KLASIFIKASI TINGKAT KEMATANGAN BUAH PEPAYA MENGGUNAKAN CONVOLUTIONAL NEURAL N…

Image classification is a major challenge in the digital world, especially in the field of deep learning. so this research develops a classification system using Convolutional Neural Network (CNN) with five architectures namely GoogLeNet (InceptionV3), MobileNet, ResNet50, SqueezeNet, and Visual Geometry Group (VGG16) to classify papaya fruit. With the number of data for ripe papaya 267, unripe…

FINE-TUNING INDOBERT UNTUK KLASIFIKASI KATEGORI BERITA BERBAHASA INDONESIA.

The availability of Indonesian news articles on the internet has greatly increased, making it more challenging to recognize and categorize news accurately. Therefore, a solution to this issue is to develop a classification system for Indonesian news article categories. This research aims to classify Indonesian news category using fine-tuning on the pre-trained IndoBERT model. The dataset consis…

ANALISIS SENTIMEN MASYARAKAT TERKAIT PEMBANGUNAN IBU KOTA NUSANTARA (IKN) MEN…

The development of Ibu Kota Nusantara (IKN) has become a topic of public interest, generating various opinions reflecting societal sentiment. This study aims to analyze public sentiment toward the development of IKN using a fine-tuned IndoBERT-based deep learning model. The dataset was collected from platform X, consisting of 18,264 training data, 2,283 validation data, and 2,283 test data, wit…

Fisika Komputasi

Edition

-

ISBN/ISSN

978-623-372-956-7

Collation

x, 252 hlm.; 23 cm

Series Title

-

Call Number

530.028 5 Akm F

Kriptografi, Teknik Keamanan Data Dan InformasiPengantar Ilmu Kriptografi, Te…

Edition

-

ISBN/ISSN

978-623-010-288-2

Collation

xvi, 392 hlm.; 23 cm

Series Title

-

Call Number

005.824 Sim k

KLASIFIKASI SMS SPAM BERBAHASA INDONESIA MENGGUNAKAN K-NEAREST NEIGHBOR DAN C…

SMS Spam sangat membahayakan sehingga dapat menyebabkan kerugian bagi pengguna layanan SMS. Untuk mengatasi hal tersebut, dibutuhkan metode yang dapat membantu mengelompokan SMS sesuai dengan ketegorinya, yaitu Spam dan non spam. Klasifikasi merupakan salah satu proses mengelompokkan data kedalam kelas yang telah ditentukan sebelumnya. Pengklasifikasian melewati beberapa tahapan yaitu, pra peng…

PENERAPAN ALGORITMA RANDOM FOREST UNTUK SENTIMEN ANALISIS PADA POSTINGAN FACE…

Traffic congestion is a recurring issue in Palembang City and significantly affects the daily activities of its residents. Social media, particularly Facebook, serves as a platform for the public to express their opinions and complaints regarding traffic conditions. This study aims to analyze public sentiment toward traffic congestion in Palembang City using the Random Forest algorithm. The res…

SEGMENTASI PELANGGAN MENGGUNAKAN ALGORITMA K-MEANS DENGAN ELBOW METHOD PADA S…

Customer segmentation is a significant application of data analysis in business. This research uses the K-Means algorithm to group customer data based on transaction habits, with parameters from the dataset as cluster determinants. To determine the optimal number of clusters, the Elbow Method is applied, which is based on the highest difference of inertia values. The results show that 2 cluster…

ANALISIS EVALUASI TINGKAT LITERASI KEAMANAN CYBER PENGGUNAAN MEDIA SOSIAL (ST…

This study aims to analyze the level of cyber security literacy among students of SMK Bukit Asam and classify it using the Random Forest algorithm. The research employed a quantitative approach using a questionnaire consisting of four main indicators: knowledge, attitude, behavior, and overall cyber security literacy. A total of 192 students participated as respondents in this study. The result…

ANALISIS KLASTERING KELOMPOK PEKERJAAN MENGGUNAKAN METODE K-MEANS PADA DATA S…

The oil and gas industry involves high-risk activities that require accurate utilization of operational data to support occupational safety. However, at PT Pertamina Hulu Rokan Zona 4 Field Limau, the Work Permit Safety System (SIKA) is still used mainly as an administrative document and has not been leveraged to analytically identify work permit patterns. This study aims to explore clustering …

PENERAPAN METODE LONG SHORT-TERM MEMORY (LSTM) UNTUK PREDIKSI PRODUKSI MINYAK…

Oil production prediction is a crucial component of operational planning and strategic decision-making in the upstream oil and gas industry. This study applies the Long Short-Term Memory (LSTM) method to model and predict oil production using daily historical data from PT Pertamina Hulu Rokan Regional 1 Zona 4 Limau Field for the period January 1, 2022, to July 31, 2025. Data processing steps i…

KNOWLEDGE DISCOVERY DALAM KOMPARASI ALGORITMA ENSEMBLE BOOSTING PADA KLASIFIK…

Good water quality is one of the leading indicators in supporting the life of living things. However, pollution from industrial, domestic, and agricultural waste has resulted in a decline in water quality, which has the potential to cause environmental and health problems. Rapid technological advancements have made machine learning algorithms a viable alternative for classifying water quality. …

KNOWLEDGE DISCOVERY DALAM MEMPREDIKSI SKOR SUSTAINABLE DEVELOPMENT GOALS (SDG…

SDGs score prediction is important in assisting the planning and evaluation of policies to achieve these global targets. This study aims to compare the performance of several regression algorithms in predicting the SDGs score: Polynomial Regression, Support Vector Regression, Random Forest Regression, and Gradient Boosting Regressor. The dataset used consists of data on country names, years, SD…

PERBANDINGAN ALGORITMA KLASIFIKASI DALAM MENGANALISIS KONSISTENSI PEMILIHAN J…

Choosing a college major that is consistent with a student's high school background is a crucial factor in supporting academic achievement and career preparation. This study focuses on a comparative analysis of the Support Vector Machine (SVM) and K-Nearest Neighbor (KNN) algorithms in evaluating the consistency of college major selection. This study used processed data from 636 students for an…

PENERAPAN ADASYN UNTUK MENANGANI DATA IMBALANCE DALAM PERBANDINGAN KINERJA SV…

The rapid growth of digital applications has heightened the need to understand user perceptions more thoroughly, particularly through sentiment analysis of user-generated reviews. In practice, sentiment classification often faces challenges related to class imbalance, especially when neutral reviews are significantly fewer than positive or negative ones. This imbalance can limit a model’s abi…

ANALISIS SENTIMEN PADA APLIKASI JMO MOBILE DALAM PERBANDINGAN KINERJA SUPPORT…

JMO Mobile is a digital service application that enables the public to access employment-related information and benefits. User reviews serve as a valuable resource for evaluating service quality, yet systematic sentiment analysis on this application remains limited. This study aims to classify the sentiment of user reviews and compare the performance of Support Vector Machine (SVM) and Random …

EVALUASI PENDEKATAN ENSEMBLE LEARNING UNTUK ANALISIS SENTIMEN PADA ULASAN APL…

The development of online transportation applications such as Maxim has increased the need for sentiment analysis to understand user opinions from reviews on the Google Play Store. The main challenges in this analysis are language diversity, variations in writing style, and data imbalance, which affect model accuracy. This study aims to evaluate the performance of the Support Vector Machine (SV…

IMPLEMENTASI INDOBERT UNTUK ANALISIS SENTIMEN BERBASIS ASPEK TERHADAP ULASAN …

Aspect-Based Sentiment Analysis (ABSA) has become a crucial approach for extracting detailed opinions from user-generated content, especially in the healthcare domain. This study analyzes public sentiment toward hospital services in Indonesia using IndoBERT, fine-tuned on 2.448 reviews collected from Google Reviews and Instagram. Sentiment labels were automatically assigned with a pre-trained I…

PERBANDINGAN ALGORITMA RANDOM FOREST, LOGISTIC REGRESSION, DAN XGBOOST DALAM …

Understanding user sentiment from e-commerce reviews is essential for platform improvement and business strategy. This study compares three machine learning algorithms—Logistic Regression, Random Forest, and XGBoost—for sentiment classification of Indonesian-language Tokopedia reviews. A dataset of 6,822 user reviews was preprocessed through tokenization, stopword removal, and TF-IDF vector…

ANALISIS SENTIMEN PELANGGAN TERHADAP PENILAIAN PRODUK PADA TOKOPEDIA NYEMIL.S…

Penelitian ini bertujuan menganalisis sentimen pelanggan terhadap ulasan produk pada toko Nyemil.Saji di Tokopedia menggunakan metode Support Vector Machine (SVM). Permasalahan utama yang melatarbelakangi penelitian adalah adanya ketidaksesuaian antara isi ulasan teks dan rating bintang yang menyulitkan evaluasi kualitas produk secara objektif. Data dikumpulkan melalui web scraping dan diproses…

ANALISIS DAMPAK QUANTUM COMPUTING TERHADAP KEAMANAN SISTEM KRIPTOGRAFI KONVEN…

Kemajuan komputasi kuantum membawa tantangan besar bagi keamanan sistem kriptografi konvensional yang saat ini banyak digunakan, seperti RSA dan ECC, yang bergantung pada kesulitan komputasi faktorisasi bilangan besar dan logaritma diskret. Penelitian ini bertujuan untuk menganalisis dampak dari komputasi kuantum terhadap algoritma kriptografi konvensional dengan menggunakan simulasi algoritma …

SISTEM REKOMENDASI COLLABORATIVE FILTERING MENGGUNAKAN KOMBINASI METODE CLUST…

A recommendation system helps collect and analyze user data to generate personalized recommendations for users. A recommendation system for movies has been implemented, considering the vast number of available films and the difficulty users face in finding movies that match their interests. One popular recommendation method is Collaborative Filtering (CF). Although widely applied, CF still has …

TOPIC MODELLING PEMBERITAAN KASUS KDRT LESTI KEJORA DAN RIZKY BILLAR PADA DET…

This research was conducted to find out what topics exist in the reporting of Lesti Kejora and Rizky Billar's domestic violence cases on online media Detik.com and Tribunnews. The analysis was conducted by comparing two periods, namely before and after Lesti Kejora withdrew the report. With the help of Octoparse and Voyant Tools, the researcher obtained a total of 2,110 news articles written be…

PENERAPAN METODE EXTREME GRADIENT BOOSTING UNTUK DETEKSI MULTI-CLASSIFICATION…

In the developing digital era, cybersecurity threats are increasing. One of the solutions commonly used in securing networks is the Network Intrusion Detection System (NIDS). To improve the performance of NIDS, this study applies the Machine Learning (ML) method, namely the Extreme Gradient Boosting (XGBoost) method, because it is considered to have high performance and its ability to handle co…

KOMPARASI KLASTERISASI DATA HISTORIS GEMPA BUMI MENGGUNAKAN DBSCAN, K-MEANS, …

Earthquakes belong to the category of natural disasters that are prone to occur on the island of Sumatera and pose a serious challenge because they can have a devastating impact on human life, such as loss of life, material losses, and environmental damage. Consequently, earthquake hazard zone mapping is needed to provide information about the potential and history of disasters and is an import…

VISUALISASI TRAFIK SERANGAN SIBER DENGAN METODE GEO IP

The escalation of cyber attack activities demands intensive network traffic monitoring by network administrators. However, conventional monitoring methods relying on text-based log analysis are often inefficient due to the difficulty in rapidly identifying attack patterns and origins. This study aims to design and build a cyber attack traffic visualization system by applying the Geo IPmethod. T…

EVALUASI TINGKAT KEMATANGAN TATA KELOLA TEKNOLOGI INFORMASI MENGGUNAKAN FRAME…

The implementation of the BRAVO application at the Traffic Directorate (Ditlantas) of the South Sumatra Regional Police still faces challenges such as network instability, third-party dependency, and technical disruptions, indicating weaknesses in IT governance. This study aims to assess the maturity level of IT governance using the COBIT 2019 and ITIL V4 frameworks. The research began with a d…

ANALISIS KLASTERISASI KUALITAS INTERNET SELULER MENGGUNAKAN METODE K-MEANS DA…

Penelitian ini menggunakan data jaringan internet dari Ookla Open Data (Speedtest Global Performance) yang mencakup tiga variabel utama, yaitu kecepatan unduh (download speed), kecepatan unggah (upload speed), dan latensi (latency). Tujuan penelitian ini adalah menganalisis kondisi dan performa jaringan internet seluler di 17 kabupaten/kota Provinsi Sumatera Selatan tahun 2025 serta memberikan …

ASPECT-BASED SENTIMENT ANALYSIS DAN KNOWLEDGE EXTRACTION UNTUK EVALUASI PERSE…

The rapid growth of digital wallet usage in Indonesia has raised concerns regarding user security and account protection. This study evaluates user sentiment related to the security features of the DANA digital wallet by applying Aspect Sentiment Classification (ASC), a subtask of Aspect-Based Sentiment Analysis (ABSA). A total of 4,846 security-related reviews were collected using keyword-base…

KNOWLEDGE DISCOVERY MENGGUNAKAN ANALISIS SENTIMEN DAN PEMODELAN TOPIK PADA UL…

The rapid growth of mobile banking in Indonesia underscores the need for secure and innovative digital financial services. However, studies that compare user experiences across multiple applications within the same bank remain limited. To address this research gap, we analyze BCA’s two primary applications, BCA Mobile and myBCA, which serve millions of users in Indonesia. Data collected from …