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INDONESIA
Jurnal Algoritma
Published by Institut Teknologi Garut
ISSN : 14123622     EISSN : 23027339     DOI : https://doi.org/10.33364/algoritma
Core Subject : Science,
Computer Science & IT
Jurnal Algoritma merupakan jurnal yang digunakan untuk mempublikasikan hasil penelitian dalam bidang Teknologi Informasi (TI), Sistem Informasi (SI), dan Rekayasa Perangkat Lunak (RPL), Multimedia (MM), dan Ilmu Komputer (Computer Science).
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 1,026 Documents
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Sistem Informasi Perpustakaan Di Smp Negeri 19 Semarang Berbasis Web Graciano, Joy Arnold; Yusup; Tridian Galih, Sinta
Jurnal Algoritma Vol 22 No 2 (2025): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.22-2.2553

Abstract

This study aims to develop a web-based Library Information System at SMP Negeri 19 Semarang. This system is expected to improve efficiency in the process of borrowing, returning, and managing library member data. Currently, these processes are still carried out manually, which causes data inconsistencies and increases the possibility of errors in data collection. The method used is system development using the Waterfall model, with data collection through observation, interviews, and literature study. The developed system is equipped with features such as book borrowing and return records, member data management, and automatic report generation. System testing was conducted using trials to ensure the functionality and ease of use of the system. The results of this study indicate that the developed system can improve library operational efficiency and ease of access for users in accessing books. It is hoped that this system can be implemented to facilitate more efficient and organized library activities in the future.
Deteksi Serangan DoS pada IoT Berbasis MQTT Menggunakan XGB dan PSO Dwi Azahra, Aisya; Monika Dian Pertiwi, Kharisma
Jurnal Algoritma Vol 22 No 2 (2025): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.22-2.2623

Abstract

The Internet of Things (IoT) is a technological innovation that enables physical devices to connect and communicate with one another through the internet, allowing them to exchange data automatically. This technology has been widely applied in various domains, such as smart homes and security systems. However, as the number of connected devices increases, the risk of cyberattacks also grows. One common type of attack is Denial of Service (DoS), an attempt to flood a system with excessive traffic, thereby disrupting communication between devices. This attack often exploits the MQTT protocol, which is popular in IoT environments due to its lightweight and efficient nature. This study aims to detect DoS attacks in MQTT-based IoT systems by implementing the Extreme Gradient Boosting (XGBoost) algorithm combined with feature selection using Particle Swarm Optimization (PSO). The dataset used consists of simulated MQTT traffic designed to resemble real-world conditions. The developed model is capable of classifying data into either normal or attack categories. The evaluation results demonstrate excellent performance, with precision ranging from 94.44% to 96.80%, recall from 99.63% to 99.97%, F1-scores between 96.95% and 97.81%, and an average accuracy of 99.89%. The main contribution of this research lies in integrating XGBoost with PSO on a realistic MQTT-based simulation dataset. This approach enhances both accuracy and computational efficiency, making it more suitable for resource-constrained IoT devices, and underscores the novelty of producing a DoS attack detection system that is accurate, efficient, and adaptive to real IoT network conditions.
Audit Sistem Akademik Terhadap Akurasi Data Mahasiswa Universitas XXX dengan Framework COBIT 4.1 Juniar Wibowo, Yehezkiel; Dharmawan, Alexander; Wahyuni, Ana
Jurnal Algoritma Vol 22 No 2 (2025): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.22-2.2629

Abstract

This study aims to evaluate and provide recommendations for improvements to IT governance in the Integrated Information System (SISTA) at XXX University, using the COBIT 4.1 standard with domains AI2, AI7, DS5, DS10, DS11, ME1, and ME2. This study uses a literature review method and data collection by distributing questionnaires to 6 respondents consisting of PUSTIK staff and lecturers. The results of the data collection show the maturity level of each domain. The AI domain score was 3.4, which is at the Defined level, DS was 2.7 at the Repeatable but Intuitive level, and ME was 2.7 at the Repeatable but Intuitive level. Based on the analysis of the maturity level results, recommendations for improvement are needed to improve IT governance in SISTA at XXX University in order to improve its quality.
Pengembangan dan Evaluasi Aplikasi Interaktif Berbasis Android untuk Pendidikan Agama Islam dalam Meningkatkan Keterlibatan dan Pemahaman Siswa di Sekolah Dasar Versanika, Dayanni Vera; Nugraha, Ahmad Lukman; Kartaputrra, Dani Pradana
Jurnal Algoritma Vol 22 No 2 (2025): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.22-2.2923

Abstract

Penelitian ini bertujuan untuk mengembangkan aplikasi edukasi interaktif Pendidikan Agama Islam (PAI) berbasis Android yang dirancang khusus bagi siswa kelas IV SD Negeri Cipadang. Aplikasi ini dikembangkan menggunakan metode Multimedia Development Life Cycle (MDLC) yang mencakup enam tahap, serta berisi sepuluh bab materi sesuai Kurikulum Merdeka dalam bentuk teks, gambar, audio, dan fitur interaktif. Hasil pengujian menunjukkan fungsionalitas aplikasi berjalan baik dengan tingkat keberhasilan 86% dari 402 test case. Validasi ahli materi menggunakan Aiken’s V menghasilkan indeks rata-rata 0,915 (kategori “Sangat Tinggi”), sedangkan uji reliabilitas instrumen memperoleh nilai Cronbach’s Alpha sebesar 0,84 yang menandakan konsistensi instrumen yang baik. Uji coba lapangan (beta testing) yang melibatkan 50 siswa menunjukkan tingkat penerimaan pengguna pada kategori “Sangat Layak” dengan rata-rata persentase di atas 88% pada seluruh aspek yang diukur. Temuan ini membuktikan bahwa aplikasi edukasi interaktif PAI mampu meningkatkan pemahaman siswa, mendukung internalisasi nilai-nilai agama, serta memberikan pengalaman belajar yang lebih menarik dan sesuai dengan kebutuhan pembelajaran era digital. Penelitian ini berkontribusi terhadap pengembangan media pembelajaran berbasis digital dalam konteks PAI serta memberikan implikasi praktis bagi peningkatan keterlibatan belajar siswa di sekolah dasar.
Rancang Bangun Sistem IoT Berbasis Energi Hibrid untuk Pemantauan Real-Time dan Peringatan Dini Banjir Rob Pesisir Al Haris, Firdhaus Hari Saputro; Wisudawanto, Rahmat; Fathin Wahyu Lestari, Azizun
Jurnal Algoritma Vol 22 No 2 (2025): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.22-2.2948

Abstract

Tidal flooding is a chronic problem in the coastal areas of Semarang that requires a reliable, real-time monitoring system. This study aims to design, build, and test a prototype Internet of Things (IoT) system for tidal flood monitoring that can operate in coastal environments with limited infrastructure. The research method used is Research and Development (R&D), which includes needs analysis, system design, implementation, and experimental testing. The resulting prototype consists of an HC-SR04 ultrasonic sensor, an Arduino Nano microcontroller, and a NodeMCU ESP8266 communication module supported by a hybrid energy source of a 100-watt solar panel and a 12V 8Ah battery. The measured data is sent to the server and visualized on the web dashboard https://pasutmaritimsmg.store/dashboard.php and sent as an early warning notification via the Telegram application. The test results show that the system has a measurement accuracy of plus or minus 0.25 cm with a data delivery success rate of 98.2%. The system can operate independently for more than 5 days without sunlight. Validation with data from the Indonesian Meteorological, Climatological, and Geophysical Agency (BMKG) shows a very high correlation (R² = 0.98). It is concluded that this prototype is effective as a real-time tidal flood monitoring solution and can be further developed to support an integrated early warning system.
Peningkatan Sensitivitas Deteksi Diabetic Retinopathy melalui Mekanisme Hierarchical Self-Attention pada Swin Transformer Mustaqim, Tanzilal; Safitri, Pima Hani; Oktavia, Vessa Rizky
Jurnal Algoritma Vol 22 No 2 (2025): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.22-2.2986

Abstract

Diabetic Retinopathy (DR) is a complication of diabetes that can cause blindness if not detected early. CNN has limitations in capturing scattered lesions due to its narrow receptive field, while Vision Transformers are generally less computationally efficient. The objective of this study is to develop an approach that can capture long-range spatial dependencies while maintaining computational efficiency for resource-limited clinical applications. The Swin Transformer-Tiny was implemented with a shifted window-based hierarchical self-attention mechanism on the APTOS 2019 dataset (3,663 retinal images), with pre-processing (CLAHE, gamma correction, Gaussian filtering) and data augmentation. The model was trained using SGD with CosineAnnealingLR and evaluated based on accuracy, precision, recall, and F1-score with a focus on minimizing false negatives. Swin Transformer-Tiny achieved an accuracy of 84.99%, precision of 84.89%, and recall of 84.99%, surpassing EfficientNet-B0 by 1.32% in F1-score and outperforming ResNet50 by 5.60%. The attention mechanism reduces false negatives by 1.28% compared to conventional CNNs while maintaining linear computational complexity. This research contributes to showing that hierarchical self-attention in Swin Transformer effectively improves DR detection sensitivity by overcoming the limitations of CNN receptive fields, while maintaining computational efficiency for clinical implementation.
Sistem Pendukung Keputusan Kelayakan Nasabah Peminjam Menggunakan Metode COPRAS Berbasis Website Murni, Ira; Ikhwan, Ali
Jurnal Algoritma Vol 22 No 2 (2025): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.22-2.2993

Abstract

In the financial industry, assessing customer eligibility for loans is a necessary process to avoid bad credit risks. This study offers the implementation of Complex Proportional Assessment (COPRAS) for customer eligibility. This study contributes to the development of a decision support system that improves the efficiency of microloan eligibility analysis. A decision support system is a framework or intelligent tool that enables decision makers to make decisions based on alternatives, criteria, and weights. The COPRAS method is useful for analyzing and determining the differences between several alternatives based on predetermined criteria. The final results show that Wiji Muliyani ranks first with the highest score of 100. This score was obtained from manual calculations and the system. The system also works well, as proven through black-box testing and usability testing using the System Usability Scale (SUS) method, which showed an average score of 95, meaning that the system is very good and easy to use. This system is expected to help reduce bad credit risk and improve decision accuracy.
Perancangan Enterprise Architecture untuk UMKM Pengolahan Produk Perikanan Menggunakan TOGAF ADM Ningtyas, Mastuty Ayu; Ananda, Dahliar; Amri, Arni Muarifah; Atha Ningrum, Maharani Febhi
Jurnal Algoritma Vol 22 No 2 (2025): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.22-2.2999

Abstract

The use of information technology in the micro, small, and medium enterprises (MSMEs) sector for processing fishery products at PT. Anugrah Laut Indonesia plays an important role in improving operational efficiency and industrial competitiveness. However, most of the company's core business processes are not yet running optimally due to the absence of an integrated system architecture blueprint as a guide for information system development. This condition has resulted in key operational activities, such as sales, raw material procurement, production, and distribution, not being adequately documented and integrated. Therefore, it is necessary to design an Enterprise Resource Planning (ERP) architecture that integrates information technology to align business needs and improve operational efficiency. This study uses a qualitative approach, with architecture design based on The Open Group Architecture Framework, Architecture Development Method (TOGAF ADM), and focuses on three main phases: Architecture Vision, Business Architecture, and Information System Architecture. The results of this study are in the form of an IT blueprint design that describes the integration of key business processes, data requirements, and information system plans to support improved operational efficiency and decision making.
Prediksi Kebutuhan Peralatan Gudang Menggunakan Triple Exponential Smoothing dalam Sistem Inventaris Berbasis Android Pratiwi, Radila; Triase
Jurnal Algoritma Vol 22 No 2 (2025): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.22-2.3043

Abstract

Spare parts inventory management at PT Wilco Tera Citra is still hampered by manual recording and fluctuations in demand. This study aims to develop an Android-based spare parts demand forecasting system using the Triple Exponential Smoothing (TES) method to support more measurable procurement decisions. The data consists of historical demand for 15 items over 12 months (2024). TES was applied to analyze the level, trend, and seasonal components, as well as to evaluate the sensitivity of the parameters a = 0.2, B = 0.2, y = 0.2. The results show low MAPE for Cylinder Liners (3.74%) and Fuel Injectors (4.60%), and moderate MAPE for Turbochargers (13.21%), with respective demand patterns: stable, seasonal, and declining trend. This study emphasizes methodological contributions through inter-item performance evaluation, TES integration into mobile inventory systems, and prediction support in procurement decision-making. Limitations include a relatively short 12-month dataset and an application that is not yet integrated with real-time stock data.
Analisis Sentimen Ulasan Pengguna GoPay di Google Play Store menggunakan Model IndoELECTRA Fitriati, Lisna Rahma; Guntara, Rangga Gelar; Purwaamijaya, Btari Mariska
Jurnal Algoritma Vol 22 No 2 (2025): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.22-2.3053

Abstract

The use of digital wallets in Indonesia continues to increase, making it important to analyze user opinions on services such as GoPay. This study analyzes the sentiment of 9,713 GoPay user reviews from the Google Play Store (September 16–October 2, 2025) using the IndoELECTRA model. The research stages included data collection, pre-processing, tokenization, training, and model evaluation. IndoELECTRA produced 95% accuracy and an F1-score of 0.95, demonstrating its strong performance in processing informal Indonesian text. These results confirm the potential of monolingual models in understanding local linguistic contexts compared to some multilingual models. This research contributes to the development of Indonesian NLP, including sentiment evaluation on neutral ratings, although it is limited to Google Play Store data sources and only covers two main sentiment classes.

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