Mining companies are one of the companies that have great prospects in the future. Mining companies are one of the corporate sectors that are targeted for investment, this causes investors to often calculate share returns for their investments in companies in this sector. Stock returns in companies tend to fluctuate or experience erratic increases and decreases in stock returns. The increase or decrease in stock returns is caused by internal and external factors, internal factors can be seen through financial reports and external factors can be seen from macroeconomic and other factors. This research is secondary data, namely it comes from financial reports of mining companies registered in JII70 for the 2018-2022 period. This research is included in the type of quantitative research, using Eviews as a statistical medium and the statistical methods used in this research are multiple linear regression analysis, panel data testing, classical assumption testing, and hypothesis testing. while the results of this research show that partially both Net Profit Margin and Price To Book Value have a positive and significant effect on Stock Returns as well as simultaneously Net Profit Margin and Price To Book Value together or simultaneously have a positive and significant effect on Stock Returns while inflation weaken the relationship Net Profit Margin and Price To Book Value on Share Returns in mining companies registered on JII70.

This study investigates the influence of profitability, solvency, and activity financial ratios on firm value within the energy sector (oil, gas, and coal) listed on the Indonesia Stock Exchange from 2021 to 2023. Utilizing multiple linear regression analysis, the research demonstrates that profitability (ROA), solvency (DER), and activity (TATO) collectively and individually impact firm value (PBV). The findings suggest that financial performance management is crucial for enhancing firm value in this sector, especially in response to market dynamics and regulatory changes.

Penelitian ini bertujuan untuk mendapatkan bukti empiris mengenai pengaruh tekanan (pressure), peluang (opportunity), rasionalisasi (rationalization), dan kapabilitas terhadap pencegahan kecurangan (fraud prevention), serta peran moderasi nilai etika dalam hubungan tersebut. Menggunakan desain penelitian kausal, data dikumpulkan melalui survei menggunakan kuesioner kepada 311 pimpinan dan karyawan Grup PT. Asvia Laguna Medis. Analisis dilakukan dengan metode kuantitatif untuk mengevaluasi hubungan antar variabel. Hasil penelitian menunjukkan bahwa tekanan, peluang, rasionalisasi, dan kapabilitas memiliki pengaruh positif dan signifikan terhadap pencegahan kecurangan. Selain itu, nilai etika memperkuat pengaruh tekanan terhadap pencegahan kecurangan, namun memperlemah pengaruh peluang, rasionalisasi, dan kapabilitas terhadap pencegahan kecurangan. Kesimpulan dari penelitian ini adalah bahwa faktor-faktor internal seperti tekanan, peluang, rasionalisasi, dan kapabilitas penting dalam mencegah kecurangan, dan nilai etika memainkan peran kritis dalam memoderasi hubungan ini.

This study compares family-based and institutional care models for the elderly, focusing on their impacts on well-being and quality of life. Through interviews with elderly individuals and caregivers, the research assesses how each model meets the emotional, social, and healthcare needs of the elderly. Findings suggest that while family care offers emotional benefits, institutional models can provide better healthcare, calling for integrated approaches to eldercare.

This research investigates school scope classification using Deep Neural Networks (DNN), focusing on students living environments and educational opportunities. By addressing the interplay of socioeconomic and educational factors, the study aims to develop an analytical framework for understanding how environmental contexts shape academic trajectories. The research provides a nuanced understanding of the importance of features in educational classification by developing DNN models based on Spearman's Rank Correlation Coefficient (SRCC). The methodology employs machine learning techniques, integrating data wrangling, exploratory analysis, and multiple DNN models with K-fold cross-validation. The study analyzes 677 student records from two schools. The research examined multiple model configurations. Results show that the 'All Data' model achieved 83.08% accuracy, the 'Top 5' model 81.54%, and the 'Non-Top 5' model 79.23%. The SRCC-based approach revealed that while top correlated features are important, additional variables significantly contribute to model performance. The study highlights the profound impact of family background, social environment, and educational contexts on school selection. Furthermore, it demonstrates DNN's capability to uncover intricate, non-linear relationships, offering actionable insights for policymakers to leverage machine learning's potential in developing targeted educational strategies.

Konsep Orientasi Pelanggan sangat penting bagi perusahaan untuk berkembang di era saat ini, dengan memanfaatkan teknologi untuk mendapatkan wawasan yang mendalam tentang perilaku pelanggan mereka. Salah satu alat teknologi tersebut adalah pembelajaran mesin, khususnya yang menggunakan pendekatan pemrosesan bahasa alami (NLP). Penelitian ini menggunakan lima algoritma yang berbeda dan menggabungkan berbagai metode untuk meningkatkan kinerja model machine learning. Melalui penerapan teknik-teknik seperti random over-sampling (ROS) dan ensemble learning, akurasi prediksi keseluruhan untuk kelas minoritas meningkat secara signifikan. Model ensemble yang diintegrasikan dengan ROS mencapai akurasi 0,90 dan mean square error 0,91, mengungguli algoritma lain yang diuji dalam penelitian ini. Pendekatan yang dioptimalkan ini tidak hanya menunjukkan keefektifan pemanfaatan teknologi untuk sebuah perusahaan dapat menerapkan strategi yang berpusat pada pelanggan, tetapi juga menyoroti pentingnya peningkatan metodologi dalam pemodelan prediktif untuk keberlanjutan bisnis.
 
Kata kunci: Klasifikasi Emosi, Pembelajaran Mesin, Pemrosesan Bahasa Alami, Hard Voting, Random Over Sampling.

Penyakit paru-paru, seperti pneumonia dan kanker paru-paru, menjadi masalah kesehatan global dengan tingkat kematian tinggi, terutama dipengaruhi oleh polusi udara, infeksi, dan kebiasaan merokok. Pencegahan dan deteksi dini sangat penting dalam mengurangi dampaknya. Algoritma yang digunakan dalam penelitian ini meliputi Random Forest, XGBoost, dan Logistic Regression. Tujuannya yaitu untuk membandingkan performa tiga algoritma machine learning dalam mengklasifikasikan penyakit paru-paru menggunakan metrik evaluasi seperti, akurasi, presisi, recall, dan F1-score.  Setelah hyperparameter tuning, XGBoost menunjukkan hasil terbaik dengan akurasi 94,44%, presisi 94,98%, recall 94,44%, dan F1-score 94,41%, menunjukkan keseimbangan optimal antara presisi dan recall. Random Forest juga memberikan hasil yang sebanding dengan XGBoost dengan akurasi dan presisi yang tinggi. Sementara itu, Logistic Regression menunjukkan keterbatasan dalam menangani data yang kompleks, dengan performa yang lebih rendah pada seluruh metrik evaluasi. Penelitian ini menunjukkan bahwa algoritma berbasis pohon keputusan seperti XGBoost dan Random Forest lebih unggul untuk klasifikasi penyakit paru-paru, menjadikannya metode yang lebih andal untuk mendukung deteksi dini penyakit ini.
 
Kata kunci: Hyperparameter Tuning, Logistic Regression, Penyakit Paru-paru, Random Forest, XGBoost.

Guna mendukung proses pembelajaran sistem otomasi di sebuah lembaga pendidikan dibutuhkan sebuah alat peraga yang mudah dipelajari dan dimengerti oleh mahasiswa. Tujuan pembuatan alat peraga ini agar peserta didik mengetahui dan dapat mengimplementasikan proses kerja sistem otomasi di industri menggunakan media yang disimulasikan dalam bentuk alat peraga. Alat peraga yang digunakan adalah integrasi PLC-HMI pada aplikasi pengisian tangki air. Alat peraga dirangkai dengan  menggunakan PLC dan HMI merk Omron dengan software CX-Programmer dan NB-Designer. Rangkaian wiring alat peraga PLC-HMI disusun secara teratur dan sistematis agar mudah dibongkar pasang dan disesuaikan dengan diagram wiring oleh peserta didik. Program ladder pada software CX-Programmer didesain dengan menerapkan logika dasar, instruksi dan beberapa fungsi program yang sesuai dengan level kompetensi dasar pembelajaran PLC. Desain tampilan dan fungsi HMI dirancang menggunakan software NB-Designer yang diintegrasikan dengan program ladder, serta disesuaikan penggunaan alamat I/O nya. Wiring alat peraga berfungsi secara normal sehingga seluruh perangkat dapat terkoneksi dengan baik. Program ladder yang telah dirancang dapat berfungsi optimal dan tidak didapati error pada hasil kompilasi. Desain HMI dapat berfungsi secara efektif untuk monitoring proses maupun saat berfungsi sebagai programmable terminal. Secara keseluruhan hasil rancang bangun alat peraga simulasi sistem pengisian tangki air telah diuji coba dan berfungsi sesuai rancangan yang telah ditetapkan.

The era of the digital economy in Indonesia has made buying and selling transactions easier and faster to carry out. By using social media, consumers can channel their opinions, criticism and suggestions regarding the products/services they consume to business actors in various forms. One of them is in the form of a review (overview) of products/services expressed through photos or videos. However, this activity has reaped pros and cons in society, because it is considered that this activity actually tarnishes a good name. This research aims to examine the form of legal protection for the provisions for reviewing products on social media. The sources of legal materials used in this writing are firstly primary legal material sources which have binding force, secondly secondary legal material sources which are legal materials originating from the results of a literature review by reading books, legal journals, and articles that are in accordance with the law. the issue being faced. Data were analyzed using qualitative methods. This research uses a normative research type using a deductive thinking approach. The data that has been analyzed shows that legal protection for the provisions for reviewing products on social media is stated in Law Number 12 of 2005 article 23 paragraph (2) concerning Human Rights, Article 44 paragraph (3) UUPK, and criminal sanctions for perpetrators are stipulated in the UUPK which can be sentenced to prison and a fine.

Since 2004, Indonesians have been granted the opportunity to directly elect their president and vice president, leading to two rounds of elections to select legislative members, as well as the president. In 2019, the Indonesian government made a significant decision to conduct concurrent general elections for both legislative and presidential. This research adopts qualitative research methods and utilizes literature review as its data collection approach. The findings of this study reveal that the simultaneous holding of the 2019 General Election has yielded diverse impacts, primarily stemming from logistical challenges, duplicated data on the voters list, excessive information overload among the public leading to irrational voting decisions, and unfortunate casualties, including the loss of hundreds of election committee officers' lives. Consequently, it highlights the pressing need for the General Election Commission (KPU) to thoroughly evaluate and address these issues while organizing the 2024 elections simultaneously.