E-Jurnal Politeknik Dharma Patria
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Penerapan Aplikasi Digital untuk Link and Match di SMK
No full textTujuan dari kegiatan program ini adalah Pelatihan penggunaan Platform digital untuk pencarian tempat praktik industri secara online di sekolah mitra. Metode yang digunakan dalam kegiatan pemberdayaan ini adalah melalui analisis situasi dan potensi, perencanaan kegiatan, pelaksanaan dengan menyelenggarakan pelatihan pengelolaan praktik kerja industri serta penerapan apikasi digital “PRAKTEKKERJA” di sekolah mitra. Akhir kegiatan ini dengan evaluasi untuk mengetahui apakah kegiatan yang dilakukan sudah mampu mencapai target yang telah ditetapkan. Hasil evaluasi penyebaran angket dari program ini antara lain: Presentase penguasaan materi sebesar 93 persen, untuk ketepatan waktu dalam penyajian dan acara kegiatan sebesar 89 persen, materi memberikan manfaat kepada peserta 96 persen, penyelenggaran kegiatan cukup profesonal dengan presentase 91 persen dan presentase kepasan peserta cukup tinggi yakni sebesar 95 persen. platform ini memiliki potensi besar untuk diimplementasikan secara luas di sekolah tersebut
User Interface, User Experience, Gratis Ongkir Terhadap Keputusan pembelian melalui Preferensi E-Commerce Sebagai mediasi
No full textAda banyak faktor yang Mempengaruhi preferensi seseorang dalam memilih aplikasi e-commerce dan melakukan keputusan pembelian, Tmenganalisis pengaruh User Interface (UI), User Experience (UX), dan promo Gratis.Ongkos kirim r terhadap keputusan pembelian.dengan.preferensi.penggunaan aplikasi sebagai variabel intervening. Fokus penelitian adalah pengguna e-commerce Tokopedia di wilayah.Yogyakarta. Peneliti ingin mengetahui apakah variabel preferensi penggunaan apliaksi e-commerce dapat memediasi variabel User interface, User.experience dan promo gratis ongkir terhadap keputusan pembelian ? Metode penelitian menggunakan kuantitatif data dikumpulkan melalui survei online. Analisis data dilakukan menggunakan teknik regresi 2 jalur untuk mengidentifikasi hubungan antara variabel independen (UI, UX, dan promo Gratis Ongkir) terhadap variabel intervening (preferensi penggunaan aplikasi) lalu selanjutnya dengan variabel dependen (keputusan pembelian) Hasilnya variabel Preferensi tidak memediasi pengaruh antara variabel user interface terhadap keputusan pembelian, tetapi Variabel Preferensi penggunaan aplikasi e-commerce mampu memediasi antara Variabel user experience, promo gratis ongkir terhadap keputusan pembelian
 
Dilema Religiusitas: Sebuah Paradoks Terkait Implementasi SDG
No full textThis study is undertaken to offer empirical insights into the impact of countries with varying levels of religiosity and different GDP conditions on the implementation of the Sustainable Development Goals (SDGs). There are 127 countries in the world as the sample. The data analysis method uses multiple regression analysis. To separate between low and high-religiosity countries, the data is separated based on the median of religiosity. The religiosity variable uses an index religiosity publication, GDP uses a measure of country income released by the World Bank, while the implementation of SDGs uses an index released by the United Nations. The results of this study show that religiosity has a negative effect on SDG while GDP has a positive effect on SDG. The findings of this study should be interpreted with caution. Commitment to realizing sustainability goals needs the support of various stakeholders, according to the findings of this research including religious leaders, government, and the community.
 
Advanced Credit Scoring with Naive Bayes Algorithm: Improving Accuracy and Reliability in Financial Risk Assessment
No full textThis study develops a credit application recommendation system based on the Naive Bayes method to improve accuracy and reliability in financial risk assessment. Using the CRISP-DM framework, the research process starts with understanding the business needs to implement a web-based system. The Naive Bayes algorithm was chosen because of its ability to handle binary data classification and generate reliable predictions even with limited training data. This study combines feature selection and unbalanced data handling techniques to improve model performance. The evaluation results showed that the system achieved an accuracy of 70.50%, with a precision of 92.16%, a recall of 64.57%, and an F1-score of 75.83%. This system is implemented as a web-based application to help financial institutions make credit decisions quickly and accurately. These findings significantly contribute to developing a data-based classification system for the banking sector, especially in reducing the risk of bad loans and improving decision-making efficienc
Website Penetration Testing With SQL Injection Technique Using SQLMAP on Termux
No full textWebsites make it easier for us to find information or do our daily work. Almost all companies have websites, be it company profiles or application websites. With the development of technology, some programmers forget about website security. Websites with security weaknesses can be easily hacked, such as changing appearance to taking essential data. One thing to watch out for is external factors in the form of attacks carried out by hackers using the SQL Injection technique. This technique can find and take all databases stored on the website server. The purpose of this study is so that programmers and companies, in general, can be more careful with this attack so as not to experience losses from both the company and the consumer side. The results obtained in this study show that SQL injection attacks can cause significant losses because they can modify and take over the database on the attacked website. This tool also runs automatically so that laypeople without an understanding of hacking can carry out this attack. Thus, programmers can secure their websites using techniques to secure SQL Injection attacks
Optimization of Convolutional Neural Network (CNN) Using Transfer Learning for Disease Identification in Rice Leaf Images
No full textRice productivity, as one of the key commodities in Southeast Asia, is often hindered by various plant diseases such as Rice Blast, Bacterial Leaf Blight, and Brown Spot, which can cause significant economic losses for farmers. This study aims to develop an automated rice leaf disease detection system using deep learning, specifically leveraging the Convolutional Neural Networks (CNN) architecture with a transfer learning approach. The dataset used comprises 10,407 images of rice leaves categorized into 10 classes, including various diseases and healthy leaves. The dataset is divided into three parts: 80% (8,323 images) for training, 15% (1,557 images) for validation, and 5% (527 images) for testing. The trained EfficientNetB0 model was utilized for feature extraction and classification. The evaluation used accuracy, precision, recall, and F1-score metrics based on a confusion matrix. The results revealed that the model achieved a global accuracy of 98.86%, a micro precision of 100%, a micro recall of 99.42%, and a micro F1-score of 99.70%. These findings underscore the effectiveness of the proposed approach in automating rice leaf disease detection, providing a significant contribution to technology-based agricultural solutions
Decision Support System Implementation of Decision Tree Algorithm C4.5 In Employee Performance Assessment
No full textEmployee performance assessment can be used as an evaluation tool to improve employee performance to achieve more. Some of the benefits of performance appraisal are such as improving business quality, driving business progress, and improving employee welfare. Yasmin Medical Clinic requires an employee performance appraisal system that can help superiors to process data properly so that it can shorten the time and produce an assessment that is in accordance with the subjective value of decision making. One method that can be used in a decision support system is a decision tree. Current decision trees such as C4.5 and CART are widely used in various fields. The results of the analysis show that the application of the decision support system of the decision tree algorithm c4.5 in employee performance appraisal is able to solve problems at the Yasmin Medical Clinic. A computerized decision support system helps the decision-making process and produces objective decisions that are in accordance with actual conditions.Penilaian kinerja karyawan dapat digunakan sebagai alat evaluasi untuk meningkatkan kinerja karyawan agar semakin berprestasi. Beberapa manfaat dari penilaian kinerja yakni seperti meningkatkan kualitas bisnis, mendorong kemajuan bisnis, dan meningkatkan kesejahteraan karyawan. Klinik Yasmin Medical membutuhkan sistem penilaian kinerja karyawan yang dapat membantu atasan untuk mengolah data dengan baik sehingga dapat mempersingkat waktu serta menghasilkan penilaian yang sesuai dengan nilai subjektivitas pengambilan keputusan. Salah satu metode yang dapat dipakai dalam sistem pendukung keputusan adalah adalah pohon keputusan (decision tree). Pohon keputusan saat ini seperti C4.5 dan CART banyak digunakan di berbagai bidang. Hasil analisis menunjukkan bahwa penerapan sistem pendukung keputusan implementasi decision tree algoritma c4.5 dalam penilaian kinerja karyawan mampu menyelesaikan masalah di Klinik Yasmin Medical. Sistem pendukung keputusan yang terkomputerisasi membantu proses pengambilan keputusan dan menghasilkan keputusan yang objektif yang sesuai dengan kondisi sebenarnya
Towards Predictive Fatigue Management: A Blockchain-Enabled IoT Framework for Driver Safety in Logistics
No full textDriver fatigue is a critical issue in the logistics industry, contributing significantly to accidents and operational inefficiencies. The system utilizes IoT devices, including physiological and vehicular sensors, to monitor real-time data, such as Heart Rate Variability (HRV), Galvanic Skin Response (GSR), and Acceleration Variance (AV). Blockchain integration ensures secure, immutable data storage and transparency, with smart contracts automating fatigue alerts and management actions. The research results show that HRV increased from 50 ms to 70 ms, reflecting better stress recovery, while AV decreased from 0.85 m/s² to 0.45 m/s², indicating more stable driving behavior. Fatigue alerts dropped by 60%, from 25 to 10 alerts per observation period, demonstrating the system’s effectiveness in early fatigue detection and prevention. The study concludes that the IoT-blockchain integration provides a robust, scalable solution for mitigating fatigue-related risks, enhancing driver safety, and fostering operational efficiency in the logistics sector
Strategi dan Tantangan dalam Menuju Pasar Global pada UMKM "Miz Titin"
No full textThis research aims to explore effective methods for expanding market reach and identify the main obstacles that may be encountered. The methodology used includes case studies and in-depth interviews with MSME owners as well as analysis of relevant literature. The research results show that the main strategies implemented include product quality evaluation, use of technology, business development, and relationships with customers in global market orientation and innovation. The challenges faced include competitors, human resources, services, markets, raw materials and brand image in the global market network and efficiency. In conclusion, researchers hope that in the future the development of MSMEs in the global market sector will continue to be carried out and supported by all levels of society where the government plays an important role regarding the development of MSMEs, such as regulations and training guidance for MSMEs so they can compete in the global market.Penelitian ini bertujuan untuk mengeksplorasi metode yang efektif untuk memperluas jangkauan pasar dan mengidentifikasi hambatan utama yang mungkin dihadapi. Metodologi yang digunakan meliputi studi kasus dan wawancara mendalam dengan pemilik UMKM serta analisis literatur yang relevan. Hasil penelitian menunjukkan bahwa strategi utama yang diterapkan meliputi evaluasi kualitas produk, penggunaan teknologi, pengembangan bisnis, dan hubungan dengan pelanggan dalam orientasi dan inovasi pasar global. Tantangan yang dihadapi mencakup kompetitor, SDM, pelayanan, pasar, bahan baku dan citra merek dalam jaringan dan efisiensi pasar global. Kesimpulannya, peneliti mengharapkan kedepannya pengembangan UMKM pada sektor pasar global terus dilakukan dan didukung oleh seluruh lapisan masyarakat dimana pemerintah memegang peran penting terkait perkembangan suatu UMKM seperti halnya regulasi dan pengarahan pelatihan pada UMKM agar bisa bersaing di pasar global
Literasi Keuangan Memoderasi Hubungan FoMO, Love of Money, dan Self Control terhadap Pengelolaan Keuangan Pribadi
No full textSebagai individu yang rentan terhadap konsumerisme yang dipengaruhi oleh tren global, media sosial, dan budaya popular, sangat penting bagi K-Popers untuk mengelola keuangan, yang mungkin memiliki efek negatif yang beragam. Oleh karena itu, penelitian ini bertujuan untuk mengetahui pengaruh FoMO, love of money, self control, terhadap pengelolaan keuangan pribadi pada penggemar K-Pop (Army) di Kota Malang dengan literasi keuangan sebagai variabel moderasi. Metode yang digunakan penelitian ini adalah kuantitatif deskriptif. 367 penggemar K-Pop (Army) di Kota Malang adalah sampel, yang dipilih menggunakan purposive sampling. Setelah pengumpulan data melalui kuesioner, SmartPLS digunakan untuk menganalisis data. Hasil penelitian memperlihatkan bahwa diantara para penggemar K-Pop (Army), love of money dan self control tidak memiliki dampak signifikan terhadap pengelolaan keuangan, FoMO memiliki dampak negatif yang signifikan terhadap pengelolaan keuangan pribadi. Sedangkan literasi keuangan berpengaruh signifikan sebagai moderasi antara pengelolaan keuangan terhadap FoMO, love of money, self control