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All Journal Jurnal Ilmu Komputer dan Sistem Komputer Terapan (JIKSTRA) Teknik: Jurnal Ilmu Teknik dan Informatika Biner : Jurnal Ilmu Komputer, Teknik dan Multimedia
Khodotun Hadawiyah Margolang
Universitas Negeri Medan
Humanities Computer Science & IT Engineering Industrial & Manufacturing Engineering Materials Science & Nanotechnology Transportation

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Analisis Perbandingan Kinerja Binary Search Tree dan AVL Tree dalam Sistem Pencarian Data Mahasiswa Siti Haliza Zamili; Alya Namira; Khodotun Hadawiyah Margolang; Adinda Soleha; Adidtya Perdana
BINER : Jurnal Ilmu Komputer, Teknik dan Multimedia Vol. 3 No. 6 (2026): BINER : Jurnal Ilmu Komputer, Teknik dan Multimedia
Publisher : CV. Shofanah Media Berkah

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Abstract

Information retrieval systems are a crucial part of data management, particularly in academic systems that store a large amount of student data. Search effectiveness is greatly influenced by the format and organization of the data. This study aims to evaluate and compare the performance of two types of tree data structures, namely Binary Search Trees and AVL Trees, in student data retrieval activities. Testing was conducted using numerical datasets reflecting student information with varying amounts of data: 20, 40, 60, 80, and 100. Parameters used in the assessment included tree height and data search duration. The algorithm was implemented using the Python programming language. The test results show that Binary Search Trees tend to have tree heights that increase significantly with increasing data volume due to the absence of a balancing mechanism. Meanwhile, AVL Trees can maintain the balance of their tree structure through a rotation process that makes the tree height more consistent. In addition, search time in AVL Trees also appears faster than Binary Search Trees, especially when the amount of data encountered is larger. Therefore, AVL Trees are considered more efficient and ideal for implementation in student data retrieval systems that require fast and stable searches.
Perbandingan Algoritma Random Forest, K-Nearest Neighbor dan Support Vector Machine Untuk Deteksi Anomali Trafik Jaringan Menggunakan Dataset CICIDS2017 Siti Zamili; Dedy Kiswanto; Khodotun Hadawiyah Margolang
Jurnal Ilmu Komputer dan Sistem Komputer Terapan (JIKSTRA) Vol. 8 No. 2 (2026): Edisi Oktober
Publisher : Universitas Harapan Medan

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Abstract

The increasingly complex development of cyber threats has driven the need for network protection systems capable of detecting intrusions intelligently and automatically. Machine learning-based approaches have been widely adopted as intrusion detection solutions due to their ability to recognize attack patterns without relying on manually defined rules. This study examines the effectiveness of four machine learning algorithms, namely Random Forest, Decision Tree, Stacked LSTM, and AdaBoost, in network traffic classification tasks using the CICIDS2017 dataset as the evaluation benchmark. Before model training, the data was processed through normalization and relevant feature selection stages to ensure optimal data representation. Model performance was measured using four main evaluation metrics, namely accuracy, precision, recall, and F1-score, to obtain a comprehensive assessment of the  classification capability of each algorithm. From the test results, Decision Tree stood out with a precision value reaching 99.87%, recall of 99.59%, and F1-score of 99.32%, indicating excellent per-class classification capability with a very low error rate. On the other hand, Random Forest recorded the highest overall accuracy value of 99.90%, accompanied by a precision of 97.78%, recall of 97.08%, and F1-score of 97.41%, reflecting the model's reliability in consistently maintaining performance across all classes. Both the Stacked LSTM and AdaBoost-based models showed lower performance compared to tree-based approaches in the same testing scenario. Overall, the results of this study confirm that decision tree-based algorithms offer a combination of high accuracy and superior classification stability, making them the right choice for implementing machine learning-based network intrusion detection systems.
Analisis dan Perancangan Sistem Informasi Manajemen Rumah Kos Digital Berbasis Web (SmartKost) Menggunakan Metode Waterfall Siti Haliza Zamili; Zulfahmi Indra; Khodotun Hadawiyah Margolang; Hafizham Mufti Siregar
Teknik: Jurnal Ilmu Teknik dan Informatika Vol. 6 No. 2 (2026): Oktober: Teknik: Jurnal Ilmu Teknik dan Informatika
Publisher : LPPM Sekolah Tinggi Ilmu Ekonomi - Studi Ekonomi Modern

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/teknik.v6i2.1261

Abstract

The management of boarding houses conducted manually often causes problems such as data recording errors, delayed payment recaps, data loss, and lack of information transparency. This study aims to analyze and design a web-based digital boarding house management information system named SmartKost using the Waterfall method. The system was developed using PHP Native, MySQL, HTML, CSS, JavaScript, and Chart.js on a XAMPP local server environment. The Waterfall method was chosen because system requirements were clearly defined from the beginning, enabling structured development through five phases: requirements analysis, system design, implementation, testing, and maintenance. SmartKost supports two user roles, admin and tenant, with features including room management with photo uploads, online booking with admin approval, payment management with proof of transfer upload, financial reporting, and a real-time statistics dashboard. System testing used the Black Box Testing method with 15 functional test scenarios covering authentication, CRUD operations for rooms, tenants, and bills, as well as payment verification. All test scenarios passed successfully, proving the system functions according to specified requirements. SmartKost effectively makes boarding house management faster, more accurate, and more transparent compared to manual systems.
Implementasi Finite State Automata pada Smart Vending MachineBerbasis Pembayaran Digital Khodotun Hadawiyah Margolang; Zulfahmi Indra; Siti Haliza Zamili; Hafizham Mufti Siregar
Teknik: Jurnal Ilmu Teknik dan Informatika Vol. 6 No. 2 (2026): Oktober: Teknik: Jurnal Ilmu Teknik dan Informatika
Publisher : LPPM Sekolah Tinggi Ilmu Ekonomi - Studi Ekonomi Modern

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/teknik.v6i2.1266

Abstract

This research aims to design and implement a Smart Vending Machine based on Finite State Automata (FSA) integrated with a digital payment simulation system called SimPay. The growing use of digital payment technology and automated transaction systems requires a reliable control mechanism to ensure transaction accuracy and consistency. The proposed system applies FSA as the core logic to manage transaction stages, including product selection, order confirmation, QR code generation, payment processing, product dispensing, and transaction completion. The system was developed using the prototyping method and implemented as a web-based application utilizing HTML5, CSS3, JavaScript, QR Code technology, and cloud-based data storage. The developed system consists of three main components: a vending machine interface for users, the SimPay digital wallet simulator for payment processing, and an administrative dashboard for managing products, stock, and transaction data. Functional testing was conducted using the Black Box Testing method to evaluate system performance and state-transition accuracy. The results show that all transaction scenarios and administrative functions operated according to the designed FSA model. The implementation demonstrates that integrating FSA with a digital payment simulation can provide a structured, transparent, and reliable transaction process. The proposed system can serve as a practical model for developing web-based smart vending machines and digital payment applications.
Co-Authors Adidtya Perdana, Adidtya Adinda Soleha Alya Namira Dedy Kiswanto Hafizham Mufti Siregar Siti Haliza Zamili Siti Zamili Zulfahmi Indra, Zulfahmi