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Infotek : Jurnal Informatika dan Teknologi
Published by Universitas Hamzanwadi
ISSN : 26148773     EISSN : 26148773     DOI : -
Core Subject : Science, Engineering,
Computer Science & IT Control & Systems Engineering Engineering
INFOTEK Jurnal Informatika dan Teknologi Fakultas Teknik Universitas Hamzanwadi selanjutnya disebut Jurnal Infotek (e-ISSN: 2614-8773) merupakan Jurnal yang dikelola oleh Fakultas Teknik Universitas Hamzanwadi yang mempublikasikan artikel ilmiah hasil penelitian atau kajian teoritis (invited authors) dalam bidang (1) keilmuan informatika, (2) Rekayasa Perangkat Lunak, (3) Multimedia, (4) Jaringan Komputer, (5) Data Mining, (6) Image Processing, (7) Komputer Vision, (8) Mikrokontroller, (9) Robotik, (10) IOT yang belum pernah dipublikasikan. Jurnal Infotek diterbitkan oleh Fakultas Teknik Universitas Hamzanwadi dua kali setahun yaitu pada bulan Januari dan Juli. Jurnal Infotek Telah Terindeks pada Google Scholar.
Arjuna Subject : Ilmu Komputer (semua kategori) - Perangkat Lunak
Articles 458 Documents
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Rancang Bangun dan Evaluasi User Experience Sistem Short Link UNCP Menggunakan Metode System Usability Scale (SUS) Wisnu Kurniadi; Risna Sari; Erwin Sukma
Infotek: Jurnal Informatika dan Teknologi Vol. 9 No. 2 (2026): Infotek : Jurnal Informatika dan Teknologi
Publisher : Fakultas Teknik Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/jit.v9i2.34679

Abstract

Managing long URLs in higher education environments often poses challenges for efficient academic information dissemination. Universitas Cokroaminoto Palopo (UNCP) faces similar challenges, particularly in distributing links to academic information systems, research portals, and the Learning Management System (LMS). This study aims to design, develop, and evaluate an institution-based short link system deployed under the institutional subdomain short.uncp.ac.id, representing a distinctive institutional advantage over third-party services. The system was developed using the Agile Development methodology, adopting a three-tier architecture consisting of a React 18 and TypeScript-based presentation layer, a business logic layer handling URL validation and base-62 short code generation, and a data layer equipped with security mechanisms including link verification and institutional security badges. Core features include URL shortening, custom alias generation, QR Code generation, and a real-time analytics dashboard that processes click data in near real-time with visualizations of daily trends, user geographic distribution, and per-link engagement metrics. Usability evaluation was conducted using the System Usability Scale (SUS) method on 30 respondents from the UNCP academic community. The SUS instrument comprises 10 statements rated on a 1–5 Likert scale. Results indicate that the system achieved an average SUS score of 84.33, categorized as Excellent and graded B according to Bangor et al. (2009). These findings indicate that the UNCP short link system has a high level of usability and can be widely implemented across the campus environment. This study contributes to the development of an independent, secure, scalable, and institutionally branded academic digital infrastructure.
Implementasi Manajemen Bandwidth pada Jaringan WLAN Hotspot Berbasis MikroTik Menggunakan Metode Network Planning and Analysis (NPA) Taufik Rahman; Moh Faisal Abdullah
Infotek: Jurnal Informatika dan Teknologi Vol. 9 No. 2 (2026): Infotek : Jurnal Informatika dan Teknologi
Publisher : Fakultas Teknik Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/jit.v9i2.34698

Abstract

This study addresses the importance of stable and equitable internet access in WLAN hotspot networks, particularly in overcoming uncontrolled bandwidth usage that can degrade network service quality. The objective of this research is to implement bandwidth management on a MikroTik-based WLAN hotspot using the Network Planning and Analysis (NPA) method to improve network performance. The NPA method is applied through stages including problem identification, data collection, user needs analysis, network topology design, system implementation, and performance evaluation. The implementation utilizes hotspot features and Simple Queue to allocate bandwidth based on user requirements. Performance evaluation is conducted by comparing Quality of Service (QoS) parameters before and after implementation, including throughput, delay, jitter, and packet loss. The results show a 48% increase in throughput (from 1.25 Mbps to 1.85 Mbps), a 57.14% reduction in delay (from 280 ms to 120 ms), an 83.33% decrease in packet loss (from 6% to 1%), and a 68.42% reduction in jitter (from 95 ms to 30 ms). The main contribution of this study lies in integrating the NPA method with MikroTik-based bandwidth management through a user-based bandwidth planning approach, resulting in a more effective, measurable, and user-oriented network system.
Implementasi Automation Testing End-to-End Menggunakan Cypress pada Web E-Conference Parisada serta Evaluasi Efisiensi Pengujian Raditya Aria; Eri Haryanto; Ryan Ari Setyawan
Infotek: Jurnal Informatika dan Teknologi Vol. 9 No. 2 (2026): Infotek : Jurnal Informatika dan Teknologi
Publisher : Fakultas Teknik Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/jit.v9i2.34714

Abstract

Manual testing on interactive applications such as web e-conferences often faces constraints in the form of human error and long execution durations, especially in repetitive regression processes. This research aims to implement automated end-to-end (E2E) testing using the Cypress framework and evaluate the level of testing time efficiency on the Parisada platform. The research methodology includes designing core functionality scenarios covering the authentication process, system navigation, meeting room creation, and communication session termination. Testing was conducted through three trials (P1, P2, P3) to simulate various inhibiting variables, such as unstable network latency and user familiarity levels with the application interface. The results showed that all automated testing scenarios successfully achieved a 100% pass rate. In terms of efficiency, the use of Cypress significantly reduced the execution duration from an average of 60.0 seconds in manual testing to only 23.67 seconds in automated testing. Data analysis indicates an average time efficiency increase of 60.55%. Automated testing also proved to be more consistent and reliable in dealing with technical fluctuations compared to manual testing. In conclusion, the transition to automation testing using Cypress has proven highly effective in accelerating the quality assurance (QA) cycle and maintaining continuous software functionality stability on the Parisada application.
Pendekatan Interpretable Machine Learning untuk Analisis Keberhasilan Kampanye Pemasaran Menggunakan CatBoost dan SHAP Aprilisa Arum Sari; Oktalia Kumala Sari
Infotek: Jurnal Informatika dan Teknologi Vol. 9 No. 2 (2026): Infotek : Jurnal Informatika dan Teknologi
Publisher : Fakultas Teknik Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/jit.v9i2.34715

Abstract

Predicting the success of digital marketing campaigns remains a significant challenge due to the complex interactions among various variables, such as budget allocation and advertising channel selection. This study aims to develop a marketing analytics model that achieves high predictive accuracy while also providing clear interpretability of the prediction results. The study uses the SalesMind Marketing Campaigns 2026 dataset, which simulates 3,478 digital marketing campaign records from 2026. The dataset consists of categorical variables such as ad_channel and campaign_type, as well as numerical variables including marketing_spend, impressions, and conversion_rate as the prediction target. The proposed approach applies Interpretable Machine Learning by combining the CatBoost algorithm to predict conversion rates and SHAP (SHapley Additive exPlanations) to analyze the contribution of each variable. Model optimization was performed using GridSearchCV, resulting in excellent performance with an RMSE of 0.0012, an MAE of 0.005, and a coefficient of determination (R²) of 99.12%. The analysis results indicate that budget allocation is the most dominant factor in improving conversion rates without showing indications of diminishing marginal effectiveness. In addition, the use of interactive platforms such as Meta and TikTok significantly contributes to campaign effectiveness. These findings contribute to providing an accurate and informative predictive model that can support strategic decision-making in digital marketing management more effectively.
Rancang Bangun Sistem Rekomendasi Teman Belajar Berbasis Web untuk Kolaborasi Akademik Mahasiswa Bicanro Gebriyan Panjaitan; Lastri Putri Silaban; Azis Kurniadi; Debi Yandra Niska
Infotek: Jurnal Informatika dan Teknologi Vol. 9 No. 2 (2026): Infotek : Jurnal Informatika dan Teknologi
Publisher : Fakultas Teknik Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/jit.v9i2.34746

Abstract

The advancement of web-based information technology has encouraged the transformation of collaborative learning processes in higher education environments. However, students still experience difficulties in finding suitable study partners due to the absence of a system capable of integrating learning preferences, available schedules, and academic needs in a structured manner. This study aims to design and develop a web-based study partner recommendation system to support students’ academic collaboration through the EduMate platform. The research method used in this study is Research and Development (R&D) with a software development approach using the Prototype method. The research stages include user requirements identification, system requirements analysis, system design, prototype development, system implementation, and system testing using the Black Box Testing method. The system was developed using Node.js and Express.js on the backend side, HTML, CSS, and JavaScript on the frontend side, and MySQL as the primary database. The system also implements Google OAuth authentication, a scoring matching algorithm, study schedule management, automatic notifications, as well as rating and review features. The results of the study indicate that the EduMate system was successfully implemented and is capable of supporting the process of finding study partners in a more effective and structured manner. Based on the Black Box Testing results, all main system features operated according to the specified requirements with a testing success rate of 100%. The system is also able to provide study partner recommendations based on profile compatibility, learning preferences, and user schedules, thereby improving the effectiveness of collaborative learning among students. Therefore, EduMate has the potential to serve as a digital solution in supporting the collaborative learning ecosystem in higher education institutions.
Pengaruh Sistem Informasi Akuntansi dan Digital Marketing terhadap Kinerja Keuangan UMKM di Eks Karesidenan Surakarta Frido Oktaviandre; Nurita Elfani Prasetyaningrum; Ramadhian Agus Triono Sudalyo
Infotek: Jurnal Informatika dan Teknologi Vol. 9 No. 2 (2026): Infotek : Jurnal Informatika dan Teknologi
Publisher : Fakultas Teknik Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/jit.v9i2.34779

Abstract

This study aims to analyze the influence of Accounting Information Systems (AIS) and Digital Marketing on the Financial Performance of Micro, Small, and Medium Enterprises (MSMEs) in the Eks Karesidenan Surakarta region. The study employs a causal associative quantitative approach using a Likert-scale questionnaire distributed to 395 MSME respondents selected through Proportionate Stratified Random Sampling. Data analysis utilizes multiple linear regression. The results indicate that: (1) AIS has a positive and significant effect on MSME Financial Performance (t=5.803; Sig.=0.000); (2) Digital Marketing has a positive and significant effect (t=5.691; Sig.=0.000); and (3) simultaneously both variables have a positive and significant effect (F=47.382; Sig.=0.000) with an Adjusted R² of 52.4%.
Pengembangan Sistem Keamanan dan Pelacakan Sepeda Motor Pintar Berbasis Internet of Things (IoT) Menggunakan RFID dan GPS Ramli Ahmad; Mareta Julia Saputra; Ahwan Ahmadi
Infotek: Jurnal Informatika dan Teknologi Vol. 9 No. 2 (2026): Infotek : Jurnal Informatika dan Teknologi
Publisher : Fakultas Teknik Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/jit.v9i2.34784

Abstract

The high rate of motorcycle theft has become a significant issue that requires an effective and integrated technology-based solution. This study aims to develop a smart motorcycle security and tracking system based on the Internet of Things (IoT) by utilizing Radio Frequency Identification (RFID) technology as a user authentication system and the Global Positioning System (GPS) as a real-time vehicle tracking system. The methodology employed includes hardware and software design, integration of the RFID RC522 and GPS Neo-6M modules with an ESP32 IoT-based microcontroller, and system testing under eight usage scenarios covering RFID authentication, remote control and location requests via Telegram, GPS testing in open and covered areas, a power-supply test from the 12 V motorcycle battery, and a one-hour endurance test. The results indicate that the developed system is capable of enhancing vehicle security through an RFID-based authentication mechanism that only allows registered users to access the motorcycle. In addition, the GPS-based tracking feature enables accurate and real-time monitoring of the vehicle's location through a web-based or mobile application. The system performance evaluation shows a GPS tracking accuracy of ±3 meters in open areas, an RFID authentication response time of less than 1 second, and an average remote-control response time of 1–2 seconds via Telegram, although coordinate delivery was delayed in covered areas; the system also remained stable during a one-hour endurance test powered by the 12 V motorcycle battery. Therefore, the proposed system has the potential to serve as an innovative solution for improving motorcycle security and monitoring, as well as supporting the development of intelligent transportation technologies based on IoT.
Evaluasi Performa Random Forest Dengan Penyesuaian Threshold Klasifikasi Pada Prediksi Penyakit Jantung Lidya Shafadhila; Andreas Perdana
Infotek: Jurnal Informatika dan Teknologi Vol. 9 No. 2 (2026): Infotek : Jurnal Informatika dan Teknologi
Publisher : Fakultas Teknik Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/jit.v9i2.34799

Abstract

Heart disease remains one of the leading causes of death worldwide, necessitating an accurate prediction system to support early detection. This study aims to evaluate the performance of the Random Forest algorithm in predicting heart disease through the application of a threshold adjustment method. This research implements a Youden Index-based threshold adjustment, tested on the Statlog and Cleveland datasets, to assess the consistency of model performance across different data characteristics that share similar features. This method is utilized to determine the optimal threshold to achieve the best balance between recall and specificity. Additionally, the study analyzes the impact of threshold variations on accuracy, recall, specificity, and F1-score metrics to minimize false-negative errors and enhance the clinical relevance of the prediction results. Testing was conducted using the Cleveland Heart Disease Dataset and the Statlog Heart Disease Dataset with stratified sampling techniques. The results demonstrate that threshold adjustment significantly improves classification performance. The Cleveland dataset yielded an accuracy of 0.867, a recall of 0.893, and a Youden Index of 0.737 at an optimal threshold of 4.0, while the Statlog dataset achieved an accuracy of 0.833, a recall of 0.833, and a Youden Index of 0.667 at a threshold of 5.0. Overall, the combination of Random Forest and threshold adjustment proven to be effective in improving the quality of heart disease predictions.
Analisis Pengaruh Distance Metric Pada Algoritma K-Medoids Dalam Pengelompokan Kinerja Guru Menggunakan Silhouette Coefficent Rosmini; Muhammad Fadlan; Sinawati
Infotek: Jurnal Informatika dan Teknologi Vol. 9 No. 2 (2026): Infotek : Jurnal Informatika dan Teknologi
Publisher : Fakultas Teknik Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/jit.v9i2.34814

Abstract

This study aims to analyze the effect of distance metrics on the K-Medoids algorithm in clustering teacher performance based on pedagogical, personality, social, and professional indicators. This study was conducted because previous research on teacher performance clustering has generally focused more on the use of clustering algorithms without comparatively evaluating the effect of distance metric selection on the quality of the resulting clusters. The research data were obtained from assessor evaluations of teacher performance at SD Islam Al-Irsyad involving 16 teacher data records, which were first normalized to standardize the scale among attributes before the clustering process was carried out. Clustering was performed using the K-Medoids algorithm with Euclidean, Manhattan, and Cosine distance methods, as well as variations in the number of clusters (K) from 2 to 5 using RapidMiner. The clustering results were evaluated using the Silhouette Coefficient method calculated with Python to determine the cluster quality and the optimal number of clusters. The results showed that the highest Silhouette Coefficient value of 0.290 was obtained at K=4 using the Euclidean and Manhattan methods. Based on these results, the Euclidean method was selected as the best method because it is more widely used and capable of representing the distance between data points more effectively. The clustering results were then analyzed by assigning labels to each cluster based on the average value of the indicators to facilitate interpretation. Thus, this study demonstrates that the selection of distance metrics affects the quality of clustering results in teacher performance grouping.
Prediksi Kualitas Udara Berbasis Citra Menggunakan Pre-Trained Inception V3 dalam Perspektif Keberlanjutan Aliyah Kurniasih; Cantika Nur Previana; Andi Purnomo
Infotek: Jurnal Informatika dan Teknologi Vol. 9 No. 2 (2026): Infotek : Jurnal Informatika dan Teknologi
Publisher : Fakultas Teknik Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/jit.v9i2.34839

Abstract

Advances in artificial intelligence are driving the optimization of deep learning models for image analysis. Air pollution is a significant environmental problem that impacts human health and the balance of ecosystems. Increased emissions from industrial activities, transportation, and the burning of fossil fuels are major factors contributing to deteriorating air quality in various regions. This study aims to analyze the influence of data preprocessing and training strategies on model performance, including the removal of duplicate image data, data splitting, data augmentation, the use of class weights on training data, and learning rate tuning using the Inception V3 transfer learning model. The results show that the combination of these strategies achieved an accuracy of 89.28% with an error rate of only 0.338, demonstrating stability and good model generalization capabilities. The application of appropriate and effective preprocessing and training strategies enhances model performance. Consequently, a more accurate and reliable model can support data-driven decision-making more efficiently and contribute to various sectors such as health and the environment in supporting sustainable development.

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