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Jurnal Computer Science and Information Technology (CoSciTech)
Published by Universitas Muhammadiyah Riau
ISSN : 2723567X     EISSN : 27235661     DOI : https://doi.org/10.37859/coscitech
Core Subject : Science,
Computer Science & IT
Jurnal CoSciTech (Computer Science and Information Technology) merupakan jurnal peer-review yang diterbitkan oleh Program Studi Teknik Informatika, Fakultas Ilmu Komputer, Univeritas Muhammadiyah Riau (UMRI) sejak April tahun 2020. Jurnal CoSciTech terdaftar pada PDII LIPI dengan Nomor ISSN 2723-5661 (Online) dan 2723-567X (Cetak). Jurnal CoSciTech berkomitmen menjadi jurnal nasional terbaik untuk publikasi hasil penelitian yang berkualitas dan menjadi rujukan bagi para peneliti. Jurnal CoSciTech menerbitkan paper secara berkala dua kali setahun yaitu pada bulan April dan Oktober. Semua publikasi di jurnal CoSciTech bersifat terbuka yang memungkinkan artikel tersedia secara bebas online tanpa berlangganan.
Arjuna Subject : Ilmu Komputer (semua kategori) - Aplikasi Ilmu Komputer
Articles 37 Documents
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Search results for , issue "Vol 5 No 3 (2024): Jurnal Computer Science and Information Technology (CoSciTech)" : 37 Documents clear
Perbandingan Algoritma SIMON dan SPECK Dalam Pengamanan Citra Digital Fatma, Yulia; Soni; Mikdad Amseno
Computer Science and Information Technology Vol 5 No 3 (2024): Jurnal Computer Science and Information Technology (CoSciTech)
Publisher : Universitas Muhammadiyah Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/coscitech.v5i2.7619

Abstract

Cryptography is a data security technique by encoding data that is to be kept secret so that the original meaning of the data can no longer be understood. SIMON and SPECK are modern cryptographic algorithms issued by the National Security Agency (NSA). SIMON and SPECK are said to be algorithms that are known for their efficiency and strong security. This research will compare the performance of the SIMON and SPECK algorithms in securing digital images. Comparisons were made by testing time performance, changes in file size, and the level of randomness of image files using the Unified Average Changing Intensity (UACI) and Number of Pixels Change Rate (NPCR) metrics. The research results show that the average encryption and decryption time required by the SIMON algorithm is greater when compared to the SPECK algorithm. The image file size resulting from encryption using the SIMON and SPECK algorithms both increased by 24% from the original image. The level of randomness of the resulting image based on the UACI value obtained using the SIMON algorithm was found to be an average of 19.65%, while the UACI value obtained using the SPECK algorithm was an average of 20.94%. This shows that there is a significant change in intensity between the original image and the encrypted image. However, not all pixels in the encrypted image change when compared to the original image, this is shown by the NPCR value obtained from the SIMON and SPECK algorithm encrypted image, with average results of 49.98% and 50.17%.
Dampak pembobotan pada metode hybrid user-based dan item-based untuk sistem rekomendasi film Fitriyeh, Fadetul; Haqqi, Nuskhatul; Choiriyah, Layla Mufah; Ifada, Noor
Computer Science and Information Technology Vol 5 No 3 (2024): Jurnal Computer Science and Information Technology (CoSciTech)
Publisher : Universitas Muhammadiyah Riau

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Abstract

The rapid development of technology means that information is becoming more abundant and diverse, including in the movie industry. The number of movies each year can reach tens of thousands with various genres, making it difficult for potential viewers to choose a movie that suits their interests. One solution to the problem is the existence of a recommendation system that can provide movie recommendations based on information on movies that have been watched previously. Collaborative Filtering is a widely used approach in recommendation systems. Collaborative Filtering offers recommendations based on the similarity between users for User-based methods and the similarity between items for Item-based methods. However, the similarity value can be high for data with high dispersion even though only one item is in common. The Hybrid method can be a solution to overcome this by combining User-based and Item-based methods and adding genre information from the items. The final prediction result is obtained from the prediction results of all methods combined using linear combination. The combination is done by giving weight to each method and then summarising it. This study aims to determine the impact of weighting variations on Hybrid User-based and Item-based Collaborative Filtering methods. The results obtained from this study show that More Dominant User-based and Very Dominant User-based weightings are superior to other weightings because they show good performance for a smaller list of recommendations.
Sistem Informasi penjualan Alat Tulis Kantor (ATK) Pondok Pesantren Al-Falah Yang Efektif Dan Efisien Dengan Menggunakan Php Dan Mysql Mardani, Alif; Achmad Baijuri; Firman Santoso
Computer Science and Information Technology Vol 5 No 3 (2024): Jurnal Computer Science and Information Technology (CoSciTech)
Publisher : Universitas Muhammadiyah Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/coscitech.v5i3.7774

Abstract

The rapid development of information technology has permeated various sectors, including cooperatives. Utilizing technology in cooperatives is crucial for enhancing the efficiency and effectiveness of decision-making. This study aims to design an integrated sales management system for ATK Mitra Kopontren Musa'adah. The current manual system has several drawbacks, such as data loss and inaccurate financial reports. By implementing an integrated information system, the cooperative is expected to produce more accurate, timely, and accessible financial reports, thereby improving its performance and transparency.
Analisis Data Forensik Pada Rekaman CCTV Menggunakan Metode National Institute Of Standard Techology (NIST) Ilham Asy'ari; Yuhandri; Sumijan
Computer Science and Information Technology Vol 5 No 3 (2024): Jurnal Computer Science and Information Technology (CoSciTech)
Publisher : Universitas Muhammadiyah Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/coscitech.v5i3.7779

Abstract

CCTV (Closed-Circuit Television) recordings have become one of the important instruments in monitoring and securing various places such as companies, commercial buildings, public institutions, and households. CCTV recordings are often vital evidence in investigating crimes, accidents, or other incidents. However, in addition to the visual content stored in CCTV recordings, metadata also plays an essential role in forensic analysis and event reconstruction. The NIST method has developed several techniques and guidelines for forensic metadata analysis on CCTV recordings. This research aims to explore and apply the forensic metadata analysis methods recommended by NIST (National Institute of Standards and Technology) in the context of CCTV recordings. By involving forensic data analysis techniques and information security principles, this study will delve into the potential of metadata analysis in supporting criminal investigations, event reconstructions, and meeting the security standards established by NIST. This research is crucial in the context of digital security and modern forensic investigations. The outcome of applying the NIST methods in forensic data analysis of CCTV recordings is the preparation of an official report derived from the stages outlined in the NIST method, so that the report can serve as a reference in court, and the authenticity of the digital evidence can be validated. By applying the NIST method in forensic data analysis of CCTV recordings, the case handling process becomes structured and adheres to procedures, with a valid report ensuring the integrity of the digital evidence.
Rancang Bangun Aplikasi Android Pengenalan Pembelahan Sel Menggunakan Teknologi Augmented Reality Markerless Fatma Dwi Anisa; T. Yudi Hadiwandra
Computer Science and Information Technology Vol 5 No 3 (2024): Jurnal Computer Science and Information Technology (CoSciTech)
Publisher : Universitas Muhammadiyah Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/coscitech.v5i3.7922

Abstract

Biology learning at SMA N 2 Pangkalan Kuras often requires practical sessions for several learning topics. However, the lack of a dedicated laboratory room and practical tools has led to the discontinuation of practical lessons. One of the topics that requires high visualization is cell division. This research aims to design and develop an Android application based on Augmented Reality (AR) using a markerless method as a practical medium for introducing the process of cell division. The markerless method is used so that the application can be used anywhere and anytime without relying on physical markers. This research utilizes the R&D method, and the application development follows the Multimedia Development Life Cycle (MDLC) method. The markerless AR-based cell division Android application system uses C# programming language and applies the Simultaneous Localization and Mapping (SLAM) algorithm. The application testing follows the ISO 25010 standard, consisting of functional suitability aspects, which achieved a result of 100%. The compatibility test also received a score of 100% for each smartphone that installed, ran, and uninstalled the application. The performance efficiency test shows that the camera system is capable of detecting flat surfaces such as tables, walls, and floors, while the average response time test revealed that the highest response speed was achieved on the latest Android types with larger RAM. The user experience received an "excellent" rating.
Implementasi Healthy Building Berbasis Internet of Things pada Taman Kanak-kanak Al Baraakah, RA Kreatif Kusumaningrum, Evy; Sumarsono, Sumarsono; Setiawan, Chanief Budi; Hariyadi, Dedy
Computer Science and Information Technology Vol 5 No 3 (2024): Jurnal Computer Science and Information Technology (CoSciTech)
Publisher : Universitas Muhammadiyah Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/coscitech.v5i3.8093

Abstract

The limited availability of air quality sensors leads to potential exposure to pollution that poses health risks. Monitoring of crucial clean air indicators, such as ISPU standards and emission requirements, as well as management of important aspects of healthy buildings such as ventilation, temperature, humidity, and security, are also inadequate. As a solution, this article proposes the development of an Internet of Things (IoT)-based smart school that utilizes advanced sensor technology to monitor and manage the condition of the educational environment in accordance with the healthy building foundation proposed by the Harvard T.H. Chan School of Public Health. With the integration of Tuya-based sensors and the use of HomeAssistant platform for automation, the implementation of this system in educational institutions such as TK Al Baraakah, RA Kreatif successfully created a healthier environment. As a result, better building conditions are achieved through real-time monitoring of vital parameters, forming a structured approach to creating safer and more comfortable schools for students and faculty. Monitoring and management can be shown on the Dashboard of the HomeAssistant platform.
Perbandingan Metode Learning Vector Quantization Dan Backpropagation Dalam Klasifikasi Personality Pada Anak Novita, Rita; Sujana, Teguh; Agusviyanda, Agusviyanda; Fitri, Triyani Arita; Susanti, Susanti
Computer Science and Information Technology Vol 5 No 3 (2024): Jurnal Computer Science and Information Technology (CoSciTech)
Publisher : Universitas Muhammadiyah Riau

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Abstract

This research focuses on classifying children's personalities at Rumah Bermain Bilal using Artificial Neural Network algorithms, specifically Learning Vector Quantization (LVQ) and Backpropagation. The primary objective of this study is to evaluate the effectiveness of these algorithms in categorizing children's personality data and to identify the most accurate method for educational settings. The experiments were conducted with various configurations, including the number of iterations and learning rate, to assess the performance of each algorithm comprehensively. The findings show that the LVQ method demonstrates higher accuracy than Backpropagation. For training data, LVQ achieved an accuracy of 73.47%, whereas Backpropagation reached only 40.82%. For test data, LVQ achieved an accuracy of 84.62%, significantly outperforming Backpropagation's 53.85%. These results indicate that LVQ is more effective in personality classification, especially in an educational context. It is hoped that these findings will assist educational institutions in implementing artificial intelligence-based methods to understand children's personality traits better, thereby supporting the development of more targeted teaching strategies.
Sistem pendukung keputusan untuk evaluasi kinerja pegawai honorer dengan metode weighted product Lia, Lia Umbari Putri; Yesputra, Rolly
Computer Science and Information Technology Vol 5 No 3 (2024): Jurnal Computer Science and Information Technology (CoSciTech)
Publisher : Universitas Muhammadiyah Riau

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Abstract

Evaluating the performance of contractual employees is a crucial step to ensure operational effectiveness and efficiency within government institutions, including at the Wali Nagari Binjai Office. However, manual evaluation processes often face challenges such as subjectivity and inaccuracy. This study aims to develop a Decision Support System (DSS) based on the Weighted Product (WP) method to provide an objective and transparent solution for evaluating the performance of contractual employees. The WP method was selected for its capability to process multi-criteria data by considering the weights of relevant criteria, such as work discipline, productivity, and attendance. The web-based system automates the calculation of preference values for each employee, simplifying the management process of identifying top performers efficiently. System testing results indicate that this approach produces more accurate evaluations compared to manual methods, with an accuracy rate of up to 90% based on historical data. Additionally, the system is user-friendly and can be integrated with other management processes. This study not only provides practical contributions to the Wali Nagari Binjai Office but also offers a model that can be adapted by other government institutions.
Analisis Perbandingan Model Fully Connected Neural Networks (FCNN) dan TabNet Untuk Klasifikasi Perawatan Pasien Pada Data Tabular Ismanto, Edi; Abdul Fadlil; Anton Yudhana
Computer Science and Information Technology Vol 5 No 3 (2024): Jurnal Computer Science and Information Technology (CoSciTech)
Publisher : Universitas Muhammadiyah Riau

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Abstract

Electronic Health Records (EHR) store tabular data that is rich in information and play a critical role in supporting decision-making within the healthcare field, particularly for patient care classification. This study evaluates the performance of two artificial intelligence models, Fully Connected Neural Networks (FCNN) and TabNet, in processing tabular data for patient care classification tasks. The findings reveal that both models demonstrate strong performance, with TabNet showing a slight advantage. TabNet achieves an accuracy of 0.74, marginally surpassing FCNN's 0.73. Furthermore, TabNet excels in precision (0.74 vs. 0.72), recall (0.72 vs. 0.71), and F1-Score (0.73 vs. 0.71), highlighting its greater reliability in minimizing false positives and accurately detecting positive cases with a better balance between precision and recall. With its architecture specifically tailored for tabular data and its capacity for direct interpretability, TabNet offers enhanced efficiency and ease of implementation compared to FCNN, which demands more complex data preprocessing. For future research, it is suggested to employ larger and more diverse datasets, explore data with higher feature complexity, and conduct comprehensive hyperparameter tuning to further improve the performance of both models.
Perancangan sistem informasi manajemen persediaan barang untuk usaha Mikro kecil dan menengah (UMKM) : Studi kasus pada toko arkhan jaya Rizka Hafsari; Andika Pratama
Computer Science and Information Technology Vol 5 No 3 (2024): Jurnal Computer Science and Information Technology (CoSciTech)
Publisher : Universitas Muhammadiyah Riau

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Abstract

In the current digitalization era and the increasing demand for efficiency, flexibility is a crucial aspect for the continuity of Small and Medium Enterprises (UMKM) in Indonesia. This research aims to design a more effective and efficient inventory management system for Arkhan Jaya, a UMKM in Indonesia. The system is expected to assist the management in reducing human errors, increasing productivity, and improving the accuracy of inventory information. The waterfall research methodology is used, which includes system requirements analysis, system architecture design, data technology design, system testing, and maintenance.During the analysis phase, specific needs of Toko Arkhan Jaya are identified to ensure that the developed system is suitable. The design phase produces a system architecture that includes a database, user interface, and functional modules. The design phase involves coding the main modules, system configuration, and user training. Testing is carried out to ensure that the system functions according to specifications, focusing on inventory management, purchasing, and sales processes.The research findings indicate that the designed information system can increase inventory management efficiency, enable quick and accurate decision-making, and provide accurate and real-time inventory information. This research contributes to improving inventory management in UMKMs.

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