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Pengaruh Kepemimpinan, Motivasi Kerja, dan Lingkungan Kerja terhadap Kinerja Guru (Studi Kasus di SMK Negeri 2 Depok Sleman Yogyakarta)
No full textABSTRAK
Penelitian ini bertujuan untuk menganalisis pengaruh Kepemimpinan, Motivasi Kerja, dan Lingkungan Kerja terhadap Kinerja Guru SMK Negeri 2 Depok Sleman Yogyakarta. Populasi dalam penelitian ini adalah seluruh guru yang berjumlah 126 orang, maka pengambilan sampel menggunakan teknik sampling jenuh. Sampel dalam penelitian ini berjumlah 126 orang. Penelitian ini menggunakan metode kuantitatif. Teknik pengumpulan data menggunakan kuesioner dengan Skala Likert. Teknik analisis data yang digunakan adalah regresi linier berganda dengan menggunakan aplikasi SPSS versi 24. Hasil penelitian menunjukkan bahwa Kepemimpinan, Motivasi Kerja, dan Lingkungan Kerja berpengaruh positif dan signifikan secara parsial terhadap Kinerja Guru SMK Negeri 2 Depok. Kepemimpinan, Motivasi Kerja, dan Lingkungan Kerja secara simultan berpengaruh terhadap Kinerja Guru SMK Negeri 2 Depok. Nilai R Square sebesar 0,892 menunjukkan bahwa sebesar 89,2% Kinerja Guru mampu dijelaskan oleh Kepemimpinan, Motivasi Kerja, dan Lingkungan Kerja kemudian untuk sisanya 10,8% dijelaskan oleh faktor-faktor lain di luar penelitian ini
Development of a remote physics laboratory to support equitable access to education
No full textEconomic disparities and variations in geographical conditions in Indonesia exacerbate access to physics laboratories. Therefore, innovative solutions such as remote physics laboratories are needed to bridge this gap and provide more equitable access to students across the region, regardless of economic or geographical conditions. To overcome this, this research aims to develop a remote physics laboratory for equitable access to quality physics experiments. This research includes 4D model development research. The research subjects involved five students for the functionality test, 84 people for the user test, and ten media experts to assess the feasibility of the product. The instruments used include functionality test instruments, media expert assessments, and usefulness, satisfaction, and ease of use (USE) questionnaires. Tool functionality data and media expert validation were analyzed using the Aiken V technique. At the same time, the level of user acceptance was examined through a combination of Wright maps and logit item values. This development resulted in a remote physics experiment architecture and device with a good functionality assessment index. The assessment by media experts showed high validity. The level of user acceptance is classified in the medium to high category. Thus, the developed R-PhyLab has the potential to be an effective medium in equalizing access to quality physics laboratories in educational institutions that face economic limitations and unfavorable geographical conditions
Sistem Pendukung Keputusan Pemilihan Menu Makanan untuk Anak Sekolah Menggunakan Metode Profile Matching dan Simple Additive Weighting
No full textPemilihan menu makanan yang sesuai untuk anak usia sekolah merupakan tantangan bagi penyedia jasa katering. Anak-anak pada rentang usia tersebut sering kali memiliki preferensi makanan yang dipengaruhi oleh berbagai faktor seperti kebiasaan keluarga, pengaruh teman sebaya, serta paparan media dan iklan. Sementara itu, kebutuhan energi mereka juga harus terpenuhi untuk mendukung aktivitas sehari-hari. Selain itu, efektivitas produksi menjadi pertimbangan penting bagi pihak katering. Oleh karena itu, dikembangkan suatu sistem pendukung keputusan yang diharapkan membantu pengambilan keputusan dalam memilih menu makanan yang tepat untuk anak.
Metode yang akan digunakan dalam pengembangan sistem ini adalah kombinasi dari metode Profile Matching dan Simple Additive Weighting (SAW). Penggabungan kedua metode ini dilakukan karena Profile Matching dapat menilai sejauh mana suatu menu sesuai dengan standar ideal berdasarkan kriteria yang ditentukan, sedangkan SAW membantu dalam pembobotan nilai kriteria. Kombinasi ini diharapkan menghasilkan sistem yang lebih akurat dalam merekomendasikan menu makanan. Tahapan penelitian yang dilakukan meliputi identifikasi masalah, penentuan tujuan, pengumpulan data, analisis kebutuhan, perancangan sistem, implementasi, dan pengujian.
Hasil penelitian berupa sistem pendukung keputusan berbasis web yang memberikan rekomendasi paket menu makanan untuk anak sekolah. Pengujian dengan metode blackbox menyatakan bahwa sistem yang dihasilkan bejalan sesuai dengan skenario pengujian. Validasi menggunakan expert judgement menghasilkan tingkat akurasi 100% yang berarti hasil rekomendasi sistem sesuai dengan keputusan ahli dan perhitungan manual. Hasil pengujian sistem dengan metode SUS mendapatkan skor 78,75 dan masuk dalam kategori acceptable, menunjukkan bahwa sistem ini dapat diteima dengan baik oleh pengguna
The Use of Attention-RNN and Dense Layer Combinations and The Performance Metrics Achieved in Palm Vein Recognition
Get PDFThe utilization of palm veins in vascular biometrics is widely recognized, offering significant potential and challenges for advancing individual recognition technology. Deep learning has played a crucial role in enhancing the accuracy of these recognition systems. In this study, we proposed combining Attention-RNN and Dense Layer. To validate this proposed method, three deep learning model scenarios were implemented: (1) a combined Dense Layer with RNN, (2) an Attention-RNN model, and (3) a combined Attention-RNN with a Dense Layer for palm vein recognition. Experimental results demonstrated that the Attention-RNN combined with the Dense Layer achieved the highest accuracy, outperforming the other two models. The model’s performance was evaluated on two datasets, achieving 95% accuracy on the Kaggle dataset and 83% on the CASIA dataset, confirming its effectiveness in palm vein recognition
Solution Stirring Design Using Magnetic Stirrer on DC Motor with PLC-Based PID Method
Get PDFAlong with the development of the times, the industrial and manufacturing world also develops. One of the activities that is widely carried out in the industrial and manufacturing world is stirring production raw materials, either in the form of solutions or liquids. The purpose of the stirring process is to get a perfectly mixed (homogeneous) stirring. For this reason, a device is needed that can stir the solution as desired. One type of tool that can be used is a magnetic stirrer placed on a DC motor. However, when the DC motor is given a load, the DC motor tends to become unstable so a controller is needed. To solve this problem used PID controller. PID controllers use control constants in the form of PB, Tick, and Tdk. To obtain the controlling constant, a process of trial and error is carried out. The most stable results obtained from the testing process were PB = 600%, Tik = 1.2 s, and Tdk = 0.2 s. With system response in the form of rise time 0.7778 s, peak time = 5s. settling time 5.4286 s, overshoot = 2.8571 RPM and steady state error = 0%. The setpoint used is 700 RPM with a sampling time of 60 ms. The developed system successfully achieves stable and well-controlled stirring. The results of this research contribute to the improvement of solution stirring processes in the industrial and manufacturing domains. The developed system can be effectively utilized for stirring solutions, enhancing the efficiency and quality of production processes
A Hybrid Classification Model Based on BERT for Multi-Class Sentiment Analysis on Twitter
Get PDFSocial media is one of the media to convey opinions and sentiments. Sentiment analysis is an important tool for researchers and business people to understand user emotions efficiently and accurately. Choosing the right classification model has a significant impact on sentiment classification performance. However, the diversity of model architectures and training techniques poses its own challenges. In addition, relying on a single classification model often causes noise, bias, data imbalance, and limitations in handling data variations effectively. This study proposes a hybrid classification model where BERT is the baseline. Furthermore, BERT will be hybridized using LSTM, and BERT is hybridized with CNN to improve sentiment analysis on Twitter social media data. The hybrid approach aims to reduce the limitations of a single model classifier by increasing model effectiveness, reducing bias, and optimizing the model on imbalanced data. The following are the steps in this study, data preprocessing, data balancing, tokenization, model training, and performance evaluation. Three models were trained: the baseline BERT model, the BERT-CNN hybrid, and the BERT-LSTM hybrid. Model performance was assessed using accuracy, precision, recall, and F1 score. Experimental results show that the baseline BERT model achieves an accuracy of 91.45%, while BERT-LSTM achieves 91.60%, and BERT-CNN achieves the highest accuracy of 91.80%. However, further analysis is needed to determine whether these improvements are statistically significant and whether the hybrid model offers additional benefits beyond accuracy, such as remembering underrepresented sentiment categories
Handwritten Digits Detection Using Convolutional Neural Network
Get PDFNumbers are a collection of many lines and curves and play a vital role in everyday life. Each person has unique characteristics in handwriting, making handwritten digit detection a challenging task. This paper presents an approach for detecting handwritten digits using deep learning algorithms, particularly the Convolutional Neural Network (CNN)-based YOLOv8 family models. The main objective is to compare various YOLOv8 variants (YOLOv8n, YOLOv8s, YOLOv8m, YOLOv8l, and YOLOv8x) and determine the most optimal one in detecting handwritten digits. Experimental results show that the YOLOv8x variant achieves the highest performance, with a mean Average Precision (mAP) of 96.9%, a recall of 100%, a precision of 99.8%, and an F1-score of 99.9%. The research contributions are achieving high accuracy in handwritten digit detection using the YOLOv8x model and utilizing a custom primary dataset of 3,000 handwritten digits for training and evaluation, which adds novelty and real-world relevance to the study
PENGEMBANGAN WEBSITE PORTAL KERJA SAMA UNIVERSITAS AHMAD DAHLAN MENGGUNAKAN FRAMEWORK LARAVEL DI BIRO SISTEM INFORMASI
No full textUniversitas Ahmad Dahlan (UAD) mengambil inisiatif untuk mengembangkan Portal Kerja Sama (OIA UAD) sebagai sebuah platform digital yang bertujuan memfasilitasi dan mengoptimalkan proses kerja sama antara UAD dengan berbagai institusi, baik di dalam maupun luar negeri. Portal ini dirancang untuk mempermudah pengelolaan data kerja sama, menyajikan informasi terkini, serta mendukung interaksi yang efisien antar pemangku kepentingan. Dalam rangka pelaksanaan program magang di BSI UAD, peneliti turut berperan aktif dalam proses pengembangan portal ini, khususnya pada aspek frontend. Pengembangan dilakukan menggunakan framework Laravel yang memungkinkan integrasi logika frontend dan backend secara efisien melalui fitur Blade Templating. Peneliti bertanggung jawab untuk merancang antarmuka pengguna (UI) yang intuitif, menarik, serta responsif, dengan memanfaatkan Tailwind CSS untuk memastikan konsistensi dan modernitas tampilan. Hasil pengembangan frontend ini mampu menampilkan data dinamis secara optimal dan mendukung pengalaman pengguna yang baik, sesuai dengan kebutuhan portal kerja sama UAD
