cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
Yuhefizar
Contact Email
ephi.lintau@gmail.com
Phone
+628126777956
Journal Mail Official
ephi.lintau@gmail.com
Editorial Address
Jalan Jati Padang Raya No. 41 Jati Padang Pasar Minggu Jakarta Selatan Kode Pos 12540
Location
,
INDONESIA
Prosiding Seminar Nasional Sisfotek (Sistem Informasi dan Teknologi Informasi)
Published by Ikatan Ahli Informatika Indonesia
ISSN : -     EISSN : 25973584     DOI : -
Core Subject : Science,
Computer Science & IT
Seminar Nasional Sistem Informasi dan Teknologi (SISFOTEK) merupakan ajang pertemuan ilmiah, sarana diskusi dan publikasi hasil penelitian maupun penerapan teknologi terkini dari para praktisi, peneliti, akademisi dan umum di bidang sistem informasi dan teknologi dalam artian luas.
Arjuna Subject : Ilmu Komputer (semua kategori) - Aplikasi Ilmu Komputer
Articles 471 Documents
 37   38   39   40   41 
Analisis Query MySQL pada Sistem Akademik Nadia Syafitri; Afrio Irwando; Juma Riah
Prosiding SISFOTEK Vol 9 No 1 (2025): SISFOTEK IX 2025
Publisher : Ikatan Ahli Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

This study discusses the analysis of MySQL query optimization in academic information systems to improve database performance in supporting campus operational activities. The research scope includes identifying query performance issues in MySQL-based academic systems, applying various optimization techniques, and evaluating their impact on execution speed and resource efficiency. The main objective is to design effective and practical optimization strategies to reduce query response time and increase system throughput. The research employed an experimental quantitative method involving: (1) building a test environment that simulates a real academic system, (2) applying optimization techniques such as indexing, query rewriting, table partitioning, and MySQL parameter tuning, and (3) measuring performance using tools like EXPLAIN, mysqlslap, and sysbench. The dataset consisted of large synthetic data to represent real workloads. The results show that a combination of proper indexing, query rewriting based on execution plan analysis, and InnoDB parameter tuning significantly accelerates query execution time and reduces I/O load by more than 50% compared to the baseline configuration. The study concludes that applying appropriate MySQL query optimization techniques can significantly enhance academic system performance without requiring major architectural changes, providing practical guidance for developers and database administrators.
Analisis Sentimen Ulasan Pengguna Aplikasi Grab di Google Play Store Menggunakan Pendekatan Machine Learning dan Deep Learning Muhammad Azzukhruf; Firman Hidayat; Muhammad Haikal; Pratama Oktavianus
Prosiding SISFOTEK Vol 9 No 1 (2025): SISFOTEK IX 2025
Publisher : Ikatan Ahli Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

This study presents a sentiment analysis of user reviews for the Grab application on Google Play Store using both machine learning and deep learning approaches. The objective is to compare the performance of four algorithms—Random Forest, XGBoost, BiLSTM, and IndoBERT—in classifying positive, negative, and neutral sentiments in Indonesian-language texts. The dataset consists of 2,000 user reviews collected through web scraping, followed by preprocessing steps such as case folding, stopword removal, and tokenization. Feature representation was conducted using TF-IDF for machine learning models and word embeddings for deep learning models. The experimental results using 5-fold cross-validation show that IndoBERT achieved the highest accuracy of 91%, followed by Random Forest (88%), XGBoost (88%), and BiLSTM (84%). These results indicate that IndoBERT demonstrates superior capability in capturing the semantic context of Indonesian text, making it the most effective model for sentiment analysis of mobile application reviews written in the Indonesian language.
Analitik Sampah: Eksplorasi Proyeksi Pengelolaan Sampah Kota Batam Menggunakan Pemrograman R Gita Prajati; Suryo Widiantoro; Akhmad Rezki Purnajaya
Prosiding SISFOTEK Vol 9 No 1 (2025): SISFOTEK IX 2025
Publisher : Ikatan Ahli Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

The increasing amount of waste requires a better waste management plan. Batam is one of the cities in Indonesia with a high population and economic growth rate. Batam will need better waste management planning in the future. This study aims to project waste generation in Batam City. The study will be divided into three stages, namely secondary data collection, correlation analysis, and waste generation projection calculations. Secondary data collection will be carried out by collecting data from relevant agencies. Waste generation projections are made based on sociodemographic and socioeconomic factors using R programming. The results show that there are four variables with negative values, namely population, GDP, length of schooling, and literacy rate. Meanwhile, the variables of population density and economic growth rate have positive values. Waste generation projections were made using the variables of literacy rate, length of schooling, population size, and population density. As a result, waste generation in 2030 is projected to decrease to 0.592 kg/person/day.
Studi Komparatif YOLOv8 dan Vision Transformer dalam Deteksi Kendaraan Ekstrem Nurul Jamila; Angga Saputra; Siti Nikmat; Hifni Khakim
Prosiding SISFOTEK Vol 9 No 1 (2025): SISFOTEK IX 2025
Publisher : Ikatan Ahli Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

The core challenge in object detection for autonomous systems lies in maintaining accuracy across extreme object scales, particularly for small, distant targets. This study conducts a quantitative performance comparison between two distinct deep learning architectures: the CNN-based YOLOv8-m and the Vision Transformer (ViT)-based YOLOS. Both models were implemented and evaluated on a custom vehicle detection dataset. YOLOv8-m was trained from scratch, while YOLOS was evaluated using a proxy precision method on a pre-trained model to gauge its inherent capability in contextual reasoning. The results, analyzed using Mean Average Precision (mAP) categorized by object scale (mAPS,mAPM,mAPL), reveal a significant architectural trade-off. YOLOv8 demonstrated superior overall performance and excelled in mAPL (Large objects), affirming the strength of CNNs in local feature extraction. Conversely, YOLOS showed higher precision for mAPS (Small objects), suggesting that the global attention mechanism of ViT is more effective for long-range surveillance where objects are scarce in pixels. This research provides evidence-based guidance for selecting the optimal detection architecture based on the target object scale and application scenario.
Pengembangan Aplikasi Smart Coffee Roaster berbasis IoT untuk Pengendalian dan Monitoring Proses Penyangraian Kopi Aris Munandar; Oka Mahendra; Jony Winaryo Wibowo
Prosiding SISFOTEK Vol 9 No 1 (2025): SISFOTEK IX 2025
Publisher : Ikatan Ahli Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

The coffee roasting process plays a crucial role in determining flavor quality; therefore, a system that ensures consistency and easy replication of roasting profiles is required. This study developed a smartphone-based Smart Coffee Roaster integrated with an ESP32 microcontroller to support manual and automatic roasting control and monitoring. The system was designed to record and store roasting profiles, synchronize parameters with the ESP32 device, and display temperature and roasting stages in real time. The hardware was designed using relay modules and an ESP32 microcontroller, while the software was developed using Kodular and Arduino IDE. The system was tested using black-box methods and successfully executed all key functions, including profile selection, actuator control, and real-time visualization. The application simplified the monitoring and control of the roasting process and provided structured profile data to maintain coffee quality consistency and support further analysis based on artificial intelligence
Rancangan Buku Kas Digital Berbasis Web Studi Kasus: PBSS DPC Kota Batam Yusuf Harianto Sihombing; Mohd Iqbal; Rezi Elsya Putra
Prosiding SISFOTEK Vol 9 No 1 (2025): SISFOTEK IX 2025
Publisher : Ikatan Ahli Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Effective and transparent financial management is essential for the sustainability and accountability of community organizations. However, many organizations still rely on manual financial recording systems that are time-consuming and prone to errors. This study aims to develop a web-based digital cash book system to support financial management in community organizations, using BORSAK Batam City as a case study. The System Development Life Cycle (SDLC) method was applied, with data collected through interviews, observations, system testing, and questionnaires involving eight organization administrators. The system adopts a client–server architecture with a relational database and features transaction recording, real-time balance calculation, automated financial reports, data search, and audit trails. Testing results indicate a 67% increase in transaction recording efficiency and a 96% improvement in report generation time, while manual calculation errors were completely eliminated. Usability evaluation using the System Usability Scale (SUS) yielded a score of 84, classified as excellent. This study demonstrates that a web-based digital cash book system effectively enhances efficiency, accuracy, transparency, and accountability in community organization financial management.
Transformasi Kebijakan Pidana Siber Menuju Keamanan dan Keadilan Digital Fatri Sagita; Ardiansyah; Noercholis Rafid. A
Prosiding SISFOTEK Vol 9 No 1 (2025): SISFOTEK IX 2025
Publisher : Ikatan Ahli Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

This study examines the effectiveness of Indonesia’s criminal law in addressing cybersecurity and personal data protection amid the rise of artificial intelligence (AI). Using a normative juridical method with statutory and conceptual approaches, the analysis examines the Electronic Information and Transactions Law (Law No. 11 of 2008) and the Personal Data Protection Law (Law No. 27 of 2022), supported by secondary data from legislation, scholarly works, and official reports. The findings show that the criminal law framework remains fragmented, reactive, and unprepared for AI-driven cyber offenses. Overlapping institutional authority, the absence of an independent supervisory body, and limited digital forensic capacity undermine enforcement and legal certainty. Normatively, the study concludes that reforming Indonesia’s cyber penal policy is essential to extend criminal liability to algorithmic offenses, establish an independent supervisory authority, and integrate national digital forensic systems. Such reforms align with the principle of criminal law as ultima ratio, ensuring justice, security, and protection of citizens’ digital rights.
Implementasi Model CNN Untuk Klasifikasi Kanker Paru dan Usus Berbasis Citra Histopatologis Nisa Dienwati Nuris; Kukun Kurniawan; Muhammad Rizky Zulkarnaen; Rian Muhamad Yanuari Alfarisi
Prosiding SISFOTEK Vol 9 No 1 (2025): SISFOTEK IX 2025
Publisher : Ikatan Ahli Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Cancer diagnosis from histopathological images is a crucial but complex task that can be improved through artificial intelligence. This study aims to design and evaluate a deep learning model for the automatic classification of five classes of histopathological networks of lung and colon cancer. The methodology used is to train and compare two neural network architectures, namely a custom Convolutional Neural Network (CNN) and a custom Recurrent Neural Network (RNN), on a balanced public dataset consisting of 25,000 images. The dataset was divided into training data (80%), validation data (10%), and testing data (10%) to ensure objective evaluation. The experimental results showed that the CNN model was significantly superior, achieving an accuracy of 97.52% on the test data, compared to the RNN, which only achieved 95.12%. Further analysis of the CNN model revealed very high classification performance across most classes, with an average F1 score of 98%, although it was found to have some difficulty distinguishing between two morphologically similar subtypes of lung cancer. It is concluded that the specifically designed CNN architecture is a highly effective and reliable approach for histopathological image classification, with strong implications as a potential diagnostic tool to accelerate and improve accuracy in clinical pathology practice.
Analisis Efektivitas Penggunaan QRIS terhadap Sistem Pembayaran Digital Mahasiswa dengan Business Intelligence Hikmatun Hasana; Moch Luthfi Rachman; Shabrina Thufailah; Vannita Citra Kirana
Prosiding SISFOTEK Vol 9 No 1 (2025): SISFOTEK IX 2025
Publisher : Ikatan Ahli Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

This study aims to analyze the effectiveness of using the Quick Response Code Indonesian Standard (QRIS) as a digital payment system among university students through a Business Intelligence (BI) approach. The research employed a qualitative method with a single case study design within a campus environment, involving students, campus merchants, and institutional administrators. The findings reveal that perceived ease of use and perceived usefulness are the primary factors influencing students’ intention and intensity of using QRIS, while trust and security determine continued usage. Challenges identified include low digital financial literacy, limited internet infrastructure, and the persistence of cash transaction habits. The implementation of BI supports data-driven decision-making by identifying transaction patterns, failure rates, and user segmentation. This study highlights the importance of digital literacy enhancement, infrastructure support, and multi-stakeholder collaboration to improve the effectiveness of digital payment systems in higher education settings.
Evaluasi Pembelajaran AR Sejarah Berbasis SUS, UEQ, TAM Rudi Kurniawan; Dadang Sudrajat; Kaslani; Gifthera Dwilestari; Sandy Eka Permana
Prosiding SISFOTEK Vol 9 No 1 (2025): SISFOTEK IX 2025
Publisher : Ikatan Ahli Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

History education in secondary schools still faces challenges in presenting material that attracts the digital generation’s attention. The Bandung Lautan Api event, a topic rich in local and national values, is often taught using conventional methods that limit student engagement and motivation. This study evaluates the feasibility of Augmented Reality (AR)-based learning media to enhance students’ historical literacy on the Bandung Lautan Api topic. A quantitative approach was applied using three integrated evaluation models: the System Usability Scale (SUS), User Experience Questionnaire (UEQ), and Technology Acceptance Model (TAM), involving 100 respondents comprising high school teachers and students. The results indicate that the AR media demonstrates excellent usability (SUS = 87.69), a highly positive user experience across all UEQ dimensions (highest attractiveness = 2.12), and strong technology acceptance (PU = 5.87; PEOU = 5.69; BI = 6.18). Both teachers and students shared consistent perceptions. These findings confirm that the AR media is feasible and capable of creating immersive and interactive learning experiences. Theoretically, this research enriches AR-based learning evaluation literature, while practically, it provides a ready-to-adopt model for integrating AR into history education.

Page 39 of 48 | Total Record : 471

 37   38   39   40   41 

Filter by Year

2017 2025


Reset
Filter By Issues
All Issue Vol 9 No 1 (2025): SISFOTEK IX 2025 Vol 8 No 1 (2024): SISFOTEK VIII 2024 Vol 7 No 1 (2023): SISFOTEK VII 2023 Vol 5 No 1 (2021): SISFOTEK V 2021 Vol 4 No 1 (2020): Vol 4 No 1 (2020): SISFOTEK 2020 Vol 3 No 1 (2019): SISFOTEK 2019 Vol 2 No 1 (2018): SISFOTEK 2018 Vol 1 No 1 (2017): SISFOTEK 2017