This study was conducted due to the low interest of seventh-grade students in learning Islamic Education (PAI) at SMP Al-Mushlih Telukjambe Timur, Karawang. The purpose of this research is to determine the improvement of students’ learning interest through the use of visual learning strategies. The method used was classroom action research conducted in two cycles. Contextual learning strategies were applied using visual media, and students’ interest was assessed through observation sheets. The results showed a significant increase in interest, from 50% before the action, to 70% in the first cycle, and 95% in the second cycle. In conclusion, the use of contextual visual learning strategies effectively improves students’ interest in learning Islamic Education. This approach offers benefits for both educators and students in creating more engaging and interactive learning environments.
 

This study investigates how teaching methods affect students' willingness to learn. Students' interest and engagement in the learning process can be enhanced by effective teaching methods. Different teaching philosophies, including collaborative, inventive, interactive, and authoritative, have varying effects on students' willingness to learn. To achieve the best learning outcomes, it is necessary to choose a teaching style that suits the needs and characteristics of students. In this study, a qualitative approach was used to analyze students' perceptions of various teaching styles in the classroom environment. The results showed that interactive and collaborative methods tend to increase learning motivation more than the one-way authoritative style. In addition, teacher emotional involvement, the use of interesting learning media, and a conducive classroom atmosphere also contribute greatly to shaping students' learning interests. These findings are expected to be a reference in designing more adaptive and effective teaching strategies.

The rapid evolution of industrial robotics has been significantly influenced by the integration of computational data and social media, enabling robots to become more adaptive and responsive in collaborative work environments. This study investigates the role of social media and computational data in enhancing the adaptability of industrial robotics through machine learning techniques. By integrating sentiment analysis from social media with sensor data from industrial robots, this study examines how real-time data functions can improve robot decision-making and human-robot collaboration. Experimental results show a 23% increase in operational efficiency, an 89% accuracy rate in social interaction classification, and a 15% reduction in prediction errors. Furthermore, 62% of public sentiment toward adaptive robots is positive, highlighting the growing acceptance despite concerns over the impact of automation on jobs. These findings suggest that leveraging social media and computational data can significantly enhance the adaptability of robots, leading to a more efficient and socially conscious industrial ecosystem.

This research discusses the application of musyarakah contracts as a sharia financing solution for Micro, Small and Medium Enterprises (MSMEs) in the midst of digital economic development. MSMEs have a crucial role in sustaining the Indonesian economy, but still experience difficulties in accessing fair and sustainable financing. The musyarakah agreement, with its partnership and profit-sharing principles, is considered to be in line with the character of MSMEs that prioritize cooperation and justice. Through a qualitative approach based on a literature study, this research explores the potential, regulatory challenges, and strategies to strengthen the implementation of digital musyarakah. The results of the analysis show that digitalization offers great opportunities in promoting Islamic financial inclusion, but is still constrained by low digital literacy, limited infrastructure, and weak supervision of sharia principles. Therefore, a strategy is needed that includes improving education, developing Islamic financial technology, and collaboration between regulators, financial service providers, and MSME players. This study concludes that the successful implementation of digital musyarakah requires an integrated approach so that MSMEs are able to access Islamic financing independently, fairly and sustainably.

Penelitian ini bertujuan untuk mengkaji dampak ekuitas merek, desain produk, dan gaya hidup terhadap keputusan pembelian ponsel iPhone di kalangan generasi muda yang tinggal di Kecamatan Gajah, Demak. Sebanyak 60 responden yang dipilih menggunakan teknik purposive sampling menjadi sampel dalam penelitian ini. Data dikumpulkan melalui kuesioner, dan analisis data dilakukan dengan menggunakan SPSS versi 30. Uji analisis yang diterapkan meliputi uji kualitas data (validitas dan reliabilitas), uji asumsi klasik (normalitas, heteroskedastisitas, dan multikolinearitas), serta uji hipotesis (regresi linear berganda, uji R, uji t, dan uji F). Hasil penelitian menunjukkan bahwa ekuitas merek, desain produk, dan gaya hidup memiliki pengaruh positif dan signifikan terhadap keputusan pembelian iPhone pada generasi muda di Kecamatan Gajah, Demak.
 

This study examines the effect of product quality, brand image, and price on consumer loyalty through satisfaction in students using Acer laptops at Dian Nuswantoro University. Data were collected from 115 respondents and analyzed using PLS-SEM through SmartPLS 4.0 software. The results show that product quality and brand image have a positive and significant effect on satisfaction, while price does not have a significant effect on satisfaction. On the other hand, only brand image and consumer satisfaction are proven to have a significant effect on consumer loyalty, while product quality and price do not show a significant direct effect on loyalty. However, product quality is proven to have an indirect effect on consumer loyalty through consumer satisfaction as a mediating variable. These findings emphasize the importance of improving quality and brand image to build loyalty.

Student learning outcomes are a benchmark for achieving learning objectives in schools, but it is not uncommon for learning outcomes to be one of the problems that are often experienced in various school institutions. Learning problems and school demands cause anxiety, such as difficulty managing study time, anxiety of failing exams and grades below the standard are considered to be problems that are often found in schools. This study aims to determine how junior high school students' learning outcomes are influenced by the school environment and their learning motivation. This study combines literature study methodology with a qualitative approach. Books, journals, and articles relevant to the research topic are examples of research sources. The findings of the study indicate that learning motivation and the school environment have a significant impact on junior high school students' learning outcomes.
 

This study investigates the effect of Current Ratio (CR), Debt to Equity Ratio (DER), and Total Asset Turnover (TATO) on Return on Assets (ROA) in banking companies listed on the Indonesia Stock Exchange (IDX) during 2019–2023. Using purposive sampling, 20 companies were selected over 5 years (100 observations). Multiple linear regression analysis shows that CR has a significant positive effect on ROA, DER has no significant effect, while TATO has a significant negative effect on ROA.

A study on the challenges of pension fund literacy and inclusion in Indonesia concluded that the average level of pension fund literacy in the period 2013 - 2025 only reached 18.08%, while the average level of inclusion in that period only reached 4.23%. The level of pension fund literacy and inclusion in Indonesia is low. In SNLIK 2025, the pension fund literacy rate was 27.79%, while the pension fund inclusion rate was 5.37%. Compared to the 2022 pension literacy rate of 30.46% and the 2022 inclusion rate of 5.40%, this means that pension literacy and inclusion rates are declining. It can be said that out of 10 Indonesians, only 2.7 people “understand” pension funds and only 0.5 (half) people “have” pension funds. This means that for every 10 Indonesians, less than 1 person has a pension fund. Low pension literacy and inclusion has a direct impact in the form of 1) an older generation at risk of poverty or financial dependence on children/family, 2) a continuing sandwich generation cycle, 3) stagnant growth of the pension fund industry, 4) low public trust, and 5) the emergence of public skepticism towards pension funds in the future.

Kemajuan teknologi informasi mendorong perubahan sistem pendidikan, termasuk kebijakan perkuliahan online sejak pandemi COVID-19. Penelitian ini menganalisis sentimen mahasiswa terhadap kebijakan tersebut menggunakan pendekatan multibahasa dengan algoritma K-Nearest Neighbor (KNN) dan Naïve Bayes. Adapun aspek pembeda penelitian ini adalah penggunaan data dari bahasa Indonesia dan bahasa daerah Sulawesi Barat, yaitu bahasa Mandar, yang menambah kompleksitas tahap preprocessing. Data dikumpulkan melalui kuesioner yang menghasilkan 1.680 opini mahasiswa, dan setelah tahap preprocessing menghasilkan 1.679 data yang siap dianalisis. Hasil klasifikasi menunjukkan algoritma K-Nearest Neighbor terdapat 1002 kategori positif dan 677 kategori negatif. Kemudian pada algoritma Naïve Bayes terdapat 1020 kategori positif dan 659 kategori negatif. Berdasarkan hasil klasifikasi, mayoritas opini bersifat positif, mencerminkan bahwa mahasiswa menerima adanya kebijakan tersebut. Hasil evaluasi melalui confusion matrix serta K-Fold Cross Validation menunjukkan bahwa pendekatan klasifikasi Naïve Bayes mengungguli KNN dengan accuracy 74.87%, precision 74.92%, recall 74.87%, dan f1-score 74.64%. Sementara itu, KNN mencatat accuracy 72.84%, precision 72.80%, recall 72.84%, dan f1-score 72.67%. Hal tersebut mengindikasikan bahwa Naïve Bayes mempunyai kemampuan generalisasi yang lebih unggul pada konteks data teks multibahasa yang kompleks. Penelitian ini menyoroti pentingnya strategi evaluasi dan teknik preprocessing yang sesuai dalam klasifikasi sentimen multibahasa.
 
Kata Kunci - Analisis Sentimen, K-Nearest Neighbor, Multi Bahasa, Naïve Bayes; Perkuliahan Online.