CICES (Cyberpreneurship Innovative and Creative Exact and Social Science) merupakan salah satu wadah publikasi jurnal yang diterbitkan oleh Universitas Raharja, melalui Raharja Enrichment Centre selaku LPPM-Mutu untuk multidisiplin ilmu Meliputi bidang pendidikan, politik, manajemen, sosial, budaya, kesehatan, hukum, ekonomi, IT (Teknik Informatika), Teknik Sipil, Teknik Elektro, Teknik Mesin dan bidang ilmu lainnya. Frekuensi terbitan CICES (Cyberpreneurship Innovative and Creative Exact and Social Science) setiap 6 bulan atau 2 kali dalam setahun pada periode Februari dan Agustus. dengan Nomor ISSN 2356-5209 (media cetak) dan e-ISSN 2655-3058 (media online) mulai edisi Vol. 5, No. 1, Februari 2019. >> cices@raharja.info | https://raharja.ac.id/ This work is licensed under a Lisensi Creative Commons Attribution-ShareAlike 4.0 International (CC BY-SA 4.0) Indexed By
Pengembangan Sistem Validasi Keabsahan Invoice Dengan Integrasi QR Code Dan Algoritma TOTP (Studi Kasus CV. Mandiri Bersama)
Sistem validasi keabsahan invoice sangat penting dalam dunia bisnis untuk mencegah pemalsuan dokumen dan memastikan transaksi yang sah. Penelitian ini mengembangkan sistem berbasis web yang mengintegrasikan Quick Response (QR) Code dan algoritma Time-based One-Time Password (TOTP) untuk meningkatkan keamanan dan keabsahan invoice pada CV. Mandiri Bersama. QR Code digunakan untuk memberikan akses cepat dan langsung ke informasi invoice, sementara algoritma TOTP digunakan untuk mengotentikasi pengguna yang berwenang dengan kode unik yang terus berubah dalam interval tertentu. Sistem ini juga menerapkan metode Two-Factor Authentication (2FA) dengan kombinasi email dan OTP yang dihasilkan menggunakan algoritma TOTP, memastikan bahwa hanya pengguna yang memiliki akses email yang sah yang dapat melakukan validasi invoice. Dengan penerapan sistem ini, proses validasi invoice menjadi lebih aman, akurat, dan efisien. Hasil implementasi menunjukkan bahwa QR Code dapat dimanfaatkan untuk memvalidasi keabsahan invoice dengan cepat dan efisien, sementara OTP dari algoritma TOTP dapat menjaga keamanan akses invoice dengan memastikan hanya pengguna yang berhak yang dapat melakukan verifikasi, sehingga mengurangi risiko manipulasi atau penyalahgunaan dokumen.
Perbandingan Hukum Pidana Indonesia dan Malaysia Terhadap Kekerasan Dalam Rumah Tangga KDRT
This study aims to analyze the comparative regulation and implementation of criminal law related to domestic violence (DV) in Indonesia and Malaysia. In Indonesia, DV is specifically regulated in Law Number 23 of 2004 concerning the Elimination of Domestic Violence (UU PKDRT). Meanwhile, Malaysia uses a combination of the Kanun Keseksaan (Act 574) and the Domestic Violence Act 1994 (Act 521). Both countries share similarities in terms of recognizing physical violence, classifying victims, and threatening criminal sanctions. However, there are fundamental differences regarding the number of articles governing it, the types of offenses, the formulation of criminal penalties, and the severity of the criminal sanctions. The methodology used in this study is normative juridical, a legal research approach that focuses on applicable positive legal norms or rules. The results show that although Indonesia has more comprehensive regulations, in practice, both countries still face structural and cultural challenges in enforcing domestic violence laws. The conclusion of this study confirms that comparative criminal law studies provide a broader understanding of the diversity of legal systems and can serve as a foundation for strengthening victim protection more effectively.
Media Informasi Terkait Peraturan Pengangkutan Prohibited Items Bagi Penumpang Pesawat Udara
Aviation security plays a crucial role in ensuring the safety, security, and convenience of air transportation. One of the challenges frequently encountered at airports is the limited awareness of passengers regarding regulations on prohibited items and dangerous goods, resulting in a high number of restricted items being detected during security screening procedures. This condition may lead to delays in security inspections, increased passenger queues, and reduced airport operational efficiency. This study aims to develop Trip.buddy, a mobile-based digital information application designed to provide educational content and information regarding baggage transportation regulations for airline passengers. The research employed a qualitative descriptive approach, with data collected through observation, interviews, and literature review. System requirements were analyzed using the PIECES framework (Performance, Information, Economy, Control, Efficiency, and Service), while the application was developed using the Software Development Life Cycle (SDLC) model. The results indicate that Trip.buddy effectively provides accessible information on dangerous goods classifications, power bank transportation regulations, prohibited items guidelines, and a “What Can I Bring?” search feature that enables users to verify the status of items before traveling. The implementation of the application improves information quality, facilitates access to aviation security regulations, enhances the efficiency of security screening processes, and increases passenger awareness of aviation security requirements. Therefore, Trip.buddy can serve as an innovative digital solution to support airport service digitalization and improve the dissemination of prohibited items regulations among airline passengers.
Perbandingan Kinerja Algoritma Apriori dan Eclat Equivalence Class Transformation Dalam Menerapkan Rekomendasi Barang Diskon pada Data Transaksi
This research aims to compare the performance of the Apriori and ECLAT algorithms in applying discounted goods recommendations on sales transaction data. The research method used involves six main stages, namely collecting transaction data from CV SOSO Group Jombang, preprocessing data to clean and prepare data, implementing the Apriori and ECLAT algorithms, forming association rules, evaluating algorithm performance, and visualizing analysis results. The transaction dataset used comes from sales during October and is processed using the Market Basket Analysis approach. Apriori and ECLAT algorithms are tested to find customer purchase patterns by considering the support, confidence, and lift factors in the association rules. Performance evaluation is done by measuring the number of intemsets generated, computation time, and the quality of the rules obtained. The results showed significant differences between the two algorithms. Apriori is easier to implement and provides rules that are more easily understood by decision makers, while ECLAT is superior in time efficiency and memory usage, especially on small to medium-sized datasets. After a comparative analysis, it was found that the ECLAT algorithm is faster in finding transaction patterns with a shorter execution time than Apriori. However, Apriori algorithm is more effective in displaying association rules that are clearer and easier to interpret. With these results, this research recommends the use of algorithms based on specific needs, namely Apriori for more interpretative analysis and ECLAT for analysis with larger and more complex datasets.
Copyright (c) 2026 CICES (Cyberpreneurship Innovative and Creative Exact and Social Science)
Analisa Yuridis Dalam Konteks Pembaharuan Hukum Pidana di Indonesia
The purpose of this paper is to analyze criminal law reform in Indonesia, which is crucial to ensure justice and security in society. Criminal law itself is a branch of law that regulates criminal acts and the sanctions imposed on perpetrators. The methodology used in this paper is a juridical-normative approach to legal research that focuses on applicable legal norms or regulations based on statutes. The results of this analysis indicate the need for efforts to improve the quality of criminal law enforcement in Indonesia, such as improving the quality of investigations and trials, and strengthening the independence of law enforcement agencies. Overall, criminal law reform is crucial to ensure justice and security in society. However, it is important to remember that criminal law reform is insufficient if it is not accompanied by sound and effective law enforcement.
Performa Model Faster R-Cnn Untuk Klasifikasi Penyakit Daun Jagung
Image classification is one of the main challenges in the field of digital image processing and computer vision. This study aims to develop an image classification system using the Faster R-CNN object detection method. The Faster R-CNN model is utilized to detect objects in images while also classifying the extracted features from those images. The dataset used in this study was sourced from Kaggle and data taken directly by researcher. The data underwent several preprocessing stages, including data transformation, splitting into training / validation / testing sets, and model performance evaluation based on metrics such as accuracy, precision, recall, anda F1-Score. The experimental results demonstrate that the Faster R-CNN method can achieve high classification performance, with accuracy reaching up to 98,98% at a data ratio of 60:20:20. In addition, the model also shows performance stability at other data ratios. This study confirms that deep learning methods can deliver excellent results in image classification tasks. This research is expected to be a reference for the development of other image classification systems, especially those that require accurate object detection and classification.
Aplikasi Mobile Penjualan Makanan Sisa Dengan Geolocation Dan Metode Haversine
Food waste is a critical global issue with significant economic and environmental implications. In 2021, approximately 40% of the total global food production, equivalent to 2.5 billion tons, was wasted. This figure marks a notable increase of 1.2 billion tons from the estimated food waste in 2011. Globally, Indonesia ranks second in terms of the highest levels of food waste, with 39.4% of the total waste generated in the country being food waste. This statistic makes food waste the predominant type of waste in Indonesia. This research aims to design and develop a mobile geolocation based application for the sale of surplus food, utilizing the haversine method to facilitate this process. The application is designed to allow users to access the locations of surplus food sellers within a maximum radius of 25 kilometers from their position. The results indicate that the developed application successfully displays the distance between consumers and surplus food sellers. Black box testing successfully ensures that all application functionality runs well. The level of user acceptance of the application is at the acceptable level, and the application grade is B.
Copyright (c) 2025 CICES (Cyberpreneurship Innovative and Creative Exact and Social Science)
Implementasi Aplikasi CRM Berbasis Mobile dengan Waterfall Development untuk Efisiensi Kerja Karyawan di PT Kobe Boga Utama Kudus
Penelitian ini bertujuan untuk mengembangkan aplikasi Customer Relationship Management (CRM) berbasis Android dengan menggunakan model pengembangan Waterfall untuk meningkatkan efisiensi kerja karyawan di PT Kobe Boga Utama, Kudus. Aplikasi ini dirancang dengan memanfaatkan Flutter sebagai framework pengembangan dan bahasa pemrograman Dart, yang mendukung fitur-fitur unggulan seperti notifikasi real-time, manajemen tugas, proyek, jadwal, serta komunikasi berbasis chat. Penelitian menggunakan metode kualitatif dengan pengumpulan data melalui wawancara, observasi, dan studi literatur. Hasil implementasi menunjukkan bahwa aplikasi ini mampu mengatasi kendala operasional seperti koordinasi yang kurang efektif dan pengelolaan tugas manual. Pengujian menggunakan metode Black Box Testing memastikan seluruh fungsi aplikasi berjalan sesuai spesifikasi, seperti pengelolaan tugas, integrasi kalender, dan notifikasi real-time. Hasil penelitian ini menunjukkan bahwa aplikasi CRM berbasis Android tidak hanya meningkatkan efisiensi kerja karyawan tetapi juga memberikan kontribusi positif terhadap pertumbuhan bisnis secara berkelanjutan. Kata Kunci— Customer Relationship Management, Flutter, Efisiensi Kerja, Waterfall Development, Aplikasi Mobile
Sistem Informasi Kpi Untuk Analisis Kinerja Karyawan Menggunakan Naive Bayes Di Pt Jembatan Data Pangrango
Penelitian ini mengembangkan sistem analisis kinerja karyawan berbasis web untuk menganalisis dan memprediksi kinerja karyawan menggunakan metode Recurrent Neural Network (RNN) di PT Jembatan Data Pangrango, sebuah perusahaan penyedia layanan internet di Sukabumi. Sistem analisis kinerja karyawan manual yang sebelumnya digunakan menyebabkan inefisiensi dalam memantau dan mengevaluasi kinerja. Dengan pendekatan Rapid Application Development (RAD), sistem ini dibangun untuk mencatat absensi, mendeteksi anomali, dan menganalisis pola kinerja karyawan berdasarkan data historis. Sistem ini juga mampu memprediksi performa karyawan secara individual dan memberikan rekomendasi pelatihan yang sesuai untuk peningkatan kinerja. Hasil pengujian menunjukkan bahwa sistem dapat mendeteksi pola ketidakhadiran, keterlambatan, dan lembur, sehingga memudahkan perusahaan dalam melakukan evaluasi kinerja dan perencanaan pengembangan karyawan secara lebih efektif.
Optimasi Model Prediksi Kelulusan Mahasiswa Berbasis Principal Component Analysis dan Modified KNearest Neighbor
Angka drop-out mahasiswa di perguruan tinggi masih menjadi permasalahan serius karena berdampak pada pemborosan sumber daya dan perkembangan institusi. Identifikasi dini terhadap mahasiswa berisiko drop-out sangat penting, namun metode manual dan algoritma K-Nearest Neighbor (KNN) konvensional masih memiliki keterbatasan, seperti sensitivitas terhadap outlier dan data berdimensi tinggi. Penelitian ini mengusulkan integrasi Principal Component Analysis (PCA) dan Modified K-Nearest Neighbor (MKNN) untuk meningkatkan akurasi klasifikasi kelulusan mahasiswa. PCA digunakan untuk mereduksi 14 variabel menjadi 2 variabel utama, sedangkan MKNN memodifikasi KNN dengan teknik weight voting berbasis jarak serta validasi data latih guna mengurangi perngaruh outlier. Model diujikan dengan skema pembagian data 60:40 (latih:uji) dan parameter optimal k=9. Hasil penelitian menunjukkan bahwa kombinasi PCA dan MKNN mampu mencapai akurasi 99,31%, meningkat 0,93% dibanding KNN standar, serta menghasilkan presisi, recall, dan F1-Score sebesar 99,3%. Temuan ini menegaskan bahwa integrasi reduksi dimensi dan weight voting efektif dalam meningkatkan kinerja klasifikasi, sehingga model ini berpotensi menjadi alat prediksi drop-out yang andal di lingkungan pendidikan tinggi.
Analisis User Experience Pada Website Pendaftaran Santri Pondok Pesantren Salafiyyah AlHidayah Kudus Menggunakan Metode Heuristic Evaluation
Penelitian ini menganalisis User Experience pada website pendaftaran santri Pondok Pesantren Salafiyyah Al-Hidayah Kudus menggunakan metode Heuristic Evaluation. Evaluasi ini penting dilakukan untuk memastikan website yang dikembangkan dapat memenuhi kebutuhan pengguna secara optimal dalam proses pendaftaran santri baru yang sebelumnya dilakukan secara manual. Penelitian menggunakan pendekatan kuantitatif dengan menyebarkan kuesioner kepada 20 responden yang pernah menggunakan website tersebut. Kuesioner dirancang berdasarkan 10 prinsip Heuristic Evaluation yang dikembangkan oleh Jakob Nielsen. Hasil analisis menunjukkan bahwa seluruh aspek yang dievaluasi berada pada tingkat Severity Rating 1 (Cosmetic Problem), yang mengindikasikan adanya masalah-masalah kecil yang tidak terlalu mengganggu kenyamanan pengguna. Aspek Aesthetic and Minimalist Design (1.275) dan Consistency and Standards (1.225) memerlukan perhatian lebih dalam perbaikan, sementara aspek Visibility of System Status (0.95) menunjukkan performa terbaik. Hasil evaluasi ini dapat menjadi dasar untuk pengembangan dan perbaikan website guna meningkatkan kualitas pengalaman pengguna dalam proses pendaftaran santri.
Sistem Informasi Distribusi LPG 3 Kg Pada PT Explorindo Solusi Gasindo Kudus Berbasis Website
The 3 kg LPG distribution system plays an important role in ensuring the fuel supply is well-targeted. 3 kg Liquefied Petroleum Gas (LPG) is an important subsidized fuel for households and small businesses in Indonesia. PT Explorindo Solusi Gasindo Kudus faces obstacles in the distribution and management of new base registration manually, such as long lines, data errors, and payment complexity. This research develops a web-based information system to improve administrative efficiency, simplify registration, and increase service transparency. This research aims to develop a web-based LPG 3 KG Distribution Information System for PT Explorindo Solusi Gasindo Kudus. This system is designed to facilitate distribution data management, including base registration, cross-check for base acceptance, and real-time base data reporting. This system is expected to support modern and effective management of LPG distribution. The implementation results show an increase in operational efficiency, data transparency, and ease of access for related parties, supporting the optimization of LPG distribution in the Kudus area.
Pengembangan Sistem Monitoring dan Manajemen ATK Berbasis Website dengan Fitur RealTime Reporting di Pengadilan Negeri Kudus
Pengelolaan alat tulis kantor (ATK) yang optimal menjadi elemen penting dalam mendukung kelancaran administrasi di instansi pemerintahan, termasuk di Pengadilan Negeri Kudus. Namun, masih terdapat tantangan dalam melakukan pemantauan terhadap ketersediaan stok, permintaan, serta distribusi ATK secara real-time. Penelitian ini bertujuan untuk merancang dan membangun sistem berbasis web yang dapat memantau serta mengelola ATK guna meningkatkan efisiensi pengelolaannya. Metode penelitian melibatkan analisis kebutuhan, desain sistem menggunakan framework Laravel, serta implementasi dan pengujian fitur utama, seperti manajemen stok, pemrosesan permintaan, dan pelaporan otomatis. Hasil penelitian menunjukkan bahwa sistem ini memudahkan bendahara dalam memantau ketersediaan ATK sekaligus mengelola permintaan dari pengguna. Selain itu, sistem menyediakan laporan yang dapat diakses secara real-time untuk mendukung proses pengambilan keputusan yang lebih baik. Dengan demikian, sistem ini diharapkan mampu meningkatkan efisiensi operasional serta transparansi dalam pengelolaan ATK.
Komunikasi Interpersonal Coach dengan Atlet Pebasket Klub CLS Surabaya
Perkembangan kemampuan serta keterampilan atlet memerlukan komunikasi serta hubungan antara coach dengan atlet harus berjalan dengan baik. Hubungan yang dibangun tersebut tentu saja memerlukan adanya proses komunikasi. Komunikasi interpersonal merupakan komunikasi yang tepat untuk digunakan dalam hubungan tersebut. Komunikasi interpersonal merupakan proses komunikasi yang terjadi secara langsung. Dengan adanya permasalahan tersebut peneliti tertarik untuk membahas mengenai bagaimana proses komunikasi interpersonal antara coach dan atlet di klub CLS Surabaya. Komunikasi interpersonal antara coach dengan altet pebasket klub CLS Surabaya dilihat melalui cir-ciri serta proses komunikasi interpersonal yang terjalin. Peneliti menggunakan pendekatan kuasi-kualitatif dengan memerlukan teori yang mendasarinya, dan dari pengumplan data yang didapatkan melalui wawancara dan dokumnetasi. Hasil penelitian ini didapatkan bahwa komunikasi interpersonal yang terjalin antara coach dan atlet di CLS Surabaya menunjukan beberapa ciri komunikasi interpersonal, yaitu selektif, sistematis, unik, processual, transaksional, individual, pengetahuan personal, serta menciptakan makna. Serta proses atau tahapan dalam komunikasi interpersonal yang dilalui oleh coach dengan atlet. Namun, ditemukan pula dalam beberapa kasus terjadi kemerosotan komunikasi yang dapat diperbaiki melalui pendekatan komunikasi yang lebih efektif. ​ Kata Kunci—Atlet, Coach, Komunikasi Interpersonal
Analisis Perbandingan Test Case Prioritization Menggunakan Algoritma Greedy dan Algoritma Hill Climbing
Software Testing merupakan salah satu langkah penting dalam memastikan suatu software tetap unggul serta dapat berjalan dan digunakan oleh masyarakat luas, software testing dapat dilakukan menggunakan Regression Testing untuk memastikan software tidak mengalami kerusakan atau terdapat bug baru setelah perubahan terjadi. Regression Testing digunakan untuk menghemat waktu dan biaya pengujian dengan menerapkan Test Case Prioritization yang berfungsi agar software tester dapat memilih test case yang paling penting untuk dilakukan pengujian berdasarkan penggunaan algoritma Greedy dan algoritma Hill Climbing yang digabungkan dengan parameter lain seperti Severity Rating, dan matriks Average Percentage Fault Detection (APFD). Fokus penelitian ini adalah mencari urutan prioritas test case berdasarkan hasil pengujian Regression Testing pada website demoblaze.com berdasarkan perbandingan algoritma Greedy dan algoritma Hill Climbing yang digabungkan dengan parameter Severity Rating berdasarkan nilai APFD tertinggi. Hasil dari penelitian menunjukkan penggunaan algoritma Hill Climbing lebih efektif dalam menentukan prioritas test case dengan memperoleh nilai APFD sebesar 0.91, sedangkan algoritma Greedy mendapatkan nilai APFD sebesar 0.9.
ELearning Responsif Berbasis Laravel untuk Mendukung Pembelajaran Daring di SMP Negeri 1 Kudus
The advancement of information technology has driven educational institutions to adapt, particularly in implementing responsive and integrated online learning. This study aims to design and develop a Laravel-based e-learning system at SMP Negeri 1 Kudus to support digital teaching and learning processes. The system was designed using the Waterfall software development method, which includes requirement analysis, system design, implementation, testing, and maintenance. This system provides key features such as user management, learning material management, assignments, exams, and grade reports, accessible via both desktop and mobile devices. During development, web technologies such as HTML, CSS, JavaScript, and the MySQL database were utilized. Testing results showed that the application operated according to specifications and positively impacted the effectiveness of online learning, particularly in enhancing interactions between teachers and students. Additionally, the system is responsive and supports cross-device accessibility, facilitating students and teachers in various situations. This research is expected to offer an innovative solution to overcome the limitations of conventional learning, support digital transformation in education, and provide a more interactive and adaptive learning experience in line with technological advancements.
Pengukuran Hasil Belajar Mata Kuliah Agama Islam Berbasis Multiple Intelligence di Universitas Raharja Tangerang
Islamic Religious Education held at Higher Education in Indonesia generally has the same problem, namely the lack of methodology in learning so that it is less interesting. For this reason, innovation is needed in Islamic Religious Education. One solution is to use multiple intelligences-based learning. The formulation of the problem in this study is: 1. Is there a direct or indirect influence between kinesthetic intelligence, visual-spatial intelligence and language intelligence mediated by mathematical intelligence on the results of learning Islamic Religious Education at Raharja University in Tangerang? 2. Is there a direct or indirect influence between interpersonal intelligence, intrapersonal intelligence and existential intelligence mediated by naturalist intelligence on the results of learning Islamic Religious Education at Raharja University in Tangerang? This study is a quantitative study using the Smart-PLS Version 4.0 application for data analysis. The results of the study are: 1. Based on the results of the analysis, the R Square value of 0.651 was obtained for language intelligence, indicating that 65.1% of the variation in this variable can be explained by kinesthetic intelligence and visual-spatial intelligence in the model, with 34.9% influenced by external factors. This can be explained that the results of learning Islamic religion at Raharja University are influenced by language intelligence supported by kinesthetic intelligence and visual-spatial intelligence which are significant even though there are external factors on learning outcomes.2. Likewise, the R Square value of 0.646 for mathematical intelligence indicates that 64.6% of the variation in this variable can be explained by kinesthetic intelligence and visual-spatial intelligence in the model, with 35.5% influenced by external factors. From these results, it can also be said that the results of studying Islamic religion at Raharja University students have a significant influence on mathematical intelligence mediated by kinesthetic intelligence and visual-spatial intelligence. It can be said that there is a positive correlation between the three intelligences. 3. Based on the results of the analysis, the R Square value of 0.806 for existential intelligence indicates that 80.6% of the variation in this variable can be explained by intrapersonal intelligence and interpersonal intelligence in the model, with 19.4% influenced by external factors. Likewise, the R Square value of 0.697 for naturalist intelligence indicates that 69.7% of the variation in this variable can be explained by intrapersonal intelligence and interpersonal intelligence in the model, with 31.3% influenced by external factors.
Penerapan Website EGovernment Dalam Pendataan Infrastruktur Dan Fasilitas Publik
The development of science and technology in the management system of social and public facilities will assist in improving the performance of the sub-district government. Currently, the Pasar Kemis District office does not yet have a web-based infrastructure and facility management system to overcome the problem of collecting data on social and public facilities that still use a semi-computer system, namely recording infrastructure and facility data using paper, then recapitulation is carried out to make reports on social facilities. And general. This system still has shortcomings such as difficulty in finding data, allowing errors in data collection, data piling up and requiring a long time in the reporting process. To overcome the problems faced, the authors propose a web-based social and public facility management system so that data collection on facilities becomes easier, shortens time, is organized in data storage. The author uses the method of Observation, Interview, and Literature Study in collecting data. All data are summarized and then clearly described in the Unified Modeling Language (UML). Making a prototype system using Adobe XD application and in analyzing the advantages and disadvantages of the system, the researcher uses the SWOT method. This system is made using the PHP programming language with the Codeigniter framework. The system was tested using the Black Box Testing method. The computerized system makes it easier to manage infrastructure and facilities data so as to assist in the data collection process, data retrieval and reporting of social and public facilities.
Copyright (c) 2024 CICES (Cyberpreneurship Innovative and Creative Exact and Social Science)
Implementasi ANOVA Pada Algoritma KNN++ Untuk Klasifikasi Serangan DDoS UDP Flood
Cybersecurity has become a critical issue in the digital era, particularly with the significant rise of Distributed Denial of Service (DDoS) UDP Flood attacks, which increased by 59.77% in 2023. This study implements the K-Nearest Neighbors++ (KNN++) algorithm, enhanced with feature selection using Analysis of Variance (ANOVA) and data balancing through the Synthetic Minority Oversampling Technique (SMOTE), to detect UDP Flood DDoS attacks based on network traffic anomalies. The CICDDoS2019 dataset is processed through comprehensive preprocessing stages, including the removal of 20 irrelevant features, Min-Max normalization, and class distribution balancing. Experimental results show the best performance at K=3, achieving an accuracy of 99.994%, precision of 99.998%, recall of 99.996%, and an F1-score of 99.997%. The application of SMOTE successfully increased the minority class recall by 2.51% compared to the model without SMOTE, with a computation time of 3,846 seconds, which is considered efficient for large-scale datasets. These findings demonstrate the effectiveness of the combined KNN++, ANOVA, and SMOTE approach as a comprehensive solution for anomaly-based intrusion detection systems
Pengembangan Sistem Informasi Pelaporan Kejahatan Berbasis Web untuk Meningkatkan Aksesibilitas dan Responsivitas Kepolisian di Polres Kudus
This study aims to develop and test an online-based criminal reporting information system at Polres Kudus to enhance the efficiency and effectiveness of police services. The background of this research is based on the need for a faster, more accurate, and transparent reporting system compared to the previously used manual methods. The research method applied is Research and Development (R&D) with a Human-Centered Design (HCD) approach and testing using the System Usability Scale (SUS). The results show that the developed system achieved an average SUS score of 80.6, categorized as "Excellent," indicating that the system is feasible and meets user needs. These findings emphasize the importance of implementing a user-friendly interface design and features aligned with user needs to enhance public trust in the police institution.
Implementasi Aplikasi Web untuk Deteksi Manipulasi Gambar Menggunakan ELA, SRM, dan CNN
Kemajuan teknologi digital telah mempermudah praktik manipulasi terhadap konten visual seperti gambar, yang berpotensi menyebarkan informasi palsu atau menyesatkan. Deteksi terhadap manipulasi gambar menjadi sangat krusial, terutama bagi pengguna umum yang tidak memiliki akses ke perangkat forensik digital yang kompleks. Penelitian ini bertujuan untuk merancang dan mengimplementasikan sebuah aplikasi web yang sederhana namun mampu mendeteksi manipulasi gambar secara otomatis. Sistem ini menggabungkan metode Error Level Analysis (ELA), Spatial Rich Model (SRM), dan Convolutional Neural Network (CNN) sebagai inti proses deteksi. Proses pengembangan dilakukan melalui analisis kebutuhan pengguna, desain sistem, implementasi antarmuka berbasis HTML dan Tailwind CSS, serta integrasi model CNN menggunakan framework Flask. Berdasarkan hasil uji coba, sistem mampu melakukan deteksi dalam waktu 2 hingga 5 detik, serta memperoleh respons positif dari 10 pengguna terkait kemudahan penggunaan dan kejelasan informasi yang ditampilkan. Aplikasi ini diharapkan dapat menjadi solusi yang praktis dalam memverifikasi keaslian gambar digital, khususnya bagi pengguna non-teknis
Implementasi Portal Akademik Berbasis Website Untuk Digitalisasi Administrasi Sekolah di SMP 2 Jekulo Kudus Menggunakan Metode Waterfall
The implementation of an Academic Portal based on a website for digitalizing school administration at SMP 2 Jekulo Kudus aims to enhance the efficiency of administrative tasks through a modern digital system. The traditional paper-based approach often led to delays and errors in managing student data, grades, attendance, and other administrative aspects. This research adopts the Waterfall method, a sequential development approach, to build a user-friendly academic portal tailored to the needs of SMP 2 Jekulo. The study outlines the system requirements, design, implementation, and testing phases. The development process includes features such as student registration, grade input, attendance monitoring, and reporting. The results of this implementation are expected to streamline administrative work, reduce errors, and provide real-time access to academic information. The academic portal offers benefits to both administrative staff and students, providing a more organized and efficient system. The study concludes that digitalizing administrative tasks is essential for improving the overall management of educational institutions.
Sistem Presensi Karyawan SISKA Menggunakan RFID dan NodeMCU Pada CV Mulia Abadi
This research aims to develop an Internet of Things-based employee attendance system using RFID and NodeMCU technology in CV Mulia Abadi Jepara. The system is designed to replace the presence of conventional or manual methods. In this study, the attendance reader machine was designed using a NodeMCU ESP8266 microcontroller and an MFRC-522 RFID module for RFID card reading. This system is also equipped with a PHP and MySQL-based website to monitor and recapitulate attendance data automatically. The waterfall method is used in the development of this system which consists of five stages, namely requirement analysis, system design, implementation, testing, and maintenance. System testing is carried out with two types of tests, namely blackbox testing and User Acceptance Testing (UAT). The test results show that the RFID presence system using a 13.56MHz RFID card can function well with an average card reading distance of 4 cm and a user satisfaction rate of 89%. With this implementation, the employee attendance system can increase efficiency in managing attendance recapitulation data that is practical and accurate for the company.
Implementasi Klasifikasi Jenis Kayu Menggunakan Algoritma KNN dan Gray Level Cooccurence Matrix
This study aims to obtain classification accuracy results derived from testing various K parameters. The research method uses the K-Nearest Neighbor algorithm as the determinant of classification results, supported by the Gray Level Co-occurrence Matrix (GLCM) for feature extraction. Through GLCM feature extraction, grayscale values have been obtained and used as data to determine the final nearest neighbor. The testing is limited to using only odd-numbered K parameters, totaling eight K parameters. This study employs K parameters: K=1, K=3, K=5, K=7, K=9, K=11, K=13, and K=15, using a dataset of 150 wood images. The wood images are divided into three different wood types that have been collected. The dataset is divided into 120 training data and 30 testing data. The testing results show that the system achieves the lowest accuracy of 76.67% when using parameter K=13, while the highest accuracy of 90.00% is achieved when using parameter K=1. The average accuracy across all tests is 83.75%
Implementasi Metode Waterfall dalam Rancang Bangun Website ELearning untuk Pembelajaran di SMP 2 Jekulo Kudus
Digital development in education is driven by advances in information technology, including at SMP 2 Jekulo Kudus. The purpose of this research is to create and build an e-learning website that uses the Waterfall method effectively to support online learning. Requirement analysis is the first step in the development process, which determines functional requirements such as user management, learning material management, online exam system, discussion forum, and data security. In the design stage, the system is designed to be scalable, accessible, and easy to use. Implementation is done using contemporary web technology and thoroughly tested to ensure that all features run according to specifications. The results show that the e-learning platform can help teachers and students learn better by providing an interactive platform. Systems such as exams and online discussion forums increase student participation in learning, while structured material management makes it easier for teachers to deliver material. The website also provides solutions to conventional learning constraints, supports flexibility of access, and strengthens digital transformation efforts in the school environment.
Komparasi Kernel SVM Pada Klasifikasi Citra Tumor Otak Menggunakan Ekstraksi Fitur GLCM
The human brain contains more than 100 billion cells that function to transmit information. Brain tumors occur due to the abnormal growth of cells within or around the brain. Early detection is crucial to prevent tumors from progressing to more severe stages. Manual processes such as biopsies are time-consuming and prone to errors. Therefore, computer technology, such as machine learning, offers an effective solution to support brain tumor diagnosis. This study applies brain tumor image classification using the GLCM feature extraction method and the SVM algorithm as a classifier with four different kernels: linear, polynomial, RBF, and sigmoid with default parameter. The dataset used consists of 2,800 images divided into two classes: tumor and no-tumor. Testing results indicate that the linear kernel achieved an accuracy of 97%, while the polynomial kernel also reached 97%. The RBF kernel achieved 75% accuracy, while the sigmoid kernel produced the lowest accuracy at 48%. These results demonstrate that the linear and polynomial kernels are better at capturing patterns compared to other kernels for brain tumor image classification. With a high confusion matrix score, the linear kernel is recommended for similar image classification tasks.
Implementasi Framework Laravel dalam Optimalisasi ECommerce Penjualan Produk pada Pabrik Tahu RZP Kudus
Advances in digital technology encourage MSMEs to transform by adopting technology-based systems, including in the sales process. RZP's Tofu Factory faced challenges in managing sales manually, which led to problems such as unintegrated data, slow transactions, and difficulties in analyzing data in real-time. This research aims to design and develop a website-based e-commerce system using the Laravel framework to improve the sales performance of RZP Tofu Factory products. In this study, the approach used is the waterfall method which consists of the stages of needs analysis, design, implementation, testing, and maintenance. Testing is carried out using the blackbox testing method to ensure that every function in the system can run according to the purpose. The findings of the study show that the e-commerce system developed is able to integrate the entire sales process, facilitate data recording, speed up transactions, and generate real-time sales reports. In addition, this system can also expand market reach by utilizing digital platforms. The implementation of the Laravel framework has proven to be effective in providing optimal performance and flexibility for system development.
Implementasi Teknologi AJAX dalam Sistem Pemesanan Menu Berbasis Web Responsif Studi Kasus: Sego Sambel Ndeso Kudus
Sego Sambel Ndeso adalah salah satu rumah makan yang terletak di Jl. KH Moh. Arwani No.8 Singocandi, Kecamatan Kota, Kabupaten Kudus. Rumah makan ini menghadirkan konsep kuliner tradisional dengan harga yang terjangkau. Sego Sambel Ndeso beradaptasi dengan perkembangan teknologi melalui sistem pemesanan berbasis web responsif yang didukung teknologi AJAX. Sistem ini memudahkan pelanggan memesan menu langsung melalui perangkat mereka tanpa antri atau mengisi nota manual. Teknologi AJAX memungkinkan pengelolaan pesanan secara real-time dengan pembaruan otomatis dan notifikasi. Sistem ini dikembangkan menggunakan metode pembayaran Payment Gateway Midtrans, basis data MySQL dan framework Laravel dengan web responsif, sehingga dapat diakses melalui berbagai perangkat, termasuk ponsel, tablet, dan komputer. Pengembangan sistem mengikuti model waterfall, meliputi analisis kebutuhan, desain, pengkodean, pengujian, dan pemeliharaan. Hasil penelitian menunjukkan bahwa sistem pemesanan ini berhasil meningkatkan kualitas layanan, efisiensi operasional, mengurangi kesalahan pemesanan dan memberikan kemudahan bagi pelanggan maupun pegawai dalam mengelola pemesanan serta mendukung kebutuhan modernisasi layanan rumah makan. Dengan adanya sistem ini, Sego Sambel Ndeso dapat meningkatkan daya saing dan memberikan nilai tambah bagi pelanggan.
Pengembangan Sistem Informasi Pengelolaan Distribusi Bantuan Bencana Berbasis Web Pada Koramil 09 Kaliwungu Kudus Untuk Peningkatan Efektivitas Respon Bencana
Disaster is an event that causes damage and suffering, whether caused by natural or human factors. In disaster management, Koramil 09/Kaliwungu has a very important role, especially in distributing aid to affected communities. However, Koramil 09/Kaliwungu faces several problems in managing aid distribution, such as the use of Microsoft Excel to record aid recipient data that is inefficient and prone to errors. This results in data that is not well integrated, leading to the risk of providing aid that is not on target or multiple recipients. In addition, the problem of inefficient logistics and distribution coordination, as well as the lack of transparency in monitoring aid, worsens the situation. The lack of a support system also has an impact on the quality of service and slow response time in distributing aid. As a solution, the author proposes the development of a web-based aid distribution management information system, which can integrate data accurately, improve logistics efficiency, and provide transparency and accountability in aid distribution. This system is expected to facilitate distribution management, monitor aid in real-time, and support personnel in making faster and more targeted decisions
Implementasi Ekstraksi Fitur dalam Deteksi Pneumonia
Pneumonia adalah infeksi paru-paru yang menjadi salah satu penyebab utama kematian di seluruh dunia. Deteksi dini yang cepat dan akurat sangat penting dalam penanganan penyakit ini. Penelitian ini bertujuan mengembangkan sistem klasifikasi pneumonia berbasis citra X-ray dengan menggabungkan ekstraksi fitur Local Binary Pattern (LBP) dan Gray Level Co-occurrence Matrix (GLCM), serta menggunakan algoritma XGBoost untuk proses klasifikasi. Metode yang digunakan mencakup pemrosesan citra, yaitu konversi citra ke grayscale, median filtering, dan adaptive histogram equalization. Fitur tekstur diekstraksi menggunakan LBP dan GLCM untuk memperoleh informasi yang lebih mendalam. Selanjutnya, model XGBoost dilatih dengan mengoptimalkan hyperparameter melalui teknik random search. Hasil eksperimen menunjukkan bahwa model yang dikembangkan memperoleh akurasi 97,27%, presisi 99,28%, recall 96,69%, dan F1-score 98,11%. Penelitian ini membuktikan bahwa kombinasi LBP, GLCM, dan XGBoost dapat menjadi alternatif yang efisien dalam deteksi pneumonia, dengan keunggulan akurasi tinggi dan efisiensi komputasi dibandingkan dengan teknik deep learning yang memerlukan sumber daya lebih besar.