Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi)最新文献

Mapping Residential Land Suitability Using a WEB-GIS-Based Multi-Criteria Spatial Analysis Approach: Integration of AHP and WPM Methods 利用基于 WEB-GIS 的多标准空间分析方法绘制住宅用地适宜性地图：整合 AHP 和 WPM 方法

Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Pub Date : 2024-04-20 DOI: 10.29207/resti.v8i2.4520

Anik Vega, Choirul Ullum, A. Maukar, Verdi Yasin, Seftin Fitri, Ana Wati

{"title":"Mapping Residential Land Suitability Using a WEB-GIS-Based Multi-Criteria Spatial Analysis Approach: Integration of AHP and WPM Methods","authors":"Anik Vega, Choirul Ullum, A. Maukar, Verdi Yasin, Seftin Fitri, Ana Wati","doi":"10.29207/resti.v8i2.4520","DOIUrl":"https://doi.org/10.29207/resti.v8i2.4520","url":null,"abstract":"Along with the rise in population and the acceleration of economic expansion, there has been a concomitant rise in the urgent requirement for additional property that can serve as a venue for a wide variety of community activities. It is not uncommon for large cities that are the epicenter of urbanization, such as the city of Surabaya, to experience a sharp uptick in the demand for land. One of the regions that has excellent accessibility is the Sidoarjo Regency, which is comparable to the City of Surabaya in this regard. The goal of this research is to use Web-GIS to conduct an analysis of spatial data in order to identify the land functions that are most suitable for use in residential areas. The Analytic Hierarchy Process (AHP) and the Weighted Product Model (WPM) are two of the methodologies that are included in the spatial data modeling method that uses multi-criteria decision making (MCDM). The characteristics parameters that are employed are derived from data such as the distance to the city center, the distance to the market, the distance to the hospital, the distance to public transit, the slope, the kind of soil, and the amount of rainfall. The outcomes of spatial data modeling categorize the suitability of new residential land into categories of land that is not suitable for residential use and land that is acceptable for residential use. A K value of 0.27 is the outcome of the comparison test that was run between the two MCDM approaches using Cohen's Kappa coefficients.","PeriodicalId":435683,"journal":{"name":"Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi)","volume":"9 14","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140680932","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Balinese Script Handwriting Recognition Using Faster R-CNN 使用更快的 R-CNN 识别巴厘岛文字手写体

Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Pub Date : 2023-11-26 DOI: 10.29207/resti.v7i6.5176

Alif Adwitiya Pratama, M. D. Sulistiyo, Aditya Firman Ihsan

{"title":"Balinese Script Handwriting Recognition Using Faster R-CNN","authors":"Alif Adwitiya Pratama, M. D. Sulistiyo, Aditya Firman Ihsan","doi":"10.29207/resti.v7i6.5176","DOIUrl":"https://doi.org/10.29207/resti.v7i6.5176","url":null,"abstract":"In Balinese culture, the ability to read Balinese script is one of the challenges young generations face. Advances in machine learning have proposed handwriting detection systems using both traditional and deep learning models. However, the traditional approach is usually impractical and is prone to inaccurate identification results. Convolutional Neural Network (CNN)-based models integrate feature extraction and classification into an end-to-end pipeline to increase performance. This research proposes that recognizing characters through an object detection approach makes an end-to-end process of localizing and classifying several characters simultaneously using the Faster R-CNN. Four CNN models, including ResNet-50, ResNet-101, ResNet-152, and Inception ResNet V2 were tested to detect 28 Balinese characters in a single form covering 18 consonants and 10 digits using Intersection over Union (IoU) thresholds: 0.5 and 0.75. ResNet-50 and Inception ResNet V2 achieve 0.991 mAP at IoU of 0.5, while Inception ResNet V2 excels at IoU of 0.75. Further analysis showed that class “nol” had the lowest Recall due to many undetected ground truths. Meanwhile, class “ba” had the lowest Precision due to its similarity with classes “ga” and “nga”. This research contributes to experimenting with Faster R-CNN in detecting handwritten Balinese scripts.","PeriodicalId":435683,"journal":{"name":"Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi)","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139235634","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Forecasting Photovoltaic Output Power Based on Environmental Parameters Using Artificial Neural Network Methods 利用人工神经网络方法预测基于环境参数的光伏输出功率

Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Pub Date : 2023-11-26 DOI: 10.29207/resti.v7i6.5214

Desri Kristina, Silalahi, Agnes Christy, Margareth Rumapea, Wahmisari Priharti, B. S. Aprillia, Agnes Silalahi, Christy Margareth, Wahmisari Rumapea, Bandiyah Priharti, Sri Aprillia

{"title":"Forecasting Photovoltaic Output Power Based on Environmental Parameters Using Artificial Neural Network Methods","authors":"Desri Kristina, Silalahi, Agnes Christy, Margareth Rumapea, Wahmisari Priharti, B. S. Aprillia, Agnes Silalahi, Christy Margareth, Wahmisari Rumapea, Bandiyah Priharti, Sri Aprillia","doi":"10.29207/resti.v7i6.5214","DOIUrl":"https://doi.org/10.29207/resti.v7i6.5214","url":null,"abstract":"Photovoltaic is a system that can convert sunlight into electrical energy. However, photovoltaic efficiency tends to be low and its performance is affected by several environmental parameters such as dust, wind speed, humidity, temperature and other external factors. Because there are many factors that can affect the power generated, we need a power output prediction system that can assist in planning and managing as well as increasing the efficiency of photovoltaic systems. In this research a system is designed that can predict the photovoltaic output power in the short term using the Artificial Neural Network method or what is often called an artificial neural network. Predictions are made based on the effects of several environmental parameters such as wind speed, dust, humidity, and temperature on a 10 Wp photovoltaic system. Performance data for 7 days is used as a dataset and then processed using ANN with 1 input layer, 3 hidden layers and 1 output layer and 3 sample epochs (10, 100, and 1000). The results of the study can predict the output of photovoltaic power for the next 4 days with an error value of Mean Square Error (MSE) of 0.0010, Mean Absolute Error (MAE) of 0.0155, Root Mean Square Error (RMSE) of 0.0229 with an increase in power reach 0.5 to 1 watt.","PeriodicalId":435683,"journal":{"name":"Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi)","volume":"18 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139235572","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Imputation Missing Value to Overcome Sparsity Problems in The Recommendation System 计算缺失值以克服推荐系统中的稀疏性问题

Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Pub Date : 2023-11-26 DOI: 10.29207/resti.v7i6.5300

Sri Lestari, M. E. Afdila, Y. A. Pratama

引用次数: 0

Android Application for Tomato Leaf Disease Prediction Based on MobileNet Fine-tuning 基于移动网络微调的番茄叶病预测 Android 应用程序

Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Pub Date : 2023-11-26 DOI: 10.29207/resti.v7i6.5132

Mutia Fadhilla, Des Suryani

引用次数: 0

Digital Image Encryption Using Logistic Map 利用逻辑图进行数字图像加密

Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Pub Date : 2023-11-26 DOI: 10.29207/resti.v7i6.5389

Muhammad Rizki, Erik Iman, Heri Ujianto, Rianto

{"title":"Digital Image Encryption Using Logistic Map","authors":"Muhammad Rizki, Erik Iman, Heri Ujianto, Rianto","doi":"10.29207/resti.v7i6.5389","DOIUrl":"https://doi.org/10.29207/resti.v7i6.5389","url":null,"abstract":"This study focuses on the application of the Logistic Map algorithm in the Python programming language for digital image encryption and decryption. It investigates the impact of image type, image size, and Logistic Map parameter values on computational speed, memory usage, encryption, and decryption results. Three image sizes (300px x 300px, 500px x 500px, and 1024px x 1024px) in TIFF, JPG, and PNG formats are considered. The Digital Image Encryption and Decryption process utilizes the Logistic Map algorithm implemented in Python. Various parameter values are tested for each image type and size to analyze the encryption and decryption outcomes. The findings indicate that image type does not affect memory usage, which remains consistent regardless of image type. However, image type significantly influences Decryption results and computation time. Notably, the TIFF image type exhibits the fastest computation time, with durations of 0.17188 seconds, 0.28125 seconds, and 1.10938 seconds for 300px x 300px, 500px x 500px, and 1024px x 1024px images, respectively. Additionally, the encryption results vary depending on the image type. The Logistic Map algorithm is unable to restore encryption results accurately for JPG images. Furthermore, the research highlights that higher values of x, Mu, and Chaos lead to narrower histogram values, resulting in improved encryption outcomes. This study contributes to the field by exploring the application of the Logistic Map algorithm in Python and analyzing the effects of image type, image size, and Logistic Map parameter values on computation time, memory usage, and Digital Image Encryption and Decryption results. Prior research has not extensively addressed these aspects in relation to the Logistic Map algorithm in Python","PeriodicalId":435683,"journal":{"name":"Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi)","volume":"120 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139235623","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Analysis and Classification of Customer Churn Using Machine Learning Models 使用机器学习模型对客户流失进行分析和分类

Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Pub Date : 2023-11-25 DOI: 10.29207/resti.v7i6.4933

Muhammad Maulana Sidiq, Dyah Anggraini

{"title":"Analysis and Classification of Customer Churn Using Machine Learning Models","authors":"Muhammad Maulana Sidiq, Dyah Anggraini","doi":"10.29207/resti.v7i6.4933","DOIUrl":"https://doi.org/10.29207/resti.v7i6.4933","url":null,"abstract":"Analysis studies of customer loss (customer churn) have been used for years to increase profitability and build customer relationships with companies. Customer analysis using exploratory data analysis (EDA) for visualizing data and the use of machine learning for the classification of customer churn are often used by past analysts. This study uses several machine learning models that can be used for customer churn classification, namely Logistic Regression, Random Forest, Support Vector Machine (SVM), Gradient Boosting, AdaBoost, and Extreme Gradient Boosting (XGBoost). However, there is a class imbalance factor in the dataset, which is the biggest challenge that is usually faced by analysts to get good results in the classification of machine learning models. The Synthetic Minority Over-sampling Technique (SMOTE) method is a popular method applied to deal with class imbalances in datasets. The results of the analysis show that the classification of churn customers using the XGBoost algorithm has the best level of accuracy compared to other algorithms, with an accuracy value of 0.829424, and the oversampling method with SMOTE tends to reduce the accuracy value of each classification algorithm. The Permutation Feature Importance (PFI) technique from the XGBoost model gets the result that tenure, monthly contracts, and TV streaming are the features that affect customer churn the most.","PeriodicalId":435683,"journal":{"name":"Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi)","volume":"66 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139237047","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

MSER-Vertical Sobel for Vehicle Logo Detection mser -垂直索贝尔车辆标志检测

Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Pub Date : 2023-10-29 DOI: 10.29207/resti.v7i5.5034

None Gamma Kosala, None Agus Harjoko, None Sri Hartati

{"title":"MSER-Vertical Sobel for Vehicle Logo Detection","authors":"None Gamma Kosala, None Agus Harjoko, None Sri Hartati","doi":"10.29207/resti.v7i5.5034","DOIUrl":"https://doi.org/10.29207/resti.v7i5.5034","url":null,"abstract":"Detecting a vehicle logo is the first step before realizing the identity of the logo. However, the detection of logos can pose difficulties due to various factors, including logo variations, differing scales and orientations, background interference, varying lighting conditions, and partial obstruction. This paper presents a vehicle logo detection method using hand-crafted features. We used a combination of Maximally Stable Extremal Region (MSER) and Vertical Sobel. We combine vertical Sobel with MSER to overcome MSER's limitation in recognizing objects of different sizes. These two features are merged using a closing morphology operation to form blobs selected as logo candidate areas. Moreover, a Support Vector Machine (SVM) is implemented to choose a logo area by analyzing each candidate's Histogram of Oriented Gradient (HOG). The proposed method was compared with other methods by implementing them on the same dataset. The significant advantage of using MSER-Vertical Sobel is its fast computation time. It is faster than other approaches that use non-handcrafted features. The test results show that the MSER-Vertical Sobel can achieve high accuracy and the fastest computation time.","PeriodicalId":435683,"journal":{"name":"Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi)","volume":"26 2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136158092","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Critical Factors to Improve Teamwork Quality in Indonesian Startups Using aTWQ Framework 运用aTWQ框架提高印尼创业公司团队合作质量的关键因素

Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Pub Date : 2023-10-29 DOI: 10.29207/resti.v7i5.5099

Muhammad Fathin, Teguh Raharjo

{"title":"Critical Factors to Improve Teamwork Quality in Indonesian Startups Using aTWQ Framework","authors":"Muhammad Fathin, Teguh Raharjo","doi":"10.29207/resti.v7i5.5099","DOIUrl":"https://doi.org/10.29207/resti.v7i5.5099","url":null,"abstract":"Due to the ever-changing needs of IT in today's businesses, agile software development has become popular due to its adaptive capabilities. Startups are among those who continuously strive to meet changing needs. Despite the potential benefits of the Agile methodology, teamwork quality remains a challenge. Furthermore, the global recession has made it increasingly important for startups to have effective teamwork, given the high level of uncertainty that leads to challenges in surviving, especially with cost-cutting and downsizing efforts. Therefore, this study aims to evaluate teamwork quality in Indonesian startups using the Agile Teamwork Quality (aTWQ) approach. TWQ is a comprehensive set of criteria designed to assess teamwork quality in agile environments. The primary objective of this study is to identify the factors that most strongly increase the quality of teamwork of Indonesian startups. To achieve this objective, data will be collected from Indonesian companies using an online survey based on the aTWQ framework. The challenges were identified most on the dimensions of cohesion, balance of contribution, and effort. The findings of this study are consistent with previous research, which may hopefully help start-ups in Indonesia improve their teamwork quality and achieve greater success in their respective industries.","PeriodicalId":435683,"journal":{"name":"Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi)","volume":"11 2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136157361","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Robust Digital Watermarking on Vital Archives using Hybrid SVD and DWT Methods 基于SVD和DWT混合方法的重要档案鲁棒数字水印

Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Pub Date : 2023-10-28 DOI: 10.29207/resti.v7i5.5003

None Alita Wulan Dini, None Shelvie Nidya Neyman, None Toto Haryanto

{"title":"Robust Digital Watermarking on Vital Archives using Hybrid SVD and DWT Methods","authors":"None Alita Wulan Dini, None Shelvie Nidya Neyman, None Toto Haryanto","doi":"10.29207/resti.v7i5.5003","DOIUrl":"https://doi.org/10.29207/resti.v7i5.5003","url":null,"abstract":"The development of internet technology affects the dissemination of data, especially in vital government archives. This research uses a hybrid Singular Value Decomposition (SVD) and Discrete Wavelet Transform (DWT) method, which aims to protect the copyright of vital archives. The stages of the insertion and extraction process are carried out to test the effect of the alpha value on the quality (imperceptibility) and robustness of the inserted image by measuring the Peak Signal to Noise Ratio (PSNR), verifying similarity by measuring the Normalized Cross-Correlation (NC) and Structural Similarity Index (SSIM). The results of research with ten vital archives and a protection watermark logo in JPEG format with a size of 512x512 pixels obtained a maximum PSNR with a value of α = 0.01 of 41.0567 dB, NC of 0.98904, and SSIM of 0.98023 on the Cibereum Land Certificate. So it can be proven that this method produces vital archive watermarks that can be extracted and are robust to JPEG compression attacks of 75%, median filtering 3x3, Gaussian noise 0.01, speckle noise 0.01, and salt and pepper noise 0.01 but not resistant to rotation 80˚ and cropping attacks 2 %.","PeriodicalId":435683,"journal":{"name":"Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi)","volume":"57 6","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136233374","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0