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International Journal of Applied Sciences and Smart Technologies
Published by Universitas Sanata Dharma
ISSN : 26558564     EISSN : 26859432     DOI : http://dx.doi.org/10.24071/ijasst
Core Subject : Science, Engineering,
Computer Science & IT Energy Engineering Industrial & Manufacturing Engineering
International Journal of Applied Sciences and Smart Technologies (IJASST) is published by Faculty of Science and Technology, Sanata Dharma University Yogyakarta-Central Java-Indonesia. IJASST is an open-access peer reviewed journal that mediates the dissemination of academicians, researchers, and practitioners in engineering, science, technology, and basic sciences which relate to technology including applied mathematics, physics, and chemistry. IJASST accepts submission from all over the world, especially from Indonesia.
Arjuna Subject : Umum - Umum
Articles 15 Documents
 1   2 
Search results for , issue "Volume 07, Issue 1, June 2025" : 15 Documents clear
Effect of Hyperparameter Tuning on Performance on Classification model Sholeh, Muhammad; Lestari, Uning; Andayati, Dina
International Journal of Applied Sciences and Smart Technologies Volume 07, Issue 1, June 2025
Publisher : Universitas Sanata Dharma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24071/ijasst.v7i1.11735

Abstract

This research aims to analyze the effect of hyperparameter tuning on the performance of Logistic Regression, K-Nearest Neighbours, Support Vector Machine, Decision Tree, Random Forest, Random Forest Classifier, Naive Bayes algorithms.  These six algorithms were tested both using hyperparameter tuning and not using hyperparameter tuning. The dataset used in this research is a public dataset, namely the heart datasheet. This datasheet contains information about features related to the diagnosis of heart disease. Hyperparameter tuning is performed using a grid search technique to determine the best combination of hyperparameter values that can improve model accuracy. Performance comparison is done by measuring the accuracy, precision, recall, and F1-score of each algorithm before and after tuning. The research method follows the stages in the Knowledge Discovery in Databases (KDD) methodology. The KDD methodology consists of several stages of data collection, data cleaning to remove errors, data integration from various sources, and data selection and transformation to be ready for analysis. Next, data mining is performed to find patterns or relationships in the data and evaluation and interpretation of the results to ensure their validity. The results show that hyperparameter tuning applied to the six algorithms does not necessarily improve performance. In the algorithm. SVM and decision tree algorithms, the performance results before hyperparameter tuning actually have a higher accuracy value. The performance of algorithms that experienced an increase after hyperparameter tuning was logistic regression and K-Nearest neighbours. The same performance results are generated in the Random Forest and Naive Bayes algorithms. Based on testing the six algorithms and using the heart datasheet, the hyperparameter tuning process does not always result in a better performance value.
Assessing Impact of Public Transportation Services on Traffic Jam in Dhaka City Khan, Md. Tanjil Mahmud
International Journal of Applied Sciences and Smart Technologies Volume 07, Issue 1, June 2025
Publisher : Universitas Sanata Dharma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24071/ijasst.v7i1.9949

Abstract

This study used JASP Software for descriptive analysis and Chi-square tests. I surveyed 100 people of different backgrounds and age for their opinions. It determined that 56% of respondents were dissatisfied with the public transportation service, and 69% used public transportation daily. According to this study, 82% of people regularly experience traffic jams because it is hard to get to places, especially in places like Mirpur. Even though 64% of those who responded used buses as public transport, but only 18% wanted more buses to help ease traffic. They would rather see digital transportation systems, awareness and safety improvements. Notably, 80% of those who answered think improving public transportation services could help reduce the traffic jams in Dhaka city.
Topology Optimization of Rear Sprocket of Electric Prototype Vehicle Winarbawa, Heryoga
International Journal of Applied Sciences and Smart Technologies Volume 07, Issue 1, June 2025
Publisher : Universitas Sanata Dharma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24071/ijasst.v7i1.12355

Abstract

Kompetisi Mobil Hemat Energi (KMHE) competes for energy efficient vehicles, which are composed of integrated energy-saving systems. One of the systems that is required to be energy efficient is transmission. The transmission discussed in this study is the sprocket chain transmission system. The rear sprocket is an object that needs to be optimized to obtain a lighter mass, thus efficient in terms of overall weight. Using topology optimization via CAD software, rear sprocket mass can be reduced. The results of topology optimization are used as a reference for changing the shape of the sprocket face, to make it easier in terms of fabrication. These results were then re-tested with static simulations to ensure its strength. The conclusion is that the latest sprocket design has a mass reduction of 66% of its original version and the von Misses stress was only 55% of the yield strength at most.
Comparison of SVM, K-NN, RF, CART, and GNB Algorithms for Water Bodies Detection Using Sentinel-2 Level-2a Imagery in Nakhon Pathom, Thailand Nita Nathalia, Ni Putu; Andra Rizqy Wijaya, Gede; Yota Ernanda Aryanto, Kadek; Novita Puspa Dewi, Ni Putu; Hendra Saputra, Putu; Karisma Dewi, Ni Putu; Damayanti, Mellisa; Losinanda Prawira, Kadek
International Journal of Applied Sciences and Smart Technologies Volume 07, Issue 1, June 2025
Publisher : Universitas Sanata Dharma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24071/ijasst.v7i1.11608

Abstract

Satellite imagery is utilized in various fields, one of which is land use and land cover (LULC) analysis. This study aims to classify water bodies using machine learning models such as SVM, K-NN, RF, CART, and GNB. The data source is obtained from the Google Earth Engine (GEE) platform using Sentinel-2 Level-2A satellite imagery, with a dataset of 5,514 data points per year. The Pixel-Based approach is used as the main method for data extraction, while CRISP-DM is applied as a structured methodology for data management. The parameter indices used include the BSI, NDBI, MNDWI, NDVI and AWEIsh. The results of these calculations serve as dataset features for training algorithms in the model development and training process. Each model has its own parameters, making parameter selection crucial in the training process. Model evaluation is conducted using a confusion matrix. Based on confusion matrix analysis, accuracy, precision, recall, and F1-score are calculated. Among the five models, SVM achieves the highest accuracy at 87%, followed by RF and K-NN. This indicates that the SVM model performs better in binary classification. Ground truth analysis is also conducted using the QGIS platform, which visualizes the classification results, with SVM providing the best visualization.
Efficient Design of Reinforced Columns: Insights into Lateral Confinement and Performance Singha, Badhon; Chowdhury, Nafis Niaz; Sakib, Mohammad Atiqur Rahman
International Journal of Applied Sciences and Smart Technologies Volume 07, Issue 1, June 2025
Publisher : Universitas Sanata Dharma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24071/ijasst.v7i1.10376

Abstract

In structural engineering and architecture, a column is a vertical load-bearing member crucial for supporting compressive loads. Reinforced concrete columns consist of both confined and unconfined concrete. Pioneering experiments by Mander et al. (1988a) (Observed stress–strain behavior of confined concrete, 1988a) and (1988b) (Theoretical stress-strain model of confined concrete., 1988b) scrutinized the performance of columns under seismic strain rates, revealing that optimal performance is achieved through meticulous identification of maximum stress and strain locations. The initial stage is to realize the specified attributes derived from SAAP200, which are then included into the ABAQUS finite model simulation. A Validation was conducted by finite model simulation process in Abaqus by comparing results with those presented by Guadagnuolo et al. (2020) to assess the accuracy and reliability of the methodology. The resulting Load vs Displacement relations are then subjected to validation based on property-centric criteria. The efficacy of outcomes is highlighted by presenting distinct load vs displacement curves for concrete columns at various pitch distances. Excessive spacing between hoops can result in early spalling and reduced strength, whereas an increased hoop area in the intermediate zone improves both load-carrying and deformation capabilities.
Analysis of Spiral Pump Head Based on Water Wheel Parameters Luntungan, Hengky; Tangkuman, Stenly; Maluegha, Benny Lokombanua
International Journal of Applied Sciences and Smart Technologies Volume 07, Issue 1, June 2025
Publisher : Universitas Sanata Dharma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24071/ijasst.v7i1.10383

Abstract

Water supply is a crucial factor for farmers in managing agricultural land, especially those relying on river water sources. The lower position of rivers and the considerable distance from the fields often pose challenges, making water pumps powered by electricity or fuel a common choice, despite their high operational costs. To address this issue, the utilization of renewable energy through the use of a spiral pump powered by a water wheel is proposed. The spiral pump is considered an environmentally friendly technology as it does not require electricity or fossil fuels. This study aims to analyze the head of a spiral pump based on the parameters of an undershot water wheel as preparation for the design of the spiral pump. In this study, a significant decrease in discharge value was observed from a head of 0.5 m up to a head of 3 m; in contrast, from a head of 3 m to 10 m, the discharge value decreased gradually. For small agricultural land or household needs, this spiral pump water wheel would be suitable at a maximum head of 5 m with a discharge value of 0.53 L/s. The results show a negative correlation between the head of the spiral pump and the discharge produced, where an increase in head results in a lower discharge.
Bubble flow configurations generated by ejector type bubble generator Catrawedarma, I Gusti Ngurah Bagus; Ton, Sefri; Pranowo, Dadang Dwi; Surahmanto, Fredy; Astyanto, Achilleus Hermawan
International Journal of Applied Sciences and Smart Technologies Volume 07, Issue 1, June 2025
Publisher : Universitas Sanata Dharma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24071/ijasst.v7i1.10816

Abstract

Bubble flow configurations generated by an ejector bubble generator were captured using a high-speed video camera and extracted into several images. The air flow and nozzle diameter were varied during the test in ranges of 0.1-1.5 lpm and 1.17-3.5 mm, respectively. The results reveal that in general the bubble flow structure coming out from the bubble generator is divided into three regions, namely the entrance, bubble swarm, and bubble dispersed region. It is found that there is a higher time delay of bubble production when the air flow and the nozzle diameter decrease. On the other hand, the bubble production time is longer, if the air flow and the nozzle diameter increase.
Cluster Change Analysis to Assess the Effectiveness of Speaking Skill Techniques using Machine Learning Wulandari, Nunik Herani; Purwayoga, Vega
International Journal of Applied Sciences and Smart Technologies Volume 07, Issue 1, June 2025
Publisher : Universitas Sanata Dharma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24071/ijasst.v7i1.9667

Abstract

This study aims to compare effective teaching methods for speaking using machine learning. The classes used in this study consisted of three classes: conventional, vlog project, and picture series. The data used were students' pre-test and post-test scores. The machine learning algorithm used is K-Means. K-Means clusters the pre-test and post-test data. The results of K-Means clustering on the pre-test and post-test identified the differences in student groups between the pre-test and post-test. Students who experienced the most cluster movement were those in the vlog project class, the conventional class, and the picture series class.
Determination of Premium Reserves for Whole Life Insurance Using the Canadian Method with Varying Premium Payment Periods Wynnie, Illuminata; Yefan, Yefan
International Journal of Applied Sciences and Smart Technologies Volume 07, Issue 1, June 2025
Publisher : Universitas Sanata Dharma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24071/ijasst.v7i1.12283

Abstract

Premium reserves are essential funds prepared by insurance companies, particularly in life insurance, to cover potential future claims. These reserves are calculated based on premiums paid by policyholders and must be sufficient to meet all projected claim-related expenses. A lower reserve implies reduced financial liability and typically correlates with more affordable premium rates for policyholders. This study aims to analyze the determination of premium reserves using the Canadian and Prospective methods in traditional life insurance products, specifically whole life insurance, focusing on different premium payment periods. The Indonesian Population Mortality Table (TMPI) 2023 and the Bank Indonesia interest rate of 5.57% (as of April 2025) as the calculation basis. The results show that the Canadian method produces lower reserve values compared to the Prospective method and indicate a decreasing trend in reserve values as the premium payment period increases in both methods.
Comparison of Laterite Nickel Deposit Levels on the Mining Front with Stockpile at PT Ceria Nugraha Indotama, Kolaka Regency Anshariah, Anshariah; Irwan, Muhammad Reza Ardhana; Thamsi, Alam Budiman; Aswadi, Muhammad
International Journal of Applied Sciences and Smart Technologies Volume 07, Issue 1, June 2025
Publisher : Universitas Sanata Dharma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24071/ijasst.v7i1.10460

Abstract

PT Ceria Nugraha Indotama is a company engaged in mining laterite nickel ore in Wolo sub-district, Kolaka district, Southeast Sulawesi province. In lateritic nickel ore mining activities, there is often a difference in levels of laterite nickel ore when it is still in the mining front and after being transferred to the stockpile. This research is to determine the proportion of differences in the levels of Ni, Fe, MgO and SiO2 on the mining front with the stockpile and to determine the factors that influence changes in nickel content. The method used in this study is the grab sampling method in front mining and stockpile. The results of this study are based on the results of the analysis, obtained data on the levels of Ni, Fe, MgO and SiO2 on the mining front with a stockpile, the Ni content has a difference of 0.05% and the Fe content has a difference of 0.34%, the two minerals have the highest grades on the mining front. mining and MgO content has a difference of 2.68% and SiO2 content has a difference of 8.87%, the two minerals have the highest grade in the stockpile. Factors that influence changes in nickel content are the heterogeneous distribution of ore, the position of the waste above the ore and the rainy weather that occurs in the field, operator and sampling skills.

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