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Buletin Ilmiah Informatika Teknologi
Published by AMIK STIEKOM SUMATERA UTARA
ISSN : -     EISSN : 29620945     DOI : -
Core Subject : Science, Engineering,
Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Mechanical Engineering
Buletin Ilmiah Informatika Teknologi, merupakan wadah ilmiah yang menampung tulisan yang berasal dari hasil penelitian baik dari dosen maupun mahasiswa. Buletin Ilmiah Informatika Teknologi merupakan jurnal yang menampung berbagai tulisan pada bidang Ilmu Komputer. Artikel ilmiah yang dikirim pada redaksi harus merupakan naskah asli dan tidak pernah dipublikasi ditempat lain. Artikel ilmiah dalam setiap penerbitan merupakan tanggungjawab penulis. Buletin Ilmiah Informatika Teknologi terbit dalam periode 4 (Empat) bulanan Bulan September, Januari, Mei dengan ISSN :2962-0945 (media online) dengan SK Nomor: 005.29620945/K.4/SK.ISSN/2022.11 Topik utama yang diterbitkan pada Jurnal Buletin Ilmiah Informatika Teknologi, yaitu: Decision Support System, Expert System, Kriptografi, AI, Machine Learning, Data Mining, Image Processing, Pengolahan Citra, serta topik lain dalam bidang Informatika (menggunakan Metode dalam penyelesaian masalah).
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 5 Documents
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Search results for , issue "Vol. 3 No. 1: September 2024" : 5 Documents clear
Implementasi Teknologi IoT dalam Sistem Pemantauan Kualitas Udara di Politeknik Negeri Bengkalis Kurniawaty, Eva; Muhamad Nasir; M.Khairul
Buletin Ilmiah Informatika Teknologi Vol. 3 No. 1: September 2024
Publisher : AMIK STIEKOM SUMATERA UTARA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58369/biit.v3i1.81

Abstract

The campus environment, with its high daily activity, has the potential to cause air pollution if not managed properly. Therefore, it is crucial to monitor and maintain air quality at Politeknik Negeri Bengkalis to ensure a safe and healthy environment for the entire academic community. This research aims to design and implement an Internet of Things (IoT)-based air quality monitoring system that provides real-time information about air quality to users. The system utilizes MQ-2 and MQ-135 sensors to detect levels of carbon monoxide (CO) and carbon dioxide (CO2), with programming following specific protocols. The primary focus of this research is to develop a monitoring device that measures CO and CO2 levels and promotes efforts to improve air quality. Testing of the system was conducted at Politeknik Negeri Bengkalis, and the results indicated that the average CO levels fall within the normal or good category, and CO2 levels are also considered good. This research is expected to contribute to efforts to maintain air quality on campus, supporting the health and safety of the entire academic community. Keywords: Campus, Pollutan, Internet of Things, CO, CO2.
Kajian Risiko dan Manfaat Implementasi Internet of Things (IoT) Pada Pengelolaan Energi Listrik Berbasis Smart Grid Saiful Arifin, Muhammad; Ilham
Buletin Ilmiah Informatika Teknologi Vol. 3 No. 1: September 2024
Publisher : AMIK STIEKOM SUMATERA UTARA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58369/biit.v3i1.93

Abstract

The application of the Internet of Things (IoT) in smart grid-based electricity management offers great potential to enhance operational efficiency, system reliability, and environmental sustainability. IoT technology enables devices and sensors to connect and communicate in real-time. This creates a smart electricity grid that can collect accurate data, analyze energy consumption patterns, and support optimal resource management. This reduces energy waste, integrates renewable energy sources such as solar and wind power, and significantly contributes to the reduction of CO2 emissions. Additionally, IoT gives consumers greater control in monitoring and managing their energy consumption through technologies such as smart meters and cloud-based energy management systems. However, the implementation of this technology also faces various challenges, particularly related to cybersecurity threats, high initial investments, and the need for appropriate infrastructure. This research uses literature review techniques to investigate the benefits and risks of IoT implementation in smart grid systems. The research shows that cybersecurity threats such as data breaches and energy theft are one of the main obstacles that need to be addressed through security technologies such as data encryption, intrusion detection, and the development of blockchain-based security protocols. In addition, the high costs of procuring IoT hardware and software require government policy support and joint public-private sector investment. This study concludes that with the right approach, the implementation of IoT on smart grids can become a strategic solution for building a more efficient, environmentally friendly, and sustainable energy system. The recommendations provided include strengthening regulations, raising public awareness, and developing security technologies to minimize existing risks. Therefore, IoT can be the main catalyst for transforming the energy sector towards a more environmentally friendly and efficient future.
Kombinasi Metode Weighted Product Dan Simple Additiveweighting Pada Sistem Pendukung Keputusan Penerimaan Calon Siswa Baru Di SMP Negeri 1 Kualuh Hilir Sihotang, Suriani
Buletin Ilmiah Informatika Teknologi Vol. 3 No. 1: September 2024
Publisher : AMIK STIEKOM SUMATERA UTARA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58369/biit.v3i1.94

Abstract

Schools are educational institutions that provide formal education in the form of state schools managed by the government and private schools. SMP Negeri 1 Kualuh Hilir is the only school with a Junior High School education level in KAMPUNG MESJID which has been accredited B. The process of selecting new students at SMP Negeri 1 Kualuh Hilir has problems in terms of speed and the method used is not appropriate in selecting students. that school. Therefore, a decision support system is needed to solve the problems that occur. The Weighted Product (WP) method is a decision making method using multiplication to connect attribute ratings. The Simple Additive Weighting (SAW) method is a method used in decision making by finding the weighted sum of the performance ratings for each alternative on all attributes. By combining these two methods, it is hoped that it can help agencies in selecting participants who register at the school quickly and accurately. The final result of this research is that agencies can quickly and easily select students who meet the established criteria.
Komparasi Kinerja Algoritma Random Forest dan C4.5 untuk Klasifikasi Harga Mobil Ernawati, Andi; Karim, Abdul
Buletin Ilmiah Informatika Teknologi Vol. 3 No. 1: September 2024
Publisher : AMIK STIEKOM SUMATERA UTARA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58369/biit.v3i1.95

Abstract

Determining car prices is a crucial aspect of the automotive industry that requires accurate data analysis for strategic decision-making. This study aims to compare the performance of the Random Forest and C4.5 algorithms in classifying car prices based on specific features, such as technical specifications, production year, and market conditions. The dataset used in this study consists of [mention the size and source of the dataset if available], analyzed using a cross-validation approach to ensure the accuracy of the results. The performance of both algorithms is evaluated based on several metrics, including accuracy, precision, recall, and F1-score. The results show that the Random Forest algorithm consistently outperforms the C4.5 algorithm across most evaluation metrics, achieving an accuracy of [best Random Forest accuracy] compared to [best C4.5 accuracy]. These findings indicate that the Random Forest algorithm is more effective in handling multivariate data complexity and providing more reliable predictions. The conclusions of this study highlight the potential of Random Forest as the primary method for car price classification, especially in scenarios requiring high accuracy levels. This research also contributes to a comparative understanding of decision-tree-based algorithms for applications in the automotive industry and opens opportunities for further research into developing more adaptive and efficient models.
Implementasi Deteksi Objek Pada Jalan Rusak Menggunakan Metode YOLOv8
Buletin Ilmiah Informatika Teknologi Vol. 3 No. 1: September 2024
Publisher : AMIK STIEKOM SUMATERA UTARA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58369/biit.v3i1.76

Abstract

Roads are an essential transportation infrastructure that connects one place to another. Roads also have a significant impact on the development of a region because land transportation relies on roads to transport essential goods needed by the community, such as clothing and food. The dataset used consists of 26,336 images, divided into 80% training data, 10% validation data, and 10% test data. This software development aims to detect damaged road types using the YOLOv8 algorithm. The testing results showed that the best accuracy was achieved using 100 epochs, with an accuracy of 43.98%.

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