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Raissa Amanda Putri

Universitas Islam Negeri Sumatera Utara

Author-ID : 2532773

Religion 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 Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Neuroscience Physics Public Health Social Sciences Other

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Klasifikasi Stance Opini Publik Komentar TikTok Kasus Guru Menampar Murid memakai TF-IDF dan SVM Yusra, Salsabila; Putri, Raissa Amanda
Jurnal Sistem Komputer dan Informatika (JSON) Vol. 7 No. 3 (2026): Maret 2026
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/json.v7i3.9544

Media sosial TikTok menjadi salah satu platform utama dalam menyampaikan opini publik terhadap isu sosial yang bersifat viral, termasuk kasus guru yang menampar murid karena merokok di sekolah. Kasus ini memunculkan perbedaan pandangan yang tajam di masyarakat antara pihak yang mendukung tindakan guru sebagai bentuk pendisiplinan dan pihak yang menilai tindakan tersebut sebagai bentuk kekerasan dalam pendidikan. Penelitian ini bertujuan untuk menganalisis sentimen publik di TikTok terhadap kasus tersebut menggunakan metode Support Vector Machine (SVM). Data penelitian berupa 2.200 komentar publik dikumpulkan melalui teknik web scraping menggunakan Apify Web Scraper dan diolah menggunakan Google Colab. Tahapan penelitian meliputi preprocessing teks yang terdiri dari cleaning, case folding, tokenization, normalisasi, stopword removal, dan stemming. Selanjutnya, fitur diekstraksi menggunakan metode Term Frequency–Inverse Document Frequency (TF-IDF) dan diklasifikasikan ke dalam empat kategori sentimen, yaitu Mendukung Guru, Menyalahkan Guru, Mendukung Murid, dan Menyalahkan Murid. Hasil penelitian menunjukkan bahwa metode SVM dengan kernel linear berhasil mengklasifikasikan sentimen publik dengan akurasi 94% (precision 0.94, recall 0.94, F1-score 0.94). Distribusi sentimen menunjukkan 69.2% komentar mendukung guru, 20.8% mendukung murid, 5.5% menyalahkan guru, dan 4.5% menyalahkan murid. Hasil ini memberikan gambaran komprehensif bahwa mayoritas masyarakat cenderung membenarkan tindakan disiplin guru, meskipun terdapat kesadaran yang berkembang terhadap perlindungan anak dan penolakan kekerasan dalam dunia pendidikan.

Evaluasi Smile dalam Pengelolaan Data dan Informasi : ( Studi Kasus BPJS Ketenagakerjaan Cab.Tanjung Morawa ) Nurul Ifkah Lolona Silalahi; Raissa Amanda Putri
Jurnal Sistem Informasi dan Ilmu Komputer Vol. 2 No. 3 (2024): Agustus : Jurnal Sistem Informasi dan Ilmu Komputer
Publisher : International Forum of Researchers and Lecturers

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59581/jusiik-widyakarya.v2i3.3794

Evaluation of SMILE in Data and Information Management (Case Study of BPJS Employment, Tanjung Morawa Branch) Using the User Compatibility Method. Effective data and information management in financial institutions such as BPJS Employment requires an application system that meets user needs. This research aims to evaluate SMILE at the Tanjung Morawa BPJS Employment Branch using the User Compatibility method, which assesses the extent to which the application meets the user's needs, abilities and expectations. This research method involves a survey of SMILE users at BPJS Employment Tanjung Morawa Branch, taking into account aspects of usability, efficiency and user satisfaction. Data was collected through questionnaires, interviews and direct observation of smile users. The evaluation results show that SMILE at BPJS Employment Tanjung Morawa Branch has a high level of compatibility with users. The research results show that all EUCS independent variables (indicators), consisting of Content (Content), Format (report), Accurancy (accuracy), Timeliness (speed of presentation), Ease of Use (easy to use), which have a significant relationship with user satisfaction SMILE. Users find this application easy to use, improves work efficiency, and meets their expectations regarding data and information management. However, several recommendations for improvement were also put forward, including increased training for users, improved integration with other systems, and improved data security. This study makes an important contribution to further understanding the extent to which SMILE meets user needs in internal environments. The evaluation results and recommendations produced can serve as guidelines for developing and improving smile in the future.

EDUKASI PENGGUNAAN MEDIA SOSIAL UNTUK MENGANTISIPASI IBU-IBU TERHADAP BERITA HOAX DI DESA AEK LOBA AFD I, KEC. AEK KUASAN, KAB. ASAHAN Raissa Amanda Putri; Liza Khairani; Nadiyah Khairiyah; Ummi Afzah Amirah; Izma Khoiruna
Martabe : Jurnal Pengabdian Kepada Masyarakat Vol 6, No 7 (2023): Martabe : Jurnal Pengabdian Kepada Masyarakat
Publisher : Universitas Muhammadiyah Tapanuli Selatan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31604/jpm.v6i7.2595-2602

Kegiatan pengabdian masyarakat yang bertujuan mengedukasi penggunanaan media sosial untuk mengantisipasi ibu-ibu terhadap berita hoax di Desa Aek Loba Afd I Kecamatan Aek Kuasan, Kabupaten Asahan. Adapun Metode yang digunakan dalam KegiatanÂ Â PengabdianÂ Â KepadaÂ Â Masyarakat diÂ Desa Aek Loba ADF I Kecamatan Aek Kuasan, Kabupaten Asahan adalah Community Based Research (CBR) yang merupakan pendekatan dengan melibatkan masyarakat di berbagai level peran dan partisipasi yang akan memberi manfaat bagi komunitas atau masyarakat itu sendiri. RancanganÂ Â evaluasiÂ Â yangÂ Â dilakukanÂ Â dalamÂ Â kegiatanÂ Â pengabdianÂ Â masyarakat adalahÂ Â denganÂ Â cara melakukan pre-test dan post-test kepadaÂ pesertaÂ untukÂ melihat peningkatanÂ pengetahuanÂ danÂ pemahamanÂ peserta sebelumÂ danÂ setelahÂ mengikutiÂ edukasi Edukasi Penggunanaan Media Sosial Untuk Mengantisipasi Ibu-Ibu Terhadap Berita Hoax di Desa Aek Loba ADF I Kecamatan Aek Kuasan, Kabupaten Asahan melaluiÂ kuisionerÂ yangÂ telahÂ disusun oleh penulis. Setelah pelaksanaan kegiatan pengabdian masyarakat mendapatkan hasil bahwa Dari hasil jawaban kuesioner yang disebarkan kepada 40 orang peserta bahwa 33 orang (82,5%) menjawab sudah mengetahui tentang berita hoax, 29 orang (72,5%) menjawab sudah mengetahui ciri-ciri berita hoax, 32 orang (80%) menjawab sudah mengetahui dampak negative berita hoax, 35 orang (87,5%) menjawab sudah dapat membedakan berita yang valid atau yang palsu serta bagaimana cara membedakannya dan 30 orang (75%) menjawab sudah dapat mengetahui tentang pentingnya mengetahui berita hoax.Â

Application of Total Productive Maintenance in Heavy Equipment Maintenance Information Systems: Penerapan Total Productive Maintenance pada Sistem Informasi Pemeliharaan Alat Berat Diva Aulia; Raissa Amanda Putri
Academia Open Vol. 10 No. 2 (2025): December
Publisher : Universitas Muhammadiyah Sidoarjo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21070/acopen.10.2025.11863

General Background: In the era of digital transformation, efficient industrial asset maintenance is critical to meeting global competitiveness demands. Specific Background: Heavy equipment in sectors like construction, plantations, and agriculture requires significant investment and continuous maintenance, yet many companies still rely on manual, unscheduled, and reactive practices. Knowledge Gap: Limited research addresses the direct integration of Total Productive Maintenance (TPM) with real-time, data-driven maintenance information systems tailored for heavy equipment operations. Aims: This study aims to develop and implement an integrated TPM-based heavy equipment maintenance information system to improve productivity, reduce downtime, and enhance decision-making. Results: Using the Overall Equipment Effectiveness (OEE) method, the system identified performance gaps, with the highest OEE at 97% (Truck) and the lowest at 14% (Roller), enabling targeted maintenance actions. The integration reduced downtime, optimized resource use, and provided predictive insights. Novelty: Unlike prior studies focusing solely on TPM theory or measurement, this work delivers a practical, field-ready, IT-enabled solution directly integrated into daily heavy equipment operations. Implications: The approach offers a scalable model for other industries, supporting sustainable asset management through predictive, data-driven maintenance strategies.Highlight : Integrating TPM with information systems reduces downtime and improves performance. OEE is used to measure the availability, performance, and quality of heavy equipment. The system facilitates real-time monitoring and maintenance decision-making. Keywords :Heavy Equipment, Efficiency, Maintenance, Productivity, Total Productive Maintenance

Sistem Pendukung Keputusan Dalam Pemilihan Buah Semangka yang Layak Dijual Menggunakan Metode AHP dan PROMETHEE Agil Indriyani; Raissa Amanda Putri
Jurnal Sistem Komputer dan Informatika (JSON) Vol. 5 No. 1 (2023): September 2023
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/json.v5i1.6743

Watermelon and Melon Buying and Selling Twins is a business that exports watermelons and melons to various cities owned by Mr. Kliwon whose address is at Pulau Gambar Village. In the Watermelon and Melon Buying and Selling Twins, in selecting the best quality watermelons suitable for sale, problems were found, namely that usually because they were affected by high prices, farmers did not prioritize the best quality watermelons and only focused on the number of fruits to be sold and agents had difficulty selecting watermelons. The best quality is suitable for sale, especially for export outside the city. So, with this problem, the author took the initiative to solve the problem correctly and maximize the determination of watermelons that are suitable for sale by designing and building a web-based decision support system by applying the AHP and PROMETHEE methods to help agents determine the best quality of watermelon. The design of this web-based application was carried out by conducting research at the Watermelon and Melon Buying and Selling Twins by collecting data on watermelon fruit and criteria data on watermelon fruit. After the data was collected, each fruit was weighted and ranked and then entered into the application that had been built. Based on the calculation results in this research, alternative weighting using the AHP method helps weighting with a weight scale of 1 - 9 according to AHP provisions. After carrying out alternative weighting, the next ranking is using the PROMETHEE method to get the netflow value, ranking 1 is obtained by 15 with a netflow value of 3,583 and Rank 15 is obtained by fruit 5 with a netflow value of -1.833.

Sistem Pendukung Keputusan Dalam Menentukan Calon Nasabah Penerima Pinjaman Dana Menerapkan Metode TOPSIS dan AHP Sri Yuslina Siregar; Raissa Amanda Putri
Jurnal Sistem Komputer dan Informatika (JSON) Vol. 5 No. 1 (2023): September 2023
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/json.v5i1.6744

PT. FIFGroup is a company that has obtained permission from the Minister of Finance, where this company carries out business in the field of providing loans in the form of funds. PT. FIFGroup Cikampak is one of several branches in other cities, as a prospective customer there are 5 criteria that must be considered and have been determined, namely according to the prospective customer's income, collateral for the prospective customer, employment, needs and term of borrowing funds. However, when determining potential customers who will receive loan funds, PT.FIFGroup Cikampak still uses manual methods, such as analyzing the conditions attached when applying for funds. In order to avoid errors in customer decision making, a web-based decision support system is needed to provide information quickly and precisely regarding the criteria for prospective customers. This decision support system uses a combination method, namely Topsis (Technique for orders preference by siilatyt ideal solution) and AHP (Analytical hierarchy process), this system can automatically recommend potential loan recipient customers who comply with predetermined criteria. Prospective customers who receive loan funds in this system will produce a ranking based on Topsis and AHP calculations. Based on calculations using the AHP method from the five criteria elements, the alternative weightings use a satty scale weighting of 1-9 according to the provisions of the AHP method. Then the ranking was carried out using the topsis method, resulting in the first rank being the name of the Misno customer with a manual priority of 0.729 and a system of 0.729, the lowest value or lowest ranking of the 15 alternatives, namely Sri Irma Naibaho manual priority of 0.204 and system of 0.204. The design of the decision support system has been successfully built using the Topsis and AHP methods, based on the results of Black Box testing, the system runs very well as desired.

Clustering Pecandu Narkoba Menggunakan Algoritma K-Means Clustering Ikhlasul Amal; Raissa Amanda Putri
Jurnal Sistem Komputer dan Informatika (JSON) Vol. 5 No. 2 (2023): Desember 2023
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/json.v5i2.7009

With the rise of increasingly sophisticated technology in this time of globalization, it is exceptionally simple for the more extensive local area to manage exchanges (drugs). For this reason, the government is constantly trying to stop the spread of drugs among Indonesian people by using any media, ranging from verbal invitations, banners, posters, videos and photos displayed in schools, government and public places. The maltreatment of opiates and perilous medications (drugs) in Indonesia as of late has turned into a difficult issue and has arrived at a condition of concern with the goal that it has turned into a public issue.In order to make it easier for BNN to conduct monitoring and counseling to areas where there are many drug addicts, it is necessary to cluster data on drug addicts in Medan city. To solve the problem, it can be solved by clustering drug addicts in Medan city using the K-Means Clustering Algorithm. The data used comes from the BNN of North Sumatra Province, the data used is data on drug addicts in Medan City in 2020-2023. The purpose of clustering drug addict data in Medan city is to find out areas that are very high, high, low and very low levels of drug addicts.This study found that there are 2 sub-districts with the highest level of drug addiction, 7 sub-districts with a high level of addiction, 7 sub-districts with a low level of drug addiction, and 5 sub-districts with a lowest level of addiction.

Analisis Dan Visualisasi Data Penjualan Menggunakan Exploratory Data Analysis dan K-Means Clustering Shinta Permata Sari; Raissa Amanda Putri
Jurnal Sistem Komputer dan Informatika (JSON) Vol. 5 No. 2 (2023): Desember 2023
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/json.v5i2.7180

Many innovations in the retail sector are closely related to digitalization and technological advances. The value of sales data is increasing as a resource for businesses in today's digital era. Sales data consists of details about the items sold, the clients they serve, sales patterns, and other elements that influence how well a business operates. However, effectively handling and understanding vast and complex sales data can be difficult and confusing. So with this problem the author will determine the annual sales level of the products that are most widely marketed by applying Exploratory Data Analysis (EDA) and the K-Means Clustering Algorithm, the method used is to determine the sales level based on the attributes used, the sales level will later be divided into 3, namely clusters 1 is high, cluster 2 is medium and cluster 3 is low. Based on the results of the EDA and K-Means methods, the results of a sales comparison for 4 years have a average value, indicating that sales in 2019 have large average values between 2020, 2021 and 2022. From the visualization results it can be concluded that there are 27 products in the cluster-1 category, 10 products in the cluster-2 category, and 5 products in the cluster-3 category.

Sistem Informasi Penjadwalan dan Agenda Kegiatan Bagian Kesejahteraan Masyarakat Siti Kania Thisara; Raissa Amanda Putri
Jurnal Ilmu Komputer dan Sistem Informasi Vol. 5 No. 1 (2026): Januari 2026
Publisher : LKP Unity Academy

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70340/jirsi.v5i1.276

The rapid development of information technology has encouraged government institutions to improve efficiency in managing administrative and operational activities. The Community Welfare Section (Kesra) of the Governor’s Office of North Sumatra still faces difficulties in managing schedules and agendas due to manual recording processes. This often leads to overlapping schedules, delayed information delivery, and poor record management. This study aims to design and develop a web-based scheduling and agenda information system to support more effective and integrated administration. The Waterfall software development method was applied, consisting of requirement analysis, system design, implementation, testing, and maintenance stages. The system was developed using PHP programming language and MySQL database. Testing using the black-box method showed that all system functions operate properly, including agenda management, activity archiving, and notification features. The implementation of this system reduces scheduling errors, accelerates information delivery, and supports decision-making based on well-documented data.

IMPLEMENTATION OF DATA MINING ON MUSLIM WOMEN'S CLOTHING SALES USING THE FP-GROWTH METHOD Riko Aldinata; Raissa Amanda Putri
Jurnal Riset Informatika Vol. 7 No. 3 (2025): Juni 2025
Publisher : Kresnamedia Publisher

The Muslim women's fashion industry in Indonesia is growing rapidly, leading to intense competition and requiring business owners to optimize their sales strategies and inventory management. This study aims to identify consumer purchasing patterns at TM Collection Store by applying the FP-Growth data mining method. The data used consists of 1,000 sales transactions from January to April 2024. Data collection was conducted through historical data observation, interviews, and literature review, followed by processing using the FP-Growth algorithm in Google Colab. The analysis results reveal strong associations between products, such as the combination of Paris Premium, shirt cuffs XL, and shirt cuffs L, which show high confidence values and significant lift. These patterns provide valuable insights for decision-making related to restocking and promotional strategies. The findings also help improve operational efficiency by more accurately predicting customer demand. Therefore, the implementation of the FP-Growth algorithm proves effective in processing transaction data to generate relevant information and support more targeted business decisions. This data-driven strategy offers an innovative solution to enhance competitiveness in the continuously growing Muslim women's fashion industry.

Co-Authors Abdillah, Muhammad Oemar Abdul Aziz Khusen Abdul Halim Hasugian ABdul Karim Batubara, ABdul Karim Abu Dardaq Putra Adlani, Farid Adnan Buyung Nasution Afifah Balqis Pasaribu Agil Indriyani Agung Setiawan Hasibuan Agung Wijaya, Agung Agusni Firi Hasian Dalimunthe Aini Sachira, Rheana aji wardana Alasi, Galih Aldy Alfiansyah Aldyansah Arrahman Rianto Ali Ikhwan Ali Ikhwan Ali Ikhwan Alsyah Harahap, Dymas Fatthur Rohim Alwi Perdana Aritonang Amanda, Retno Tri Ananda, Bella Andini Nur Bahri Andini, Novita Rizky Andriani, Mega Andriyani Dwi Astuti Anggi Dessisiliya Anggreini Anggun Monica Dewi Aninda Muliani Anisa Yasmin Annisa Annisa Annisa Shafira Zuhri Apipah, Nur Aprilsyah, Muhammad Arbi, Haris Andika Armansyah Armansyah Aryo Pratama Asti, Dini Audy Andini Lubis Aulia Kartika Dewi Aulia, Dea Liza Aulia, Diva Azhari, M. Faishal Azzahro Simatupang , Siti Fatimah Bagus Setiawan Baridah, Lailam Batara Wardana Yuswar Batubara, Abdul Karim Batubara, Muhammad Zulpan Bela Damanik Bella Ananda Budi Askhori Sirait Budiarti, Dinda Dalimunthe, Rizna Fitriana Dalimunthe, Roma Gabe Damayanti, Alvina Daulay, Ikhsan Agus Martua Daulay, Wan Akbar Arramadhan Decfina, Fauziah Delvira Salsabila Diah Indah Sari Dicky Pratama Dinary Dwihatami Dini Anggraini Disa Pratama Diva Aulia Donas Putra Dwi Himala Kasih Dwi Nenda Putri Dwi Silviana Elang, Nusa Erano, Bhirawa Atha Bassni Erlina, Fazira Fadhlan Hussaini Srg Fadilah, Ayu Fadilah, Ulfa Fadillah, Muhammad Taufik Fahimah, Nurul Fakhri Alauddin Tarihoran Fakhriza, Fakhriza Fakhriza, M. Fara Difa Aulya Farahdiba, Dhika Farhan Rizky Wahyudi Fathiya Hasyifah S FATHIYA HASYIFAH SIBARANI Fathiyah Hasyifah Sibarani Fauziah Lubis Fazril, Fazril Febiyaula, Siti Septia Feby Hasanah Ritonga Fiddarain, Syaidah Fikri Hakiki Siregar Fiqri Fakhrizal Fitrah Al Mubaroq Fitria Tilawatil Aulia Simarmata Garnish Ayu Andini Wijaya Gina Sonia Hadi, Firman Harahap, Ahdi Alfein Harahap, Faisal Harahap, Nurhaliza Hary Isdianto Hasibuan, Muhammad Imbalo Zaki Hasibuan, Novrisyah Hasibuan, Nurhabibah Febrianty Hasyifah Sibarani, Fathiya Heri Santoso Heri Santoso Heri Santoso Hidayat, Julkarnain Hidayati, Lily Hutasuhut, Fazira Syafitri Ibnu Faisal Ikhlasul Amal Ilka Zufria Imam Adlin Sinaga Imam Adlin Sinaga Imam Zarkasih Harahap Irsandi, Mahmul Izma Khoiruna Jihan Fadhilah Taher Khairi, Ananda Salsabila Khotnai Shinta Khotnai Shinta Koto, Muhammad Hendrik Laily, Dwi Yanti Laylan Syafina Lestari, Rika Dinda Liza Khairani Lubis, Fitra Hidayat M irsyan antony manday, Irsyanmanday M Taufiq Rachman Siregar M. Fakhriza malika, Sela Maulana, Mhd.Rizki Maulina Tria Audina Gultom Maurico Liang Maya Khairani Mega Andriani Mega Andriani Mhd Furqan Miftah Siregar Mikraj, Ziyad Habibul Mohammad Badri Mohammad Badri Mu'arif, Risdani Mubaraq, Aras Maulana Much Nur Syams Simaja Muhamad Alda Muhamad Rizky Abdilah Muhammad Abdul Arip Muhammad Aprilsyah Muhammad Dedi Irawan Muhammad Ikhsan Muhammad Irvan Muhammad Naufal Al Hazmi Muhammad Ray Pratama Sembiring Muhammad Rivaldi Muhammad Setiawan Muliani Harahap, Aninda Muliani, Aninda Mulya Alfan Simatupang Nabila Bidawi, Hilwa Faza Nabila, Andini Nabilah Aliya Tasya Nadiyah Khairiyah Nafis, Ayu Najwa Nabila Nasution, Adnan Buyung Nasution, Imam Fadli Nasution, Maimanah Salsabila Nasution, Muhammad Irwan Padli Nasution, Rizki Ansyari Nataryda Lubis, Muara Novrisyah Hasibuan Nst, Achmad Ramadhan Nugroho, Agung Nurhabibah Febrianty Hasibuan Nurhasanah, Dhea Aulia Nurhayati Nurhayati Nurul Ifkah Lolona Silalahi Nurul Mawaddah Padang Nurul Zuriandini Paranindra Ardhana Biroe Aurori Pasaribu, Haryati Pertiwi, Elsa Pratama, Dino Farid Prayuda, Wahyu Putra Purwaningtyas, Franindya Puspa, Yulia Putra, Dafa Fahreza Putrawan, Putrawan Putri Agustina Putri Lubis, Dina Amalia Rafli Khalis Nugraha Rahma Yuni Rahma, Anisa Sri Rahma, Baqiyatur Rahma, Najahaura Rambe, Risti Reni Lestari Reni Yunita Riko Aldinata Rinaldy, Fahdly Ritonga, Siti Marlina RR. Ella Evrita Hestiandari Sabri, Muhammad Sahbandi Sahbandi Sahnas Wulandari Sahnas Wulandari Siregar Sait, M Ibnu Salsabila, Salsabila Salsalina Br Sembiring Samsudin Samsudin, Samsudin Santoso, Adinda Afriliya Saprida Saprida Saprida, Saprida Saputri, Indah Sardiyana Br Karo Sari, Dinda Mayang Shinta Permata Sari Siagian, Andika Fadillah Sigit Bahuraksa Silvia Kartika Sinaga, Adhe Syari Alfatah Sinaga, Imam Adlin Sinta Dewi Siregar, Ela Khairani Siregar, Elvan Dito Siregar, Fairuz Azzaria Siregar, Putri Aprilia Siswahyudianto Siti Kania Thisara Siti Zahra Situmeang, Risky Akbar Sri Yuslina Siregar Sriani Sriani Suendri Suendri, Suendri Suendri, Suendri Syah Zanul Husna Syahputra, Adam Tania Yulindra Teuku Alif Baihaqy Thamrin, Alwi Aryusya Triase Triase Triase Triase Triase Triase Triase Triase Triase Triase, Triase Tua, Anri Hafiz Ulfayani Mayasari Ummi Afzah Amirah Wahyu Herlambang Wanda Sari Wanda Wardana, Aji Wardhani, Ade Ratu Wibowo, Muhammad Rizky Widodo, Mhd. Aria Agung Willy Andri Malau Windi Maharani Winny Wiyandari Wiradito, Ade Yahfizham Yahfizham Yardha, La Saufa Yudha, Fajrul Aulia Yudi Lizardi Mahna Siregar Yulianda Tasya Yusniah Yusniah Yusra, Salsabila Yustria Handika Siregar Yusuf Ramadhan Nasution Yusuf Ramadhan Nasution, Yusuf Ramadhan Zahidah, RA. Ghina Zahrowaini, Taqiya

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