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Sumatera utara
INDONESIA
ALGORITMA : JURNAL ILMU KOMPUTER DAN INFORMATIKA
Published by Universitas Islam Negeri Sumatera Utara
ISSN : -     EISSN : 25986341     DOI : 10.30829/algoritma
Core Subject : Science,
Computer Science & IT
Arjuna Subject : -
Articles 10 Documents
 1 
Search results for , issue "Vol 9, No 2 (2025): November 2025" : 10 Documents clear
Studi Pengelompokan Multimetode Provinsi di Sumatera Utara Menggunakan Pendekatan PCA dan K-Means Lubis, Fitra Hidayat; Ashar, Suthan Farras; M.S, OK Mhd Fahri Al-Faruqy; Amari, Ahmad Boby
Algoritma: Jurnal Ilmu Komputer dan Informatika Vol 9, No 2 (2025): November 2025
Publisher : Universitas Islam Negeri Sumatera Utara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30829/algoritma.v9i2.25017

Abstract

This study aims to classify regions in North Sumatra based on a set of social and economic indicators by applying a multi-method clustering approach. Principal Component Analysis (PCA) is employed to reduce data dimensionality and identify the most influential variables, while the K-Means algorithm is used to form clusters based on similarity of characteristics. The results indicate that the combination of PCA and K-Means can cluster provinces or regions more efficiently and interpretably. The resulting clusters reflect patterns of similarity among regions in terms of social and economic development, thus providing a basis for formulating more targeted regional development policies. These findings demonstrate that a multi-method approach can yield more comprehensive results in spatial data clustering.Keywords: Clustering, Principal Component Analysis (PCA), K-Means, multi-method, North Sumatra.
Sistem Pendukung Keputusan Penilaian Kesiapan UMKM Go-Digital Menggunakan Metode EDAS Berbasis Web Wulansari, Niki; Nasriyah, Syaripah; Nurhayati, Nurhayati; Dwi Lestari, Yuyun
Algoritma: Jurnal Ilmu Komputer dan Informatika Vol 9, No 2 (2025): November 2025
Publisher : Universitas Islam Negeri Sumatera Utara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30829/algoritma.v9i2.26834

Abstract

Low levels of digital readiness and information technology literacy prevent many MSME from optimally utilizing digital platforms to support their business processes. This presents a significant challenge for accelerating digital transformation, particularly in Medan. This study aims to develop a web-based decision support system using the EDAS method to assess the level of readiness of MSME to go digital. This study employed a descriptive quantitative approach, with a sample of 15 MSME selected through a Likert-scale questionnaire. The data obtained were analyzed using the EDAS method to determine digital readiness scores based on established criteria and sub-criteria. The results showed that the system was able to provide a structured and objective assessment, with alternative A1 receiving the highest rating (0.5) and A9 the lowest (0.189). This study confirms that some MSME are still in the underprepared category and require training, mentoring, and digital capacity building support. The developed system can be a tool for the government and supporting institutions in mapping the level of digital readiness of MSME and developing more targeted strategies for accelerating digital transformation. Keywords: DSS, MSME, EDAS
Pengembangan Chatbot Rule-Based untuk Rekomendasi Wisata Berbasis Content-Based Filtering Bengi, Mahara; Gunawan, Chica Rizka
Algoritma: Jurnal Ilmu Komputer dan Informatika Vol 9, No 2 (2025): November 2025
Publisher : Universitas Islam Negeri Sumatera Utara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30829/algoritma.v9i2.27904

Abstract

Tourism is a strategic sector in supporting regional economic growth, including in Takengon City, which has high potential in natural, cultural, and culinary tourism. However, limited access to structured and relevant tourism information often becomes an obstacle for tourists in selecting destinations that match their preferences. This study aims to develop a tourism destination recommendation chatbot based on content-based filtering integrated with the Telegram platform. The methods employed include text data preprocessing, vectorization using Term Frequency-Inverse Document Frequency (TF-IDF), and similarity measurement using cosine similarity. The chatbot is designed using a rule-based approach to receive user preference inputs in the form of keywords and generate relevant tourism destination recommendations in real time. The implementation and testing results indicate that the system is able to provide tourism recommendations that align with user preferences and respond effectively to various input variations. Therefore, the developed chatbot system can serve as a practical solution for delivering tourism information and recommendations in Takengon City and has the potential to be applied to other regions with similar characteristics. Keywords: Chatbot, Recommendation System, Content-Based Filtering, TF-IDF, Cosine Similarity.
Analisis Tingkat Kematangan Buah Jeruk Menggunakan Chain Code Dan KNN (K-Nearest Neighbors) Berbasis Website Sitorus, Dicky Andreas; Aulia, Rachmat
Algoritma: Jurnal Ilmu Komputer dan Informatika Vol 9, No 2 (2025): November 2025
Publisher : Universitas Islam Negeri Sumatera Utara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30829/algoritma.v9i2.25898

Abstract

This research aims to develop a web-based orange ripeness classification system using the K-Nearest Neighbor (KNN) method, leveraging morphological and color features as the main parameters. The image processing workflow begins with converting RGB images into the HSV color space, followed by object segmentation using the thresholding method, and feature extraction including chain code, area, and shape factor. The dataset consists of 50 orange images as training data and 20 orange images as test data. The evaluation was conducted in two scenarios: single testing and batch testing. The single testing on 5 test images achieved a perfect classification accuracy of 100%. In batch testing, the system achieved an accuracy of 0.90. These results indicate that the system is capable of effectively classifying orange ripeness, with a very low rate of false-positive predictions. The application is implemented as a web-based platform, making it easily accessible, and is expected to serve as a practical tool for sorting and grading oranges based on their ripeness levels. Keywords: Orange Classification, K-Nearest Neighbor, Feature Extraction, Image Processing, Web Application.
Algoritma Pengembangan Sistem Informasi Kepegawaian Menggunakan Metode Prototype Pradipta, Rahman; Bahri, Rahmad
Algoritma: Jurnal Ilmu Komputer dan Informatika Vol 9, No 2 (2025): November 2025
Publisher : Universitas Islam Negeri Sumatera Utara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30829/algoritma.v9i2.27951

Abstract

Digital transformation in human resources (HR) functions encourages organizations to replace manual administration with web-based HR information systems to improve data integration, security, and decision-making speed. However, implementing HR systems that still rely on hardcopy files or spreadsheets faces various challenges, such as the risk of data loss, inconsistent updates, weak access control, and delays in HR services. From a software engineering perspective, the prototype method is considered effective in addressing requirement uncertainties because it allows user involvement through continuous iteration and feedback. This study aims to (1) design and implement an HR information system development algorithm using the prototype method and (2) quantitatively evaluate the impact of prototyping iterations on system quality, including usability, security, and flexibility, as well as its impact on the effectiveness of HR processes. The study used a quantitative approach with descriptive analysis based on a Likert scale to measure users' perceptions of system quality. The results showed that prototyping iterations positively contributed to improving system quality and supported the effectiveness of HR services, particularly in accelerating administrative processes and reducing operational errors. These findings reinforce the role of the prototype method as a relevant development approach for web-based personnel information systems. Keywords: Personnel Information System, Prototype Method, System Quality, Human Resource Effectiveness, Software Engineering.
Penerapan YOLO dan OCR untuk Deteksi dan Klasifikasi Plat Nomor Kendaraan di Universitas Malikussaleh Rifqi, Taruna Heza; Auliansyah, Ziky; Ratu Nazirah, Nathania
Algoritma: Jurnal Ilmu Komputer dan Informatika Vol 9, No 2 (2025): November 2025
Publisher : Universitas Islam Negeri Sumatera Utara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30829/algoritma.v9i2.25636

Abstract

Automatic vehicle license plate recognition plays a vital role in advancing intelligent transportation systems, especially in enhancing traffic monitoring, parking automation, and security management. This study explores the implementation of the You Only Look Once (YOLO) algorithm and Optical Character Recognition (OCR) for detecting and classifying vehicle license plates based on their regional codes at Malikussaleh University. YOLO is used for real-time detection of license plate regions, while EasyOCR extracts alphanumeric characters from preprocessed plate images (grayscale, sharpening, thresholding). The OCR output undergoes character correction and format validation using regular expressions. The recognized codes are then mapped to regional origins based on official Indonesian license plate regulations. Experimental results show that the system effectively detects and classifies license plates with high accuracy, even under diverse image conditions. Beyond enhancing vehicle identification efficiency, the system offers potential applications in automated campus surveillance and broader public area monitoring. This research contributes to the development of machine learning-based recognition systems and paves the way for future studies in predictive traffic analytics and smart transportation infrastructure. Keywords: YOLO, OCR, license plate detection, regional classification, vehicle identification
Perencanaan Strategis Sistem Informasi Menggunakan Enterprise Architecture Planning dan Pendekatan SDLC Sasgita, Nabila; Febriani, Widia Putri; Sabila, Wilda Putri; Nurhalizaaaaaaa, Tikooo
Algoritma: Jurnal Ilmu Komputer dan Informatika Vol 9, No 2 (2025): November 2025
Publisher : Universitas Islam Negeri Sumatera Utara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30829/algoritma.v9i2.27989

Abstract

Strategic Information Systems (IS) planning is an essential aspect in supporting organizational objectives through the effective and integrated use of information technology. However, the implementation of IS at the Muaro Jambi Education Office still encounters challenges, including fragmented data management across various work units and the use of non-integrated applications, resulting in suboptimal support for strategic decision-making. This study aims to develop strategic IS planning using the Enterprise Architecture Planning (EAP) method with the System Development Life Cycle (SDLC) approach to align business requirements with data, application, and information technology architectures. The research employed a case study method through interviews, business process observation, and literature review. The EAP stages were applied to design business, data, application, and technology architectures, while the SDLC approach was applied in a limited manner at the analysis and system design stages as a systematic framework supporting the formulation of information system architecture. Supporting analyses included Value Chain modeling, SWOT analysis, and application portfolio mapping using the McFarlan Strategic Grid. The results indicate that information system integration has not been optimally achieved despite the availability of technological infrastructure. This study produces an architectural blueprint and an implementation roadmap as a foundation for integrated and sustainable IS planning. Keywords: Enterprise Architecture, Education Office, Enterprise Architecture Planning, Strategic Planning, Information Systems
Implementasi K-Means Clustering Nilai Ujian Nasional Dalam Peminatan Jurusan Siswa Pada SMAN 1 Gorontalo Utara Rustam, Suhardi; Dunggio, Zufrianto K
Algoritma: Jurnal Ilmu Komputer dan Informatika Vol 9, No 2 (2025): November 2025
Publisher : Universitas Islam Negeri Sumatera Utara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30829/algoritma.v9i2.26172

Abstract

Permasalahan dalam penentuan peminatan jurusan di SMAN 1 Gorontalo Utara yang masih dilakukan secara manual dan hanya mengandalkan keinginan siswa sering kali menyebabkan hasil penempatan jurusan menjadi kurang akurat dan tidak sepenuhnya mencerminkan kemampuan akademik mereka. Untuk mengatasi hal tersebut, penelitian ini bertujuan menerapkan algoritma clustering K-Means sebagai metode pengelompokan yang lebih objektif, terukur, dan dapat dipertanggungjawabkan. Penelitian menggunakan 90 data nilai Ujian Nasional siswa baru tahun ajaran 2019-2020 dengan empat atribut utama, yaitu nilai Bahasa Indonesia, Matematika, Bahasa Inggris, dan IPA. Seluruh proses analisis dilakukan menggunakan perangkat lunak RapidMiner Studio untuk memastikan hasil perhitungan yang konsisten dan akurat. Berdasarkan hasil pengolahan data, terbentuk empat cluster peminatan yang stabil setelah melalui lima kali iterasi, yakni: Cluster 1 (peminatan IPA 2) dengan 24 siswa, Cluster 2 (peminatan IPS 2) dengan 27 siswa, Cluster 3 (peminatan IPS 1) dengan 27 siswa, dan Cluster 4 (peminatan IPA 1) dengan 12 siswa. Temuan ini menunjukkan bahwa metode K-Means mampu memberikan rekomendasi penentuan jurusan secara cepat, tepat, serta sesuai dengan kemampuan akademik siswa, sehingga dapat dijadikan acuan yang lebih efektif bagi pihak sekolah dalam proses penjurusan.
Deteksi Penyakit Mata Menggunakan Algoritma Region Growing Gunawan, Chicha Rizka; Bengi, Mahara; Gunawan, Chichi Rizka; Fadhilla, Cut Alna
Algoritma: Jurnal Ilmu Komputer dan Informatika Vol 9, No 2 (2025): November 2025
Publisher : Universitas Islam Negeri Sumatera Utara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30829/algoritma.v9i2.27908

Abstract

Medical image processing is a data manipulation process aimed at producing new images with improved quality. The primary objective of medical image processing is to obtain information, perform screening procedures, and support disease diagnosis, one of which is eye diseases. Nodules, as one of the indications of eye diseases, are generally analyzed visually by physicians. This study develops an algorithm to detect nodules in eye CT scan images based on the morphological characteristics of nodules, which are generally circular in shape. The experimental results show that the nodule area can be calculated based on the number of pixels forming the nodule region. In several image slices, the nodule area cannot be detected due to the condition where the nodule is attached to other parts of the eye. The developed algorithm is capable of detecting nodules in multiple eye CT scan slices and calculating the nodule area in each image slice. Therefore, the proposed nodule detection algorithm is expected to assist physicians in diagnosing eye diseases more accurately and objectively. Keywords: Detection, Region Growing, Eye Disease, Medical Image Processing, Nodule
Sistem Klasifikasi Bentuk Wajah Menggunakan EfficientNet-B4 untuk Rekomendasi Gaya Rambut Berbasis Web Maulana Putra, Dimas; Santoso, Alfareza Kamal; Fadli, Alif; Fatoni, Febrian Ahmad; Novanto, Agung Harri; Nurhasan, Fuad
Algoritma: Jurnal Ilmu Komputer dan Informatika Vol 9, No 2 (2025): November 2025
Publisher : Universitas Islam Negeri Sumatera Utara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30829/algoritma.v9i2.26763

Abstract

The suitability of a hairstyle is largely influenced by the shape of a person's face; however, manual identification can often lack consistency due to the observer's subjectivity. This study developed an automated system designed to classify face shapes using the EfficientNet-B4 model, categorizing them into five types: Heart, Oblong, Oval, Round, and Square. The model was trained on a dataset of 27,066 labeled images, which included 19,926 images for training, 3,512 for validation, and 3,628 for testing. The training process involved a two-phase transfer learning approach: first, training the head of the model, followed by fine-tuning the backbone. To enhance performance and mitigate overfitting, data augmentation, learning rate scheduling, and early stopping techniques were utilized. Evaluation results revealed exceptional performance, achieving a validation accuracy of 96. 10%, a test accuracy of 93. 52%, and a macro-F1 score of 0. 935. The highest errors were found in the Oval and Oblong categories, whereas the Square category demonstrated the most consistency. This system is implemented in a web application utilizing Next. js and Express, where face detection is carried out on the client-side using react-webcam and face-api. js. Additionally, the system provides a hairstyle preview to enhance the user experience. Keywords: EfficientNet-B4, face shape classification, hairstyle recommendation, transfer learning, web application.

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