Micro, Small, and Medium Enterprises (MSMEs) have a significant role in the economy, including MSMEs in the culinary sector such as Putri Ice Cream Business. Decision making related to optimal resource allocation is crucial to increase the efficiency and profitability of MSMEs. This study aims to apply the linear programming method with the primal simplex algorithm to minimize production costs in the case study of Putri Ice Cream MSME. The objective function is to minimize the total production cost, as well as the limitations related to the availability of main raw materials and machine production capacity. Data on main raw materials and machine production capacity were obtained from the Putri Ice Cream MSME which was the case study. The results of the study show that the application of the primal simplex method produces an optimal solution that provides recommendations for product combinations for each type of Putri Ice Cream with minimal production costs. Sensitivity analysis was also conducted to test the stability of the optimal solution to changes in capital. This study provides a practical contribution to Putri Ice Cream MSME in optimizing their resource allocation and increasing cost efficiency through a quantitative approach.
 
 

In the digital era, companies are required to manage data optimally to improve operational efficiency. This research aims to analyze the role of data management and database systems in supporting company work efficiency. A descriptive approach is used by reviewing literature from various relevant academic sources. The results show that the implementation of a structured database system can reduce data redundancy, increase the speed of information access, and strengthen the decision-making process. With good data integration between divisions, the company can improve internal coordination and response to market changes. The findings confirm the importance of an effective data management strategy in supporting an organization's competitive advantage.
 
 

Discipline character education in early childhood refers to instilling obedience to rules at home, school, and in society for children aged 0–6 years. This education serves as a crucial foundation for shaping future generations. This study aims to examine the implementation of traffic ethics education for young children, the strategies used, and influencing factors at Al-Anshor Islamic Kindergarten Palembang in the 2023/2024 Academic Year. A qualitative descriptive method was employed, involving two teachers (Class A and B) as the main data sources. Data were collected through observation, interviews, and documentation. The findings reveal that the strategy for teaching traffic ethics includes: (1) Planning, by integrating traffic ethics indicators into RKM and RPPH; (2) Implementation, through integration in learning activities, school culture, and daily routines; and (3) Evaluation, conducted in conjunction with other learning assessments. The character values fostered through this process include self-confidence, discipline, and responsibility. These findings suggest that incorporating traffic ethics education into early childhood learning can effectively instill discipline, contributing positively to children's character development and awareness of civic responsibility from an early age.

In the digital era, personal data protection has become a crucial issue due to the growing risks of privacy breaches. This study aims to explore the role of digital education in enhancing privacy literacy and mitigating the social impacts of data violations. Utilizing a mixed-methods approach, primary data was collected through online surveys and in-depth interviews with users and experts, while secondary data was analyzed from academic journals and industry reports. Results reveal that only 42.7% of respondents understood how to safely manage their personal information, reflecting a significant gap in privacy awareness. Moreover, a positive correlation (R = 0.72) was identified between improved privacy literacy and reduced social risks, such as identity theft and cyberbullying. Simulations proved to be effective educational tools, with every 10% increase in digital privacy literacy reducing social risks by 7%. The findings highlight the need for integrating privacy education into formal curricula at all educational levels, complemented by community-based initiatives for underserved populations. Collaborative efforts between governments, educational institutions, and technology organizations are essential to develop relevant and effective learning resources. The study underscores the importance of adopting holistic educational strategies to empower individuals in navigating the challenges of data protection in the digital age.

This study aims to evaluate production waste at PT XYZ, a food manufacturing company in Bandung, Indonesia, which experiences inefficiencies caused by overproduction and product defects. A descriptive qualitative method with a case study approach was used, employing data from production reports, field observations, and interviews. The analysis was conducted using the 7 Waste framework, the 5S workplace organization method, and the PDCA (Plan-Do-Check-Act) cycle. The findings show that the main types of waste at PT XYZ are overproduction and defects, which are caused by inaccurate demand forecasting, ineffective layout, and inconsistent quality control. By implementing 5S and PDCA, the company successfully reduced waste, improved workspace organization, and increased process efficiency. This study provides practical insights for manufacturing companies seeking to implement lean strategies for continuous improvement.

The purpose of writing this review article is to analyze the formulation and evaluation of the use of various additives in effervescent tablets. The method used is a literature review taken from journals and other relevant research results regarding the formulation and evaluation of additives in various types of effervescent tablets. The purpose of this analysis is to provide a summary of relevant publications and to improve current understanding in this field. The importance of the formulation and evaluation of additives in effervescent tablets cannot be ignored, because it is a crucial aspect in product development. Decisions in the use of additives must consider the objectives to be achieved, the desired physical characteristics, product stability, and the level of consumer acceptance. With a deep understanding of this formulation and evaluation, we have the potential to produce high-quality effervescent tablets. Variations in additives can also provide different taste and texture characteristics, which of course can affect consumer acceptance.
 

This study develops an image processing application to automatically detect the ripeness level of tomatoes using the YCbCr color space transformation. This method is effective because it is able to separate the luminance and chrominance components, so it can identify color changes that indicate the ripeness level of tomatoes, namely unripe, semi-ripe, and ripe tomatoes. The application is designed with matlab and uses a GUI interface that makes it easy for users to upload and process images. Based on trials on image samples, the system is able to classify tomato ripeness with 100% accuracy on a limited test dataset. The classification process is based on three main parameters: the red area ratio, the average value of the Cr channel, and the average value of the Cb channel. The results of the study indicate that this approach can be used as a digital solution in the automatic and efficient tomato sorting process

This study aims to analyze the factors influencing the risk perception of stock investments among Generation Z in Indonesia. The research method used is quantitative, employing a survey approach through questionnaires. The analytical technique applied is multiple linear regression. The results of the study indicate that financial literacy, investment experience, and social influence significantly impact risk perception. These findings have important implications for financial education providers and capital market institutions.

This research examines District Court Decision Number 113/Pdt.G/2022/PN Jap with the aim of assessing that the decision was incorrect by not granting compensation and that the request for compensation submitted was legally valid.  The urgency of this research is the injustice of the judge's decision against the Plaintiff by not providing the compensation requested by the Plaintiff even though the application is valid according to the law and assessing that the first level decision was incorrect because the Defendants committed an unlawful act by claiming, releasing, transferring and selling customary land without permission and causing losses. This reflects the lack of legal protection of landowners' rights to customary land inheritance. This research is important to provide a perspective for customary landowners in order to obtain justice from a legal perspective. The research method used is the normative juridical research method or doctrinal research. The statute approach and case approach were used. This research encourages judges to refer to Article 1365 of the Civil Code in deciding PMH cases by paying attention to proving losses so that the decisions have legal certainty and have implications for improving the quality of decisions. Therefore, this research assesses that the judge's decision in this case was incorrect because it did not provide compensation in accordance with the losses suffered by the landowner despite the fact that the losses were experienced for 35 years and the Plaintiff's request for compensation was valid according to Article 1365 of the Civil Code.
 
Penelitian ini mengkaji Putusan PN Nomor 113/Pdt.G/2022/PN Jap dengan tujuan melakukan penilaian bahwa putusan tersebut tidak tepat dengan tidak memberikan ganti kerugian dan permohonan ganti rugi yang diajukan sah secara hukum. Urgensi penelitian ini yaitu ketidakadilan putusan Hakim terhadap Penggugat dengan tidak memberikan ganti rugi yang dimohonkan Penggugat meskipun permohonan sah menurut hukum serta menilai putusan tingkat pertama tidak tepat karena para Tergugat melakukan perbuatan melanggar hukum dengan mengeklaim, melepas, mengalihkan dan menjual tanah adat tanpa izin dan menimbulkan kerugian. Hal ini, mencerminkan kurangnya perlindungan hukum terhadap hak-hak pemilik tanah atas warisan tanah adat. Penelitian ini penting untuk memberikan perspektif bagi Pemilik tanah adat agar mendapatkan keadilan dari segi hukum. Metode penelitian yang digunakan metode penelitian yuridis normatif atau doctrinal research. Digunakan pendekatan perundang-undangan (statute approach) dan pendekatan kasus (case approach). Penelitian ini mendorong Hakim mengacu pada Pasal 1365 KUHPerdata dalam memutuskan perkara PMH dengan memperhatikan pembuktian kerugian sehingga putusan yang diputus memiliki kepastian hukum dan berimplikasi terhadap peningkatan kualitas putusan. Karenanya, penelitian ini menilai bahwa putusan Hakim dalam perkara ini tidak tepat karena tidak memberikan ganti rugi sesuai kerugian yang dialami pemilik tanah padahal secara faktanya kerugian dialami selama 35 tahun serta permohonan ganti rugi Penggugat sah menurut Pasal 1365 KUHPerdata.

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.