Jurnal Politeknik Negeri Batam (PoliBatam)
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Analysis of Goods Tracking Website Quality on User Satisfaction Using the Webqual 4.0 Method: (Case Study Of The Cekresi.com Website)
No full textThe research aims to analyze the influence of both partially and simultaneously between usability quality, information quality and service interaction on user satisfaction with the Cekresi.com website. Data for this research was acquired from the results of the answers to questionnaires distributed to respondents. The analysis used Webqual 4.0, a widely accepted method for evaluating website quality and user satisfaction. Based on the study of the multiple linear regression analysis models used in this research, it is concluded that the quality of usability and the quality of service interaction are essential factors in improving the performance of the Cekresi.com website and have a positive and significant effect on user satisfaction Cekresi.com website. However, although information quality has a positive effect, it does not significantly impact the Cekresi.com website
The Influence of Media Exposure, Company Size, and Profitability on Carbon Emission Disclosure in Basic Materials Companies in Indonesia
No full textThe acceleration of global warming caused by carbon emissions continues to be a pressing worldwide concern. Disclosing carbon emissions is a measure companies can adopt to tackle environmental and social issues. In Indonesia, the extent of carbon emission disclosure remains comparatively modest, as it is conducted primarily on an initiative basis. This research primarily aims to ascertain the partial impact of media exposure, company size, and profitability on carbon emission disclosure. The research sample was obtained through purposive sampling, comprising 63 samples from basic materials businesses listed on the Indonesia Stock Exchange for the period of 2021-2023. The multi-linear regression model of analysis used in this research was performed in SPSS 20 using the SPSS 20 measurement tool. The research indicates that media exposure, organizational scale, and profitability influence carbon emission disclosure.The acceleration of global warming caused by carbon emissions continues to be a pressing worldwide concern. Disclosing carbon emissions is a measure companies can adopt to tackle environmental and social issues. In Indonesia, the extent of carbon emission disclosure remains comparatively modest, as it is conducted primarily on an initiative basis. This research primarily aims to ascertain the partial impact of media exposure, company size, and profitability on carbon emission disclosure. The research sample was obtained through purposive sampling, comprising 63 samples from basic materials businesses listed on the Indonesia Stock Exchange for the period of 2021-2023. The multi-linear regression model of analysis used in this research was performed in SPSS 20 using the SPSS 20 measurement tool. The research indicates that media exposure, organizational scale, and profitability influence carbon emission disclosure
Pengaruh Jenis Elektroda RD dan LB E6010 Terhadap Laju Korosi Sambungan Las SMAW Pada Baja Ringan Dalam Media Air Laut
No full textMild steel is widely used in construction because it is lightweight and economical, but it is susceptible to corrosion, especially in marine environments with high chloride ion content. Shielded Metal Arc Welding (SMAW) welded joints are vulnerable due to microstructural changes and weld defects that accelerate damage. This study aims to analyse the effect of RD and LB E6010 electrodes on the corrosion rate of mild steel welded joints in seawater. The research method involved welding 1.5 mm galvanised steel using 70–90 amps of current with the stringer bead technique. The samples were then immersed for 21 days in seawater from Pagatan Beach, South Kalimantan, and tested using the weight loss method. The test results showed that the RD electrode had a corrosion rate of 0.83 mm/year, which was lower than that of the LB electrode at 1.11 mm/year. This difference was influenced by weld defects, where the LB electrode produced more porosity, slag inclusion, and pitting corrosion. Based on the ASTM G46 classification, both values fall into the moderate category. It can be concluded that the use of RD electrodes is highly recommended for light steel joining applications in marine environments, given their superior corrosion resistance.Baja ringan banyak digunakan dalam konstruksi karena ringan dan ekonomis, namun rentan terhadap korosi terutama di lingkungan laut dengan kandungan ion klorida tinggi. Sambungan las hasil Shielded Metal Arc Welding (SMAW) menjadi titik rawan karena perubahan mikrostruktur dan cacat las yang mempercepat kerusakan. Penelitian ini bertujuan menganalisis pengaruh elektroda RD dan LB E6010 terhadap laju korosi sambungan las baja ringan dalam media air laut. Metode penelitian dilakukan melalui proses pengelasan pada baja galvanis 1,5 mm menggunakan arus 70–90 ampere dengan teknik stringer bead. Sampel kemudian direndam selama 21 hari dalam air laut Pantai Pagatan, Kalimantan Selatan, dan diuji menggunakan metode kehilangan berat. Hasil pengujian menunjukkan elektroda RD memiliki laju korosi 0,83 mm/tahun, lebih rendah dibandingkan LB sebesar 1,11 mm/tahun. Perbedaan ini dipengaruhi oleh cacat las, di mana elektroda LB menghasilkan porosity, slag inclusion, dan pitting corrosion lebih banyak. Berdasarkan klasifikasi ASTM G46, kedua nilai termasuk kategori sedang. Analisis statistik One-Sample T-Test menunjukkan perbedaan laju korosi belum signifikan pada taraf 95% akibat keterbatasan jumlah sampel. Kesimpulannya, elektroda RD lebih direkomendasikan untuk meningkatkan ketahanan korosi sambungan baja ringan di lingkungan laut.
 
Analisa penggunaan ESP32-Cam dan Platform Edge Impulse untuk Proses Deteksi Sepatu Safety Pada Lingkungan Industri
No full textKesehatan dan keselamatan kerja merupakan faktor utama yang harus dimiliki setiap orang. Salah satu peralatan kerja yang harus dipakai oleh pekerja adalah sepatu safety. Namun, beberapa pekerja sering lupa untuk memakai sepatu safety sehingga perlu dilakukan proses deteksi pada pemakaian sepatu pekerja. Tujuan dari penelitian ini adalah untuk mengimplementasikan deteksi sepatu safety pada lingkungan industri menggunakan perangkat ESP32-Cam dan platform Edge Impulse. Hasil akurasi yang diperoleh pada setiap pengujian sepatu yaitu pada jarak 30 cm sebesar 94,4%, pada jarak 40 cm sebesar 92,6%, dan pada jarak 50 cm sebesar 0%. Kemudian, tingkat akurasi pengenalan sepatu safety dengan sepatu bukan safety sebesar 95,4%
Analisis Perbandingan Render Engine Cycles & Eevee Pada Blender Melalui Metode Quasi- Monte Carlo Untuk Meningkatkan Rendering Di PT. Labtech Penta International
Get PDFThis research focuses on analyzing the comparison between Cycles and Eevee render engines within the open-source software Blender 3D. The test results will assist PT. Labtech Penta International and users of three-dimensional applications in selecting the appropriate render engine for 3D model projects with still image outputs. The study aims to find configurations between Cycles and Eevee render engines or investigate them using the Quasi-Monte Carlo method, where the values or configurations in the settings of each render engine are tested using multiple samples. In each sample, the values or configurations are randomly adjusted.
The measurement parameters for this test use three variables: rendering speed, size of the rendered file output, and image quality of the render result, taking into account the vertices and texture nodes on the 3D object. The results of this study indicate that Eevee outperforms Cycles in terms of rendering speed, while Cycles and Eevee produce similar file sizes in their render outputs. Regarding image quality, the results show that Cycles is superior to Eevee. The research aims to find a solution for rendering at PT. Labtech Penta International with stable and effective configurations
Analyzing Sentiment of SiCepat Express User Reviews
Get PDFThe development of e-commerce in Indonesia has led to an increase in the number of users of product delivery services to deliver their customers\u27 orders to their destination. SiCepat Ekspres is the number one fastest delivery service in Indonesia, besides JNE and JNT Express. The study aims to evaluate the performance of sentiment analysis methods in identifying and classifying sentiments related to SiCepat Ekspres. Data from Twitter media as many as 10,000 dataset records. The experimental results show that Random Forest with SMOTE is the best method, as it has the highest accuracy (91.10%), followed by improvements in precision, recall, and F-measure. SVM with SMOTE is in second place, with 90.50% accuracy and stable performance in other metrics. Naive Bayes with SMOTE shows improvement, but its performance remains slightly below Random Forest and SVM, with an accuracy of 88.80%.The development of e-commerce in Indonesia has led to an increase in the number of users of product delivery services to deliver their customers\u27 orders to their destination. SiCepat Ekspres is the number one fastest delivery service in Indonesia, besides JNE and JNT Express. The study aims to evaluate the performance of sentiment analysis methods in identifying and classifying sentiments related to SiCepat Ekspres. Data from Twitter media as many as 10,000 dataset records. The experimental results show that Random Forest with SMOTE is the best method, as it has the highest accuracy (91.10%), followed by improvements in precision, recall, and F-measure. SVM with SMOTE is in second place, with 90.50% accuracy and stable performance in other metrics. Naive Bayes with SMOTE shows improvement, but its performance remains slightly below Random Forest and SVM, with an accuracy of 88.80%
Clustering Time Series Forecasting Model for Grouping Provinces in Indonesia Based on Granulated Sugar Prices
Get PDFClustering time series is the process of organizing data into groups based on similarities in specific patterns. This research uses the prices of granulated sugar in each province of Indonesia. According to USDA reports, sugar consumption in Indonesia in 2023 reached 7.9 million tons. On April 26, 2024, the price of granulated sugar peaked in the Papua Mountains at Rp29,320 per kg, while the lowest price was recorded in the Riau Islands at Rp16,460 per kg. The research aims to cluster provinces based on the characteristics of granulated sugar prices and to use forecasting models for each group. Two groups were formed based on the price patterns of granulated sugar over time. The provinces of Papua and West Papua are in group 2, while the other 30 provinces are in group 1. The best model developed using the auto ARIMA method is ARIMA (2, 1, 0), with a MAPE value of 2.36% for cluster 1, and ARIMA (1, 1, 1), with a MAPE value of 2.59% for cluster 2. These values are less than 10%, indicating that the models built using the auto ARIMA method for clusters 1 and 2 are suitable for forecasting.Clustering time series is the process of organizing data into groups based on similarities in specific patterns. This research uses the prices of granulated sugar in each province of Indonesia. According to USDA reports, sugar consumption in Indonesia in 2023 reached 7.9 million tons. On April 26, 2024, the price of granulated sugar peaked in the Papua Mountains at Rp29,320 per kg, while the lowest price was recorded in the Riau Islands at Rp16,460 per kg. The research aims to cluster provinces based on the characteristics of granulated sugar prices and to use forecasting models for each group. Two groups were formed based on the price patterns of granulated sugar over time. The provinces of Papua and West Papua are in group 2, while the other 30 provinces are in group 1. The best model developed using the auto ARIMA method is ARIMA (2, 1, 0), with a MAPE value of 2.36% for cluster 1, and ARIMA (1, 1, 1), with a MAPE value of 2.59% for cluster 2. These values are less than 10%, indicating that the models built using the auto ARIMA method for clusters 1 and 2 are suitable for forecasting
Apriori Algorithm Analysis to Determine Purchasing Patterns at Beleven Farma Pharmacy
Get PDFBeleven Farma Pharmacy is a place that provides medicines and other health products such as supplements, vitamins and also various health tests. As a newly established pharmacy, no innovations have been made to improve sales strategies. Analysis of purchasing patterns can produce information that helps pharmacies in determining product bundling recommendations as well as determining product layout. This research applies the a priori algorithm method and uses rapidminer tools to identify drug purchasing patterns from transaction data at the Beleven Farma pharmacy. The Knowledge discovery in database (KDD) method is used as a reference in the data processing process. Based on tests carried out by the author, the resulting rules are that if you buy hemaviton you will buy vice with 4% support and 91% confidence and if you buy amoxicillin you will buy paracetamol with 4% support and 64% confidence. Thus, the resulting information can be used to support decision making in determining marketing strategies so as to increase sales at pharmacies
Analyzing the Impact of Artificial Intelligence on Student Learning: A Case Study of SMK Tri Arga 2
Get PDFThe use of artificial intelligence (AI) technology in every aspect of life is a solution that provides an important contribution to the continuity of the wheel of life, not to mention in the world of education. In this digital era, AI has become an important partner and tool for students in completing assignments and assisting in carrying out their learning activities, especially in completing assignments given by teachers. The purpose of this study is to analyze the effect of artificial intelligence on learning, especially for students of SMK Tri Arga 2. The formulation of the research problem involves a description of the use of AI in the process of completing assignments, the benefits and challenges experienced by students, and the most dominant AI applications used in completing these assignments. The research method used is a quantitative descriptive method using a questionnaire, Likert Scale, which is created on Google Form and then sent to the Whatsapp Group and student personal chat. Using a random method. 105 students of SMK Tri Arga 2 participated in this study. the results of this study showed that 51.4% stated that they often use AI. Then 52.4% or 55 students answered that they often use AI in completing school assignments. These results certainly provide a new perspective on the role of AI in helping students complete the school assignments they have been given. It is also hoped that the results of this research can help Senior High Schools (SMA) and Vocational High Schools (SMK) in improving the quality of education and learning by integrating AI more effectively in their students\u27 academic processes, improving supervision and regulations regarding the use of AI in completing assignments and making AI a companion tool while still paying attention to the ethics of plagiarism and the growth of students\u27 skill development.The use of artificial intelligence (AI) technology in every aspect of life is a solution that provides an important contribution to the continuity of the wheel of life, not to mention in the world of education. In this digital era, AI has become an important partner and tool for students in completing assignments and assisting in carrying out their learning activities, especially in completing assignments given by teachers. The purpose of this study is to analyze the effect of artificial intelligence on learning, especially for students of SMK Tri Arga 2. The formulation of the research problem involves a description of the use of AI in the process of completing assignments, the benefits and challenges experienced by students, and the most dominant AI applications used in completing these assignments. The research method used is a quantitative descriptive method using a questionnaire, Likert Scale, which is created on Google Form and then sent to the Whatsapp Group and student personal chat. Using a random method. 105 students of SMK Tri Arga 2 participated in this study. the results of this study showed that 51.4% stated that they often use AI. Then 52.4% or 55 students answered that they often use AI in completing school assignments. These results certainly provide a new perspective on the role of AI in helping students complete the school assignments they have been given. It is also hoped that the results of this research can help Senior High Schools (SMA) and Vocational High Schools (SMK) in improving the quality of education and learning by integrating AI more effectively in their students\u27 academic processes, improving supervision and regulations regarding the use of AI in completing assignments and making AI a companion tool while still paying attention to the ethics of plagiarism and the growth of students\u27 skill development
Optimization of Inventory Management with QR Code Integration and Sequential Search Algorithm: A Case Study in a Regional Revenue Office
Get PDFInventory management at a government office was previously conducted manually, leading to issues such as data inaccuracies, delays in item searches, and low work efficiency. This study develops a web-based inventory management system integrated with QR Code technology and a sequential search algorithm to address these challenges. The system was developed using the prototyping method, with iterative design based on user feedback until the final version met the office\u27s operational needs. Key features of the system include digital inventory recording, item tracking using QR Codes, and real-time information access through a web-based interface. The system was tested in two stages: simulation and direct implementation in a real-world environment, involving 10 respondents to evaluate effectiveness and usability. The test results showed a 95% improvement in data recording accuracy, a 60% reduction in item search time, and an average user satisfaction score of 77.25 based on the System Usability Scale (SUS). This research successfully improved inventory management efficiency and demonstrated the system’s potential for adoption by other similar organizations, with modular adjustments tailored to their needs