PERUBAHAN PENGGUNAAN LAHAN BERBASIS DATA SPASIAL DI KECAMATAN RAMBUTAN KABUPA…

This research aims to determine the extent of land use change, as well as the factors and impacts of swamp land use change that occurred in 2018 and 2024. The study was conducted from December 2024 to May 2025 using spatial analysis. Mapping was carried out through direct surveys at the research location in Rambutan Subdistrict, Banyuasin Regency, South Sumatra, and processed using QGIS softwar…

PENGEMBANGAN MODEL STEGANOGRAFI CITRA BERBASIS U-NET DENGAN CONVOLUTIONAL SPA…

This study proposes an image steganography architecture based on a modified U-Net integrated with Convolutional Spatial Attention (CSA) on the cover stream and a Laplacian-based Residual Map on the Y-channel, designed to produce an embedding probability map that more selectively targets textured regions. The model generates a residual embedding which is inserted using a ±1 modulation scheme wi…

PENERAPAN RANDOM FOREST UNTUK KLASIFIKASI POLA PENGETIKAN BERBASIS KEYSTROKE …

Security in authentication systems is a crucial aspect of protecting user data and identity. One approach that can be applied is keystroke dynamics, which analyzes typing patterns as a form of behavioral biometric characteristics. This study aims to develop and evaluate a machine learning based classification model using the Random Forest algorithm to identify user typing patterns. The dataset …

OPTIMASI FUZZY TSUKAMOTO DENGAN PARTICLE SWARM OPTIMIZATION (PSO) UNTUK SCREE…

The increasing problem of drug abuse has made it difficult for families to determine whether noticeable changes in a person’s behavior are normal or early signs of addiction. To address this challenge, this study develops an addiction-screening system using the Fuzzy Tsukamoto method combined with Particle Swarm Optimization (PSO). The system assesses four main indicators—physical, psycholo…

PENGEMBANGAN LKPD IPA TERPADU BERBASIS PROBLEM BASED LEARNING (PBL) TOPIK PAR…

This research is a development research that aims to produce Integrated Science Student Worksheet Based on Problem Based Learning (PBL) Topic of Material Compiling Particlees that are valid, practical, and effective. The development model used is Rowntree (planning, development stages) modified with Tessmer formative evaluation. Tessmer formative evaluation stages consist of self-evaluation, ex…

PENGEMBANGAN LKPD IPA TERPADU BERBASIS PROBLEM BASED LEARNING (PBL) TOPIK SEN…

This development research was conducted to produce Problem Based Learning (PBL) based Learner Worksheets (LKPD) and applied for learning chemical compounds in class VIII SMPN 1 Sembawa which are valid, practical, and effective. The development model used in this research is the Rowntree development model and modified with Tessmer's formative evaluation. Data were collected through interviews, q…

CLUSTERING NILAI SISWA SMA UNTUK MENENTUKAN BIDANG KEILMUAN PERGURUAN TINGGI …

Currently, there are still many students in high school who are still confused in determining the scientific field in higher education, even though the scientific field is one of the important things before determining the college they want to enter. They still depend on their parents or friends when they want to choose a scientific field, these high school students don't have a strong reason t…

PENGEMBANGAN LEMBAR KERJA PESERTA DIDIK IPA TERPADU BERBASIS PROBLEM BASED LE…

Penelitian pengembangan ini telah dilakukan untuk menghasilkan produk LKPD berbasis problem based learning IPA di kelas IX SMP IT Raudhatul Ulum yang valid, praktis, dan efektif. Metode penelitian pengembangan yang dilakukan pada penelitiam ini menggunakan model Rowntree yang dimodifikasi evaluasi formatif tessmer. Penelitian ini meliputi tiga tahap, yaitu 1) tahap perencanaan, 2) tahap pengemb…

PENGEMBANGAN LKPD IPA TERPADU BERBASIS PROJECT BASED LEARNING TOPIK UJI DAYA …

Penelitian Pengembangan ini telah dilakukan untuk menghasilkan produk LKPD LKPD IPA Terpadu berbasis project based learning di kelas IX.10 SMP Negeri 18 Palembang yang valid, praktis dan efektif.Metode penelitian Pengembangan yang dilakukan pada penelitian ini menggunakan model ADDIE yang dimodifikasi evaluasi formatif pengembangan tessmer. Penelitian ini meliputi 4 tahapan yaitu 1) tahap anali…

EKSTRAKSI KATA KUNCI PADA ARTIKEL BERBAHASA INDONESIA MENGGUNAKAN METODE RAKE.

The increasing number of scientific articles presents a challenge for researchers in quickly accessing relevant information. One of the main challenges is determining efficient keywords. To address this, an automatic keyword extraction system becomes an essential solution, aimed at developing and evaluating methods for keyword extraction to accelerate the search and management of information fr…

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…