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All Journal Jurnal Edukasi dan Penelitian Informatika (JEPIN) JURNAL PENGABDIAN KEPADA MASYARAKAT Sinkron : Jurnal dan Penelitian Teknik Informatika Tech-E RABIT: Jurnal Teknologi dan Sistem Informasi Univrab JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING JURNAL MEDIA INFORMATIKA BUDIDARMA Abdimas Talenta : Jurnal Pengabdian Kepada Masyarakat Nizhamiyah JurTI (JURNAL TEKNOLOGI INFORMASI) Query : Jurnal Sistem Informasi Zero : Jurnal Sains, Matematika, dan Terapan ALGORITMA : JURNAL ILMU KOMPUTER DAN INFORMATIKA JISTech (Journal of Islamic Science and Technology) Jurnal Teknologi Sistem Informasi dan Aplikasi Digital Zone: Jurnal Teknologi Informasi dan Komunikasi J-SAKTI (Jurnal Sains Komputer dan Informatika) IJISTECH (International Journal Of Information System & Technology) JURIKOM (Jurnal Riset Komputer) Journal on Education JOURNAL OF SCIENCE AND SOCIAL RESEARCH Saintifik : Jurnal Matematika, Sains, dan Pembelajarannya Jurnal Ilmiah Binary STMIK Bina Nusantara Jaya Jurnal Kridatama Sains dan Teknologi Jurnal Ilmu Komputer dan Bisnis Aisyah Journal of Informatics and Electrical Engineering Jatilima : Jurnal Multimedia Dan Teknologi Informasi JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Journal of Computer System and Informatics (JoSYC) INFOKUM Jurnal Sistem Komputer dan Informatika (JSON) TIN: TERAPAN INFORMATIKA NUSANTARA Brahmana : Jurnal Penerapan Kecerdasan Buatan MEANS (Media Informasi Analisa dan Sistem) Journal of Computer Networks, Architecture and High Performance Computing Jurnal Teknologi Informasi dan Komunikasi Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) IJISTECH JINAV: Journal of Information and Visualization Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer) Jurnal Responsif : Riset Sains dan Informatika Syntax: Journal of Software Engineering, Computer Science and Information Technology Journal La Multiapp Jurnal Abdi Mas Adzkia Fitrah: Journal of Islamic Education KLIK: Kajian Ilmiah Informatika dan Komputer Journal of Information Technology (JIfoTech) Instal : Jurnal Komputer J-SAKTI (Jurnal Sains Komputer dan Informatika) Journal of Dinda : Data Science, Information Technology, and Data Analytics International Journal Software Engineering and Computer Science (IJSECS) Journal of Computer Science and Informatics Engineering sudo Jurnal Teknik Informatika Jurnal Sistem Informasi Triguna Dharma (JURSI TGD) Jurnal Nasional Teknologi Komputer NUSANTARA: Jurnal Pengabdian Kepada Masyarakat Journal of Computers and Digital Business Sewagati: Jurnal Pengabdian Masyarakat Indonesia DEVICE : JOURNAL OF INFORMATION SYSTEM, COMPUTER SCIENCE AND INFORMATION TECHNOLOGY Jurnal Pengabdian Masyarakat The Indonesian Journal of Computer Science Cosmic Jurnal Teknik
Ilka Zufria
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Sentiment Analysis Study Tour Bus Ban on Twitter Using Support Vector Machine Method Purba, Ony Hizri Kaifa; Zufria, Ilka
Journal of Computer System and Informatics (JoSYC) Vol 5 No 4 (2024): August 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v5i4.5726

Abstract

Study tour is an activity outside the classroom that has the purpose of learning about the process of something directly. This activity is usually carried out by the school once a year. This activity is not only a learning tool for students, but also a recreational activity.In this activity, there are many things that need to be prepared, such as transportation, lodging, meals, and so on. This is sometimes troublesome, because not all tourists or business people have the time and willingness to prepare it. Therefore, they need services during their trip. Especially now that it is even semester, where every school usually holds a study tour, as well as a final class farewell. As a response to concerns, some parents may choose to find alternative activities that are considered safer for their children, such as joining activities in the city or at school. Based on this need, it makes opportunities for business people engaged in the tour agency industry. SVM (Support Vector Machine) is a machine learning method that works on the principle of Structural Risk Minimization (SRM) with the aim of finding the best hyperlane separating two classes in the input space. Simply put, SVM (Support Vector Machine) has the concept of finding the best hyperlane, which serves as the boundary of two classes The results of sentiment classification on Study Tour Buses using the Support Vector Machine algorithm that matches the actual data amount to 176 data out of a total of 240 test data. It is known that of the 1200 data obtained regarding sentiment towards there are 519 reviews that are positive and 681 reviews that are negative.The accuracy value of the Study Tour Bus sentiment classification using the Support Vector Machine (SVM) algorithm obtained is 73%.
Clustering Analysis of Bus Fares Trans Metro Deli Medan Using Mean Shif Clustering Method Rambe, Rinanda Putri; Zufria, Ilka
Journal of Computer System and Informatics (JoSYC) Vol 5 No 4 (2024): August 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v5i4.5728

Abstract

Medan City is the 3rd most populous city in Indonesia, according to data from the Central Statistics Agency, Medan has a population of 2.49 million in 2022, an increase from the previous 2.46 million in 2021. The increasing number of population inhabiting the city of Medan means that the need for transportation for the people of Medan is also increasing. Trans Metro Deli bus data can be grouped effectively using the mean shift algorithm based on several attributes, namely passenger category, payment method and fare. Each passenger group has different needs and ability to pay, which makes setting fair and efficient fares a challenge. Inappropriate pricing can lead to passenger dissatisfaction, reduce the number of public transportation users, and affect bus operators' revenue. Cluster technique is a well-known clustering technique, which aims to group data into clusters so that each cluster contains data that is as similar as possible. Mean shift belongs to the category of clustering algorithms with unsupervised learning that assigns data points to clusters iteratively by shifting the points towards the mode (mode is the highest density of data points in the region in the context of mean shift). Mean shift does not require determining the number of clusters in advance The attributes used in the clustering process, namely passenger category, payment method and fare can properly create a hyperplane between clusters, thus creating significant differences from each cluster, as evidenced by the silhouette score obtained by 0.64. By conducting this analysis, it is expected to find a more efficient and fair fare clustering pattern, and provide practical recommendations for management in setting fares that are more in line with passenger needs. In addition, this research also aims to evaluate the effectiveness of mean shift clustering in the context of transportation fare analysis.
Sentiment Analysis of Support for the DPR's Right to Inquiry on the Issue of 2024 Election Fraud Using the Support Vector Machine Method Sephia, Putri Aisyah; Zufria, Ilka
Journal La Multiapp Vol. 5 No. 5 (2024): Journal La Multiapp
Publisher : Newinera Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37899/journallamultiapp.v5i5.1523

Abstract

This research aims to analyze public sentiment towards supporting the DPR's right to inquiry in the 2024 Election fraud issue using the Support Vector Machine (SVM) method. Data was obtained from the social media application X which has a wide user base and is relevant to the issue under study. Comments on the application are classified into positive and negative sentiments after going through the pre-processing stage. The SVM method was chosen because of its high ability in text classification based on appropriate kernels. This research shows how much influence the X application has in identifying public sentiment and the effectiveness of the SVM method in sentiment classification. It is hoped that the research results will provide in-depth insight into public sentiment regarding the issue of fraud in the 2024 elections and support better decision making in the context of politics and democracy in Indonesia.
Android Based LPG Leak Detection Application Sari, Silvia; Zufria, Ilka; M. Fakhriza
Bahasa Indonesia Vol 16 No 01 (2024): Instal : Jurnal Komputer
Publisher : Cattleya Darmaya Fortuna

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54209/jurnalkomputer.v16i01.189

Abstract

The educational application of LPG leakage is an innovative solution designed to provide a comprehensive understanding of gas leakage in LPG devices Therefore, it is important for LPG device users requipment to understand the signs of a gas leakage, the actions should be taken, and the preventive steps that can be taken to reduce the risk of accidents and fires. This application provides information that is easy to understand with features for safe handling, tube installation, safety tips along with video tutorials and notifications when there is an LPG gas leakage. With this application, LPG device users will be able to increase their awareness and knowledge about gas leakage. This application can provide ongoing education about the importance of safety maintenance and proper prevention of gas leakage for users, so that can be reduce the risk of serious accidents.
Application of The Production Unit Method to Calculate Accumulated Depreciation of Factory Machinery using The Django Model Pratama, Bagus Aji; Ilka Zufria; M. Fakhriza
Bahasa Indonesia Vol 16 No 02 (2024): Instal : Jurnal Komputer
Publisher : Cattleya Darmaya Fortuna

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54209/jurnalinstall.v16i02.203

Abstract

The research was carried out with the aim of making it easier for companies to record and make depreciation reports on factory machines by utilizing existing information systems, to apply the service hours and production unit method in determining depreciation reports on factory machines in companies, to carry out analysis of depreciation data on factory machines in companies, to design and build a system for calculating depreciation of factory machines using the service hour method and the production unit method and to implement a comparison of the service hour method and the production unit method in the factory machine depreciation system. The problem faced by the company is that there is no application program for calculating depreciation on factory machines every month, so it takes quite a long time to determine the amount of depreciation on factory machines and the accumulated depreciation of factory machines every month and the reports obtained are less effective and less efficient. And in determining depreciation of processing factory machines, a special method has not been used to calculate depreciation of factory machines. The company still has many weaknesses, including recording errors, calculation errors, and also the process of making reports which takes a relatively long time.
ALGORITMA SAW DAN TOPSIS MENENTUKAN BIBIT UNGGUL KELAPA SAWIT Ilham Maulana Ritonga; Ilka Zufria; M. Fakhriza
JOURNAL OF SCIENCE AND SOCIAL RESEARCH Vol 7, No 3 (2024): August 2024
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/jssr.v7i3.2137

Abstract

Pemilihan bibit kelapa sawit merupakan langkah awal dari budidaya tanam kelapa sawit. Pemilihan bibit kelapa sawit perlu diperhatian untuk mendapatkn hasil panen yang baik. Sistem pendukung keputusan dapat menjadi salah satu solusi untuk permasalahan pemilihan bibit sawit. Jenis bibit kelapa sawit dapat dipilih berdasarkan aspek dan kriteria tertentu. Kriteria yang digunakan yaitu umur panen perdana, rerata produksi tandan buah segar, rerata potensi total produksi minyak, panjang pelepah, presentase inti buah, rerata berat tandan, presentase rendemen, pertumbuhan meninggi. Algoritma SAW merupakan salah satu metode pengambilan keputusan dengan konsep dasar mencari penjumlahan terbobot dari rating kinerja pada setiap alternatif pada semua atribut. Sedangkan algoritma TOPSIS merupakan mrtode pengambilan keputusan multi kriteria dengan dasar alternatif yang dipilih memiliki jarak terdekat dengan solusi ideal positif dan memiliki jarak terjauh dari solusi ideal negatif. Hasil dari penelitian yaitu metode SAW dan TOPSIS berhasil diimplementasikan kedalam bentuk pengambilan keputusan berbasis website dan menampilkan hasil perankingan bibit unggul kelapa sawit.
ANALISIS SENTIMEN KEPERCAYAAN MASYARAKAT TERHADAP KEPOLISIAN REPUBLIK INDONESIA MENGGUNAKAN ALGORITMA SVM Ilka Zufria; Aidil Halim Lubis; Siti Septia Febiyaula
JOURNAL OF SCIENCE AND SOCIAL RESEARCH Vol 7, No 3 (2024): August 2024
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/jssr.v7i3.2118

Abstract

Abstract: Based on Law No. 2 of 2002, Indonesia states that the National Police of the Republic of Indonesia is a state instrument that plays a role in maintaining security and public order, enforcing the law and providing protection, protection and service to the community. In the eyes of the public, public services are experiencing a crisis of trust. This crisis provides important lessons for local governments and the police in Indonesia. With various news about the police via internet media, especially Twitter, which can influence public opinion. User opinions are used as research material for sentiment classification using the SVM algorithm using 801 data. The data is then given labels (classes) using a lexicon based method with an Indonesian language dictionary. From the labeling results, 444 positive opinions and 357 negative opinions were obtained. From several opinions that have been obtained, sentiment analysis will be carried out using the SVM algorithm. This research also applies the word weighting method or TF-IDF. The system will be evaluated using Confusion Matrix. In the test results, it was found that the level of accuracy produced using the Support Vector Machine algorithm was 83.95%, precision was 85.71%, recall was 87,50%, and f1-score was 86.60%. Keywords: Sentiment Analysis, Indonesian Republic Police, SVM Abstrak: Berdasarkan Undang-undang No.2 Tahun 2002, Indonesia menyatakan bahwa Kepolisian Negara Republik Indonesia adalah alat negara yang berperan dalam memelihara keamanan dan ketertiban masyarakat, menegakkan hukum serta memberikan perlindungan, pengayoman dan pelayanan kepada masyarakat. Di mata masyarakat, pelayanan publik sedang mengalami krisis kepercayaan. Krisis ini menjadikan pelajaran penting bagi pemerintah daerah dan kepolisian di Indonesia. Dengan adanya berbagai berita mengenai kepolisian melalui media internet khususnya twitter yang dapat memengaruhi opini masyarakat. Opini pengguna dimanfaatkan sebagai bahan penelitian klasifikasi sentimen menggunakan algoritma SVM dengan menggunakan 801 data. Data kemudian diberi label (kelas) dengan menggunakan metode lexicon based dengan kamus berbahasa Indonesia. Dari hasil pelabelan diperoleh data berlabel positif sebanyak 444 opini dan 357 opini negatif. Dari beberapa opini yang sudah didapatkan, maka akan dilakukan analisis sentimen dengan menggunakan algoritma SVM. Penelitian ini juga menerapkan metode pembobotan kata atau TF-IDF. Sistem akan dievaluasi dengan menggunakan Confusion Matrix. Pada hasil pengujian didapatkan tingkat akurasi yang dihasilkan dengan menggunakan algoritma Support Vector Machine adalah sebesar 83.95%, precision sebesar 85.71%, recall sebesar 87,50%, dan f1-score sebesar 86,60%. Kata kunci: Analisis Sentimen, Kepolisian Republik Indonesia, SVM
PERANCANGAN SISTEM PAKAR MENDIAGNOSIS PERMASALAHAN KULIT BESERTA JENIS KULIT WAJAH DALAM PENENTUAN PRODUK PERAWATANNYA MENGGUNAKAN METODE FORWARD CHAINING DAN CERTAINTY FACTOR Winny Wiyandari; Ilka Zufria; Raissa Amanda Putri
JOURNAL OF SCIENCE AND SOCIAL RESEARCH Vol 7, No 3 (2024): August 2024
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/jssr.v7i3.2131

Abstract

Abstract: As the times progress, women need something fast and appropriate to take care of their facial skin. Most people may find it difficult to choose with certainty products that suit the problems that exist on the skin of the face. Design an expert system in diagnosing problems with facial skin and identifying facial skin types in the determination of facial care products. In this study, researchers made an expert system to diagnose skin problems and facial skin types in determining their treatment products using the Forward Chaining and Certainty Factor methods. This website can help women to choose their type of facial skin products and treatments as well as make it easier for women. Advantages of Forward Chaining and Certainty Factor in Expert Systems collect information and find the best solution obtained from the collection of information, and contain uncertainty so in the calculation process can only process some data so that the lack of data can be maintained. The need for the development of the website so that this website becomes a larger scale to be more complete and more perfect such as the addition of data about skin care and brands that are suitable for use. This website is only as an initial diagnosis, it would be nice to do more research on the products to be used and if necessary consult a dermatologist. Keywords: Certainty Factor, Forward Chaining, Expert System, Skin, Website. Abstrak: Seiring kemajuan zaman, wanita membutuhkan sesuatu yang cepat dan tepat untuk merawat kulit wajahnya. Kebanyakan orang mungkin merasa kesulitan untuk memilih dengan pasti produk yang sesuai dengan permasalahan yang ada pada kulit wajah. Merancang sistem pakar dalam mendiagnosis permasalahan pada kulit wajah dan mengidentifikasi jenis kulit wajah dalam penentuan produk perawatan wajah. Pada penelitian ini peneliti membuat sistem pakar untuk mendiagnosis permasalahan kulit dan jenis kulit wajah dalam menentukan produk perawatannya menggunakan metode forward chaining dan certainty factor. Website ini dapat membantu para wanita untuk memilih jenis produk dan perawatan kulit wajah serta memudahkan para wanita. Keunggulan forward chaining dan certainty factor pada sistem pakar mengumpulkan informasi dan mencari solusi terbaik yang diperoleh dari pengumpulan informasi tersebut, serta mengandung ketidakpastian sehingga dalam proses perhitungannya hanya dapat mengolah sebagian data saja sehingga kekurangan data dapat dipertahankan. Perlunya pengembangan website agar website ini menjadi skala yang lebih besar agar lebih lengkap dan sempurna seperti penambahan data mengenai skincare dan merk yang cocok untuk digunakan. Website ini hanya sebagai diagnosis awal, alangkah baiknya jika dilakukan penelitian lebih lanjut terhadap produk yang akan digunakan dan bila perlu berkonsultasi dengan dokter spesialis kulit Kata kunci: Certainty Factor, Forward Chaining, Sistem Pakar, Kulit, Website   
PREDIKSI PENJUALAN IKAN DENGAN METODE FUZZY TIME SERIES Ilka Zufria; Sulindawaty Sulindawaty; Nurul Fadhillah
JOURNAL OF SCIENCE AND SOCIAL RESEARCH Vol 7, No 3 (2024): August 2024
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/jssr.v7i3.2139

Abstract

UD. Ikan Segar Pasar Simpang Limun adalah salah satu Usaha Dagang di Medan yang bergerak dalam penjualan ikan untuk toko sembako, rumah makan, dan juga konsumsi rumah tangga. Pada operasinya UD. Ikan Segar Pasar Simpang Limun dikirimkan ikan dari pemasok setiap hari untuk memenuhi kebutuhan semua pelanggannya. UD. Ikan Segar Pasar Simpang Limun sering mengalami kesulitan dalam menentukan jumlah persediaan ikan yang dibutuhkan setiap hari, oleh karena itu UD. Ikan Segar Pasar Simpang Limun membutuhkan sistem yang dapat digunakan untuk memprediksi penjualan ikan secara jangka pendek. Berbasis Fuzzy Time Series Markov Chain Average-Based adalah metode prediksi yang menggunakan prinsip Fuzzy dan memiliki akurasi yang cukup baik untuk prediksi, sehingga metode ini sesuai untuk memprediksi penjualan ikan. Data yang digunakan dalam penelitian ini adalah data penjualan ikan dari Januari 2022 – Juli 2023 yang diperoleh dari UD. Ikan Segar Pasar Simpang Limun. Hasil yang diperoleh dalam penelitian ini adalah nilai prediksi dari metode Fuzzy Time Series untuk prediksi penjualan ikan dengan pengujian data pada Januari 2022 – juli 2023 sebanyak 475 data yang diuji dengan Average Forecasting Error Rate (AFER) dan mendapatkan hasil sebesar 0,09412% sehingga termasuk dalam kategori sangat baik, pengujian juga dilakukan dengan Black Box Testing untuk pengujian program.
Sistem Pakar Menggunakan Metode Backward Chaining Untuk Mengantisipasi Permasalahan Tanaman Kacang Kedelai Berbasis Web Zufria, Ilka; Santoso, Heri; Darsih, D
J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 5, No 1 (2021): EDISI MARET
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/j-sakti.v5i1.294

Abstract

Soybeans (Glycine max (L.) Merill.) are an important source of protein in Indonesia, it is a part of variety of beans. The soybeans’ need is increasing as people demand for raw materials. While there are so many problems with soy plants that they cause the decline in soy production. The decline in the production of soybean plants has been due to both pest and disease factors. Therefore in this condition it would require an expert to address the problem of soy farmers, but in this condition the lack of an expert and the time of the expert is a problem, so with by existence expert system can provide an alternative to addressing problems. This system of experts can be used to help soy farmers in an effort to identify pests and crop diseases and how the prevention and treatment of pest and soy diseases. The system was used Backward Chaining methods. This application made based Web used PHP programming language.
Co-Authors Abdul Halim Hasugian Abdul Rasyid Adelina Manik Adnan Buyung Nasution Afira Zulfa Afriani Afriani Agung Hamdika Surya Aidil Halim Lubis Aidil Halim Lubis Aidil Halim Lubis Aila Oktavia Abdul Nst Alfahri, Bagus Ageng Alfiansyah, Raja Alfin Budiman Sihotang Ali Ikhwan Ali Ikhwan Alya, Dea Amri, M Choirul Aninda Muliani Anjani, Retno Anwar Fauzi Apriani Syahputri Aprilia, Nia Arfina Handayani Arianto, Rifdah Armansyah Armansyah Armansyah Arrahman, Said Atiqi, Muhammad Farros Aulia, Muhammad Fathir Batubara, Qisti Azraladiba Ba’ayesh, Mubarak Beni Frandian Bimantara, Muhammad Dhuha Buyung Satrio Dasopang Buyung Satrio Dasopang Chairul Rizal Chintya Anggraini Cindy Juliani Cindy Novi Syahputri Danang Wahyu Wicaksono Darsih, D Daulay, Darisma dedi irawan Desmi Roma Putra Lubis Dharmawan, Kaka Davi Dimas Arya Dimas Arya Dinda Ayu Ningsih Dion Wirayuda Bahri Dollar, Dzulfikri Akbar Dwi Prapita Sari Edilia, Fazila Nazifa Efriliya Hafni Yuswinda Erwin Nasution Fachri, Barany Fadila, Daffa Fadilla, Nurul Fahlome, Dodyk Fahmi Dian Pratama Fahrizal Alwafi Chandra Susi Syafriana Barus Fakhriza, M Fakhriza, M. Fakhriza, M. Farentika, Yosi Firman Syarif Fitri, Wan Ilia Gilang Reynabil Gina Sania Habib Asy Muhyi Hafiz Fawi Anugerah Hakim, Yusrizal Hakim, Yusrizal Hanifa Salsabila Harahap, Parlindungan Harahap, Tiara Bela Harry Setiawan Hasibuan, Naina Nazwa Hasibuan, Nazwa Aliya Muthmainnah Hasugian, Aldi Ridwansyah Hazizah Ulfa Nasution Heri Santoso Heri Santoso Herman, Bintang Kurniawan Ibnu Rusydi Idris Siregar, Idris Ilham Maulana Ritonga Intan Nofitasari Intan Saleha Tinendung Irawati, Cici Iskandar, Isna Damaiani Ismail Husein, Ismail Jayyid Jiddan Juliani, Cindy Kesuma, Beny Khairani, Melvika Kherina Surya Ningsih M Fakhriza M Fakhriza M Ferdiansah Rkt M Taufiq Rachman Siregar M. Fakhriza M. Fakhriza M. Ihsan Lubis Machfudz, Emir Syarif Mahfuza, Salsabila Mardiah Ramadhani Marini Maulana, Rexa Mhd Ikhsan Rifki Mhd. Syahnan Mila Wati, Mila Muchain, Alfira Nafhan Muhamad Alda Muhammad Arif Suhada Muhammad Auliyah Al Ghazali ZA Muhammad Dedi Irawan Muhammad Eka Muhammad Iqbal Nahwi Muhammad Nabhan Akbar Marpaung Muhammad Reyhandi Akbar Muhammad Siddik Hasibuan Muhammad Syahputra Novelan Muhammad Zulfikar Lubis Nasution, Muhammad Irwan Padli Nia Aprilia Nst, Aila Oktavia Abdul Nst, Khusnul Khotimah Nur Hasanah Pohan Nur Nofrizal Agustina Srg Nurainun Syahdia Nurhasanah, Mutia Nurul Fadhillah Nurul Fikria Okta Yuliardi Pandi Ahmad Jawara Pinasthika Alya Disti Pradana, Riski Ananta Pratama, Bagus Aji Purba, Ony Hizri Kaifa Purnamawati, Sri Putra, Fahrialdy Febriansyah Ragilia Putri Dinanti Raissa Amanda Putri Raisyah, Shafira Isra Rakhmat Kurniawan R Ramadani, Suci Adina Ramadhan, M Irsyad Rambe, M. Riski Andika Rambe, Rinanda Putri Rani, Putri Meuthia Rendy Andika, Rendy Revina Putri Damayanti Reza Adhitya Budiman Rina Afriani Sitorus Rini Halila Nasution Rio Rinaldi Risky, Tengku Tanzil Azhari Riswandi Riswandi Riswandi, Arif Rita Sari Dewi Rizky, Ishlahiyah Nur Rkt, M Ferdiansah Roy Surya Fikriadi Samsudin, Samsudin Sari Jamilah Rangkuti Sari, Silvia Sarmila Sarmila Sephia, Putri Aisyah Septiana Dewi Andriana, Septiana Dewi Shania Oktawijaya Simanjuntak, Salmah Simbolon, Zianah Nafisah Sinaga, Annisa Fitri Siti Sarah, Siti Siti Septia Febiyaula Sitorus, Dhafa Hibrizi Sitorus, Dhafa Hibrizi Sitorus, Nur Shafwa Aulia Sitorus, Puan Syaharani Sitorus, Rina Afriani Sriani Sriani Suendri Suendri Suendri, Suendri Suhardi Suhardi Suhardi Suhardi, S Suhardi, Suhardi Sulindawaty Sulindawaty Supiyandi Supiyandi Surbakti, Miftah Hadi Syafitri, Febry Dwi Syafrida, Desy Syapira, Tiwi Talita, Friza Tanjung, Erti Belastari Tanjung, Siti Maya Sari Triase Triase Triase Triase, Triase Ulfia Zahra Utomo, Imam Wahyu Rahmansyah Wahyudi Wahyudi Wardani, Dina Ayu Winny Wiyandari Wiranda Wiranda Yusuf Ramadhan Nasution Yusuf Ramadhan Nasution, Yusuf Ramadhan Zaim Izza Makarim Zebua, Jelita Rahmah