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INDONESIA
Jurnal Sains dan Teknologi Informasi
Published by Forum Kerjasama Pendidikan TInggi
ISSN : -     EISSN : 2809610X     DOI : https://doi.org/10.47065/jussi.v3i2.4883
Core Subject : Science, Engineering,
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering
Bidang kajian dari Jurnal Sains dan Teknologi Informasi, yaitu: Teknik Informatika, Manajemen Informatika, Sistem Informasi, Teknik Komputer, Kecerdasan Buatan, dan Computer Science.
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 88 Documents
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Optimalisasi Rasio Data pada K-Nearest Neighbor untuk Klasifikasi Multikelas Tingkat Obesitas Populasi Dewasa Dini Aprilia Langnegara; Titik Misriati; Imam Nawawi
Jurnal Sains dan Teknologi Informasi Vol 5 No 2 (2026): Maret 2026
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/jussi.v5i2.9853

Abstract

Obesity is a complex health issue that needs a strategy for assessing its severity to facilitate earlier recognition. One can determine an individual's obesity classification by analyzing their dietary habits, level of physical activity, and overall health status. This research aims to ascertain the K-Nearest Neighbor (KNN) algorithm's efficacy in accurately classifying seven various phases of obesity. The dataset employed for predicting obesity consisted of 2,111 samples drawn from a population of both genders. For KNN testing, the dataset was divided into training and test data, with the test data allocated over three separate scenarios, including varying ratios. The ratios of 70:30, 80:20, and 90:10 were utilized in these circumstances, respectively. The value of k was varied from k=2 to k=10. The optimal configuration was achieved with a 90:10 data split ratio and a k value of 2, as evidenced by the test results. This setup concurrently attained an accuracy of 90.05%, a precision of 90.56%, a recall of 89.80%, and an F1 score of 90.18%. This categorization error was most prominent when comparing the Normal Weight category to the Class I Overweight group. A properly preprocessed KNN algorithm can attain competitive accuracy over 90 percent in classifying population obesity levels, as demonstrated by this study's findings.
Pengembangan Sistem Informasi Manajemen Bimbingan Belajar Berbasis Web dengan Pendekatan Data Mining untuk Analisis Performa Siswa Menggunakan Framework Laravel Atika Fauziyyah; Tomy Nanda Putra; Dori Gusti Alex Candra; M. Agung Vafky Ideal; Budi Permana Putra
Jurnal Sains dan Teknologi Informasi Vol 5 No 2 (2026): Maret 2026
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/jussi.v5i2.9855

Abstract

This research is motivated by the need for a system capable of managing tutoring institution data effectively while accurately analyzing student performance. The main problem at Brigade Nusantara is that data management is still conducted manually and there is no data-based analysis available to support decision-making processes. This study aims to develop a web-based Tutoring Management Information System using the Laravel framework with a data mining approach to analyze student performance. The system development method includes the stages of requirements analysis, system design, implementation, and testing. The data mining approach is utilized to process students’ historical data in order to generate information in the form of performance patterns, learning progress levels, and recommendations for academic improvement. The results of the study indicate that the developed system is capable of improving data management efficiency, facilitating the monitoring of student progress, and supporting accurate and data-driven decision making. Therefore, this system is expected to enhance the overall quality of tutoring services and assist administrators in developing more effective and targeted learning strategies.
Perancangan Sistem Informasi Penjualan Produk Frozen Food Menggunakan Metode Waterfall Berbasis Web dan Xammp Iin Parlina; Mesinta Sari
Jurnal Sains dan Teknologi Informasi Vol 5 No 3 (2026): Juni 2026
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/jussi.v5i3.9863

Abstract

This research was conducted to identify and analyze the problems occurring in UMKM regarding the processing of stock transactions, specifically in the business sector of frozen food products, which is still managed manually. This indicates that information technology optimization has not been thoroughly implemented by business actors in this field. Conventional recording processes frequently lead to errors in record-keeping, delays in report generation, and limitations in conveying product information to customers. Furthermore, the manual system poses challenges for business owners in monitoring stock in real-time, thereby hindering fast and accurate decision-making. Developing an information system for Frozen Food UMKM can help overcome these issues in processing frozen food product sales data, making it easier and more effective for system users to process or manage sales transactions. The research method used to build this information system is the Waterfall method, while data collection was carried out through direct observation by observing manual transaction processes directly and interview methods to obtain supporting information for this study. The result of this research is a system designed to provide convenience for UMKM the Frozen Food Product Sales Information System is implemented to process data effectively and efficiently. This system was designed using the PHP programming language with a MySQL database for database management, utilizing XAMPP for the MySQL database, and implemented using Visual Studio Code for the system interface. The research findings demonstrate that the developed system is capable of managing product data, sales transactions, and reports in a structured and integrated manner. The system also features data search functionalities, automated stock management, and faster, more accurate report generation. Consequently, the designed system can enhance operational efficiency and assist business operators in optimizing their business processes. Future research can achieve quality improvement and broader service coverage by developing a more complex system, integrating electronic payment functions, and system-based automatic notifications, alongside enhancing system security through routine software audits to achieve more efficient and beneficial performance.
Analisis Perbandingan Metode White Box dan Black Box Testing pada Pengujian Modul Autentikasi Sistem Web Joko Yuwono
Jurnal Sains dan Teknologi Informasi Vol 5 No 3 (2026): Juni 2026
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/jussi.v5i3.9870

Abstract

The security of authentication modules in web systems is a critical issue directly impacting user data integrity and system resilience against cyber threats. Inadequate testing can lead to serious security vulnerabilities including SQL injection, authentication bypass, and token exploitation. This study analyzes, compares, and integrates the effectiveness of white box testing and black box testing in testing a PHP-based web system authentication module using JSON Web Token (JWT). A quantitative experimental approach was adopted using seeded defect technique, deliberately injecting 32 defects to objectively measure detection effectiveness of each method. White box testing was implemented using McCabe's basis path testing with PHPUnit 10 and Xdebug-based code coverage analysis, while black box testing used equivalence partitioning and boundary value analysis through Postman API Client. White box testing detected 28 of 32 defects (87.5%), excelling in identifying logic errors and JWT cryptographic algorithm weaknesses. Black box testing detected 29 defects (91.3%), with significant advantages in uncovering input validation errors and HTTP parameter-exploitable security vulnerabilities. Combined, both methods synergistically achieved 93.75% defect coverage (30 of 32 defects). The study concludes that integrating white box testing at unit testing stage and black box testing at integration testing stage provides the most comprehensive quality assurance for web system authentication modules, supported by a strategic matrix for optimal testing method selection.
Implementasi Knowledge Management System Berbasis Web untuk Pengelolaan Tata Usaha Menggunakan Model SECI Yudi Akbar
Jurnal Sains dan Teknologi Informasi Vol 5 No 3 (2026): Juni 2026
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/jussi.v5i3.9883

Abstract

The administration of Baburrahim Islamic Boarding School faces various problems in managing organizational knowledge. There is still a lot of knowledge, work experience, and important information owned by employees that has not been well documented. The high rate of employee turnover in the administration section causes the adaptation process of new employees to be less effective. New employees must relearn various work procedures and information from the beginning. The process of sharing knowledge (knowledge sharing) between employees has not run optimally. There is no web-based Knowledge Management System (KMS) available that can be used to store, manage, and distribute knowledge in an integrated manner in the Islamic boarding school environment, with the solution of implementing a Knowledge Management System (KMS) with the SECI method. This system has proven effective in documenting and managing knowledge assets and experiences of staff optimally and has succeeded in achieving the highest standards of effectiveness with a very good predicate focused on strengthening the quality of human resources through optimizing communication channels and accelerating the transfer of insight between personnel. This system plays a strategic role in building a knowledge sharing ecosystem both at the individual and collective levels. This study formulates a KMS model that is adapted to the operational characteristics of the Administration of Baburrahim Islamic Boarding School. By integrating the Soft Systems Methodology (SSM) framework and the SECI model for knowledge conversion, the system design was visualized using the Unified Modeling Language (UML). Functional evaluation conducted through Focus Group Discussions (FGDs) demonstrated excellent validity, while software quality testing achieved the highest effectiveness standards with a very good rating. The final result is a KMS prototype that is effective in documenting employee expertise and serves as a supporting instrument for work performance in the Administration environment
Students’ Perceptions of Internet Network Problems Facilities at A Public University Using a Qualitative Descriptive Method for Service Improvement Raden Rocky Anderson; Zidni Ma’ruf; Resa Kurni Pratama; Fattar Firansyah
Jurnal Sains dan Teknologi Informasi Vol 5 No 3 (2026): Juni 2026
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/jussi.v5i3.10122

Abstract

This study examines students’ perceptions of internet network services used to support academic activities in higher education. The research was motivated by several issues frequently experienced by students, including unstable internet connections, limited coverage in certain campus areas, network congestion during peak usage periods, repeated login requirements, and limited information regarding technical support services. The objective of this study is to identify students’ perceptions regarding the quality, accessibility, and reliability of campus internet services and to formulate recommendations for service improvement. A qualitative descriptive method was employed through semi structured interviews involving six Electrical Engineering students. The collected data were analyzed using thematic analysis to identify recurring experiences and issues encountered by students. The findings indicate that campus internet services play an important role in supporting access to learning materials, e learning platforms, assignment completion, and other academic activities. However, students reported several challenges related to connection stability, internet speed, roaming capability, and technical support availability. As a practical solution, this study recommends improving network infrastructure, optimizing bandwidth capacity, enhancing roaming functionality across campus areas, and providing clearer technical support information for users. The study provides valuable insights for improving campus internet services and supporting technology-based learning environments more effectively.
Penerapan Algoritma Decision Tree untuk Klasifikasi Prestasi Akademik Mahasiswa Berdasarkan Indeks Prestasi Semester dan Kumulatif Nahot Marganda Simanjuntak
Jurnal Sains dan Teknologi Informasi Vol 5 No 3 (2026): Juni 2026
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/jussi.v5i3.10223

Abstract

Higher education institutions generally have not optimally utilized student academic data as an early detection tool, so students at risk of declining academic performance are often identified too late. This study addresses this problem by applying the Decision Tree algorithm, based on entropy and information gain calculations, to classify student academic performance into three categories (Good, Sufficient, and Poor) using Grade Point per Semester (IPS1–IPS8) and Cumulative Grade Point Average (IPK) features from 518 student records. The purpose of this study is to build a classification model that is both accurate and interpretable, so that its contribution can be used by universities as a transparent decision-support tool for early academic intervention, unlike black-box models that are difficult to explain. The dataset was divided using a 70:30 training-testing ratio. Preliminary results show that the IPK attribute is the most influential factor, with the highest Information Gain of 0.8766, selected as the root node, while model evaluation on the testing data using a confusion matrix yields an accuracy of 96.15%, precision 94.71%, recall 95.10%, and F1-score 94.87%. These results indicate that the constructed Decision Tree model is suitable for use as an early-detection tool for students requiring academic attention.
Analisis Keamanan Digital Perguruan Tinggi Terhadap Ancaman Siber Generasi Z melalui Metode Defense-In-Depth Joko Triyanto; Farros Yumna Prabowo; Muhammad Hafizh Nur Hidayat; Ramzy Alfatoni; Ahmad Baehaqi
Jurnal Sains dan Teknologi Informasi Vol 5 No 3 (2026): Juni 2026
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/jussi.v5i3.10311

Abstract

Digital transformation in higher education has increased the use of information technology in academic activities, communication, and digital data management. This condition provides various conveniences in the education system; however, it also increases cybersecurity threats toward Generation Z as the primary users of digital technology within universities. This study aims to analyze the cyber defense of higher education institutions in dealing with cyber threats among Generation Z and to identify the most dominant forms of digital threats targeting students. A qualitative approach was adopted through a library research method, examining a range of scholarly journals, academic articles, and literature on cybersecurity, digital literacy, and the digital behavior of Generation Z published within the last three years (2023–2026). The collected data were analyzed descriptively and qualitatively through reduction, classification, interpretation, and synthesis to formulate a layered campus cyber defense model (Defense-in-Depth). The findings indicate that the high intensity of social media usage, low cybersecurity literacy, and oversharing behavior are the main factors contributing to increasing cyber vulnerability among Generation Z. In addition, phishing, personal data theft, social engineering, and cyber radicalism are identified as the most dominant cyber threats within higher education environments. The analysis also reveals that only 40% of students are able to independently recognize phishing threats, while cybersecurity education improves data security knowledge by 8.33 points and technological risk understanding by 10.17 points. Therefore, strengthening cybersecurity literacy, digital education, and the development of adaptive campus cyber defense systems are strategic steps in enhancing digital security in higher education institutions.

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