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All Journal JURNAL SISTEM INFORMASI BISNIS EXPERT: Jurnal Manajemen Sistem Informasi dan Teknologi CESS (Journal of Computer Engineering, System and Science) JURNAL PENGABDIAN KEPADA MASYARAKAT Jurnal Ilmiah KOMPUTASI Sistemasi: Jurnal Sistem Informasi Sinkron : Jurnal dan Penelitian Teknik Informatika JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING JURNAL MEDIA INFORMATIKA BUDIDARMA SMARTICS Journal Indonesian Journal of Artificial Intelligence and Data Mining IJIS - Indonesian Journal On Information System JOURNAL OF APPLIED INFORMATICS AND COMPUTING Jurnal Teknik Informatika UNIKA Santo Thomas JurTI (JURNAL TEKNOLOGI INFORMASI) Jiko (Jurnal Informatika dan komputer) ALGORITMA : JURNAL ILMU KOMPUTER DAN INFORMATIKA JISTech (Journal of Islamic Science and Technology) JURNAL TEKNOLOGI DAN OPEN SOURCE Jurnal Teknologi Sistem Informasi dan Aplikasi IJISTECH (International Journal Of Information System & Technology) JOURNAL OF SCIENCE AND SOCIAL RESEARCH Simtek : Jurnal Sistem Informasi dan Teknik Komputer Jurnal Dedikasi Pendidikan Jurnal Teknologi Terpadu EDUMATIC: Jurnal Pendidikan Informatika METIK JURNAL Jurnal Mantik Progresif: Jurnal Ilmiah Komputer Jurnal Ilmiah Sains dan Teknologi (SAINTEK) Zonasi: Jurnal Sistem Informasi Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) Jatilima : Jurnal Multimedia Dan Teknologi Informasi Journal of Intelligent Decision Support System (IDSS) G-Tech : Jurnal Teknologi Terapan 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 Journal of Computer Science, Information Technology and Telecommunication Engineering (JCoSITTE) Journal of Computer Networks, Architecture and High Performance Computing IJISTECH Journal La Multiapp Jurnal Teknologi Sistem Informasi dan Sistem Komputer TGD Bulletin of Computer Science Research KLIK: Kajian Ilmiah Informatika dan Komputer Instal : Jurnal Komputer Jurnal Info Sains : Informatika dan Sains Decode: Jurnal Pendidikan Teknologi Informasi Simpatik: Jurnal sistem Informasi dan Informatika Journal of Dinda : Data Science, Information Technology, and Data Analytics Jurnal IPTEK Bagi Masyarakat Jurnal Mandiri IT Jurnal Teknik Informatika Unika Santo Thomas (JTIUST) Journal of Computer Science and Informatics Engineering Jurnal Informatika Teknologi dan Sains (Jinteks) Jurnal Algoritma Edu Society: Jurnal Pendidikan, Ilmu Sosial dan Pengabdian Kepada Masyarakat Jurnal Komputer Teknologi Informasi Sistem Komputer (JUKTISI) SENTRI: Jurnal Riset Ilmiah Malcom: Indonesian Journal of Machine Learning and Computer Science STORAGE: Jurnal Ilmiah Teknik dan Ilmu Komputer SmartComp Jurnal Ilmu Komputer dan Sistem Informasi VISA: Journal of Vision and Ideas Da'watuna: Journal of Communication and Islamic Broadcasting Future Academia : The Journal of Multidisciplinary Research on Scientific and Advanced The Indonesian Journal of Computer Science Teknologi : Jurnal Ilmiah Sistem Informasi
Rakhmat Kurniawan R
Universitas Islam Negeri Sumatera Utara
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Algoritma K-Nearest Neighbor Classification Sebagai Sistem Pengelompokan Kemampuan Akademik Siswa Berbasis Web Indah Wahyuni, Utari; Kurniawan, Rakhmat
Decode: Jurnal Pendidikan Teknologi Informasi Vol. 5 No. 2: JULI 2025
Publisher : Program Studi Pendidikan Teknologi Infromasi UMK

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51454/decode.v5i2.1246

Abstract

Penggunaan sistem berbasis web dalam pendidikan dapat meningkatkan akurasi dan efisiensi evaluasi pembelajaran, terutama dalam penerapan Kurikulum Merdeka yang menuntut diferensiasi berdasarkan kemampuan siswa. Penelitian ini bertujuan mengembangkan sistem klasifikasi kemampuan akademik siswa berbasis web menggunakan algoritma K-Nearest Neighbor (K-NN). Sebanyak 254 data nilai akhir siswa kelas XII digunakan sebagai dataset, yang dinormalisasi menggunakan MinMaxScaler dan dilatih menggunakan model K-NN dengan parameter K = 5. Proses klasifikasi dan evaluasi dilakukan menggunakan confusion matrix dan classification report, yang menghasilkan akurasi sebesar 90,19%. Sistem ini dikembangkan menggunakan framework Laravel untuk sisi web dan Python (Google Colab) untuk pemrosesan data dan model klasifikasi. Hasil klasifikasi ditampilkan dalam bentuk tabel interaktif dan rekap visual yang memudahkan guru dalam merancang treatment pembelajaran adaptif. Kontribusi utama dari penelitian ini adalah integrasi antara algoritma klasifikasi dan sistem informasi berbasis web yang mendukung evaluasi akademik secara objektif, efisien, dan selaras dengan semangat Kurikulum Merdeka.
Sistem Informasi Prediksi Tren Produk Skincare Mglam Clinic Berbasis Machine Learning Ritonga, Larasati Rince Pratita; Kurniawan, Rakhmat
Decode: Jurnal Pendidikan Teknologi Informasi Vol. 5 No. 2: JULI 2025
Publisher : Program Studi Pendidikan Teknologi Infromasi UMK

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51454/decode.v5i2.1255

Abstract

Kemajuan teknologi informasi telah memungkinkan penerapan pembelajaran mesin di berbagai industri, termasuk kecantikan dan perawatan kulit. Klinik MGlam, sebagai penyedia produk perawatan kulit, menghadapi tantangan dalam memahami tren pasar yang dinamis. Oleh karena itu, penelitian ini bertujuan untuk mengembangkan sistem prediksi tren produk perawatan kulit menggunakan algoritma naive bayes berdasarkan data penjualan tahun 2024. Algoritma naive bayes dipilih karena kemampuannya untuk mengklasifikasikan data berdasarkan probabilitas, yang memungkinkan identifikasi produk dengan tren potensial. Sistem ini dikembangkan menggunakan PHP Native dan MySQL, dengan mengimplementasikan model pembelajaran mesin untuk menganalisis pola konsumsi pelanggan. Hasil penelitian menunjukkan bahwa sistem prediksi ini dapat meningkatkan efektivitas strategi pemasaran, manajemen inventaris, dan pengambilan keputusan bisnis di Klinik M_Glam. Dengan sistem ini, klinik diharapkan dapat lebih adaptif terhadap perubahan tren pasar dan meningkatkan daya saingnya di industri kecantikan.
Application of the C4.5 Algorithm for Predicting Banana Chips Production Demand (Case Study at UD. Sinar Sejahtera Medan) M. Teguh wijaya; Rakhmat Kurniawan R
JURNAL TEKNOLOGI DAN OPEN SOURCE Vol. 7 No. 2 (2024): Jurnal Teknologi dan Open Source, December 2024
Publisher : Universitas Islam Kuantan Singingi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36378/jtos.v7i2.3975

Abstract

The rapid advancement of science and technology significantly impacts various aspects of life, including business operations. Technology plays a vital role in providing information and simplifying human tasks, addressing challenges faced by growing companies, particularly in managing sales fluctuations. Factors such as market competition, product quality, and consumer interest are critical for evaluating and improving sales strategies. UD. Sinar Sejahtera Medan, a food processing industry specializing in banana chips, faces challenges such as fluctuating raw material supply, impacting production and sales. To address this, a prediction system for raw material demand was developed, leveraging the C4.5 algorithm. The C4.5 algorithm was selected for its ability to generate decision trees from historical data, providing interpretable results and high accuracy in forecasting categorical outcomes. By analyzing past trends in raw material availability and usage, the algorithm predicts future supply needs, optimizing production planning and supporting sustainable business operations. This study's findings are expected to align with previous research, offering insights for better production and sales management.
Analysis of Public Sentiment Towards Retired Military Officers' Pressure to Impeach the Vice President Through X Using Decision Tree Dimas Andrean Andrean; Rakhmat Kurniawan
JURNAL TEKNOLOGI DAN OPEN SOURCE Vol. 8 No. 2 (2025): Jurnal Teknologi dan Open Source, December 2025
Publisher : Universitas Islam Kuantan Singingi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36378/jtos.v8i2.5138

Abstract

The advancement of information technology has strengthened the analysis of social media data, particularly in understanding public opinion on national political issues. This study examines public sentiment on the X (Twitter) platform regarding the issues of Gibran’s Impeachment and the Urging by Retired Military Officers using the Decision Tree CART algorithm. Data were collected through a crawling process, resulting in 1,020 tweets for the Impeachment issue and 89 tweets for the Urging issue. After preprocessing, the dataset was labeled using a Lexicon-Based method that classifies text into positive, negative, and neutral sentiments. The evaluation results show that for the Impeachment issue, the model achieved an accuracy of 97.05%–99.51%, with the highest performance found in the Neutral class (F1-Score 98.46%). For the Urging issue, the model obtained an overall accuracy of 88.89%, with the highest performance also in the Neutral class (F1-Score 94.12%). Model performance decreased in the Positive and Negative classes due to data imbalance. Overall, the findings indicate that Decision Tree CART is effective for sentiment classification on small to medium datasets and reveal that public sentiment toward both issues is predominantly Neutral.
Klasifikasi Teks Komentar Pengguna Aplikasi Access By Kai di Google Play Store Menggunakan Metode Naïve Bayes Fahrul Afandi; Rakhmat Kurniawan
Bulletin of Computer Science Research Vol. 5 No. 4 (2025): June 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bulletincsr.v5i4.575

Abstract

The advancement of information technology has influenced various aspects of life, including transportation. The Access by KAI application provides digital train ticket booking services. With millions of users, analyzing the level of satisfaction through reviews on the Google Play Store is important to improve service quality. This study aims to classify user reviews using the Naïve Bayes algorithm to determine the level of satisfaction, group reviews based on certain categories, and evaluate the accuracy of the classification results. The study uses the Naive Bayes method to classify text where review data collection is carried out first through a scraping process from the Google Play Store with a total of 1000 reviews. Data is analyzed through pre-processing stages such as cleaning, case folding, tokenization, normalization, stopwords, steamming and sentiment labeling using InSetLexicon. Furthermore, reviews are grouped by category using the K-Means clustering method to group data into three categories, namely Features, Services, and Systems, to improve classification accuracy followed by classification using Naïve Bayes. Evaluation is carried out using a confusion matrix to measure accuracy, precision, recall, and F1-score. The classification results show that in the Feature category, precision is 79%, recall 99%, and F1-score 88%. In the Service category, precision reaches 100%, recall 56%, and F1-score 72%. For the System category, precision is 94%, recall 68%, and F1-score 79%. Overall, the model achieves an accuracy of 83%. The benefits of this study are to provide a deep understanding of user needs and become a reference for developers to improve the Access by KAI application service.
Klasifikasi Tingkat Kepuasan Peserta Pelatihan Balai Besar Pelatihan Vokasi dan Produktivitas Menggunakan Algoritma C5.0 Fahmi Maulana; Rakhmat Kurniawan
Bulletin of Computer Science Research Vol. 5 No. 5 (2025): August 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bulletincsr.v5i5.733

Abstract

The evaluation of training participant satisfaction at the Center for Vocational Training and Productivity Development (BBPVP) has traditionally relied on conventional methods, resulting in less accurate and unstructured outcomes. The core issue necessitates a data-driven solution to enhance objectivity and reliability. This study aims to develop a C5.0 algorithm-based classification model to automatically measure participant satisfaction levels and identify dominant influencing factors. The methodology includes collecting survey data from 300 respondents across five SERVQUAL attributes (reliability, assurance, responsiveness, empathy, tangibles), data preprocessing, dataset splitting (80:20), and model development using Python’s Scikit-learn library. Results indicate a model accuracy of 98.3% (12% higher than Naïve Bayes), with "assurance" as the most influential attribute (gain ratio: 0.638). Contributions of this research include: (1) providing BBPVP with an accurate data-driven satisfaction evaluation tool, (2) offering strategic recommendations to improve training quality, particularly in assurance, and (3) potential adoption of this method as a national vocational training evaluation standard.
Penerapan Naive Bayes dalam Mengidentifikasi Penyebab Remaja Desa Terlibat dalam Judi Online M Haziq Annabil; Rakhmat Kurniawan R
TIN: Terapan Informatika Nusantara Vol 6 No 9 (2026): February 2026
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v6i9.9350

Abstract

The development of digital technology and increased internet access have driven changes in adolescent social behavior, including increased involvement in online gambling activities, not only in urban areas but also in rural areas. This study aims to identify the factors that influence adolescent involvement in online gambling and to measure the level of influence of each factor using a machine learning-based classification approach. The research was conducted in Payageli Village, Sunggal District, Deli Serdang Regency, involving 507 adolescent respondents who were surveyed using a questionnaire containing 23 questions. The data obtained was analyzed using the Naive Bayes algorithm with data preprocessing, categorical attribute coding, and data division into training and test data with a ratio of 80:20. The results showed that the dominant factors influencing adolescent involvement in online gambling included peer influence, intensity of exposure to online gambling advertisements, online gaming habits, low positive leisure activities, and lack of parental supervision. The classification model built produced an accuracy rate of 98%, with high precision and recall values in each class. These findings indicate that the Naive Bayes algorithm is effective in identifying adolescents at risk of engaging in online gambling and has the potential to be used as a basis for developing data-driven prevention strategies at the village level.
Implementasi Metode Canny dalam Sistem Penempatan Foto Kartu Identitas Siswa Otomatis Imam Sodik; Rakhmat Kurniawan
TIN: Terapan Informatika Nusantara Vol 6 No 11 (2026): April 2026
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v6i11.9674

Abstract

The manual creation of student identity cards often encounters several challenges, including inaccurate photo placement, inconsistent sizing, and lengthy processing time. These issues reduce efficiency and result in non-uniform document outputs. This study aims to develop a client-side web-based system capable of detecting empty rectangular areas in identity card templates and automatically embedding student photos using OpenCV.js. The system applies the Canny Edge Detection method combined with contour analysis to identify empty box regions, while image interpolation techniques are used to proportionally adjust photo dimensions according to the detected area. Experimental results show that the proposed system has been successfully implemented and is capable of accurately detecting empty regions in high-quality documents. Based on evaluation using the Intersection over Union (IoU) method, the system achieves an average accuracy of 98.67%, indicating that the Canny method is effective in detecting photo areas. The automatic photo adjustment process produces proportionally correct and ready-to-use digital outputs. Therefore, the system improves efficiency, accuracy, and consistency in the student identity card creation process.
Implementasi Internet of Thing (IoT) untuk Monitoring dan Kontrol Energi Listrik Rumah Tangga Menggunakan Fuzzy Tsukamoto Fadhlun Nazry Luthfy; Rakhmat Kurniawan R
CESS (Journal of Computer Engineering, System and Science) Vol. 11 No. 1 (2026): Januari 2026
Publisher : Universitas Negeri Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24114/cess.v11i1.72110

Abstract

Peningkatan konsumsi energi listrik rumah tangga dan minimnya informasi konsumsi secara real-time menyebabkan penggunaan listrik yang tidak efisien serta berpotensi menimbulkan risiko keselamatan instalasi. Oleh karena itu, diperlukan sistem pemantauan dan pengendalian energi listrik yang cerdas, adaptif, dan dapat diakses dari jarak jauh. Penelitian ini mengimplementasikan sistem Internet of Things (IoT) untuk monitoring dan kontrol energi listrik rumah tangga menggunakan algoritma Fuzzy Tsukamoto. Akuisisi data tegangan, arus, dan daya dilakukan secara real-time menggunakan sensor PZEM-004T yang terintegrasi dengan mikrokontroler ESP32. Data dianalisis menggunakan logika Fuzzy Tsukamoto untuk menentukan kondisi beban listrik, kemudian sistem secara otomatis mengendalikan relay sebagai mekanisme proteksi. Sistem dilengkapi dengan platform Blynk untuk pemantauan dan kontrol jarak jauh. Hasil pengujian menunjukkan bahwa sistem mampu mengukur parameter listrik dengan tingkat akurasi yang tinggi, ditandai dengan deviasi kesalahan pengukuran tegangan, arus, dan daya di bawah 5% dibandingkan alat ukur referensi. Sistem juga mampu mendeteksi kondisi beban tidak normal dan melakukan pemutusan suplai listrik secara otomatis dan manual. Kontribusi penelitian ini terletak pada penerapan algoritma Fuzzy Tsukamoto sebagai sistem pengambilan keputusan adaptif dalam monitoring dan kontrol energi listrik rumah tangga berbasis IoT, yang tidak hanya meningkatkan keamanan instalasi listrik, tetapi juga mendukung efisiensi energi dan pencegahan kerusakan perangkat listrik.
Implementasi Konsumsi Energi Listrik Perabotan Rumah Tangga Berbasis IoT Menggunakan ESP-32, Sensor PZEM 004T dan Fuzzy Mamdani Sultan Azka El Husein Lubis; Rakhmat Kurniawan R
CESS (Journal of Computer Engineering, System and Science) Vol. 11 No. 1 (2026): Januari 2026
Publisher : Universitas Negeri Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24114/cess.v11i1.72255

Abstract

Peningkatan konsumsi energi listrik rumah tangga menuntut adanya sistem monitoring dan kontrol yang efektif untuk meningkatkan efisiensi penggunaan energi. Penelitian ini dirancang untuk mengembangkan serta menerapkan infrastruktur sistem pemantauan dan pengendalian konsumsi energi listrik yang terintegrasi dengan teknologi Internet of Things (IoT) melalui metode logika fuzzy Mamdani. Sistem dirancang dengan mikrokontroler ESP32 berfungsi sebagai unit pemrosesan data utama, modul sensor PZEM-004T sebagai alat ukur parameter kelistrikan, relay sebagai perangkat pengendali beban, serta platform IoT Blynk sebagai media monitoring jarak jauh. Data hasil pengukuran ditampilkan secara real-time melalui antarmuka LCD dan aplikasi berbasis Internet of Things (IoT). Metode fuzzy Mamdani diterapkan dengan dua parameter input, yaitu arus dan daya, yang ditransformasi melalui proses fuzzifikasi ke dalam tiga himpunan fuzzy, linguistik kategori rendah, kategori sedang, dan kategori tinggi. Sistem menggunakan sembilan kaidah fuzzy sebagai dasar pengambilan keputusan dalam mengontrol relay. Hasil penelitian menunjukkan bahwa sistem mampu memantau parameter listrik secara real-time dengan tingkat akurasi yang tinggi. Hasil pengujian menunjukkan nilai rata-rata kesalahan pengukuran tegangan berkisar pada 0,114%, sedangkan kesalahan data pengukuran arus dan daya berada di bawah 1,3%. Mekanisme kontrol relay bekerja sesuai hasil inferensi fuzzy dan konsisten dengan perhitungan manual. Selain itu, sistem mampu mendeteksi kondisi standby power serta menghitung dan menampilkan biaya pemakaian listrik secara real-time, sehingga membantu pengguna dalam mengontrol konsumsi energi listrik secara lebih beroperasi secara optimal.
Co-Authors Abdul Halim Hasugian Adnan Buyung Nasution Agung Firmansyah Agung Pratama Ahmad Fauzi Ahmad Taufik Al Afkari Siahaan Aidil Halim Aidil Halim Lubis Aidil Halim Lubis Aidil Halim Lubis Alhafiz, Akhyar Alwy Azyari Harahap Amanda Zachra Harahap Amelia, Dara Andre Gusli Agus Riadi Armansyah Armansyah Armansyah Armansyah Arrafiq, Muhammad Sunni Asnawi, Azi Ayyina, Ayyina Nurhidayah Azhari, Fajar Bahari, Mhd Raja Doly Bayhaqi, Abdullah Bisri, Cholil Br Rambe, Indri Gusmita Dandi, Muhammad Khairil Dasopang, Buyung Satrio Dian Putri Kinanti Dimas Andrean Andrean Dwisyahputra, Achmad Adbillah Eva Darwisah Harahap Fadhlun Nazry Luthfy Fadiga, Muhammad Fahmi Maulana Fahrul Afandi Fakhriyah, Mardhiyah Fakhrizal, Fiqri Fatwa, Nursalimah Isnaina Fikri Aulia Habibie, Alief Fathul Haliem, Alexander Hanafi, Muhammad Rizky Harahap, Nita Maharani Harahap, Rina Syafiddini Harahap, Shopiah Henni Melisa Hidayat, Zulfy Hidayatullah, Catur HP, Kiki Iranda Hsb, Khoiri Sutan Ibsan, Muhammad Hanafi Ilham Rizki Ananda Ilka Zufria Imam Sodik Imam Zaki Husein Nst Indah Wahyuni, Utari Ivan Prayuda Julianti, Miranda Jusli, Dara Taqa Assajidah Kesuma Dwi Ningtyas Khairin Nadia Khairunissabina, Khairunissabina Khoiriah, Miftahul Krisdantoro, Rino Lubis, Fahrian Zibran Lubis, Farhan Rusdy Asyhary M Haziq Annabil M. Teguh wijaya Masdaliva, Fita Meilina, Indah Mey Hendra Putra Sirait Mhd Furqan Mhd Furqan Mhd. Furqan Furqan Mhd.Furqan Mohd. Wildan Qasthari Muhammad Abi Muzaki Muhammad Fahri, Muhammad Muhammad Ikhsan Muhammad Ikhsan Aji Muhammad Rizki Madani Muhammad Siddik Hasibuan Muhammad Sowban Adilla Nasution, Fitri Handayani Nasution, Raihan Hafiz Noor Azizah Novita Jambak, Indah Nur Aini, Sakina Nurjanah, Trya Nurwana Nazla Saragih Padang, Bermiko Kasah Pravda, Michellia Delphi Isfahan Prayoga, Dio Prayoga, Hafizh Putri Hanifah Putri, Raissa Ramanda Rafli Bima Sakti Rahmad Syuhada Rahmatsyah Ananta Putra Ginting Raissa Amanda Putri Ramadhan, Alfan Ramadhan, Nuzul Ramadhan, Rio Fadli Ramadhan, Rizky Syahrul Reza Muhammad Rifansyah, Mhd. Roji Rifqi Alwanu Akmal Rina Filia Sari Rina Syafiddini Harahap Rini Halila Nasution Ritonga, Larasati Rince Pratita Rizki Ananda Putra Fajar Rizky Barus Rizky Pratama Putra Rudi Riyandi Salsabillah, Ayna Sandira, Sri Delwis Saragih, Khoirul Azmi Saragih, Rafif Aprizki Sari, Desliana Sihombing, Rizki Andika Silva Ukhti Filla Silvi Joya Arditna Br Bukit Sinaga, Imam Adlin Sinaga, Muhammad Nabil Siregar, Muharram Soleh Siti Afifah Siregar Siti Ayu Hadisa Siti Nurul Aini, Siti Nurul Siti Sarah Harahap Siti Sumita Harahap Sri Marwah Badrin Sriani Sriani Sriani Stephani Silalahi Suhardi Suhardi Suhardi Suhardi, Suhardi Sultan Azka El Husein Lubis Syahira, Melani Alka Syahputra, Pii Syahputra, Zidhane Syarifudin, Zaini Tbn, Ahmad Fauza Anshori Tri Asyura Mashuri Triase Triase Triase Triase, Triase Wahyu Kurniawan Wini Istya Sari Lubis Yahya, Arfigo YENI SAFITRI Yudha, Muhammad Yudha Pratama Zahron, Almeranda Haryaveda Nurul