Jurnal Teknik

Architecture Students' Perception of AI in Academic Project Resolution

Ulfaizah Sahril Nurfadhilah — 2024-12-01

This study aims to examine architecture students' perceptions of the role of artificial intelligence (AI) in supporting the completion of academic tasks, ranging from text-based assignments to design processes. Data were collected through an online survey using Google Forms with semi-open and closed-ended questions, involving 289 undergraduate architecture students from six universities in Sulawesi Island. Data analysis was conducted using descriptive statistics and Chi-Square tests with SPSS version 26. The findings indicate that AI is well-received by architecture students, despite their limited understanding of the technology, highlighting the need for enhanced AI training and educational courses in academic institutions. Currently, AI is primarily used for non-design tasks; however, there is significant potential for AI applications in design processes. These tools can enhance students' creativity by facilitating brainstorming and providing inspiration. A balanced implementation of AI is crucial to mitigate potential negative impacts on originality and credibility. This study underscores the importance of developing AI technologies that are more relevant to the needs of architectural education and targeted training to maximize the benefits of AI in both academic and professional contexts.

A Novel Hybrid Model for Disaster Relief: Combining Operational Cost Minimization and Priority-Based Resource Allocation

Miftahol Arifin — 2024-12-01

Humanitarian logistics plays a crucial role in disaster management, yet it faces persistent challenges in ensuring equitable and efficient aid distribution. These challenges include high operational costs, inequitable resource allocation, and limited adaptability to dynamic disaster conditions. Existing models, either cost-based or priority-based, fail to balance these competing demands effectively. This research addresses this gap by developing a hybrid multi-objective optimization model that integrates cost minimization and priority-based resource allocation. The primary objective of this study is to optimize aid distribution in disaster-affected regions, ensuring both efficiency and fairness. The model employs a quantitative research approach, leveraging mathematical programming to simulate disaster scenarios. Key variables include operational costs, delivery times, demand levels, and priority rankings, collected from hypothetical disaster data. The results reveal that the hybrid model significantly outperforms conventional approaches. It achieves up to a 15% reduction in operational costs and a 25% improvement in aid coverage for high-priority regions. Furthermore, it balances resource allocation effectively across regions with varying levels of need. The discussion emphasizes the model's adaptability and scalability, offering practical solutions for disaster relief operations. In conclusion, the hybrid model presents a robust framework for humanitarian logistics, addressing inefficiencies and inequities in aid distribution. This research impacts policy-making and operational planning, paving the way for more effective disaster management strategies.

Analisis Perbandingan VGG-16 dan ResNet50 untuk Klasifikasi Multilabel Gambar Kerbau Toraja: Pendekatan Deep Learning

Tri Anita Resky Ramadhani — 2024-12-01

This study aims to compare the performance of two Convolutional Neural Networks (CNN) models, namely VGG-16 and ResNet50, in the task of multilabel classification of buffalo images. The Dataset used consists of 2009 buffalo images labeled with five categories: human, motorcycle, truck, wild animal, and buffalo. The CNN models were trained using 30 epochs and evaluated using loss, accuracy, Precision, recall, and f1-score metrics. The experimental results show that VGG-16 consistently outperforms ResNet50 by achieving the highest accuracy of 0.95 in the training set and 0.94 in the validation set, and f1-score of 0.94 in the training set and 0.92 in the validation set. These findings indicate that a deeper and more structured CNN architecture, such as VGG-16, provides better results in classifying buffalo images with complex label variations.

Pengembangan Sistem Manajemen Kelas Berbasis Website Sebagai Solusi Pelaporan Pembelajaran Digital

Widi Natasya Lalu — 2024-12-01

The use of information technology in the world of education has made a major contribution to increasing the efficiency, accuracy and transparency of the educational process. The role of the homeroom teacher is very important for student development. The process of reporting assignment data, grades, absence recaps, student report cards to parents, which still rely on conventional reporting, and conveyed via correspondence or WhatsApp messages, is a problem that must be addressed. The aim of this research is to design a website-based classroom management system; Achievement of a classroom management system by testing usability and suitability as well as testing the practicality of a system that is suitable for use. The system development method used in this research is the waterfall method. The respondents of this research are teachers, students and parents. The instrument used in the research is a questionnaire and testing in this research includes functional suitability to determine whether the system is functioning well, usability or suitability to determine whether the system is suitable for use and practicality testing to determine the efficiency of the system. The results of the functional suitability test show that the system is as expected, and based on the results of the system suitability test by the user, results were obtained with a percentage score of 84.66% from 6 teachers, including the very suitable category. Then the results of the practicality test by system user respondents were 92.47% of the results of student responses and 90.53% of the results of parent responses. So the Website-Based Class Management System is suitable for use.

Evaluasi Kualitas Pelayanan Menggunakan SERVQUAL dan FUZZY AHP Untuk Meningkatkan Kepuasan Penumpang di Bandara Djalaludin Gorontalo

Idham Halid Lahay — 2024-12-01

Indonesia, as an archipelagic nation, requires an efficient transportation system to support economic mobility and tourism. Djalaludin Airport in Gorontalo plays a pivotal role in facilitating economic and tourism activities within Gorontalo Province. Airport management, involving operators and service users, aims to deliver high-quality services. However, some service aspects still fall short, particularly in physical facility comfort and process efficiency. This study seeks to identify service attributes that need improvement to enhance overall service quality. A quantitative approach was employed, utilizing SERVQUAL analysis based on five dimensions: tangibles, reliability, responsiveness, assurance, and empathy. Data were collected through questionnaires and analyzed using a gap method to measure discrepancies between passenger expectations and perceptions. Attribute prioritization was conducted using Fuzzy AHP to identify key areas for improvement, followed by a fishbone analysis to uncover root causes of the identified issues. The results indicate a service conformity level of 87.61%, but notable negative gaps remain in key attributes, such as air circulation comfort in waiting areas and baggage claim efficiency. Recommendations include increasing air conditioning capacity and optimizing conveyor systems to expedite baggage handling. Improving these core attributes suggests that enhancing service quality at Djalaludin Airport will boost passenger satisfaction and loyalty while supporting sustainable growth in air transportation and tourism sectors in Gorontalo Province.

Analisis Persepsi Masyarakat Terhadap Implementasi Smart City di Kota Gorontalo

Irwan Wunarlan — 2024-12-01

Over the year population have continued increase and the limited natural resources make city management increasingly complex. The concept of smart cities, which is a major issue in big cities around the world, encourages community participation. The importance of community participation in the development of technology-based public services underlies the purpose of this study to analyze community perceptions regarding the implementation of smart cities in Gorontalo City. This study uses primary data collection methods assisted by distributing questionnaires to respondents in nine sub-districts and 50 villages, as well as data obtained from institutional surveys and related documents. The results of the analysis show that the developed model is able to explain 48.26% of the variation in community perceptions of city services. It was found that positive community perceptions have the potential to increase their involvement in smart city programs, while negative perceptions can be an obstacle to implementation. This study emphasizes the importance of community understanding of the benefits of smart city technology, as well as the need for effective socialization efforts to increase community support for this initiative. The results of the analysis of community perceptions regarding the implementation of smart cities are expected to be used as a reference for local governments in formulating responsive policies to community needs.

Analisis Kelelahan Dan Beban Kerja Menggunakan Subjective Self Rating Test Dan NASA-TLX

Atun Nurmarifah — 2024-12-01

The application of ergonomics in the workplace is one concept that can be done to provide comfort and safety to workers when doing work. This research was conducted on UD workers. Arafat Meubel which is a furniture manufacturing factory. The problem for workers is the number of targets from the company, which causes working time outside the normal working limits and makes workers experience fatigue and excessive workload. This study aims to analyze the level of fatigue and mental workload of workers, and determine the relationship between the two. The methods used are Subjective Self Rating Test to determine the level of fatigue and Nasa-Tlx to determine the level of mental workload, and using the Spearman Rank Test to determine the relationship between fatigue and mental workload. The results obtained from data processing and analysis were that 2 workers experienced high levels of fatigue and 5 workers experienced high levels of mental workload. In addition, there is a relationship between fatigue and mental workload with a correlation coefficient of 0.559, including in the medium relationship category.

Sistem Pakar Menu Sehat Berdasarkan Golongan Darah Menggunakan Metode Certainty Factor

Butsiarah Asikin — 2024-12-01

A healthy menu refers to a list of foods that can provide all the essential nutrients for the body, such as carbohydrates, proteins, fibers, fats, vitamins, and minerals, in balanced proportions. The types of food recommended for consumption must be in accordance with blood type, in order to affect the body's metabolism. The purpose of this study was to develop a healthy menu expert system based on blood type using the certainty factor method. The certainty factor method is used to determine the level of certainty in providing food recommendations that are in accordance with blood type in order to support health. The research approach applied is the waterfall method, which includes several stages, such as needs analysis, system design, coding, testing, and implementation. Based on the research conducted, a healthy menu expert system based on blood type using the certainty factor method was successfully developed. The results of the black box test showed that the alpha testing test obtained an average value of 4.3, which is included in the valid category, while the beta testing test produced an average value of 4.0, which is also valid. After being tested, this expert system had an accuracy of 91.6%, which indicates that the system provides healthy menu recommendations that are appropriate, accurate, and useful.