Yasi Dani - Profile on Academia.edu (original) (raw)

Papers by Yasi Dani

Engineering, Mathematics and Computer Science Journal (EMACS), Jan 31, 2024

In this paper, we discuss the implementation of momentum conservative scheme to shallow water equ... more In this paper, we discuss the implementation of momentum conservative scheme to shallow water equations (SWE). In shallow water model, the hydrodynamic pressure of the water is neglected. Here, the numerical calculation of mass and momentum conservation was applied on a staggered grid domain. The vertical interval was divided into two parts which made the computation quite efficient and accurate. Our focus is on the performance of the numerical scheme in simulating wave propagation and runup phenomena, where the main challenge is to calculate the wave speed accurately and to count the non-linear term of the model. Here we also considered the wet and dry conditions of the topography. Three benchmark tests were picked out to validate the numerical scheme. A simulation of standing wave was carried out; the results were compared to the linear analytical solution and show a good fit. In addition, a simulation of harmonic wave propagation on a sloping beach was conducted, and the results closely align with the expected values from exact solution. Finally, we carried out a simulation of solitary wave with a sloping topography; and the results were compared to laboratory data. A good agreement was observed between the simulation results and experimental measurements.

International Journal of Power Electronics and Drive Systems/International Journal of Electrical and Computer Engineering, Apr 1, 2024

In this study, we apply two classification algorithm methods, namely the Gaussian naïve Bayes (GN... more In this study, we apply two classification algorithm methods, namely the Gaussian naïve Bayes (GNB) and the decision tree (DT) classifiers. The Gaussian naïve Bayes classifier is a probability-based classification model that predicts future probabilities based on past experiences. Whereas the decision tree classifier is based on a decision tree, a series of tests that are performed adaptively where the previous test affects the next test. Both of these methods are simulated on the Iris dataset where the dataset consists of three types of Iris: setosa, virginica, and versicolor. The data is divided into two parts, namely training and testing data, in which there are several features as information on flower characteristics. Furthermore, to evaluate the performance of the algorithms on both methods and determine the best algorithm for the dataset, we evaluate it using several metrics on the training and testing data for each method. Some of these metrics are recall, precision, F1-score, and accuracy where the higher the value, the better the algorithm's performance. The results show that the performance of the decision tree classifier algorithm is the most outperformed on the Iris dataset.

Similarity search on Southeast Asian food ingredients using association rule mining

AIP Conference Proceedings, Dec 31, 2022

Mendel ..., Dec 19, 2023

Outlier analysis has been widely studied and has produced many methods. However, there is still r... more Outlier analysis has been widely studied and has produced many methods. However, there is still rare a method to detect outliers for dynamically streaming batch data (online learning). In the present research, a novel online algorithm to detect outliers in such dataset is proposed. Data points are proceeded by applying a modified recursive PCA to predict sequentially parameters of the model; eigenvalues and eigenvectors of the statistical detection model are recursively updated using approximate values by perturbation methods. More specifically, the recursive eigenstructure is obtained from the derivation of the covariance matrix using the first-order perturbation technique. The Mahalanobis distance is then used as an outlier score. Our algorithm performances are evaluated using some metrics, namely accuration, precision, recall, F1-score, AUC-PR, and the execution time. Results show that the proposed online outlier detection is computationally efficient in time and the algorithm's performance effectiveness is comparable to that of the offline outlier detection algorithm via classical PCA.

Effect of Water Temperature on Water Quality Variables in Urban Catfish Cultivation Based on Association Rule Mining

2023 10th International Conference on Information Technology, Computer, and Electrical Engineering (ICITACEE)

A Simple Dataset of Water Quality on Aquaponic Fish Ponds Based on an Internet of Things Measurement Device

JOIV : International Journal on Informatics Visualization

Nowadays, conventional marketing techniques have changed to online (digital) marketing techniques... more Nowadays, conventional marketing techniques have changed to online (digital) marketing techniques requiring internet access. Online marketing techniques have many advantages, especially in terms of cost efficiency and fast information delivery to the public. Therefore, many companies are interested in online marketing and advertising on social media platforms and websites. However, one of the challenges for companies in online marketing is determining the right target consumers since if they target consumers who are not interested in buying the product, the advertising costs will be high. One use of online advertising is clicks on ads which is a marketing measurement of how many users click on the online ad. Thus, companies need a click prediction system to know the right target consumers. And different types of advertisers and search engines rely on modeling to predict ad clicks accurately. This paper constructs the customer ad clicks prediction model using the machine learning app...

Detecting Online Outlier for Data Streams using Recursive Residual

2022 Seventh International Conference on Informatics and Computing (ICIC)

Performance Analysis Spectrum Sensing using Eigenvalue-Moment-Ratio for Internet of Things Devices

2019 International Conference on Information and Communications Technology (ICOIACT), 2019

Internet of things (IoT) is one famous technology now. IoT fit objects will be interconnected thr... more Internet of things (IoT) is one famous technology now. IoT fit objects will be interconnected through wired and wireless communication technologies. It makes demand high. One of the solutions using cognitive radio (CR) for better utilization, CR has spectrum sensing to find unoccupied channel and occupied channel. This study using Eigen Moment Ratio (EMR) for better utilization than Energy Detection (ED). The evaluation shows EMR better than ED, because EMR using a new formula eigenvalue to detect. EMR can distinguish signal + noise from background noise only. EMR also can detect unoccupied channels in multi antennas.

Fermentation of cocoa beans plays an important role in determining the quality of the cocoa beans... more Fermentation of cocoa beans plays an important role in determining the quality of the cocoa beans. Recently a new technique has been developed to test the taste of cocoa beans, namely the Metabolic Fingerprinting Technique. This technique observes the profile comparison of metabolite compounds to be applied in determining the similarities and differences between two or more samples. Since the experimental data may contain many uncertainty factors, such as measurement error, changes in lab environment, and so forth, the fuzzy clustering technique would give the appropriate answer. As a result, a set of metabolic fermentation data from several cocoa beans will be grouped by the fuzzy c-means clustering algorithm (FCM). FCM is a grouping technique where the existence of each data point in a cluster is determined by the degree of membership. This algorithm is based on the minimization of objective functions illustrated by finding the shortest distance between the center of the group and...

Waste is a material that is produced from human activities that are no longer used and disposed o... more Waste is a material that is produced from human activities that are no longer used and disposed of. Waste management really needs support and commitment from the government to produce sustainable solutions. However, the government also has limited funding in the waste handling system. PD. Kebersihan Kota Bandung is a regional company engaged and responsible in the field of cleaning the City of Bandung. Based on the daily report of waste collection, the costs incurred for the operation is quite large. These operational costs are dominated by transportation service costs (driver). Meanwhile, not all vehicles operate every day. Graph theory provides an alternative solution to solve this problem. Welch-Powell algorithm, indicate that to facilitate the transportation of garbage from the temporary landfill to the landfill, the Bandung Wetan area is sufficient to provide a minimum of 4 units of transport trucks.

Sentiment Analysis about Oximeter as Covid-19 Detection Tools on Twitter Using Sastrawi Library

2021 8th International Conference on Information Technology, Computer and Electrical Engineering (ICITACEE), 2021

Sentiment analysis is a technique used to determine whether the opinion statement is positive or ... more Sentiment analysis is a technique used to determine whether the opinion statement is positive or negative. A positive opinion means that it tends to be liked and recommended, whereas a negative opinion indicates that it tends to be disliked and not recommended. An oximeter is a device used to check the level of oxygen in the blood. If the oxygen level in the blood is less than 95%, then there is a tendency for the person to be positive for Covid-19. This study tries to trace the sentiment about the oximeter on tweets in 2021 to get information on whether the majority of tweets on Twitter have a positive or negative opinion on the oximeter. The sentiment analysis model was compared between directly processing data in English with data converted to Indonesian at the pre-processing stemming and stopwords removal stages. Data in Indonesian is processed by applying the Sastrawi library. The results obtained are that converting data to Indonesian at the pre-processing stage has better accuracy in sentiment analysis.