Abstract:Abstract: This study aims to design and develop a web-based Academic Information System at SIT Taruna Ar Risalah Tanjungpinang to digitalize academic recording processes that were previously conducted manually using paper…
r forms and Microsoft Excel. The system development method used in this study is the Waterfall method, which consists of requirements analysis, system design, implementation, and system testing stages. The system was developed using the CodeIgniter 4 framework with a Model-View-Controller (MVC) architecture, PHP programming language, and MySQL database. Data collection was carried out through observation and interviews, while system design used Unified Modeling Language (UML). System testing was conducted using the Black Box Testing method. The system implements Role-Based Access Control (RBAC) to manage user access rights consisting of Administrators, Principals, Teachers, and Students. The testing results indicate that all main system features function properly, including bulk attendance management, Qur’an memorization recording, Student Discipline Program evaluation, and real-time academic report presentation. The developed system is able to improve school administrative efficiency, minimize the risk of data loss, and facilitate digital monitoring of students’ academic achievements.
Keywords: Academic Information System; Codeigniter 4; Waterfall; RBAC; School.
Abstrak: Penelitian ini bertujuan untuk merancang dan membangun Sistem Informasi Akademik berbasis web pada SIT Taruna Ar Risalah Tanjungpinang guna mendigitalisasi proses pencatatan akademik yang sebelumnya masih dilakukan secara manual menggunakan kertas dan Microsoft Excel. Metode pengembangan sistem yang digunakan adalah metode Waterfall yang terdiri dari tahapan analisis kebutuhan, perancangan sistem, implementasi, dan pengujian sistem. Sistem dikembangkan menggunakan framework CodeIgniter 4 dengan arsitektur Model-View-Controller (MVC), bahasa pemrograman PHP, serta basis data MySQL. Pengumpulan data dilakukan melalui observasi dan wawancara, sedangkan perancangan sistem menggunakan Unified Modeling Language (UML). Pengujian sistem dilakukan menggunakan metode Black Box Testing. Sistem menerapkan Role-Based Access Control (RBAC) untuk membatasi hak akses pengguna yang terdiri dari Administrator, Kepala Sekolah, Guru, dan Siswa. Hasil pengujian menunjukkan bahwa seluruh fitur utama sistem berjalan dengan baik, meliputi pengelolaan presensi massal, pencatatan hafalan Al-Qur’an, evaluasi Program Siswa Tangguh, serta penyajian laporan akademik secara real-time. Sistem yang dibangun mampu meningkatkan efisiensi administrasi sekolah, meminimalisir risiko kehilangan data, dan mempermudah proses monitoring capaian akademik siswa secara digital.
Kata Kunci: Sistem Informasi Akademik; Codeigniter 4; Waterfall; RBAC; Sekolah.
Abstract:Text based social engineering attacks are a growing cyber threat that is difficult to detect by conventional intrusion detection systems, especially in previously unobserved or zero-day variants. This study proposes a Natural…
tural Language Processing Open-Set Intrusion Detection System (NLP-OSIDS) framework that integrates Term Frequency-Inverse Document Frequency (TF-IDF) trigram (1.3-gram) feature representation with an Open-Set Multilayer Perceptron architecture based on energy based scoring to detect zero-day social engineering attacks without requiring training examples from that class. Experiments were conducted on the public dataset phishing_email.csv with 82,486 combined samples from Enron, SpamAssassin, Nazario, Ling, CEAS, and Nigerian Fraud datasets with strict zero-day partitioning following open-set recognition evaluation standards. The results show that NLP-OSIDS achieved an AUROC of 0.7808, surpassing all closed-set baselines (AUROC = 0.500) with the lowest False Positive Rate of 0.0088, while the Zero-Day Detection Rate (ZD-DR) of 0.077 indicates the need for adaptive threshold optimization as a direction for further research.
Abstract:Abstract: The growth of semi-structured and unstructured data on web pages has increased the need for efficient, autonomous, and structure-aware methods for structured data extraction. This study proposes a mobile agent…
approach based on the BDI (Belief-Desire-Intention) architecture as an alternative to conventional wrappers for structured web data extraction. The system was developed using the JADE (Java Agent Development Framework) platform and the Prometheus methodology, involving two main agents: AgenDownload, responsible for migration and retrieval of web page content, and AgenEkstraksi, which implements the Simple Tree Matching and MDR (Mining Data Regions) algorithms to identify and extract flat data records. Experiments were conducted on 40 web pages from Indonesian and English online bookstores. The results show an average recall of 73%, indicating the system capability to locate most target records, while the average precision of 15.59% indicates that further refinement is needed in post-extraction filtering. The mobile agent approach remains relevant in distributed network scenarios with bandwidth constraints, near-source processing requirements, and autonomous operation needs. This study contributes a multi-role agent system architecture that can be adapted for automated web data extraction.
Keywords: web data extraction; mobile agent; BDI architecture; Simple Tree Matching; JADE
Abstrak: Pertumbuhan data semi-terstruktur dan tidak terstruktur pada halaman web meningkatkan kebutuhan terhadap metode ekstraksi data terstruktur yang efisien, otonom, dan dapat beradaptasi terhadap variasi struktur HTML. Penelitian ini mengajukan pendekatan berbasis mobile agent dengan arsitektur BDI (Belief-Desire-Intention) sebagai alternatif terhadap wrapper konvensional dalam proses ekstraksi data terstruktur pada halaman web. Sistem dibangun menggunakan platform JADE (Java Agent Development Framework) dan metodologi Prometheus, melibatkan dua agen utama: AgenDownload yang bertugas melakukan migrasi dan pengambilan konten halaman web, serta AgenEkstraksi yang mengimplementasikan algoritma Simple Tree Matching dan MDR (Mining Data Regions) untuk mengidentifikasi serta mengekstrak flat data records. Pengujian dilakukan terhadap 40 halaman web toko buku daring berbahasa Indonesia dan Inggris. Hasil menunjukkan rata-rata recall sebesar 73%, yang mengindikasikan kemampuan sistem dalam menemukan sebagian besar target data, sedangkan rata-rata precision sebesar 15,59% menunjukkan perlunya penyempurnaan mekanisme pemfilteran hasil ekstraksi. Pendekatan mobile agent tetap relevan pada skenario jaringan terdistribusi dengan keterbatasan bandwidth, kebutuhan pemrosesan dekat sumber data, dan operasi otonom. Kontribusi penelitian ini adalah rancangan arsitektur sistem agen multi peran yang dapat diadaptasi untuk kebutuhan ekstraksi data web secara otomatis.
Kata Kunci: ekstraksi data web; mobile agent; arsitektur BDI; Simple Tree Matching; JADE
Abstract:Pneumonia is one of the leading causes of death in children, so early detection is very important to increase the chances of recovery. This study aims to develop a hybrid model based on artificial intelligence to detect…
pneumonia in children by combining X-ray images and clinical data. The system is built in two main stages: image feature extraction using Convolutional Neural Network (CNN) based on MobileNetV2 architecture, and combined classification of visual and clinical features using Support Vector Machine (SVM). The CNN model successfully classified children's lung conditions with an accuracy of 89.92% and a recall of 0.95 in the pneumonia class, indicating excellent detection sensitivity. The SVM model built using clinical data also showed competitive performance with an accuracy of 90%, confirming the important contribution of clinical data in supporting diagnosis. The hybrid model combining visual feature vectors (128 dimensions) and 12 clinical features showed very high performance with an accuracy of 98% on the test data, and precision and recall above 0.98 in both classes. Principal Component Analysis (PCA) visualization shows a clearly separated class distribution, supporting the reliability of the multimodal representation used. The results of this study indicate that the integration of visual and clinical data significantly improves the accuracy and sensitivity of the model, making it a potential candidate as an AI-based pneumonia diagnostic tool. This model is very relevant to be applied in areas with limited medical personnel, to support faster and more accurate early detection. Further research is recommended to test the model's performance on more heterogeneous external data to ensure generalization capabilities.
Abstract:Abstract: This research aims to design and implement a web-based Optical Line Terminal (OLT) network monitoring system to detect congestion in real-time on Gigabit Passive Optical Network (GPON) architecture. The main problem…
oblem in GPON networks is the increase in customer traffic which causes bandwidth bottlenecks and decreases Quality of Service (QoS). The research methodology includes analysis of OLT performance parameters (throughput, utilization, packet loss, latency), design of a system architecture based on SNMP and REST API, development of a monitoring dashboard using a web framework, and testing in an operational network environment. The developed system is able to display PON port status, bandwidth utilization level, and automatic notification when the congestion threshold is exceeded. The test results show that the system can detect an increase in utilization above 80% with a response time of less than 5 seconds. The implementation of this system increases the effectiveness of network monitoring and speeds up the troubleshooting process by administrators.
Keywords: Network Monitoring; OLT; GPON; Congestion; Real-Time.
Abstrak: Penelitian ini bertujuan merancang dan mengimplementasikan sistem monitoring jaringan Optical Line Terminal (OLT) berbasis web untuk mendeteksi congestion secara real-time pada arsitektur Gigabit Passive Optical Network (GPON). Permasalahan utama pada jaringan GPON adalah meningkatnya trafik pelanggan yang menyebabkan bottleneck bandwidth dan penurunan Quality of Service (QoS). Metodologi penelitian meliputi analisis parameter performa OLT (throughput, utilization, packet loss, latency), perancangan arsitektur sistem berbasis SNMP dan REST API, pengembangan dashboard monitoring menggunakan framework web, serta pengujian pada lingkungan jaringan operasional. Sistem yang dikembangkan mampu menampilkan status port PON, tingkat utilisasi bandwidth, dan notifikasi otomatis ketika threshold congestion terlampaui. Hasil pengujian menunjukkan bahwa sistem dapat mendeteksi kenaikan utilisasi di atas 80% dengan waktu respons kurang dari 5 detik. Implementasi sistem ini meningkatkan efektivitas monitoring jaringan serta mempercepat proses troubleshooting oleh administrator.
Kata Kunci: Monitoring Jaringan; OLT; GPON; Congestion; Real-Time.
Abstract:Abstract: Resource scarcity in social assistance programs necessitates systematic prioritization mechanisms that integrate multidimensional vulnerability indicators while maintaining transparency and reproducibility. This…
s research proposes a computational framework leveraging Fuzzy Sugeno inference systems to optimize allocation decisions for vulnerable populations, specifically persons with disabilities. The approach transforms qualitative expert assessments and socioeconomic indicators into quantifiable priority scores through four-stage fuzzy processing: fuzzification of crisp input values into membership degrees, activation of 27 IF-THEN inference rules, computation of weighted ?-predicates via minimum operator, and defuzzification via Sugeno's weighted average method producing normalized output [0,1]. Implementation utilized PHP-MySQL architecture with JavaScript-based visualizations to develop a web-accessible prototype capable of processing multifactorial household profiles. Validation across 10 representative cases demonstrates superior consistency relative to conventional manual assessment approaches. The system eliminates subjective bias through deterministic rule-based inference while maintaining semantic alignment with domain expertise. Results indicate the framework generates transparent, auditable, and scalable solutions for social policy implementation, addressing persistent challenges in allocating limited public resources to maximally deserving beneficiaries. The methodology contributes novel applications of computational intelligence to public administration and extends Sugeno fuzzy logic paradigms beyond traditional forecasting domains toward decision support systems.
Keyword: fuzzy sugeno; resource allocation; vulnerability assessment; disability prioritization; social policy
Abstrak: Kelangkaan sumber daya dalam program bantuan sosial menuntut mekanisme prioritisasi sistematis yang mengintegrasikan indikator kerentanan multidimensi sambil mempertahankan transparansi dan reproducibilitas. Penelitian ini mengusulkan kerangka komputasi yang memanfaatkan sistem inferensi Fuzzy Sugeno untuk mengoptimalkan keputusan alokasi bagi populasi rentan, khususnya penyandang disabilitas. Pendekatan mentransformasi penilaian ahli kualitatif dan indikator sosial-ekonomi menjadi skor prioritas terkuantifikasi melalui pemrosesan fuzzy empat tahap: fuzzifikasi nilai input crisp menjadi derajat keanggotaan, aktivasi 27 aturan inferensi IF-THEN, komputasi ?-predikat tertimbang via operasi minimum, dan defuzzifikasi via metode rata-rata tertimbang Sugeno menghasilkan output ternormalisasi [0,1]. Implementasi memanfaatkan arsitektur PHP-MySQL dengan visualisasi berbasis JavaScript untuk mengembangkan prototipe web-accessible mampu memproses profil rumah tangga multifaktorial. Validasi lintas 10 kasus representatif menunjukkan konsistensi superior relatif terhadap pendekatan penilaian manual konvensional. Sistem mengeliminasi bias subjektif melalui inferensi berbasis aturan deterministik sambil mempertahankan keselarasan semantik dengan expertise domain. Hasil mengindikasikan kerangka kerja menghasilkan solusi transparan, dapat diaudit, dan scalable untuk implementasi kebijakan sosial, mengatasi tantangan persisten alokasi sumber daya publik terbatas kepada beneficiary paling layak. Metodologi berkontribusi aplikasi novel soft computing terhadap administrasi publik dan memperluas paradigma logika fuzzy Sugeno melampaui domain forecasting tradisional menuju sistem pendukung keputusan.
Kata kunci: fuzzy sugeno; alokasi sumber daya; penilaian kerentanan; prioritisasi disabilitas; kebijakan sosial
Abstract:Abstract: Forecasting non-oil export commodities is critical for Indonesia's trade strategy, as these commodities contribute 93.8% of total national exports. This study develops a multi-commodity export prediction system…
using Artificial Neural Network (ANN) with backpropagation algorithm for 32 Indonesian non-oil commodities across six strategic sectors. Using monthly export data from February to August 2025 from Indonesia's Central Statistics Agency, we identified optimal neural network architecture 6-5-1 (6 input neurons for 6-month historical data, 5 hidden neurons, 1 output neuron). The model achieved 89.16% training accuracy and 88.43% testing accuracy with minimal 0.73% differential, indicating strong generalization without overfitting. Highest accuracy occurred on stable commodities (Tobacco: 99.94%, Animal/Plant Fats: 99.90%) while volatile commodities showed lower accuracy (Oil Seeds: 42.57%). The developed web-based system enables policymakers and exporters to make strategic decisions for international trade. This research demonstrates ANN backpropagation effectiveness for multi-dimensional commodity forecasting and provides practical decision-support tools for Indonesia's non-oil export sector.
Keyword: artificial neural network; backpropagation; export forecasting; commodity prediction; Indonesia.
Abstrak: Peramalan komoditas ekspor nonmigas sangat penting untuk strategi perdagangan Indonesia karena berkontribusi 93,8% dari total ekspor nasional. Penelitian ini mengembangkan sistem prediksi ekspor multi-komoditas menggunakan Jaringan Syaraf Tiruan (JST) dengan algoritma backpropagation untuk 32 komoditas nonmigas Indonesia di enam sektor strategis. Menggunakan data ekspor bulanan Februari-Agustus 2025 dari Badan Pusat Statistik Indonesia, kami mengidentifikasi arsitektur jaringan optimal 6-5-1 (6 neuron input untuk data 6 bulan, 5 neuron tersembunyi, 1 neuron output). Model mencapai akurasi training 89,16% dan testing 88,43% dengan diferensial minimal 0,73%, menunjukkan generalisasi kuat tanpa overfitting. Akurasi tertinggi pada komoditas stabil (Tembakau: 99,94%, Lemak dan Minyak: 99,90%) sedangkan komoditas volatil menunjukkan akurasi lebih rendah (Biji-bijian Berminyak: 42,57%). Sistem berbasis web memungkinkan pembuat kebijakan dan eksportir membuat keputusan strategis untuk perdagangan internasional. Penelitian ini menunjukkan efektivitas JST backpropagation untuk peramalan komoditas multi-dimensi dan menyediakan alat pengambilan keputusan praktis untuk sektor ekspor nonmigas Indonesia.
Kata kunci: jaringan syaraf tiruan; backpropagation; peramalan ekspor; prediksi komoditas; Indonesia.
Abstract:Abstract: The digital transformation of the e-commerce sector has given rise to the phenomenon of live streaming, which integrates real-time interactivity, social presence, and instant transactions. This study explores the…
he role of information technology capabilities in shaping digital service quality and examines their influence on customer satisfaction and behavioral outcomes within live streaming e-commerce. The research employs a systematic literature review with a thematic synthesis approach, analyzing articles sourced from Google Scholar, Semantic Scholar, and other academic databases. The findings indicate that information technology capabilities, including platform architecture, real-time data analytics, recommendation algorithms, transaction security, and interactive features, play a significant role in shaping dimensions of digital service quality such as reliability, responsiveness, assurance, empathy, and tangibles. These dimensions subsequently affect the quality of live interactions, the sense of social presence, the credibility of streamers, as well as the effectiveness of gamification and scarcity-based promotions. The results suggest that higher levels of service quality foster greater trust and customer engagement, which in turn enhance satisfaction, loyalty, and the intention to repurchase. Furthermore, the study demonstrates that these relationships are moderated by contextual factors such as product type, live streaming format, consumer digital literacy, and the intensity of promotional activities. The overall conclusion emphasizes that information technology capabilities function not only as technical enablers but also as strategic resources for creating superior digital service quality, improving customer satisfaction, and supporting long-term loyalty and business sustainability in the live streaming e-commerce ecosystem.
Keyword: Information Technology, Live Streaming E-commerce, Service Quality, Customer Satisfaction, Loyalty Abstrak: Transformasi digital dalam sektor e-commerce telah memunculkan fenomena live streaming yang memadukan interaktivitas secara real-time, kehadiran sosial, dan transaksi instan. Penelitian ini bertujuan menelaah peran kapabilitas teknologi informasi dalam membentuk kualitas layanan digital serta dampaknya terhadap kepuasan dan perilaku pelanggan pada konteks live streaming e-commerce. Metode yang digunakan adalah systematic literature review dengan pendekatan thematic synthesis terhadap artikel yang diperoleh dari Google Scholar, Semantic Scholar, dan berbagai database publikasi ilmiah lainnya. Hasil kajian menunjukkan bahwa kapabilitas teknologi informasi, meliputi arsitektur platform, analitik data real-time, algoritma rekomendasi, keamanan transaksi, dan fitur interaktif, berperan penting dalam membentuk dimensi kualitas layanan digital, yaitu reliability, responsiveness, assurance, empathy, dan tangibles. Dimensi layanan tersebut selanjutnya memengaruhi kualitas interaksi secara langsung, kehadiran sosial, kredibilitas host atau streamer, serta efektivitas promosi berbasis gamifikasi dan kelangkaan. Rangkaian pengaruh ini menunjukkan bahwa peningkatan kualitas layanan akan mendorong terbentuknya kepercayaan dan keterlibatan pelanggan, yang kemudian berkontribusi pada kepuasan, loyalitas, serta kecenderungan untuk melakukan pembelian ulang. Penelitian ini juga menemukan bahwa hubungan antarvariabel tidak bersifat mutlak karena dipengaruhi oleh faktor moderator seperti jenis produk, format live streaming, tingkat literasi digital konsumen, serta intensitas promosi. Temuan ini menegaskan bahwa kapabilitas teknologi informasi tidak hanya berfungsi sebagai penopang teknis, tetapi juga menjadi strategi kunci dalam menciptakan layanan digital yang unggul, meningkatkan kepuasan, serta memperkuat loyalitas dan keberlanjutan bisnis dalam ekosistem live streaming e-commerce.
Kata Kunci: Teknologi Informasi, Live Streaming E-commerce, Kualitas Layanan, Kepuasan Pelanggan, Loyalitas
Abstract:Abstract: Strategic information system planning is an important process to combine business strategy with information technology needs, especially in the field of health services. The purpose of this research is to use the…
he Enterprise Architecture Planning (EAP) approach to design an integrated strategic information system at Kesrem Lhokseumawe Hospital. EAP includes stages such as planning initialisation, business modelling, analysis of current systems and technologies, design of data architecture, application architecture, and technology architecture, and preparation of a system implementation plan. The analysis results show that business activities at Kesrem Hospital are divided into two main categories: medical and nursing services; and supporting categories, such as financial management, human resources, and infrastructure facilities. The current information system is still manually created and not integrated, which causes data errors and high delays in decision-making. The identification of key data entities, list of candidate applications based on business functions, proposed network topology, and prioritised application implementation roadmap are all part of the resulting architecture design. It is expected that this strategic planning serves as a model for building information systems that are flexible, effective, and capable of assisting data-driven and rapid management decision-making.
Keyword: Strategic Information System Planning; Enterprise Architecture Planning (EAP); Hospital; Data Architecture; Application Portfolio.
Abstrak: Perencanaan sistem informasi strategis adalah proses penting untuk menggabungkan strategi bisnis dengan kebutuhan teknologi informasi, khususnya dalam bidang layanan kesehatan. Tujuan dari penelitian ini adalah untuk menggunakan pendekatan Enterprise Architecture Planning (EAP) untuk membuat rancangan sistem informasi strategis yang terintegrasi di Rumah Sakit Kesrem Lhokseumawe. EAP mencakup tahapan seperti inisialisasi perencanaan, pemodelan bisnis, analisis sistem dan teknologi yang sedang berjalan, perancangan arsitektur data, arsitektur aplikasi, dan arsitektur teknologi, dan penyusunan rencana implementasi sistem. Hasil analisis menunjukkan bahwa aktivitas bisnis di RS Kesrem terbagi menjadi dua kategori utama: pelayanan medis dan keperawatan; dan kategori pendukung, seperti manajemen keuangan, sumber daya manusia, dan sarana prasarana. Sistem informasi saat ini masih dibuat secara manual dan tidak terintegrasi, yang menyebabkan kesalahan data dan keterlambatan pengambilan keputusan yang tinggi. Identifikasi entitas data utama, daftar calon aplikasi berdasarkan fungsi bisnis, usulan topologi jaringan, dan roadmap implementasi aplikasi prioritas adalah semua bagian dari rancangan arsitektur yang dihasilkan. Diharapkan perencanaan strategis ini berfungsi sebagai model untuk membangun sistem informasi yang fleksibel, efektif, dan mampu membantu pengambilan keputusan manajemen yang berbasis data dan cepat.
Kata kunci: Perencanaan Sistem Informasi Strategis; Enterprise Architecture Planning (EAP); Rumah Sakit; Arsitektur Data; Portofolio Aplikasi.
Abstract:Abstract: Global climate change has increased the frequency and intensity of droughts that threaten national food security, particularly in rice agriculture sector. This research develops a system for identifying drought…
stress in rice plants using spectral analysis of multispectral images based on U-Net segmentation. The research methodology includes collecting multispectral images from rice fields, radiometric preprocessing and atmospheric correction, vegetation area segmentation using U-Net architecture, spectral feature extraction through vegetation index calculation (NDVI, NDWI, SAVI), and drought stress level classification. The U-Net architecture is trained to separate rice plant areas from the background with high accuracy, then analyzes the spectral response of plants to water deficiency. Research results show that the system can identify four levels of drought stress (normal, mild, moderate, severe) with an accuracy rate of 87.5%. The output is a spatial map of drought stress distribution that can be used as a basis for decision-making in irrigation management. This system provides significant contributions to precision agriculture and climate change adaptation in supporting sustainable food security.
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Keyword: Drought Stress, Rice Plants, Spectral Analysis, Multispectral Imagery, U-Net Segmentation
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Abstrak: Perubahan iklim global telah meningkatkan frekuensi dan intensitas kekeringan yang mengancam ketahanan pangan nasional, khususnya pada sektor pertanian padi. Penelitian ini mengembangkan sistem identifikasi stres kekeringan pada tanaman padi menggunakan analisis spektral citra multispektral berbasis segmentasi U-Net. Metodologi penelitian meliputi pengumpulan citra multispektral dari ladang padi, preprocessing radiometrik dan koreksi atmosferik, segmentasi area vegetasi menggunakan arsitektur U-Net, ekstraksi fitur spektral melalui perhitungan indeks vegetasi (NDVI, NDWI, SAVI), serta klasifikasi tingkat stres kekeringan. Arsitektur U-Net dilatih untuk memisahkan area tanaman padi dari latar belakang dengan akurasi tinggi, kemudian menganalisis respon spektral tanaman terhadap kekurangan air. Hasil penelitian menunjukkan sistem mampu mengidentifikasi empat tingkat stres kekeringan (normal, ringan, sedang, berat) dengan tingkat akurasi 87,5%. Output berupa peta spasial distribusi stres kekeringan yang dapat digunakan sebagai dasar pengambilan keputusan dalam manajemen irigasi. Sistem ini memberikan kontribusi signifikan terhadap pertanian presisi dan adaptasi terhadap perubahan iklim dalam mendukung ketahanan pangan berkelanjutan.
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Kata kunci: Stres Kekeringan, Tanaman Padi, Analisis Spektral, Citra Multispektral, U-Net Segmentation