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PERANCANGAN SISTEM ABSEN BERBASIS FACE RECOGNITION Manik, Yosep Pangihutan; Sitohang, Sunarsan
Computer Science and Industrial Engineering Vol 12 No 4 (2025): Comasie Vol 12 No 4
Publisher : LPPM Universitas Putera Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33884/comasiejournal.v12i4.9863

Abstract

The rapid advancement of face recognition technology offers potential solutions for inefficient manual attendance systems, such as the one at SMK Tunas Muda Berkarya Vocational School, which relies on time-consuming, error-prone methods. This study aimed to design and implement an automated attendance system using face recognition to enhance accuracy and efficiency. Employing Python, OpenCV, and the Eigenface method with Principal Component Analysis (PCA), the system integrated Viola-Jones algorithm for face detection and Haar-like features for training. UML diagrams guided the design, while Black Box Testing validated functionality. Results demonstrated successful implementation with 15 students, achieving efficient real-time attendance recording and reduced processing time. However, accuracy depended on optimal lighting and frontal face positioning. The conclusion affirms the Eigenface method’s effectiveness in automating attendance, significantly improving over manual systems. Future recommendations include optimizing environmental adaptability, integrating mobile platforms, and enhancing user interaction features for broader applicability. This research underscores the viability of biometric systems in educational institutional management.
PROTOTYPE SISTEM MONITORING KESEHATAN TUBUH MENGGUNAKAN IOT BERBASIS ANDROID Abdul Razaq Fatta Utama; Sunarsan Sitohang
Computer Science and Industrial Engineering Vol 12 No 4 (2025): Comasie Vol 12 No 4
Publisher : LPPM Universitas Putera Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33884/comasiejournal.v12i4.9865

Abstract

IoT (Internet of Things) is a concept that utilizes the internet network to connect various devices into a machine and allows these devices to operate automatically by collecting data in real time. body accurately and quickly. The heart works as a blood pumping device and is a very fatal organ if it does not work properly. This condition is a heart disorder which involves a delay in blood supply to the heart muscles because the blood vessels are blocked and the heart becomes abnormal. Heart problems or abnormal functioning of the heart can result in a 50% death rate. However, some people have difficulty reaching hospitals because they live in rural areas. Thus, it is hoped that today's advanced technology can help make the work of nurses easier and can help the medical field work in diagnosing patients quickly and precisely, and can be reached by all people, such as health monitoring tools based on body temperature. This tool can diagnose normal or abnormal heart conditions based on detection sensors connected to the device using network media and uses Android as a platform that provides an intuitive interface so that it can be adjusted to the needs or desires of a client or researcher. In this way, a Prototype tool is created, which is an initial design model for a design before increasing product sales.
Analisis Keamanan dan Kinerja Jaringan pada Implementasi VLAN Sebagai Upaya Segmentasi Trafik Menggunakan Cisco Packet Tracer Sitohang, Sunarsan; Pangaribuan, Hotma
Jurnal Sains Informatika Terapan Vol. 4 No. 2 (2025): Jurnal Sains Informatika Terapan (Juni, 2025)
Publisher : Riset Sinergi Indonesia (RISINDO)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62357/jsit.v4i2.673

Abstract

Dalam era digital saat ini, kebutuhan akan jaringan komputer yang andal, efisien, dan aman semakin meningkat, terutama pada organisasi yang memiliki banyak departemen dan perangkat yang saling terhubung. Untuk menjawab tantangan tersebut, konsep Virtual Local Area Network (VLAN) merupakan salah satu solusi yang digunakan secara luas dalam arsitektur jaringan modern. Switch sebagai perangkat Dimana akan diterapkannya vlan dengan mode access dan trunk. Cisco Packet Tracer merupakan perangkat lunak yang dapat digunakan dalam mensimulasikan penerapan vlan untuk melakukan segmentasi trafik. Simulasi sebagai metode yang dipilih dikarenakan sangat memudahkan untuk memahami jaringan baik untuk pembelajaran maupun untuk melihat detail dari setiap konfigurasi. Simulasi ini dilakukan pada tiga switch dan tiga vlan id yaitu Vlan 10, 20, 30 memisahkan ruang guru, lab akutansi dan lab rekayasa perangkat lunak. Berdasarkan hasil pengujian simulasi konfigurasi vlan berjalan dengan baik dilihat dari antarvlan yang berbeda terblok komunikasinya sedangkan untuk yang sama vlannya aksesnya sukses. Dengan segmentasi yang telah diterapkan menciptakan keamanan jaringan yang lebih baik sebelumnya yaitu tanpa adanya penerapan vlan
PELATIHAN VIRTUAL LOCAL AREA NETWORK (VLAN) DAN ROUTING DI SEKOLAH SMK ADVENT Sitohang, Sunarsan; Pangaribuan, Hotma
PUAN INDONESIA Vol. 7 No. 1 (2025): Jurnal PUAN Indonesia Vol. 7 No. 1 Juli 2025
Publisher : ASOSIASI IDEBAHASA KEPRI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37296/jpi.v7i1.420

Abstract

The development of technology has a very big impact on the world of education. Today's advanced technology is very helpful for humans in doing their work, so it must be applied to get its benefits. It is undeniable that there are still many educational worlds that are very reluctant to use technology. This reluctance can be caused by the lack of will to learn or inadequate facilities and the absence of motivation or training. Virtual Local Area Network (VLAN) is a logical grouping of users and equipment connected to a network that is connected to administratively designated ports on a switch without regard to the location of the switch. VLAN is a technology that allows a Local Area Network (LAN) to be divided into several different segments. VLAN also allows the merging of networks that are physically separated, but seem to be in the same segment. After the community service was carried out, it was seen that the students' knowledge had increased, marked by the results of the evaluation carried out at the end of each community service session in each topic of the material. The increase in students' understanding also increased in configuring VLANs, marked by the students' ability to do configuration exercises without any assistance from the community service. From this community service activity, it can be concluded that the community service went smoothly and the students' knowledge about Switches and VLANs increased.
PEMBINAAN ADMINISTRASI DENGAN MEMANFAATKAN SOFTWARE APPLICATION Sitohang, Sunarsan
Batoboh Vol 5, No 2 (2020): BATOBOH : JURNAL PENGABDIAN PADA MASYARAKAT
Publisher : Institut Seni Indonesia Padangpanjang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26887/bt.v5i2.1300

Abstract

Jaman digitalisasi dan teknologi maju saat ini sangat membantu manusia dalam mengerjakan pekerjaannya, sehingga harus diterapkan untuk mendapat manfaatnya. Tidak dapat dipungkiri masih banyak masyarakat sangat enggan dengan penggunaan teknologi. Keengganan ini bisa diakibatkan karena tidak adanya kemauan belajar ataupun fasilitas yang kurang memadai serta tidak adanya yang memotivasi atau pembinaan. Pembentukan RT 13 dan Pembinaan Kesejahteraan Keluarga (PKK) di Perumahan Taman Cipta Asri Tahap III masih baru sehingga beberapa pengurusnya masih tabu dengan software aplikasi untuk mengelola administrasi PKK. Pembinaan pemanfaatan software aplikasi untuk administrasi ini bertujuan agar pengurus organisasi PKK Perumahan Taman Cipta Asri Tahap 3 RT 13 RW 12 Kota Batam bisa memahami bagaimana memanfaatkan software aplikasi untuk membantu kegiatan PPK, cara penggunaan software aplikasi untuk kegiatan PPK baik berupa pembuatan laporan keuangan yang baik, presentasi yang menarik, surat undangan yang baik dan lain sebagainya. Oleh karena itu, pembinaan software aplikasi ini akan sangat dibutuhkan bagi pengurus Organisasi PKK yang berminat untuk mempelajarinya. Pembinaan dilaksanakan dengan metode memberikan materi tutorial, mempraktekkannya dengan pendampingan dan evaluasi. Target utama pembinaan ini adalah menciptakan masyarakat yang dapat menerapkan teknologi khususnya software aplikasi untuk mempermudah mengerjakan pekerjaannya, khususnya dalam administrasi PKK dengan memanfaatkan software aplikasi serta memahami bagaimana penggunaan Software aplikasi tersebut
IMPLEMENTASI FACE RECOGNITION MENGGUNAKAN METODE CONVOLUTIONAL NEURAL NETWORK UNTUK TRANSFORMASI DIGITAL ABSENSI Ricky; Sitohang, Sunarsan
Computer Science and Industrial Engineering Vol 13 No 1 (2025): Comasie Vol 13 No 1
Publisher : LPPM Universitas Putera Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33884/comasiejournal.v13i1.10263

Abstract

Advancements in digital technology have transformed conventional attendance systems into more secure and automated solutions. However, manual and online-based systems remain vulnerable to fraud, such as proxy attendance and false records. This study designs a digital attendance system using face recognition technology based on the Convolutional Neural Network method. The process begins by capturing facial images via camera, followed by preprocessing steps including grayscale conversion, face detection using Haar Cascade, and resizing images to 100x100 pixels. The CNN model is trained with the preprocessed dataset and saved in .joblib format for real-time face identification. Attendance is automatically recorded in a CSV file. Testing was conducted based on dataset size, distance, and face position relative to the camera. Results show that accuracy improves with more training data. Using 200 images per individual yielded the best balance of accuracy, speed, and storage efficiency unlike 50 images, which often failed, or 500 images, which required long training times and large storage. Lighting quality also significantly impacts recognition accuracy, poor or uneven lighting leads to unclear facial features. Thus, proper lighting is essential. This study demonstrates that CNN effectively supports the digital transformation of attendance systems, making them more accurate, efficient, and fraud-resistant.
IMPLEMENTASI NEURAL NETWORK DENGAN METODE LSTM UNTUK PREDIKSI PENJUALAN CHINTARI CAKE AND COOKIES Suranti; Sunarsan Sitohang
Computer Science and Industrial Engineering Vol 13 No 3 (2025): Comasie Vol 13 No 3
Publisher : LPPM Universitas Putera Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33884/comasiejournal.v13i3.10535

Abstract

In the competitive food and beverage industry sector, the ability to accurately predict demand is crucial to supporting effective production and marketing strategies. Chintari Cake and Cookies, a small and medium-sized enterprise (SME) specializing in homemade cakes and cookies, faces challenges in dealing with unpredictable demand fluctuations. This study aims to forecast daily sales using the Long Short-Term Memory (LSTM) algorithm, a type of Recurrent Neural Network (RNN) known for its effectiveness in processing sequential data and recognizing long-term patterns. LSTM was chosen due to its advantages over conventional statistical methods such as ARIMA, particularly in terms of prediction accuracy. Five years of historical sales data were used as model input, which was then processed through preprocessing stages before training the LSTM model. The prediction results were evaluated using RMSE (Root Mean Square Error) and MAPE (Mean Absolute Percentage Error) metrics. The results showed an RMSE value of 6.752 and a MAPE value of 6.792, indicating a low prediction error rate. These findings demonstrate that the LSTM algorithm can serve as an effective solution for SMEs in improving the accuracy of production planning and inventory management based on historical data patterns.
DESAIN DAN IMPLEMENTASI LAMPU RUANGAN OTOMATIS BERBASIS IoT Siregar, Ivan Hengki; Sitohang, Sunarsan
Computer Science and Industrial Engineering Vol 13 No 4 (2025): Comasie Vol 13 No 4
Publisher : LPPM Universitas Putera Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33884/comasiejournal.v13i4.10568

Abstract

Smart homes are part of an innovation in the application of the Internet Of Things, it can be seen that its application is able to automatically control almost all objects in the house. The purpose of the Internet Of Things (IoT) is continuously developed, one of which is to expand the use of the internet which is getting wider every day. With the development of technology and the existence of the Internet Of Things (IoT) which can be used in various fields of human needs today, for example with the existence of electronic room lighting devices that can be controlled remotely by utilizing an internet connection and controlled via an Android smartphone with a telegram application. In this study, a prototype of an automatic room lamp based on IoT was built, using the NodeMCU ESP8266 module as a microcontroller and to control remotely using the bot in the Telegram application. Based on the results of the trials carried out, it produced an IoT application that was able to control the lights from the telegram bot, so it can be concluded that the system can work well according to its objectives.  
Feature Selection to Enhance DDoS Detection Using Hybrid N-Gram Heuristic Techniques Maslan, Andi; Mohamad, Kamaruddin Malik Bin; Hamid, Abdul; Pangaribuan, Hotma; Sitohang, Sunarsan
JOIV : International Journal on Informatics Visualization Vol 7, No 3 (2023)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/joiv.7.3.1533

Abstract

Various forms of distributed denial of service (DDoS) assault systems and servers, including traffic overload, request overload, and website breakdowns. Heuristic-based DDoS attack detection is a combination of anomaly-based and pattern-based methods, and it is one of three DDoS attack detection techniques available. The pattern-based method compares a sequence of data packets sent across a computer network using a set of criteria. However, it cannot identify modern assault types, and anomaly-based methods take advantage of the habits that occur in a system. However, this method is difficult to apply because the accuracy is still low, and the false positives are relatively high. Therefore, this study proposes feature selection based on Hybrid N-Gram Heuristic Techniques. The research starts with the conversion process, package extract, and hex payload analysis, focusing on the HTTP protocol. The results show the Hybrid N-Gram Heuristic-based feature selection for the CIC-2017 dataset with the SVM algorithm on the CSDPayload+N-Gram feature with a 4-Gram accuracy rate of 99.86%, MIB- Dataset 2016 with the 2016 algorithm. SVM and CSPayload feature +N-Gram with 100% accuracy for 4-Gram, H2N-Payload Dataset with SVM Algorithm, and CSDPayload+N-Gram feature with 100% accuracy for 4-Gram. As a comparison, the KNN algorithm for 4-Gram has an accuracy rate of 99.44%, and the Neural Network Algorithm has an accuracy rate of 100% for 4-Gram. Thus, the best algorithm for DDoS detection is SVM with Hybrid N-Gram (4-Gram).