Abstract:Abstract: In the era of sensitive health data and frequent cyberattacks, securing electronic medical records (EMR) has become a critical challenge. This study proposes a hybrid encryption framework combining Affine and AES…
ES algorithms with an AI-based key management module to enhance EMR security while maintaining efficiency. A dataset of 1,000 simulated records was evaluated using five cryptographic configurations: Affine-only, AES-only, RSA-only, Affine–AES, and Affine–AES with AI. Performance was measured through encryption/decryption latency and ciphertext size, while security was assessed under brute-force, SQL injection, and phishing simulations. The AI decision tree for key generation was evaluated using accuracy, precision, recall, F1-score, and entropy metrics. Results show that the AI-enhanced hybrid method eliminates brute-force success, introduces only minor latency overhead, and generates high-entropy keys with reliability above 98%. These findings indicate that integrating AI-based dynamic key regeneration into hybrid encryption can improve EMR security while remaining practical for clinical and cloud-based healthcare systems. Future work should involve real clinical datasets and explore post-quantum cryptographic extensions.
Keywords: AI key management; attack resistance; encryption performance; electronic medical records; hybrid encryption
Abstrak: Di era meningkatnya sensitivitas data kesehatan dan maraknya serangan siber, perlindungan Rekam Medis Elektronik (RME) menjadi tantangan penting. Penelitian ini mengusulkan kerangka enkripsi hibrida yang menggabungkan algoritma Affine dan AES dengan modul manajemen kunci berbasis AI untuk meningkatkan keamanan RME tanpa mengorbankan efisiensi. Dataset simulasi berisi 1.000 entri diuji menggunakan lima konfigurasi kriptografi: Affine-only, AES-only, RSA-only, Affine–AES, serta Affine–AES dengan AI. Performa diukur melalui latensi enkripsi/dekripsi dan ukuran ciphertext, sedangkan keamanan dievaluasi melalui simulasi serangan brute force, SQL injection, dan phishing. Model decision tree untuk manajemen kunci dinilai menggunakan metrik akurasi, presisi, recall, F1-score, dan entropi. Hasil menunjukkan bahwa metode hibrida dengan AI menghilangkan keberhasilan brute force, menambah overhead latensi yang minimal, serta menghasilkan kunci berentropi tinggi dengan reliabilitas di atas 98%. Temuan ini menunjukkan bahwa regenerasi kunci dinamis berbasis AI dalam skema enkripsi hibrida dapat meningkatkan keamanan RME sekaligus tetap praktis untuk sistem klinis dan layanan kesehatan berbasis cloud. Penelitian selanjutnya disarankan menggunakan dataset klinis nyata dan mengeksplorasi kriptografi pascakuantum.
Kata kunci: enkripsi hibrida; ketahanan serangan; kinerja enkripsi; manajemen kunci berbasis AI; rekam medis elektronik
Abstract:Abstract: In the era of the Internet of Things (IoT), cyber threats are increasingly complex and dynamic, thus demanding an adaptive and intelligent network security system. This study proposes a Convolutional Neural Network…
work (CNN)-based Intrusion Detection System (IDS) implemented through a Federated Learning (FL) approach in a Non-Independent and Identically Distributed (Non-IID) data environment. This approach allows the model to be trained in a distributed manner across multiple IoT devices without having to collect sensitive data to a central server, thereby maintaining data privacy while increasing the efficiency of the training process. The experiment used the CIC IoT 2023 dataset, which represents various modern IoT network traffic patterns. The results show that the proposed CNN–FL model achieves an overall accuracy of 0.99, with excellent performance in detecting various types of network traffic. The model obtains a perfect recall value (1.00) for normal traffic (Benign), as well as a very high F1-score for DDoS (0.99) and DoS (0.99) attacks. Stable and consistent performance across all five federation rounds demonstrates that this approach is a reliable, efficient, and accurate solution for detecting threats in distributed and privacy-preserving IoT networks.
Keywords: cnn; federated_learning; ids; non-iid; ciciot2023
Abstrak: Dalam era Internet of Things (IoT), ancaman siber semakin kompleks dan dinamis, sehingga menuntut sistem keamanan jaringan yang adaptif dan cerdas. Penelitian ini mengusulkan Intrusion Detection System (IDS) berbasis Convolutional Neural Network (CNN) yang diterapkan melalui pendekatan Federated Learning (FL) pada lingkungan data yang bersifat Non-Independent and Identically Distributed (Non-IID). Pendekatan ini memungkinkan model dilatih secara terdistribusi di berbagai perangkat IoT tanpa harus mengumpulkan data sensitif ke server pusat, sehingga mampu menjaga privasi data sekaligus meningkatkan efisiensi proses pelatihan. Eksperimen menggunakan dataset CIC IoT 2023, yang merepresentasikan berbagai pola lalu lintas jaringan IoT modern. Hasil penelitian menunjukkan bahwa model CNN–FL yang diusulkan mencapai akurasi keseluruhan sebesar 0.99, dengan performa yang sangat baik dalam mendeteksi berbagai jenis lalu lintas jaringan. Model memperoleh nilai recall sempurna (1.00) untuk lalu lintas normal (Benign), serta nilai F1-score yang sangat tinggi untuk serangan DDoS (0.99) dan DoS (0.99). Kinerja yang stabil dan konsisten di seluruh lima putaran federasi membuktikan bahwa pendekatan ini merupakan solusi yang andal, efisien, dan akurat untuk mendeteksi ancaman pada jaringan IoT yang bersifat terdistribusi dan menjaga privasi (privacy-preserving).
Kata kunci: cnn; federated_learning; ids; non-iid; ciciot2023
Abstract:Abstract: The global transition towards sustainable food systems faces significant challenges in vegetarian food supply chains, including transparency issues, distribution inefficiencies, and quality verification problems.…
s. This research proposes VegeChain development, a decentralized marketplace ecosystem based on smart contracts designed to transform vegetarian food supply chains and accelerate Meatless, Balanced, Green (MBG) program adoption. Using mixed-method methodology integrating blockchain system design, stakeholder analysis, and economic simulation, this research develops a comprehensive technology framework combining blockchain transparency, smart contract automation, and sustainable tokenomics with novel mathematical models. The system implements dynamic pricing algorithms based on Automated Market Maker (AMM) mechanisms, multi-objective optimization for supply chain efficiency, and reputation-based consensus protocols. Simulation results demonstrate that VegeChain implementation can improve supply chain efficiency by 35%, reduce food waste by 28%, and increase consumer trust by 42% measured through validated stakeholder satisfaction surveys (n=456) using 5-point Likert scales with statistical significance p<0.001. Technical innovations include Byzantine Fault Tolerant consensus with 99.9% reliability, gas optimization achieving 67% cost reduction, and real-time quality verification algorithms with 98.7% accuracy.
Keywords: smart contracts; supply chain optimization; automated market makers; blockchain technology; sustainable tokenomics
Abstract:Abstract: Ms Glow Kisaran Original Store is one of the beauty companies that sells skincare products that are useful for maintaining healthy facial and body skin. However, the Original Ms. Glow series currently faces challenges…
hallenges such as tight competition and ineffective inventory management in terms of sales figures. This company sells ± 1500 products a month, but also often faces shortages and stockpiles of product, which can reduce customer confidence and cause Ms. Glow Kisaran Original to experience financial losses, among others. Conversely, if the demand for skincare increases but the skincare supply cannot be prepared, this is a loss for the store and customers. The purpose of this study is to improve the accuracy of the forecast, the use of the Single Exponential Smoothing Method is proposed. This method smoothes past values with exponential weights, placing greater emphasis on the latest data. The use of data from the last 12 months as reference data for past recording for forecasting experiments for the next 1 (one) month. The results of the study at Ms Glow Kisaran show the flexibility of the method in adapting to different sales dynamics. Overall, this research helps in predicting skincare sales predictions at the Ms Glow Kisaran Original Kisaran Store using the Single Exponentian Smoothing method, so that it can overcome the challenges in predicting sales figures.
Keywords: ms glow kisaran; skincare sales; ses.
Abstrak: Toko Ms Glow Kisaran Original merupakan salah satu perusahaan di bidang kecantikan yang menjual produk-produk skincare yang bermanfaat untuk menjaga kesehatan kulit wajah dan tubuh. Namun rangkaian Original Ms. Glow saat ini menghadapi tantangan seperti persaingan yang ketat dan pengelolaan inventaris yang kurang efektif dalam hal angka penjualan. Perusahaan ini menjual ±1500 produk dalam sebulan, namun juga sering menghadapi kekurangan dan penumpukan stok produk, yang dapat menurunkan kepercayaan pelanggan dan menyebabkan Ms. Glow Kisaran Original mengalami kerugian finansial. Sebaliknya jika permintaan akan skincare meningkat namun persediaan skincare tidak dapat disiapkan maka ini menjadi kerugian bagi pihak toko dan pelanggan. Tujuan penelitian ini adalah untuk meningkatkan ketepatan perkiraan, penggunaan Metode Single Exponential Smoothing diusulkan. Metode ini menghaluskan nilai masa lalu dengan bobot eksponensial, memberikan penekanan lebih besar pada data terbaru. Penggunaan data 12 bulan terakhir sebagai data acuan pencatatan masa lalu untuk percobaan peramalan untuk 1 (satu) bulan kedepan. Hasil penelitian pada Ms Glow Kisaran menunjukkan fleksibilitas metode dalam menyesuaikan diri dengan dinamika penjualan yang berbeda. Secara keseluruhan, Penelitian ini membantu dalam meramalkan prediksi penjualan skincare di Toko Ms glow Kisaran Original Kisaran menggunakan metode Single Exponentian Smoothing, sehingga dapat mengatasi tantangan dalam memprediksi angka penjualan.
Kata kunci: ms glow kisaran; penjualan skincare; ses.
Abstract:Abstract: Unemployment is a global economic issue that directly impacts human life in both developed and developing countries, especially in Indonesia, which, if ignored, will severely impact society's social dynamics. To…
o overcome this problem, forecasts are made so that later, the government can take policies to control and suppress the unemployment growth rate. This research aims to predict unemployment in Indonesia in 2023 using the Weighted Moving Average method, widely used to determine the trend of a time series, which is part of one of the Time Series methods that gives different weights. The dataset used was obtained from the Central Statistics Agency (BPS) relating to unemployment data from 2000 to 2022 (23 years). To analyze the level of accuracy of the results of this unemployment forecast using the MAD, MSE, and MAPE methods. This research concludes that the Weighted Moving Average method can be applied in predicting unemployment in Indonesia in 2023. The results of this research are a prediction of the number of unemployed in Indonesia, as many as 8,874,942 people at a weight value of 3 (three) where the accuracy of the MAD value is 745786.1833, the MSE value is 948402050986.3 and MAPE is 8.28%.
Keywords: forecasting; unemployment; weigth moving average; indonesia
Abstrak: Pengangguran menjadi isu ekonomi global yang berdampak secara langsung terhadap tingkat kehidupan manusia di negara-negara yang sudah maju maupun yang sedang berkembang khususnya di negara Indonesia, yang jika diabaikan akan berdampak serius terhadap dinamika sosial masyarakat. Untuk mengatasi permasalahan tersebut dibuatlah peramalan agar nantinya pemerinta dapat mengambil kebijakan dalam mengendalikan dan menekan angka pertumbuhan pengangguran tersebut. Penelitian ini bertujuan untuk memprediksi pengangguran di Indonesia pada tahun 2023 menggunakan metode Weighted Moving Average dimana metode ini banyak digunakan untuk menentukan trend dari suatu deret waktu yang merupakan bagian dari salah satu metode Time Series yang memberikan bobot yang berbeda-beda. Adapun dataset yang digunakan diperoleh dari Badan Pusat Satatistik (BPS) berkaitan dengan data pengangguran dari tahun 2000 sampai dengan tahun 2022 (selama 23 tahun). Untuk menganalisa tingkat akurasi dari hasil peramalan pengangguran ini memakai metode MAD, MSE, dan MAPE. Kesimpulan dari penelitian ini yaitu dapat diterapkannya metode Weighted Moving Average dalam memprediksi pengangguran di Indonesia pada tahun 2023. hasil dari penelitian ini berupa prediksi jumlah pengangguran di Indonesia sebanyak 8.874.942 orang pada nilai bobot 3 (tiga) dimana akurasi nilai MAD sebesar 745786,1833, nilai MSE sebesar 948402050986,3 dan MAPE sebesar 8,28 %.
Kata kunci: peramalan; pengangguran; weigth moving average; indonesia
Abstract:Abstract: Pasuruan is a well-known area for producing furniture products in East Java. The furniture commodity industry is widely spread in this city. This industry is also one of the top products. To boost market interest…
st in the furniture industry in Pasuruan City, which has been affected by the COVID-19 pandemic, and a geographic information system has not yet been developed in an effort to develop the furniture industry, research has been carried out on a web-based geographic information system (WebGIS) mapping the furniture industry in Pasuruan City using Leaflets and OpenStreetMap. The developed furniture industry WebGIS application takes advantage of the open source and dynamic advantages of Leflet and OpenStreetMap technologies which have provided very decent results on several GIS web-based application systems. In the testing phase with the Blackbox method, the WebGIS application for the furniture industry in Pasuruan City functionally has run well on desktop devices and also run well on simulated mobile devices. Testing was carried out on several types of browsers like Google Chrome and Microsoft Edge. This WebGIS application has been able to map the furniture industry in Pasuruan City so that the distribution of economic activity actors, especially the furniture industry, can be seen throughout the city and each sub-district. It can provide detailed information on furniture industry players in Pasuruan.
Keywords: framework; leaflet; mapping; openstreetmap; webgis
Abstrak: Pasuruan merupakan salah satu daerah yang terkenal sebagai penghasil produk mebel di Jawa Timur. Industri komoditas mebel tersebar cukup banyak di kota ini. Industri ini juga merupakan salah satu produk unggulan. Guna mendongkrak minat pasar akan industri mebel kota Pasuruan yang terimbas pandemi COVID-19, dan belum dikembangkannya suatu sistem informasi geografis sebagai upaya pengembangan industri mebel maka dilaksanakan penelitian tentang sistem informasi geografis berbasis web (WebGIS) pemetaan industri mebel kota Pasuruan menggunakan Leaflet dan OpenStreetMap. Aplikasi WebGIS industri mebel yang dikembangkan memanfaatkan kelebihan teknologi Leflet dan OpenStreetMap yang bersifat open source dan dinamis yang telah memberikan hasil yang sangat layak pada beberapa sistem aplikasi berbasis WebGIS. Pada tahap pengujian dengan metode Blackbox, aplikasi WebGIS industri mebel kota Pasuruan secara fungsional telah dapat berjalan dengan baik pada perangkat dekstop dan juga berhasil berjalan dengan baik pada simulated mobile device. Pengujian dilakukan pada beberapa macam browser seperti Google Chrome dan Microsoft Edge. Aplikasi WebGIS ini telah dapat memetakan industri mebel kota Pasuruan, sehingga dapat diketahui sebaran pelaku kegiatan ekonomi khususnya industri mebel, baik seluruh kota maupun tiap-tiap kecamatan, serta dapat memberikan detail informasi pelaku industri mebel di kota Pasuruan.
Kata kunci: framework; leaflet; openstreetmap; pemetaan; webgis
Abstract:Abstract: Distribution is an important the business sector, the agricultural sector for distributing seeds to ensure the location of customers selling seeds. Problems that are often encountered seed distribution process…
are the efficiency of the time and distance distribution. Re search will build software entering initial location data and several dynamically added consumer agents. The distance parameter uses latitude-longitude integrated on google maps and detects varying store locations, the generation of chromosomes or the best distribution path with the minimum distance route. The heuristic approach using the Genetic Algorithm imitates the concept of biological evolution of random exchange structure series. This study is to distribute 3 types of seeds with a choice of weights that have been divided into 3 areas located on the map of Indonesia using land routes. The results of the test of the population of the average fitness value tend to remain from the previous value of 1-10 the fitness value and the optimum iteration with 9-12 with an average fitness value of 44.2. Optimal results are obtained when Mr is higher than the Cr values. Thus, the Genetic Algorithm can be used for TSP seed distribution paths. 1:2 fitness evaluation compared with the usual estimates used .
Keywords: Genetic Algorithm; Route Optimization; Seed Distribution; TSP
Abstrak: Distribusi menjadi hal penting berwirausaha, salah satunya pada bidang pertanian untuk pendistribusian benih sampai lokasi tujuan. Permasalahan sering ditemui dalam proses pendistribusian adalah efektifan, efisiensi waktu dan jarak tempuh. Sehingga penelitian akan membangun perangkat lunak dengan memasukan data titik lokasi awal dan beberapa lokasi tujuan agen konsumen ditambahkan secara dinamis. Parameter jarak menggunakan latitude-longitude terintegrasi pada google maps yang mendeteksi keberadaan lokasi, selanjutnya diketahui generasi kromosom atau jalur distribusi terbaik dengan rute minimum. Pendekatan Heuristic menggunakan Algoritma Genetika meniru konsep evolusi biologis deretan struktur pertukaran informasi secara acak. Tujuan dalam penelitian ini dapat mendistribusikan jenis benih dengan pilihan bobot yang telah terbagi dalam wilayah lokasi. Satu wilayah lokasi terdapat beberapa lokasi toko ditambahkan secara dinamis, dengan proses yang sudah ditentukan titik awal keberangkatan. Penelitian ini menekankan pada proses penentuan rute lokasi saja. Hasil pengujian jumlah populasi rata-rata nilai fitness cenderung bersifat tetap dari nilai sebelumnya selisih 1-10 nilai fitness dan iterasi optimum dengan 9-12 dengan rata-rata nilai fitness 44,2. Hasil optimum didapatkan ketika Mutation rate (Mr) lebih tinggi dibanding nilai Crossover rate (Cr). Maka, Algoritma Genetika bisa digunakan untuk TSP jalur distribusi benih pengujian menghasilkan evaluasi fitnes 1:2 untuk Algoritma Genetika dibandingkan dengan estimasi jarak biasa digunakan.
Kata kunci: Algoritma Genetika; Distribusi Benih; Optimalisasi Rute; TSP
Abstract:Abstract: Most farmers are do’nt know what plants are suitable for planting on their land. This is due to the lack of knowledge of farmers regarding the suitability of land with the growing requirements of a crop. The…
The lack of knowledge of farmers and the community about the evaluation of land suitability causes the cultivated plants do not produce optimally, because the conditions required by these plants are not in accordance with the conditions of the land that supports the growth of these plants. Seeing the importance of the process of selecting plants based on land suitability, while determining the selection of plants is still done only by looking at the experience of farmers who have not been tested. So the authors feel the need to make research to determine plants on land based on land suitability and plant growth requirements. The Analytical Hierarchy Process method is very suitable to be used to calculate the priority weight of each criterion because it is objective, which will later be used as a reference ranking by the TOPSIS method. With this research, it can determine the estate crops that will be planted on a land based on the level of land suitability and the requirements for growing plants that are alternative precisely, accurately and dynamically.
Keywords: DSS, AHP, TOPSIS
Abstrak: Kebanyakan Petani masih banyak yang belum mengetahui tanaman apa yang cocok ditanaman di lahannya. Hal ini disebabkan karena kurangnya pengetahuan petani mengenai kesesuaian lahan dengan persyaratan tumbuh suatu tanaman. Lemahnya tingkat pengetahuan petani dan masyarakat tentang evaluasi kesesuaian lahan menyebabkan tanaman yang dibudidayakan tidak berproduksi optimal, karena syarat yang dibutuhkan tanaman tersebut belum sesuai dengan kondisi lahan yang mendukung pertumbuhan tanaman tersebut. Melihat pentingnya proses pemilihan tanaman berdasarkan kesesuain lahan, sedangkan penentuan pemilihan tanaman masih dilakukan hanya berdasarkan dengan melihat pengalaman petani yang belum teruji. Maka penulis merasa perlu membuat penelitian untuk menentukan tanaman pada lahan berdasarkan kesesuain lahan dan persyaratan tumbuh tanaman. Metode Analytical Hierarchy Process sangat cocok digunakan untuk menghitung bobot prioritas dari tiap kriteria karena bersifat obyektif, yang nantinya menjadi acuan perangkingan yang dilakukan dengan metode TOPSIS. Dengan adanya penelitian ini, maka dapat menentukan tanaman perkebunan yang akan ditanam pada suatu lahan berdasarkan tingkat kesesuaian lahan dan persyaratan tumbuh tanaman yang menjadi alternatif secara tepat, akurat dan dinamis.
Kata kunci: SPK, AHP, TOPSIS
Abstract:This study examines how employees perceive and trust Algorithmic Performance Appraisal (APA) in digital-native and technology-driven companies. Adopting Organizational Justice Theory, the Trust in Technology Framework, and…
nd Cognitive Appraisal Theory, the research explores both the direct and indirect effects of APA on employee trust, with Perceived Procedural Fairness (PPF) as a mediating variable. The study uses a quantitative, cross-sectional approach, collecting data from 200 employees in technology-based organizations and analyzing the data with Partial Least Squares Structural Equation Modeling (PLS-SEM). Results show that APA significantly enhances both procedural fairness and employee trust, with PPF playing a partial mediating role in this relationship. These findings underscore the importance of transparency, procedural legitimacy, and avenues for employee voice in cultivating trust in algorithmic systems. The study’s theoretical contribution lies in its integration of multiple perspectives on trust and fairness within algorithmic HR management. The practical implication calls for the careful design and implementation of APA systems that employees perceive as fair and trustworthy. Future research should investigate these relationships in longitudinal and multi-contextual settings to deepen the understanding of trust dynamics in evolving AI-mediated work environments.
Abstract:The rapid advancement of digital technology and artificial intelligence (AI) in the twenty-first century has fundamentally transformed the structure of modern constitutional governance. Digitalization has reshaped the interactions…
teractions between governments and citizens, altered the patterns of political participation, and presented major challenges to constitutional principles. This study aims to analyze the implications of technological development for constitutional law and propose the concept of a digital constitution as an adaptive framework in the AI era. This study employs a normative legal method, using both conceptual and statutory approaches. Legal materials consist of primary, secondary, and tertiary sources, which are analyzed qualitatively and descriptively. The findings reveal that, while digital transformation enhances governmental efficiency and public transparency, it also generates serious risks, including data misuse, digital surveillance, and political disinformation. These dynamics demand a reinterpretation of constitutional norms to protect citizens' digital rights in cyberspace. The concept of a digital constitution is proposed as a normative response that integrates digital rights into constitutional rights and reaffirms the principle of the rule of law within technological governance. To achieve a democratic and just constitutional order, it is crucial to strengthen regulatory frameworks, ensure algorithmic accountability, and foster collaboration among state institutions, civil society, and the private sector. Ultimately, constitutional law must evolve into an adaptive, transparent, and fair system that can address the profound challenges of the digital and AI-driven era.