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Informatik : Jurnal Ilmu Komputer
Published by Universitas Pembangunan Nasional Veteran Jakarta
ISSN : 02164221     EISSN : 2655139X     DOI : -
Core Subject : Science,
Computer Science & IT
Informatik menerima artikel ilmiah dengan area penelitian pada area Internet Business & Application, Networking & Cyber Security, Statistics & Computation, Elearning & Multimedia, Robotics & Intelligene.
Arjuna Subject : -
Articles 192 Documents
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Analisis Komparasi Model Deep Learning CNN dengan VGG16 dalam Klasifikasi Jenis Bunga Rumui, Nelson; Mualo, Ardhyansyah; Rahayaan, Jacob; Batjo, Lourdes; Mokansi, Misael
Informatik : Jurnal Ilmu Komputer Vol 21 No 1 (2025): April 2025
Publisher : Fakultas Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52958/iftk.v21i1.11105

Abstract

Klasifikasi citra bunga merupakan tantangan penting dalam visi komputer karena citra bunga memiliki tingkat variasi yang tinggi dalam hal bentuk, warna, latar belakang, dan sudut pengambilan gambar, yang sering kali menyulitkan proses klasifikasi secara akurat. Permasalahan ini mendorong dilakukannya penelitian untuk mengembangkan dan membandingkan efektivitas dua pendekatan deep learning, yaitu arsitektur Convolutional Neural Network (CNN) yang dibangun dari awal dan model VGG16 pre-trained yang diterapkan melalui metode transfer learning. Tujuan dari penelitian ini adalah untuk mengevaluasi kinerja kedua model dalam mengklasifikasikan lima jenis bunga daisy, dandelion, rose, sunflower, dan tulip berdasarkan akurasi, efisiensi pelatihan, dan kemampuan generalisasi. Dataset yang digunakan bersifat open-source dan diperoleh dari platform Kaggle, kemudian dibagi menjadi data pelatihan dan pengujian. Hasil eksperimen menunjukkan bahwa model CNN standar hanya mencapai akurasi sebesar 48%, sementara model berbasis VGG16 mencapai akurasi hingga 90%. Temuan ini menegaskan bahwa transfer learning dengan VGG16 merupakan pendekatan yang lebih unggul dan efektif untuk tugas klasifikasi citra bunga, terutama dalam skenario yang menuntut akurasi tinggi.  Penelitian ini memberikan wawasan penting bagi pengembangan sistem klasifikasi visual berbasis deep learning.
Implementasi Fuzzy Logic pada Sistem Robotik Ball Balancing Table dengan Konfigurasi Ball Joint untuk Stabilitas Dinamis Khoirunnisa, Hilda; Suryatini, Fitria; Pancono, Suharyadi; Al Ghafara, Muhamad; Ramdani, Cepi
Informatik : Jurnal Ilmu Komputer Vol 21 No 1 (2025): April 2025
Publisher : Fakultas Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52958/iftk.v21i1.11168

Abstract

Penelitian ini bertujuan untuk menerapkan Fuzzy Logic Controller (FLC) pada sistem Ball Balancing Table (BBT) dengan konfigurasi struktur mekanik Ball Joint untuk stabilitas dinamis. Sistem ini dirancang untuk dapat menempatkan bola pada posisi tertentu. Posisi bola dideteksi secara real-time menggunakan panel touchscreen resistif dan sinyal posisi diproses oleh kontroler fuzzy pada NI myRIO, yang kemudian mengendalikan aktuator motor servo untuk menyesuaikan kemiringan permukaan meja. Hasil pengujian menunjukkan bahwa sistem mampu menempatkan bola pada posisi target dengan tingkat akurasi yang baik sebesar 93.63% untuk sumbu X dan 90.41% untuk sumbu Y. Rerata Kesalahan posisi bola pada sumbu X tercatat sebesar 17.33 mm sedangkan pada sumbu Y sebesar 14.55 mm. Untuk waktu respons penempatan bola terhadap titik target, hasil pengujian mencatat waktu tercepat 10.8 detik dan waktu terlama 16.82 detik. Hasil ini menunjukkan bahwa implementasi fuzzy logic dan struktur mekanik Ball Joint menghasilkan sistem kendali yang cukup akurat dan responsif.
Sistem Informasi Hukum dengan Perizinan Perumahan untuk Proses Efisiensi Administrasi: Sistem Informasi Hukum dengan Perizinan Perumahan untuk Proses Efisiensi Administrasi SAYUTI, Akhmad; Krisna, Robi; Efniar; Triana, Dora Indah
Informatik : Jurnal Ilmu Komputer Vol 21 No 3 (2025): Desember 2025
Publisher : Fakultas Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52958/iftk.v21i3.10792

Abstract

The housing permit administration process often encounters challenges such as bureaucratic complexity, long processing times, and poor information integration between systems. These issues create inefficiency, data overlap, and limited transparency. To address this, this study aims to integrate legal information systems with the housing permit process through the development of a web-based platform. The proposed system synchronizes legal data related to housing regulations with administrative mechanisms, enabling faster and more reliable services. The research applies the Waterfall method, consisting of needs analysis, system design, implementation, testing, and maintenance. The system is designed with key features, including online permit applications, automatic validation of legal documents, real-time application tracking, and digital document archiving. These functions provide applicants and agencies with better access to information, while ensuring that legal and administrative aspects remain aligned with regulatory provisions. Case study implementation demonstrates that system integration can reduce processing time, minimize administrative errors, and accelerate decision-making. Additionally, the platform enhances transparency by allowing applicants to monitor their application status directly, thereby fostering accountability in public administration. The results highlight that digital transformation in housing permit services not only improves efficiency but also strengthens legal certainty and administrative order. This approach contributes significantly to optimizing governance in regional development and can serve as a model for other digital permit systems within the government sector. Ultimately, the integration of technology and legal frameworks creates a more efficient, transparent, and accountable housing permit process.
Evaluasi Kualitas Layanan dalam Load Balancing NGINX : Studi Perbandingan Algoritma Round Robin dan Least Connection Ikramsyah, Muhammad Aldy; Seta, Henki Bayu; Isnainiyah, Ika Nurlaili; Theresiawati, Theresiawati
Informatik : Jurnal Ilmu Komputer Vol 21 No 3 (2025): Desember 2025
Publisher : Fakultas Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52958/iftk.v21i3.10796

Abstract

This study evaluates the Quality of Service (QoS) of the Round-Robin and Least Connection algorithms in load balancing with NGINX. Round Robin outperformed and was consistent across most of the evaluated parameters, including throughput, latency, jitter, and packet loss. Its simplicity stems from the repeated distribution of requests without monitoring server connections, making it ideal for homogeneous traffic and consistent server specifications. However, its performance is poor in dynamic traffic or heterogeneous server architectures. In contrast, Least Connection is more advanced in accommodating dynamic traffic and heterogeneous server environments by allocating load in real-time based on active server connections. Nevertheless, Least Connection showed instability in various tests, especially at high thread counts, where anomalies such as substantial value spikes were recorded. This indicates that it is not suitable for scenarios involving uniform traffic and server specifications. Least Connection is more suitable for complex networks with dynamic traffic and varying server specifications, while Round Robin is recommended for stable workload environments because it provides consistency and simplicity. Round Robin demonstrated superior overall performance, while Least Connection excelled in adaptability, highlighting the need to align algorithm selection with traffic characteristics and server infrastructure. To improve the effectiveness of load balancing strategies, future research should investigate dynamic traffic, higher loads, and diverse environments.
Integrasi Convolutional Block Attention Module ke dalam CNN untuk Meningkatkan Deteksi Malaria pada Citra Sel Darah Mikroskopis Saputro, Pujo Hari; Salassa, Norris Elden; Payuk, Fajar Salinding Buntu
Informatik : Jurnal Ilmu Komputer Vol 21 No 3 (2025): Desember 2025
Publisher : Fakultas Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52958/iftk.v21i3.11106

Abstract

Malaria is a life-threatening disease caused by Plasmodium parasites and transmitted through the bite of infected mosquitoes. Accurate and early detection is essential for effective treatment and control. In this study, we propose an enhanced deep learning approach using a Convolutional Neural Network (CNN) optimized with a Convolutional Block Attention Module (CBAM) to classify red blood cell images as malaria-infected or uninfected. The CBAM mechanism enables the model to focus more effectively on the most informative spatial and channel features, thereby improving its ability to detect subtle patterns in microscopic blood smear images. We compare the performance of the CBAM-optimized CNN against a baseline CNN using accuracy, precision, recall, and F1-score metrics. Experimental results show that integrating CBAM significantly improves classification performance, achieving higher detection accuracy and greater robustness against visual noise and variations. This study highlights the effectiveness of attention-based optimization in medical image classification tasks, particularly in resource-limited settings where reliable and automated diagnosis is highly needed.
Perancangan Sistem Penyewaan Sepeda Listrik Berbasis Mobile dengan Pendekatan UML Niqotaini, Zatin; Vernanda, Dwi; Seta, Henki Bayu; Andriyani, Yanti
Informatik : Jurnal Ilmu Komputer Vol 21 No 3 (2025): Desember 2025
Publisher : Fakultas Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52958/iftk.v21i3.11815

Abstract

Innovation in transportation, such as online transportation booking applications and electric vehicles are phenomena caused by the development of information technology. But, the likes of traffic safety and complex transportation system integration are some obstacles that still need to be addressed. This research aims to design a Mobile-Based Electric Bicycle Rental System using Unified Modeling Language (UML) in order to increase efficiency and convenience. A Qualitative Research Method is used to analyze the Business Process. The System Analysis stage involves identification, determining requirements, and systematic study to ensure design compliance or suitability. The System Designing stage covers creating structured UML Model, Database Design, determining Table Structure, and developing a User Interface. This study’s result presents a comprehensive design of the Electric Bicycle Rental System, reflected by well-structured UML Diagrams, efficient Database Design and an intuitive User Interface. This System is expected to be an innovative solution to conquer efficiency and convenience hurdles in renting an Electric Bicycle.
Perancangan Sistem Informasi Manajemen Kost Berbasis Website Pada Kost Bima Dengan Metode Prototype Zendrato, Mei Albert; Heksaputra, Dadang; Harahap, Avrillaila Akbar; Wicaksono, Yanuar
Informatik : Jurnal Ilmu Komputer Vol 21 No 3 (2025): Desember 2025
Publisher : Fakultas Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52958/iftk.v21i3.11877

Abstract

Advances in information technology have encouraged various sectors, including boarding house management, to utilize digital systems. Kost Bima in Tamantirto Village, Bantul, faces challenges in recording tenants, verifying payments, and handling complaints, which are still done manually, thus being time-consuming and prone to irregularities. This study aims to design a website-based boarding house management information system as a solution. The system is designed for three users: admin (boarding house owner), tenants, and prospective tenants. The prototype method was used so that development involved user input at every stage, and in the process, two iterations were carried out to refine the system. The result is a system with features for room reservations, lease extensions, payments, complaint management, and tenant data. Black-box testing showed that all features worked well without bugs. In addition, User Acceptance Testing (UAT) was conducted with five assessment aspects: Learnability, Efficiency, Memorability, Errors, and Satisfaction. The UAT results showed an excellent score of 87.8%, indicating that the system is feasible for use.
Audit Sistem Informasi Menggunakan Framework COBIT5 Pada Sistem informasi Akademik Universitas Alma Ata Darmawan, Rachmat; Rochmadi, Tri; Heksaputra, Dadang; Wicaksono, Yanuar
Informatik : Jurnal Ilmu Komputer Vol 21 No 3 (2025): Desember 2025
Publisher : Fakultas Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52958/iftk.v21i3.11974

Abstract

The rapid development of information technology encourages universities to provide fast, effective, and integrated academic services. Alma Ata University has implemented an Academic Information System (SIAKAD) which functions as a service support in the learning process. However, this system is still faced with several obstacles, including constrained access speed when filling in attendance and the occurrence of recurring service interruptions. This research aims to evaluate the capability level of SIAKAD and develop recommendations for improvement based on the results of the audit conducted with the COBIT 5 framework, especially in the Deliver, Service, and Support (DSS) domain. The methodology applied is mixed methods, which combines qualitative and quantitative approaches. The research findings show that the capability of each subdomain is measured at level 4 (Predictable Process), while the desired target is level 5 in each DSS subdomain. Thus, it can be concluded that SIAKAD of Alma Ata University has been operating well and consistently, but requires improvement steps to achieve the expected level 5.
Towards Interpretable Intrusion Detection: A Double-Layer GRU with Feature Fusion Explained by SHAP and LIME Wijaya, Mochamad Rozikul; M. Hanafi
Informatik : Jurnal Ilmu Komputer Vol 21 No 3 (2025): Desember 2025
Publisher : Fakultas Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52958/iftk.v21i3.12187

Abstract

Computer network security has become increasingly important with the growing complexity of cyberattacks. Deep learning-based Intrusion Detection Systems (IDS) represent a potential solution due to their capability to capture sequential patterns in network traffic. This study proposes a Double-Layer GRU-based IDS with Feature Fusion to enhance the representation of both numerical and categorical data in the NSL-KDD dataset. The training process employs systematic preprocessing techniques, including normalization and one-hot encoding. Experimental results demonstrate high accuracy and generalization with stable performance on both training and testing data, as well as competitive macro F1-scores for multi-class attack detection. Furthermore, interpretability aspects are explored through Explainable Artificial Intelligence (XAI) methods using SHAP and LIME. SHAP provides global insights into the contributions of important features, while LIME explains the influence of features at the local level for individual predictions. The integration of both methods not only enhances transparency and trust in the IDS but also offers deeper insights into dominant attributes in detecting attack patterns. Accordingly, this study contributes to the development of IDS that are accurate, interpretable, and applicable to modern network security.
Application of Rapid Application Development Method in WEB-Based Social Assistance Data Collection System in Lombu Village Lende, Erniati; Neno, Friden Elefri; Ate, Paulus Mikku
Informatik : Jurnal Ilmu Komputer Vol 21 No 3 (2025): Desember 2025
Publisher : Fakultas Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52958/iftk.v21i3.12260

Abstract

The process of collecting social assistance data in Lombu Village has been done manually, which has led to various problems such as duplicate data, delays in reporting, and inaccuracy in targeting recipients. To overcome these problems, this study aims to develop a web-based social assistance data collection information system that can improve efficiency, accuracy, and transparency in data management. The system development method used is Rapid Application Development (RAD), which emphasizes speed in development and direct user involvement in the system design and evaluation process. The research stages include needs identification, system design with users, prototype development, system testing, and feedback-based evaluation. Data was collected through interviews, observations, and documentation of the ongoing data collection process. The result of this research is a web-based system that is capable of storing, updating, and displaying beneficiary data in a structured manner and can be accessed by village officials with a simple and easy-to-use interface. System trials show that the system can facilitate data management and accelerate the social assistance reporting process at the village level.

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