Jurnal Teknik Informatika dan Teknologi Informasi
Journal Title:Jurnal Teknik Informatika dan Teknologi Informasi (JUTITI) Initials: JUTITI Frequency: April, Agustus, dan Desember. Print ISSN: 2827-9379 Online ISSN:2827-9387 Editor in Chief: Dr. Eng. Ir. Wahyul Amien Syafei, S.T., M.T., IPM. DOI: 10.55606 Publisher: Lembaga Pengembangan Kinerja Dosen Jurnal Teknik Informatika dan Teknologi Informasi (JUTITI) : ISSN: 2827-9379 (cetak), 2827-9387 (Online) berfokus pada penerbitan artikel berkualitas tinggi yang didedikasikan untuk semua aspek penelitian, masalah, dan perkembangan terbaru di bidang Teknologi Informatika dan Teknologi Informasi.Jurnal ini terakreditasi SINTA 5 (Surat Keputusan Direktur Jenderal Pendidikan Tinggi, Riset, dan Teknologi Nomor 10/C/C3/DT.05.00/2025 tanggal 21 Maret 2025 tentang Peringkat Akreditasi Jurnal Ilmiah Periode I Tahun 2025) dimulai dari Volume 2 Nomor 2 Tahun 2022 sampai Volume 7 Nomor 1 Tahun 2027. Artikel dapat ditulis dalam bahasa Inggris atau bahasa Indonesia. Indexed by: Journal Sponsors and Partners :
Implementasi Metode Simple Additive Weighting pada Sistem Pendukung Keputusan Deteksi Dini Mahasiswa Beresiko Drop Out
This researchaims to develop a Decision Support System (DSS) based on theSimple Additive Weighting (SAW) method to detect students who are at risk of dropping out early. The problem of high dropout rates in higher education is often caused by delays in identifying student swho are at academic risk, so a system is needed that is capable ofobjective, rapid, and structured assessment. The study uses five main criteria, namely the number of failed credits, academic leave/inactive status,frequency of late payments, GPA, and remaining study period. Student data is processed through the SAW stages, starting from the formation of a decision matrix,normalization, to the calculation of preference values to determine the drop out risk ranking DO risk. The implementation results show that the system is capable of producing calculations that are fully consistent with manual calculations, thusproving the accuracy and validity of the system's calculation process. This systemis expected to assist academic staff in early detection, so that interventions for at-risk students can be carried out more quickly and effectively.
Copyright (c) 2025 Jurnal Teknik Informatika dan Teknologi Informasi https://creativecommons.org/licenses/by-sa/4.0
Implementasi Sistem Smart Parking Menggunakan Raspberry Pi Pico W Berbasis Internet Of Things
This study aims to design and implement an Internet of Things (IoT)-based Smart Parking system using a Raspberry Pi Pico W as the main controller and the Telegram Bot API as the user interface. The system is developed to monitor parking space availability in real time and to operate an automatic gate using a servo motor. The research methodology includes hardware design, microcontroller programming in Python, and integration with Telegram Bot for remote notifications and control. Experimental results show that the system can accurately detect parking status changes with 100% accuracy and respond in less than two seconds. The use of Telegram Bot enables efficient and lightweight remote access without the need for additional applications or complex servers. This study demonstrates that the integration of IoT and cloud messaging services provides an effective solution for intelligent parking systems that enhance efficiency, automation, and support the development of smart city concepts.
Copyright (c) 2026 Jurnal Teknik Informatika dan Teknologi Informasi https://creativecommons.org/licenses/by-sa/4.0
Sistem Penghitung Jumlah Produk Industri Berbasis ESP32-CAM Dengan Deteksi Real Time
This study develops a real-time industrial product counting system using the ESP32-CAM module to address efficiency and accuracy challenges in production automation. The main problem investigated is the reliance on manual counting, which is prone to errors, and the use of expensive device-based systems that are less accessible to small and medium-sized industries. The research aims to design a low-cost system capable of accurately and rapidly detecting and counting products, integrated with an Internet of Things (IoT) platform for real-time notifications. The methods used include the implementation of the Tiny You Only Look Once version 3 (Tiny-YOLOv3) algorithm for object detection on the ESP32-CAM, image preprocessing to enhance detection quality, and integration with Telegram to send product count notifications. Testing was conducted in an industrial simulation environment with varying product quantities (5, 10, 20, 50) and lighting conditions (optimal: 500–700 lux; low: 200–300 lux). The results showed the highest detection accuracy of 92.3% under optimal lighting for 5 products, an average processing time of under 1 second for up to 20 products, and notification reliability above 93%. This system offers a cost-effective and scalable solution, although accuracy decreases under low lighting and larger product quantities. The research contributes to industrial automation through affordable technology.
Prediksi Kelulusan Siswa Berdasarkan Nilai Akademik Menggunakan Algoritma Perceptron
Early monitoring of the risk of student non-graduation at the secondary school level is important so that learning interventions can be carried out in a timely and data-driven manner. This study aims to apply the Perceptron algorithm as a simple machine learning method to predict student graduation status using academic score data, namely UTS and UAS. This approach was chosen because it is lightweight, easy to interpret, and relevant to support educational decision-making. The evaluation of model performance was carried out using accuracy, precision, recall, F1-score, and confusion matrix metrics. The results showed that the Perceptron model was able to classify students who passed with high precision of 0.86, but had limitations in recognizing students who did not pass which was reflected in the recall value of 0.60. An overall accuracy of 0.55 and an F1-score of 0.71 indicate that the model's performance is still affected by data imbalances and limitations of linear separation. These findings suggest that Perceptron has potential as an early tool for predicting graduation, but improved data quality, feature additions, and the use of nonlinear models are recommended for further research.
Pemanfaatan Teknologi Informasi dalam Peran Polisi Lalu Lintas Polsek Padang Bolak dalam Meningkatkan Kesadaran Hukum Bagi Pengendara di Bawah Umur
The development of information technology has had a significant impact on various aspects of life, including traffic law enforcement. The utilization of technology by law enforcement agencies can serve as an effective means of increasing public legal awareness, particularly among underage riders who frequently commit traffic violations. This study aims to examine how information technology is utilized by the Traffic Police of the Padang Bolak Sector Police and to what extent it influences the enhancement of public legal awareness. This research employs a descriptive qualitative method, with data collected through interviews, observations, and documentation. The results indicate that the use of social media, digital reporting systems, and technology-based socialization activities constitutes the primary strategies for delivering legal messages to the public. The utilization of technology has proven effective in expanding the reach of legal education and accelerating two-way communication between the police and the community. However, limitations in human resources, low levels of digital literacy, and insufficient community participation remain challenges that need to be addressed.
Evaluasi Kinerja Sistem Peminjaman Buku di Perpustakaan SMP Santo Leo II dengan Pendekatan Pieces
This study evaluates the Performance of the book lending system at the SMP Santo Leo II Library using the PIECES framework. The lending process is still fully manual, which affects the accuracy, speed, and Efficiency of Services. Data were collected through observation, interviews, documentation, and questionnaires involving 45 respondents. The questionnaire results show that the overall Performance of the system remains low: Performance (1.96), Information (1.79), Economy (1.90), Control (1.75), Efficiency (2.01), and Service (1.90). These scores fall within the low to very low categories. The findings indicate frequent inconsistencies in book availability data, slow transaction handling during peak hours, limited Control and data security, and inefficient workflows due to the absence of a computerized system. Users also experience difficulties in locating books and delays in returning them because no structured reminder system exists. The study concludes that the existing manual system is no longer adequate to support library operations, and a computerized library Information system is urgently needed to improve accuracy, Service speed, and overall operational Efficiency.
Opini Publik terhadap Pernyataan Presiden Prabowo tentang Proyek Whoosh: Analisis Sentimen Komentar YouTube Menggunakan Multinomial Naive Bayes dalam Perspektif Commentary Engagement
YouTube plays a crucial role in shaping and expressing public opinion on national political issues. President Prabowo Subianto's statement regarding the Whoosh High-Speed ​​Rail project in the video "Tegas! Prabowo: Apa Itu Ribut-Ribut Whoosh, Saya Tanggung Tanggung" (Firm! Prabowo: Apa Itu Ribut-Ribut Whoosh, Saya Tanggung Tanggung) sparked a variety of responses in the comments section. This study aims to analyze public comment sentiment and its relationship to user engagement levels. The method used is sentiment analysis based on the Multinomial Naive Bayes algorithm with TF-IDF weighting, through text preprocessing and K-Fold Cross Validation (k = 2, 5, and 10) validation stages. The best results were obtained with the 10-fold scheme with an accuracy of 79.45%, a precision of 82.05%, and a recall of 79.45%. The sentiment distribution shows a dominance of neutral sentiment (59.41%), followed by negative (26.81%) and positive (13.78%), indicating a tendency for users to express opinions informatively and critically. The engagement level is relatively low with an average of 2.61 likes, 0.30 replies, and an engagement score of 0.0036. Correlation analysis shows that sentiment does not have a significant effect on engagement, so sentiment analysis is more appropriate for monitoring public opinion than predicting user engagement.
Perbandingan Metode Naïve Bayes dan Support Vector Machine untuk Analisis Sentimen pada Ulasan Pengguna Aplikasi Roblox
This study aims to compare the performance of two popular classification algorithms, namely Naïve Bayes and Support Vector Machine (SVM), in analyzing the sentiment of user reviews of the Roblox game application found on the Google Play Store. The data used in this study amounted to 2,000 user reviews collected through web scraping techniques from January to December 2023. The data processing stage began with text pre-processing, including data cleaning, word normalization, tokenization, stopword removal, and stemming. Next, the text data was converted into numeric form using the Term Frequency–Inverse Document Frequency (TF-IDF) weighting method. The dataset was then divided into 80% training data and 20% test data for model training and testing purposes. The performance evaluation of both algorithms was carried out using a Confusion Matrix with an accuracy indicator. The results showed that the Support Vector Machine algorithm performed superiorly compared to Naïve Bayes, with the highest accuracy level reaching 87.20%. This finding indicates that SVM is more effective in handling game review data that has high dimensions and non-standard language variations.
Analisis Sentimen Publik pada Media Sosial X terhadap Program Magang Pemerintah Menggunakan Algoritma Naïve Bayes
Internship programs organized by the government are a strategic effort to enhance human resource competencies while providing employment opportunities for the younger generation. This study aims to examine public perceptions of these programs through sentiment classification on the social media platform X (formerly Twitter). The method employed is Naive Bayes, a probabilistic classification algorithm that is effective for text analysis. Data were collected from tweets containing keywords related to government internship programs within a specific time frame. After the data underwent cleaning and preprocessing, the model was trained and tested to classify sentiments into positive and negative categories. The classification results indicate that positive sentiment dominates with 52.3%, while negative sentiment accounts for 47.7%. This relatively narrow margin suggests that although the majority of users responded positively, a considerable portion expressed criticism or dissatisfaction with the programs. These findings serve as valuable input for the government to improve the quality and implementation of internship initiatives to better align with public expectations. Furthermore, this study demonstrates that the Naive Bayes method is capable of automatically identifying public sentiment using data from social media platform X. The conclusions drawn can be used as a reference for policymakers to enhance communication and execution of government internship programs in the future. It is also recommended that future research expand the data sources by including various other social media platforms to gain a more comprehensive view of public sentiment. This approach would enrich the analysis and contribute to more data-driven and responsive policy development.
Pengaduk Pakan Ayam Otomatis Berbasis IoT
The development of Internet of Things (IoT) technology has significantly influenced the livestock sector, particularly in improving the efficiency of feed management in poultry farming. Manual feed mixing is still widely applied, despite its limitations in terms of time, labor, and feed uniformity. This study aims to design and evaluate the performance of an IoT-based automatic chicken feed mixing system to enhance operational efficiency and real-time monitoring. The research employs a quantitative experimental approach based on system simulation, including hardware and software design, system modeling, and functional performance testing. The system is controlled by an ESP32 microcontroller integrated with a DC motor, servo motor, relay, and an IoT-based monitoring application. Experimental results indicate that the system operates stably under various feed load conditions, with relatively constant motor voltage and power consumption increasing proportionally with the applied load. Energy consumption remains within an efficient range, while the IoT application successfully provides real-time system status monitoring with responsive performance. Overall, the proposed IoT-based automatic feed mixing system effectively improves feed processing efficiency, reduces dependence on manual labor, and supports the implementation of modern, technology-driven poultry farming systems.
Analisis Hubungan Persentase Ketidakseimbangan Beban terhadap Rugi Daya pada Transformator Distribusi di PT PLN (Persero) ULP Binjai Timur
The distribution transformer is one of the most important components in the electrical power distribution system. Distribution transformers often experience load imbalance issues. One previous study indicated that load imbalance can reach 25.6%, contributing to an increase in power losses. This study aims to analyze the relationship between the percentage of load imbalance and the power losses that occur at PT. PLN (Persero) ULP Binjai Timur. This research was conducted using a quantitative approach by calculating the percentage of load imbalance and the resulting power losses. Data were collected through direct observation, voltage and current measurements, followed by calculations and analysis. The results of the study show that the higher percentage of load imbalance occurred at night, with 12.96%, while during the day it was 10.03%. The power losses were higher at night, amounting to 853.3 watts, while during the day it was 4,386.3 watts. Therefore, it can be concluded that the higher the percentage of load imbalance, the higher the power losses that occur.
Rancang Bangun Sistem Informasi Manajemen Data Kelompok Tani dan Pembagian Subsidi Berbasis Web
This research ams to design and develop a web-based information system for managing farmer group data and subsidy distribution at the Agricultural Extension Center (BPP) of Batang Asai District. The system was developed to address problems in manual data management, which often lead to administrative delays, data inaccuracies, and a lack of transparency in subsidy distribution. The research method used is Research and Development (R\&D) with the Waterfall development model, which consists of requirements analysis, system design, implementation, and testing. Requirements analysis was carried out through interviews,observations, documentation, and literature study. The system design utilized Unified Modeling Language (UML) diagrams (Use Case, Activity, Class, and Sequence Diagram) and was implemented using PHP Native and MySQL as the database. Testing was performed using the blackbox testing method to ensure the system works according to user requirements. The result of this study is a web-based information system that enables integrated management of farmer group data, member data, production data, subsidy applications, verification, and report generation. The system is equipped with rolebased access control (administrator, village admin, and farmer group leader) to support accuracy, efficiency, and transparency in data management and subsidy distribution processes.
Prototype Digitalisasi Layanan Bebas Pustaka pada Perpustakaan Berbasis Website dan Mobile
The process of managing the library clearance at the Faculty of Economics and Islamic Business at UIN Sulthan Thaha Saifuddin Jambi is still conducted manually, which causes inefficiency for both students and library staff. Students have to come directly to submit their requests, while staff perform checks and record data manually, which slows down the service and complicates data archiving. This research aims to design and implement a library clearance system based on a website and mobile platform using the prototype method. The application was developed using the Python programming language with the Django framework for the website and Flutter for the mobile platform. The results show that the system can provide online submission, verification, and status tracking services, making the process faster, more practical, and secure. User evaluations of the system show positive results, with the design aspect scoring 80% (Good), ease of use 83.75% (Very Good), and usability 83.33% (Very Good). This indicates that the system is functioning well and providing ease for both students and staff, although there is room for improvement, particularly in the design aspect. Therefore, the implementation of this system provides a more efficient and modern solution for managing library clearance.
Penyiraman Tanaman Berbasis Arduino Menggunakan Sensor Soil Moisture dan Telegram
Currently, most plant watering methods in gardens and yards are still manual or require human labor. This method of watering plants is considered less than optimal because it requires more energy and less efficient water use. Furthermore, humidity control requires constant monitoring to ensure adequate water supply for the plants. However, this can be time-consuming and labor-intensive, increasing maintenance costs. Based on these challenges, the author developed an innovation by creating an automatic plant watering device. This device automatically turns on and off, determined by soil moisture parameters, eliminating the need for manual watering. This system utilizes an Arduino UNO and a Soil Moisture Sensor as the primary components for measuring soil moisture. The output of this final project is a device that can automatically control the on and off of a water pump based on the moisture level. In addition, the owner can also control the condition of the plants remotely, because this tool is connected to Telegram software, with this Telegram the plant owner can control manually or automatically to turn the water pump on and off and notifications will appear on the Telegram that has been installed on the cellphone, so the owner does not need to be afraid if he wants to travel.
Influencer sebagai Agen Promosi Produk Kuliner Tradisional di Era Digital
This study aims to explore how influencers perceive and enact their role as promoters of traditional culinary products in the digital era. Employing a qualitative phenomenological approach, data were collected through in-depth interviews and digital observation of two local culinary influencers from Garut and Tasikmalaya. The findings reveal that influencers serve not only as content creators but also as cultural communicators who strive to preserve local values through social media. Their communication strategies include personal storytelling, culinary process visualization, two-way interaction, and collaboration with local MSMEs. Challenges encountered include limited resources, commercialization pressures, and lack of government support. However, opportunities such as rising public awareness and expanded access to digital markets offer space for more inclusive and sustainable promotion of traditional cuisine. This study contributes theoretically to the field of culturally grounded digital communication and offers practical implications for developing local culinary promotion strategies. Future research is encouraged to examine cross-regional promotional dynamics and emerging digital platforms.
Implementasi Algoritma Dijkstraa Berbasis Teori Graf untuk Penentuan Rute Terpendek dari STIKOM Tunas Bangsa ke Suzuya Merdeka Mall Kota Pematangsiantar
Determining the shortest route is an important problem in graph theory that is widely applied in digital navigation systems. This study aims to implement the Dijkstra algorithm based on graph theory to determine the shortest route from STIKOM Tunas Bangsa to Suzuya Merdeka Mall in Pematangsiantar City. The research method used is a quantitative approach by modeling the road network as a weighted graph, where vertices represent locations or road intersections and edges represent road segments with distance weights. Distance data between locations were obtained through observation and digital map data from Google Maps, which were then processed using the Dijkstra algorithm to calculate the minimum distance from the starting point to the destination. The results show that the Dijkstra algorithm is able to determine the shortest route systematically and efficiently. The optimal route obtained is A → B → C → D → L with a total distance of 690 meters. The comparison results with Google Maps indicate a distance similarity of 0.69 km with an accuracy level of 99%. Therefore, the Dijkstra algorithm is proven to be effective in solving the shortest path problem and has the potential to be implemented in web-based or mobile navigation systems.
Sistem Informasi Perdagangan Berbasis Web sebagai Media Promosi bagi Pedagang di Lapak Alun-Alun Tambolaka
The development of information technology provides significant opportunities for businesses to utilize digital media as a means of promoting and managing culinary products. Alun-Alun Tambolaka Stalls is a center for community culinary activities with high economic potential, but still faces obstacles in terms of product promotion, information dissemination, and limited marketing reach. This research aims to design and build a web-based trade information system that can be used as a promotional medium for vendors at Alun-Alun Tambolaka Stalls. This system is designed to display complete product information, including product name, category, description, price, and product image, so that it can be easily accessed by the general public via the internet. The system development method used is the Waterfall method, which includes requirements analysis, system design, implementation, testing, and maintenance. This system has several key features, including a shop information page, product catalog, product categories, a login page, an admin dashboard, and merchant and product data management. The results of this study indicate that the web-based trade information system developed can help merchants promote their products more effectively and efficiently, expand their marketing reach, and facilitate the public's access to product information available at the Tambolaka Square stalls. Therefore, this system is expected to increase the competitiveness of local merchants and support the economic development of the local community.
Website Pemetaan Aset Daerah Kota Bandung Berbasis Sistem Informasi Geografis
The Geographic Information System (GIS) for regional asset mapping plays a vital role in delivering accessible and transparent government asset information to the public. The City of Bandung has a wide range of regional assets, including both immovable and movable types, which have not yet been fully integrated into a comprehensive spatial-based information system. This study aims to design and develop a web-based GIS application for mapping regional assets in Bandung using the Laravel framework and the Leaflet.js library. The research adopts a descriptive method, while system development follows a prototype model to ensure iterative improvement. Data were collected through observation and literature review. The resulting system features an interactive map interface, as well as search, filtering, and asset transfer reporting functions. The findings show that the developed GIS application improves public access to regional asset data and enhances transparency, accountability, and efficiency in the management of government-owned assets in Bandung.
Pengembangan Layanan Room Service Berbasis React Native Menggunakan Database Mysql Untuk Meningkatkan Kepuasan Pelanggan Di Hotel Petra Tegal
The development of mobile technology has encouraged various industries to improve service quality through digital systems, including the hospitality sector. Hotel Petra Tegal still uses conventional methods in providing room service, namely through telephone calls or direct communication with staff, which sometimes makes the ordering process less efficient and potentially causes errors in recording orders. This study aims to develop a mobile-based room service application to facilitate hotel guests in ordering room services. The application was developed using the React Native framework with MySQL as the database for data storage. The research method used is the prototype method, which allows system development to be carried out iteratively through the creation of an initial model, user evaluation, and system improvements according to user needs. The system design was carried out using Unified Modeling Language (UML), Data Flow Diagram (DFD), and Entity Relationship Diagram (ERD) to describe the system processes and data structure. System testing was conducted using the black box testing method to ensure that each function of the application runs according to the designed requirements. The results show that the developed application can facilitate the room service ordering process, accelerate the delivery of order information to hotel staff, and improve the effectiveness of services provided to customers.
Sistem Informasi Pemesanan Makanan dan Minuman Berbasis Aplikasi Android pada Caffe Corner
The rapid development of information technology has encouraged the culinary business sector to adopt digital systems in order to improve operational efficiency and service quality. Caffe Corner still applies a manual ordering system for food and beverages, which may result in recording errors, service delays, and inefficient transaction data management. This study aims to design and develop an Android-based Food and Beverage Ordering Information System to facilitate the ordering process and manage data in an integrated manner. The research method used is the Waterfall model, which consists of requirement analysis, system design, implementation, testing, and maintenance stages. The system was developed as an Android application to enable users to place orders more practically through mobile devices. The application is designed to manage menu data, ordering transactions, and sales reports in a structured manner. System testing was conducted using the Black Box Testing method to ensure that each function operates according to user requirements and predefined system specifications. The testing results indicate that all main features, such as menu selection, ordering process, and transaction management, function properly without any functional errors. The implementation of this system is expected to enhance the effectiveness and efficiency of the ordering process at Caffe Corner and improve overall customer service quality.
Analisis Perubahan Tap Trafo Unit 2 PLTG Payo Selincah untuk Memenuhi Kelayakan Sinkronisasi saat Tegangan Sistem Melebihi 153 kV
Synchronization between power plants and interconnected systems requires matching voltage, frequency, and phase angle parameters. At the Payo Selincah Unit 2 Gas Turbine Power Plant (PLTG), synchronization often encounters issues due to transmission system voltage frequently exceeding 153 kV. This study aims to analyze the need for adjusting the tap position of the 11.5 kV/150 kV step-up transformer to ensure synchronization is still possible even under overvoltage conditions. The methodology includes a literature review, field testing, and TTR (Tap Transformer Ratio) analysis based on voltage readings from the HV (High Voltage) and LV (Low Voltage) sides. The results show that changing from Tap 3 to Tap 2 reduces the LV side voltage from 19.89 kV to 19.42 kV, while the HV side voltage drops from 11.93 kV to 11.65 kV. This reduction ensures that synchronization can still be performed even when the system voltage reaches 155–157 kV. Based on these findings, the study provides technical recommendations for system operators to adjust the tap positions accurately, ensuring reliable synchronization of the power plant with the interconnected system safely and effectively under overvoltage conditions.
Penyaringan Paket Berbasis MikroTik untuk Meningkatkan Keamanan Jaringan dan Akses Internet Positif Studi Berbasis Quality Of Service (di SMKS Al-Islam Joresan Mlarak Ponorogo)
Internet use in educational settings requires secure, controlled network management with good service quality. However, at SMKS Al-Islam Joresan Mlarak Ponorogo, problems persist, including low network security, access to inappropriate content, and suboptimal bandwidth distribution. This study aims to analyze and implement a MikroTik-based packet filtering system to improve network security and support positive Internet access through a Quality of Service approach. The methods used include network requirements analysis, system design using a MikroTik Firewall, implementation of packet filtering and bandwidth management, and network performance testing based on Quality of Service parameters, namely throughput, delay, jitter, and packet loss. The results show that implementing packet filtering can limit access to unwanted sites and significantly improve network security. Furthermore, Quality of Service implementation has been proven to optimize bandwidth usage and improve network stability and service quality. Thus, the integration of packet filtering and Quality of Service is an effective solution for creating a secure, controlled, and high-quality network system in educational settings.
Sistem Penyusunan Jadwal Perkuliahan Menggunakan Library Unitime University Timetabling pada Program Studi Sistem Informasi
The lecture scheduling process at the Information Systems Study Program of UIN Alauddin Makassar currently faces significant challenges due to the use of manual methods using spreadsheets. This conventional approach is highly susceptible to human errors, such as overlapping schedules for lecturers or rooms, is time-consuming, and lacks flexibility in handling sudden changes. This study aims to design and develop a web-based lecture scheduling information system by integrating the Unitime University Timetabling library to automate the process effectively and efficiently. The research methodology follows the Agile development model, which includes stages of requirement analysis, system design, implementation, and testing. The system utilizes the UniTime solver to model scheduling as a Constraint Satisfaction Problem (CSP), taking into account both hard constraints (e.g., no room conflicts) and soft constraints (e.g., lecturer preferences). System testing was conducted using Black Box Testing to validate functionalities and performance comparison testing to measure efficiency improvements. The results demonstrate that the developed system can generate a complete, conflict-free schedule in just 1 minute, compared to the 300 minutes required by manual methods. Furthermore, the system successfully eliminated 100% of detected potential scheduling conflicts. This research proves that integrating advanced scheduling libraries into modern web frameworks like Laravel provides a professional and highly efficient solution for academic management in higher education.
Analisis Sentimen terhadap Brand Skincare Lokal Sesuai Tipe Kulit Wajah di Media Sosial X Menggunakan Algoritma Support Vector Machine dan Particle Swarm Optimization
Social media has transformed into one of the primary platforms for consumers to openly share their personal experiences, impressions, and opinions regarding the skincare products they use. The wide variety of reviews on platforms like X reflects genuine user responses to a product's effectiveness, which significantly depends on each individual’s specific skin type characteristics. Therefore, sentiment analysis of consumer reviews on social media has become crucial in assisting the public to identify products that are best suited to their skin conditions. This study aims to analyze sentiment toward several popular local skincare brands, specifically Wardah, Emina, and Azarine, by categorizing them based on five distinct skin types: normal, oily, combination, dry, and sensitive. Sentiment data is classified into two categories: positive and negative. For the classification process, this research employs the Support Vector Machine (SVM) algorithm as the core model. To further enhance the classification accuracy and effectiveness, the model is optimized using the Particle Swarm Optimization (PSO) algorithm to fine-tune the parameters and improve overall performance. The results of this study are expected to provide a deep evaluation of how the integrated SVM-PSO approach performs in handling review data specific to skin type categories, ultimately providing data-driven recommendations for consumers.
Identifikasi Pola Spasial-Temporal Tindakan Pencurian di Kota X menggunakan Algoritma DBSCAN
Community safety is a fundamental element of quality of life, yet the increasing phenomenon of criminal acts, especially theft, requires a deep understanding of spatio-temporal patterns for effective prevention. This study aims to visualize the spatial distribution of theft, provide information for authorities in designing more effective crime prevention strategies, and cluster crime types based on location and time. Methods using a quantitative descriptive approach, secondary crime data (Chicago Crimes 2012-2017) consisting of 1,048,575 rows from Kaggle was processed through pre-processing (handling duplicates, missing values, data inconsistencies) and analyzed using the Density-Based Spatial Clustering of Applications with Noise (DBSCAN) algorithm for spatio-temporal clustering, with results visualized using Tableau. The research results identified spatial and temporal patterns of theft in City X from 2012-2017. It was found that theft is widespread, with streets, residences, and parking lots being the most vulnerable locations. Temporally, mid-July to August was the most vulnerable period. Spatial clusters (-1: safe; 0: vulnerable; 1, 2, 3: safe) and temporal clusters (night and day: watched; morning: not many occurrences) were successfully identified. This study confirms that Convolutional Neural Network with Inception-v4 is highly effective for oil palm fruit classification and can be applied in plantation industries to improve harvest efficiency and production quality. The use of AI-based methods like Convolutional Neural Network offers fast, accurate, and reliable solutions for agricultural object classification.
Clustering Dataset Numerik Multivariat menggunakan Algoritma K-Means dengan Evaluasi Silhouette dan Davies–Bouldin Index
Clustering is a data mining technique used to group data based on similarity. This study applies the K-Means clustering algorithm to analyze multivariate numerical data from the Standard Minimum Service (SPM) dataset of Nusa Tenggara Timur Province. The dataset is structured and consists of six numerical attributes representing basic service sectors, namely education, health, public works, housing and settlement, public order and community protection, and social services. The research stages include data cleaning, data standardization using the Z-score method, determination of the optimal number of clusters, and clustering using the K-Means algorithm. The quality of the clustering results is evaluated using the Silhouette Score and Davies–Bouldin Index. The results show that the optimal number of clusters is three (k = 3), with a Silhouette Score of 0.327 and a Davies–Bouldin Index of 0.872. The clustering process produces three data groups with different characteristics based on the average values of each sector. These results indicate that the K-Means algorithm can be used to group SPM data into meaningful clusters based on similarity patterns.
Sistem Informasi Manajemen Jalan untuk Monitoring Beban Lalulintas dan Evaluasi Kinerja Perkerasan
An integrated road management information system was developed to continuously collect vehicle volume, composition, and load data through moving weight sensors. The data allows the calculation of the Equivalent Single Axle Load (ESAL) which is the basis for evaluating the performance of road pavement. This information supports managers in predicting the remaining life of pavement, proactively adjusting maintenance schedules, and allocating repair budgets to the most critical segments. The system also functions as a law enforcement instrument against overloaded vehicles that accelerate pavement damage. Integration with geographic information systems and asset management systems strengthens spatial analysis as well as lifecycle cost calculations. Successful implementation depends on periodic sensor calibration, the availability of skilled personnel, a sustainable funding model, and a modular architecture that supports technology improvements. Real-time data enables dynamic maintenance planning that is responsive to changing traffic patterns. The results of the study confirm that this system is able to increase the effectiveness of road infrastructure management, extend the life of pavement services, and support data-driven decision-making. The practical implication is the need for a strategy of strengthening technical and institutional capacity so that the system can be widely adopted as a modern solution in sustainable road management.