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The dynamics of the global coffee industry during the 2024–2026 period were characterized by significant fluctuations that placed Starbucks in a vulnerable position due to multidimensional reputation crises, ranging from geopolitical sentiments to industrial relations tensions. This study aims to analyze the effectiveness of Public Relations (PR) management strategies and integrated media models in restoring brand equity post-crisis. The research method applied is descriptive qualitative with a conceptual analysis approach, relying on digital literature studies and the collection of secondary data from international reputation research firm reports and credible mass media documentation. The research results indicate that the drastic decline in the Brand Strength Index was successfully mitigated through a strategic narrative transition from service efficiency toward the reinforcement of the original "The Third Place" identity. The utilization of data-driven Owned Media channels through loyalty applications proved to be the most crucial instrument in maintaining consumer retention amidst the global boycott. The research conclusion emphasizes that brand resilience in the era of digital volatility depends not only on rhetoric but on the synchronization between adaptive leadership, operational transparency, and the integration of an agile PESO communication model. This study provides a theoretical contribution regarding the importance of managing "reputation capital" through consistent sustainability commitments to maintain a balance between profitability and corporate communication ethics in an increasingly polarized global market

This study implements the Damerau-Levenshtein algorithm for an Indonesian spelling checking and correction system based on the distance editing approach. The main objective of this study is to develop a system capable of automatically detecting and correcting spelling errors at the character level through a matching process against the KBBI dictionary and the Indonesian corpus. The methods used include data collection, text pre-processing, system design, and implementation of the Damerau-Levenshtein algorithm which includes insertion, deletion, substitution, and transposition operations. Testing was conducted using 25 test data consisting of standard words and modified words for typographical errors. The results show that the system is able to measure all test data with an accuracy level of 100% on a limited dataset. In addition, the average Damerau-Levenshtein Distance value of 0.84 indicates that most errors are in the light category. Evaluation using a confusion matrix produces precision, recall, and F1-score values ​​of 100% each. These results indicate that the Damerau-Levenshtein algorithm is effective in handling character-based spelling errors. However, the system still has limitations in handling complex semantic contexts and language variations. Therefore, further research is recommended to integrate language model-based approaches to improve the system's accuracy and generalization on real-world data.

This research aims to classify students’ lifestyles using the K-Nearest Neighbors (KNN) algorithm. The dataset consists of 392 high school students obtained from Kaggle, with key attributes including study hours, social media usage, Netflix viewing duration, attendance, sleep quality, internet quality, mental health, and extracurricular activities. KNN was chosen for its simplicity in distance-based classification, measured using Euclidean Distance. The data was divided into training and testing sets, then evaluated using accuracy and a confusion matrix. The results show that KNN effectively classifies students’ lifestyles into four categories: healthy, less active, at risk, and highly at risk. This classification is expected to assist educational institutions, parents, and students in understanding lifestyle patterns and their impact on academic performance and mental well-being. Furthermore, this study emphasizes the relevance of applying machine learning in education, aligned with Islamic values concerning health, discipline, and the optimal use of time.

Lagu Jawa modern merupakan perkembangan kontemporer dari musik tradisional Jawa yang semakin banyak dinikmati generasi muda melalui platform digital. Namun, meningkatnya jumlah lagu baru membuat pengguna sulit menemukan lagu yang sesuai dengan preferensi musikal jika pencarian hanya dilakukan berdasarkan judul atau nama artis. Penelitian ini mengembangkan pendekatan rekomendasi berbasis konten melalui klasterisasi fitur audio terhadap 100 lagu Jawa modern yang dikumpulkan dari YouTube. Fitur audio diekstraksi menggunakan Librosa pada Python, meliputi tempo BPM, danceability, RMS energy, zero-crossing rate, MFCC means, spectral contrast means, dan chroma features means, sehingga setiap lagu menghasilkan 36 fitur numerik. Algoritma K-Means digunakan untuk membentuk tiga klaster, PCA digunakan untuk memvisualisasikan distribusi klaster, dan Silhouette Score digunakan untuk mengevaluasi kualitas pengelompokan. Hasil penelitian mengidentifikasi tiga gaya musikal yang dapat diinterpretasikan, yaitu Jawa modern enerjik, lagu tradisional atau akustik, serta Jawa eksperimental atau ambient, dengan Silhouette Score sebesar 0,114. Temuan ini menunjukkan bahwa fitur audio mampu merepresentasikan karakter lagu secara objektif dan mendukung sistem rekomendasi adaptif untuk pelestarian musik daerah. Pendekatan ini juga membantu memperluas akses pendengar terhadap kekayaan musik lokal di era digital secara berkelanjutan.

This study implements the Damerau-Levenshtein algorithm for an Indonesian spelling checking and correction system based on the distance editing approach. The main objective of this study is to develop a system capable of automatically detecting and correcting spelling errors at the character level through a matching process against the KBBI dictionary and the Indonesian corpus. The methods used include data collection, text pre-processing, system design, and implementation of the Damerau-Levenshtein algorithm which includes insertion, deletion, substitution, and transposition operations. Testing was conducted using 25 test data consisting of standard words and modified words for typographical errors. The results show that the system is able to measure all test data with an accuracy level of 100% on a limited dataset. In addition, the average Damerau-Levenshtein Distance value of 0.84 indicates that most errors are in the light category. Evaluation using a confusion matrix produces precision, recall, and F1-score values ​​of 100% each. These results indicate that the Damerau-Levenshtein algorithm is effective in handling character-based spelling errors. However, the system still has limitations in handling complex semantic contexts and language variations. Therefore, further research is recommended to integrate language model-based approaches to improve the system's accuracy and generalization on real-world data.

This research aims to classify students’ lifestyles using the K-Nearest Neighbors (KNN) algorithm. The dataset consists of 392 high school students obtained from Kaggle, with key attributes including study hours, social media usage, Netflix viewing duration, attendance, sleep quality, internet quality, mental health, and extracurricular activities. KNN was chosen for its simplicity in distance-based classification, measured using Euclidean Distance. The data was divided into training and testing sets, then evaluated using accuracy and a confusion matrix. The results show that KNN effectively classifies students’ lifestyles into four categories: healthy, less active, at risk, and highly at risk. This classification is expected to assist educational institutions, parents, and students in understanding lifestyle patterns and their impact on academic performance and mental well-being. Furthermore, this study emphasizes the relevance of applying machine learning in education, aligned with Islamic values concerning health, discipline, and the optimal use of time.

Lagu Jawa modern merupakan perkembangan kontemporer dari musik tradisional Jawa yang semakin banyak dinikmati generasi muda melalui platform digital. Namun, meningkatnya jumlah lagu baru membuat pengguna sulit menemukan lagu yang sesuai dengan preferensi musikal jika pencarian hanya dilakukan berdasarkan judul atau nama artis. Penelitian ini mengembangkan pendekatan rekomendasi berbasis konten melalui klasterisasi fitur audio terhadap 100 lagu Jawa modern yang dikumpulkan dari YouTube. Fitur audio diekstraksi menggunakan Librosa pada Python, meliputi tempo BPM, danceability, RMS energy, zero-crossing rate, MFCC means, spectral contrast means, dan chroma features means, sehingga setiap lagu menghasilkan 36 fitur numerik. Algoritma K-Means digunakan untuk membentuk tiga klaster, PCA digunakan untuk memvisualisasikan distribusi klaster, dan Silhouette Score digunakan untuk mengevaluasi kualitas pengelompokan. Hasil penelitian mengidentifikasi tiga gaya musikal yang dapat diinterpretasikan, yaitu Jawa modern enerjik, lagu tradisional atau akustik, serta Jawa eksperimental atau ambient, dengan Silhouette Score sebesar 0,114. Temuan ini menunjukkan bahwa fitur audio mampu merepresentasikan karakter lagu secara objektif dan mendukung sistem rekomendasi adaptif untuk pelestarian musik daerah. Pendekatan ini juga membantu memperluas akses pendengar terhadap kekayaan musik lokal di era digital secara berkelanjutan.

This systematic literature study conducts a comparative analysis of Reliability-Centered Maintenance (RCM) and Total Productive Maintenance (TPM) in manufacturing, and proposes an integrated hybrid model. The research concludes that RCM and TPM are fundamentally distinct methodologies: RCM excels in risk-based, analytical management of complex, high-criticality assets, while TPM is superior for achieving broad-based productivity gains and cultural empowerment through total employee involvement. The effectiveness of each approach is contingent upon factors such as asset characteristics, organizational culture, data availability, and level of automation. To leverage their complementary strengths, the study proposes the Synergistic RCM-TPM Hybrid Model (SRTHM). This framework advocates for a sequential implementation where TPM establishes the foundational operational stability, discipline, and data culture, upon which selective RCM analysis is applied to critical assets for precision risk management. The model incorporates explicit feedback mechanisms to create a continuous organizational learning cycle. The study provides a contingency framework for methodology selection and a practical roadmap for integration, offering theoretical and practical guidance for building more resilient and context-appropriate maintenance systems in modern manufacturing.

Korosi pada material stainless steel dalam lingkungan basa dan temperatur tinggi menjadi salah satu faktor yang memengaruhi umur pakai peralatan pada sistem netralisasi minyak sawit. Penelitian ini bertujuan menganalisis pengaruh temperatur dan kecepatan pengadukan terhadap laju korosi serta membandingkan ketahanan korosi baja tahan karat SS304 dan SS316 dalam larutan NaOH 1 M. Pengujian dilakukan menggunakan metode weight loss berdasarkan standar ASTM G31–72 selama 49 hari dengan variasi temperatur 70°C, 90°C, dan 110°C serta kecepatan pengadukan 100 rpm, 200 rpm, dan 300 rpm. Laju korosi dihitung berdasarkan kehilangan massa spesimen dan dianalisis menggunakan klasifikasi ketahanan korosi. Hasil penelitian menunjukkan bahwa peningkatan temperatur dan kecepatan pengadukan menyebabkan peningkatan laju korosi pada kedua material. Nilai laju korosi tertinggi diperoleh pada SS304 sebesar 0,0247 mm/tahun pada kondisi 110°C dan 300 rpm, sedangkan nilai terendah diperoleh pada SS316 sebesar 0,0124 mm/tahun pada kondisi 70°C dan 100 rpm. Secara umum, SS316 menunjukkan ketahanan korosi yang lebih baik dibandingkan SS304 karena kemampuan mempertahankan lapisan pasif yang lebih tinggi. Berdasarkan klasifikasi ketahanan korosi, sebagian besar kondisi pengujian berada pada kategori sangat baik sehingga kedua material masih layak digunakan pada sistem netralisasi minyak sawit, dengan SS316 lebih direkomendasikan untuk kondisi operasi yang lebih agresif.

Green transportation policy has increasingly been regarded as a cornerstone of urban mobility reform worldwide, yet its explicit orientation toward cyclist safety remains insufficiently developed. This paper examines how sustainable transportation management policies can be normatively designed to advance cyclist safety as a primary policy objective, not a secondary concern. Drawing on a qualitative literature review, the study explores the structural relationship between green transportation frameworks and the protection of cyclists within urban road systems. The discussion covers key policy dimensions including physical infrastructure standards, speed regulation, legal frameworks, public education, technological support systems, and inter-agency coordination. The study argues that a coherent policy architecture is essential for ensuring that the promotion of cycling as a low-emission mode is accompanied by robust safety provisions. Without this coherence, green transportation policy risks generating a structural contradiction between its environmental aspirations and its duty of care toward vulnerable road users. The findings affirm that cyclist safety and environmental sustainability are mutually reinforcing values that must be embedded together within any credible urban transportation governance framework.

The low thermal efficiency of Gas Power Plants (PLTG) due to exhaust gas heat loss drives the implementation of cogeneration at PLTGU Block II PT. PLN Indonesia Power UBP Semarang. This study analyzes the performance of the Gas Turbine Generator (GTG), combined cycle efficiency, and Exergy distribution using a 3-3-1 configuration. The research utilizes actual operational data from January 28, 2026, sampled at 10-minute intervals. Results indicate that cogeneration via a Heat Recovery Steam Generator (HRSG) significantly enhances plant efficiency. The GTG output ranged from 273–283 MW with an efficiency of 30.0–30.2%. Following combined cycle integration, system efficiency increased to 43.9–44.4%, a gain of approximately 14%, with a heat rate of 11,916–11,988 kJ/kWh. Exhaust heat of 665–713 MW was recovered to generate an additional 130 MW through the Steam Turbine Generator (STG). Exergy analysis reveals that the largest irreversibility occurs in the GTG combustion process (285 MW), followed by the HRSG (185 MW) and STG (49 MW).

This study aims to analyze the impact of the USD/CNY exchange rate and the Federal Reserve interest rate on the stock returns of Volkswagen AG. Volkswagen AG is chosen as the object of analysis because it is a multinational corporation with significant exposure to the Chinese market, making it highly sensitive to fluctuations in global economic conditions, particularly exchange rate movements and monetary policy changes. The study adopts a quantitative research approach using multiple linear regression analysis to examine the relationships between variables. The data used are monthly secondary data covering the period from 2017 to 2023, resulting in 84 observations. The dependent variable in this study is Volkswagen AG stock returns, while the independent variables consist of the USD/CNY exchange rate and the Federal Funds Rate. The empirical results show that the USD/CNY exchange rate has a negative and statistically significant effect on Volkswagen AG stock returns, indicating that currency depreciation or appreciation plays a crucial role in influencing investor sentiment and firm valuation. In contrast, the Federal Funds Rate does not show a statistically significant effect on stock returns during the observed period. However, the simultaneous test indicates that both variables jointly have a significant influence on Volkswagen AG stock returns. Overall, the findings suggest that exchange rate risk is more dominant than U.S. monetary policy in affecting the stock performance of Volkswagen AG over the study period.

The implementation of active learning models such as Problem-Based Learning (PBL) and Project-Based Learning (PjBL) at the junior high school level is often constrained by the complexity of instructional time management. This study aims to examine the role of the principal’s instructional leadership in addressing time management dilemmas in the implementation of active learning at SMP Negeri 6 Panyabungan. A qualitative approach with a descriptive method was employed in this study. Data were collected through non-participant observation and in-depth interviews with key informants, namely the school principal and an Islamic Religious Education (PAI) teacher selected as representatives of field conditions. The findings reveal three main results. First, teachers’ time management constraints are caused by weak control of learning activity transitions, noisy classroom conditions during group division, and low initial student learning readiness. Second, the principal implemented several concrete interventions, including the adoption of block scheduling, clinical supervision focused on classroom management, and the optimization of the Subject Teacher Forum (MGMP) or school learning community. Third, these interventions improved teachers’ instructional efficiency, strengthened classroom activity control, and created a more structured active learning process. However, sustainability challenges remain, particularly resistance from senior teachers who tend to prefer conventional teaching methods. This study concludes that adaptive and solution-oriented instructional leadership is a key factor in addressing the complexity of time management constraints in active learning implementation.

The increasing number of corruption cases involving School Operational Assistance (BOS) funds has become a serious challenge for the education sector in Indonesia. These cases not only undermine public trust in educational institutions but also hinder the achievement of equitable and quality education. This study aims to analyze the role of professional leadership in preventing and addressing the misuse of BOS funds within educational institutions. The research employs a qualitative approach through literature review and analysis of relevant regulations, scholarly publications, and documented corruption cases in the education sector. The findings indicate that professional leadership characterized by integrity, accountability, transparency, and strong ethical commitment plays a significant role in minimizing opportunities for corruption. Effective leaders are able to establish robust internal control systems, promote a culture of honesty, and ensure participatory financial management involving various stakeholders. Furthermore, continuous supervision and adherence to governance principles strengthen institutional resilience against financial misconduct. The study implies that strengthening leadership capacity and ethical values among educational leaders is essential for improving financial governance and fostering public confidence in educational management. Professional leadership is therefore a crucial factor in supporting clean, transparent, and sustainable education administration.

This study aims to analyze the factors influencing customer satisfaction at PT JNE Cabang Latta Ambon, focusing on five dimensions of service quality according to the SERVQUAL model: Tangibles, Reliability, Responsiveness, Assurance, and Empathy. Data were collected through a questionnaire distributed to 145 respondents using shipping services. The results of the analysis indicate that of the five dimensions, only the Empathy dimension has a positive and significant effect on customer satisfaction (β = 0.204; p = 0.048). The other variables, while showing positive effects, did not demonstrate statistical significance. The regression model developed was able to explain approximately 22.1% of the variation in customer satisfaction, emphasizing that there are other factors beyond the measured dimensions that also influence satisfaction. The F-test results show that, simultaneously, all five dimensions of service quality significantly affect customer satisfaction, supporting the SERVQUAL theory that highlights the importance of a multidimensional approach in service delivery. Practical implications of this study suggest that PT JNE Latta Ambon should focus more on enhancing empathy and responsiveness in service, while maintaining the quality of other aspects as a minimum standard. This research provides valuable insights for developing more effective customer-oriented service strategies and opens opportunities for further research in this field.

This study aims to analyze the effect of Digital Accounting Systems on Financial Decision Quality through Accounting Information Quality in modern companies. This research employed a quantitative explanatory approach using a survey design. Primary data were collected from 100 employees working in finance, accounting, and financial administration departments through purposive sampling and analyzed using Structural Equation Modeling–Partial Least Squares (SEM-PLS) with SmartPLS. The findings reveal that Digital Accounting Systems have a positive and significant effect on Accounting Information Quality, Accounting Information Quality has a positive and significant effect on Financial Decision Quality, and Digital Accounting Systems also directly improve Financial Decision Quality. The mediation test confirms that Accounting Information Quality partially mediates the relationship between Digital Accounting Systems and Financial Decision Quality. These results imply that companies should not only adopt digital accounting technology but also strengthen system integration, data validation, transaction standardization, and user competence to ensure that digital accounting systems produce accurate, timely, relevant, and useful information for effective financial decision-making.  

This study aims to examine the effect of Return on Assets (ROA), Debt to Equity Ratio (DER), and e-IPO regulation on the level of IPO underpricing on the Indonesia Stock Exchange during the 2021–2025 period. The research employs a causal quantitative approach using multiple linear regression analysis. Secondary data were collected from the prospectuses and financial statements of companies conducting Initial Public Offerings (IPOs).The results indicate that ROA does not have a significant effect on underpricing (significance value = 0.181). Similarly, DER is found to have no significant influence on underpricing (significance value = 0.268). The simultaneous test also shows a non-significant result, with an F-significance value of 0.120, suggesting that the independent variables collectively do not affect IPO underpricing. Furthermore, the coefficient of determination (R²) of 0.175 implies that only 17.5% of the variation in underpricing can be explained by the variables included in the model, while the remaining 82.5% is attributable to other factors outside the study, such as market sentiment, underwriter reputation, and oversubscription levels. These findings suggest that investors in the Indonesian IPO market tend to prioritize short-term capital gain opportunities rather than relying on firms’ financial fundamentals. Consequently, accounting-based indicators are not sufficiently influential in shaping stock prices during the first day of trading.

Shares trading below their intrinsic value present compelling return opportunities, particularly for long‑term investors. This study aims to assess the valuation of eight food‑and‑beverage issuers listed on the Indonesia Stock Exchange (IDX) over the 2021–2025 period using two market‑based valuation instruments: the Price to Earnings Ratio (PER) and the Price to Book Value (PBV). A quantitative descriptive design was employed, and a purposive sampling technique selected eight issuers: INDF, ICBP, MYOR, ROTI, GOOD, CLEO, CMRY, and CAMP. The sectoral benchmarks obtained were an average industry PER of 22.64 times and an average industry PBV of 3.45 times. Comparative analysis reveals that INDF (PER 7.38x; PBV 0.59x), ICBP (PER 17.60x; PBV 1.83x), ROTI (PER 18.86x; PBV 2.47x), and CAMP (PER 16.59x; PBV 1.78x) are undervalued relative to the industry average and therefore merit consideration as buy candidates, while MYOR, GOOD, CLEO, and CMRY are overvalued. INDF emerges as the most attractive investment candidate because its PBV remained consistently below 1.00 throughout the observation window, a condition recognized in value‑investing literature as deeply undervalued. The findings reinforce the argument that combining PER and PBV serves as a reliable tool for identifying high‑potential stocks from a fundamental analysis perspective.

Penelitian ini bertujuan untuk mengetahui pengaruh disiplin kerja dan lingkungan kerja terhadap kinerja karyawan pada PT Kangklin Jaya Bersih di Jakarta Selatan. Metode yang digunakan adalah kuantitatif. Penelitian ini populasi sebanyak 150 karyawan dan teknik pengambilan sampel menggunakan rumus slovin dengan eror 5% dan diperoleh sampel sebanyak 86 responden. Analisis data menggunakan uji validitas, uji realibilitas, uji asumsi klasik, analisis regresi, koefisien korelasi, koefisien determinasi, uji hipotesis. Hasil penelitian ini adalah Disiplin kerja berpengaruh signifikan terhadap kinerja karyawan dengan persamaan regrensi Y = 4,371 + 0,800 X1. Nilai koefisien korelasi sebesar 0,853 artinya kedua variabel memiliki tingkat hubungan yang sangat kuat. Nilai koefisien determinasi sebesar 72,7%. Uji hipotesis diperoleh hasil t hitung > t tabel atau (14,953 > 1,988). Hal tersebut juga diperkuat dengan nilai signifikansi < 0,05 atau (0,000 < 0,05). Lingkungan kerja berpengaruh signifikan terhadap kinerja karyawan dengan persamaan regrensi Y = 3,163 + 0,867 X2. Nilai koefisien korelasi sebesar 0,864 artinya kedua variabel memiliki tingkat hubungan yang sangat kuat. Nilai koefisien determinasi sebesar 74,6%. Uji hipotesis diperoleh hasil t hitung > t tabel atau (15,694 > 1,988). Hal tersebut diperkuat dengan nilai signifikansi < 0,05 atau (0,000 < 0,05). Disiplin kerja dan lingkungan  kerja secara simultan berpengaruh signifikan terhadap kinerja karyawan dengan persamaan regrensi Y = 1,468 + 0,390 X1 + 0,474 X2. Nilai koefisien korelasi diperoleh 0,887 artinya memiliki hubungan yang sangat kuat. Nilai koefisien determinasi sebesar 78,8% dan uji hipotesis diperoleh hasil F hitung > F tabel atau (153,833 > 3,11). Dengan demikian terbukti Ha3 diterima dan Ho3 ditolak. Hal ini juga diperkuat dengan nilai signifikansi < 0,05 (0,000 < 0,05). Artinya terdapat pengaruh yang signifikan antara disiplin kerja dan lingkungan kerja terhadap kinerja karyawan pada PT Kangklin Jaya Bersih Di Jakarta Selatan.

Baros District has the potential for creative economy-based Micro, Small, and Medium Enterprises (MSMEs) products that need to be strengthened, including products from the agricultural, livestock, crafts, food, and various other types of trade sectors. This study aims to analyze and assess the steps for developing creative economy-based MSMEs in Baros District, located in Serang Regency, Banten. The method applied is a qualitative approach through observation, interviews, document collection, and using a SWOT Matrix analysis to identify the strengths, weaknesses, opportunities, and challenges faced in developing creative economy-based MSMEs in Baros District, Serang Regency, Banten. Data sources used include the Head of Baros District, local village heads, academics, MSME actors, employees from the Serang Regency MSME Office, and MSME observers. This study lasted for one year. The appropriate strategy for developing MSMEs in Baros District is the SO (Growth) strategy, which utilizes existing strengths to increase competitiveness. The research revealed that MSMEs operating in the creative economy sector in Baros District still face various challenges in developing their businesses, such as limited capital, the use of simple production equipment, suboptimal marketing, a shortage of skilled labor, and limited use of technology and copyright registration for their products.