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INDONESIA
Sistemasi: Jurnal Sistem Informasi
Published by Universitas Islam Indragiri
ISSN : 23028149     EISSN : 25409719     DOI : -
Core Subject : Science, Engineering,
Computer Science & IT Electrical & Electronics Engineering
Sistemasi adalah nama terbitan jurnal ilmiah dalam bidang ilmu sains komputer program studi Sistem Informasi Universitas Islam Indragiri, Tembilahan Riau. Jurnal Sistemasi Terbit 3x setahun yaitu bulan Januari, Mei dan September,Focus dan Scope Umum dari Sistemasi yaitu Bidang Sistem Informasi, Teknologi Informasi,Computer Science,Rekayasa Perangkat Lunak,Teknik Informatika
Arjuna Subject : -
Articles 920 Documents
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Literature Review: A Comparative Study of Waste Classification using Deep Learning Algorithms Ikhlas, Ariza; Hendrik, Billy
Sistemasi: Jurnal Sistem Informasi Vol 14, No 3 (2025): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v14i3.5163

Abstract

Waste type classification remains a daily challenge in modern waste management. Proper waste classification contributes significantly to environmental protection and enhances the efficiency of the recycling process. Unfortunately, manual waste classification is rarely performed by individuals, resulting in mixed waste that is difficult to separate into recyclable and non-recyclable categories. This leads to increased waste accumulation, which becomes harder to process over time. Therefore, automating this procedure using computer vision is of critical importance. This study adopts a Systematic Literature Review (SLR) methodology to analyze existing research conducted by previous scholars. The main objectives are to identify the most appropriate algorithms for waste type classification, determine the most suitable model architectures, and examine the correlation between dataset size, number of classes, and classification accuracy. The results of the literature review show that the Convolutional Neural Network (CNN) algorithm is widely used and considered highly effective for computer vision tasks. Among the best-performing models are: A standard CNN architecture achieving 100% accuracy with 150 data points and 3 classes, CNN with ResNet50 model achieving 99.41% accuracy on 2,527 data points and 6 classes, A combination of ResNet, k-Nearest Neighbors (kNN), and Neighborhood Component Analysis (NCA) achieving 99.35% accuracy on 13,089 data points and 1,672 classes, CNN with CapSA ECOC + ANN model reaching 99.01% accuracy on 1,515 data points and 12 classes. These findings indicate that numerous prior studies have successfully developed high-accuracy models for waste classification, which can serve as a solid foundation for building computer vision systems to automate the waste sorting process.
Conversion Prediction in Google Search Ads Keyword Selection Using the K-Nearest Neighbor and C4.5 Algorithms Harahap, Muhammad Sya'ban; Muhammad, Alva Hendi
Sistemasi: Jurnal Sistem Informasi Vol 14, No 3 (2025): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v14i3.5174

Abstract

This study was conducted to analyze and compare the effectiveness of two algorithms—K-Nearest Neighbor (K-NN) and C4.5—in predicting keyword conversion on the Google Ads platform. With the rapid growth of digital marketing, selecting the right keywords has become crucial for improving conversion rates. The research utilized a dataset of 673 entries with 12 relevant attributes, collected from historical ads and the Google Ads Keyword Planner. A comparative experimental approach was employed, with the data split into training (80%) and testing (20%) sets. The analysis revealed that the C4.5 algorithm achieved higher accuracy (85.41%) compared to K-NN (74.86%). Evaluation was based on metrics such as accuracy, precision, recall, and F1-score, which indicated that C4.5 was more effective in predicting conversions using the given dataset. These findings offer valuable insights for advertisers aiming to optimize their ad campaigns by selecting more effective keywords. However, the study also acknowledges limitations and recommends further research using larger and more diverse datasets to enhance model accuracy.
Security Analysis of the Final Project Information System (SITASI) Website using Penetration Testing Method Renaldi, Rengga; Fronita, Mona; Ahsyar, Tengku Khairil; Jazman, Muhammad
Sistemasi: Jurnal Sistem Informasi Vol 14, No 5 (2025): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v14i5.5406

Abstract

The Final Project Information System (SITASI) website plays a critical role in supporting academic administrative processes at the Faculty of Science and Technology, UIN Sultan Syarif Kasim Riau. This study aims to evaluate the website’s security level following recent maintenance using penetration testing, conducted with the OWASP Zed Attack Proxy (ZAP) tool. The testing revealed eight vulnerabilities, including two classified as medium risk, four as low risk, and two informational. The medium-risk issues involved the absence of an Anti-CSRF token and the lack of a Content Security Policy (CSP), both of which could expose the system to attacks such as CSRF and XSS. The low-risk findings included loading JavaScript from third-party domains, information disclosure via X-Powered-By and Server headers, and the absence of HTTP Strict Transport Security (HSTS). The two informational findings involved suspicious comments in the code and improper Cache-Control settings. Remediation actions were implemented based on OWASP security best practices, including the integration of CSRF tokens, configuration of CSP and HSTS headers, and removal of sensitive information from server responses. A follow-up evaluation confirmed that all identified risks had been successfully mitigated. This study highlights that penetration testing combined with standard-based mitigation is effective in enhancing web application security resilience, particularly within academic environments.
Design of Umrah Registration Information System PT Amanah Wisata Group using Waterfall Method Setyanto, Rangga; Setiaji, Pratomo; Muzid, Syafiul
Sistemasi: Jurnal Sistem Informasi Vol 14, No 4 (2025): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v14i4.5266

Abstract

This study aims to replace the manual registration system still used by PT Amanah Wisata Group with a web-based digital system. Previously, 80% of the registration process was conducted manually, often leading to errors and delays, including having to wait up to two working days to receive registration forms. The research methodology includes the collection of primary data through interviews with administrative staff and direct observation of the registration process, as well as secondary data from literature reviews and relevant documentation. The system development follows the Waterfall method, consisting of requirement analysis and system design using Unified Modeling Language (UML). The registration system also integrates a Customer Relationship Management (CRM) approach to foster stronger relationships with prospective pilgrims, improve two-way communication, and enable faster and more accurate delivery of Umrah package information and notifications. The results show that the developed system consists of three main modules: an online registration module, a pilgrim data management module, and a payment module. This system enhances administrative efficiency, reduces data entry errors, improves staff performance, and strengthens customer interaction. In conclusion, the web-based information system combined with a CRM approach not only supports the digital transformation of Umrah services but also enhances service quality and the overall experience of prospective pilgrims.
Evaluation of Artificial Neural Network Model for Predicting Nitrogen Oxides (NOₓ) Concentration Arsyada, Muhammad Farrih Mahabbataka; Tyasnurita, Raras
Sistemasi: Jurnal Sistem Informasi Vol 14, No 3 (2025): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v14i3.4371

Abstract

Nitrogen Oxides (NOₓ) are air pollutants that require serious attention due to their potential negative impacts on human health, the environment, and the economy. This research is crucial to provide accurate predictive models of NOₓ concentration, which can serve as a foundation for decision-making and effective air pollution mitigation measures. The objective of this study is to evaluate several artificial neural network (ANN) models to determine the most effective model for accurately predicting NOₓ concentrations. One of the methods used for predicting air pollution data, such as NOₓ, is artificial neural networks (ANN). In this study, four ANN models were constructed and evaluated: Feed Forward Neural Network (FNN), Time Lagged Neural Network (TLNN), Seasonal Artificial Neural Network (SANN), and Long Short-Term Memory (LSTM). The models predict NOₓ concentration using data from the air quality dataset provided by the UCI Machine Learning Repository. Testing results indicate that the LSTM model performs best, achieving the lowest error value, characterized by 24 input nodes, three hidden nodes, one output node, and 300 training epochs. The RMSE values for LSTM, FNN, TLNN, and SANN are 57.3, 62.8, 64, and 89, respectively.
Design and Implementation of an ETL Pipeline for Prospective Student Data Analysis in Higher Education Admissions Setiyawati, Nina; Bangkalang, Dwi Hosanna; Asmara, Gilang Windu
Sistemasi: Jurnal Sistem Informasi Vol 14, No 5 (2025): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v14i4.5158

Abstract

The number of universities in Indonesia continues to grow. This condition certainly makes the flow of new student admissions increasingly competitive between universities, thus encouraging universities to do branding, show quality, and do the right positioning. Therefore, it is important for universities to adopt a data-driven approach that can provide in-depth insights into prospective students and the effectiveness of marketing strategies. The purpose of this study is to design and build an ETL (Extract, Transform, Load) pipeline to collect, process, and analyze prospective student data as part of the business intelligence (BI) system to be built. The proposed ETL architecture design supports automated microservices-based data transformation in data cleaning, normalization, and integration. In addition, it can also be used as a solution to increase the scalability and flexibility of data mobilization in the BI system. This study introduces a novel approach by designing an ETL pipeline within a business intelligence framework aimed at enhancing university marketing efforts. Unlike prior research, which has primarily applied business intelligence tools to evaluate academic activities within learning management systems, this work shifts the focus to marketing analytics. Additionally, while existing studies on higher education marketing often center around digital marketing techniques and the marketing mix, this research fills a gap by proposing a technical infrastructure that supports data-driven marketing through automated ETL processes. The resulting ETL was tested using several methods, namely Source to Target Count Testing, Source to Target Data Testing, Duplicate Data Check Testing, and Data Transformation Testing. The results of each test are valid
Improving the Usability of the Sumber Alam Express Ticket Booking Application using the Heuristic Evaluation Method Kurniawan, Rizki Candra; Frobenius, Arvin Claudy
Sistemasi: Jurnal Sistem Informasi Vol 14, No 4 (2025): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v14i4.5221

Abstract

This study aims to evaluate improvements in the usability quality of the Sumber Alam Express application prototype using the Heuristic Evaluation method. The test results show that out of the ten heuristic evaluation factors, nine received high/agree ratings, while one factor received a moderate/neutral rating. There was a significant improvement across all factors compared to the previous study. Notably, "help users recognize, diagnose, and recover from errors" increased by 43.7%, and "help and documentation" improved by 42.5%. The only factor that remained at a neutral level was "flexibility and efficiency of use," which was due to the absence of shortcut features in the prototype—despite the application's flow remaining clear and easy to understand. The validity test indicated that one questionnaire item was invalid, mainly due to the limited number of respondents. This study involved 10 purposively selected respondents with diverse backgrounds, including employees and students who are active users, users of similar applications, and a frontend developer. Although the number of respondents was smaller than in the previous study, the diversity and depth of their experience ensured a comparable level of data representativeness. This research acknowledges its limitations, particularly the small sample size and partial instrument validity, both of which were constrained by time and resource limitations during the data collection process.
Social Media Adoption in the Marketing Strategy of Radiant Buket SME: A UTAUT Model Approach Bindas, Asniati; Pawirosumarto, Suharno; Lusiana, Lusiana; Sari, Silvia
Sistemasi: Jurnal Sistem Informasi Vol 14, No 4 (2025): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v14i4.5330

Abstract

The advancement of digital technology has encouraged SMEs to adopt social media as part of their marketing strategies to enhance customer engagement and expand market reach. This study aims to analyze the factors influencing social media adoption by Radiant Buket SME using the Unified Theory of Acceptance and Use of Technology (UTAUT) model. The key variables examined include performance expectancy (PE), effort expectancy (EE), social influence (SI), and facilitating conditions (FC), which are hypothesized to affect behavioral intention (BI) and actual use behavior (UB) of social media. Radiant Buket’s marketing strategy involves the use of platforms such as Instagram and TikTok for product promotion, direct customer interaction, and the dissemination of information and testimonials through visual content. The findings show that PE and SI have a positive influence on BI, indicating that perceived usefulness and social encouragement drive the intention to adopt social media. Although EE has a negative effect, it still significantly influences BI, suggesting that users are willing to adopt social media despite perceiving it as requiring more effort. Additionally, FC positively affects UB, and BI significantly impacts UB, indicating that strong intention indeed leads to actual usage behavior. These findings offer practical insights for Radiant Buket in strengthening its digital marketing strategy, particularly through customer-oriented promotional content, enhanced two-way interaction on social media, and the optimization of support resources such as staff training and digital infrastructure. Theoretically, this study enriches the literature on technology adoption in the context of Indonesian SMEs, particularly in applying the UTAUT model within digital marketing. It also highlights the importance of a data-driven approach in developing sustainable and effective social media marketing strategies.
Development of Joomla based Website for Mapping and Location Information of Waste Disposal Sites in Palembang Wibagso, Stefanus Setyo; Adi, Steven
Sistemasi: Jurnal Sistem Informasi Vol 14, No 3 (2025): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v14i3.4965

Abstract

Waste is a problem that occurs in many areas. Palembang City is no exception, which will contribute 1,180 tons of waste per day in 2023. One solution that can be offered to reduce the amount of waste scattered around is the existence of a website that provides map information and the location of Temporary Waste Disposal Sites (TPS). This website facilitates the retrieval of information regarding local waste disposal sites, enabling individuals to locate them swiftly and effortlessly, thus promoting the proper disposal of waste at designated areas. For website development, researchers will use CMS Joomla and the Phoca Maps extension. The design stages adopt RAD methodology consisting of requirement planning, user design, construction, and cutover. In the functionality assessment, accurate results were achieved for Map Search and locations categorized by Specific Area Categories and TPS Names. The results obtained from this research are that the website provides information on maps and TPS locations. Joomla CMS, along with the Phoca Maps extension, offers benefits in terms of convenience, affordability, and ease of managing maps and location markers. Additionally, this study presents an alternative perspective on the use of Joomla CMS, which is typically associated with text or image content usage.
Comparison of Manhattan and Chebyshev Distance Metrics in Quantum-Based K-Medoids Clustering Solikhun, Solikhun; Siregar, Muhammad Rahmansyah; Pujiastuti, Lise; Wahyudi, Mochamad; Kurniawan, Deny
Sistemasi: Jurnal Sistem Informasi Vol 14, No 4 (2025): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v14i4.5193

Abstract

Anemia is a condition characterized by a decrease in the number of red blood cells or hemoglobin levels in the bloodstream. It can lead to fatigue and reduced productivity. Clustering is a technique in data mining used to identify patterns that can support decision-making processes. In the case of anemia, clustering plays a crucial role in identifying various severity patterns and understanding the contributing factors behind the condition. Quantum computers, which utilize the principles of quantum mechanics for information processing, have made significant advancements over the past decade. Quantum computing is an advanced method of information processing that leverages qubits, enabling systems to exist in multiple states simultaneously. This technology offers the potential to solve complex problems at exponentially faster speeds than classical computers. In this study, researchers applied the K-Medoids clustering algorithm, calculated using quantum-based equations. The research compares two distance measurement methods: Chebyshev distance and Manhattan distance. The results show that the Manhattan algorithm performs better in medical contexts, particularly for detecting positive cases, with a recall of 0.57 and an F1-score of 0.695, although it has a slightly lower precision of 0.88. This makes it more suitable for medical applications where false negatives carry high risks, such as disease detection, despite its higher cost and mean squared error (MSE). On the other hand, Chebyshev distance achieved perfect precision (1.0) and higher accuracy (80%), but its low recall (0.33) indicates that many positive cases were missed. Therefore, Manhattan distance is more recommended for medical applications that require the detection of more positive cases, while Chebyshev is more efficient for scenarios that prioritize accuracy and cost.

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