Football is one of the most popular sports in Indonesia. Besides being popular, the money circulation in this sport is also very large. Because of the high interest of the people in football, football often becomes a unifying tool and even breaks down the barriers of difference in each event. However, football can also have a negative impact if it is managed poorly. Gambling cases that cause losses and violence in stadiums that often occur must be valuable lessons. This paper tries to make a review of the current condition of Indonesian football and its potential and threats. This paper will also provide strategic steps so that football can benefit the unity and integrity of the Indonesian nation.

Predicting credit worthiness is an important step for banks to reduce the risk of bad credit. This research compares the performance of four classification algorithms, namely SVM, Naïve Bayes, Random Forest and Decision Tree using simulated datasets. The results obtained on the metrics of accuracy, precision, recall, F1 score, and AUC-ROC, show that Decision Tree has the best performance with 42.5% accuracy, 48.3% precision, 47.5% recall, 47.5% F1 score, and AUC 0.60, indicating its ability to is in differentiating credit worthiness. Random Forest achieved an accuracy of 37.5% and an AUC of 0.493, while Naïve Bayes had the lowest accuracy with an accuracy of 27.5% and an AUC of 0.425. SVM gives better results than Naïve Bayes but is still inferior to Decision Tree. This research recommends implementing a Decision Tree as the main model with optimization through hyperparameter tuning, adding relevant features, and handling data accounting. These results are expected to support banking decision making more effectively and efficiently.

In today's digital era, introducing the concept of computational thinking ( CT ) from an early age is very important. Binekas School, as an educational partner at the Playgroup, Kindergarten (TK), and Elementary School (SD) levels, is committed to introducing CT to children starting at the age of 4. Currently, Binekas School only offers optional extracurricular coding activities at the elementary school level and uses a hard coding approach, which may be too challenging for most students. This school wants to prepare students with an introduction to the basics of coding from kindergarten using a more child-friendly approach, namely plugged-in with tangible robotics. The proposed solution includes an introduction to CT knowledge with a focus on algorithm development and CT training through tangible plugged-in techniques using robots for children aged 4 years and above. This training will not only improve children's understanding of the CT concept in an interactive and fun way, but will also prepare them for future educational challenges. The tools that will be used in this training are the Robotic Gigo Smart Brick, a robotic system designed for children so that they can learn basic programming concepts and computational thinking through interactive games. This outreach activity uses a combination of unplugged CT through card media and physical maps to train problem-solving mindsets accompanied by the opportunity to test proposed solutions with plugged-in CT using the Robotic Gigo Smart Brick. From the results of the activity evaluation through a questionnaire, it was found that 92% of students agreed that the application of the combination of unplugged CT and plugged-in CT was fun, the material was easy to understand and they were interested in getting further material.

This study aims to optimize the implementation of the K-Nearest Neighbors (K-NN) algorithm for medical image classification by focusing on selecting the optimal KKK parameter and applying dimensionality reduction techniques to improve accuracy and efficiency. The data used was sourced from public medical image repositories such as The Cancer Imaging Archive (TCIA) and Medical Image Analysis datasets, covering various diseases, including brain tumors, lung cancer, and kidney lesions. The research process involves data collection, data preprocessing, dimensionality reduction using Principal Component Analysis (PCA), applying the K-NN algorithm with Euclidean, Minkowski, and Cosine distance metrics, and performance evaluation using accuracy, precision, recall, and F1-score. Experimental results demonstrate that K=5with the Euclidean distance metric provides the best performance, achieving an accuracy of 90%. Additionally, PCA effectively reduces computational time by 30% without significantly compromising accuracy. This study proves that K-NN is an effective method for medical image classification. However, further research is needed to integrate K-NN with deep learning models to enhance performance and feature extraction capabilities.

This research examines the role of Indonesian Notary Position Regulations (UUJN) in enhancing integrity and professionalism within the notarial profession in Indonesia. The study adopts a normative legal research methodology, integrating both statutory and conceptual approaches to evaluate the effectiveness of existing regulatory frameworks governing notarial practice. Primary objectives include analyzing the impact of current regulations on notarial standards, identifying implementation challenges, and developing recommendations for regulatory enhancement. The research findings demonstrate that while the UUJN serves as a crucial foundation for professional notarial practice, several significant challenges persist in its implementation. These challenges encompass technological adaptation requirements, increasing transaction complexity, and the need for stronger oversight mechanisms. Analysis reveals opportunities for regulatory refinement to address emerging professional demands while maintaining high standards of integrity. This study contributes to the existing body of knowledge by providing comprehensive insights into the relationship between regulatory frameworks and professional excellence in notarial practice. The findings lead to specific recommendations for regulatory enhancement, including strengthening supervisory mechanisms, developing continuous professional development programs, and harmonizing standards with international best practices. These recommendations aim to foster a more robust and adaptable notarial profession in Indonesia while maintaining its fundamental role in ensuring legal certainty and protection for society.

Eco-print adalah teknik cetak daun yang diimplementasikan ke atas permukaan kain. Teknik yang dipergunakan dalam kasus ini adalah teknik pounding. Permasalahan dalam penelitian ini bagaimana proses penciptaan eco-print dengan menggunakan teknik pounding. Penelitian ini bertujuan untuk mengeksplorasi potensi batik eco print sebagai bentuk kegiatan kreatif dalam dunia pendidikan. Desain penelitian yang digunakan adalah kualitatif deskriptif. Adapun pengumpulan data dilakukan dengan observasi, eksperimen dan dokumentasi. Sampel dari penciptaan adalah hasil karya penciptaan dengan metode eksperimen yang dilakukan oleh lima orang perupa yang menggunakan berbagai macam daun dan bunga. Hasil dari penelitian penciptaan menunjukan karya yang dibuat diatas kain katun yang menghasilkan cetak daun berwarna hijau kontras adalah daun pepaya jepang. Sedangkan hasil karya cetak bunga yang berwarna terang adalah bunga telang. Batik eco-print ini dapat dilakukan oleh semua kalangan masyarakat, dapat dilakukan dengan mudah, aman, menyenangkan, dan ramah lingkungan karena hanya membutuhkan alat dan bahan yang sederhana, tanpa melibatkan bahan kimia berbahaya. Batik kreatif dapat di implementasikan menjadi alternatif media pembelajaran seni rupa yang menarik dan efektif. Bidang pendidikan menggunakan batik eco-print ini sebagai jembatan dalam mengembangkan kreativitas dan imajinasi siswa dengan mengeksplorasi variasi motif, warna dan juga segi estetika. Tingkat kegagalan yang rendah akan membuat masyarakat lebih percaya diri untuk mengeksplor design yang diinginkan. Batik eco print ini juga memiliki potensi menjadi produk UMKM berbasis masyarakat yang mudah dilakukan.

The number of investment instrument is often confusing for people who have minimal knowledge but still want to investing. Due to the many investments instrument offered, with the lack of public literacy in financial management, most people have a fear of missing out which case the phenomena of FOMO (Fear of Missing Out), the desire of people to get rich quick without thinking about the risk future which result in many fraudulent practices circulating in the community. This study aims to assist users in deciding the right investment instrument according to the user s risk profile. The decision support system in determining investment instrument with AHP (Analytical Hierarchy Process) Method is a method for problems in determining priorities from various alternative. AHP will make it easier to determine the right instrument.    

This study aims to determine the effect of price and trust on consumer satisfaction in J&T Express delivery services in Kediri City. This type of research is quantitative research. The data for this study were obtained through primary and secondary data. The population in this study were consumers of J&T Express in Kediri City. The sample in this study was 100 consumers with the sampling technique using accidental sampling. The analysis techniques used were validity testing, reliability testing, classical assumption testing, multiple linear regression analysis and hypothesis testing. The results of the study showed that the partial t-test results of the price and trust variables influenced consumer satisfaction. The results of the simultaneous F-test showed that price and trust influenced consumer satisfaction.

Implementation of the Naive Bayes algorithm for the classification of recipients of the Certificate of Inability to Pay (SKTM) assistance in Pesanggrahan Village. The classification process is carried out manually and using the RapidMiner application to validate the results. Manual calculations are carried out by calculating the probability of each attribute, such as occupation, age, income, marital status, vehicle, and asset ownership. The calculation results show that the probability for the "eligible" category is 0.097254, while the "uneligible" category has a probability of zero, so that the resident is classified as eligible to receive assistance. And, the calculation results using RapidMiner show results that are consistent with manual calculations. The Naive Bayes algorithm successfully classifies data with high accuracy, ensuring that assistance is more targeted to residents who meet the criteria. The implementation of this method provides an effective solution to overcome the problem of inaccurate distribution of assistance, increasing efficiency and transparency in decision-making by village officials. Thus, the Naive Bayes algorithm can be used as a tool in the process of determining recipients of assistance that is more objective and data-based.

Teacher ethics serves as a crucial moral foundation for educators in establishing a conducive educational environment. It encompasses relationships between teachers and students, colleagues, parents, and the broader community. This article aims to examine the role of teacher ethics in building student trust, which is an essential aspect of successful teaching and learning processes. Employing a qualitative approach through literature studies, this research identifies key dimensions of teacher ethics, including justice, honesty, responsibility, and empathy, which underpin the development of student trust. The findings reveal that consistent application of teacher ethics can enhance students’ respect for their teachers, encourage active student engagement in the learning process, and foster a positive learning atmosphere. Furthermore, the trust developed strengthens the emotional connection between teachers and students, ultimately improving student learning outcomes. This study recommends the importance of teacher ethics training for educators to ensure integrity and professionalism in every educational interaction.