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Sistem Informasi Publik Dan Aspirasi Masyarakat Berbasis Web Pada Pemerintah Desa Kalikuto Kecamatan Grabag
The purpose of this research is to design and build a web-based public information and community aspiration system at the Government of Kalikuto Village as well as to determine the impact of the implementation of the web-based public information and community aspiration system at the Government of Kalikuto Village. The research method used is a software engineering approach with the Waterfall system development model. The data collection methods used are observation, interviews, and documentation. The problem analysis method used is PIECES. The design used in this research is UML (Unified Modeling Language) with the PHP programming language and MySQL database using the CodeIgniter framework. The result of this research is the successful design and development of a web-based public information and aspiration system for the Kalikuto Village Government. System testing using Black Box Testing obtained a 100% conformity rate for all system functions. This study also successfully identified the impact of the system implementation, as demonstrated by the user evaluation results through a questionnaire using the Likert Scale. The feasibility score was 85.4%, indicating that the system is highly feasible for implementation. With the existence of this public information and aspiration system, it is expected to improve service activities in Kalikuto Village.
Black Box Testing; Community Aspiration; Kalikuto; Likert Scale; Public Information System
Copyright (c) 2026 Julia: Jurnal Ilmu Komputer An Nuur
Membangun Network Video Recorder (NVR) MenggunakanSet Top Box (STB) Pada Rusunawa Poltesa Berbasis Wireless
This research proposes an innovative solution for recording and storing surveillance video data in the parking environment of Rusunawa Poltesa using a Set Top Box (STB)-based Network Video Recorder (NVR) with Armbian Linux operating system. STBs, typically used for television signal reception, are adapted into intelligent devices to efficiently control and manage surveillance cameras (IP Camera) at a lower cost compared to conventional NVRs. The use of wireless technology increases the flexibility of camera placement without the limitations of cables, simplifies installation, and allows for the adjustment of camera positions according to surveillance needs. The STB-based NVR implementation uses the open-source Shinobi Community Edition (Shinobi CE) software written in Node.js, enabling video recording from IP cameras in H.264 and H.265 formats. This research aims to find an integrated and innovative solution to improve the surveillance system in Rusunawa Poltesa in a modern, efficient, and cost-effective manner. The research results show that the STB-based NVR system can record video at frame rates up to 15 FPS at HD resolution and 5 FPS at SD resolution, with memory consumption of approximately 4.02 MB per minute for HD resolution (1920x1080) and 1.98 MB per minute for SD resolution (1280x720).
Set Top Box; Armbian Linux; Shinobi CE; Network Video Recorder; IP Camera; Wireless; Security System
Sistem Reservasi berbasis Web Pada Tata Salon Boloh
The rapid development of information technology demands that beauty salon businesses optimize their operational processes through computerized systems. Tata Salon Boloh still relies on manual management systems, resulting in inefficiencies in customer data management, service scheduling, inventory control, and financial reporting. This study aims to design a web-based salon management information system using Object-Oriented Programming (OOP) concepts with PHP and MySQL to improve accuracy, efficiency, and service quality. The system development method applies waterfall paradigm with OOP approach to ensure modularity and scalability. The database is designed with MySQL to store customer, service, product, transaction, and report data. The research stages include requirements analysis, UML design implementation, and system testing using a localhost environment. The results show that the developed web-based system features customer management, online booking, service management, product sales, payment gateway integration (Midtrans), financial reporting, and administrative dashboard. Functional testing confirms that all features operate according to salon needs and significantly enhance operational efficiency by 40% with 95% data accuracy. The system also successfully expands market reach by 300% through online booking capabilities. In conclusion, this system supports the digitalization of beauty salon businesses with an intuitive interface, secure data management, and comprehensive business process automation.
beauty salon; MySQL; PHP; Tata Salon Boloh; web-based
SENTINEL-CAI: Secure Ensemble of Neural Threat Intelligence with Noise-resilient Extraction Learning dan Constitutional AI Integration untuk Comprehensive Claude AI Security Framework
The massive adoption of Claude AI in mission-critical applications has exposed a variety of sophisticated vulnerabilities, including prompt injection attacks, model inversion, adversarial perturbations, and multi-modal exploitation. This paper develops the SENTINEL-CAI framework that integrates Constitutional AI enhancement, adversarial training, erase-and-check mechanisms, and multi-layered behavioral analysis to create a comprehensive security framework specifically designed for Claude AI protection. The proposed framework combines an ensemble of specialized neural networks for threat classification, constitutional constraint enforcement through reinforcement learning from AI feedback (RLAIF), adversarial robustness training with certified defense guarantees, and real-time behavioral anomaly detection using transformer-based sequence analysis. The evaluation is performed on a comprehensive dataset that includes 25,000 benign prompts, 15,000 malicious injection attempts, and 8,500 zero-day attack simulations against Claude 3.5 Sonnet and Claude Computer Use. Experimental results show that SENTINEL-CAI achieves an attack detection accuracy of 99.2%, a false positive rate of 0.8%, and a certified robustness guarantee up to a perturbation budget of ε = 0.15. This framework successfully detects 96.4% of zero-day prompt injection attacks with an average response time of 0.12 seconds. The main contribution of this research is the development of the first comprehensive security framework specifically engineered for Claude AI with mathematically provable security guarantees and real-world deployment feasibility.
adversarial training; behavioral analysis; certified robustness; Claude AI security; constitutional AI; LLM security
Sistem Informasi Persediaan Domba Pada Asosiasi Kelompok Ternak Domba Secang Grabag Berbasis Google Maps
The dissemination of information related to the location and availability of sheep within livestock group associations is still carried out manually, making it less effective and hindering consumers from obtaining accurate information. This study aims to design and develop a Sheep Inventory Information System based on Google Maps to help livestock groups disseminate information interactively and improve data accessibility for the public. The system was developed using the Waterfall model, with modeling through Unified Modeling Language (UML) and database design using Entity Relationship Diagram (ERD). It was built using the PHP programming language with the CodeIgniter framework and a MySQL database. Testing was conducted using the Black Box Testing method. The results show that all system functions run properly, and user evaluation using the Likert scale obtained a feasibility percentage of 86%, which is categorized as highly feasible.
MySQL, Sheep Inventory, Likert Scale, Information System, UML
SISTEM INFORMASI PENJUALAN BERBASIS WEB PADA TOKO ERLANGGA FURNITURE MENGGUNAKAN PHP DAN MYSQL DENGAN PENDEKATAN OBJECT ORIENTED PROGRAMMING
The rapid development of information technology demands that business actors optimize sales processes through computerized systems. Erlangga Furniture Store still relies on a manual sales system, resulting in inefficiencies in transaction recording, stock management, and reporting. This study aims to design a web-based sales information system using Object-Oriented Programming (OOP) concepts with PHP and MySQL to improve accuracy and speed in business processes. The system development method applies waterfall paradigm with OOP approach to ensure modularity and scalability. The database is designed with MySQL to store product, transaction, customer, and report data. The research stages include requirements analysis, UML design (Use Case Diagram and Class Diagram), implementation, and system testing using a localhost environment. The results show that the developed web-based system features product management, sales transactions, financial reporting, payment gateway integration, and user authentication. Functional testing confirms that all features operate according to the store's needs and significantly enhance the efficiency of sales processes by 70% with 95% data accuracy. In conclusion, this system supports the digitalization of small businesses like Erlangga Furniture Store with an intuitive interface and secure data management.
Erlangga; Furniture; PHP; Sales Information System; Web-based.
PERANCANGAN SISTEM INFORMASI PENJUALAN PADA TOKO KUEROTI GEMBUL BERBASIS WEB
The development of information technology encourages various business sectors to adopt digital systems in order to improve operational efficiency and effectiveness. Roti Gembul Cake Shop is a micro-enterprise that still conducts its sales processes manually, often facing issues such as recording errors, report delays, and difficulties in managing transaction data. To address these problems, a web-based sales information system was designed, developed using the PHP programming language and MySQL database. The system development uses the Prototyping method, which allows direct interaction with users through the creation of an initial prototype, evaluation, and gradual refinement. The resulting system includes features for recording transactions, managing product data, and generating integrated sales reports that can be accessed in real time. With this system, the sales process is expected to become more efficient, accurate, and supportive of faster decision-making based on valid data.
Information System; Selling; PHP; MySQl; Prototyping;Roti Gembul Cake Shop
Model Hibrid Keamanan Komunikasi Data Menggunakan Federated Lattice-Based Cryptography Dan Homomorphic Stegnography Dengan Optimasi Quantum-Resistant Protocol
Data communication security faces significant challenges with the development of quantum computing and the increasing complexity of cyberattacks. This research proposes an innovative hybrid model that combines Federated Lattice-based Cryptography (FLC) and Homomorphic Steganography (HS) with optimization of Quantum-Resistant Protocol (QRP) for data communication security. This hybrid approach addresses the weaknesses of conventional methods by providing layered security that is resistant to quantum threats and advanced persistent threat attacks. The research methodology uses an experimental approach with the simulation of attacks in a controlled communication environment. Results show that the proposed hybrid model increases resilience against side-channel attacks by 97.3%, reduces latency overhead by up to 42% compared to conventional post-quantum methods, and guarantees mathematical security even in the presence of an adversary with limited quantum computing capabilities. The main contribution of this research is the development of the FLC-HS-QRP algorithm that combines lattice-based key federation with homomorphic steganography in a quantum-resistant communication protocol, as well as parameter optimization for implementation on resource-limited devices. This research fills a critical gap in the literature on communication security and offers a practical approach to securing data communication in the era of quantum computing.
data communication security; lattice-based cryptography; homomorphic steganography; quantum-resistant protocol;cryptographic key federation
Articel TRANSFORMASI DIGITAL UMKM PERCETAKAN: OPTIMALISASI PLATFORM ECOMMERCE TERINTEGRASI PADA ESPRINT.STORE
Digital transformation has become a strategic necessity for Micro, Small, and Medium Enterprises (MSMEs), particularly in the printing sector which demands speed, flexibility, and personalized services. This study aims to examine the effectiveness of the esprint.store platform as a web-based eCommerce solution integrated with WhatsApp API and a dynamic pricing system. A mixed-method approach was employed, combining Google Analytics data, a System Usability Scale (SUS) questionnaire from 120 respondents, and system architecture observation. The results indicate a 35% increase in sales conversion and a reduction in customer response time from 24 hours to 15 minutes. These findings suggest that digitalization through a simple yet functional system can enhance service efficiency and customer satisfaction within the MSME.
Digital transformation; Dynamic pricing; eCommerce; MSMEs; WhatsApp integration
Copyright (c) 2025 Julia: Jurnal Ilmu Komputer An Nuur
WEB-BASED SALES INFORMATION SYSTEM AT ERLANGGA FURNITURE STORE USING PHP AND MYSQL WITH AN OBJECT ORIENTED PROGRAMMING APPROACH
PENGAMANAN DATABASE MENGGUNAKAN MODEL HIBRID BLOCKCHAIN DAN HOMOMORPIC ENCRYPTION DENGAN OPTIMASI ZERO-KNOWLEDGE PROOF
Database security has become a crucial issue with the increasing cyber threats and data breaches that significantly impact organizations and individuals. This research proposes an innovative hybrid model that integrates blockchain technology, homomorphic encryption, and zero-knowledge proof to secure databases. This approach offers a multi-layer security mechanism that enables user identity verification without exposing credentials, encrypted data processing, and immutable access tracking. The research method uses an experimental approach with attack simulations on databases implemented with and without the proposed hybrid model. Results show significant improvements in resistance against SQL injection attacks (99.7%), man-in-the-middle attacks (98.2%), and unauthorized access (100%) compared to conventional methods. Although there is a trade-off in the form of a 12% latency increase, this hybrid model offers an optimal balance between security and performance. The main contribution of this research is the development of zero-knowledge proof integration algorithm that optimizes the verification process by reducing computational overhead by 35% compared to conventional implementations.
blockchain; databasesecurity; ecryption; homomorphic; proof security hybridization; zero-knowledge
SMART-GUARD: Self-adaptive Multi-Agent Reinforcement learning Threat Guard dengan Game Theory dan Consensus Mechanisms untuk Enhanced Wireless Access Point Security
Kompleksitas serangan cyber terhadap wireless access point semakin meningkat dengan munculnya adversarial AI dan coordinated attack scenarios. Penelitian ini mengembangkan framework SMART-GUARD (Self-adaptive Multi-Agent Reinforcement learning Threat Guard) yang mengintegrasikan multi-agent reinforcement learning (MARL), game theory, dan consensus mechanisms untuk membangun sistem pertahanan adaptif dan kolaboratif. Framework yang diusulkan menggabungkan Deep Q-Networks (DQN) dengan hierarchical multi-agent architecture, Stackelberg game untuk strategic defense planning, Self-Organizing Maps (SOM) untuk threat clustering, dan Byzantine-fault tolerant consensus untuk koordinasi terdistribusi. Evaluasi dilakukan pada testbed yang mensimulasikan 20 access points dengan 500 client devices dan 15 jenis serangan berbeda. Hasil eksperimen menunjukkan SMART-GUARD mencapai defense success rate 97.4%, mean response time 1.2 detik, dan resource utilization efficiency 89.3%. Framework ini mampu beradaptasi dengan 12 jenis zero-day attacks dengan confidence level 92.8% dan menunjukkan scalability yang superior hingga 1000+ access points. Kontribusi utama penelitian ini adalah pengembangan self-adaptive defense ecosystem yang dapat melakukan strategic decision making secara autonomous melalui game-theoretic analysis dan koordinasi multi-agent yang fault-tolerant.
multi-agent reinforcement learning, game theory, wireless security, consensus mechanisms, adaptive defense, distributed intelligence;
AI-BAHSI: A Hybrid Method of Artificial Intelligence-Behavioral Analysis and Hybrid Security Intelligence for Real-time Threat Detection and Mitigation on Wireless Access Points
Wireless access point (AP) security faces significant challenges with the emergence of sophisticated attacks such as SSID Confusion (CVE-2023-52424), KRACK attacks, and advanced persistent threats. This research develops a hybrid AI-BAHSI (Artificial Intelligence-Behavioral Analysis and Hybrid Security Intelligence) method that integrates deep learning, ensemble machine learning, and federated learning for real-time threat detection and mitigation on wireless access points. The proposed method combines Convolutional Neural Network-Long Short Term Memory (CNN-LSTM) for pattern recognition, Random Forest-Support Vector Machine ensemble for threat classification, and federated learning for privacy-preserving security intelligence. Evaluation was conducted on a synthetic dataset that includes 15,000 normal traffic samples and 8,500 attack samples of various types. The results show that AI-BAHSI achieves a detection accuracy of 98.7%, a precision of 97.3%, a recall of 98.1%, and an F1-score of 97.7% with a false positive rate of only 1.2%. This method successfully detected zero-day attacks with a 94.6% confidence level and was able to automatically mitigate them in an average of 0.8 seconds. The main contribution of this research is the development of an adaptive security framework that can learn from new attack patterns in real time while preserving privacy through a federated learning architecture.
wireless security; access point protection; machine learning; behavioral analysis; federated learning;
Optimalisasi Manajemen Kampanye Airdrop Kripto pada Blockchain Layer 1 dan Layer 2 dalam Fase Pengembangan: Studi Kasus Implementasi AirdropHub
This study analyzes the optimalization strategies for managing crypto airdrop campaigns on Layer 1 blockchain projects (e.g., Ethereum, Solana) and Layer 2 projects (e.g., Polygon, Arbitrum) during the development phase, with a focus on the AirdropHub platform based on native PHP MVC. This study evaluates the effectiveness of AirdropHub in supporting the planning, execution, and monitoring of airdrop campaigns, particularly through its daily quest management and wallet participation tracking features. A descriptive-analytical approach was used with a case study on AirdropHub, involving observations of system functionality, analysis of participation data, and evaluation of technological architecture. The results show that AirdropHub is capable of efficiently managing airdrop campaigns with CRUD features and activity tracking, although challenges such as system scalability and blockchain integration remain. This research provides practical insights for blockchain developers and community managers in designing structured, secure airdrop campaigns that encourage community engagement.
Airdrop Crypto; Blockchain Layer 1; Blockchain Layer 2; Blockchain; PHP Native MVC;
Sistem Penjualan Pakaian Online "tukuCALAMBY"
The development of information and communication technology has changed the way consumers shop, especially in the fashion and clothing industry. This study aims to develop an online clothing ordering system called “tukuCALAMBY.” This system is useful for improving the efficiency of the sales process and providing convenience for customers when shopping. The system is designed using a web-based approach with two main actors, namely the admin and the customer. The system development method employs the Software Development Life Cycle (SDLC) approach using the Waterfall model by Sommerville. The design utilizes system modeling with the Unified Modeling Language (UML). The development results demonstrate that the “tukuCALAMBY” system successfully integrates features for managing product data, ordering, payment, and reporting into a single user-friendly platform. This system provides an effective solution to expand market reach and improve operational efficiency for online clothing stores. User Acceptance Testing (UAT) involving 20 users yielded a testing result of 92%.
clothing, online ordering, tukuCALAMBY, UML, Waterfall, web-based
PREDIKSI LUAS PANEN DI KECAMATAN PURWOADADI MENGGUNAKAN ALGORITMA REGRESI LINEAR BERGANDA
Agriculture, particularly rice cultivation, is highly vulnerable to climate change because it depends on water cycles and weather conditions to maintain productivity. Climate change affects crop growth, development, and yields, as agricultural activities are heavily dependent on weather and climate. This study utilizes data mining to introduce a new breakthrough in addressing rice farming issues in Grobogan Regency, Purwodadi District. The method used is multiple linear regression, with the dependent variable being harvested area and the independent variables including plxanted area and rainfall. The objective of this research is to test and develop data mining methods to predict yield levels, thereby assisting local governments in decision-making during crop failures, based on agricultural data from 2019 2023. The research process involves data collection, preprocessing, algorithm implementation, and result evaluation. The analysis shows that the multiple linear regression model provides reasonably accurate predictions, with a Root Mean Square Error (RMSE) value of 209.042 and a Relative Root Squared Error (RRSE) of 0.111. Furthermore, the analysis reveals that planted area significantly influence the harvested area. These findings offer insights for local governments as policymakers in providing aid during crop failures.
Data mining1; Yield prediction2; Multiple linear regression3
PENERAPAN SISTEM INFORMASI STOK BARANG BERBASIS APLIKASI UNTUK MENINGKATKAN EFISIENSI PENGELOLAAN INVENTARIS PADA TOKO SEMBAKO
Perkembangan teknologi informasi yang berkembang pesat memberikan dampak yang signifikan ke berbagai sektor, seperti pengelolaan inventaris di sektor ritel. penelitian ini bertujuan untuk menerapkan sistem informasi yang berbasis aplikasi untuk stock barang agar meningkatkan efisiensi pengelolaan inventaris pada toko. aplikasi yang di bangun di harapkan dapat mempermudah pemantauan stok barang, mempercepat proses pencatatan transaksi, serta meminimalisir kesalahan dalam mengelola data stock. metode yyang di gunakan dalam penelitian ini adalah pengembangan aplikasi berbasis perangkat lunak yang dapat memberikan hasil laporan inventaris secara akurat. hasil yang di harapkan dari penerapan sistem informasi ini adalah pengurangan tingkat kesalahan, serta pengelolaan stok yang lebih mudah dan cepat. Penelitian ini memiliki kontribusi dalam memberikan solusi bagi toko-toko untuk menghadapi tantangan pengelolaan inventaris yang lebih kompleks di era digital sekarang.
sistem informasi; stock barang; aplikasi; pengelolaan inventaris; efisiensi;
Sistem Informasi Pembuatan Aplikasi Berbasis Web Pada Konveksi ‘Sania Komveksi’
Perkembangan teknologi informasi yang pesat telah mempengaruhi berbagai sektor bisnis, termasuk industri konveksi. Sistem informasi berbasis web kini menjadi solusi efektif untuk meningkatkan efisiensi operasional dan manajemen data. Penelitian ini bertujuan untuk merancang dan mengimplementasikan sebuah aplikasi berbasis web pada konveksi ‘Sania Konveksi’ yang dapat membantu dalam pengelolaan data produksi, pemesanan, inventaris, serta pelaporan secara lebih terstruktur dan real-time. Aplikasi ini dibangun dengan menggunakan metode pengembangan perangkat lunak Waterfall, dimulai dari tahap analisis kebutuhan, desain sistem, implementasi, sampai dengan pengujian. Hasil penelitian ini adalah sebuah aplikasi berbasis web yang mampu mengintegrasikan berbagai proses bisnis pada konveksi, memudahkan pihak manajemen dalam memonitor kinerja operasional, serta meningkatkan efisiensi dalam pengelolaan data dan proses produksi. Berdasarkan hasil pengujian, sistem ini terbukti dapat memberikan kemudahan dan efisiensi dalam pengelolaan operasional konveksi ‘Sania Konveksi’
IMPLEMENTASI ALGORITMA APRIORI UNTUK MENCARI POLA TRANSAKSI PENJUALAN PADA TOKO PERTANIAN TOKO BIDSALTANI
Progress in the industrial sector is currently growing rapidly, especially in medium and upper-class businesses, especially in agricultural shop businesses. Agricultural shops are one of the medium-sized businesses where competition is quite tight, this can be seen from the high consumer demand for fertilizer and agricultural equipment.With the high demand of consumers for agricultural needs as well as intense competition, agricultural shop companies must further improve their business performance in order to be able to face the problems that occur.Bidsal Tani is one of the many agricultural shops in Purwodadi District that sells agricultural necessities, such as chemical fertilizer, compost, plant seeds and all other agricultural necessities, it can be seen that to make a profit as expected.The a priori algorithm is a market basket analysis algorithm used to produce association rules. Association rules can be used to find relationships or cause and effect. The results of the research are that the products frequently purchased by consumers are PHONSKA, NPA, ZA, FASTAC, KOGE, UREA, GANDASIL, FLORAN, SP36, TSP, WUXAL, BAYFOLAN, BLOPATEK, KCL, HYDRASIL AND DECIS products.
Data mining1; Appriori2; Fp-Growt3; rapid miner4
Copyright (c) 2024 Julia: Jurnal Ilmu Komputer An Nuur
ANALYSIS OF SENTIMENT ON TEACHER MARKETPLACE ISSUES USING THE LEXICON AND K-NEAREST NEIGHBOR ALGORITHMS
The advancement of social media makes it easier for users to express opinions. Twitter has become one of the media that is loved by internet users, users can freely express their thoughts or opinions, apart from that they can also express everything that is being experienced. The busy issue of the Teacher Marketplace initiated by the Minister of Education, Nadiem Makarim, has invited many comments from internet users. Twitter users' tendencies in posting content can be determined by analyzing sentiment. In this research, the Lexicon and K-Nearest Neighbor (KNN) methods are proposed to analyze sentiment towards the education minister's discourse on Twitter social media on the topic of Teacher Marketplace Issue Sentiment by classifying it into positive, neutral and negative. The results of this research show that the accuracy value obtained was 91.70%, precision 90.51%, recall 71.95%. By carrying out this sentiment analysis, it is hoped that the problems contained in the Marketplace Guru topic controversy can be identified, used as input and consideration for further research.
Twitter, K-Nearest Neighbor, sentiment analysis.
PREDIKSI TINGKAT KELULUSAN MAHASISWA S1 UNIVERSITAS AN NUUR DENGAN METODE DECISION TREE C4.5
One of the private universities in Purwodadi is An Nuur Purwodadi University. Many students have graduated from An Nuur Purwodadi University, but there are some students who did not graduate on time. This poses a problem and raises a significant question as to why these students did not graduate on time. A decision tree is a suitable data mining method for this research because it has the advantage of identifying and summarizing patterns in the data. The Decision Tree algorithm has an accuracy of 96.25%. The recall values for each class are 97.37% for the "Late" class and 95.00% for the "On-Time" class. Meanwhile, the precision values for each class are 94.87% for the "Late" class and 97.44% for the "On-Time" class
Student graduation1; decision tree2; university3; rapid miner4
OPTIMIZATION OF PARTICLE SWARM OPTIMIZATION IN NAÏVE BAYES FOR CAESAREAN BIRTH PREDICTION
The Maternal Mortality Rate (MMR) in 2017 according to the World Health Organization (WHO) is estimated to reach 296,000 women who die during and after pregnancy or childbirth. Caesarean birth is the last alternative in labor if the mother cannot give birth normally due to certain indications with a high risk, both for the mother and the baby. factors of a mother giving birth by caesarean section, such as placenta previa, hypertension, breech baby, fetal distress, narrow hips, and can also experience bleeding in the mother before the delivery stage. It is hoped that delivery by caesarean method can minimize problems for the baby and mother. Accurate prediction of the condition of the mother's pregnancy can enable d octors, health care providers and mothers to make more informed decisions regarding the management of childbirth. To predict caesarean births, data mining techniques using the Naive Bayes algorithm can be used. Naive Bayes is very simple and efficient but very sensitive to features, therefore the selection of appropriate features is very necessary because irrelevant features can reduce the level of accuracy. Naive Bayes will work more effectively when combined with several attribute selection procedures such as Particle Swarm Optimization. In this study, the researcher proposes a Particle Swarm Optimization algorithm for attribute weighting in Naive Bayes so as to increase the accuracy of Caesarean birth prediction results
Caesarean Birth, Prediction, Naïve Bayes, Particle Swarm Optimization
Copyright (c) 2022 Julia: Jurnal Ilmu Komputer An Nuur
PENGGUNAAN ALGORITMA FP-GROWTH UNTUK MENENTUKAN PAKET PENJUALAN PADA TOKO PERLENGKAPAN KONVEKSI SRI BUSANA
Consumers of the Sri Busana convection shop are mostly tailors, both home and convection tailors, which are pretty large, especially in Grobogan district. The increasing number of fashion businesses or tailors in Grobogan district makes data on goods and sales at the sri busana convection shop increase because the sri busana convection shop always strives to meet the needs of tailors or home convection. In overcoming the problem of finding more efficient consumer patterns, an analysis of buying patterns is carried out. Consumer buying patterns were analyzed using Association rules and FP-Growth methods. With this algorithm, the process of determining consumer purchasing patterns consists of 2 product combinations with a support value of 50% and a confidence value of 100%. 3 product combinations with a support value of 40% and a confidence value of 80%. 4 product combinations with a support value of 40% and a confidence value of 80%.
toko; transaksi_penjualan; data_mining; fp_growth; konsumen;
Risk Management in Final Semester Exam Information System Using NIST 800-30 Method (Case Study of SMKN 2 Baleendah)
In the use of information systems and technology, risk is something that must be anticipated. Risks can arise from various things such as information security, fire, hardware damage, etc. that can disrupt the organization's business processes. With the possible emergence of risks in the use of information systems and technology, risk management is needed to facilitate the identification of possible occurrences of these risks. Risk management is the practice of identifying, assessing, controlling and mitigating risks. SMK Negeri 2 Baleendah is a vocational high school that has 5 areas of expertise competence, namely culinary, beauty, fashion, industrial chemistry, and computer network engineering. SMK Negeri 2 Baleendah as an organization engaged in education has implemented online exam information technology. Of course, the application of information technology raises a problem. From these problems, risk management is needed to minimize risk by conducting a risk assessment. NIST 800-30 is a standard document developed by the National Institute of Standards and Technology. NIST 800-30 has two important stages, namely risk assessment and risk mitigation. This research will use the NIST SP 800-30 method as a method that will solve the existing problems. Therefore, a risk assessment was chosen using the NIST SP 800-30 method (Case Study: SMK Negeri 2 Baleendah)
information systems and technology; risk management; SMK Negeri 2 Baleendah; NIST 800-30.
GENETIC ALGORITHM FOR FEATURE SELECTION IN NAÏVE BAYES IN LIFE RESISTANCE CLASSIFICATION ON BREAST CANCER PATIENT
Breast cancer is the most common cancer in women's suffering and is the second leading cause of death for women (after lung cancer). More than one million cases and nearly 600,000 breast cancer deaths occur worldwide each year. Survival is generally defined as surviving patients over a period of time after the diagnosis of the disease. Accurate predictions about the likelihood of survival of breast cancer patients can allow doctors and healthcare providers to make more informed decisions about patient care. To classify the survival of breast cancer patients can do the utilization of data mining techniques with Naive Bayes algorithm. Naive Bayes is very simple and efficient but very sensitive to the features so from it the selection of the appropriate features is in need because irrelevant features can reduce the level of accuracy. Naive Bayes will work more effectively when combined with some attribute selection procedures such as Genetic Algorithm. In this study the researchers proposed the Genetic Algorithm for Feature Selection on Naive Bayes so as to improve the accuracy of breast cancer survival classification results. In this study using a private dataset breast cancer patients. The results show that Naive Bayes Genetic Algorithm has a higher accuracy of 90% compared to Naive Bayes with 86% accuracy
Breast Cancer, Survival, Classification, Feature Selection, Naive Bayes, Genetic Algorithm
Copyright (c) 2021 Julia: Jurnal Ilmu Komputer An Nuur
EARLY DETECTION OF DIABETES MELLITUS USING RANDOM FOREST ALGORITHM
Diabetes mellitus is a deadly disease. Patients with this disease often do not realize that they are improving their diabetes mellitus. It is necessary to do early prevention in order to reduce the sudden death rate of people with diabetes mellitus. In addition, during the COVID-19 pandemic, which increases the risk of death for people with comorbid diabetes mellitus. A system model for the prediction of diabetes mellitus is needed for early diagnosis of this disease. By using machine learning techniques using the Random Forest algorithm and Information Gain can be used to predict diabetes mellitus. This model has a fairly high level of accuracy, which is 98.27%, precision is 97.69% and recall is 98%.
diabetes mellitus; random forest; information gain; machine learning;
STRATEGIC PLANNING OF MONTHLY DONATION PAYMENT INFORMATION SYSTEM AT SMK AT-THOAT TOROH
The development of a school, has an impact on the development of various services in the school. If school doesn’t improve the services, schools can lose competition, especially for private schools. The same thing happened at SMK At-Thoat Toroh. This Vocational High School, located in Grobogan Regency, Central Java, experiences significant development every year. One of the indicators is the increasing number of new students enrolling to the school. Even though the number of new students is increasing, At-Thoat Toroh Vocational School must still be able to serve the needs of all its students well. One form of this service is the payment of monthly donations. So far, students who will pay monthly contributions have to come to the teacher's office to meet the administration department. This often creates a crowd at the teacher's office door. Apart from being uncomfortable, it's certainly not a good thing in the midst of the current Covid-19 outbreak. In addition, the recording of monthly contributions by the administrative division is still done manually. This often causes disorder and confusion in recording student monthly contributions. Even though this record is very sensitive, because it relates to school finances. To overcome this problem, it is necessary to have a strategic planning of a monthly donation payment information system. This strategic planning uses the waterfall method and SWOT analysis. It aims to facilitate the analysis and process of making a monthly donation payment information system. The result of this research is the formulation of a monthly donation payment information system business strategy.
Information System, Strategic Planning, SWOT Analysis, Waterfall
COMPARISON OF SVM, KNN, AND NAIVE BAYES METHOD WITH N-GRAM IN TRAFFIC ACCIDENT CLASSIFICATION
Traffic accidents that occur in Indonesia are still relatively high, the information can be easily obtained through social media, one of which is Twitter. The amount of traffic accident information can be processed and classified according to certain categories. Traffic accident data classification is done using SVM, KNN and Naïve Bayes methods using n-gram feature extraction. The results of this study indicate the best accuracy is 87.63 using the KNN method.
Traffic Accident, Classification, SVM, KNN, Naïve Bayes, N-Gram
COMPUTER NETWORK ANALYSIS USING NETWORK MANAGEMENT SYSTEM AT AN NUUR UNIVERSITY
During the pandemic, teaching and learning activities have changed. Which originally used the offline format to go online and its combinations. Internet bandwidth usage plays an important role in the success of the teaching and learning process on campus, including at An Nuur University. By using Cacti Network Management System it can be used as a monitoring system to monitor the movement of internet bandwidth whether it meets the needs of the online learning process or not. Internet bandwidth usage is influenced by several factors such as logical topology, physical topology and configuration in computer networks.
Internet Bandwidth; Cacti; Network Management System;
Information System Using The Web For Garbage Bank Transactions (A Case Study of TPS 3R Sido Makmur, Sidoharjo, Pacitan)
The construction of a web software, is expected to assist users in processing data and obtaining information quickly, precisely and as needed, along with technological developments, especially in the field of information technology This application contains the Garbage Bank Information System at TPS 3R Sido Makmur, Sidoharjo village, Pacitan district. Application is built using HTML, PHP and CSS programming. The database used is MySQL. With this information system, it is expected to be able to handle transactions that run at the waste bank and provide data reports needed by system users, so that the waste bank work process is more effective and efficient.
Garbage Bank; Information System; PHP; HTML; CSS;