JURNAL MEDIA INFOTAMA

Perancangan Aplikasi Steganografi Pada Citra Digital Menggunakan Algoritma Diversity Untuk Keamanan Pesan

Aji Legawa — 2026-10-12

The rapid advancement of digital technology and internet communication necessitates robust information security mechanisms that not only protect message content but also conceal the existence of the communication itself. Steganography provides an effective approach by embedding secret messages within digital media, particularly digital images. This study aims to design of Steganography Application in Digital Images Using the Diversity Algorithm for Message Security. The research adopts an applied research methodology with a system design and implementation approach. The Diversity algorithm is employed to exploit variations in pixel color values for embedding message bits, resulting in a more randomized embedding pattern that is resistant to detection and analysis. The experimental results demonstrate that the proposed system is capable of embedding and extracting text messages accurately without degrading the original image information. Furthermore, the steno-image maintains high visual quality, indicating good imperceptibility of the embedded data. In conclusion, the developed application proves to be an effective and reliable solution for secure message transmission using digital image-based steganography.

Penerapan Metode Probabilitas Symetric Pada Sistem Pakar Untuk Mendiagnosa Penyakit Tanaman Jamur Tiram

Dicky Firmansyah — 2026-10-12

Oyster mushrooms are a highly sought-after cultivated commodity due to their high economic value and relatively easy cultivation process. However, various diseases often occur during cultivation, which can reduce the quality and yield of the crop. The main problem faced by farmers is limited knowledge in quickly and accurately recognizing disease symptoms. Therefore, a system is needed to assist in the automatic diagnosis of oyster mushroom diseases. This study aims to design and build an expert system for oyster mushroom disease diagnosis using the Symmetric Probability method with the PHP programming language and a MySQL database. This system is designed to assist users in identifying the type of disease based on the symptoms experienced by oyster mushrooms. The Symmetric Probability method is used to calculate the likelihood level of a disease based on the probability value of each symptom selected by the user. The results show that the expert system is capable of providing a diagnosis of oyster mushroom diseases, along with a percentage value of the disease probability and treatment solutions. This system can facilitate farmers and cultivators in obtaining diagnostic information quickly, effectively, and efficiently without having to rely directly on experts.

Sistem Informasi Pengarsipan Data Skripsi Di Fakultas Ilmu Sosial Universitas Dehasen Bengkulu Berbasis Web

Rafid Ula Penta — 2026-10-14

Archiving is an important part of document management, especially in universities that produce theses every year as proof of students' academic abilities. The Faculty of Social Sciences at Dehasen University in Bengkulu still archives theses manually, which causes various problems such as difficulty in searching for data, the risk of losing documents, and inefficient archive management processes. Therefore, an archiving information system is needed that can store, manage, and display thesis data in a structured and easily accessible manner. This study aims to design and develop a web-based thesis data archiving information system at the Faculty of Social Sciences, Dehasen University Bengkulu. The methods used include data collection through observation and interviews, as well as system design stages using a structured development model. The result of this research is a web-based information system that can facilitate the process of archiving, searching, and managing thesis data, especially in the Communication Science Study Program. With this system, the archiving process becomes more effective and efficient compared to the manual management system that was previously used.

Analisis Pengguna Terhadap Sistem Informasi Pelaporan Keuangan (SIPELUK) Pada Kantor Kecamatan Kelapa Gading

Defira Patricia Defira Patricia — 2026-10-14

Sistem Informasi Pelaporan Keuangan (SIPELUK) pada Kantor Kecamatan Kelapa Gading. Penelitian ini dilatarbelakangi oleh pentingnya pemanfaatan teknologi informasi dalam mendukung transparansi, akuntabilitas, dan efisiensi pelaporan keuangan pada instansi pemerintahan. Metode penelitian yang digunakan adalah deskriptif kuantitatif dengan teknik pengumpulan data melalui kuesioner dan dokumentasi tampilan aplikasi. Sampel penelitian berjumlah lima responden yang dipilih menggunakan teknik purposive sampling berdasarkan keterlibatan langsung dalam penggunaan atau pengelolaan SIPELUK. Data dianalisis secara deskriptif dengan menghitung nilai rata-rata pada setiap indikator penilaian. Hasil penelitian menunjukkan bahwa SIPELUK memperoleh penilaian sangat baik dari pengguna, dengan rata-rata skor 5,00 pada aspek kemudahan akses, formulir input data, percepatan pelaporan, kelancaran teknis, keakuratan laporan, dukungan fitur, dan manfaat transparansi. Temuan ini menunjukkan bahwa SIPELUK mampu mendukung proses pelaporan keuangan secara lebih efektif, efisien, dan terstruktur. Meskipun pengguna tidak mengalami kendala teknis yang berarti, pengembangan sistem tetap diperlukan melalui penambahan fitur barcode, notifikasi, serta pembaruan tampilan aplikasi agar lebih optimal sesuai kebutuhan pengguna.

Pembuatan Alat Kontrol Suhu Pada Kandang Ayam Berbasis Internet of Things (IoT)

Bima Kusuma Wardana — 2026-10-15

This study aims to design and build an Internet of Things (IoT)-based temperature control device for broiler chicken cages. The system was developed to help farmers monitor temperature and humidity in real time and control a heating device remotely through a smartphone. The hardware consists of an ESP8266 microcontroller, DHT11/DHT22 temperature and humidity sensor, relay module, 40-watt incandescent lamp as the heater, LCD 16x2 display, power supply, and supporting electronic components. The software was developed using Arduino IDE and integrated with the Blynk IoT platform for monitoring and manual control. The research method used was experimental design with black-box testing on sensor detection, data transmission, relay response, and Blynk application performance. The test results show that sensor data were received within 1.8-2.1 seconds, while commands from Blynk were received within 2.5-2.7 seconds. The relay response to the heater ranged from 1.5 to 1.9 seconds, and the Blynk display response ranged from 2.3 to 2.9 seconds. These results indicate that the proposed system works properly for real-time temperature monitoring and automatic/manual heating control in a small-scale broiler cage simulation.

Penerapan Snort Dalam Mendeteksi Penyerangan Pada Sistem Keamanan Jaringan Komputer SMKN 2 Seluma

Ade Manza Putra — 2026-10-16

This research focuses on deploying Snort as an Intrusion Detection System (IDS) to fortify the computer network security at SMK Negeri 2 Seluma, specifically targeting the protection of school servers and network infrastructure. Empirical testing demonstrated that the system successfully detected Ping of Death attacks by identifying anomalous Internet Control Message Protocol (ICMP) traffic, consequently generating high-priority alerts. During malware evaluation, Snort effectively flagged the EICAR Standard Anti-Virus Test File when accessed through PowerShell; however, it failed to recognize the payload when downloaded via a standard web browser. Furthermore, the system successfully identified simulated W32/ProxyBack trojan activity executed via HTTP CONNECT communications using PowerShell, triggering maximum-priority alerts to indicate a critical threat level.

Implemetasi Machine Learning Metode K-Nearest Neighbor Untuk Memprediksi Status Kelulusan Mahasiswa Program Studi Informatika Universitas Dehasen Bengkulu

AL Kausar AH — 2026-10-16

Student graduation rates are a key performance indicator that’s really crucial for the quality and reputation of a university. However, study delays and the risk of dropping out are still serious challenges for the Informatics Study Program at Dehasen University Bengkulu. This research focuses on tackling these issues by developing an early prediction system for student graduation status to help support more proactive academic decision-making. This research uses an Educational Data Mining (EDM) approach with the Knowledge Discovery in Databases (KDD) framework to process student academic datasets. It implements the K-Nearest Neighbor (KNN) algorithm. Based on the testing results with the hyperparameter K=5, the KNN model achieved an accuracy rate of 50%, which indicates that the decision boundary between students who pass and those who don't cannot be significantly separated by the numeric academic variables currently used. This finding suggests that further development is needed by adding latent variables or sociological data, as well as more specific feature selection techniques to better capture student behavior patterns and improve the model's performance in the future.

Analisis Performa Algoritma Hierarchical Clustering Untuk Identifikasi Pola Kematian Ikan Lele Pada Budidaya Lele Tiga Saudara

Agung Amanda Pratama — 2026-10-18

Tiga Saudara Catfish Farm in Bengkulu City has experienced varying mortality rates across different cultivation periods; however, these patterns have not been systematically analyzed using a data-driven approach. This study aims to identify catfish mortality patterns using Agglomerative Hierarchical Clustering (AHC) method. The dataset consisted of 90 days of operational records, including water temperature, pH levels, and feed types. The analytical process followed the Knowledge Discovery in Databases (KDD) framework, encompassing data preprocessing through One-Hot Encoding and Min–Max normalization, Euclidean distance calculation, and the implementation of the AHC algorithm using Single, Average, and Complete Linkage methods. The results indicate that the Average Linkage method achieved the best performance, with a Cophenetic Correlation Coefficient (CCC) value of 0.9789. The optimal number of clusters was determined to be four (k=4) based on a Silhouette Score of 0.8175. These four clusters represent distinct operational conditions within the farming system, namely Safe, Alert, Critical, and Recovery conditions. The findings further reveal that the use of alternative feed derived from bread waste contributed to a decline in water pH levels to a range of 6.0–6.8 and a significant increase in fish mortality, resulting in a total loss of 1,465 fish and an estimated financial loss of IDR 1,044,000 per production cycle. Model validity testing through White-Box Testing produced a CCC value of 0.9789 and a Silhouette Score of 0.8175, both exceeding the predetermined acceptance thresholds. Furthermore, system functionality testing through Black-Box Testing on 14 test cases within the AHC pipeline and Power BI dashboard demonstrated a 100% success rate. The clustering results were visualized through an interactive Microsoft Power BI dashboard, providing risk maps, daily mortality trends, and cluster distributions as decision-support tools for catfish farmers. This enables rapid identification of risk conditions and facilitates preventive actions before mass mortality events occur

Penerapan Deep Learning Untuk Klasifikasi Penyakit Mata Menggunakan Metode Convolutional Neural Network

Alfarida Dewi Aprilia — 2026-10-18

Eye diseases such as cataracts, diabetic retinopathy, and glaucoma are among the leading causes of visual impairment and can result in blindness if not detected at an early stage. The application of Deep Learning technology, particularly Convolutional Neural Networks (CNNs), provides an opportunity to support the automatic classification of eye diseases based on retinal fundus images. This study aims to develop an eye diseaseclassification model using the EfficientNetB0 architecture with a transfer learning approach. The dataset used was the Eye Diseases Classification dataset from Kaggle, consisting of 4,217 retinal fundus images categorized into four classes: Cataract, Diabetic Retinopathy, Glaucoma, and Normal. Before the training process, the images underwent preprocessing, including image resizing, normalization, and data augmentation. The model was trained using the Tensor Flow/Keras framework in the Google Colab environment and evaluated using accuracy, precision, recall, F1-score, and confusion matrix metrics. The experimental results showed that the proposed model achieved an overall accuracy of 73.23%. The Cataract class demonstrated the best performance, with a precision of 0.78, a recall of 0.92, and an F1-score of 0.84. In contrast, the Glaucoma class obtained the lowest recall of 0.36, indicating that the model still encountered difficulties in correctly identifying a considerable number of glaucoma images. Overall, the results indicate that the EfficientNetB0 architecture is capable of classifying eye diseases from retinal fundus images with satisfactory performance. However, increasing the dataset size, optimizing preprocessing techniques, and applying more extensive fine-tuning are recommended to further improve the model's performance, particularly in glaucoma classification

Sistem Informasi Penyewaan Kamar Kost Berbasis Web

Putri Fajar Wati — 2026-10-19

The management and rental transaction processes at Kost Lineska are currently conducted manually, resulting in inefficiencies in tenant data recording, difficulties in confirming room availability, and a risk of errors in rental payment bookkeeping. This study aims to design and develop Web-Based Boarding House Room Rental Information System that transforms the rental management process into a computerized system, making it easier, more accurate, transparent, and wellorganized. The system was developed using the PHP programming language and a MySQL database. The results of the study successfully produced an online boarding house rental application that supports two user access levels, namely administrators and tenants. Through this system, boarding house managers can manage room data, verify rental applications, update payment statuses, and view monthly rental reports. Meanwhile, tenants can register accounts, view available rooms, submit rental requests, upload proof of payment transfers, and independently print payment receipts. Based on functional testing using the Black Box Testing method, all features of the application were proven to operate properly and successfully without any system errors. Therefore, the system is considered highly feasible for supporting convenient and integrated boarding house rental management.

E-Commerce Produk Minuman Pada Toko Minumin

Bobby Dwi Saputra — 2026-10-20

Commerce for Beverage Products at Minumin Shop is a web-based system designed to support the online sales process of beverage products. This research was motivated by the existing sales process, which was still conducted manually, requiring customers to visit the store directly to view the menu, inquire about prices, and place orders. This condition resulted in inefficient service, increased the risk of order-recording errors, and complicated the management of product data, transactions, and sales reports. The objective of this study is to develop an e-commerce system that facilitates consumers in obtaining product information, placing orders, making payments, and monitoring order status online. The system development method employed was Rapid Application Development (RAD), consisting of the phases of requirements planning, user design, construction, and implementation. The system was developed using the PHP programming language and MySQL database. The results of the study indicate that the system is capable of performing its main features, including login, member registration, product categories, product details, shopping cart, checkout, payment processing, invoice generation, order status tracking, notifications, transaction history, as well as sales, payment, and sold-product reports. Based on the results of Black Box testing, all system functions operated in accordance with the expected outputs. Therefore, the system can assist the sales process at Minumin Shop by making it easier, faster, more structured, and more efficient.

Klasifikasi Parameter Penyebab Kecelakaan Lalu Lintas Dengan Algoritma Decission Tree Di Wilayah Polresta Kota Bengkulu

Ronna Mutiara Maheswari Wahyudi — 2026-10-22

The Traffic accidents are a complex issue influenced by multiple factors, including human behavior, vehicle conditions, road characteristics, and environmental conditions. Historically, traffic accident data maintained by the Police Department of Bengkulu City have been utilized primarily for descriptive reporting, limiting their potential to reveal comprehensive patterns of accident causation. This study aims to identify the dominant factors contributing to traffic accidents, implement the Decision Tree C4.5 algorithm for accident classification, and evaluate the performance of the resulting classification model. This study used the Knowledge Discovery in Databases (KDD) methodology. The dataset consisted of historical traffic accident records obtained from the Jurisdiction of Bengkulu City Police. Data processing was conducted using Python in the Google Collaboratory environment through several stages, including exploratory data analysis (EDA), data preprocessing, model development, and performance evaluation. The results demonstrate that the proposed model successfully identified relationships among accident causative factors through the construction of a decision tree, generating 20 classification rules. Road Surface Condition was identified as the most influential predictor, with a feature importance value of 0.30, followed by Special Information (0.15), Speed Limit at the Accident Location (0.13), and Lighting Condition (0.10). Model evaluation showed an overall accuracy of 65.2%, with a weighted average F1-score of 75.9%, indicating satisfactory performance in classifying the majority classes. However, the macro average F1-score of 28.9% suggests that the model's performance on minority classes remains limited due to class imbalance in the dataset. This study is expected to provide a data-driven foundation for developing more effective traffic accident prevention and mitigation strategies in the Jurisdiction of Bengkulu City Police.

Optimalisasi Pencarian Data Menggunakan Algoritma B-TREE

Muhammad Yusuf — 2026-10-22

The performance of the information system at the Regional Library Agency of Bengkulu Province currently experiences responsiveness constraints, particularly in the book and membership data retrieval processes. This high latency is triggered by an increasing volume of data that is still processed using linear scanning or a full table scan method on the database. Therefore, this study aims to optimize query execution time through the design and implementation of the B-Tree indexing algorithm within a MySQL database management system environment. The execution of this research adopts the stages of the Waterfall method to ensure a structured implementation without rebuilding the system from scratch. Testing was executed through two approaches: Black Box functionality testing to validate user interface precision, and Performance Testing to comparatively analyze computational execution times between non-indexed and indexed tables. Empirical experimental results on a population of 10,000 data rows prove that the implementation of the B-Tree algorithm yields highly significant computational efficiency. The average execution time for book data searches was successfully reduced from 2.9651 milliseconds to 0.5895 milliseconds, creating an 80.12% increase in efficiency. In member data retrieval, the execution time was compressed from an average of 5.8076 milliseconds to 0.7430 milliseconds, achieving an efficiency surge of 87.21%. In conclusion, the application of the B-Tree indexing technique is quantitatively proven to resolve data processing latency bottlenecks. This optimization solution enables library circulation services to operate much more responsively and consistently, with waiting times under one millisecond.

Implementasi Metode Weighted Agregated Sum Product Assesment (WASPAS) Untuk Seleksi Penerimaan Beasiswa Prestasi Pada SMA Negeri 7 Bengkulu Selatan

Ande Alfa Dela — 2026-10-23

Scholarships are a form of recognition provided as financial assistance to individuals or organizations based on their achievements and performance. The provision of merit-based scholarships aims to enhance the quality of students' learning and academic performance. However, one of the main challenges in the scholarship selection process is conducting objective evaluations, as the assessment involves multiple criteria, including students' academic abilities and participation in school activities. To address this challenge, a Decision Support System (DSS) employing the Weighted Aggregated Sum Product Assessment (WASPAS) method was developed to assist decision-makers in the scholarship selection process. The WASPAS method minimizes assessment errors and optimizes the ranking process by accurately determining the highest- and lowest-scoring candidates. The system was implemented using the PHP programming language and a MySQL database, while the software development process followed the Waterfall methodology. The results of system testing indicate that the WASPAS-based Decision Support System effectively performs the ranking process and supports the selection of merit scholarship recipients accurately and efficiently.

Sistem Pendukung Keputusan Penerimaan Beasiswa Dengan Metode SAW (Simple Additive Weighting) Dan Electre (Elimination Et Choix Traduisant La Réalité) Pada Pondok Pesantren Darul Amal

Candra Handika — 2026-10-23

Scholarship awards are one of the efforts to support academically outstanding students who face financial constraints. At Darul Amal Islamic Boarding School, the scholarship selection process is still conducted manually, making it susceptible to subjectivity, limited transparency, and relatively lengthy processing times. Therefore, a Decision Support System (DSS) is needed to facilitate the selection of scholarship recipients in an objective, efficient, and accurate manner. This study aims to design and develop a Decision Support System for scholarship selection by implementing the Simple Additive Weighting (SAW) and Elimination Et Choix Traduisant La Realité (ELECTRE) methods at Darul Amal Islamic Boarding School. The evaluation criteria include students' average academic report scores, number of parental dependents, and parents' income. The SAW method is employed to calculate preference values through normalization and weighting processes, while the ELECTRE method is used to select alternatives based on the concepts of concordance and discordance. The system was developed using the PHP programming language with a MySQL database and followed the System Development Life Cycle (SDLC) methodology. The results demonstrate that the developed system effectively supports the scholarship selection process by making it more efficient, transparent, and objective. Based on the SAW calculation results, a ranking of scholarship candidates was generated, providing recommendations to assist the boarding school in identifying the most eligible scholarship recipients. The implementation of the SAW and ELECTRE methods produces more objective decisions because the evaluation is based on predetermined criteria and weights. In conclusion, the developed system provides reliable decision support for the scholarship selection process, ensuring that scholarship awards are determined in a fair, accurate, transparent, and accountable manner.

Sistem Pakar Untuk Diagnosa Penyakit Kardiovaskular (Jantung Dan Pembuluh Darah) Menggunakan Metode Dempster Shafer

Bima Defriansyah — 2026-10-23

Cardiovascular system plays a vital role in the human body, as no cells or tissues can function properly without an adequate supply of oxygen and blood. When the cardiovascular system is impaired, the entire body is affected. Cardiovascular diseases, particularly heart and blood vessel disorders, are among the most common health problems experienced by the general population. To assist the public and healthcare professionals in providing education, consultation, and awareness regarding cardiovascular diseases, this study designed and developed an expert system application by implementing the Dempster–Shafer method. The Dempster–Shafer method determines the degree of belief based on the symptoms experienced by the user and combines evidence from multiple symptoms to calculate the probability of the cardiovascular disease being diagnosed. The final outcome of this research is an expert system capable of diagnosing cardiovascular diseases using the Dempster–Shafer method and providing the probability value for each diagnosis, representing the system's level of confidence in the identified disease. The developed system is expected to support preliminary diagnosis and improve public awareness of cardiovascular diseases while serving as a decision-support tool for healthcare professionals

Analisis Kesenjangan (Gap Analysis) Keamanan Informasi pada Instansi Pemerintah Indonesia Berdasarkan Indeks KAMI 5.0 dan Standar Internasional

Dimas Ahsanul Habibi — 2026-10-24

Penelitian ini bertujuan menganalisis kesenjangan (gap analysis) keamanan informasi pada instansi pemerintah di Indonesia menggunakan Indeks Keamanan Informasi (KAMI) versi 5.0 yang dikembangkan oleh Badan Siber dan Sandi Negara (BSSN). Evaluasi difokuskan pada tiga aspek utama, yaitu tata kelola keamanan informasi, pengelolaan risiko, dan kerangka kerja keamanan informasi, kemudian dibandingkan dengan persyaratan ISO/IEC 27001:2022 serta NIST Cybersecurity Framework (CSF). Hasil analisis menunjukkan bahwa sebagian besar instansi pemerintah masih berada pada tingkat kematangan dasar dengan nilai rata-rata 450 dari total 645 poin. Kesenjangan yang paling signifikan ditemukan pada aspek pengelolaan risiko, implementasi pengendalian keamanan, serta mekanisme pemantauan dan evaluasi yang belum sepenuhnya memenuhi standar internasional. Kondisi tersebut menunjukkan bahwa penerapan keamanan informasi masih memerlukan penguatan, baik dari sisi kebijakan, tata kelola, maupun pengendalian teknis untuk meningkatkan efektivitas perlindungan aset informasi. Berdasarkan temuan tersebut, penelitian ini merekomendasikan penguatan manajemen risiko, peningkatan kepatuhan terhadap ISO/IEC 27001:2022, optimalisasi penerapan NIST CSF, serta pengembangan kompetensi sumber daya manusia sebagai langkah strategis dalam meningkatkan tingkat kematangan keamanan informasi di lingkungan instansi pemerintah Indonesia.

Klasifikasi Tingkat Kerapatan Tajuk Kelapa Sawit Menggunakan Metode Convolutional Neural Network (CNN) Berdasarkan Citra Drone.

Muhammad Apriliansyah Rahmadhani — 2026-10-26

Monitoring the canopy density of oil palm plantations is essential for assessing plant health, optimizing plantation management, and improving productivity. Conventional monitoring methods generally rely on field observations, which are time-consuming, labor-intensive, and often less efficient for large-scale plantations. The advancement of unmanned aerial vehicle (UAV) technology and deep learning offers an alternative solution for automated canopy analysis. This study aims to classify oil palm canopy density levels using the Convolutional Neural Network (CNN) method based on drone imagery. The dataset was acquired using drone flights over oil palm plantation areas and subsequently preprocessed through cropping, resizing, and data augmentation techniques. The canopy density was categorized into three classes: low, medium, and high. A CNN model was developed and trained to automatically extract image features and perform classification. Model performance was evaluated using accuracy, precision, recall, and F1-score metrics. The experimental results indicate that the proposed CNN-based approach effectively classifies oil palm canopy density with high performance. The integration of drone imagery and deep learning provides a rapid, accurate, and efficient solution for supporting precision agriculture and sustainable plantation management.

Optimasi Proses Seleksi Calon Peserta Olimpiade Sains Menggunakan Metode Promethee

Muntahanah Muntahanah — 2026-10-26

selection of candidates for the National Science Olympiad (OSN) is a crucial stage in identifying students with outstanding academic abilities. Manual selection processes can lead to inefficient assessments, require significant time, and potentially introduce subjectivity when identifying the best students. This study aims to develop a decision support system to facilitate the selection and ranking of OSN candidates in an objective, effective, and transparent manner. The method employed is the Preference Ranking Organization Method for Enrichment Evaluation (PROMETHEE), a multi-criteria decision-making technique capable of ranking alternatives based on multiple criteria. The study utilizes primary student data, with assessment criteria comprising scores in Chemistry, Physics, Mathematics, and Biology; eligible students are those with scores ranging from 75 to 100. The research stages include data collection, the determination of criteria and weights, data processing using the PROMETHEE method, the calculation of leaving flow, entering flow, and net flow, and the final ranking process. The study results in a decision support system that generates student recommendations based on the highest net flow values. This system is expected to enhance the effectiveness of the selection process, reduce subjectivity, minimize calculation errors, and support decision-making in identifying OSN candidates in a more structured and accurate way.

Pendekatan Data-Driven Menggunakan Metode SAW untuk Pemilihan Karyawan Terbaik pada Mitra Jaya Komputer

Muntahanah Muntahanah — 2026-10-27

Advancements in computer technology have significantly contributed to enhancing the efficiency and effectiveness of human resource management, particularly in the process of selecting the best employee. As employees are a crucial factor in a company's success, the assessment process must be objective, systematic, and transparent. Mitra Jaya Komputer in Bengkulu City routinely selects its best employee based on criteria such as discipline, creativity, attendance, teamwork, and orderliness. However, the current manual assessment process is time-consuming and prone to subjectivity in decision-making. This study aims to develop a Decision Support System (DSS) to facilitate the best employee selection process using the Simple Additive Weighting (SAW) method. The SAW method involves normalizing values based on the specific criteria, then multiplying these normalized values by predetermined weights to calculate a preference score for each employee. These scores are subsequently used to rank the employees based on their final results. The system was developed using the PHP programming language to enable faster and more structured data management and assessment processes. The results indicate that implementing the SAW method assists management in identifying the best employee more effectively, objectively, quickly, and transparently, providing a reliable basis for decision-making. The system also streamlines the documentation and presentation of assessment results.

Implementasi Sistem Ekstraksi Data Otomatis Dari Formulir Administrasi Penduduk Menggunakan Optical Character Recognition Tesseract Di Kelurahan Berkas Kota Bengkulu

Ramalia Apriani — 2026-10-27

Penelitian ini bertujuan membangun aplikasi digitalisasi dokumen administrasi penduduk di Kelurahan Berkas Kota Bengkulu menggunakan Optical Character Recognition (OCR) dan Rule-Based Text Extraction. Aplikasi dikembangkan menggunakan PHP dan MySQL untuk mengubah dokumen citra menjadi data terstruktur. Tesseract OCR digunakan sebagai metode utama dalam proses pembacaan teks, sedangkan EasyOCR digunakan sebagai metode pembanding untuk mengevaluasi hasil pembacaan pada kondisi dokumen yang berbeda. Pengujian dilakukan menggunakan Black Box Testing terhadap 31 dokumen administrasi. Hasil pengujian menunjukkan seluruh fungsi aplikasi berjalan sesuai rancangan. Tesseract menghasilkan rata-rata 921,88 karakter dan 122,98 kata per dokumen, sedangkan EasyOCR menghasilkan rata-rata 908,26 karakter dan 121,16 kata per dokumen. Hasil perbandingan menunjukkan bahwa EasyOCR memberikan hasil pembacaan yang lebih baik pada beberapa kondisi dokumen, yaitu kertas bercak atau bernoda, kusut atau kerumuk, miring, dan buram, berdasarkan kesesuaian hasil pembacaan terhadap ground truth serta tingkat kesalahan pembacaan. Selanjutnya, Rule-Based Text Extraction berhasil mengenali 230 dari 248 field dengan tingkat keberhasilan sebesar 92,74%. Hasil tersebut menunjukkan bahwa aplikasi dapat membantu mempercepat proses digitalisasi dan pengolahan data dokumen administrasi penduduk

Analisis Pola Kriminalitas Menggunakan Data Science Dengan Metode Catboost Classifier Di Polres Kota Bengkulu

Santiya Saputri — 2026-10-28

Crime data management at the Bengkulu City Police Station currently faces several operational constraints, including underutilized historical data and conventional analytical methods that prolong the crime-pattern mapping process. This study aimed to analyze crime patterns through a data science approach using the CatBoost Classifier method to support data-driven tactical decision-making within the police department. A quantitative methodology using an Applied Data Science framework was executed following the Cross-Industry Standard Process for Data Mining (CRISP-DM) framework. The study analyzed crime report data extracted from the Bengkulu City Police database, focusing on temporal (time of occurrence) and spatial (district/kecamatan) variables. Model performance was comprehensively evaluated using a Confusion Matrix. Findings revealed that Motor Vehicle Theft (Curanmor) was the most dominant crime category, with peak vulnerability observed in Selebar District and the majority of incidents concentrated during the early morning hours. Feature Importance analysis indicated that the temporal dimension (Time Category) contributed the most (30.37%), followed by geographical location (District) at 29.30% identifying them as the primary predictors shaping crime patterns. Model evaluation for the CatBoost Classifier yielded an overall accuracy of 49%, reflecting performance limitations due to the small dataset size and imbalanced class distribution. Nevertheless, the model demonstrated a high recall value (89%) specifically in detecting Motor Vehicle Theft. maintaining its mility as an early warning signal for street crimes. Conversely, the model completely failed to predict fraud offenses (0% accuracy) because fraud characteristics are not tied to spatial-temporal patterns. The application of the CatBoost Classifier in this study ts best suited as a tactical intelligence support instrument for street crime mitigation, enabling police administrators to optimize directed patrol strategies in high-risk zones and time windows

Artikel Implementasi Metode Multi Attributive Ideal-Real Comparative Analysis Untuk Pemilihan Guru Terbaik

Andre pranista — 2026-10-28

memiliki peran krusial dalam menentukan mutu pembelajaran dan keberhasilan peserta didik. Karakteristik utama dari seorang guru tidak hanya dinilai dari kompetensi pedagogik di dalam kelas. Proses penentuan guru terbaik masih didominasi oleh penilaian yang bersifat subjektif, kedekatan personal (halo effect), serta kalkulasi data yang bersifat manual. Banyaknya jumlah kriteria yang harus dinilai mulai dari kehadiran, pencapaian akademik siswa, administrasi mengajar, hingga perilaku sosial membuat pengambil keputusan kesulitan dalam menentukan bobot prioritas yang adil. Akibat tidak adanya standarisasi model perhitungan yang transparan. Pemanfaatan Multi Attributive Ideal-Real Comparative Analysis (MAIRCA) ini karena memiliki keunggulan matematis dalam menentukan celah (gap) antara peringkat ideal (apa yang diharapkan) dan peringkat riil (apa yang dicapai secara nyata oleh alternatif). Hasil penelitian menunjukkan bahwa sistem mampu melakukan proses perengkingan dengan baik sesuai dengan tahapan dari algoritma yang digunakan

Sistem Pendukung Keputusan Kelayakan Penerima Kartu Indonesia Pintar Di Madrasah Aliyah Negeri 2 Kota Bengkulu Menggunakan Metode Vlsekriterijumska Optimizacija I Kompromisno Resenje

Oki Ardiansyah — 2026-10-28

The Smart Indonesia Card (Kartu Indonesia Pintar—KIP) is a government educational assistance program designed for underprivileged students to complete their education and prevent dropouts. At State Islamic Senior High School 2 (Madrasah Aliyah Negeri—MAN 2) Bengkulu City, the high volume of KIP applicants relative to the limited quota necessitates a rigorous selection process. However, conventional selection processes remain susceptible to human error. This study aimed to implement the VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) method in a Decision Support System to determine student eligibility for KIP at MAN 2 Bengkulu City. The VIKOR method was selected due to its capability to resolve multi-criteria decision problems with conflicting criteria using a compromise ranking approach. The criteria evaluation comprised academic report grades, parental income, number of dependents, and parental status. The system was developed using Visual Basic.Net programming language following the Waterfall software development life cycle model. The implementation and testing results demonstrated that the application automatically executed student rankings according to VIKOR scores. Computation outcomes generated by the application were completely identical to manual calculations, proving that the system can streamline KIP recipient selection, minimize errors, and produce highly accurate administrative reports.

Analisa Dan Implementasi Sistem Monitoring Jaringan Menggunakan The Dude Dan Routerboard Pada SMKN 5 Bengkulu Selatan

Rexsa Dewantara — 2026-10-29

This study aims to analyze and implement a network monitoring system using The Dude integrated with a MikroTik RouterBoard RB750GR3 at SMKN 5 Bengkulu Selatan. The system is applied to the Computer Laboratory and Teachers’ Room LAN to support real-time monitoring, fault detection, notification, and bandwidth management. The research used a quantitative method with an experimental approach. Testing covered connection status monitoring, network quality, fault detection, and bandwidth management using The Dude, ping, and Simple Queue. The results show that the system can monitor network devices in real time through a network map and send notifications via WhatsApp. The detection time for a connection change from up to down was 5–6 seconds. Manual ping testing produced a delay of 0–1 ms with 0% packet loss, while bandwidth control using Simple Queue successfully applied the configured limits. These results indicate that the implementation improves the effectiveness of network monitoring and supports faster detection and handling of network disruptions.

Optimalisasi Jaringan Wifi Menggunakan VLAN Dan DHCP

Eldy Ovino — 2026-10-29

This study optimizes the WiFi network at SMK Negeri 1 Bengkulu Selatan by implementing Virtual Local Area Network (VLAN) and Dynamic Host Configuration Protocol (DHCP). The implementation uses a MikroTik RB951Ui-2HnD router and a TP-Link ES205G managed switch. The network is divided into VLAN 10 for the Laboratory, VLAN 20 for Administration, and VLAN 30 for the Teachers’ Room, each with a separate DHCP service. Bandwidth management uses Simple Queue with the Hierarchical Token Bucket (HTB) method, while network quality is evaluated using Wireshark. The results show that throughput increased from 4.06 Kbps to 180.02 Kbps, delay decreased from 2.461 ms to 0.256 ms, jitter decreased from 0.352 to 0.335, and packet loss remained at 0%. Bandwidth allocation became more balanced, and inter-VLAN isolation operated as designed. These results indicate that VLAN and DHCP can improve network structure, traffic management, and the reliability of the school WiFi network.

Rancang Bangun Website Informasi Dan Promosi Hotel Harmony In Berbasis Laravel Dengan Integrasi Pemesanan Melalui Whatsapp

Wandi Aprianto — 2026-10-30

Abstract—Hotels that offer several services, such as rooms, villas, karaoke, and a restaurant, need an online medium that presents information and promotions in one place and that the hotel staff can manage independently. This study aims to design and build an information and promotion website for Harmony In Hotel in Kubu Raya, West Kalimantan, with bookings directed to WhatsApp. Development followed the Waterfall model: requirements analysis, design, implementation, testing, and deployment. The system was modeled with the Unified Modeling Language (UML) and built with Laravel, Tailwind CSS, TypeScript, and MySQL, and hosted on IDCloudHost. It provides public pages for rooms, villas, promotions, karaoke, the restaurant, facilities, and a gallery, and an admin panel for content management. Black-box testing of 14 scenarios showed that 14 passed. The website meets the functional requirements defined during the analysis stage. This study did not test the website’s effect on bookings or guest satisfaction.

Intelligent Web Based Admission System Untuk Meningkatkan Kualitas Layanan PPDB

Riska Eka Aprianty — 2026-10-30

The New Student Admission (PPDB) process at MA Hidayatul Qomariah was previously conducted manually, resulting in challenges in recording, verification, storage, and management of applicant data. Prospective students were also required to visit the school directly to obtain information and complete the registration process. This study aims to develop an Intelligent Web-Based Admission System to improve PPDB service quality, simplify the registration process, and assist schools in managing applicant data. The research method used was Research and Development (R&D) with the Waterfall software development model, consisting of requirements analysis, design, implementation, testing, and maintenance stages. Data collection was conducted through observation, interviews, documentation, and literature studies. The system was developed using PHP and MySQL with features including registration, form submission, student and parent data management, document upload, document verification, payment confirmation, announcements, registration status monitoring, and report generation. The results showed that the system successfully transformed the manual registration process into a computerized system. Black Box Testing on 28 test scenarios showed that all functions operated as expected. The system was able to improve registration efficiency, data management accuracy, information delivery speed, and the quality of PPDB services.