bluuebunny/crossref_metadata_2025 huggingface dataset:
Earthquake Resistance of Masonry-Infilled RC Frames Strengthened with Expanded Metal
Authors: Kusonkhum Wuttipong , Tankasem Phongphan , Leeanansaksiri Anuchat
Published: January 2025

This research aimed to investigate the compressive strength of lightweight concrete walls before and after reinforcement using the expanded metal reinforced with ferrocement jacketing method and to evaluate the performance level of lightweight concrete walls in reinforced concrete rigid frames. Masonry infill walls were tested using seven samples of lightweight concrete with an average size of 600×600 mm under axial force. The study results were found that in the part of control, non-plastered lightweight concrete wall (CWL) bore an average compressive strength of 2.52 MPa, and plastered lightweight concrete (WPL) bore an average compressive strength of 2.95 MPa. It indicated that plastering on masonry infill walls was able to bear higher impact strength at 1.17 times due to the bonding force of plastering cement at the masonry infill wall. Lightweight concrete walls reinforced with expanded metal, which were able to bear the maximum compressive strength, were lightweight concrete walls reinforced with 1 layer of expanded metal (WPL-E1) that bore the maximum compressive strength capacity, which was equal to 6.40 MPa. When compared with plastered lightweight concrete walls (WPL) samples, masonry infill walls had 2.16 times higher strength capacity. It was shown that reinforcement using the ferrocement technique significantly increased compressive strength capacity. However, in this research, WPL samples, the plastered lightweight concrete walls, were selected as the control samples, and WPL-E1 test samples with the highest compressive strength were used to evaluate the performance level of the reinforced concrete rigid frame. It was found that lightweight concrete walls reinforced with expanded metal were able to bear higher strength at 1.92 and 3.66 times, respectively. When compared to unreinforced masonry infill wall samples and the bare rigid frame, reinforcement with expanded metal effectively was able to increase the strength and stiffness of the reinforced concrete rigid frame. Doi: 10.28991/CEJ-2024-010-12-017 Full Text: PDF
The Performance of Geosynthetic Reinforcement Road Pavement Over Expansive Soil Subgrade
Authors: Hairulla . , Harianto Tri , Djamaluddin Abdul Rahman , Arsyad Ardy
Published: January 2025

One of the problems faced in infrastructure development, especially roads, is problematic soils, including expansive soils, which are distributed around 20% of national road construction in Indonesia. Geosynthetics are reinforcement materials that can be used to overcome problematic soils. The study aimed to determine the behavior of expansive soil with geosynthetic reinforcement against swelling potential and swelling pressure in the wetting cycle. The research utilized an experimental approach involving three test concepts. The first was a control test without reinforcement. The second included a combination of geogrid, geotextile, and geomembrane layers, while the third utilized an H2Rx reinforcement layer. Analysis was carried out on the development potential and pressure; the test was carried out for 57 days using displacement sensors and pressure sensors, and data recording was carried out every 5 seconds using a computer. The findings from the results of this study indicated that the presence of reinforcement using a geosynthetic reinforcement layer can overcome the behavior that occurs in expansive soils with swelling potential and swelling pressure. The novelty of this research is the inclusion of a geosynthetic reinforcement layer on expansive soil combined with a drainage layer in the pavement subgrade. Doi: 10.28991/CEJ-2024-010-12-020 Full Text: PDF
Comparison of Multi-Objective Metaheuristics for Discrete Optimization of Steel Trusses Using Direct Analysis
Authors: Tran Trung-Hieu , Vu Quoc-Anh , Truong Viet-Hung , Nguyen Ngoc-Thang
Published: January 2025

This study enriches structural optimization research using direct analysis for steel truss structures, which is often hampered by high computational demands. The main objective of this work is to evaluate multi-objective optimization algorithms in truss sizing optimization with discrete variables, focusing on minimizing total mass and controlling inter-story drift under multiple load combinations. Five leading multi-objective metaheuristic algorithms were assessed: SPEA2, GDE3, NSGA2, MOEA/D, and the novel MOEA/D-EpDE, which uniquely combines MOEA/D with Dynamical Resource Allocation and pbest Differential Evolution. Four performance indicators, such as Generational Distance (GD), GD Plus (GD+), Inverted GD+ (IGD+), and Hypervolume (HV), were utilized. Findings from four truss optimization problems revealed that all considered algorithms located feasible optimal solutions, but MOEA/D-EpDE excelled, consistently securing the lowest GD, GD+, IGD+, and anchor point values, along with the highest HV values in most scenarios. This indicates its superior capability in addressing the problem efficiently. NSGA2 and MOEA/D also performed well, outperforming GDE3 and SPEA2. This study is pioneering in its application of these algorithms to steel truss optimization via direct analysis, highlighting the potential for advanced computational techniques in structural engineering. Doi: 10.28991/CEJ-2024-010-12-07 Full Text: PDF
Coca Codo Sinclair Hydropower Plant: A time bomb in the energy sector for Ecuador or a successful project?
Authors: Naranjo-Silva Sebastian , Romero-Bermeo Juliana
Published: January 2025

In Ecuador, the electricity sector has undergone significant transformation over the past 15 years, with a marked increase in renewable energy capacity, particularly hydropower, which grew from 1,707 MW in 2000 to 5,100 MW in 2022. This shift, driven by the need to diversify the energy grid and reduce fossil fuel dependence. Despite its importance, the Coca Codo Sinclair project with 1,500 MW has faced several technical, environmental, and social challenges, including erosion and structural issues, raising concerns about its long-term sustainability. This article aims to analyze these challenges, their causes, impacts, and potential solutions, providing insights for future hydropower developments in similar regions. Coca Codo Sinclair is an example of the ambition of a government that did not follow the recommendations of technical studies on the maximum capacity that could be generated by a plant that now has more problems than advantages, analyzing all the associated drawbacks that the largest hydropower plant in Ecuador, it is important to understand that technical criteria must prevail over political decisions. In order to keep the more than 3 billion dollars of investment going, urgent action is required on CCS remediation works, with a combination of investments in repairs and maintenance activities, improvements in management and governance of the project, therefore, currently the largest plant in Ecuador represents a time bomb that can collapse due to any of the various problems.
Geographic Information System for Mapping Drug Abuse Areas in Lhokseumawe City Using the Average Linkage Method
Authors: Syintia Icut , Fuadi Wahyu , Yunizar Zara
Published: January 2025

Aceh is one of the provinces in Indonesia where the development of drug abuse has increased. The system that runs at BNN Lhokseumawe City in recording data and information about drug abuse cases has not been integrated with the mapping of drug abuse areas. Therefore, BNN and Lhokseumawe City Police need a drug abuse area mapping system in the Lhokseumawe City area. This research aims to build a webgis-based geographic information system using the Google Maps API for map visualization. The data mining method used is Average Linkage, clustering is done based on the number of cases, number of suspects and population in each sub-district in Lhokseumawe City. Cluster 1 consists of 1 sub-district, namely Banda Sakti, which in cluster 1 has a relatively high average value compared to clusters 2 and 3 so that it is included in a very vulnerable level. In cluster 2 consists of 2 sub-districts, namely Muara Satu and Muara Dua, because this cluster has a medium average value compared to clusters 1 and 3 so that it is included in the vulnerable level. Whereas the cluster in cluster 3 consists of 1 sub-district, namely Blang Mangat, which in cluster 3 has a relatively lower average value than clusters 1 and 2 so that it is included in the moderately vulnerable level.
Implementing a Therapeutic Music Program in the ICU
Authors: Kleinpell Ruth , Schlesinger JJ , Gururaja Akash , Michel M.B.
Published: January 2025

Introduction: In an effort to promote a healing environment in the intensive care unit (ICU), the use of therapeutic music offers an opportunity to expand patient and family centered care initiatives.  However, limited information is available on the benefits of therapeutic music for patients, family members and clinical staff. 
Objective: The objective of this study was to implement a therapeutic music program in the ICU setting.  Using musicians who were processed as hospital volunteers, the program was implemented starting in the medical ICU and expanding to 4 other clinical ICUs at an academic medical center.
Methods: Institutional review board approval for the study was received.  Musicians provide live music several times a week, typically in the late afternoon, visiting patient rooms and playing music in the hallways for those patients with isolation precautions (Figure 1). The volunteer musicians play classical genre music songs for patients using a variety of instruments including piano, cello, viola, violin, oboe, flute, and saxophone. Non-identifiable data was collected from patients, clinical nurses, and musicians using Research Electronic Data Capture (REDCap) in several descriptive studies. Responses to five open ended questions assessed perceptions of the therapeutic music.  The qualitative data was analyzed using NVivo, a qualitative data analysis computer software, to sort into themes. 
Results: Majority (92% ) of patients indicated that music was a significant part of their life and 90% indicated that they enjoyed the experience and would participate in the future. Clinical nursing staff and musicians highlighted the benefits of having live music for patients to provide a momentary disruption to the busy ICU environment. Major themes reflected the calming and relaxation effects of music, and the benefits of having live music played by musicians in the ICU.
Conclusions: The results suggest that therapeutic music is beneficial in helping to promote a healing environment in the ICU.  Additional ongoing research is exploring the impact of different music genres and the ideal exposure “dose” of therapeutic music, as well as the potential to impact patient outcomes including the development of delirium in the ICU.
References:
Bruder AL, Gururaja A, Narayani N, Kleinpell R, Schlesinger JJ. (2024) Patients' Perceptions of Virtual Live Music in the Intensive Care Unit. American Journal of Critical Care. 1;33(1):54-59. doi: 10.4037/ajcc2024140
Schlesinger JJ, Pearson M, O'Briant D, Bose J, Yang ST, Li J, Rice T, Kleinpel R. (2022) Implementing and Evaluating a Pilot Therapeutic Music Program in the Intensive Care Unit. International Journal of Critical Care;16:2. doi.org/10.29173/ijcc44
Immeasurable Impact of a Community of Practice
Authors: Williams Ged , Vollman Kathleen
Published: January 2025

No Abstract
Reading Galvanometers
Authors: Weidenhammer Erich , Fisher Victoria , Yeang Chen-Pang , Spurr Ava , Finnigan Patrick
Published: January 2025

The methodology of experimental reenactment has typically been used by historians to better understand landmark experiments. In this paper, we apply this approach to the galvanometer, an instrument so fundamental to the study of electricity that we may consider it infrastructure underlying the teaching of physics and engineering through the 19th century and well into the 20th centuries. We study a selection of galvanometers from the University of Toronto Scientific Instruments Collection, using them to explore their institutional context. Finally, we operate a representative galvanometer to explore several of the teaching experiments undertaken by engineering and physics students of the late 19th and early 20th centuries.
No Contest Pleas as a Response to False Guilty Pleas
Authors: Sherrin Christopher
Published: January 2025

False guilty pleas are a major source of wrongful convictions. They are also probably inevitable; innocent accused have powerful reasons for resolving their cases short of trial. Given this, it might be wise to add the plea of no contest to the Canadian criminal justice system. A no contest plea could offer advantages for innocent accused, including the opportunity to obtain a reduced sentence without having to publicly (but falsely) admit guilt. It could also bring benefits to the system itself. It could come with some social costs, but those costs might not outweigh the benefits. This paper seeks to encourage discussion of the idea of a contest plea by analyzing its pros and cons.
Wrongful Convictions and Prosecutions in Latin America
Authors: Beltran Roman Victor , Duce Mauricio
Published: January 2025

Drawing on a systematic literature review, this paper examines the scholarly discourse surrounding wrongful convictions and prosecutions in Latin America, spanning from 2010 to July 2023, across the WoS, Scopus, and SciELO databases, identifying a set of 50 publications. From a quantitative perspective, the paper inquiries into aspects such as publication year, countries covered, characteristics of the scientific community involved, and the topics addressed. Then, the paper briefly delves into a qualitative analysis of the publications’ content, distinguishing among those that address general aspects, factors contributing to wrongful convictions and prosecutions, correction mechanisms, and compensation mechanisms for wrongful convictions and prosecutions. Although with limitations, the findings provide an overview of research in this area in Latin America, showing that, although scholarship is still scarce compared with other latitudes, the topic has begun to attract interest in recent years in the region.
What's in a Name? The Impact of Labels on Attitudes Toward Exonerees
Authors: Hamilton Karli , Kukucka Jeff , Allen Erik , Clow Kimberley
Published: January 2025

As exonerations have increased, so too has research into exonerees’ post-release challenges, including stigma, discrimination, mental illness, and inadequate support. In so doing, researchers and advocates have described this population in varied ways, which may elicit differing attitudes. To explore that possibility, 188 citizens read a tweet in which we varied the label ascribed to a newly released prisoner (i.e., wrongly convicted, exonerated, innocent, or control), then reported their attitudes. Contrary to expectation, different labels did not produce different judgements of the individual’s character, criminality, or deservingness of support, which were consistently significantly more favourable for exonerees (regardless of label) than other formerly incarcerated people (control). Troubling, however, was that the terms wrongly convicted, exonerated, and innocent still led to some concerns that the individual was somehow involved in—or had committed—the crime for which he was erroneously convicted, that he may have committed other crimes in the past, and that he might commit crimes in the future.  Implications are discussed in terms of stigma theory, growing media attention to wrongful convictions, and the disconnect between public and government support for post-release services.
Acne Severity Classification Study Using Convolutional Neural Network Algorithm with MobileNetV2 Architecture
Authors: Ramadhani Faadiyah , Rahardiantoro Septian , Masjkur Mohammad
Published: January 2025

Data classification is a key technique in machine learning that maps patterns and features of input data into a target class. Significant developments in data classification occur in deep learning with neural networks and Convolutional Neural Networks (CNN) that are able to extract image features automatically. CNN can classify the level of a condition based on image data, one of which is the severity of acne. Acne (acne vulgaris) is a common skin disease with varying severity. This study aims to apply the CNN MobileNetV2 model to classify acne severity based on acne input images. The data consists of 1457 acne images at 4 severity levels divided into 80% training data and 20% test data. MobileNetV2 was used as a feature extractor through transfer learning. Fine-tuning and classification were performed using fully connected layers with ReLU and softmax activation functions. The model was evaluated with a confusion matrix and classification report. The model with a combination of hyperparameter batch size 16 and a learning rate of 0.00001 was the best model that achieved 87.29% accuracy with 89% precision, 84% recall, and 86% F1 score for classifying acne severity.
Multi-Objective Optimization by Ratio Analysis (MOORA) Method for Decision Support System in Selecting the Best Electric Car
Authors: Humaira Zakiyah , Ariandi M. Irfan , Qur’ania Arie , Puja Negara Teguh
Published: January 2025

Implementasi metode Multi-Objective Optimization by Ratio Analysis (MOORA) telah berhasil diterapkan untuk memilih mobil listrik terbaik. Hasil penelitian menunjukkan bahwa implementasi Metode MOORA berhasil merangking untuk 10 jenis mobil listrik dengan 8 jenis kriteria, yaitu: kapasitas baterai, kecepatan pengisian baterai, fitur kenyamanan, fitur keselamatan, jarak tempuh, kecepatan maksimum, harga, dan tenaga. Penerapan algoritma Moora didasarkan pada 4 tahapan, yaitu: penentuan nilai kriteria, penyusunan matriks keputusan, normalisasi dan optimasi atribut, dan penentuan rangking. Hasil penerapan metode MOORA merangking 10 jenis mobil listrik dengan urutan: Toyota BZ 4X, Hyundai ionic 5 2022, Cherry omodo E5 2024, Wuling cloud EV, Vinvost VF5, Nissan leaf 2021, Kia EV5 2023, BYD Dolphin, Wuling binguo EV, Wuling air EV 2022. Ketika terjadi penambahan dan pengurangan kriteria terjadi perubahan perangkingan. Hasil perangkingan mobil listrik terbaik ditampilkan dalam website dengan pemrograman Javascript dan PHP yang memuat tampilan halaman dashboard, halaman kriteria, halaman data, dan halaman perangkingan. Perhitungan pada sistem website telah divalidasi dengan aplikasi Excell menghasilkan akurasi 100%.
Energy Sector Stock Price Forecasting with Time Series Clustering Approach
Authors: Linda Sakinah  , Rahma Anisa  , I Made Sumertajaya
Published: January 2025

Stock investment promises higher returns but carries high risks because unpredictable price fluctuations. Energy sector shows potential due to its highest sectoral index growth in 2022. However, this doesn’t indicate that stock price increases occur evenly among all issuers. Therefore, it’s necessary to analyze clustering of issuers based on similarity of their stock price movements and used for forecasting stock prices at cluster level. This study aims to evaluate performance of clustering energy sector issuers using autocorrelation-based distance and dynamic time warping(DTW), and to forecast stock prices at cluster level. The data used consists weekly closing stock prices. The clustering used hierarchical average linkage method. Stock price forecast for each cluster used ARIMA model and its performance was evaluated using rolling-cross validation. The results showed that DTW distance had the best clustering performance. Energy sector issuers were grouped into four clusters with strong cluster category, indicated by silhouette coefficient >0.71. ARIMA models for each cluster produced MAPE values between 10-20%, categorizing them as good forecasting models. Clusters A and D were recommended for investors because have highest potential for capital gain based on forecasted stock prices. That clusters also consisted of companies with strong fundamentals and dividend policies.
Implementation of Fuzzy C-Means Algorithm for Clustering Provinces in Indonesia Based on Micro and Small Industry Ratio in Village Areas
Authors: Rahmanesta Frandito , Martha Zamahsary , Vionanda Dodi , Zilrahmi Zilrahmi
Published: January 2025

Post-economic crisis, the micro and small industries contribute the most labor compared to other industries. Regional development sourced from small micro industries is a strategic force in developing a country because the development of small micro industries leads to realizing equitable welfare to reduce income inequality. Development in village areas is an important factor for regional development, reducing inequality between regions, and alleviating poverty. However, based on the 2018 PODES survey, there are regional imbalances in Indonesia in the small micro industry which is centralized on Java Island. Therefore, clustering and characteristics of the province were carried out based on the PODES survey of the small micro industry sector. This research uses the Fuzzy C-Means algorithm to cluster 34 provinces in Indonesia based on the ratio of small micro industries in village areas in 2021, to see how the development of small micro industries in village areas in each province in Indonesia. Fuzzy C-Means is one of the data clustering techniques that uses a fuzzy clustering model, where cluster formation is based on a membership degree value that varies between 0 and 1. The Fuzzy C-Means algorithm generates 4 clusters, cluster 1 and 2 represents provinces with high and very high micro and small industry development in village areas and cluster 3 and 4 represents provinces with medium and low micro and small industry development in village areas. The Fuzzy C-Means algorithm produces a good cluster structure with a silhouette coefficient value of 0,6406.
Comparison of K-Means and K-Medoids in Clustering Regency/City in West Sumatra Province Based on Environmental Indicators
Authors: Robiati Silfi , Fitria Dina , Vionanda Dodi , Sulistiowati Dwi
Published: January 2025

The Environmental Quality Index is an index that describes the condition of environmental management results nationally, and generalises from all regencies/cities and provinces in Indonesia. Although the Environmental Quality Index of West Sumatra Province has increased, there are still regencies/cities in West Sumatra Province have decreasing Environmental Quality Index. Therefore, it is necessary to conduct further analysis, one of which is to form a group of regencies/cities into a group according to their similarities or characteristics. This study aims to compare the K-Means and K-Medoids methods in grouping regencies/cities in West Sumatra Province based on environmental quality indicators in 2023. The data used in this research is secondary data, which is orginally the publication of Central Bureau of Statistics namely Sumatera Barat Dalam Angka in 2024. The research compares the K-Means cluster method and the K-Medoids cluster method. It concludes K-Means better than K-Medoids methods based on DB index with three clusters. First cluster has 12 regencies/cities with a high average air quality index, the second cluster has 6 regencies/cities that have small amounts of waste, and the third cluster has 1 city with a high average water quality index and land quality index, but a large amount of waste.
 
Keywords: Cluster, Comparison, Environmental, K-Means, K-Medoids
Sentiment Classification on the 2024 Indonesian Presidential Candidate Dataset Using Deep Learning Approaches
Authors: Suhaeni Cici , Wijayanto Hari , Kurnia Anang
Published: January 2025

This study aims to compare the performance of three deep learning models (LSTM, BiLSTM, and GRU) in the task of sentiment classification for the 2024 Indonesian Presidential Candidate dataset, focusing specifically on the case of Prabowo Subianto. The dataset comprises social media X posts sourced from kaggle, and the analysis investigates the effectiveness of different variants of recurrent neural network architectures in identifying public sentiment. The models were evaluated on accuracy and F1 score. The results demonstrate that BiLSTM outperformed both LSTM and GRU models in all metrics, achieving a testing accuracy of 80.70% and an F1 score of 86.86%, compared to LSTM and GRU which both achieved a testing accuracy of 72.56% and an F1 score of approximately 84%. The higher performance of BiLSTM is attributed to its ability to capture bidirectional context within the text, thereby understanding complex sentiment patterns more effectively. LSTM and GRU models displayed similar performance, therefore BiLSTM is the best model for this dataset. These results indicate that BiLSTM is especially well-suited for analyzing public sentiment towards political figures like Prabowo Subianto, offering significant insights into public discussions surrounding the 2024 Indonesian Presidential Election. This study recommends exploring transformer-based models like BERT or GPT variants to enhance sentiment classification accuracy in this domain.
Bioassay the Composition of the Organic Pot as a Container Media for Balsa (Ocrhoma bicolor Rowlee) Growth in Nursery
Authors: Al Muzahiq Hizbullah , Budi Sri Wilarso , Wulandari Arum Sekar
Published: January 2025

Forestry plant seedling production uses non-eco-friendly polybags. Organic pots are a solution that can be applied. This research aimed to analyze the composition and size of raw materials in organic pots for balsa growth and to examine the composition of raw materials in organic pots appropriate for balsa growth. This study used a factorial complete randomized design (CRD). There are two factors: the organic pot composition factor (A) and the mesh size factor (M). The observed parameters included the C/N ratio of organic pots, height, diameter, biomass, and plant chlorophyll content. The results showed that the highest percentage decrease in the C/N ratio was found in the A3M2 treatment. The highest average value of balsa plant growth was found in the A3M2 treatment (15% newspaper, 80% goat manure, 5% cocopeat, and ten mesh material size). The highest chlorophyll content was found in A3M1 treatments (15% newspaper, 80% goat manure, 5%cocopeat, five mesh material size). Organic pots with low C/N ratio values had higher average increases in height and diameter of plants compared to organic pots with high C/N ratio values. The optimal composition of the organic pot in this study was the A3M2 treatment.
Performance Comparison of Waste Management Approach in West Java through Masaro and Waste-to-Energy (WtE) Power Plant Technologies
Authors: Abidin A. Zainal , Steven Soen , Silitonga Andreas B. A. , Christian Axel A. , Suyadi Malikul M. A. , Soekotjo Ernie S. A. , Yemensia Elsye V. , Matin Alex , Putra Ridwan P.
Published: January 2025

Waste is often considered as something useless and valueless. However, as the world enters a new industrial era, there is a growing awareness that waste has a high economic value. With proper processing, the waste can be recycled and even used as a feedstock for power generators. With a waste production reaching 24,000 tons per day in West Java, waste becomes a sustainable raw material. There are several methods for processing waste, such as Zero Waste Management Technology (Masaro) and Waste-to-Energy Power Plant (WtE). This study aims to compare the performance of Masaro and WtE technologies from their potential and economic impact. Both methods certainly have their advantages and disadvantages in terms of waste reduction capacities, products obtained, and financial benefits. This study reveals that Masaro technology can reduce 100% waste, whereas WtE can only reduce up to 70–97%. Subsequently, Masaro technology offers more diverse products rather than WtE (6 products vs. 3 products). Moreover, the gross profit margin (GPM) shows that Masaro can reach 99.27% while WtE is still in the range of 12.23–25.30%. It can be concluded that Masaro has quite higher potential and economic benefits compared to WtE.
Nesting Site Preference of Tarsius fuscus in Bantimurung Bulusaraung National Park, South Sulawesi
Authors: Meo Lorenzo Elton , Meylia Safira Arda , Rahman Reja , Majid Ranti Gasela , Amin Salwa Nimatul Maula , Gibran Muhammad Kahlil , Ali Muhammad Ridwan , Mustari Abdul Haris , Laijanan Theresia avilla
Published: January 2025

Tarsius fuscus is one of the smallest primates in the world endemic to South Sulawesi. T. fuscus as a wildlife is thought to tend to choose nests in places with certain criteria. Nests have an important role in wildlife habitats related to anti-predator, sleeping, and reproductive functions. Research on T. fuscus nesting preferences is important to do with the aim of analyzing T. fuscus nesting preferences and the factors that influence them. This research was conducted at the Mallawa Resort, Bantimurung Bulusaraung National Park, South Sulawesi from July to August 2021. The method used was direct observation of T. fuscus nesting points. Biotic and abiotic data are recorded at each of these points either by direct measurement or with the help of GIS. T. fuscus nesting preference was determined by PCA calculation and Neu index. There are 7 parameters that influence the preferences of T. fuscus nesting sites, namely land cover, nest substrate, the height of the nest from ground level, distance from settlements, slope, elevation, and distance from rivers.
Persepsi Mahasiswa terhadap Pemanfaatan Teknologi Artificial Intelligence (AI) dalam Memecahkan Masalah Matematika dan Membuat Karya Ilmiah
Authors: Tyaningsih Ratna Yulis , Nourma Pramestie Wulandari  , Dita Oktavihari
Published: January 2025

This study aims to analyze students' perceptions of the use of Artificial Intelligence (AI) technology in solving mathematical problems and creating scientific papers. The study uses a descriptive quantitative method with data collection through questionnaires and semi-structured interviews. The subjects of the study consist of 58 active students from the University of Mataram who have experience using AI technology in completing their coursework assignments. The results of this study show that: 1) the majority of students (89.6%) feel that AI technology is easy to use, 2) 75,9% have confidence in the accuracy of this technology, 3) 94,9% experience increased efficiency in completing coursework assignments, and 4) based on interviews, concerns were found regarding the potential dependency on AI (29.3%) and ethical issues in its use (24.1%). This study emphasizes that AI can be an effective tool in education if used wisely. Therefore, policies are needed to support the ethical and responsible use of AI to ensure that students continue to develop critical thinking skills.
Hubungan Number Sense dan Kemampuan Pemecahan Masalah Matematika Mahasiswa Pendidikan Matematika
Authors: Wulandari Nourma Pramestie , Junaidi Junaidi , Novitasari Dwi , Triutami Tabita Wahyu
Published: January 2025

This study aims to analyze the relationship between number sense and mathematical problem-solving abilities among mathematics education students. Number sense refers to an individual's ability to understand basic mathematical concepts intuitively, while problem-solving ability involves applying mathematical knowledge to solve complex problems. This research employs a quantitative approach with a correlational design. Data were collected through number sense tests and mathematical problem-solving tests administered to Mathematics Education students at a university. The results indicate a significant positive correlation between number sense and mathematical problem-solving ability. This suggests that students with good number sense tend to be more effective in solving mathematical problems. This research is expected to contribute to the development of mathematics education curricula by emphasizing number sense as a foundation for enhancing students' problem-solving skills.
Teaching Strategies of English Teacher with Tour Guide Experiences: A Case Study in Sembalun High Schools
Authors: Agina Meri , Amin Muhammad , Apgrianto Kurniawan
Published: January 2025

This study intended to describe the strategies of English teachers with tour guide experiences used in teaching English and the effects of teachers’ experiences as a tour guide on their teaching. The research used a qualitative research method which implemented a case study approach. The procedures of data collection were observation and interview. Technique of data analysis were data condensation, data display, and verification and conclusion. The result of the data showed that there were 8 (eight) cognitive strategies and 3 (three) metacognitive strategies that teachers used in their teaching. The cognitive strategies include repetition, resourcing, translation, note-taking, elaboration, imagery, and inferencing whereas, whilst, the metacognitive strategies encompass setting learning objectives, creating study plans, and monitoring comprehension and production. Moreover, the effects of English teachers’ experiences as tour guides on their teaching include the teachers' concerns to help students be familiar with several accents and help them understand variations in pronunciation and intonation, then minimizing confusion when students are faced with various accents. Another effect is the process of running the class in which the teachers occasionally involve tourists in classroom activities. Because of this, students can speak directly with them, and improve their English speaking, listening, and understanding skills with authentic accents.
Comparative Analysis on the Translation of the Academic Handbook of University of Mataram Using ChatGPT and Professional Translation
Authors: Rilasti Fifi , Junaidi Ahmad , Putera Lalu Jaswadi
Published: January 2025

Translation can be interpreted as the concept of transferring meaning from one language to another according to the meaning the author wants to convey. This study aims to find out the aspect of the differences between translation using ChatGPT and Professional in the Academic Handbook of University of Mataram and to determine the more accurate translation between ChatGPT and Professional translation. This study used a qualitative method. The researcher applied a comparative analysis technique of the results of the ChatGPT and Professional translations of the Academic Handbook of University of Mataram. The results of this research show that of the three translation techniques applied, borrowing techniques were used 147 times, adaptation techniques were used 90 times and literal translation techniques were used 86 times. After conducting a comparative analysis, the researcher then tested the level of accuracy of the analysis data results using House's theory (1997). Then, the results of the accuracy level data test show that the translation by Professionals is more accurate than the ChatGPT translation results.
Students’ Learning Strategies to Acquire Vocabulary Using TikTok by 8th Grade of SMPN 1 Mataram
Authors: Andriana Devina Rizki Ayu , Muhaimi Lalu , Lail Husnul
Published: January 2025

This study aims to identify the learning strategies used by students in acquiring vocabulary through TikTok, the hurdles that they face, and how they overcome them utilizing the Oxford’s (1990) theory. This study is designed to use a qualitative descriptive method. The majority of the data in this study are collected through focus group discussions (FGDs), questionnaires, interviews, and documentation. The subjects of this study consist 66 of eighth-grade students at SMPN 1 Mataram who use TikTok for vocabulary acquisition. The analysis reveals that the overall use of learning strategies in acquiring vocabulary through TikTok is at a medium level, with an average score of 2.73. The most frequently used strategy is the affective strategy, with an average score of 3.06. Meanwhile the least utilized strategy is the social strategy, with an average score of 2.04. Other strategies include memory (3.05), cognitive (2.87), compensation (2.87), and metacognitive strategies (2.52). Furthermore, the findings indicate that the most common hurdles faced by students include difficulties in understanding vocabulary, reported by 30% of the students, followed by a lack of detailed explanations (20%), variability in content quality (18%), and inaccurate subtitles (14%). Students primarily overcome these hurdles by using additional tools (27%), followed by asking experts (18%), repeating videos (15%), and seeking other videos (11%). The implications of these findings suggest that enhancing students’ awareness of effective learning strategies and improving content quality could significantly benefit vocabulary acquisition through digital platforms.
English Teachers’ Perception of Project-Based Learning in Teaching English (A Case Study at SMPN 1 Jonggat)
Authors: Rampes Sovia Lavender , Arafiq  , Wardana Lalu Ali
Published: January 2025

In the era of global competition, enhancing English language skills is critical, and project-based learning (PjBL) presents a potential model to improve student engagement and language competence. This qualitative case study, conducted at SMPN 1 Jonggat in Central Lombok, Nusa Tenggara Barat, examines English teachers' perceptions of PjBL, focusing on its effectiveness, challenges, and implementation strategies. Using a purposive sample of three English teachers who employ PjBL in their classrooms, data were collected through semi-structured interviews and close-ended questionnaires to capture detailed insights into teachers' attitudes and experiences with PjBL. Semi-structured interviews allowed for in-depth exploration of teachers' subjective experiences, while questionnaires provided structured data on specific aspects of PjBL’s implementation. Data were analyzed following Miles and Huberman's three-step process—data reduction, data display, and conclusion drawing/verification—to systematically interpret findings. This study contributes valuable insights for educators seeking to enhance English language teaching through PjBL, offering a framework for understanding both the benefits and challenges of PjBL from teachers’ perspectives in a secondary school context. Findings are expected to support improved teaching strategies and contribute to more effective English education practices.
Analysis of Students Difficulty in Essay Writing Course
Authors: Aulia Lailani Sarafina , Rizal David
Published: January 2025

This study investigates the difficulties faced by university students in writing essays, particularly in the context of English education in Indonesia. The research identified key challenges such as limited vocabulary, anxiety, time constraints, and difficulty in organizing ideas. Through a quantitative approach that included an online distributed survey, this study collected data on students' experiences and perceptions of their writing skills. The results showed that many students experienced difficulties in various aspects of writing, including grammar and coherence, which often led to a lack of confidence and motivation. The findings highlight the need for better teaching strategies to improve students' writing skills. Recommendations include providing intensive guidance during the writing process, implementing project-based learning, and utilizing technology to support learning. In addition, fostering a supportive environment where students can freely explore topics of interest is essential to motivate them to write effectively. Overall, this study underscores the importance of overcoming skill-based and psychological barriers to improve academic writing proficiency among students in the digital age.
Cultural Diversity and Language Education: Lessons from the European Migrant Crisis
Authors: Mukti Muhammad Abdee Praja , Maulana Muhamad Trian , Kamaluddin Mohamad Ihsan , Wardoyo Cipto
Published: January 2025

This study investigates the European migration crisis, focusing on its root causes, cultural conflicts, and social integration challenges. The research highlights how armed conflict, political instability, economic disparities, and climate change drive mass migration and create significant social and economic pressures on host countries. Using a systematic literature review, this paper identifies the main barriers to integration, including language differences, discrimination, and unequal access to resources. The findings emphasize the importance of comprehensive policies that promote social cohesion, inclusive integration programs, and international cooperation to address migration flows and humanitarian concerns effectively. This research contributes to the ongoing discussion on sustainable migration policies by providing insights into both immediate and long-term strategies for managing migration challenges.
Development of a Physics E-Module Integrated Local Wisdon and Problem Based Learning (PBL) to Increase Student Preparedness
Authors: Sahida Desrianti , Huriati Nining
Published: January 2025

The goal of this research is to create e-module teaching materials based on PBL integrated with local wisdom in Physics subjects that are reliable, useful, and efficient. Research and development is the study's technique. The 4-D model, which consists of definition, design, development, and distribution, is the development model that is employed. An e-module with valid criteria (0.86) and practical criteria (94%) was achieved during the design stage, along with an early draft of the module that included the development stage and was effective for cognitive aspects (76%), effective in increasing preparedness (79%) was in the very ready category, the character category became a habit (86%), and moderate skills (87%). At the dissemination stage, it was found to be effective for the cognitive aspect (76.9%), effective in increasing preparedness (78.4%) in the very prepared category, character becomes a habit category (84%), and moderate skills (81.9%). It can be concluded that the developed e-module can improve students' preparedness by applying the PBL model integrated with local wisdom in accordance with the provisions of the Kurikulum Merdeka.
Developing Multi-Frequency Bioelectrical Impedance Analysis for Fat-Free Mass Estimation in Early Childhood
Authors: Wismaya Herenda Sela , Sugianto Wahyu , Hanifah Rida Dwi
Published: January 2025

This study aims to develop and evaluate a Multi-Frequency Bioelectrical Impedance Analysis (MFBIA) system for estimating body composition, specifically Fat-Free Mass (FFM) and Body Fat Percentage (BF%). The primary objective was to assess the accuracy and reliability of the MFBIA system by comparing its measurements with those obtained from a commercially validated Smart Body Fat analyzer and traditional anthropometric methods. The research involved regression analysis to examine the correlation between FFM and BF% measurements from MFBIA and anthropometric data, including height and weight. Additionally, impedance measurements were taken at multiple frequencies (25 kHz, 50 kHz, and 100 kHz) to determine the system's ability to estimate body composition parameters across various conditions. The results showed a strong correlation between the FFM and BF% values ​​derived from MFBIA and those obtained using the Smart Body Fat analyzer. The regression analysis indicated high linearity, with R² values ​​ranging from 0.9439 to 0.9692, signifying the robustness of the system in predicting body composition. Furthermore, the MFBIA system demonstrated a high degree of consistency and accuracy in measuring FFM and BF%, with minimal deviations from the reference device. This research presents a multi-frequency BIA device designed specifically to measure fat-free mass (FFM), an important indicator for assessing the nutritional status of children. The results of this research offer a practical, affordable, and non-invasive tool for healthcare providers to assess body composition in children. The MFBIA system has the ability to track nutritional status, supporting targeted interventions to promote child health and prevent stunting.
Analysis of Kidney Tissue Keting Mystus gulio (Hamilton, 1822) in Gembong and Rejoso River, Pasuruan, Indonesia
Authors: Lestariaji Chandika , Herawati Endang Yuli , Arfiati Diana , Djaduk Saddam Langkung , Ristianadewi Priska , Anjasmara Aang Setyawan , Valina Rahmi
Published: January 2025

Mystus gulio is a local fish that can open up opportunities for the community. Pollution causes water quality to decrease. Fish are an important indicator in the aquatic environment, Histological analysis can be said to have a function as a natural biological sign to determine the health condition of fish which can be seen from changes in tissue structure in organs exposed to pollutants. Organs that’s vulnerable to water pollution is kidneys.  Kidney tissue is susceptible to damage because kidneys function as a means of filtration and excretion, The method used in this research is descriptive method. Fish were caught from river than dissected to remove the kidneys for histopathological analysis using the HE method, analyzed using the scoring method. The results obtained in both rivers were that fish kidneys caught in the Gembong River were categorized as moderately damaged, while fish kidneys caught from the Rejoso River were categorized as lightly damaged. This is in line with the results of the heavy metal lead from both rivers. Where the yield of lead in fish kidneys caught from the Gembong is on average higher than the yield from fish kidneys caught from the Rejoso.
Implementation of Project Based Learning based on Local Wisdom in Port Numbay Papua and its Impact on Students' Critical Thinking Skills
Authors: Risamasu Putu Victoria M. , Pieter Jan
Published: January 2025

The education sector bears a significant duty to nurture a generation prepared for the period of Society 5.0; thus, systematic initiatives to foster analytical, critical, and creative thinking are essential. We refer to this cognitive approach as higher-order thinking Skills (HOTS). This research aims to develop science instructional materials using a project-based learning approach, rooted in the local wisdom of Port Numbay, and assess its influence on students' critical thinking skills concerning Earth's structure and surface content. We conducted Research and Development (R&D) on the 4D model, transforming it into a 3D format without a dissemination phase. The research sample comprised seventh-grade pupils from public junior high schools in Jayapura City. Five validators approved the developed physics teaching materials. We utilized a quasi-experiment with a randomized pretest-posttest control group design to assess the impact of the teaching materials. The research findings indicated that the created teaching materials positively influenced student outcomes, revealing significant disparities in critical thinking skills between students utilizing the developed materials and those employing traditional teaching methods. The designed instructional materials facilitate student learning transitions and enhance critical thinking skills due to their inherent ability to stimulate creativity, originality, and independence in scientific learning.