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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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Penerapan Text Mining Pada Sistem Penyeleksian Judul Skripsi Menggunakan Algoritma Latent Dirichlet Allocation(LDA) Kurniawan R, Rakhmat; Zufria, Ilka
The Indonesian Journal of Computer Science Vol. 11 No. 3 (2022): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v11i3.3120

Abstract

Dalam proses pengajuan judul proposal skripsi, banyak mahasiswa yang judulnya ditolak dikarenakan adanya kesamaan judul atau tema penelitian yang telah dilakukan sebelumnya. Proses ini dilakukan secara manual dimana judul skripsi direkapitulasi dengan menggunakan aplikasi Microsoft Excel, sehingga membuka peluang kekeliruan dalam pemeriksaan yang disebabkan oleh tim penyeleksi memeriksa judul secara manual baris per baris. Selanjutnya dirasa perlu melakukan penelitian untuk mengatasi masalah tersebut. Dengan harapan memudahkan pengelola program studi dalam menentukan judul skripsi yang potensial dan berkualitas pada mahasiswa. Selanjutnya mempercepat proses penentuan judul skripsi mahasiswa dan tentunya juga akan mempercepat proses penyelesaian studi mahasiswa strata 1. Maka dirancanglah sebuah sistem yang mampu merekomendasi kelayakan judul skripsi yang diajukan melalui teknologi text mining menggunakan algoritma LDA. Algoritma LDA mampu untuk mendeteksi topik yang ada pada suatu koleksi dokumen beserta besarnya kemunculan topik tersebut.
Analisis Sentimen Mengenai Childfree Menggunakan Metode Naïve Bayes: Analisis Sentimen Mengenai Childfree Menggunakan Metode Naïve Bayes Yeni Safitri; Rakhmat Kurniawan; Suhardi
The Indonesian Journal of Computer Science Vol. 13 No. 4 (2024): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i4.4136

Abstract

The emergence of the issue of childfree has become a trending topic on Twitter since the beginning of 2020 until now, which has given rise to many positive and negative opinions from various groups, especially on Twitter social media. This sentiment analysis research aims to determine the responses given regarding childfree in the form of positive, neutral or negative opinions by collecting Twitter data. The number of datasets used is 700 data, divided into 630 training data and 70 test data. This research uses the Naïve Bayes algorithm classification and confusion matrix as a performance evaluation of the system being built. The test results show an accuracy value of 64.29%, precision of 68.25%, recall of 64.29% and fi-score of 55.69%.
Pencarian Rute Terpendek Dalam Pendistribusian Darah di Palang Merah Indonesia (PMI) dengan Algoritma Dijkstra Hidayatullah, Catur; R, Rakhmat Kurniawan; Armansyah, Armansyah
TIN: Terapan Informatika Nusantara Vol 4 No 11 (2024): April 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/tin.v4i11.5028

Abstract

The Indonesian Red Cross (PMI) is an independent and neutral organization in Indonesia engaged in humanitarian activities. One of the departments within the Indonesian Red Cross is the blood donor unit. The Blood Donor Unit (UDD) of PMI Deli Serdang is one of the Indonesian Red Cross offices in the Deli Serdang district, which deals with social humanitarian activities such as blood donation, volunteer recruitment, emergency response, and others. One common issue in blood distribution is the numerous routes that need to be taken, resulting in wasted time and delayed blood deliveries. Due to this issue, the implementation of artificial intelligence is needed to determine the shortest route for optimal and fast blood delivery. The application of artificial intelligence in problem-solving in the field of computer science has seen rapid development over the years in line with the advancement of artificial intelligence itself. In determining the shortest route, several algorithms can be used, one of which is the Dijkstra algorithm. It is used to solve problems in a graph to determine the shortest route. In the process, the Dijkstra algorithm determines the points that will become the distance weights connected from one point to another, resulting in the desired nodes. Therefore, an application is needed to find the nearest route to make blood delivery more time-efficient. In manual calculations using the algorithm, it was found that the shortest route from UDD (PMI Deli Serdang Blood Donation Unit) to GM (Grand Medistra Hospital) is through the route UDD → A → B → C → D → GM = 0 + 300 m + 250 m + 1,500 m + 35 m + 90 m with a total distance of 2,175 meters or 2.1 kilometers in 5 minutes. Thus, the use of the Dijkstra algorithm can assist in determining the fastest and optimal route for blood distribution, saving time and improving delivery efficiency.
Hyperparameter Optimization of Naive Bayes for Supervisor Recommendation in Computer Science Sinaga, Muhammad Nabil; Kurniawan R, 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.v6i5.8478

Abstract

The increasing number of students in the Department of Computer Science at UIN Sumatera Utara has made the process of selecting thesis supervisors more complex and time-consuming. This study aims to develop a system that automatically recommends the most suitable supervisor based on the similarity between thesis titles and lecturers’ areas of expertise. The proposed model applies text preprocessing techniques such as case folding, tokenization, stopword removal, and keyword extraction to transform thesis titles into meaningful features. These features are then classified using the Naive Bayes algorithm to predict the probability of each lecturer being the most relevant supervisor. The dataset consists of 794 thesis titles and 25 lecturers collected from 2019–2024. The model was evaluated using an 80:20 data split, achieving an accuracy of 87.3% with stable precision and recall scores, demonstrating reliable performance in supervisor recommendations. This enhanced Naive Bayes model can assist academic departments in ensuring a fairer and more efficient supervisor assignment process.
SISTEM INFORMASI PERSEDIAAN BERAS DI CV XYZ MENGGUNAKAN METODE PERIODIC REVIEW SYSTEM (PRS) BERBASIS WEB Rudi Riyandi; Kurniawan R, Rakhmat
ZONAsi: Jurnal Sistem Informasi Vol. 6 No. 2 (2024): Publikasi Artikel ZONAsi: Periode Mei 2024
Publisher : Universitas Lancang Kuning

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31849/zn.v6i2.20023

Abstract

Beras, sebagai komoditas pangan pokok yang vital dalam kehidupan sehari-hari, memainkan peran sentral dalam industri makanan di berbagai negara, termasuk Indonesia. Manajemen persediaan beras yang efektif adalah kunci untuk memastikan ketersediaan dan distribusi yang lancar. Penelitian ini bertujuan untuk mengembangkan Sistem Informasi Persediaan Beras di CV XYZ dengan metode Periodic Review System (PRS) berbasis web. Dalam konteks ini, PRS diterapkan sebagai pendekatan untuk meningkatkan efisiensi dan ketepatan dalam pengelolaan persediaan beras. Evaluasi sistem menunjukkan peningkatan yang signifikan dalam optimisasi level persediaan, penurunan biaya penyimpanan, serta peningkatan responsibilitas staf dalam manajemen persediaan. Selain itu, peningkatan akurasi dalam perkiraan permintaan dan ketersediaan produk juga diamati. Implikasi praktis dari penelitian ini menyediakan panduan berharga bagi perusahaan dalam menerapkan solusi berbasis web untuk meningkatkan manajemen persediaan.
Sistem Pengendalian Water Pump Untuk Mengatur Volume Level Air Dengan Logika Fuzzy Pada Pengairan Hidroponik Kurniawan, Rakhmat; Sriani, S; Ramadhan, Alfan
Brahmana : Jurnal Penerapan Kecerdasan Buatan Vol 4, No 2 (2023): Edisi Juni
Publisher : LPPM STIKOM Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/brahmana.v4i2.186

Abstract

Hydroponic culture can produce optimal plant growth, the yield and quality are better than soil media, the efficiency and quality of production depends on many factors such as controlling nutrition, plant genotype, freezing method, disease control, temperature control and controlling the amount of water in the tendons. Water that is circulated through the hydroponic network is supplied through a water pump. A lot of water supply cannot be stable, which can result in a decrease in plant quality, namely the control of hydroponic water pumps can be adjusted with the Tsukamoto fuzzy system. This study used the NFT hydroponic method, which is suitable for green vegetables such as mustard greens, lettuce, spinach, pakcoy, cucumber, tomatoes, and others. The application of this pump sensor monitoring tool uses a microcontroller based on the IoT platform. Also used Blynk software to display information from programming via Arduino software. Ultrasonic circuit, the sensor will measure the distance to the air surface, which will determine at what distance the water tap will open to fill air into the tendons. After running a number of experiments the content of water tendons can be controlled by fuzzy Tsukamoto. It is hoped that for further development it can use sensors other than Ultrasonic, and for further development it can use a large number of plants.
Analysis Of Opinion Sentiment Towards Electric Vehicle Tax On Social Media X Using The Support Vector Machine (SVM) Method Jusli, Dara Taqa Assajidah; Kurniawan, Rakhmat
Journal of Computer Networks, Architecture and High Performance Computing Vol. 6 No. 4 (2024): Articles Research October 2024
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v6i4.4739

Abstract

Electric vehicle tax is increasingly becoming an important issue related to environmental and fiscal policies. Electric vehicles are considered an environmentally friendly solution to reduce greenhouse gas emissions and dependence on fossil fuels. However, public perception of electric vehicle tax is still mixed. This study aims to analyze public sentiment about electric vehicle tax based on data from social media platform X, using the Support Vector Machine (SVM) method. The data used was taken through a crawling technique with a total of 1,014 valid data. The data was then classified into positive and negative classes with a transformer. In this analysis, the data was divided with a ratio of 8:2 between training data and test data. 811 were used as training data and 203 as test data. The research stages involved data preprocessing, sentiment labeling, data separation into training and test data, and weighting using TF-IDF. After that, SVM was applied to classify tweets into positive and negative sentiments. The test results showed that the SVM algorithm had an accuracy of 79%, precision of 85%, recall of 89%, and F1-score of 87%. Based on the results of this study, some people feel unsure about the government's policy regarding electric vehicle tax, because it is considered unfair to the lower middle class. Electric vehicles are considered more expensive than fuel-powered vehicles, so this policy is considered unprofitable.
Measuring Water Content in Hydroponic Plants Based on PH Values and Nutriens Using Fuzzy Logic Microcontroller Based Tsukamoto Julianti, Miranda; Rakhmat Kurniawan R
Journal of Computer Networks, Architecture and High Performance Computing Vol. 6 No. 4 (2024): Articles Research October 2024
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v6i4.4764

Abstract

Hydroponic cultivation is a method of planting without soil by utilizing water containing nutrients and oxygen at certain levels. Regulation and monitoring of pH, nutrients (TDS), and water temperature are crucial factors in the success of a hydroponic system. Inaccuracies in nutrient water management can significantly affect plant growth. This study aims to design an automation system capable of monitoring pH and water nutrient levels using the Fuzzy Tsukamoto method based on the Nodemcu ESP32 microcontroller. The sensors used in this study are the MSP340 pH Module sensor to measure acidity (pH) and the Df Robot Module TDS sensor to detect nutrient levels in water. The Fuzzy Tsukamoto method is applied to make fuzzy logic-based decision-making, where the input values of pH and nutrients are converted into linguistic variables. The fuzzyfication process is carried out to determine the level of plant fertility, while the inference method is used to produce output based on previously set rules. This monitoring system also utilizes the Nutrient Film Technique (NFT) technique with a linear regression method to optimize the use of water pumps, making it more energy efficient. With the design of this system, hydroponic farmers can monitor water conditions automatically and in real-time, increasing efficiency and reducing human error in nutrient water management. The results of this study are expected to provide innovative solutions for the development of more efficient and sustainable hydroponic systems.
Analysis of Drug Sales Patterns in the Belawan Naval Hospital Pharmacy Using Apriori Algorithm Bahari, Mhd Raja Doly; Kurniawan, Rakhmat
Journal of Computer Networks, Architecture and High Performance Computing Vol. 6 No. 4 (2024): Articles Research October 2024
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v6i4.4805

Abstract

Hospital pharmacy plays an important role in ensuring drug availability and effective stock management. With the increasing number of drug redemptions, manual data management becomes inefficient and can lead to understocking or overstocking. Therefore, a method is needed that is able to automatically analyze drug sales patterns to improve stock management efficiency. One approach that can be used is the Apriori algorithm, an effective data mining technique for finding patterns in drug redemptions. This study aims to analyze drug redemption patterns at the Belawan Navy Hospital Pharmacy using the Apriori algorithm. The data used is drug redemption data. The Apriori algorithm is applied to find relationships between drug items that are often purchased together, so that it can provide useful insights in drug stock management. The results of the study showed that the Apriori algorithm successfully identified several significant drug redemption patterns. These patterns can be used to improve the efficiency of drug stock management and ensure timely drug availability, as well as reduce the risk of understocking or overstocking. The results of the study used logistic regression to predict discrete (binary) values from a column based on values from other columns and the accuracy obtained was 1.0 or 100%. This study concludes that the application of data mining with the Apriori algorithm can provide significant benefits in optimizing the management of drug stock redemption in hospital pharmacies.
Prediction of the Number of Patient Visits in a Psychiatric Hospital Prof. Dr. M. Ildrem Using Naive Bayesian Algorithm Syahputra, Zidhane; Kurniawan, Rakhmat
Journal of Computer Networks, Architecture and High Performance Computing Vol. 7 No. 1 (2025): Article Research January 2025
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v7i1.5145

Abstract

This study was conducted to predict the number of patient visits at Prof. Dr. M. Ildrem Mental Hospital using the Naive Bayes algorithm, which is relevant given the increasing need for global mental health care. The main problem of this study is the difficulty in managing hospital resources efficiently due to unpredictable fluctuations in the number of patient visits. The research aims to apply the Naive Bayes algorithm to predict the number of patient visits and evaluate their performance. The method used is a naïve Bayes algorithm with systematic steps including historical data collection, data preprocessing using LabelEncoder, and dividing the dataset into training data and test data (80:20) where the training data totals 1331 data and the test data has 333 data. The Naive Bayes model is built and tested with metrics such as accuracy, precision, recall, and F1-score. The results of the study based on confusion matrix analysis, the model achieved an accuracy of 0.8108108108108109 or 81%, a precision of 0.8206686930091185 or 82.07%, a recall value of 0.9926470588235294 or 99.26%, and an F1-score of 0.90 or 90%, which shows that this model is quite effective in predicting service units with the dominance of adolescent category patient data where it is concluded that this prediction model is able to provide accurate estimates of patient visits,  supporting the management of hospital resources, and improving the operational efficiency of mental health services. This research is expected to help hospitals in planning facilities and workforce more effectively.
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