Jurnal Testing dan Implementasi Sistem Informasi
Jurnal Testing dan Implementasi Sistem Informasi is published by Lembaga Riset dan Inovasi Almatani, Pekanbaru, Indonesia. It is academic, online, open access, peer reviewed international journal. It aims to publish original, theoretical and practical advances in Software Engineering, Computer Science, User Experience, Testing of Software and Applications, Computer Architecture, Operating Systems, Computer Networks, Systems Analysis and Design, Programming, Web and Mobile Application Development, User Interface and User Experience (UI/UX), Database Systems, Data Warehousing, Data Mining, Big Data Analytics, Data Management, Enterprise Resource Planning (ERP), Management Information Systems (MIS), Decision Support Systems (DSS), Business Intelligence, Knowledge Management Systems, Information Systems Project Management, IT Governance, Information Systems Audit, IT Risk Management, Information Systems Strategy, Digital Transformation, E-Business and E-Commerce, Financial Technology (FinTech), Digital Marketing, Digital Platforms and Digital Economy, Business Analytics, Predictive Analytics, Machine Learning for Business, Artificial Intelligence in Business, Data Visualization, Information Security, Cybersecurity, Data Privacy, IT Ethics, IT Regulations and Compliance, Internet of Things (IoT), Cloud Computing, Blockchain Technology, Smart Systems, and Integrated Information Systems. Jurnal Testing dan Implementasi Sistem Informasi (JTISI) is published annually 2 times every June and December. E-ISSN : 2986-7991. SINTA 2 Based on SK Direktur Jenderal Riset dan Pengembangan No. 2/C/C3/KPT/2026, from 1(1) 2023 until 5(2) 2027. https://suggestor.step.scopus.com/progressTracker/?trackingID=777E10741D88FABE Journal title Initials Frequency DOI Online ISSN Editor-in-chief Publisher Language Indexing Citation Analysis : Jurnal Testing dan Implementasi Sistem Informasi : JTISI : 2 issues per year (December and June) : by with Prefix 10.355583(https://doi.org/10.55583/jtisi) : 2986-7991 : Assoc. Prof. Dr. Muhammad Luthfi Hamzah, B.IT., M.Kom : Lembaga Riset dan Inovasi Almatani : English : Garuda | Google Scholar | Dimensions | Sinta 2 : Scopus Citedness
Phishing Detection Model on Social Media Enhanced With CNN and BERT
Phishing on social media has become an increasingly serious cyber threat because attackers exploit persuasive language, conversational context, and dynamic interaction patterns to deceive users. This study proposes a hybrid CNN-BERT model for detecting phishing content in Indonesian social media text by combining BERT’s contextual semantic representation with CNN’s ability to capture locally relevant textual patterns. The dataset was preprocessed to remove noise, normalize writing variations, and prepare the text for deep learning analysis; class proportions were also examined to support fairer evaluation. Model performance was assessed under multiple data-splitting scenarios and cross-validation to examine robustness and consistency. The experimental results indicate that the proposed hybrid model achieves strong and stable performance across accuracy, precision, recall, and F1-score, and outperforms the baseline model when the BERT backbone is frozen. However, when BERT is fully fine-tuned, the performance gain from the CNN layer becomes marginal, suggesting that strong contextual representations are already highly effective for this task. These findings indicate that integrating CNN and BERT is effective for phishing detection on social media, although domain adaptation challenges, overfitting risk, and real-world deployment constraints remain important considerations. The novelty of this work lies in systematically comparing frozen versus fully fine-tuned IndoBERT backbones with and without a CNN head for Indonesian short-message phishing detection.
Copyright (c) 2026 Jurnal Testing dan Implementasi Sistem Informasi
Design and Evaluation of an AI-Assisted Digital KPI Information System for Employee Performance Monitoring and Recommendation
Manual and fragmented KPI-based evaluation often weakens employee performance monitoring by causing delays, input errors, and inconsistent interpretation. This study addresses that problem by designing and evaluating an AI-assisted digital KPI information system that integrates competency assessment, digital KPI records, performance scoring, dashboard-based monitoring, and recommendation support in a single environment. The study contributes by transforming the conventional competency–KPI–performance framework into an operational decision-support artifact with embedded AI classification. Using a prototype-based approach, the system was evaluated with a structured dataset of 340 employee-year records from 2021–2025. Three machine learning models were compared for classifying employee performance into High, Moderate, and Low categories. The results show that the system is functionally feasible and usable for KPI-based performance monitoring, while Random Forest achieved the best classification performance with 0.9853 accuracy and 0.9852 F1-score. The findings indicate that the proposed system can improve the structure of digital KPI monitoring and provide AI-assisted support for managerial review and follow-up actions. The study contributes theoretically by extending KPI-based performance management into an intelligent information system context and practically by offering a feasible model for organizations operating under limited implementation conditions.
Design and Evaluation of a Decision Support System for Classifying Tourism Site Crowding and Recommending Governance Responses in Bunaken National Park
Effective governance of marine protected areas (MPAs) requires reliable mechanisms to translate multidimensional ecological and social data into coordinated institutional action. Despite widespread adoption of carrying capacity frameworks, a significant "implementation gap" persists between theoretical conservation thresholds and operational decision-making at the site level. This study addresses that gap by designing, implementing, and evaluating a Decision Support System (DSS) artifact tailored for Bunaken National Park (BNP), Indonesia. Grounded in Design Science Research (DSR) principles, the artifact employs a deterministic, rule-based classification engine that processes four normalized input dimensions visitor density, social carrying capacity, infrastructure load, and governance readiness to compute a Composite Crowding Index (CCI). The CCI is mapped through an explicit IF-THEN rule engine to four crowding categories (Low, Moderate, High, Extreme), each linked to a validated governance action package. A deterministic rule-based approach was chosen over probabilistic or machine-learning alternatives to ensure full decision traceability, which is a non-negotiable requirement for public-sector governance. System robustness was evaluated through structured scenario testing across 140 logic-coverage cases, assessed against four criteria: output consistency (100%), expert rule alignment (97.8%), decision traceability (100%), and processing efficiency (<1.15 seconds per scenario). The artifact successfully automates the mapping of site-level crowding status to discrete, auditable governance actions. The theoretical contribution lies in formalizing subjective management reasoning into a transparent, reproducible DSS that bridges sustainability science and institutional practice in high-pressure marine tourism environments.
Analysis of User Reviews for The Mytelkomsel App Using Naïve Bayes and Random Forest Methods
While sentiment analysis of local application reviews predominantly utilizes native Indonesian data, these datasets frequently suffer from colloquial ambiguities and informal structures that degrade classifier performance. This study addresses this gap by implementing a language-filtering mechanism to separate and analyze English and Indonesian user opinions from the MyTelkomsel application, specifically justifying the inclusion of English reviews due to their superior grammatical structure and syntactic consistency, which inherently enhances feature extraction. A systematic methodology was employed, encompassing data collection from the Google Play Store, comprehensive pre-processing (case folding, tokenization, stopword removal, and stemming), and Term Frequency-Inverse Document Frequency (TF-IDF) vectorization. Evaluated using Naïve Bayes and Random Forest algorithms on 25,000 customer feedbacks, the models were compared across accuracy, precision, recall, and F1-score. The empirical results demonstrated that Random Forest outperformed Naïve Bayes, achieving a higher accuracy of 86.85% compared to 86.36%. This superiority stems from Random Forest’s robust capability to mitigate class imbalance and minimize error distribution across sentiment categories. Ultimately, this approach provides precise, actionable insights into service quality, enabling Telkomsel to effectively distinguish user satisfaction, target operational improvements, and mitigate customer churn.
An Expert System for Early Detection of Mental Health Conditions Using Certainty Factor and DASS-42
Mental health problems such as depression, anxiety, and stress continue to increase in many countries, while access to professional services is still limited. Many digital screening systems use fixed scoring methods and do not consider uncertainty in user responses. This study developed a web-based expert system by combining the Depression Anxiety Stress Scales (DASS-42) and the Certainty Factor (CF) method to represent uncertainty in overlapping emotional symptoms and provide more flexible screening results. The knowledge base was prepared through consultation with a licensed clinical psychologist and converted into 42 production rules based on the DASS-42 items. Each rule was assigned a confidence value according to expert judgment. The system uses forward chaining to combine active rules and calculate confidence scores for depression, anxiety, and stress at the same time. System evaluation was conducted using 50 community cases aged 18–35 years and compared with independent expert assessment. The overall accuracy reached 86% (43 of 50 cases). The accuracy for each category was 88.2% for depression, 82.3% for anxiety, and 87.5% for stress. Most classification errors occurred between anxiety and stress, which may be related to overlapping symptoms in the DASS-42 instrument. The findings indicate that the proposed system can support early mental health screening through interpretable confidence-based results. However, this study used a limited dataset and only one expert in knowledge development. The system is intended as a screening support tool and not as a replacement for clinical diagnosis.
Improving FAQ Retrieval for Academic Regulations Using Semantic Embeddings and LLM Question Augmentation
Academic regulations in higher education are often documented in lengthy and formal handbooks, making it difficult for students to find relevant information using everyday language. This study developed a semantic FAQ retrieval system for academic regulations using IndoSBERT and question augmentation. The FAQ corpus was constructed from official academic and internship documents, resulting in 92 FAQ entries across 33 topical categories. Seed questions were generated from category–keyword pairs and expanded using simple rule-based augmentation and FLAN-T5-based paraphrasing. The dataset was evaluated using an 80:10:10 train–validation–test split. IndoSBERT was fine-tuned with Multiple Negatives Ranking Loss under three configurations: baseline, baseline with simple augmentation, and baseline with simple plus LLM-based augmentation. Retrieval performance was measured using Recall@1, Recall@3, Recall@5, and Mean Reciprocal Rank. The best result was achieved by the simple plus LLM augmentation configuration, with Recall@1 of 0.7848, Recall@5 of 0.8987, and MRR of 0.8396. These findings show that LLM-based question augmentation improves semantic retrieval robustness while keeping answers grounded in curated academic regulations.
Optimized Land Surface Low Point Detection Using the D8 Algorithm in a Geographic Information System (GIS) Framework
Hydrological analysis in urban areas often suffers from inaccuracies in Digital Elevation Model (DEM) interpretation, especially in detecting micro-depressions and small-scale surface flow patterns. Previous studies typically relied solely on the automatic D8 algorithm in GIS without manual verification, resulting in flow directions that do not fully represent actual surface conditions. This study aims to compare manual D8-based flow direction calculations with automatic ArcGIS processing using DEMNAS data for Langsa City. The DEM (8.1 m resolution) underwent sink filling, hydrological conditioning, slope and aspect processing, followed by field validation using GPS measurements. The results show that the manual method identified 23 flow paths, whereas ArcGIS detected only 11. The differences stem mainly from micro-topographic variations that the automatic algorithm failed to capture in flat areas or anthropogenically modified surfaces. Field validation confirmed that 8 of the 11 ArcGIS-derived paths matched the actual drainage patterns, while the additional manual paths better represented subtle elevation gradients.This research contributes by offering a systematic comparison between manual and automatic D8 approaches, highlighting the importance of manual verification in low-slope urban terrains. The findings are valuable for micro-scale flood mitigation planning and urban surface hydrology analysis.
EMPLOYEE PAYROLL SYSTEM DESIGN USING EXTREME PROGRAMMING ALGORITHM
The employee payroll system was built to make it easier for companies, especially those that still handle payroll manually, to manage employee payroll data. Company X still records employee information, absence information, and salary information manually in a book as part of its employee payroll process. The design of the employee payroll system in this study uses the Extreme Programming method. The Extreme Programming approach is used in the design of the employee payroll system in this study. This study also tests the system. The system is tested using White-box and Black-box testing methodologies, with the aim of testing the functional and non-functional requirements of the system. The findings of this study lead to the creation of an employee payroll information system that Company X can use to facilitate the payroll process for its employees.
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THE INFLUENCE OF MARKETING MIX ON CONSUMER PURCHASE PATTERNS USING THE APRIORI DATA MINING ALGORITHM
The increasing volume of sales transaction data in retail and marketplace environments presents an opportunity to extract valuable insights for decision-making; however, such data are often underutilized. This study aims to analyze consumer purchasing patterns using the Apriori algorithm and to examine the influence of the marketing mix (product, price, place, and promotion) on purchasing decisions that shape these patterns. This research employs a quantitative approach by integrating data mining and statistical analysis. Transaction data are processed using the Apriori algorithm through RapidMiner to generate association rules and identify frequent itemsets. In addition, questionnaire data are analyzed using multiple linear regression to evaluate the effect of marketing mix variables on purchasing decisions. The results show that product, price, place, and promotion simultaneously have a significant effect on purchasing decisions. Partially, product (t = 2.622; p = 0.011), price (t = 4.738; p = 0.000), and place/distribution (t = 2.239; p = 0.029) have a significant positive effect, while promotion does not have a significant effect (t = 1.486; p = 0.143). The Apriori analysis reveals dominant purchasing patterns that can be translated into practical marketing strategies, such as product bundling and layout optimization. This study contributes by integrating association rule mining with marketing mix analysis to provide both predictive patterns and explanatory insights. However, the findings should be interpreted with caution due to data limitations, including a relatively small sample size (n = 148) and a short observation period of three months during peak season, which may limit generalizability. Despite these constraints, the results offer practical implications for optimizing marketing strategies and contribute theoretically to interdisciplinary research in data mining and consumer behavior.
HAND POSE CLASSIFICATION USING MEDIAPIPE HANDS AND CNN-LSTM FOR AUGMENTED REALITY BASED INTRAVENOUS INFUSION LEARNING
Intravenous infusion training requires precise hand positioning and coordinated movements; however, conventional training approaches remain subjective and lack consistent real-time feedback. Moreover, existing augmented reality (AR)-based systems are largely limited to visualization and do not provide intelligent, automated skill evaluation. To address this gap, this study proposes an integrated hand pose classification framework that combines MediaPipe-based landmark extraction, CNN-LSTM spatio-temporal modeling, and AR-based feedback for real-time procedural learning. The novelty of this work lies in the seamless integration of lightweight feature representation, hybrid deep learning, and interactive AR feedback within a unified learning system. Experimental results demonstrate that the proposed approach achieves high classification performance, with an accuracy of 94.82% and an AUC of approximately 0.97, indicating strong discriminative capability. The system also operates in real time with low latency, enabling immediate feedback and adaptive learning. This study contributes theoretically to spatio-temporal gesture modeling and practically to the development of intelligent AR-based training systems. The proposed framework offers a scalable and objective solution for improving procedural accuracy, consistency, and accessibility in medical education.
A QUALITATIVE SYNTHESIS OF ARTIFICIAL INTELLIGENCE ADOPTION IN MSMES: INSIGHTS INTO OPPORTUNITIES AND CHALLENGES
Artificial intelligence (AI) has emerged as a transformative technology that is reshaping business processes, innovation, and competitiveness, particularly for Micro, Small, and Medium Enterprises (MSMEs). Despite its potential, AI adoption among MSMEs remains uneven and is often constrained by various technological, organizational, and environmental factors. This study aims to provide a comprehensive understanding of AI adoption in MSMEs by conducting a qualitative synthesis of existing literature, focusing on the identification of key drivers, barriers, opportunities, and organizational impacts. This research adopts a systematic literature review (SLR) approach, guided by the PRISMA framework, to analyze 25 peer-reviewed articles indexed in Scopus. A thematic analysis was employed to systematically code and categorize the findings, enabling the identification of recurring patterns and critical themes related to AI adoption in MSMEs. The results reveal four major themes: (1) drivers of adoption, including technological readiness, organizational capabilities, competitive pressure, and perceived benefits; (2) barriers to adoption, such as financial constraints, lack of expertise, technological complexity, and organizational resistance; (3) opportunities enabled by AI, including enhanced operational efficiency, improved customer insights, innovation, and market expansion; and (4) organizational impacts, particularly in terms of performance improvement, digital transformation, innovation capability, and strategic alignment. The study contributes to the literature by providing an integrative and qualitative perspective on AI adoption in MSMEs, extending the Technology-Organization-Environment (TOE) framework with AI-specific insights. Practically, the findings offer guidance for MSME managers and policymakers in designing strategies to overcome adoption barriers and leverage AI for sustainable growth. Future research is encouraged to explore empirical and longitudinal approaches to further examine the dynamic nature of AI adoption in MSMEs.
DESIGN AND IMPLEMENTATION OF A DECENTRALIZED E-VOTING SYSTEM ON LOCAL SERVER INFRASTRUCTURE
This study addresses the limitations of existing decentralized e-voting systems, particularly their reliance on public distributed infrastructures, limited real-world deployment feasibility, and lack of comprehensive evaluation. Previous studies have demonstrated the potential of distributed ledger-based voting mechanisms; however, most focus on conceptual designs or small-scale prototypes without detailed performance and usability validation. To address this gap, this research proposes and implements a decentralized e-voting system deployed on a local server infrastructure using distributed ledger technology and automated validation mechanisms for vote integrity. The system is designed to reduce dependency on external networks while maintaining transparency, immutability, and operational efficiency. The system was evaluated through functional testing, performance analysis, and user acceptance testing involving 30 participants in a controlled environment with 20 simulated voters. The results show that the system achieved a functional accuracy of 96% across 25 test scenarios. The average transaction response time ranged between 0.6 and 1.6 seconds, indicating efficient processing under moderate load conditions. However, the evaluation is limited to small-scale simulations and does not include stress testing, large-scale scalability analysis, or advanced security validation. Therefore, the findings demonstrate system feasibility rather than fully validated effectiveness. These results suggest that decentralized e-voting systems deployed on local infrastructures can provide a practical and efficient solution for controlled election environments, while further research is required to evaluate scalability, security robustness, and real-world deployment readiness.
ANALYSIS OF TESTS USING THE WHITEBOX AND BLACKBOX METHODS ON WEB-BASED CAR RENTAL SYSTEMS
Car rentall is a company engaged in the service sector which provides services in the form of car loans based on predetermined conditions. in this company there are obstacles faced by cv. Prime car rental in Pekanbaru, where the administration still uses paper media and writing is still in the form of documents on car return data, tenant data, and car renter transaction reports. However, with this error several problems often occur which cause a slow process of car rental, data search, and the process of making monthly reports. For this reason, it is necessary to test a web-based car rental information system so that it can be used optimally according to the functions and needs of the company. In solving this problem we use the whitebox and blackbox methods to test the car rental system at Pekanbaru. where is the test that we did to provide an explanation with the results of the system that has been made where, it can be concluded whether the system can help the company.
APPLIED MATHEMATICAL MODELING FOR 3D KINEMATIC SPATIAL RECONSTRUCTION IN A LOW-COST MONOCULAR WEBCAM-BASED SQUAT ANALYSIS SYSTEM
Squat is a fundamental exercise for improving lower body strength; however, improper execution may increase the risk of musculoskeletal injury. Conventional motion analysis systems, such as marker-based technologies, provide high accuracy but require expensive equipment and controlled environments, while monocular camera-based approaches often suffer from limited three-dimensional representation. Therefore, this study proposes a low-cost squat analysis system, gui_mocap, which integrates monocular computer vision with vector-based mathematical modeling for real-time motion analysis. The system employs pose estimation to detect body landmarks and reconstructs joint kinematics in three-dimensional space using geometric vector operations. Knee joint angles are computed using the dot product formulation, and an Exponential Moving Average (EMA) filter is applied to improve measurement stability. Experimental evaluation was conducted using multiple squat repetitions to analyze motion patterns and consistency. The results demonstrate that the system can accurately identify key movement phases, including standing, deep flexion, and return to standing, while producing smooth and stable joint angle trajectories. Furthermore, the system is capable of analyzing repeated movements and generating descriptive statistics, such as average joint angles and range of motion, indicating consistent performance across repetitions. This study contributes a practical and affordable solution for real-time motion analysis using a monocular webcam, with potential applications in home-based exercise monitoring and basic rehabilitation.
FROM DIGITAL SHOPPING EXPERIENCE TO SOCIAL INFLUENCE: EXAMINING THE ROLES OF ONLINE SHOPPING EXPERIENCE AND INFLUENCER MARKETING IN SHAPING CONSUMER TRUST AND LOYALTY IN E-COMMERCE
The aim of this research is to analyze the influence of online shopping experiences and influencer marketing on consumer trust and loyalty when shopping via e-commerce platforms (study in the Pekanbaru community). The population in this study is unknown to the people of Pekanbaru. The sampling technique used was the Roscoe method. The sample size for this study was 170 respondents from the Pek-anbaru community. The sampling technique was carried out using non-probability sampling with Purposive Sampling Technique. The data analysis technique uses the Structural Equation Model (SEM) approach with Partial Least Squares (PLS). The results of this research show that online shopping experience and influencer marketing have a significant positive effect on consumer trust and loyalty in the Pekanbaru community, being the most dominant variables in influencing consumer loyalty.
ANALYSIS OF TESTING OF WEB BASED E-RAPORT INFORMATION SYSTEMS USING BLACK BOX AND WHITE BOX METHODS
An online tool called e-report is utilized to process students' final grades. For SMP 4 Muhammadiyah Pekanbaru pupils, manual delivery methods like regular paper and report cards are still used for information submission and checking marks on report cards. A website-based report card application was developed in order to make it simpler for students at SMP Muhammadiyah 4 Pekanbaru to view grades and obtain information on report cards by utilizing existing technology and computerization. The author offers using the e-report as a solution to the issue. The authors employ the agile technique, which is a development model that is carried out iteratively, repeatedly, and can experience modifications as needed, in order to create and build the report card system.
TESTING OF WEB-BASED LEARNING MEDIA INFORMATION SYSTEMS WITH WHITE BOX AND BLACK BOX TESTING
Learning media is a tool in the process of delivering learning materials to students both inside and outside the classroom. Current technological developments have also brought developments in learning media. The most widely used learning media today is website-based information systems. Testing is a stage in the software development life cycle. Testing is conducted to determine the feasibility and quality of the information system. Based on this, this study aims to test a website-based learning information system using white box and black box methods based on equivalence partitions. Testing was conducted on four features: login, material input, attendance, and logout. Based on the testing conducted on these four features, the results indicate that the features are functioning as expected.
Sistem Absensi Dan Kegiatan Mahasiswa Magang Menggunakan Metode Spiral
Artikel ini membahas implementasi dan perancangan sistem informasi untuk pencatatan absensi dan kegiatan mahasiswa magang dengan tujuan meningkatkan efisiensi dan akurasi dalam pengelolaan program magang. Dengan menggunakan Model Spiral dalam pengembangan sistem, serta metode pengumpulan data melalui studi literatur dan kuesioner, penelitian ini menunjukkan bahwa sistem absensi dan manajemen kegiatan magang online dapat memberikan solusi yang lebih efisien dan akurat dibandingkan dengan metode manual. Fitur-fitur seperti login, dashboard admin dan mahasiswa, serta input data absensi dan kegiatan menjadi bagian dari sistem ini yang dapat memudahkan pengelolaan program magang. Hasil kuesioner menunjukkan bahwa sebagian besar responden kurang setuju terhadap kemampuan pencatatan manual dalam menghasilkan data yang akurat, sehingga implementasi sistem ini diharapkan dapat menawarkan solusi yang terbaik pada segi efisiensi serta transparansi dalam pengelolaan kehadiran dan kegiatan mahasiswa magang.
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Rancang Bangun Sistem Informasi Pemesanan Accessories Berbasis Online Dengan Metode Prototype
Pandemi (COVID-19) telah berdampak pada perekonomian global dan meningkatkan popularitas e-commerce. Karena perekonomian bergantung pada e-commerce untuk bertahan selama pandemi. E-commerce memberikan peluang bagi siapa saja untuk dengan mudah memulai atau mengembangkan bisnis. Tujuan penelitian ini telah dimanfaatkan oleh pebisnis tokohitstore merupakan toko yang didirikan pada tanggal 28 Maret 2024 yang dimana pada tokohitstore ini menyediakan berbagai macam accessories. Penulis menggunakan metode prototyping dalam merancang sistem baru. Metode ini melibatkan lima tahapan, yang dimulai dengan pengumpulan data melalui kuesioner dan analisis kebutuhan. Hasil dari penelitian ini adalah pembangunan sistem informasi pemesanan aksesori berbasis online, yang memiliki modul pelanggan untuk mencari, melihat detail, dan memesan aksesori, modul admin untuk mengelola data aksesori, pelanggan, dan pesanan, serta modul laporan untuk memberikan informasi kepada pelanggan tentang aksesori yang tersedia.
A Rancang Bangun Sistem Informasi Penjualan Mainan Edukasi BricksGenius Berbasis Web Menggunakan Metode SCRUM
Saat ini, IT telah digunakan di banyak bidang, seperti pemerintahan, kesehatan, militer, pendidikan, ekonomi, dan lainnya. Tujuan penggunaan teknologi ini adalah untuk meningkatkan produktivitas dan memudahkan pekerjaan. Bisnis di bidang ekonomi atau perdagangan menggunakan informasi teknologi untuk meningkatkan kinerja dan daya saing mereka dibandingkan dengan pesaingnya. Toko BrickGenius, yang fokus pada penjualan mainan Bricks untuk anak-anak, menjadi subjek studi kasus ini. Toko ini menghadapi beberapa masalah karena proses penjualan mereka yang masih konvensional, seperti pencatatan laporan penjualan menggunakan Microoft Exel dan buku, yang mengakibatkan kesalahan pencatatan dan data yang tidak akurat. Tujuan dari penelitian ini adalah untuk mengembangkan aplikasi penjualan berbasis web yang beroperasi melalui internet dengan menerapkan Metode Scrum. Metode Scrum adalah salah satu pendekatan manajemen proyek yang paling populer dan berhasil. Inti dari pendekatan ini adalah Pembagian proyek besar menjadi beberapa siklus pendek yang disebut sprint, yang digunakan untuk merancang, mengembangkan, dan menguji fitur baru. Hasil penelitian menunjukkan bahwa sistem penjualan berbasis web yang responsif, aman, dan mudah digunakan telah berhasil dikembangkan. Hal ini akan membantu Toko BrickGenius untuk meningkatkan pangsa pasar di pasar online yang kompetitif.
Rancang Bangun Sistem Kepuasan Pengguna Pada Layanan Akademik Menggunakan Metode Rapid Application Development
Dalam standar ISO 9001:2015 klausul 9.1.2, organisasi diwajibkan untuk memantau persepsi pelanggan untuk memastikan kebutuhan dan harapan mereka terpenuhi. Universitas Islam Negeri Sultan Syarif Kasim Riau menggunakan Google Form untuk mengumpulkan data kepuasan pengguna terhadap layanan administrasi. Namun, berdasarkan survei, sebagian besar responden menyatakan bahwa Google Form memiliki keterbatasan dalam desain, format, keamanan, dan transparansi data. Untuk mengatasi permasalahan ini, penelitian ini mengusulkan pembangunan sistem kepuasan pengguna yang lebih terstruktur dan sistematis. Metode Rapid Aplication Development (RAD) digunakan untuk membuat sistem ini menjadi aplikasi web yang menggunakan PHP dan MySQL. Hasil pengujian menunjukkan bahwa sistem ini berhasil memenuhi persyaratan fungsional dan non-fungsional di Universitas Islam Negeri Sultan Syarif Kasim Riau dan mampu meningkatkan kualitas layanan administrasi.
Implementation of Local Mean Distance Weighting k-Nearest Neighbor in Determining Vocational High School Majors in Pekanbaru
Vocational High School is a formal education at the secondary education level. SMK X Pekanbaru is one of the private vocational schools in Pekanbaru that provides IT-based education. There are 5 (five) majors in SMK X Pekanbaru, namely Computer and Network Engineering (TKJ), Software Engineering (RPL), Accounting and Financial Institution (AKL), Office Automation and Governance (OTKP), and Online Business and Marketing (BDP). During the registration period, prospective SMK students will enter their score data and will also choose the majors they want to take. In the absence of a system that can determine majors for prospective SMK students, obstacles will arise including errors in determining majors and requiring a long time to process prospective student data. Based on the above problems, a system will be built that can speed up and simplify the determination of new student majors by using Supervised Learning algorithms in Machine Learning, namely Local Mean Distance Weight k-Nearest Neighbor (LMDWkNN). Based on the results of the confusion matrix testing carried out, the accuracy results were 88.89%, the precision, recall and F1 score were 89%, which states that the model is good enough to determine majors
Analisa Tingkat Usability Website Menggunakan Metode System Usability Scale Dan Post Study System Usability Questionnaire
Website Diskominfo Kabupaten Bengkalis merupakan situs yang menyajikan informasi terkait kegiatan pemerintahan dan pengabdian masyarakat Kabupaten Bengkalis sesuai dengan tugas pokok dan fungsi Diskominfo. Untuk mengetahui kualitas suatu website, perlu dilakukan evaluasi tingkat kegunaan website tersebut dengan menggunakan metode System Usability Scale (SUS) dan Post Study System Usability Questionnaire (PSSUQ). Perhitungan dilakukan dengan menganalisis kuesioner yang telah disebarkan kepada masyarakat Bengkalis, kemudian dihitung dengan menggunakan rumus metode System Usability Scale (SUS) dan Post Study System Usability Questionnaire (PSSUQ). Hasil perhitungan dari kuisioner yang telah disebar nantinya akan dijadikan dasar dalam memberikan saran dan rekomendasi hasil yang sesuai serta kesimpulan perbandingan evaluasi dengan metode System Usability Scale (SUS) dan Post Study System Usability Questionnaire (PSSUQ). di website Diskominfo Kabupaten Bengkalis.
Tata Kelola Audit Sistem Informasi Pada BMKG Stasiun Meteorologi SSK II Pekanbaru Menggunakan COBIT 2019
Badan Meteorologi, Klimatologi, dan Geofisika (BMKG) merupakan Lembaga pemerintah di Indonesia yang tidak termasuk dalam departemen dan memiliki tanggung jawab melaksanakan tugas pemerintahan di bidang Meteorologi, Klimatologi, dan Geofisika. Manfaat yang melimpah dapat diperoleh dengan memanfaatkan teknologi di perusahaan. Oleh karena itu, setiap perusahaan memerlukan manajemen teknologi informasi yang efisien, mulai dari perencanaan hingga implementasi, guna menjaga kinerja yang optimal. penulis ingin menilai Penggunaan COBIT Framework 2019 dalam tata kelola teknologi informasi di BMKG telah dijalankan dan menyarankan pendidikan dan pelatihan berkala untuk membantu SDM mengantisipasi masalah Hasil Evaluasi Tingkat Kemampuan Tata Kelola Audit Sistem Informasi di Stasiun Meteorologi SSK II Pekanbaru BMKG dengan menggunakan COBIT 2019 menunjukkan bahwa Objektif APO03 dan APO05 telah mencapai tingkat 3 Largely Achieved. Meskipun implementasi proses telah dilakukan, tetapi Beberapa proses dalam tingkat ini masih belum beroperasi sepenuhnya untuk mencapai hasil yang diinginkan. Oleh karena itu, perbaikan diperlukan dalam ketiga domain ini berdasarkan temuan kesenjangan agar dapat mencapai tingkat 3 Fully Achieved. Sementara itu, Objektif APO07, APO12, dan BAI02 masih di tingkat 2 Largely Achieved. implementasi proses telah mencapai tujuannya dengan efisiens, namun masih belum memenuhi standar yang diharapkan oleh perusahaan.
Sistem Informasi Pelaporan Kendaraan Dan Alat Berat Menggunakan Metode Rapid Application Development
Andalas karya mulia (AKM) merupakan perusahaan yang bergerak di bidang jasa konstruksi dan penyewaan alat berat. PT. AKM Saat ini perusahaan melakukan pelaporan kendaraan berat dan alat berat masih dilakukan secara manual melalui via whatsapp. sehingga pihak kantor kesulitan dalam mendapatkan data-data yang terbaru dari setiap proyek yang dimiliki perusahaan. Berdasarkan dari permasalahan tersebut diperlukan sebuah sistem yang dapat memudahkan karyawan yang berada di lokasi proyek dalam melakukan pelaporan kendaraan berat dan alat berat, Agar memudahkan karyawan kantor mendapatkan laporan kendaraan yang terbaru. Dari penjelasan diatas dapat dibuat sebuah sistem yaitu sistem pelaporan kendaraan berat dan alat berat. Sistem ini dirancang menggunakan Framework Laravel, Flutter dengan Bahasa pemogramman PHP dan MySQL sebagai DBMS nya. Pembangunan sistem ini dilakukan menggunakan metode Rapid Aplication Development (RAD) agar pembangunan sistem ini dapat terselesaikan dalam waktu 60-90 hari sehingga dapat segera di praktekkan dilapangan. Diharapkan dengan adanya sistem ini diharapkan dapat membantu karyawan dalam melakukan pelaporan kendaraan berat dan alat berat. Penelitian ini dilakukan menggunakan metode pengujian blackbox testing, dengan hasil seluruh test case berhasil berfungsi sesuai yang diharapkan dari penggunanya. dilakukan pengujian menggunakan usability testing dari 6 orang responden dengan hasil rata-rata rekapitulasi pengujian dari 5 aspek usability testing sebesar 68.24% responden setuju bahwa sistem pelaporan alat berat dan kendaraan berat telah memenuhi kriteria secara fungsional.
Audit Tata Kelola Universitas Islam Negeri Sultan Syarif Kasim Riau Kuliah Kerja Nyata Sistem Menggunakan COBIT 2019
Penelitian ini menggunakan framework Control Objectives for Information and Related Technology (COBIT) 2019. Tujuannya adalah untuk mengidentifikasi masalah-masalah yang ada dan memberikan rekomendasi perbaikan guna meningkatkan tata kelola teknologi informasi di LPPM. Penelitian ini melibatkan tahap perencanaan, pengumpulan data, dan analisis hasil. Hasil audit menggunakan COBIT 2019 menunjukkan bahwa sistem berada pada level 2 dengan kategori Large Achieved (L) untuk proses APO01, APO04, APO14, dan BAI03. Hal ini menandakan bahwa sistem berjalan dengan baik meskipun masih ada kekurangan dalam konsistensinya. Sementara itu, proses APO06 mencapai level 5 dengan kategori Fully Achieved (F), menunjukkan bahwa sistem telah terdefinisi dengan baik, namun perlu pengukuran kinerja untuk meningkatkan perbaikan yang berkelanjutan. Penelitian ini memberikan kontribusi dalam meningkatkan tata kelola teknologi informasi di LPPM Universitas Islam Negeri Sultan Syarif Qasim. Rekomendasi perbaikan yang diberikan dapat menjadi panduan bagi LPPM dalam mengoptimalkan penggunaan teknologi informasi dalam proses pemilihan lokasi Kuliah Kerja Nyata (KKN) Mahasiswa. Diharapkan dengan implementasi rekomendasi ini, efektivitas penggunaan website LPPM dapat ditingkatkan, sehingga masalah seperti server yang sering down, kesulitan dalam proses login, kurangnya integrasi database, dan user interface yang membingungkan dapat diatasi.
Evaluasi Dan Implementasi Tata Kelola TI Pada Sma Negeri 4 Pekanbaru Menggunakan COBIT 2019
Audit tata kelola teknologi informasi di SMA Negeri 4 Pekanbaru perlu dilakukan karena adanya beberapa permasalahan yang sering muncul dan menurunkan tingkat tata kelola di sana. Kerangka Audit Tata Kelola TI COBIT 2019 menawarkan pedoman dan praktik terbaik untuk membantu organisasi mendapatkan hasil maksimal dalam pemanfaatan TI. Didapatkan hasil enam titik kritis pada SMA Negeri 4 Pekanbaru. Sasaran perusahaan dan sasaran penyelarasan disesuaikan dengan setiap poin utama, sehingga menciptakan domain yang terdiri dari APO07, APO08, APO11, BAI03, dan BAI08. Nilai kapabilitas saat ini digunakan untuk menghitung nilai kesenjangan, dan rekomendasi perbaikan diberikan berdasarkan nilai kapasitas yang diharapkan dan saat ini yang terdapat pada studi tingkat kematangan. Perbaikan diterapkan pada proses domain APO08, mengikuti timeline yang telah ditentukan. Hal ini menghasilkan hasil yang diinginkan yaitu meningkatkan nilai kemampuan dari level 2, yang merupakan kondisi sebelumnya, ke level 3.
Audit Tata Kelola Universitas Islam Negara Sultan Syarif Kasim Riau Repository System Menggunakan COBIT 2019
Teknologi Informasi telah menjadi pendorong utama keberhasilan organisasi di berbagai sektor, termasuk dunia Pendidikan. Universitas, sebagai lembaga pendidikan tinggi, semakin mengandalkan TI untuk mendukung operasional dan pengelolaan informasi akademis. Perpustakaan Universitas Islam Negeri Sultan Syarif Kasim Riau mendukukng fungsi operasional, pengelolaan di perpustakaan. Proses audit pada Perpustakaan dilakukan untuk mengetahui sejauh mana kinerja IT, sumber daya manusia serta capability level di perpustakaan. Penelitian ini menggunakan Framework COBIT 2019 dalam melakukan auidit. Didapatkan hasil pada 4 domain proses yaitu APO09, APO11, BAI04 dan BAI06. APO09 dan BAI04 berada pada level 2 dengan kategori largely achieved, sedangkan APO11 dan BAI06 berada pada level 5 dengan kategori fully achieved.
Perancangan Sistem Informasi Pendaftaran Online Pasien Rawat Jalan Pada Puskesmas Menggunakan Metode Prototype
Pendaftaran merupakan tahapan awal bagi pasien untuk mendapatkan layanan kesehatan. Pendaftaran pasien di Puskesmas Alai Padang yang dilakukan secara manual dan kurangnya sumber daya manusia pada bagian pendaftaran membuat peneliti berupaya mengatasi kekurangan tersebut dengan merancang sistem informasi pendaftaran online pasien rawat jalan untuk mengatasi permasalahan yang terjadi. Metode yang digunakan, yaitu Research and development dengan pengembangan prototyping. Sehingga penelitian ini menghasilkan suatu aplikasi sistem informasi pendaftaran online pasien rawat jalan dengan di dukung oleh Unified Modeling Language (UML), yaitu dengan use case diagram, activity diagram, class diagram dan sequence diagram. Hasil uji coba simulasi penggunaan yang dilakukan dapat di nilai bahwa aplikasi pendaftaran online pasien rawat jalan ini sudah dapat digunakan serta elemen data yang ada sudah sesuai dengan kebutuhan. Sehingga kesimpulan pada penlitian ini adalah didapatkannya rancangan aplikasi pendaftaran online pasien rawat jalan yang berbasis web dengan tujuan pendaftaran online ini dapat memudahkan pasien dalam melakukan pendaftaran berobat
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Implementasi Multi-Objective Optimization Based On Ratio Analysis (MOORA) Dalam Sistem Pengambilan Keputusan Pemilihan Jurusan Berbasis Minat Siswa
Di era digital sekarang ini dibutuhkan kemampuan individu yang lebih kreatif dan inovatif diberbagai bidang, sehingga siswa SMK harus lebih mempersiapkan kompetensinya. Dalam hal ini kompetensi berkaitan dengan jurusan yang mereka pilih. Rata-rata siswa salah mengambil jurusan sekitar 35%, ikut teman sekitar 50%, untuk siswa yang benar-benar tepat memilih jurusan 15%. Untuk hal ini maka dibutuhkan metode sistem pendukung keputusan MOORA dalam hal mennetukan jurusan sesuai dengna minat dan bakat siswa. Pengembangan sistem menggunakan metode Waterfall. Tujuan penelitian ini mendesain sistem pendukung keputusan yang dapat digunakan untuk pemilihan jurusan sesuai minat siswa dengan memanfaatkan keputusan hasil metode MOORA. Hasil dari penelitian ini menggambarkan perhitungan MOORA untuk pemilihan jurusan maka calon siswa mendapatkan keputusan untuk memilih jurusan Multimedia karena memiliki nilai tertinggi