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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
Analisis Kualitas Perbandingan Citra Dengan Metode Segmentasi Citra Pangaribuan, Hotma; Simanjuntak, Pastima
Jurnal Teknik Informatika UNIKA Santo Thomas Vol 6 No. 2 : Tahun 2021
Publisher : LPPM UNIKA Santo Thomas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54367/jtiust.v6i2.1470

Abstract

-Citra digital merupakan gambaran yang jelas dari objek yang dapat diolah dengan komputer. Semakin besar ukuran (pixel) citra akan membutuhkan tempat penyimpanan yang besar pula. Dasar pengolahan citra yang dilakukan dalam penelitian ini terletak pada proses segmentasi pengolahan citra. Hal yang perlu dipertimbangkan adalah objek dari citra abu abu yang akan diidentifikasi. Proses pengolahan citra melibatkan beberapa proses mulai dari akuisisi citra, preprocessing dan proses pengolahan citra sampai hasilnya. Preprocessing dilakukan untuk proses segmentasi yaitu dengan mengubah citra menjadi citra grayscale, dan kemudian diubah menjadi citra hitam putih. Dalam setiap proses dilakukan padding haar untuk mengurangi ukuran (size on disk) dengan matriks Ukuran 8x8. Dan juga dilakukan proses dilasi dan opening untuk membuat objek terlihat jelas sertamenghaluskan permukaan untuk menghilangkan noise. Nilai GCE dan MSE yang dihasilkan dari ketiga ekstensi tersebut juga relatif kecil, mendekati 0. Ini menandakan citra hasil segmentasi memiliki nilai kesamaan yang yang besar dengan citra aslinya. Setelah dilakukan Analisa perbandingan maka dapat diambil kesimpulan citra yang paling berkualitas
Data Mining Rekomendasi Pemakaian Skincare Simanjuntak, Pastima; Pangaribuan, Hotma; Syastra, Muhammad Taufik
MEANS (Media Informasi Analisa dan Sistem) Volume 6 Nomor 1
Publisher : LPPM UNIKA Santo Thomas Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (604.417 KB) | DOI: 10.54367/means.v6i1.1224

Abstract

Facial treatments or skincare treatments contained in beauty care are divided into two categories, namely home treatment (such as giving face soap, morning cream, night cream, etc.) and direct care (such as facials, chemical peels, and so on). Home treatment facials consist of a variety of care products. Each home treatment product has a specific function both for treating the face or fixing the skin on consumers' faces such as acne, black spots, blackheads, oily skin, and others. Therefore, in order to determine the right home treatment product for consumers, knowledge of the usefulness of a home treatment product is needed. One of the factors of trade problems that exist in Batam City, there are still many products that enter without knowing whether the product is safe or not to be used, especially for cosmetic or skincare products where many cosmetic products are not licensed by BPOM but can still be traded to the people of Batam City. Finding skincare cosmetics that are good for the community is very difficult, because too many skincare products are sold in the market that do not have a BPOM permit and it will be dangerous for people who use these products. It is also due to the absence of a recommendation from a doctor or a beautician, which causes the wrong or bad skincare selection and will have a bad impact on one's face. The purpose of this study was to make recommendations for the use of skincare products in Batam City. For this reason, through this research, the researcher intends to apply one of the data mining techniques with the naïve Bayes algorithm with software implementation using the Tanagra 4.1 software, where the results of this study can be used to see consumer buying patterns that have been neglected to increase product sales, and also see the decisions made to help recommendations for skincare use in Batam City.
Analisis Kualitas Perbandingan Citra Dengan Metode Segmentasi Citra Pangaribuan, Hotma; Simanjuntak, Pastima
Jurnal Teknik Informatika UNIKA Santo Thomas Vol 6 No. 2 : Tahun 2021
Publisher : LPPM UNIKA Santo Thomas

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (425.796 KB) | DOI: 10.54367/jtiust.v6i2.1470

Abstract

-Citra digital merupakan gambaran yang jelas dari objek yang dapat diolah dengan komputer. Semakin besar ukuran (pixel) citra akan membutuhkan tempat penyimpanan yang besar pula. Dasar pengolahan citra yang dilakukan dalam penelitian ini terletak pada proses segmentasi pengolahan citra. Hal yang perlu dipertimbangkan adalah objek dari citra abu abu yang akan diidentifikasi. Proses pengolahan citra melibatkan beberapa proses mulai dari akuisisi citra, preprocessing dan proses pengolahan citra sampai hasilnya. Preprocessing dilakukan untuk proses segmentasi yaitu dengan mengubah citra menjadi citra grayscale, dan kemudian diubah menjadi citra hitam putih. Dalam setiap proses dilakukan padding haar untuk mengurangi ukuran (size on disk) dengan matriks Ukuran 8x8. Dan juga dilakukan proses dilasi dan opening untuk membuat objek terlihat jelas sertamenghaluskan permukaan untuk menghilangkan noise. Nilai GCE dan MSE yang dihasilkan dari ketiga ekstensi tersebut juga relatif kecil, mendekati 0. Ini menandakan citra hasil segmentasi memiliki nilai kesamaan yang yang besar dengan citra aslinya. Setelah dilakukan Analisa perbandingan maka dapat diambil kesimpulan citra yang paling berkualitas
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.
PERANCANGAN SISTEM MONITORING KELEMBAPAN TANAH PADA TANAMAN CABAI BERBASIS INTERNET OF THINGS Rajagukguk, David; Pangaribuan, Hotma
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.v13i4.10445

Abstract

Chili plants require proper and consistent irrigation to ensure healthy growth and optimal crop yields. However, in many agricultural settings, especially in small to medium-scale farming, the absence of a real-time monitoring system often leads to under-watering or over-watering. These issues can result in wilting, root damage, or even crop failure. To address this challenge, this study presents the development of a soil moisture monitoring system based on the Internet of Things (IoT). The system integrates a soil moisture sensor (YL-69), NodeMCU ESP8266 microcontroller, and the Blynk mobile application. The NodeMCU acts as the main controller that receives data from the sensor, processes it, and transmits the information to the Blynk platform via Wifi.The Blynk app provides a user-friendly interface that displays soil moisture conditions in real-time. Moisture levels are categorized into three conditions: dry (<50%), normal (50–70%), and wet (>70%). A Gauge widget shows the moisture percentage visually in analog form, while the SuperChart logs the historical moisture data. When moisture falls below 50%, the system triggers a notification alert to the user. The test results demonstrate accurate sensor readings, real-time data transmission, and effective notification delivery. Overall, this system enhances irrigation decision-making and helps farmers maintain optimal soil moisture, thereby improving the sustainability and productivity of chili cultivation.
ANALISIS SENTIMEN KEPUASAN PELANGGAN TRANSPORTASI ONLINE PADA GRAB MENGGUNAKAN SUPPORT VERCTOR MACHINE Sitanggang, Denny; Pangaribuan, Hotma
Computer Science and Industrial Engineering Vol 13 No 2 (2025): Comasie Vol 13 No 2
Publisher : LPPM Universitas Putera Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33884/comasiejournal.v13i2.10452

Abstract

Online transportation services such as Grab have become an essential part of urban mobility in Indonesia, generating a wide range of user reviews that reflect levels of satisfaction. This study aims to analyze the sentiment of these reviews using the Support Vector Machine (SVM) algorithm. Data were collected from the Google Play Store and processed through several stages, including text preprocessing, automatic labeling based on rating scores (≤3 as negative, ≥4 as positive), and feature representation using the Term Frequency–Inverse Document Frequency (TF-IDF) method. The dataset was split into training data (80%) and testing data (20%), and the SVM model was trained using a linear kernel. Evaluation results showed an accuracy of 82%, precision of 84%, recall of 78%, F1-score of 79%, and an AUC of 0.9015. Further analysis of negative reviews revealed that the aspects of “drivers,” “application,” and “payment” were the main sources of complaints. These findings demonstrate the effectiveness of SVM in sentiment classification and its potential as a data-driven service evaluation tool. The study also recommends manual labeling or semantic-based approaches to address inconsistencies between review scores and content.
PERANCANGAN APLIKASI PENDETEKSI STUNTING PADA BALITA DENGAN AUGMENTED REALTY Dofariando, Muhammad Ariel; Pangaribuan, Hotma
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.v13i3.10519

Abstract

Stunting is a form of chronic malnutrition that causes impaired growth and development in children under five, especially in their first 1,000 days of life. The high prevalence of stunting in Indonesia, despite national reduction efforts, demands more effective and innovative early detection solutions. Conventional anthropometric measurements are still carried out manually and often overlooked by the public due to lack of awareness and tools. This research aims to design and implement an Android-based application utilizing Augmented Reality (AR) technology to assist in early detection of stunting in toddlers. The application uses the WHO Z-score Height-for-Age standard and camera-based real-time measurement with AR support on devices equipped with Time-of-Flight (ToF) sensors. The study applied a structured development methodology and was implemented using Unity and ARCore SDK. Users input the child’s age and weight, then scan the child’s height with their device, and the system automatically classifies stunting status visually and informatively. Testing showed that the application achieved an accuracy rate of approximately 99% at optimal lighting and scanning distance, with successful rendering of 2D and 3D objects. It also proved effective in raising awareness by offering educational content such as interactive visualizations, growth graphics, and parenting tips. The results confirm that the AR-based stunting detection application is functional, user-friendly, and informative, providing both a diagnostic tool and a medium for public health education. It supports government stunting reduction programs and empowers parents and healthcare workers in remote or underserved areas.
REKOMENDASI PRODUK E-COMMERCE BERBASIS KLASIFIKASI MENGGUNAKAN ALGORITMA MACHINE LEARNING Nehe, Intensif; Pangaribuan, Hotma
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.v13i4.10562

Abstract

The growth of e-commerce is driving an increase in the number of product reviews, but notall reviews are informative and relevant. This study aims to build a Tokopedia reviewclassification system using the Naive Bayes algorithm to filter relevant reviews. The datasetused totaled 40,607 product review lines. The preprocessing process includes cleaning,tokenization, stopword removal, and feature transformation using TF-IDF with 5,000 featurewords. Labels are determined based on ratings, where a rating of 4-5 is considered relevant.The Multinomial Naive Bayes model yielded an accuracy of 93.71%, a precision of 0.94, arecall of 0.99 for the relevant class, and an F1-score of 0.96. Although performance inirrelevant classes is still low, this model is effective in supporting product recommendations
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).