4 research outputs found
An Improved Frank–Wolfe Algorithm to Solve the Tactical Investment Portfolio Optimization Problem
No full textQuadratic programming (QP) formulations are widely used in optimal investment portfolio selection, a central problem in financial decision-making. In practice, asset allocation decisions operate at two interconnected levels: the strategic level, which allocates the budget across major asset classes, and the tactical level, which distributes the allocation within each class to individual securities or instruments. This study evaluates the Frank–Wolfe (FW) algorithm as a computationally alternative to a QP formulation implemented in CVXPY and solved using OSQP (CVXPY–OSQP solver) for tactical investment portfolio optimization. By iteratively solving a linear approximation of the convex objective function, FW offers a distinct approach to portfolio construction. A comparative analysis was conducted using a tactical portfolio model with a small number of stock assets, assessing solution similarity, computational running time, and memory usage. The results demonstrate a clear trade-off between the two methods. While FW can produce portfolio weights closely matching those of the CVXPY–OSQP solver at lower and feasible target returns, its solutions differ at higher returns near the limits of the feasible set. However, FW consistently achieved shorter execution times and lower memory consumption. This study quantifies the trade-offs between accuracy and efficiency and identifies opportunities to improve FW’s accuracy through adaptive iteration strategies under more challenging optimization conditions
Indonesian Banking Stock Portfolio Optimization Based on Ridge Regression Prediction
No full textThe Indonesian stock market in the banking sector is a popular investment instrument with high return potential but faces market volatility and global economic uncertainty that requires adaptive and data-driven portfolio management strategies. Traditional asset allocation strategies such as equal weighting or based on historical performance have limitations in dynamic market conditions, while the application of machine learning, especially Ridge Regression, in stock return prediction and portfolio optimization in the Indonesian market has not been widely explored. This study aims to build an integrated pipeline for portfolio prediction and optimization using Ridge Regression on Indonesian banking stocks. Methods: Daily closing price data of five major banking stocks (BBRI, BBCA, BMRI, BBNI, BBTN) for the period 2015-2025 are used with technical indicators of moving average and rolling standard deviation as input features. The Ridge Regression model is trained using TimeSeriesSplit cross-validation to predict daily returns, then the prediction results are integrated into the Mean-Variance optimization framework to maximize the Sharpe ratio. The Ridge Regression model shows excellent predictive performance with an average R² of 0.9986, MAE of 0.000466, and RMSE of 0.000720. The Ridge-based portfolio strategy achieves identical performance to the historical optimal strategy with an annualized return of 10.64% and a Sharpe ratio of 0.4705, significantly outperforming the equal-weight strategy (return of 6.63%, Sharpe ratio of 0.2562). A practical implementation simulation with IDR 100 million funds shows feasible execution with less than 1% deviation from the optimal weights. Ridge Regression is proven to be effective in capturing the return pattern of Indonesian banking stocks and enables superior portfolio performance when integrated with modern portfolio theory, providing investors with a robust and data-driven approach to portfolio optimization in emerging markets
Kreasi Huruf dengan Konsep Urban Art melalui Media Fotografi
No full textHuruf sejak zaman dahulu hingga era modern sekarang merupakan suatu elemenyang penting bagi perkembangan kehidupan manusia di dunia. Huruf dan tulisanmemiliki arti amat penting bagi manusia. Bahkan, yang namanya peradaban ataumasa sejarah ditandai dengan peristiwa dikenalnya tulisan oleh manusia. Jika kitamelihat ke buku atau ke layar komputer, kita akan melihat huruf dan tulisan.Selain gambar, huruf adalah cara manusia berkomunikasi secara visual. Urbanart merupakan perwujudan seni yang dihadirkan melalui media-media seni rupa,seni pertunjukan, dan seni media rekam yang erat dengan problematika kehidupanyang terjadi dalam keseharian masyarakat, serta bisa menjadi simbol yang menarikdan menjadi elemen penting yang menjadi ciri khas dari kota tersebut. Kawasanpinggiran kota dan segala macam fasilitas yang ada di ruang publik menjaditarget utama dalam mencari dan mendapatkan objek-objek huruf alfabet dalampenciptaan fotografi ini. Penciptaan fotografi ini berangkat dari ketertarikanpenulis mengenai huruf, dari desain, bentuk, warna-warnanya, hingga susunanyang menarik yang bisa membuat penulis terkagum-kagum sehingga memunculkanide penciptaan melalui media fotografi mengenai segala hal tentang bentukhuruf. Melalui media fotografi ini nantinya akan tercipta suatu bentuk huruf ataumenangkap moment yang terjadi menggunakan kamera yang terdapat di lingkungansekitar dan fasilitas yang ada melalui hunting di berbagai tempat. Di sini dibatasi fontfontatau huruf-huruf alphabet sebagai objek yang akan di-explore dan dikembangkansebagai objeknya. Tujuan dalam proses pembuatan karya huruf dalam fotografi iniadalah menunjukkan bahwa setiap hal kecil, sepele bisa menjadi ide yang menarikserta unik. Tiap bentuk huruf yang ditemukan berasal dari bentuk sudut (angle)yang tak terduga bisa menjadi objek yang menarik mengasilkan bentuk-bentukhuruf alfabet yang unik. Manfaat dari penciptaan ini adalah secara tidak langsungmemberikan wawasan tambahan mengenai penerapan bahasa dan pengetahuanmengenai huruf-huruf. Bahwa huruf (font) tidak hanya diucapkan serta ditulisseperti biasa tetapi bisa juga dapat dikatakan sebagai “visual language” atau dapatberarti bahasa yang dapat dilihat melalui media fotografi. The Creation of Letters with Urban Art Concept through the Medium ofPhotography. The letters, since ancient times until the modern era, have constitutedan important element for the development of human life in the world. Letters andwritings have very important meaning for human. In fact, the name of civilizationor historical period marked by the events of the familiar writings by men. When we look at the book or the computer screen, we will look at letters and writings. Inaddition to images, the letter is the way people communicate visually. Urban art isan embodiment of art that is presented through the media of visual arts, performingarts, and recording media arts which are closed to our everyday life; and can be aninteresting symbol and becomes the important element of the hallmark of the city.The suburbs and all kinds of facilities in public spaces become a primary target forsearching for and geting alphabetical objects in the creation of this photography. Thecreation of this photography came from the writer’s interest of the letter, whether it isfrom the design, shapes, colours, up to an interesting arrangement of it which couldmake him bringing up the idea of the creation through the medium of photographyabout the shape of the letter. Through the medium of photography, future writers cancreate a form of letters or capture the moment that occurs by using the camera onthe surrounding environment and facilities through hunting the objects in variousplaces. The author limited the Alphabetical letters or as the object to be explored anddeveloped. The purpose in the process of making a piece of letters in photography wasshowing that a small thing could be an interesting and unique idea. Every singleform of the letter found was derived from an angular shape (angle) that unexpectedlycould become the object of the interesting letters of the alphabet producing the uniqueforms. The benefit of the creation is indirectly to give the additional insight onimposing the language and knowledge about the letters. Letters (fonts) are not justspoken and written as usual but they can also be considered as “visual language“orcan be meant a language seen through the medium of photography.</p
Implementation of Machine Learning Model for Pest Classification in Rice Plants
No full textRice cultivation is a cornerstone of food security in agrarian countries like Indonesia, yet it remains highly vulnerable to pest infestations that can severely impact crop productivity. Manual identification of pests is time-consuming and error-prone, especially when pest species exhibit similar morphological characteristics. This study aims to implement and evaluate the performance of four classical machine learning algorithms Support Vector Machine (SVM), K-Nearest Neighbor (KNN), Random Forest (RF), and Logistic Regression (LR) for classifying rice pests based on image data. The dataset, derived from Kaggle’s “Rice Pest Detection Dataset,” includes 12 pest classes and underwent a series of preprocessing steps: grayscale conversion, image resizing to 128×128 pixels, feature extraction using Histogram of Oriented Gradients (HOG), label encoding, and class balancing via SMOTE. The experimental setup used 80% of the data for training and 20% for testing. Performance was evaluated using precision, recall, F1-score, and confusion matrices. Among the four models, SVM achieved the most consistent and robust performance, with F1-scores reaching up to 0.98 in several pest classes and an overall balanced classification across the dataset. Random Forest followed closely, particularly excelling in distinguishing classes such as Rice Water Weevil and Yellow Rice Borer, achieving F1-scores of 0.99 and 0.96 respectively. In contrast, KNN showed signs of overfitting, with extreme precision-recall imbalances, while LR was more stable but less accurate in separating visually similar classes like Rice Stem Fly and Thrips. Visual analysis of correct and incorrect predictions revealed that classes 7 (Rice Stem Fly) and 11 (Thrips) were consistently misclassified across all models, likely due to high visual similarity
