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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 49 Documents
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Implementasi Struktur Data Array dalam Sistem Perpustakaan Berbasis Web dengan Python Flask Rudianto; Sapaatullah , Asep; Rakhim Setya Permana, Basuki; Darip, Mochammad
Buletin Ilmiah Informatika Teknologi Vol. 3 No. 2: Januari 2025
Publisher : AMIK STIEKOM SUMATERA UTARA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58369/biit.v3i2.91

Abstract

− Library services must provide convenience for users in finding books, journals, and other references, and over time, especially in the digital era, libraries must be able to adapt to the rapid evolution of information technology. Technological transformation is expected to improve the efficiency, speed, and quality of library services. However, many library services still rely on manual systems in managing book collections and circulation services. This manual system causes various problems, ranging from difficulty in finding information on book collections, inefficient recording, to long queues for the borrowing process. In addition, manual services are often unable to provide real-time book availability information, thereby reducing user satisfaction. Therefore, a technology-based solution is needed to improve the efficiency of library management and make it easier for users to access information. One approach that can be used is the development of a web-based library system using the Python Flask framework by utilizing array data structures to store book collection information in an organized manner. The results of the implementation of this system show how information technology, especially Python Flask and array data structures can be used to overcome library service problems in universities, such as integrating book management by admins, searching for books based on keywords, updating book availability status, updating borrowing status, and ordering online. This information is very useful for users to improve the efficiency of librarians' work in increasing satisfaction with library services, thus making library services more responsive to user needs.
Simulasi Model Antrean FIFO Untuk Mengoptimalisasikan Penanganan Permintaan Layanan Di KUD CV. Rama Investama Sapaatullah, Asep; Rudianto; Rakhim Setya Permana, Basuki; Darip, Mochammad
Buletin Ilmiah Informatika Teknologi Vol. 3 No. 2: Januari 2025
Publisher : AMIK STIEKOM SUMATERA UTARA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58369/biit.v3i2.92

Abstract

Good service quality plays an important role in increasing the satisfaction and loyalty of cooperative members. However, challenges in providing optimal service often arise due to limited resources, such as limited number of employees, limited equipment and technology, and lack of training and development. The queue phenomenon is difficult to predict because the arrival time and service time are uncertain. Therefore, a more optimal queue management strategy is needed to reduce waiting time and ensure that service quality is maintained. The research method starts from problem identification, data collection, queue system modeling, to simulation result analysis. The FIFO model-based simulation approach was chosen because it allows testing various scenarios without disrupting company operations. The variables tested in this simulation include waiting time and its average, arrival time, and completion time. This simulation is designed using the Python programming language for flexibility and accuracy in testing queue scenarios. Based on the results of the simulation analysis, it was obtained that the application of the FIFO model provides a clear picture of the waiting time pattern, average waiting time, arrival time, and completion time. The simulation results show that an optimized queue management strategy can significantly reduce waiting time, especially during peak hours. In addition, with this simulation, improvement steps can be identified such as adding employees at certain times, increasing the efficiency of the service process, or using technology to support the automatic queuing system. This study provides strategic recommendations that can be implemented by KUD CV. Rama Investama in improving service quality. The implementation of the simulation results is expected to not only reduce waiting time, but also increase the satisfaction and loyalty of cooperative members, thus supporting the sustainability of overall operations.
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.
Rancang Bangun Sistem Informasi Donor Darah Pada UTD-PMI Kabupaten Sumbawa Berbasis Web App Imanura Bagaskara, Kukuh; Esabella, Shinta
Buletin Ilmiah Informatika Teknologi Vol. 3 No. 2: Januari 2025
Publisher : AMIK STIEKOM SUMATERA UTARA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58369/biit.v3i2.98

Abstract

The rapid advancement of technology has had a significant impact on the healthcare sector, including blood donor management. The Blood Transfusion Unit (UTD) of the Indonesian Red Cross (PMI) in Sumbawa Regency still relies on a manual system, such as paper forms and WhatsApp communication, leading to long queues, data errors, and delays in donor management. This study aims to design and implement a web-based information system utilizing Progressive Web App (PWA) technology to enhance the efficiency of blood donor registration and data management. The system enables donors and administrators to access and manage data in real time via web and mobile devices. This research employs a qualitative method with an iterative and Agile approach in software development. Testing results indicate that the developed system can accelerate the registration process, reduce queues, and minimize data errors. The implementation of this system is expected to improve the operational efficiency of the UTD-PMI in Sumbawa Regency and support a more responsive and accurate blood supply to meet medical needs.
Analisis Opini Masyarakat Terhadap Jasa Transportasi Online Menggunakan Text Mining Classification Santi
Buletin Ilmiah Informatika Teknologi Vol. 3 No. 2: Januari 2025
Publisher : AMIK STIEKOM SUMATERA UTARA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58369/biit.v3i2.117

Abstract

The rapid development of communication technology has brought about social changes in society. Many businesses have emerged by taking advantage of this development, one of which is the emergence of online motorcycle taxi services. The presence of Ojek Online has provided solutions and addressed various concerns of the public regarding public transportation services. Traffic congestion in the capital city and public safety concerns regarding public transportation have been addressed by the emergence of Ojek Online, which offers convenience and comfort to its users. The presence of Ojek Online, which applies appropriate communication technology at a time when the public needs safe transportation and can serve as a solution during traffic congestion, is the focus of this study, which is considered necessary to be constructed in this research. Moreover, the integration of transportation services with the sophistication of Internet technology has made it easier for the public to make bookings, know transportation rates, destination locations, and identify drivers, which is a new innovation in the transportation business world. By using the Innovation Diffusion Theory and a heuristic qualitative research approach on two of the largest online motorcycle taxi service providers in Indonesia, namely Grab Bike and PT Gojek Indonesia, this study provides an in-depth, comprehensive, and holistic understanding of the development of appropriate communication technology. The findings of this study will contribute concepts, particularly in the application of appropriate communication technology innovations that can bring about changes in the social system of society.
Klasifikasi kelayakan Calon Pegawai Honorer Dinas Pendidikan Kabupaten Labuhanbatu Menggunakan Metode Knn-Confunsion Hasibuan, Nursilmi
Buletin Ilmiah Informatika Teknologi Vol. 3 No. 2: Januari 2025
Publisher : AMIK STIEKOM SUMATERA UTARA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58369/biit.v3i2.118

Abstract

Eligibility Classification of Candidates for Honorary Personnel at the Education Service in Labuhanbatu Regency, policies will be made that can direct Honorary Personnel to be able to carry out their duties optimally. One of the policies of the Head of the Labuhanbatu Regency Education Service is to assess the suitability of Candidates for Honorary Staff. This policy aims to encourage honorary staff to carry out their duties well and with discipline, and this policy is sufficient to improve the performance of the honorary staff at the Labuhanbatu Regency Education Office. The biggest problem with the performance of Honorary Staff within the Labuhanbatu Regency Education Service is service orientation, integrity and discipline. In selecting new Honorary Staff Candidates, it is necessary to have a Classification of the Eligibility of the new Honorary Staff Candidates. The way to determine the eligibility of new Honorary Staff Candidates to become Honorary Staff is by calculating the similarity value. Next, to ensure errors in assessing the similarity of criteria, measurements of the level of accuracy, precision, recall are carried out, and comparison measurements are made of the level of accuracy, precision and recall. Based on the problems above, there is a need to develop a Decision Support System that is capable of selecting the Eligibility Classification of Candidates for Honorary Staff at the Labuhanbatu Regency Education Service. K-nearest Neighbors or KNN is a classification algorithm that works by taking a number of K nearest data (neighbors) as a reference to determine the class of new data. This algorithm classifies data based on similarity or closeness to other data. Confusion Matrix is a performance measurement for machine learning classification problems where the output can be two or more classes.
Analisis Topik Dominan Dalam Paper Ilmu Komputer Menggunakan TF-IDF Dan K-Means Laksana, Jovansa Putra; Shela, Shela; Irsyad, Hafiz; Rahman, Abdul
Buletin Ilmiah Informatika Teknologi Vol. 3 No. 3: Mei 2025
Publisher : AMIK STIEKOM SUMATERA UTARA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58369/biit.v3i3.122

Abstract

The rapid growth of scientific publications in the field of computer science has created a need to understand the distribution and trends of emerging research topics. This study aims to identify and analyze dominant topics in computer science literature using a text mining approach based on Term Frequency–Inverse Document Frequency (TF-IDF) vectorization and the K-Means clustering algorithm. A total of 1,222 publication titles from Semantic Scholar (2020–2025) were processed through language normalization, text preprocessing, TF-IDF feature extraction, optimal cluster determination, and cluster quality evaluation using Silhouette Score and Davies-Bouldin Index (DBI). The results reveal that topics such as cybersecurity, artificial intelligence, and machine learning are the most prevalent. While some clusters show good internal cohesion, the overall evaluation yielded a Silhouette Score of 0.0585 and a DBI of 4.387, indicating overlapping topics and limited cluster separation. These findings suggest that although the TF-IDF and K-Means approach can highlight general topic trends, it has limitations in capturing semantic context. Future research is encouraged to explore more contextual representation and clustering techniques to improve topic analysis quality.
Penerapan Smart, Edas, Dan Cosine Similarity Dalam Rekomendasi Lowongan Pekerjaan Di Era Digital levid, Jonathan Felix; WIjaya, Daniel; Irsyad, Hafiz; Rahman, Abdul
Buletin Ilmiah Informatika Teknologi Vol. 3 No. 3: Mei 2025
Publisher : AMIK STIEKOM SUMATERA UTARA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58369/biit.v3i3.128

Abstract

The rapid advancement of digital technology has increased the need for intelligent systems to filter job vacancies that match user profiles. This study aims to develop a job recommendation system based on a combination of Cosine Similarity, SMART, and EDAS methods. Job data were obtained from the JobStreet website and processed through text preprocessing stages such as tokenization, stopword removal, and stemming. Job descriptions and job seeker profiles were converted into numerical vectors using the TF-IDF method. Cosine Similarity was used to measure content similarity, SMART to evaluate suitability based on weighted criteria such as education and experience, and EDAS to assess alternatives relative to the average solution. System evaluation was conducted using precision, recall, F1-score, and mean Average Precision (mAP) metrics. Results show that Cosine Similarity alone had the lowest performance (F1-score 41.9%, mAP 42.3%), improved with the addition of SMART (F1-score 51.1%, mAP 50.9%), and achieved the best results with the integration of Cosine Similarity and EDAS (F1-score 66.5%, mAP 65.8%). Therefore, the integration of text similarity and multi-criteria decision-making methods effectively enhances the accuracy and relevance of job vacancy recommendations.

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