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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
Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Immunology & microbiology Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Neuroscience Nursing Physics Public Health Social Sciences Veterinary Other

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Forecasting building permit submissions with fuzzy time series at DPMPTSP Medan Dasopang, Buyung Satrio; Kurniawan, Rakhmat
Jurnal Mandiri IT Vol. 14 No. 1 (2025): July: Computer Science and Field.
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/mandiri.v14i1.444

Abstract

Public service is a vital part of government performance, including how the Investment and One-Stop Integrated Services Agency (DPMPTSP) handles building permit applications (IMB). This study aims to estimate the number of IMB applications in Medan City using a method called Fuzzy Time Series (FTS). The forecast is intended as a preliminary step to support better spatial planning, especially as urban building density continues to rise. The FTS method was chosen for its ability to process time series data containing uncertainty. The forecasting process involves several stages: identifying the dataset, setting interval ranges, performing fuzzification, forming fuzzy logical relationships (FLR), grouping fuzzy logical relationship groups (FLRG), applying defuzzification, and measuring accuracy using Mean Absolute Percentage Error (MAPE). The data used include IMB applications from 2022 to 2023, with predictions made for 12 months in 2024. The results show that the FTS model closely follows historical data patterns, evidenced by a MAPE value of 1.99%, which indicates excellent accuracy as it is well below the 10% threshold. A comparative graph between actual and predicted data further supports this, revealing similar trends. In conclusion, the Fuzzy Time Series method is effective for forecasting IMB application volumes and can serve as a valuable reference for urban planning decisions and future time series-based forecasting research involving uncertainty.
Implementation of the K-Nearest Neighbor Algorithm for Birth Rate Prediction Alhafiz, Akhyar; Kurniawan R., Rakhmat
Journal of Applied Informatics and Computing Vol. 9 No. 4 (2025): August 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i4.9886

Abstract

This study aims to predict the monthly birth rate using the K-Nearest Neighbor (KNN) regression algorithm. The dataset consists of historical data from 2010 to 2020, covering six districts and including variables such as total population, number of couples of reproductive age, family planning participation rate, and monthly birth rate as the prediction target. Data preprocessing involved handling missing values and applying Min-Max normalization. To maintain the time-series nature of the data, a chronological split was used, with 576 records from 2010 to 2018 for training and 216 records from 2019 to 2020 for testing. The model was evaluated using Mean Absolute Error (MAE), Root Mean Squared Error (RMSE), and R-squared (R²). The best performance was achieved at K = 7, with MAE = 19.94, RMSE = 30.91, and R² = 0.34. Additionally, the KNN model was compared with Linear Regression and Decision Tree, where KNN outperformed both alternatives. The final model was implemented in a web-based application to facilitate demographic data management and automatic birth rate prediction per district. This system is expected to support policy planning in the fields of population control and public health.
Clustering Data Penjualan Kopi Sidikalang Menggunakan Metode K-Means Padang, Bermiko Kasah; Kurniawan, Rakhmat
SENTRI: Jurnal Riset Ilmiah Vol. 4 No. 8 (2025): SENTRI : Jurnal Riset Ilmiah, Agustus 2025
Publisher : LPPM Institut Pendidikan Nusantara Global

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55681/sentri.v4i8.4400

Abstract

This study aims to analyze the sales patterns of Sidikalang coffee using the K-Means clustering method to optimize stock management and marketing strategies. Three months of sales data were analyzed based on the attributes of sales volume, price, and season. The results showed that the data could be grouped into four clusters with distinct characteristics: low sales (52 data points), medium sales (50 data points), high sales (21 data points), and high stock with sporadic sales (77 data points). Evaluation using the Davies-Bouldin Index (DBI) yielded a score of 0.52, indicating good clustering quality. These findings provide valuable insights for business actors in developing more targeted marketing strategies and efficient stock management. This research also contributes to the literature on the application of machine learning in analyzing local product sales, particularly Sidikalang coffee.
Implementasi Metode Fuzzy Mamdani Untuk Pemilihan Keramik Rumah Bangunan Nasution, Raihan Hafiz; Rakhmat Kurniawan R
Jurnal Multimedia dan Teknologi Informasi (Jatilima) Vol. 7 No. 03 (2025): Jatilima : Jurnal Multimedia Dan Teknologi Informasi
Publisher : Cattleya Darmaya Fortuna

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54209/jatilima.v7i03.1644

Abstract

Pemilihan keramik merupakan salah satu aspek penting dalam konstruksi bangunan karena berpengaruh pada kenyamanan, keamanan, dan estetika hunian. Variasi produk serta perbedaan karakteristik teknis seperti harga, kualitas, daya serap air, dan kekasaran permukaan sering menyulitkan konsumen dalam menentukan pilihan yang tepat. Penelitian ini bertujuan untuk mengembangkan sistem pendukung keputusan pemilihan keramik rumah bangunan berbasis metode Fuzzy Mamdani. Metode penelitian yang digunakan adalah Research and Development (R&D) dengan melibatkan proses fuzzifikasi, inferensi fuzzy, dan defuzzifikasi. Data penelitian mencakup 120 jenis keramik dari berbagai merek ternama di Indonesia. Hasil pengujian menunjukkan bahwa empat produk keramik, yaitu Indogress Batu Alam Lux, Roman Batu Alam Lux, Granito Batu Alam Lux, dan Platinum Kayu Eksklusif, memperoleh skor 80 dengan kategori “Sangat Direkomendasikan”, sementara Kia Marmer Classic hanya memperoleh skor 50 dengan kategori “Cukup Direkomendasikan”. Temuan ini mengindikasikan bahwa harga dan kualitas menjadi faktor dominan dalam penentuan rekomendasi, sedangkan daya serap air dan kekasaran berperan sebagai variabel pendukung. Dengan demikian, sistem yang dikembangkan mampu membantu konsumen memilih keramik secara lebih objektif dan akurat.
IMPLEMENTASI METODE SMART dan WP UNTUK MENENTUKAN SISWA KELAS UNGGULAN BERDASARKAN PRESTASI AKADEMIK BERBASIS WEBSITE Nurjanah, Trya; R, Rakhmat Kurniawan
IJIS - Indonesian Journal On Information System Vol 10, No 2 (2025): SEPTEMBER
Publisher : POLITEKNIK SAINS DAN TEKNOLOGI WIRATAMA MALUKU UTARA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36549/ijis.v10i2.421

Abstract

Pemilihan siswa berprestasi di sekolah memerlukan sistem yang objektif dan terukur agar prosesnya berjalan adil dan transparan. Penelitian ini bertujuan untuk membangun sistem pendukung keputusan berbasis web yang mampu menentukan siswa berprestasi dengan menggunakan metode SMART (Simple Multi-Attribute Rating Technique) dan metode WP (Weighted Product). Penelitian ini menggunakan Metode RAD (Rappid Aplication Development) dalam proses pengembangan sistem, mulai dari analisis kebutuhan, perancangan antarmuka, hingga implementasi sistem berbasis web menggunakan PHP dan MySQL. Data yang digunakan berasal dari kriteria penilaian siswa seperti nilai akademik, keaktifan, kepribadian, dan prestasi. Hasil pengujian menunjukkan bahwa sistem yang dibangun mampu menampilkan hasil perhitungan alternatif siswa secara akurat, baik melalui metode SMART maupun WP, serta menghasilkan rekomendasi terbaik melalui kombinasi keduanya. Dengan sistem ini, sekolah dapat lebih mudah mengambil keputusan yang tepat dalam menentukan siswa berprestasi.Kata Kunci: Sistem Pendukung Keputusan, SMART, WP
Sentiment analysis of privacy issues in the digital era using the naïve bayes method Ramadhan, Rio Fadli; Kurniawan, Rakhmat
Jurnal Mandiri IT Vol. 14 No. 2 (2025): Computer Science and Field
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/mandiri.v14i2.450

Abstract

The development of information technology has triggered public concern about data privacy issues, especially on social media such as X (formerly Twitter). The rampant leaks of personal data have driven the need for a deeper understanding of public opinion. This study aims to analyze public sentiment towards data privacy issues by applying the Naïve Bayes algorithm. The formulation of the problem includes how the public perceives data privacy, how the algorithm performs in classifying sentiment, and how the evaluation results of the model used are. This study uses a quantitative method with a text mining and machine learning approach. Data were taken through crawling techniques on 1,500 tweets related to data privacy. The pre-processing stages were carried out through cleaning, tokenizing, normalization, stopword removal, and stemming. Furthermore, the data was labeled using the InsetLexicon dictionary and weighted using the TF-IDF method. The classification model was built using the Naïve Bayes algorithm and evaluated using accuracy, precision, recall, and f1-score metrics. The results showed that the majority of public opinion on data privacy issues was negative, reflecting concerns over the weak protection of personal data. The Naïve Bayes model performed quite well in sentiment classification. This research is useful in providing insight to the government and digital service providers in developing data protection policies that are more responsive to public opinion.
Optimasi Rute Terdekat Dalam Pencarian Bengkel Sepeda Motor di Kota Medan dengan Pendekatan Algoritma Floyd Warshall Harahap, Shopiah; Kurniawan, Rakhmat; Suhardi, Suhardi
EDU SOCIETY: JURNAL PENDIDIKAN, ILMU SOSIAL DAN PENGABDIAN KEPADA MASYARAKAT Vol. 5 No. 2 (2025): June-September 2025
Publisher : Association of Islamic Education Managers (Permapendis) Indonesia, North Sumatra Province

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56832/edu.v5i2.1686

Abstract

Pencarian bengkel motor terdekat secara efisien merupakan tantangan bagi pengendara, terutama dalam kondisi mendesak. Tulisan ini berusaha memberikan solusi dengan metode pendekatan Algoritma Floyd Warshall untuk mengidentifikasi rute terpendek dalam sistem pencarian bengkel sepeda motor. Mekanisme kerja algoritma ini adalah menghitung jarak terpendek antar semua pasangan node (lokasi) dalam graf dengan membandingkan jalur langsung dan jalur melalui intermediate node, secara iteratif. Pemodelan jaringan jalan dan lokasi bengkel sepeda motor dilakukan sebagai graf berbobot, di mana node merepresentasikan lokasi dan edge merepresentasikan segmen jalan dengan bobot jarak atau waktu. Variabel utama yang digunakan adalah matriks jarak antar node yang diperbarui secara progresif. Hasil penelitian menunjukkan bahwa Algoritma Floyd Warshall berhasil 95 % untuk menentukan rute optimal ke bengkel sepeda motor terdekat dari posisi pengguna. Hasil pengujian menunjukkan sistem mampu mengidentifikasi rute terpendek, meskipun waktu komputasi akan meningkat seiring pertambahan jumlah node dan edge. Pengaruh variabel jarak antar node memberi pengaruh nilai bobot secara langsung dalam hasil perhitungan rute terpendek.
Naïve bayes algorithm for early diagnosis of non-communicable diseases Ramadhan, Nuzul; Ramli, Rakhmat Kurniawan
Journal of Intelligent Decision Support System (IDSS) Vol 8 No 3 (2025): September: Intelligent Decision Support System (IDSS)
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/idss.v8i3.306

Abstract

Non-communicable diseases such as heart disease, diabetes mellitus, hypertension, stroke, asthma, rheumatism, and GRED are still the main causes of illness and death in Indonesia. This problem is more serious in rural areas with limited health services, such as Lubuk Palas Village, Asahan Regency, which faces obstacles in distance, road infrastructure, and a limited number of medical personnel, so early diagnosis is often neglected. This research aims to apply the Naïve Bayes method in a non-communicable disease diagnosis expert system and develop web and mobile-based applications to support the community and medical personnel in early detection. The research method combines primary data from observations and interviews with health workers and secondary data from medical literature. Each symptom is given a probability weight of 0.00–1.00 according to medical consultation, then processed using the Naïve Bayes algorithm with two approaches, namely direct calculation and gradual filtering. The results show that the system produces a posterior probability of 99.32% in the heart disease scenario with typical symptoms and 90.00% in the stroke scenario with partial symptoms. The findings of this research are that the application of two Naïve Bayes inference pathways is proven effective in producing an initial diagnosis that is adaptive to variations in symptoms, relevant for rural conditions with limited health services, and capable of providing fast, practical, and widely accessible medical decision support.
Bird Sound Quality Analysis for Chirping Masters Using Mel Frequency Cepstrum Coefficiens (MFCC) and Svm Classification Algorithm Zahron, Almeranda Haryaveda Nurul; Kurniawan, Rakhmat
Journal of Computer Science, Information Technology and Telecommunication Engineering Vol 6, No 2 (2025)
Publisher : Universitas Muhammadiyah Sumatera Utara, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30596/jcositte.v6i2.26410

Abstract

Birds play an important role in ecosystems as indicators of environmental health and biodiversity. In Indonesia, there are approximately 1,531 bird species, including songbirds that are popular for their melodious chirps. Bird sounds are used for communication, territorial marking, and are a key attraction in bird song competitions. However, obtaining a bird with high-quality vocalization requires specific training, one of which is the mastering method using recordings of champion bird songs. Additionally, the Support Vector Machine (SVM) algorithm has proven effective in classifying bird species based on sound, achieving 77% accuracy after noise reduction. The combination of MFCC and SVM allows for more systematic and accurate analysis of bird vocalizations. This research is expected to contribute to the field of ornithology, the development of songbird husbandry techniques, and serve as a guide for bird enthusiasts in selecting high-quality master bird sounds.
Sistem Rekomendasi Pemilihan Saham Blue-Chip di Bursa Efek Indonesia Menggunakan Fuzzy Mamdani Dandi, Muhammad Khairil; Kurniawan, Rakhmat
TIN: Terapan Informatika Nusantara Vol 6 No 5 (2025): October 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v6i5.8465

Abstract

The Indonesian capital market plays an important role in supporting national economic growth, particularly through stock investments. Blue-chip stocks are considered stable and have the potential to provide long-term returns, yet selecting the right ones remains a challenge for investors. This study aims to develop a recommendation system for selecting blue-chip stocks on the Indonesia Stock Exchange (BEI) using the Fuzzy Mamdani method. The research data were collected from a set of actively traded blue-chip stocks within a specific period and analyzed using four main variables: stock price, trading volume, market capitalization, and financial ratios. The recommendation process involves fuzzification, the formulation of 15 rule bases established through expert consultation with market analysts, Mamdani inference, and defuzzification to produce recommendation scores. The implementation results show that the system achieved an accuracy level of 84.65%, indicating stable consistency with actual market conditions. These findings confirm that the Fuzzy Mamdani method is effective in generating objective and systematic recommendations for blue-chip stock selection. The developed system successfully meets the research objective by assisting investors in identifying suitable stocks based on data-driven analysis.
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