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Smatika Jurnal : STIKI Informatika Jurnal
Published by Universitas Bhinneka Nusantara
ISSN : 20870256     EISSN : 25806939     DOI : https://doi.org/10.32664/smatika
Core Subject : Science,
Computer Science & IT
SMATIKA: STIKI Informatika Jurnal is a journal published by Lembaga Penelitian & Pengabdian kepada Masyarakat (LPPM) of Universitas Bhinneka Nusantara Malang. The scope of this journal in the field of Computer Science, Information Systems, and Information Management.
Arjuna Subject : Ilmu Komputer (semua kategori) - Sistem Informasi
Articles 300 Documents
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Design and Implementation of an ESP32-Based Smart Home Electricity Monitoring and Control Module Using MQTT Dash and Telegram Integration Muh Asnoer Laagu; Bayu Retno Joyo Nendriyo; Iftiqori Fiqi Anshori; Immawan Wicaksono; Ali Rizal Chaidir
SMATIKA JURNAL : STIKI Informatika Jurnal Vol 16 No 02 (2026): SMATIKA Jurnal : STIKI Informatika Jurnal
Publisher : LPPM Universitas Bhinneka Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32664/smatika.v16i02.2321

Abstract

This study presents the design and implementation of an ESP32-based smart home box module that integrates multi-channel load control, real-time electrical energy monitoring, and automated user reporting within a single compact and modular system. The proposed module employs an eight-channel relay for household appliance control using the MQTT communication protocol, with MQTT Dash providing real-time visualization and manual control. Electrical parameters, including voltage, current, active power, and cumulative energy consumption (kWh), are measured using a PZEM-004T sensor and transmitted continuously via MQTT. The main contribution of this work lies in the unified system architecture that consolidates device control, energy measurement, and user interaction without reliance on proprietary cloud platforms. In addition to dashboard-based monitoring, a Telegram bot is integrated to deliver real-time system status notifications, on-demand energy reports summarizing average power and total consumption, and fully automated 24-hour periodic reports. This dual interaction mechanism enables both active real-time supervision and passive long-term monitoring, addressing limitations commonly found in prior IoT smart home implementations. Experimental evaluations confirm that the proposed system operates reliably, responsively, and with acceptable measurement accuracy for residential applications. All relays on the eight-channel module respond stably to ON/OFF commands from the MQTT Dash interface with delays of less than one second, ensuring dependable real-time control. The PZEM-004T-based monitoring subsystem provides voltage, current, power, and energy data with power measurement errors ranging from 0.83% to 2.66%, which is suitable for daily household energy monitoring. Tests under various single and combined load conditions demonstrate consistent detection of power variations. Overall, the results indicate that the proposed smart home box module provides a practical, low-cost, and scalable solution for integrated IoT-based residential energy control and monitoring.
Analisis Segmentasi Kunjungan Wisata Menggunakan Algoritma K-Means pada Dinas Pariwisata Kutai Kartanegara Rully Wijaya Saputra; Nursobah; Ahmad Abul Khair
SMATIKA JURNAL : STIKI Informatika Jurnal Vol 16 No 02 (2026): SMATIKA Jurnal : STIKI Informatika Jurnal
Publisher : LPPM Universitas Bhinneka Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32664/smatika.v16i02.2324

Abstract

Kutai Kartanegara Regency possesses abundant and diverse tourism potential that can contribute significantly to regional economic development. Nevertheless, tourism visitation data has generally been utilized only for administrative documentation and reporting purposes, limiting its role in supporting strategic decision-making. Therefore, a data-driven approach is required to identify the characteristics and performance of tourism destinations more effectively. This study aims to analyze and segment tourism destinations in Kutai Kartanegara Regency using the K-Means Clustering algorithm. The research employed secondary data obtained from the Kutai Kartanegara Tourism Office covering the period from 2023 to 2025. Three variables were used in the clustering process, namely total domestic tourist visits (Wisnus), total international tourist visits (Wisman), and seasonal visitation fluctuations. Prior to clustering, the data underwent preprocessing and normalization to improve clustering performance. The Elbow Method was applied to determine an appropriate number of clusters, resulting in a three-cluster solution representing high-, medium-, and low-visitation categories. The clustering process successfully grouped 56 tourism destinations into 28 destinations in the medium-visitation cluster, 12 destinations in the high-visitation cluster, and 16 destinations in the low-visitation cluster. Furthermore, model evaluation using the Silhouette Score produced a value of 0.4288, indicating a moderate and acceptable level of cluster quality. The findings provide a comprehensive overview of tourism destination performance and can support policymakers in prioritizing destination development, improving resource allocation, and formulating more targeted tourism promotion strategies to enhance regional tourism competitiveness.
Comparative Analysis of Transfer Learning-Based Deep Learning Models for Jatropha Leaf Disease Classification Sarifah Agustiani; Sulistiyah; Agus Junaidi; Cucu Ika Agustyaningrum; Yoseph Tajul Arifin
SMATIKA JURNAL : STIKI Informatika Jurnal Vol 16 No 02 (2026): SMATIKA Jurnal : STIKI Informatika Jurnal
Publisher : LPPM Universitas Bhinneka Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32664/smatika.v16i02.2325

Abstract

Plant disease identification is essential for enhancing agricultural productivity and promoting sustainable crop management practices. Jatropha curcas has considerable potential as a biofuel-producing plant; however, its growth and productivity can be significantly affected by various leaf diseases. Conventional disease diagnosis often requires substantial time and relies heavily on expert knowledge, creating a need for automated solutions based on deep learning techniques. Although deep learning has been widely applied in plant disease recognition, comparative studies focusing on transfer learning models for Jatropha leaf disease classification remain limited, particularly for datasets characterized by distinctive visual features and relatively small sample sizes. This research conducts a comparative assessment of several deep learning architectures to determine the most effective model for classifying Jatropha leaf diseases. The evaluated architectures include MobileNetV2, EfficientNetB0, ResNet50, DenseNet121, and VGG16. All models utilized ImageNet pre-trained weights and were adapted through fine-tuning of the final classification layers to accommodate a dataset containing healthy and diseased Jatropha leaf images. Experimental findings reveal that ResNet50 achieved the highest classification accuracy of 93.81%, followed by VGG16 at 93.58% and EfficientNetB0 at 90.49%. In comparison, DenseNet121 and MobileNetV2 attained accuracies of 85.40% and 74.56%, respectively. Model effectiveness was assessed using accuracy, training duration, confusion matrix analysis, and ROC curve evaluation to examine classification capability across categories. The results demonstrate that ResNet50 offers the most balanced combination of predictive accuracy and performance stability. Overall, the study confirms that transfer learning-based deep learning models are highly effective for Jatropha leaf disease classification, with ResNet50 emerging as the most suitable architecture among those investigated. These findings may serve as a valuable reference for the development of reliable and efficient plant disease detection systems in agricultural environments.
Design and Development of a Web-Based Audit Clearance Letter Application System Using PHP Framework at the Karanganyar Inspectorate Wahyu Putri Sholefah; Nova Tri Romadloni
SMATIKA JURNAL : STIKI Informatika Jurnal Vol 16 No 02 (2026): SMATIKA Jurnal : STIKI Informatika Jurnal
Publisher : LPPM Universitas Bhinneka Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32664/smatika.v16i02.2330

Abstract

This research aims to design and develop a web-based Audit Clearance Letter application system at the Karanganyar Regency Inspectorate using the Laravel framework and MySQL database. The previous manual administrative process caused delays in verification, difficulties in tracking application status, and risks of data recording errors. This study adopted the Research and Development (R&D) methodology in conjunction with the Waterfall development model, which encompasses five sequential phases: requirements specification, system design, implementation, verification, and operational maintenance. The architectural foundation of the system was established upon the Model-View-Controller (MVC) pattern, selected to ensure a more organized, secure, and sustainable application structure. The results indicate that the system successfully integrates application submission, document upload, verification, letter issuance, and real-time status tracking within a single digital platform. Black Box Testing conducted on 14 testing scenarios achieved a 100% success rate and improved administrative efficiency from 2–3 working days to less than 1 working day in the verification and document monitoring process. In addition, User Acceptance Testing (UAT) achieved a User Satisfaction Index (USI) score of 88.2%, categorized as “Very Satisfactory.” The novelty of this research lies in the integration of a web-based Audit Clearance Letter administrative service specifically designed to improve transparency and efficiency in government supervisory institutions.
Rancang Bangun Sistem E-Survey Berbasis Web dengan Fitur Speech-to-Text Menggunakan Metode Waterfall M. Aziz Kurniawan; Yumna Zahran Ramadhan; Muhammad Solehuddin; Deki Satria; Sasmi Hidayatul Yulianing Tyas
SMATIKA JURNAL : STIKI Informatika Jurnal Vol 16 No 02 (2026): SMATIKA Jurnal : STIKI Informatika Jurnal
Publisher : LPPM Universitas Bhinneka Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32664/smatika.v16i02.2331

Abstract

Web-based electronic survey systems are widely used in higher education due to their efficiency and flexibility in data collection. However, many existing survey platforms still rely on conventional text-based input and provide limited accessibility support for users with disabilities. This study aims to develop a web-based E-Survey system integrated with a speech-to-text feature to improve accessibility and support inclusive participation in digital survey activities. The system was developed using the System Development Life Cycle (SDLC) with the Waterfall method, covering requirements analysis, system design, implementation, and testing. Accessibility considerations were based on the Web Content Accessibility Guidelines (WCAG) 2.1, while speech-to-text functionality was implemented using Automatic Speech Recognition (ASR) technology. System evaluation included black box testing, WCAG-based accessibility assessment, and speech-to-text performance testing using Accuracy and Word Error Rate (WER) metrics. The results indicate that all selected accessibility criteria evaluated in this study were successfully implemented and were consistent with the selected WCAG 2.1 principles assessed through developer-based inspection. The speech-to-text feature achieved an accuracy rate of 85.71% and a Word Error Rate (WER) of 5.41%. These findings demonstrate that the proposed system provides a more accessible and inclusive survey environment by enabling respondents to complete surveys through text or voice input, while highlighting the potential of speech-to-text technology in supporting inclusive participation in higher education.
Cybersecurity Awareness and Community Response to Phishing Threats: An Indonesian Social Behavior Analysis Fadhil Rozi Hendrawan; Arif Rahman Hakim; Dewi Marini Umi Atmaja; Zaidan Mufaddhal
SMATIKA JURNAL : STIKI Informatika Jurnal Vol 16 No 02 (2026): SMATIKA Jurnal : STIKI Informatika Jurnal
Publisher : LPPM Universitas Bhinneka Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32664/smatika.v16i02.2332

Abstract

This research discusses the increased levels of connectivity and digital engagement experienced by the people of Indonesia due to the development of digital technology as well as the risks associated with the growing prevalence of phishing cyber crimes in the country despite having the third-highest population of internet users globally. Although the level of digital literacy varies across different regions in the country, younger users in Indonesia appear to be the most vulnerable to phishing attacks. In view of the above, this paper seeks to identify and explore the behavioral dimensions that determine vulnerability to phishing amongst young internet users in Indonesia through a qualitative exploration of behavioral exposure towards such cyber crime. The research employs a quantitative cross-sectional survey method using structured questionnaires provided to 53 participants in their teens who were frequently involved in using digital platforms for purposes such as engaging on social media, making purchases from e-commerce sites, and executing payments via digital platforms, all chosen using a purposive sample method. Validity and reliability were measured using the Principal Component Analysis, the Kaiser-Meyer-Olkin validity test, Bartlett's Test of Sphericity and Cronbach's Alpha test respectively. Validity tests produced a KMO measure of 0.587 with a statistically significant Bartlett test result (χ²=71.940, df=10, p<0.001). Using PCA, two factors contributing 70.997% cumulative variance were identified with Eigenvalue values of 2.299(45.98%) and 1.251(25.02%). The first factor measures active reception of links via digital platforms and the second measures exposure to bypassing attempts via OTP channels. The four-item scale had a Cronbach Alpha of 0.743 implying acceptable internal consistency.
YOLOv11-Based AIoT System for Automated Size Detection and Counting of G0 Seed Potatoes Using MQTT Protocol Alvandi Fredik Sembiring; Indah Permatasari; Prasetyo Yuliantoro
SMATIKA JURNAL : STIKI Informatika Jurnal Vol 16 No 02 (2026): SMATIKA Jurnal : STIKI Informatika Jurnal
Publisher : LPPM Universitas Bhinneka Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32664/smatika.v16i02.2336

Abstract

The increasing demand for G0 seed potatoes in Indonesia, reaching approximately 143,740 tons in 2021 while only 8.6% of the demand could be supplied, highlights the need for more efficient production and monitoring systems at the early stage of the potato seed supply chain. Current manual sorting and counting processes are labor-intensive, time-consuming, and prone to human error, creating a need for an automated and reliable monitoring solution. This study develops and implements an Artificial Intelligence of Things (AIoT) system based on the YOLOv11n object detection algorithm for real-time detection, size classification, and counting of G0 seed potatoes. The proposed system integrates a conveyor belt, a Logitech C922 Pro USB webcam for image acquisition, and a laptop as the edge computing unit running the YOLOv11n model. Detection results are transmitted through the MQTT protocol to a Node-RED dashboard for real-time remote monitoring. Unlike conventional approaches, the system combines a lightweight YOLOv11n model with MQTT communication to support simultaneous multi-category size classification and synchronized dashboard visualization. Detected potatoes are classified into three size categories (small, medium, and large) based on calibrated bounding-box pixel areas validated with potato farmers. The model was trained and evaluated using four epoch configurations (25, 50, 75, and 100 epochs) with Precision, Recall, F1-score, mAP@0.5, and mAP@0.5–0.95 as evaluation metrics. The 100-epoch model achieved the best performance, with precision approaching 1.00, recall of approximately 0.98, mAP@0.5 of 0.986, and mAP@0.5–0.95 of 0.96. Validation confirmed that calibrated geometric measurements matched the physical potato dimensions, while dashboard data were fully consistent with edge-computing outputs. These findings demonstrate that the proposed YOLOv11n-based AIoT system provides accurate, reliable, and real-time monitoring of G0 potato production, offering a practical solution to improve operational efficiency and data accuracy in Indonesia's potato seed supply chain.
Implementasi Metode Naive Bayes dan Natural Language Processing pada Sistem Deteksi Berita Hoax Online Berbasis Web Mohammad Ainur Rofiqi; Ahmad Heru Mujianto
SMATIKA JURNAL : STIKI Informatika Jurnal Vol 16 No 02 (2026): SMATIKA Jurnal : STIKI Informatika Jurnal
Publisher : LPPM Universitas Bhinneka Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32664/smatika.v16i02.2338

Abstract

The rapid growth of digital media in Indonesia has accelerated the spread of hoax news, which poses serious threats to public trust and social stability. Based on data from the Ministry of Communication and Informatics of the Republic of Indonesia, a total of 12,547 hoax contents were identified from 2018 to 2023, while 1,923 new hoax contents emerged in 2024 alone. This research aims to design and build a web-based hoax news detection system by implementing the Multinomial Naive Bayes algorithm combined with Natural Language Processing (NLP) techniques. The system processes text through five NLP stages: sentence splitting, case folding, tokenizing, stopword removal, and stemming using PySastrawi. Feature weighting is performed using TF-IDF (Term Frequency–Inverse Document Frequency), and classification is executed using the Multinomial Naive Bayes algorithm enhanced with Laplace Smoothing and Log Posterior Probability. The output is converted using the Softmax function to produce probability percentages for each sentence. A manual calculation simulation using 10 training sentences and one test narrative containing four sentences was conducted to verify the algorithm. The system successfully classified the test narrative as hoax with a probability of 62.00% hoax and 38.00% non-hoax, consistent with the actual label. The system was evaluated using a Confusion Matrix on a 50-sentence test dataset, achieving Accuracy of 90.00%, Precision of 91.67%, Recall of 88.00%, and F1-Score of 89.80%. The resulting system provides a practical tool for the public to verify the credibility of news information in the digital era.
Pengembangan Sistem Penandatanganan Digital pada Layanan Sertifikasi Elektronik Berbasis Public Key Infrastructure Diaz Seno Hutomo; Wakhid Kurniawan
SMATIKA JURNAL : STIKI Informatika Jurnal Vol 16 No 02 (2026): SMATIKA Jurnal : STIKI Informatika Jurnal
Publisher : LPPM Universitas Bhinneka Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32664/smatika.v16i02.2348

Abstract

Digital transformation in the modern era shifts documents from physical to electronic formats, improving administrative efficiency but simultaneously introducing new vulnerabilities like identity fraud, content manipulation, and signature repudiation. To mitigate these risks, this research successfully designs a robust digital certification service system ensuring data integrity, sender authenticity, and non-repudiation. The methodology adopted an experimental observational approach through software development based on the Waterfall model. It was evaluated using thirty PDF certification documents on a server environment running Go 1.26, an AMD Ryzen 7 4700 processor, and 16 GB RAM. The system architecture integrates a React.js frontend for visual interaction and a Golang backend focused purely on cryptographic computation. Its security infrastructure employs a Public Key Infrastructure (PKI) model, integrating the 2048-bit RSA algorithm for asymmetric key encryption and SHA-256 for document identity hashing. Testing revealed the signature placement mechanism succeeded with an average single-signature execution time of 8.05 ms, displaying zero failures across all documents. Employing binary byte structure analysis and the Force Binary Download method successfully eliminated false positive anomalies caused by browser metadata modifications, which were independently validated via OpenSSL and Python scripts  in Google Colab. In conclusion, this electronic certification service platform effectively facilitates real-time document verification, provides absolute protection of data integrity, and ensures the validity of authentication in accordance with Indonesian legal standards for electronic transactions.
Design of a Web-Based QR Code Attendance System with Real-Time Notifications at Darul Arqom Junior High School Karanganyar Abid Nasiruddin; Wakhid Kurniawan
SMATIKA JURNAL : STIKI Informatika Jurnal Vol 16 No 02 (2026): SMATIKA Jurnal : STIKI Informatika Jurnal
Publisher : LPPM Universitas Bhinneka Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32664/smatika.v16i02.2352

Abstract

The rapid development of information technology has encouraged educational institutions to implement digital transformation in administrative management, including student attendance systems in Islamic boarding schools. SMP Darul Arqom Karanganyar still uses a manual paper-based attendance system that often causes recording errors, delays in attendance recapitulation, difficulties in monitoring student attendance, potential data manipulation, and delays in delivering attendance information to parents. These problems indicate that the attendance management process is inefficient and requires a more integrated digital solution. This study aims to design and develop a web-based attendance system using QR Code technology integrated with real-time notifications to improve the efficiency, accuracy, and transparency of student attendance management. The novelty of this research lies in integrating QR Code-based attendance validation with automatic real-time notifications for parents in a system specifically designed for the Islamic boarding school environment. Unlike previous attendance applications that mainly focus on digital attendance recording, the proposed system emphasizes attendance transparency, fraud prevention, and direct communication between schools and parents. The system was developed using the Agile Development method through iterative sprint-based stages, including planning, design, development, testing, evaluation, and implementation. The system utilizes the CodeIgniter framework, MySQL database, and QR Code technology for attendance validation. The results show that the system accelerates the attendance process, minimizes fraudulent attendance practices, improves attendance data accuracy, and assists administrators in monitoring attendance data efficiently. In addition, the system increases information transparency through direct real-time notifications to parents. Therefore, the system can support administrative digitalization and student discipline management in Islamic boarding schools.

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