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CSRID
Published by Universitas Potensi Utama
ISSN : 20851367     EISSN : 2460870X     DOI : https://doi.org/10.22303/csrid
Core Subject : Science,
Computer Science & IT
CSRID (Computer Science Research and Its Development Journal) is a scientific journal published by LPPM Universitas Potensi Utama in collaboration with professional computer science associations, Indonesian Computer Electronics and Instrumentation Support Society (IndoCEISS) and CORIS (Cooperation Research Inter University).
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 156 Documents
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Classification of Film Genres Based on Synopsis Using Support Vector Machine (SVM) Method with TF-IDF and N-Gram Rita Novita Sari; Dea Alya; Dodyk Fahlome
CSRID (Computer Science Research and Its Development Journal) Vol. 18 No. 2 (2026): Juni 2026
Publisher : LPPM Universitas Potensi Utama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22303/csrid-.18.2.2026.381-394

Abstract

With the wide variety of film genres available, audiences often face difficulties in determining a movie’s genre solely based on its synopsis. Therefore, an automated system is needed to classify movie genres effectively. This study aims to classify movie genres based on film synopses using the Support Vector Machine (SVM) method combined with TF-IDF and N-Gram feature extraction techniques. The dataset used in this research was obtained from Kaggle and consisted of 10,000 movie records with multi-label characteristics, which were subsequently transformed into Single-label data. Four main genres were selected, namely Action, Comedy, Drama, and Horror, resulting in a final dataset of 6,000 records. The research process included data preparation, text preprocessing, TF-IDF feature extraction using unigram and bigram models, data splitting, and model evaluation. All data processing procedures were carried out in Google Colab using the Python programming language. The evaluation results indicate that the SVM model with a linear kernel achieved an accuracy of 83%. The Horror genre demonstrated the best performance, with a precision value of 91%, recall of 92%, and F1-score of 92%. These findings suggest that the combination of TF-IDF, N-Gram, and SVM provides satisfactory results for movie genre classification based on film synopses.
E-Canteen Universitas Al Washliyah Labuhanbatu Berbasis WEB Selamat Subagio; Samsir; Muhammad Rusdi
CSRID (Computer Science Research and Its Development Journal) Vol. 18 No. 2 (2026): Juni 2026
Publisher : LPPM Universitas Potensi Utama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22303/csrid-.18.2.2026.395-408

Abstract

The rapid advancement of information technology has driven significant changes across various sectors, including facility management within higher education institutions. The Universitas Al Washliyah Labuhanbatu canteen—a crucial facility supporting daily campus activities—frequently faces operational challenges. These issues include long customer queues during break times, a lack of transparency in financial record-keeping, and difficulties for canteen owners in monitoring real-time stock levels. To address these problems, this study aimed to design and implement a web-based e-canteen management system. The system was designed to integrate the functional needs of students and lecturers (as buyers), canteen owners (as sellers), and campus administrators. The development process adopted the System Development Life Cycle (SDLC) methodology, encompassing user requirements analysis, database modeling (using ERD and DFD), and coding utilizing HTML, CSS, PHP, and MySQL technologies. Functionality testing demonstrated that the e-canteen application successfully reduces customer waiting times through an online ordering feature, provides clear digital cash flow records for management, and minimizes errors in product inventory tracking. The implementation of this platform is expected to accelerate digital transformation and help realize the "smart campus" concept at Universitas Al Washliyah Labuhanbatu.
Pengembangan Sistem Pendukung Keputusan Pemilihan Siswa Berprestasi Berbasis Multi-Kriteria Menggunakan Metode Simple Additive Weighting (SAW) pada Sekolah Menengah Kejuruan Samsir; Maisarah Ritonga; Muhammad Siddik
CSRID (Computer Science Research and Its Development Journal) Vol. 18 No. 2 (2026): Juni 2026
Publisher : LPPM Universitas Potensi Utama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22303/csrid-.18.2.2026.205-217

Abstract

The selection process of outstanding students in Vocational High Schools (SMK) often suffers from subjectivity and inefficiency due to manual assessment procedures. This study aims to develop a web-based Decision Support System (DSS) using the Simple Additive Weighting (SAW) method to determine outstanding students more objectively. The system integrates three achievement categories—academic, professional, and sports achievements—represented by nine evaluation indicators with different weights according to their importance. The SAW method was applied through decision matrix construction, normalization, weighting, and preference value calculation. The results show that the best alternative obtained a preference value of 6.77 and was recommended as the outstanding student. Black Box testing indicated that all system functions operated successfully with a 100% success rate. Furthermore, the system reduced the selection process time from 40 minutes to 8 minutes, representing an 80% efficiency improvement compared with the manual process. These findings demonstrate that the implementation of the SAW method effectively improves objectivity, transparency, and efficiency in the outstanding student selection process in vocational high schools.
Sistem Pakar Deteksi Penyakit THT Menggunakan Metode SAW Samsir; Muhammad siddik; Azrai Sirait
CSRID (Computer Science Research and Its Development Journal) Vol. 18 No. 2 (2026): Juni 2026
Publisher : LPPM Universitas Potensi Utama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22303/csrid-.18.2.2026.409-425

Abstract

Ear, Nose, and Throat (ENT) disorders are common health issues that require timely intervention from the early stages to prevent complications. However, a shortage of ENT specialists and the unequal distribution of healthcare services hinder optimal consultation and initial diagnosis, particularly in areas with limited access to healthcare. While various studies have developed disease diagnosis systems using inference methods—such as Forward Chaining and Certainty Factor—the application of the Simple Additive Weighting (SAW) method as a Multi-Criteria Decision Making (MCDM) approach to rank potential diseases based on symptom combinations remains relatively limited. This study aims to develop a web-based expert system for the initial diagnosis of ENT disorders by utilizing a knowledge base derived from ENT specialists and implementing the SAW method as a decision-making mechanism to identify the most likely disease (the alternative with the highest preference value). The knowledge base is represented through relationships between symptoms, diseases, symptom weights, and management guidelines. The diagnostic process involves constructing a decision matrix, normalizing values, weighting symptoms, and calculating preference values ​​using the SAW method. Developed using PHP and MySQL, the system provides initial diagnostic recommendations and management advice based on user-selected symptoms. This research contributes by applying the SAW method as a multi-criteria decision-making mechanism within an ENT diagnosis system, thereby making the process of identifying potential diseases more systematic, transparent, and adaptable to changes in the knowledge base
Pengembangan Sistem Informasi Laporan Praktik Kerja Lapangan Mahasiswa Berbasis Web Menggunakan Metode Waterfall di Universitas Alwashliyah Labuhanbatu Abdul Hakim Dalimunthe; Selamat Subagio; Samsir
CSRID (Computer Science Research and Its Development Journal) Vol. 18 No. 2 (2026): Juni 2026
Publisher : LPPM Universitas Potensi Utama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22303/csrid-.18.2.2026.232-244

Abstract

The management of Field Work Practice (PKL) reports at the Faculty of Computer Science, Alwashliyah University (UNIVA) Labuhanbatu, is currently handled manually, leading to various issues such as delayed report submissions, document archiving difficulties, ineffective supervision monitoring, and slow grading processes by supervisors. This research aims to develop a web-based PKL report information system capable of centrally integrating administrative processes—ranging from student data management, placement, and report uploading to supervision monitoring and grading. The system was developed using the Waterfall method, comprising stages for requirements analysis, system design, implementation, testing, and maintenance. It was built using PHP, MySQL, and the Bootstrap framework. System testing employed the Black Box Testing method across 25 scenarios covering user authentication, management of student, lecturer, and industry partner (DU/DI) data, report uploads, the supervision process, and grading. Test results demonstrated that all scenarios executed successfully according to functional requirements, achieving a 100% success rate. Implementing this system improves the efficiency of PKL administration, accelerates information exchange among students, supervisors, and administrators, and results in report archiving that is more structured, well-documented, and accessible compared to the manual process.
Sistem Pendukung Keputusan Pemilihan Pengobatan Tradisional Kardivaskular Dengan Metode SAW Rahmad Aditiya; Samsir; Reagan Surbakti Saragih
CSRID (Computer Science Research and Its Development Journal) Vol. 18 No. 2 (2026): Juni 2026
Publisher : LPPM Universitas Potensi Utama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22303/csrid-.18.2.2026.287-299

Abstract

Cardiovascular disease is one of the leading causes of death worldwide and requires appropriate treatment and therapy selection. In addition to conventional medical treatment, traditional herbal medicine is widely used as an alternative therapy. However, the large number of available herbal remedies often makes it difficult for people to determine the most appropriate option. This study aims to develop a web-based Decision Support System (DSS) to recommend traditional herbal treatments for cardiovascular diseases using the Simple Additive Weighting (SAW) method. The SAW method was implemented through the stages of alternative determination, criteria identification, criteria weighting, decision matrix construction, normalization, preference value calculation, and ranking. The system was developed using PHP and MySQL and evaluated through Black Box Testing. The results indicate that the system is capable of integrating disease data, symptom data, herbal treatment alternatives, and evaluation criteria to generate recommendations based on the highest preference values. Based on the SAW calculation, A1 (Garlic) achieved the highest preference value of 0.94, followed by A5 (0.91) and A7 (0.89), making it the most recommended traditional treatment according to the criteria of treatment effectiveness, cost, side effects, and herbal availability. The system testing results also showed that all major functions operated as expected. Therefore, the SAW method can be effectively applied as a simple, objective, and practical decision-making approach for recommending traditional treatments for cardiovascular diseases.

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