusat Akses Kajian Teknologi Artificial Intelligence) Vol 5 No 2 (2025): Pustaka AI (Pusat Akses Kajian Teknologi Artificial Intelligence)
Publisher : Pustaka Galeri Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55382/jurnalpustakaai.v5i2.1214

Abstract

Pelestarian aksara daerah penting untuk menjaga warisan budaya bangsa. Aksara Minangkabau, sebagai salah satu kekayaan budaya Indonesia, masih minim penelitian dan belum memiliki sistem digitalisasi memadai. Penelitian ini merupakan tahap awal eksplorasi pengenalan aksara Minangkabau menggunakan pendekatan Convolutional Neural Network (CNN) sebagai upaya mendokumentasikan dan menguji potensi digitalisasi aksara tersebut. CNN merupakan salah satu model deep learning yang dirancang untuk memproses data grid terstruktur seperti citra. Penelitian sebelumnya menunjukan kinerja CNN sangat baik dalam pengenalan tulisan tangan. Citra aksara yang digunakan dalam penelitian ini diperoleh dari sumber museum dan tulisan tangan dari 31 sukarelawan. Dataset terdiri dari 4.650 citra karakter dari 75 kelas dengan berbagai kombinasi tanda baca pada lima huruf vokal, yang kemudian diproses melalui konversi grayscale, peningkatan kontras, segmentasi, dan augmentasi hingga menghasilkan total 8.537 citra. Model CNN yang dirancang mengklasifikasikan karakter ke dalam 75 kelas. Hasil pengujian mengindikasikan bahwa model dapat mengenali karakter dengan sangat baik. Pengujian menunjukkan akurasi 99% dalam skenario pengujian terbatas pada 500 data uji. Temuan ini memberikan landasan awal untuk digunakan dalam kajian akademis lanjutan maupun diskusi kultural yang lebih luas terkait keberadaan aksara Minangkabau.
Diagnosa Penyakit Tuberkulosis Paru Menggunakan Metode Forward Chaining dan Certainty Factor Wirdawati, Wira; Sovia, Rini; Hendrik, Billy
Jurnal Pustaka AI (Pusat Akses Kajian Teknologi Artificial Intelligence) Vol 5 No 2 (2025): Pustaka AI (Pusat Akses Kajian Teknologi Artificial Intelligence)
Publisher : Pustaka Galeri Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55382/jurnalpustakaai.v5i2.1217

Abstract

Tuberculosis (TB) is an infectious disease that can affect people of all ages, including children, adolescents, and the elderly, and can cause illness and death in over one million people. The disease is spread through coughs or sneezes by people with pulmonary TB, through contaminated saliva, and inhalation by healthy people with weakened immune systems. Therefore, this study aims to develop an expert system to assist in the diagnosis of pulmonary tuberculosis using the Forward Chaining and Certainty Factor methods. This process begins by identifying symptoms reported by the user and then searching for rules in the knowledge base that match those symptoms. This method allows the system to follow a logical flow of reasoning similar to the way a doctor diagnoses a disease. This study used data from 100 patients from 2023 at the Pariaman Community Health Center. Using the Forward Chaining and Certainty Factor methods, three patient data sets with three types of tuberculosis were tested. The percentage results for each type of disease were 100% positive for pulmonary tuberculosis, 0.91% negative for pulmonary tuberculosis, and 0.92% latent for pulmonary tuberculosis, with a confidence level of Very Confident. This research contributes to increasing knowledge and understanding in the field of expert systems, particularly in the application of the Forward Chaining and Certainty Factor methods for diagnosing tuberculosis.
APLIKASI MOBILE E-COMMERCE UNTUK PEMBELAJARAN DENGAN FITUR PEMBAYARAN ONLINE AMAN Gema, Rima Liana; Sovia, Rini; Awal, Hasri
Jurnal Review Pendidikan dan Pengajaran Vol. 8 No. 1 (2025): Volume 8 No. 1 Tahun 2025
Publisher : LPPM Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/jrpp.v8i1.41433

Abstract

Pengembangan aplikasi e-commerce berbasis mobile dengan fitur pembayaran online yang aman bertujuan untuk meningkatkan kenyamanan dan keamanan transaksi digital. Dengan pesatnya perkembangan belanja online, dibutuhkan platform yang mudah diakses dan aman bagi pengguna. Penelitian ini mengembangkan aplikasi e-commerce yang mengintegrasikan sistem pembayaran menggunakan teknologi enkripsi dan otentikasi multi-faktor untuk melindungi data pengguna. Metode yang digunakan dalam penelitian ini mencakup analisis kebutuhan, desain sistem, dan implementasi aplikasi berbasis Android menggunakan bahasa pemrograman Java. Hasil penelitian menunjukkan aplikasi ini berhasil meningkatkan pengalaman pengguna melalui antarmuka yang ramah pengguna serta memperkuat keamanan transaksi online. Kesimpulannya, aplikasi ini dapat menjadi solusi bagi konsumen dan pelaku bisnis dalam melakukan transaksi secara efisien dan aman, memenuhi kebutuhan pasar yang semakin mengutamakan kenyamanan dan proteksi data pribadi.
The Development of Affine Transformation Method Using Scale Invariant Feature Transform (SIFT) Hartika Zain, Ruri Hartika; Yuhandri, Yuhandri; Sovia, Rini
JOIV : International Journal on Informatics Visualization Vol 9, No 6 (2025)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.9.6.3653

Abstract

Carving is a technique used to create decorative images on wood, stone, and other materials. In Indonesia, wood is a popular choice because of its durability and attractive grain. Examples of wood carvings include floral designs. The carving process can involve changes in color, texture, and scale, which may affect the carving's size and appearance and cause dimensional changes in certain materials. This study addresses the issue of quality control in wood carving on thin veneer layers. Free wood-carving data are provided as 200 flower images that can be used as input images. Affine transformation is used to determine the system behavior and the material transfer function during the production process. Additionally, we propose extending the affine transformation method to use the Scale-Invariant Feature Transform (SIFT). Affine transformations enable correlation analysis, outlier removal, and feature orientation in the affine domain. The SIFT algorithm accounts for scale, rotation, brightness, and perspective. Applications using ASIFT can efficiently process images and handle those with different pixel sizes to create new carvings. Training samples used to update the filter model are changed to the same pose. This enables the flower wood carving filter to represent objects with 98% accuracy. The model is then used to predict the class of the flower-carving data and to compute the distance between the template image's features and those of the input flower-wood-carving image. This research project has successfully developed an Affine Transformation method using SIFT features to create a new engraving application based on the ASIFT approach. 
PEMBERDAYAAN SISWA PERHOTELAN MENGGUNAKAN APLIKASI SPEECH RECOGNITION UNTUK MENINGKATKAN KEMAMPUAN BAHASA INGGRIS Rini Sovia; Shally Amna; Randy Permana
JMM (Jurnal Masyarakat Mandiri) Vol 9, No 6 (2025): Desember
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jmm.v9i6.35886

Abstract

Abstrak Pentingnya penguasaan Bahasa Inggris bagi lulusan SMK jurusan perhotelan Padang menjadi perhatian penting bagi kepala sekolah dan guru, karena mayoritas siswanya masih belum mampu menguasai bahasa Inggris dengan baik. Oleh karena itu, kegiatan pengabdian masyarakat ini bertujuan untuk meningkatkan kemampuan siswa mulai dari kemampuan dasar kosakata dan pengucapan Bahasa Inggris. Kegiatan ini dimulai dengan memberikan modul dan aplikasi dengan speech recognition software (SRS) yang materinya telah disesuaikan dengan kebutuhan siswa, kemudian memberikan pelatihan dan pendampingan kepada 30 siswa dengan metode partisipatif selama tiga hari. Evaluasi dilakukan dengan melihat peningkatan nilai siswa dari hasil pre-test dan post-test. Hasil evaluasi kegiatan menunjukkan adanya peningkatan nilai dengan selisih peningkatan nilai sebanyak 22,67 poin. Kegiatan PKM ini dinilai dan diakui oleh siswa dan guru memberikan manfaat untuk meningkatkan kemampuan pronunciation dan vocabulary bahasa Inggris siswa, terutama dengan diberikannya modul dan aplikasi pendamping.Abstract: The importance of English proficiency for vocational school graduates majoring in hospitality in Padang is a major concern for school principals and teachers, as the majority of students are still unable to master English well. Therefore, this community service activity aims to improve students' skills, starting with basic English vocabulary and pronunciation. This activity began with providing modules and applications with speech recognition software (SRS) whose material had been tailored to the students' needs, then providing training and assistance to 30 students using participatory methods for three days. The evaluation was carried out by looking at the increase in student scores from the pre-test and post-test results. The results of the activity evaluation showed an increase in scores with a difference of 22.67 points. This PKM activity was assessed and recognised by students and teachers as beneficial for improving students' English pronunciation and vocabulary skills, particularly through the provision of modules and supporting applications.
Penerapan Metode Simple Additive Weighting (SAW) untuk Menilai Kinerja Karyawan di Toko Al-Fazza Cosmetic Ardiansyah, Ricki; Rani, Maha; Rindhani Aditia, Mellya; Sovia, Rini; Christy, Tika
Jurnal Pustaka Data (Pusat Akses Kajian Database, Analisa Teknologi, dan Arsitektur Komputer) Vol 5 No 2 (2025): Jurnal Pustaka Data (Pusat Akses Kajian Database, Analisa Teknologi, dan Arsitekt
Publisher : Pustaka Galeri Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55382/jurnalpustakadata.v5i2.1486

Abstract

Karyawan merupakan aset penting dalam keberlangsungan sebuah usaha. Karyawan yang kompeten dan memiliki motivasi tinggi berperan dalam mempertahankan usaha ditengah perkembangan teknologi dan industri. Penilaian kinerja berfungsi untuk mengevaluasi sekaligus menjadi acuan dalam memberikan penghargaan serta menentukan posisi yang ideal bagi karyawan. Tapi penilaian kinerja masih menjadi salah satu tantangan bagi sebuah usaha. Belum adanya standar yang baku serta subjektifitas pemilik usaha dan pihak terkait yang melakukan penilaian sering menimbulkan kecemburuan, ambiguitas, dan kekhawatiran, yang mengakibatkan penurunan stabilitas dan motivasi kerja di toko al-fazza cosmetic. Untuk mempermudah dan mempercepat hasil penilaian kinerja karyawan dirancanglah sebuah sistem pendukung keputusan yang dapat membantu pemilik toko dan pihak terkait yang melakukan penilaian kinerja di toko al-fazza cosmetic. Metode yang digunakan untuk memproses penilaian kinerja di toko al-fazza cosmetic adalah simple additive weighting (saw). Kriteria yang menjadi standar dalam penilaian adalah  absensi, disiplin, tanggung jawab, sikap, layanan, pengetahuan produk, dan penampilan. Dari pengolahan data dengan metode saw sistem pendukung keputusan ini dapat memberikan penilaian kinerja dari beberapa karyawan yang menjadi alternatif dan memberikan perangkingan yang dapat digunakan oleh pemilik toko dan pihak terkait untuk menentukan hasil kinerja karyawan dan menentukan penghargaan terhadap hasil kinerja mereka. berdasarkan proses penilaian kinerja menggunakan metode SAW didapat hasil perangkingan kinerja karyawan dengan nilai tertinggi alternatif pertama Ari dengan total Vector 25.05, peringkat kedua widia dengan total nilai Vector 23.40 selanjutnya, Rizki nilai Vector 23.20, diikuti Mega dengan niali Vector 22.85, terakhir Nora dengan Nilai Vector 21,80.
Robust Predictive Model for Heart Disease Diagnosis Using Advanced Machine Learning Techniques Sovia, Rini; Anam, M. Khairul; Wisky, Irzal Arief; Permana, Randy; Rahmi, Nadya Alinda; Zain, Ruri Hartika
Journal of Applied Data Sciences Vol 7, No 1: January 2026
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v7i1.1092

Abstract

This study presents a hybrid ensemble learning framework designed to enhance the predictive accuracy, robustness, and generalizability of heart disease classification models. The framework integrates three base classifiers: Decision Tree (DT), Gaussian Naive Bayes (GNB), and K Nearest Neighbor (KNN), which are combined using a stacking ensemble method with Logistic Regression (LR) as the meta learner. Each classifier contributes a distinct analytical perspective: DT models nonlinear relationships, GNB provides probabilistic reasoning, and KNN captures similarity-based patterns. Logistic Regression aggregates their outputs to produce a unified predictive decision. To mitigate class imbalance commonly observed in clinical datasets, the Synthetic Minority Oversampling Technique (SMOTE) is applied to generate synthetic samples of the minority class, improving the model’s ability to recognize underrepresented cases. Hyperparameter optimization is performed using the Optuna framework, which applies the algorithm to efficiently explore parameter configurations. The proposed model was evaluated on a publicly available heart disease dataset and achieved an accuracy of 99.61%, precision of 99.62%, recall of 99.59%, F1 score of 99.60%, and specificity of 99.58%, corresponding to a false positive rate of only 0.42 percent. These results demonstrate the framework’s strong ability to accurately identify heart disease cases while minimizing misclassification. The integration of SMOTE, stacking, and Optuna optimization contributes to its superior performance and robustness. Consequently, this approach shows strong potential for integration into clinical decision support systems to assist healthcare professionals in reliable and timely diagnosis.
Optimization of LPG Gas Distribution Routes with a Combination of the Saving Matrix Method and Nearest Neighbor Amin Amirul Mukminin, Andi; Hendrik, Billy; Sovia, Rini
Jurnal KomtekInfo Vol. 12 No. 4 (2025): Komtekinfo
Publisher : Universitas Putra Indonesia YPTK Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35134/komtekinfo.v12i4.656

Abstract

Distribution is an important process in economic activities, which involves the delivery of goods or products from producers to end consumers. Efficiency in the distribution system highly depends on the selection of optimal routes, which can affect costs, time, and the quality of service provided. PT Amartha Anugrah Mandiri, which operates in the distribution of 3 kg LPG, faces significant challenges in terms of inefficient distribution route selection, limited fleet capacity, and unstructured variations in LPG demand. The distribution routes currently used do not consider the aspects of distance, time, and cost efficiency, resulting in the wastage of resources such as fuel and time. This research aims to optimize LPG distribution routes. The methods used in this study are the Saving Matrix and Nearest Neighbor. The Saving Matrix method is used to reduce distribution distance and costs by combining existing delivery routes, while the Nearest Neighbor is applied to determine the order of visits to the nearest bases gradually. Both methods are designed to produce distribution routes that are efficient in terms of time, distance, and cost, as well as to maximize the use of the existing fleet. The data in this study were obtained thru direct observation at PT. Amartha Anugrah Mandiri. The data collected included base locations, LPG demand, vehicle capacity, and operational costs. There are 22 bases served with a total delivery reaching 1120 LPG 3 kg cylinders spread across various sub-districts of Batam City. Deliveries are carried out using trucks with a maximum capacity of 560 cylinders, so in one day, distribution requires more than one trip. Using this data, the distance matrix and savings matrix were calculated to design a more efficient distribution system. The research results show that the application of these two methods successfully reduced the total distance traveled, delivery time, and operational costs significantly, as well as improved the efficiency of LPG distribution. This research is expected to contribute to the company so that the 3 kg LPG delivery process can run optimally.
Co-Authors Abuzar Gafari Adiddo Restiady Adinda Syalsabila Aditra Agus Salim, David Ahsan Firdaus Al-arrafi, Muhammad Ikhsan Amin Amirul Mukminin, Andi Anam, M Khairul Anggy Wahyudi ANIP FEBTRIKO Aulia Fitrul Hadi Aulia Fitrul Hadi Awal, Hasri Borianto, B Chairunnissa Deliva Akbar, Syifa Dede Pratama Deny Suyandi Deval Gusrion Devia Kartika Devita, Retno Dila, Rahmah Dwi Andhara Valkyrie Dwiki Aulia Fakhri Edo Rinaldi Rais Effendy, Geraldo Revanska Eka Praja Wiyata Mandala Elmi Rahmawati Elmi Rahmawati, Elmi Encik Yoega Renaldi Erlanda, Hadrian Fana, Wulan Stau Fatimah, Noor Firdaus Gema, Rima Liana Gunadi Widi Nurcahyo Guslendra Guslendra Guslendra Guslendra Gusriva, Revi Hadi, Aulia Fitrul Hadiyanto, Tegas Hanippa Prima Putra Harnaranda, Jefri Hartika Zain, Ruri Hartika Hendri Irawan Hendrik, Billy Heriyanto Hoka Muhgrah Sandawa Huda, Ramzil Ika Melinia Sapitri Fitriyanti Ilsa Hidayat Irzal Arief Wisky Islam, Md Ataul Jimmy Febio Julsapargi Nursam Khomsi, Ahmad Lidya Adriani Darma Lony Armawati Tambunan Lubis, Fitri Amelia Sari maha rani Maha Rani Mardhiah, Sitty Mhd Wedo Muhammad Aidil Rahman Muhammad Reza Putra Muhammad, Abulwafa Mutiana Pratiwi Niken Rindiana Noviardi, Refli Nugraha, Fajri Nurdiansyah, Ali Nursam, Julsapargi Nursyahrina Permana, Randi Permana, Randy Prihandoko Putra, Kharisma Utama Putri Melati Putri Melati Rahmad Rahmad Rahman, Muhammad Aidil Rahman, Zumardi Rahmi, Nadya Alinda Raja Ayu Mahessya Ramadani, Sela Ramadhanu, Agung - Randa Mahardika Randy Permana Randy Permana Revi Gusriva Ricki Ardiansyah ricki ardiansyah Ricki Ardiansyah Ricki Ardiansyah, Ricki Ridwan Sutri Rinaldi Chan, Fajri Rindhani Aditia, Mellya Riska Amelia Riyan Saputra Riyan Saputra, Riyan Roza, Yesi Betriana Rozakh, Muhammad Ruri Hartika Zain Ruri Hartika Zain Ruri Hartika Zain S, Sumijan Sandawa, Hoka Muhgrah Saputra, Charisman Fajri Saputra, Oriza Rama Saputra, Randy Sarjo Defit Sarjon Defit Sarjon Defit Selfi Melisa Selvia, Dina Shally Amna Shary Armonitha Lusinia Shary Armonitha Lusinia Silky Safira Siregar, Diffri Sulastri Sulastri Sumijan Sumijan Sumijan Sumijan Sumijan Sumijan Sutri, Ridwan Syafri Arlis Syafril Syafril Syaiffullah, Afif Tika Christy Tri Rahayuningsih Tuti Nabila Wahyudi, Anggy Widya Nursanty Wifra Safitri Wirdawati, Wira Yanti, Rahma Yanto, Musli Yanto, Musli Yasmin, Nabilla Yenila, Firna Yuhandri Yuhandri Yuhandri Yuhandri Yuhandri, Yuhandri Yuhandri, Y