301 hasil
Menampilkan 1–20 · 0,14 detik · RSS
JITeCS (Journal of Information Technology and Computer Science)
ISSN 2540-9433 · University of Brawijaya · 301 artikel di indeks
-
Artikel Jurnal Teks lengkap
Multilingual Sentiment Analysis of RCTI+ Reviews Utilising Orange, ChatGPT, and Naïve Bayes
Low user ratings on mobile applications often reflect underlying dissatisfaction that is not immediately apparent through quantitative scores alone. To uncover the sentiment dynamics behind such evaluations, this study analyzes user reviews of the RCTI+ Superapp in both the original Indonesian and…
Juga tersedia di: DOAJ
-
Artikel Jurnal
Prediction of On-Time Graduation of Students Using Random Forest Algorithm (Case Study: Faculty of Computer Science, Universitas Brawijaya)
The timeliness of student graduation is an important indicator of academic quality and institutional performance. Delayed graduation not only affects university evaluation metrics but also postpones students’ entry into the workforce. This study proposes a predictive model to identify students at…
-
Artikel Jurnal
Root Cause Analysis of Government Readiness in Realizing the Concept of E-Government System: A Case Study of Palu City Government
This study aims to analyse the root causes of the readiness issues faced by the Palu City Government in implementing the concept of an E-Government System. The main focus of this research is to assess the government's readiness in realizing the implementation of E-Government System and to identify…
-
Artikel Jurnal
Prediction of Tides in the Gisik Cemandi Coastal Area Using the Support Vector Regression (SVR) Method
This study was conducted to predict tidal fluctuations in the coastal area of Gisik Cemandi Village, Sidoarjo, using the Support Vector Regression (SVR) method. The dataset consisted of time series records of sea level height for the period of March . The prediction process was implemented by…
-
Artikel Jurnal
Integrated NTT-Karatsuba for fast multiplication of NTRU Algorithm
The increasing threat of attacks from quantum computers requires the development of more efficient and secure post-quantum cryptographic algorithms, one of which is NTRU. The main challenge in this algorithm lies in the high complexity of large-dimensional polynomial multiplication operations and…
-
Artikel Jurnal
Prediction of Wastewater Treatment Revenue Based on Volume and Number of Transactions Using the Long Short-Term Memory (LSTM) Method
This study aims to develop a prediction model for the total Revenue value of the operational activities of the Keputih Surabaya Sewage Sludge Treatment Plant (IPLT) using the Long Short-Term Memory (LSTM) method. The data used is daily data on total transactions and total Revenue from January 2022…
-
Artikel Jurnal
The Sentiment Analysis Of Indonesian Startup Application Reviews Using TF-IDF+SVM and FastText: A Comparative Study
The rapid rise of startups in Indonesia makes user reviews on the Google Play Store a valuable data source for understanding user perceptions and satisfaction. These unstructured reviews contain insights supporting product development and business strategies. This study analyzes sentiments in…
-
Artikel Jurnal
Enhancing Brain Tumor MRI Classification Performance Using EfficientNetV2-B3 with an Efficient Channel Attention Module
Early identification of brain tumors using magnetic resonance imaging helps doctors make quick and informed decisions about treatment. Although recent deep learning approaches achieve high accuracy, many rely on complex architectures that increase computational cost and limit interpretability. In…
-
Artikel Jurnal
An Expert System for Early Risk Diagnosis of Breast Cancer Using Fuzzy Mamdani and Case-Based Reasoning
Breast cancer remains one of the leading causes of morbidity and mortality among women worldwide, making early detection essential to improve treatment outcomes. However, early-stage breast cancer symptoms are often subjective and non-specific, which complicates initial risk assessment. This study…
-
Artikel Jurnal
Hyperparameter Optimization of Extreme Gradient Boosting Using Particle Swarm Optimization For Diabetic Nephropathy Prediction
Diabetic Nephropathy (DN) is a critical complication with a mortality rate 20-40 times higher than in non-diabetic nephropathy patients, necessitating precise machine learning models to determine whether a patient has nephropathy. Extreme Gradient Boosting (XGBoost) has emerged as a prominent…
-
Artikel Jurnal
Implementation of YOLOv8 Instance Segmentation for Automatic Counting and Identification of Multispecies Bacterial Colony
This study introduces the implementation of YOLOv8 instance segmentation model, for automating the quantification and identification of multispecies bacterial colonies. In microbiological research, accurate counting and rapid identification of various species within colonies are essential. YOLOv8's…
-
Artikel Jurnal
Comparative Analysis of Random Forest, Support Vector Machine, and K-Nearest Neighbor with Image Feature Extraction for Rice Leaf Disease Detection
Plant diseases and pest infestations have caused a decline in global food production of up to 40%, including in Indonesia, making an efficient and accurate disease detection system essential to support food security. This study proposes a supervised learning approach to detect rice leaf diseases…
-
Artikel Jurnal
Predicting On-Time Graduation Using the C 4.5 Algorithm with Forward Selection Optimization (Case Study: Computer Engineering Study Program, Faculty of Computer Science, Brawijaya University)
On-time student graduation is a key indicator of academic effectiveness and higher education quality. Timely graduation reflects efficient academic management, while delays may negatively impact institutional performance and accreditation. Graduation delays are influenced by various academic and…
-
Artikel Jurnal
Detection of God Class Smells in PHP Systems Using Object-Oriented Metrics
Software maintainability becomes difficult when object-oriented systems contain God Class code smells, where a single class handles excessive responsibilities and controls large portions of system behavior. Most existing God Class detection approaches use metric thresholds developed for statically…
-
Artikel Jurnal
Deep Learning-Based Edge Proctor System: A Resource-Efficient Multi-Modal Exam Monitoring Solution for Indonesian Schools
Academic dishonesty in computer-based exams reaches 67.5% in Indonesia, threatening educational evaluation validity and undermining academic certificate credibility. This research develops the Edge Proctor System, a deep learning-based digital proctoring system integrating three detection…
-
Artikel Jurnal
Development of the "Pulih" User Interface: A Smartwatch-Integrated Digital Counseling Application for Survivors of Post-Traumatic Stress Disorder due to Violence and Sexual Abuse
The high prevalence of mental health disorders resulting from trauma caused by violence and sexual abuse has not been matched by adequate access to recovery services due to psychological barriers in the form of social stigma. This situation motivated the design of the “Pulih” interface, a…
-
Artikel Jurnal
Participant-Driven Design of Community Program Topics for Aging Communities: A Text Clustering Approach to Activity Preferences
The rapid growth of Indonesia’s elderly population highlights the need for community programmes that not only extend lifespan but also improve healthspan. This study aims to design ageing activity topics based on participants’ suggestions using Natural Language Processing (NLP) and unsupervised…
-
Artikel Jurnal
Machine Learning Comparison for Housing Rehabilitation Beneficiary Selection in Surabaya
The Surabaya City Government launched the ‘Dandan Omah’ Social Rehabilitation Program for Uninhabitable Houses (RTLH) in 2022. However, beneficiary selection for the 2022–2024 period was conducted manually, which may have led to subjective and less targeted decisions. This study proposed a…
-
Artikel Jurnal
Early Detection of Digital Transaction Fraud in Banking Systems Using the Random Forest Algorithm
This research aims to develop methods for preventing and detecting cyberattacks in banking systems by leveraging machine learning techniques.[1] Cybersecurity threats are becoming increasingly complex and pose significant risks to banking institutions and their customers through various attack…