Teknik: Jurnal Ilmu Teknik dan Informatika
Teknik: Jurnal Ilmu Teknik dan Informatika ; eISSN: ISSN: 2798-2513; pISSN: 2808-8751 merupakan peer-reviewed journal yang mempublikasikan artikel-artikel ilmiah dalam bidang ilmu-ilmu Teknik dan Informatika yang meliputi bidang : Network Computer and Security, Computer Architecture Design, Data Mining & Big Data, Human Computer & Interaction, Sistem pakar (Expert System), Jaringan syaraf tiruan (Artificial Neural Network), Algoritma genetic, Penalaran komputer berbasis kasus (Case Based Reasoning), Agen Cerdas (Intelligent Software Agents), Geographical Information System, Decision Support System, Mobile Computing & Application, Projeck Management IT. Yang dikelola dan diterbitkan oleh LPPM Sekolah Tinggi Ilmu Ekonomi - Studi Ekonomi Modern. Artikel-artikel yang dipublikasikan di Jurnal Ilmu Teknik dan Informasi meliputi hasil penelitian ilmiah asli (prioritas utama) dan artikel ulasan ilmiah yang bersifat baru (tidak prioritas) dari berbagai kalangan akademisi dan peneliti yang belum diterbitkan di tempat lain. Teknik: Jurnal Ilmu Teknik dan Informatika terbit secara berkala tiap 6 bulanan, yaitu pada Mei dan Oktober.
LPPM Sekolah Tinggi Ilmu Ekonomi - Studi Ekonomi Modern
Analisis Sentimen Komentar Netizen Terhadap 17+8 Tuntutan Rakyat Pada X Menggunakan Naive Bayes Classifier
This study analyzes netizen sentiment concerning the 17+8 public aspirations circulating the digital platform X spanning the period from August 18 through October 31, 2025. 1,837 comments obtained through scraping method. Classification Research stages include data preprocessing, sentiment weighting based on lexicon, and feature extraction using TF-IDF. Data 80% used for learning purposes and the remaining 20% utilized for validation. The findings reveal that the majority of comments, amounting to 81.14%, contained negative sentiment, while the remaining 18.86% were positive. The outcomes demonstrate that community reactions toward the 17+8 People's Demands were dominated by unsupportive views. From a theoretical standpoint this scholarly work offers to enriching knowledge concerning public opinion classification on political issues through a computational approach, while also serving as a reference for future research focused on improving the accuracy of sentiment analysis related to political dynamics and the behavior of state institutions.
Sentiment Analysis; 17+8 People’s Demands; Naïve Bayes Classifier,X
Copyright (c) 2026 Teknik: Jurnal Ilmu Teknik dan Informatika https://creativecommons.org/licenses/by-sa/4.0
Analisis Sentimen Masyarakat Terhadap Objek Wisata Di Kabupaten Lahat Menggunakan Algoritma Support Vector Machine
Nature tourism is one of the sectors that plays an important role in supporting the development of regional tourism, including in Lahat Regency, which has significant waterfall tourism potential. Currently, many visitors share their reviews and experiences through digital platforms such as Google Maps. This review can be used as a source of information to understand the public's evaluation of the quality of tourist attractions. This study aims to examine public perception of tourist attractions in Lahat Regency using the Support Vector Machine (SVM) method. Research data were collected through scraping from Google Maps, totaling 500 reviews from five tourist attractions, namely Curup Maung, Curup Buluh, Senyawe Waterfall, Panjang Waterfall, and Green Canyon. The research stages include data preprocessing, consisting of cleaning, case folding, normalization, tokenization, stopword removal, and stemming. After that, feature extraction was carried out using the TF-IDF method and the classification process using the SVM algorithm. Based on the research results, the Support Vector Machine (SVM) method is able to perform sentiment classification quite well, although the accuracy level varies for each tourist attraction. Curup Maung and Panjang Waterfall achieved the highest accuracy level of 90%. Nevertheless, most visitor reviews were dominated by negative sentiments. This indicates that there are still several aspects that need to be improved, particularly related to tourist facilities and services. This research is expected to serve as a consideration for tourism managers and local governments in efforts to improve management quality as well as the development of tourism in Lahat Regency.
Sentiment Analysis; Google Maps; Tourist Attractions; Support Vector Machine; Text Mining.
Implementasi Data Mining Menggunakan Metode RapidMiner Untuk Optimasi Manajemen Akademik Di SMK Secang
Education in vocational high schools (SMKs) requires effective data management to improve students’ academic achievement and discipline. At SMK Islam Secang, students’ academic scores and attendance data have so far functioned merely as administrative archives, making it difficult to identify patterns of student performance. This study aims to classify students based on academic achievement and discipline by applying the K-Means Clustering algorithm using RapidMiner. The data used in this study consist of scores from six subjects and attendance records of 35 students from the Light Vehicle Engineering (TKR) department over two semesters. The data were obtained from original school records, compiled using Microsoft Excel, and processed in RapidMiner. The clustering process employed four clusters for academic achievement and two clusters for discipline, with Euclidean Distance used as the similarity measure. The results show that in the first semester, students were grouped into four academic achievement clusters: high achievement (6 students), moderate achievement (7 students), potentially problematic (14 students), and problematic (8 students). In the second semester, the distribution changed to high achievement (19 students), moderate achievement (14 students), potentially problematic (4 students), and problematic (1 student). Meanwhile, student discipline was divided into two clusters: disciplined (31 students) and undisciplined (4 students). These results demonstrate that K-Means Clustering is effective in mapping student conditions, revealing patterns in academic performance and attendance, and supporting educational evaluation, learning planning, and early detection of students who require academic or disciplinary intervention. Keywords: Data Mining, K-Means Clustering, Academic Achievement, Discipline, RapidMiner, Vocational High School (SMK)
Data Mining; K-Means Clustering; Academic Achievement; Discipline; RapidMiner; Vocational High School (SMK)
Rancang Bangun Sistem Diskusi Hukum Islam Berbasis Multi-Agent AI dengan Metode Retrieval-Augmented Generation (RAG) pada Platform Web Bahtsul Masail
The development of generative artificial intelligence has opened opportunities for strengthening Islamic legal learning through a digital forum that remains connected to authoritative textual references. This study aims to design and build a web-based bahtsul masail discussion system using a multi-agent AI architecture and the Retrieval-Augmented Generation (RAG) method. The proposed system simulates the deliberative roles commonly found in pesantren-based Islamic legal discussion, namely Moderator, Mubahits, Mu'aridh, and Mushahih. The research applies a Research and Development approach with the Waterfall model, covering requirement analysis, interface design, multi-agent workflow design, implementation, functional testing, and evaluation. RAG is implemented by allowing users to upload PDF documents of kitab kuning and assign the documents to particular agent roles. The uploaded texts are then used as contextual grounding so that each agent can formulate arguments, rebuttals, and final decisions based on traceable references rather than unsupported model memory. The application is implemented using HTML, CSS, and JavaScript on the front end, while the AI reasoning process is orchestrated through an API-based large language model. Functional testing shows that the system can complete five sequential stages of bahtsul masail, display role-based responses, manage uploaded references, and present discussion history. The main contribution of this study is a system design that combines pesantren deliberation procedures with AI-based retrieval support to provide an interactive learning medium for Islamic law, while emphasizing that the final authority of legal validation remains with qualified scholars
Copyright (c) 2025 Teknik: Jurnal Ilmu Teknik dan Informatika https://creativecommons.org/licenses/by-sa/4.0
Pengembangan Prototipe Detektor Kebakaran Cerdas dengan Sensor Suhu, Kelembapan, dan Api Berbasis IoT (Studi Kasus: Dinas Pendidikan Kabupaten Semarang)
Fire disasters can occur at any time in residential areas or schools, which are often triggered by electrical short circuits, the use of gas stoves, to minor negligence such as cigarette butts. As a preventive effort of Department of Education of Semarang, this research aims to create a prototype of a microcontroller-based early detection and fire suppression system with C programming. This tool uses NodeMCU as a control center that integrates fire sensors and DHT11 sensors to monitor room temperature in real-time. If the system detects any indication of fire or a significant temperature spike, a buzzer will activate as a warning alarm and the fan will work automatically to assist the initial extinguishing process.
Perancangan Aplikasi Pelaporan Kerusakan Infrastruktur Publik Berbasis Android di Pulau Lepar Kabupaten Bangka Selatan untuk Mendukung Konsep Smart Island
This study aims to design and develop an Android-based public infrastructure damage reporting application on Lepat Island, South Bangka Regency, as an effort to support the Smart Island concept. The background of this study is the continued use of a manual reporting system that causes delays in handling and a lack of transparency. The method used is Agile which includes the stages of system design, implementation, testing and periodic evaluation. Data collection techniques are carried out through observation, interviews, and literature studies. The results of the study are an Android-based application that allows the public to report infrastructure damage with features to upload photos, descriptions, and GPS-based locations. In addition, the application provides report history and status monitoring features to increase transparency. The implementation results show that the use of mobile technology can improve service efficiency, speed up the reporting process, and increase community participation. This application is expected to support the implementation of Smart Governance and Smart Island in the region.
Android Applications, Infrastructure Reporting, Public Services, Smart Governance, Smart Island
Perancangan Sistem Penerjemah Bahasa Isyarat bagi Tunarungu dan Tunawicara Berbasis Pengolahan Citra Digital dan Text-to-Speech
Communication is an essential human right, yet a significant communication gap persists between individuals with sensory disabilities, specifically the deaf and speech-impaired, and the general public. While many technological solutions have been proposed to translate sign language, existing models primarily rely on heavy deep learning architectures such as Convolutional Neural Networks (CNN) or Recurrent Neural Networks (RNN/LSTM). These models often demand high computational power, leading to latency and limiting real-time application on standard devices. This study proposes a lightweight, fast, and highly responsive sign language translation system specifically designed to recognize static alphabets (A-Z) and single-character air writing. The system utilizes MediaPipe for hand tracking, where feature extraction is intelligently processed by calculating the relative spatial coordinates of fingertips to the wrist, reducing dependency on raw camera coordinates. Classification is performed using a Support Vector Machine (SVM) with a Radial Basis Function (RBF) kernel, prioritizing computational efficiency without sacrificing accuracy. To enhance user experience, the system introduces three key novelties: smart relative feature extraction, an anti-duplication hold system with a 1-second timer to prevent input spamming, and a non-blocking multithreaded audio execution (Daemon Thread) utilizing Google Text-to-Speech (gTTS), ensuring the webcam feed remains fluid during audio playback. Additionally, an alternative air-writing mode is integrated, utilizing geometric heuristics and PyTesseract OCR to read single drawn letters in the air. The results indicate that the proposed system operates swiftly and efficiently, bridging the communication barrier with a hardware-friendly approach.
Air Writing, BISINDO, MediaPipe, Support Vector Machine, Text-to-Speech
Perbandingan Algoritma Divide and Conquer dan Searching pada Pengolahan Data Nilai Mahasiswa Berbasis Web
The rapid digital transformation in educational institutions demands an efficient student grade data processing system capable of handling workloads responsively. This study aims to analyze and compare the efficiency of sorting algorithms (Merge Sort and Quick Sort) and searching algorithms (Linear Search and Binary Search) on a web-based platform. The research method employed is laboratory experimental, testing algorithm performance across various data volume stratifications, ranging from 50 to 1000 entities, using the V8 JavaScript engine. Research findings indicate that Quick Sort possesses superior speed compared to Merge Sort due to its efficient in-place sorting architecture, which minimizes memory overhead and Garbage Collection activity. Furthermore, a performance anomaly was discovered where the Just-In-Time (JIT) Compiler mechanism optimizes execution on large data volumes through a warm-up phase. In the searching aspect, Binary Search demonstrates superior O(log n) logarithmic stability compared to Linear Search, which risks causing interface freezing on massive data. The implication of this study is the critical importance of implementing data pre-sorting protocols to exploit logarithmic search speeds to ensure academic information system scalability. The integration of appropriate algorithms proves to be a crucial foundation in maintaining web application responsiveness amidst the ever-increasing escalation of educational data.
Algoritma Searching, Algoritma Sorting, Binary Search, Data Mahasiswa, Quick Sort.
Copyright (c) 2021 Teknik: Jurnal Ilmu Teknik dan Informatika https://creativecommons.org/licenses/by-sa/4.0
Analisis Komparatif XGBoost dan Temporal Fusion Transformer (TFT) pada Time Series Forecasting Harga Solana
Cryptocurrency price prediction, particularly for highly volatile assets like Solana (SOL), is a crucial challenge in time series data analysis in digital finance. This study aims to compare the performance of the XGBoost machine learning algorithm with the Temporal Fusion Transformer (TFT) deep learning model in predicting Solana's daily closing price. The dataset used consists of historical Solana price data and network fundamentals data in the form of Total Value Locked (TVL). The research process includes data preprocessing, dividing training and test data, model training, and evaluation using the Root Mean Squared Error (RMSE) metric. The results show that using the same-day price feature has the potential to cause target leakage, resulting in invalid prediction accuracy. In testing using pure historical data without data leakage, the XGBoost model performed better than TFT with an RMSE of 4.27, while TFT produced an RMSE of 18.59. Furthermore, the integration of network fundamentals data in the form of TVL did not improve prediction accuracy and even caused a decrease in performance for the XGBoost model with an RMSE of 7.10. The results of this study show that the use of historical price action features is more effective than fundamental network indicators for short-term daily Solana price predictions.
Solana; XGBoost; Temporal Fusion Transformer (TFT); On-Chain Data; Machine Learning
Clustering Pola Intensitas Curah Hujan Berbasis Data Radar NOAA NEXRAD Level II Menggunakan Algoritma K-Means
Accurate classification of rainfall intensity patterns is important for early warning systems, hydrometeorological risk assessment, and water resource management. Surface rain gauges have limited spatial coverage, so this study uses NOAA NEXRAD Level II radar data from the KTLX station in 2023. K-Means clustering was applied to identify rainfall intensity patterns from 30 randomly selected days, with scans stratified into four daily time intervals. Seven features were extracted from each radar sweep, including reflectivity statistics, convective and stratiform ratios, and rainfall coverage. The data were normalized and balanced before clustering. The optimal cluster count was determined through a combined evaluation of the Elbow Method, Silhouette Score, and Davies-Bouldin Index, yielding K=5 as the most representative configuration. Evaluation results demonstrated a Silhouette Score of 0.3871 and a Davies-Bouldin Index of 0.8599, indicating moderate cluster cohesion that reflects the inherent overlapping nature of rainfall intensity transitions in radar reflectivity data. The clusters represent rainfall regimes from non-precipitating conditions to intense convective events. These results support the use of K-Means for automated rainfall pattern recognition and flood forecasting applications.
K-Means clustering, NEXRAD Level II, radar reflectivity, rainfall intensity, unsupervised learning.
Perbandingan Algoritma Greedy dan Dynamic Programming pada Penyelesaian Knapsack Problem untuk Optimasi Pemilihan Barang
Optimization problems in computer science often arise when a system must select the best combination from several alternatives under limited resources such as capacity, time, or cost. One commonly used optimization model is the Knapsack Problem, which involves selecting a number of items with specific weights and values to obtain the maximum profit without exceeding the available capacity. This study aims to analyze and compare the performance of the Greedy algorithm and Dynamic Programming in solving the 0–1 Knapsack Problem. The research employs a quantitative experimental approach by implementing both algorithms in a computer program and testing them on several datasets with different sizes. The evaluation parameters include the maximum value obtained and the algorithm execution time. The results show that the Greedy algorithm has faster execution time and more efficient memory usage, but it does not always produce an optimal solution. In contrast, the Dynamic Programming algorithm consistently produces an optimal solution, although it requires greater computational time. Therefore, the choice of algorithm should be adjusted to system requirements, whether prioritizing computational efficiency or optimal solution quality.
Algoritma Greedy; Analisis Performa; Dynamic Programming; Knapsack Problem; Optimasi.
Simulasi Sensor Fotodioda Pada Sistem Lampu Otomatis Berbasis Arduino
This study discusses the design and simulation of an automatic lighting system based on a photodiode sensor using an Arduino Uno microcontroller as the main controller. The system is designed to detect changes in ambient light intensity and automatically control the lamp without human intervention. The photodiode sensor is used as a light detector that converts light energy into an analog electrical signal, which is then processed by the Arduino to determine bright or dark conditions. The output from the Arduino subsequently controls a relay module that functions as an electronic switch to connect or disconnect the current to the light bulb. The research method employed is an experimental approach, which includes system planning, hardware design, software programming, simulation using Proteus, and system performance testing. The simulation results indicate that the system operates as expected, where the lamp automatically turns on when the light intensity decreases and turns off when the ambient brightness increases. This system is expected to improve electrical energy efficiency and provide ease of operation for lighting control, particularly in public facilitiesand workplace environments.
Arduio Uno; Automatic Lightning System; Photodiode sensor
Analisis Performa PID, Fuzzy-PID, dan Model Predictive Control (MPC) untuk Pengaturan Ketinggian Air Bendungan
This study analyzes the performance of three types of controllers—PID, Fuzzy-PID, and Model Predictive Control (MPC)—in maintaining water level stability in a dam system. Proper water level regulation is essential to prevent flooding, ensure adequate water distribution, and maintain the structural safety of the dam. Previous studies have widely implemented PID and Fuzzy-PID controllers; however, MPC offers significant advantages through system prediction and multivariable optimization. This research compares the performance of the three controllers through simulation analysis using a second-order mathematical model. The results indicate that MPC has the potential to deliver a faster settling time and a smaller steady-state error compared to PID and Fuzzy-PID, although it requires higher computational complexity.
Fuzzy-Pid, MPC, dam System, Water Level, Control System
Penerapan Metode SAW (Simple Additive Weight) Dalam Sistem Pendukung Keputusan Pemilihan Internet Service Provider
The use of internet network services is currently in high demand in various sectors, ranging from education, business, households, government, banking, industry, large companies, healthcare, entertainment and media, transportation, and public spaces. The SAW algorithm method is used to assist in making decision-making recommendations to determine internet services from providers that are more objective, accurate, and supported by good service. From the results of the research using four alternatives, namely ISP1, ISP2, ISP3, and ISP4, each alternative has the following weight values: ISP1 has a value of 83.54, ISP2 has a value of 87.80, ISP3 has a value of 87.75, and ISP4 has a value of 92.56. Therefore, the best alternative is ISP4 as the best internet service provider.
User-Centered Mobile Navigation: Evaluating Local Usability for Improved UX
Mobile navigation interfaces continue to be plagued by a key usability problem, particularly when widely accepted design traditions fail to address the specific requirements and mental models of local user populations. This research addresses this significant limitation by using a comprehensive user-focused measurement framework to identify and investigate context-dependent navigation problems in mobile applications. The research employed a multi-method qualitative approach, using in-depth questionnaires, semi-structured interviews, and laboratory-based usability testing of 15 participants on an interactive Figma prototype that simulated real-world navigation tasks. Our analysis, step by step, revealed significant navigation issues in the local context, as evidenced by a 73% task-completion rate and an average participant error of 2.8 across the core navigation tasks. The most significant usability issues were ambiguous iconography, inconsistent application of platform design patterns, and insufficient system feedback mechanisms. The results conclusively demonstrate that localized usability testing is not merely beneficial but necessary while creating genuinely good and accessible mobile experiences. The study provides a replicable, practical context-aware evaluation approach and tangible, right-now-applicable design recommendations, such as enhancing icons with descriptive text labels and using instant visual feedback mechanisms. The study provides developers and designers with tangible takeaways for significantly enhancing navigation user experience without sacrificing methodological availability or implementation convenience across different development environments.
Resilient Federated Learning Against Injection and Evasion Attacks in Edge Smart Grids: A Simulation Study
The modernization of smart grids through edge computing introduces significant cybersecurity challenges, most stemming from adversarial machine learning attacks that compromise distributed intelligence. Although Federated Learning is an appealing decentralized model training paradigm for edge smart grids, its resilience against coordinated injection and evasion attacks has not yet been thoroughly explored. To address this critical gap, we develop and evaluate a resilient Federated Learning model for edge-based innovative grid applications. Under a rigorous simulation-based experimental design, we created a controlled environment based on synthetic energy-demand data and implemented adversarial attack scenarios to ensure model robustness. We propose a resilience enhancement layer in our framework during the federated aggregation process to curtail malicious model updates and adversarial inferences. The results show significant improvement in the stability of the proposed model under attack, maintaining a robustness index above 0.62, whereas baseline approaches exhibit complete degradation. This corresponds to a reduction of approximately 34% in the attack impact rate across different-intensity attack scenarios, while maintaining high stability in aggregation. In addition to the adversarial testing framework in the domain of Federated Learning, this work provides a validated resilience model that secures analytics of smart grids without requiring access to raw data. Our methodology presents a resource-efficient alternative to physical testing and enables safe yet comprehensive security evaluation in critical infrastructure applications.
Adaptive Fuzzy Logic Integration for Optimizing Decision Support Systems under Data Uncertainty
Decision Support Systems (DSS) can become inaccurate when used with imprecise, incomplete, or dynamically changing data. Fuzzy logic techniques based on conventional methodologies may be strong at handling vagueness, but are unable to adapt their behavior in response to different data distributions on their own. This paper recommends the creation of an Adaptive Fuzzy Logic Integration Framework that dynamically updates membership functions and rule weights in response to data variation to enhance decision accuracy under uncertainty. The described framework combines Fuzzy Inference Systems (FIS) with learning-based parameter update concepts borrowed from adaptive optimisation. The model was simulated and executed on a hybrid algorithmic platform that included gradient-based parameter tuning and iterative feedback learning. Experimental tests were conducted on uncertainty-generated data sets to compare adaptive and conventional fuzzy models in terms of ISME (Root Mean Square Error), convergence stability, and decision accuracy. Previous results show that the adaptive model achieves a 21.4% increase in accuracy and a 28% improvement in convergence rate compared to non-adaptive fuzzy systems. Moreover, the model ensures stable performance even in the presence of random data perturbations, demonstrating its ability to handle uncertainty. This book incorporates a self-tuning fuzzy decision model that converts static inference structures to dynamic evolving decision engines. The outcomes establish a foundation for next-generation smart DSS for real-time optimization in uncertainty.
Analisis Perbandingan Algoritma Penjadwalan Prioritas Preemptive dan Non-Preemptive Menggunakan Aplikasi Web Interaktif
CPU scheduling is a core function in modern operating systems that significantly impacts system performance and efficiency. Among various scheduling algorithms, Priority Scheduling is widely used and exists in two main variants: non-preemptive and preemptive. The non-preemptive mode allows a process to run to completion, while the preemptive mode can interrupt a running process for a higher-priority one. Understanding the behavioral differences between these modes is crucial but often challenging through manual calculations. To address this, an interactive web-based application was developed to simulate and visualize both preemptive and non-preemptive Priority Scheduling algorithms. The research method involved designing the system logic based on the core principles of each scheduling variant, followed by implementation using standard web technologies: HTML, Tailwind CSS, and JavaScript. The application allows users to input custom process data or load predefined case studies, select the scheduling mode, and instantly receive a comprehensive analysis. The results include a dynamically generated Gantt chart, a detailed performance metrics table (including turnaround time and waiting time), and a step-by-step execution log. Through a comparative analysis of a specific case study, the application is proven to be an effective educational tool. It accurately simulates both modes and visually demonstrates the impact of preemption on execution order, resource utilization, and key performance metrics, thereby simplifying the learning process for students and educators.
CPU scheduling, non-preemptive, preemptive, priority scheduling, web application
Jurnal Sistem Informasi Persediaan Barang Dengan Metode Buffer Stock Berbasis Web
Inventory management plays a crucial role in ensuring smooth business operations by preventing stockouts that may cause losses. Toko Cat Gani still relies on manual recording, which is prone to data loss, duplicate entries, and delays in stock reporting, thus requiring a systematic solution. This study aims to design and implement a web-based inventory information system using the buffer stock method to overcome these issues. The research method employed is Research and Development (R&D) with a prototype model, consisting of needs analysis, system design, validation, and testing stages. The system was developed using PHP, MySQL, and XAMPP, featuring item data management, supplier management, inbound and outbound transactions, buffer stock calculations, and real-time inventory reports. The implementation results show that the system facilitates transaction recording, minimizes data entry errors, provides notifications when stock reaches the minimum threshold, and generates accurate and timely reports. Expert validation and user testing confirm that the system is feasible and effective in supporting inventory management at Toko Cat Gani. Therefore, the implementation of a web-based inventory information system with the buffer stock method can be considered an efficient and reliable solution to improve accuracy and effectiveness in inventory control.
Information System; Inventory; Buffer Stock; Web
Evaluating Digital Readiness for Adopting Mobile-Based Public Service Information Systems in Rural Areas
In recent years, the Indonesian government has actively promoted digital transformation in public service delivery, including in rural and remote areas. However, digital adoption among communities in these regions remains inconsistent and often hindered by infrastructural and socio-cultural constraints. This study aims to assess the digital readiness of rural communities in adopting mobile-based public service information systems, with a specific focus on understanding the social and technological dynamics that shape their engagement. Employing a mixed methods approach with an explanatory sequential design, the research began with a structured survey involving 150-200 respondents per location, followed by in-depth interviews with key informants such as village officials, service operators, and local users. The quantitative data were analyzed using SPSS to identify general patterns in digital readiness based on the Technology Readiness Index and the Digital Readiness Framework, while qualitative insights were thematically analyzed using NVivo to uncover contextual factors. The findings reveal that while some respondents exhibit a moderate level of digital optimism, barriers such as unstable internet access, limited digital literacy, and fear of misusing technology significantly affect adoption rates. Furthermore, social support from family members emerged as a critical facilitator in overcoming these challenges. This study contributes to the discourse on inclusive digital transformation by highlighting the importance of integrating community-based support mechanisms into system design and policy planning. The implications suggest that successful digitalization efforts in rural areas must go beyond infrastructure development and address the social readiness of users through culturally sensitive and participatory approaches.
Perancangan dan Implementasi Website Sistem Antrian Bank Berbasis Queue untuk Efisiensi Pelayanan Nasabah
This study designs and implements Bank Jali, a web-based bank queue system that applies a queue data structure with the First In First Out (FIFO) principle to improve service efficiency. The research and development method includes requirement analysis, design, implementation, testing, and evaluation. The application is built with HTML, CSS, and JavaScript, storing queue data temporarily through localStorage so the entire process runs client-side without a dedicated server. Key features include online queue registration, digital ticket generation, real-time status monitoring with waiting-time estimation, and an admin dashboard for managing teller and customer service queues. Testing shows the system operates reliably, processes queues according to FIFO, and provides a practical, lightweight user experience across devices.
Bank Queuing System; Service Management; Service Efficiency; Queue; FIFO.
Pengembangan Sistem Informasi Pengelolaan Aset dan Barang Berbasis Web untuk Meningkatkan Efisiensi Inventaris di Perguruan Tinggi: Studi Kasus Universitas STEKOM Kampus Kendal
This study aims to design and develop a web-based Asset and Goods Management Information System (SIPAB) implemented at Universitas STEKOM, Kendal Campus. The primary issue in asset management at this institution lies in the continued use of conventional tools such as Microsoft Excel and Word, which are prone to errors and inefficiency in reporting and monitoring. The research method used is Research and Development (R&D) with the Waterfall development model. Data collection techniques include observation, interviews, and literature study. The result of this research is a web-based system comprising modules for asset data, maintenance, disposal, and reports accessible internally. The system is expected to improve the efficiency, accuracy, and security of campus asset management.
Information System; Asset Management; SIPAB; Web-based; Waterfall.
Perancangan dan Pembuatan Interface Komunikasi Data antara ECU Sepeda Motor dan Sistem Android
Penelitian ini bertujuan untuk merancang dan membuat interface komunikasi data antara Electronic Control Unit (ECU) sepeda motor dengan sistem Android. Masalah yang dihadapi oleh bengkel rumahan seperti Ngoprek Garage Motoshop adalah keterbatasan alat untuk mendeteksi kerusakan ECU secara otomatis. Penelitian ini menggunakan mikrokontroler ESP32 sebagai penghubung antara ECU dan aplikasi Android, yang dirancang menggunakan MIT App Inventor. Sistem ini mampu membaca data kesalahan (Diagnostic Trouble Code/DTC) dari ECU dan menampilkannya secara langsung pada aplikasi Android. Metode penelitian yang digunakan mencakup perancangan perangkat keras dan perangkat lunak, serta pengujian sistem terhadap sepeda motor Honda. Hasil menunjukkan bahwa sistem ini mampu membaca dan menampilkan kode DTC dengan akurasi yang cukup tinggi, meskipun terdapat keterbatasan pada pembacaan parameter data secara real-time. Sistem ini diharapkan menjadi solusi alternatif bagi bengkel kecil dalam melakukan diagnosa awal terhadap kerusakan ECU.
Android System; Communication Interface; DTC; ECU; ESP32
Rekomendasi Pemilihan Jurusan Bagi Siswa Baru Di SMK XYZ Menggunakan Metode Naive Bayes Dan Simple Additive Weighting ( SAW )
Pemilihan jurusan di Sekolah Menengah Kejuruan (SMK) merupakan tahap penting yang mempengaruhi arah pendidikan dan karier siswa di masa depan. Di SMK XYZ Kabupaten Tegal, pemilihan jurusan masih dilakukan secara konvensional dengan mempertimbangkan nilai rapor dan saran dari guru atau orang tua, yang cenderung bersifat subjektif dan tidak sepenuhnya memperhatikan potensi serta minat individual siswa. Untuk itu, penelitian ini bertujuan mengembangkan sistem pendukung keputusan (SPK) yang dapat memberikan rekomendasi jurusan secara objektif dan sistematis menggunakan dua metode, yaitu Naive Bayes dan Simple Additive Weighting (SAW). Naive Bayes, yang berbasis pada algoritma probabilistik, telah terbukti efektif dalam memprediksi ketuntasan belajar siswa, sementara SAW banyak digunakan dalam pengambilan keputusan multikriteria dengan memperhitungkan beberapa aspek kriteria seperti nilai rapor, hasil psikotes, dan minat siswa. Penelitian ini mengkomparasi kedua metode tersebut untuk menentukan mana yang lebih optimal dalam memberikan rekomendasi jurusan yang akurat dan sesuai dengan karakteristik siswa di SMK XYZ. Hasil penelitian diharapkan dapat memberikan solusi alternatif bagi sekolah dalam proses pemilihan jurusan yang lebih objektif, efisien, dan minim subjektivitas, serta dapat diterapkan pada proses pendidikan di SMK lainnya.
Evaluasi Incident dan Service Request Management pada Layanan e-Visa di Kantor Imigrasi Cirebon Menggunakan ITIL 4
This study evaluates the service maturity of the e-Visa system at the Class I TPI Cirebon Immigration Office with reference to two ITIL 4 practices: Incident Management and Service Request Management. Operationally, the office acts as a user while technical handling is centralized at a national helpdesk. A mixed-method approach was applied, combining staff/admin questionnaires with instrument validity, reliability checks, snapshot analysis of helpdesk tickets, and brief observations. The analysis identifies key issues: the absence of a locally agreed Service Level Agreement (SLA), delays in resolving high-priority incidents, and inconsistent communication of status and estimated time to resolution. Findings indicate a gap between perceived process maturity and ticket-based operational performance, especially for high-priority cases. The study proposes actionable improvements formalizing SLAs with the central team, a fast-track for urgent cases, concise submission guidance for routine requests, and results of the web-based recommendation dashboard. These results are relevant for similar user units operating under centralized support.
e-Visa; ITIL 4; Incident Management; Service Request Management; service maturity
Pengembangan Aplikasi Android Sistem Informasi Perpustakaan Sekolah
This research stems from the problem of manual book lending management in libraries, which often leads to obstacles such as delays in recording, data errors, and difficulties in monitoring collections. The main objective of this research is to design and develop a web-based library information system that can facilitate member data management, borrowing, and returning, as well as providing real-time book availability information. The method used is software development with a structured approach, through the stages of needs analysis, design, implementation, and testing with black box testing. The results of the study indicate that the system built is able to meet user needs, as evidenced by the successful testing that carried out all main functions without errors. The implications of this research are increased efficiency in library management and ease for students in borrowing and checking book availability. However, this research still has limitations in advanced features such as integration with the attendance system or automatic fine payments, so that these can be developed in future research.
Digital librar; Book lending; Information system; Web-based
Penerapan Eigenface pada Sistem Absensi Wajah Berbasis Android di RSU Khalishah
The development of information technology has encouraged institutions, including hospitals, to adopt digital systems to improve operational efficiency. One important aspect is the employee attendance system, which previously relied on fingerprints. This method has limitations, such as difficulty detecting when fingers are not in ideal condition and causing queues during peak hours. This research aims to design and implement an Android-based attendance system using the Eigenface facial recognition method as a faster, safer, and more accurate alternative. Eigenface works by extracting facial features using Principal Component Analysis (PCA), thus being able to efficiently recognize individual identities. The system was developed with MySQL database integration and tested on employees of Khalishah General Hospital. The implementation results showed that the system can recognize faces with a good level of accuracy and increase the effectiveness of attendance recording. Furthermore, the use of facial-based attendance can minimize the potential for fraud and increase user comfort because it does not require physical contact. Thus, the Eigenface method has proven feasible to be implemented as a modern attendance solution to support employee attendance management in hospital work environments and other institutions.
employee attendance; facial recognition; Eigenface; Android; PCA.
Analisis Efektivitas Layanan M-Paspor Berdasarkan ITIL V3 pada Kantor Imigrasi Kelas I TPI Cirebon
This study evaluates the effectiveness of M-Passport service management at the Immigration Office Class I TPI Cirebon using the ITIL V3 framework, focusing on Service Strategy and Service Operation. A quantitative approach was applied through observation, structured interviews, and questionnaires distributed to applicants and staff. Data were analyzed using Maturity Level assessment and GAP Analysis. The findings indicate that the M-Passport service has reached Level 4 (Managed) with an average score of 3.77, showing that processes are measurable, controlled, and consistently implemented. However, Incident Management remains at Level 3 (Defined) with the largest deviation from the expected level, while Problem Management, Request Fulfillment, and Business Relationship Management also show minor gaps. The study recommends strengthening incident handling procedures, enhancing communication strategies, improving applicants’ digital literacy, and increasing staff competencies. These improvements are expected to optimize ITIL V3 implementation and enhance technology-based public service delivery.
M-Passport; ITIL V3; Service Strategy; Service Operation; Maturity Level
Perancangan Aplikasi Pemesanan Catering Berbasis Web Pada Cafe D’Carlos
The development of information technology has affected a large number of sectors, one of which is the culinary industry, namely Cafe D'Carlos located in Parepare. This cafe has problems with the manual catering ordering process due to impracticality, recording errors, and long processing times. This study aims to design and develop a web-based catering ordering application to improve operational efficiency and service quality. In general, the development method for various applications tends to be the same depending on the case being handled. The method used includes several stages, namely: literature study, observation, system design using UML, implementation with PHP programming language and testing with the black box method. The features available in this application consist of main features including user registration, menu package selection, online ordering, payment, order and data management by the admin. The results of the application testing indicate that the system has run according to its function, namely it can reduce frequent order compliance, speed up the ordering process and increase customer satisfaction.
Cafe D’Carlos; catering ordering; web application; PHP.
Optimization of Logistics Electrical Systems with a Safety Approach
Electrical systems are fundamental infrastructures that support the operational continuity of logistics companies. However, without a structured approach to safety and optimization, these systems can become a source of inefficiency and risk. This study aims to analyze and optimize the use of electrical systems within logistics environments by applying a safety-oriented framework. The research investigates how electricity is distributed, utilized, and safeguarded in logistics companies and warehouses. Using a combination of observational methods and literature-based analysis, the study identifies critical issues related to energy reliability, system efficiency, and workplace safety. The findings are expected to contribute to the development of safer, more resilient, and energy-efficient electrical infrastructures in logistics operations. Keywords: Electrical system, logistics optimization, safety, warehouse, infrastructure.
Electrical system, logistics optimization, safety, warehouse, infrastructure