Abstract:Sustainable leadership is increasingly important for translating the Sustainable Development Goals (SDGs) into effective decision-making, yet research on sustainable leadership, SDG trade-offs and synergies, and multi-actor…
tor governance remains fragmented. This study integrates these perspectives to develop a unified framework for SDG-oriented decision-making. A structured integrative literature review was conducted using Scopus as the primary database, complemented by Google Scholar and backward citation searching, with emphasis on studies published between 2015 and 2026. The synthesis shows that sustainable leadership extends beyond environmental responsibility by combining long-term orientation, stakeholder accountability, multidimensional sustainability objectives, and adaptive learning. Effective SDG-oriented decision-making also requires explicit assessment of trade-offs and synergies and governance mechanisms capable of aligning actors with different interests, resources, knowledge, and authority. Based on these findings, the study proposes the Sustainable Leadership–SDG Decision Framework (SL-SDG Framework), consisting of Leadership Orientation, Stakeholder Alignment, Policy Prioritization, Trade-Off and Synergy Assessment, Collaborative Implementation, SDG Outcomes, and Adaptive Feedback. Illustrative applications across coastal management, fisheries, mangrove restoration, sustainable tourism, urban sustainability, and organizational settings indicate that the framework is context-flexible but process-consistent. The framework contributes by positioning sustainable leadership as an iterative decision process for managing both inter-objective and inter-actor complexity. Future research should empirically validate its components, indicators, and causal relationships across governance and sustainability contexts.
Abstract:This study employed an integrated approach of side-scan sonar imaging and bathymetric surveying to precisely locate and characterize collapsed navigation structures within the dynamic Mahakam River Delta. This crucial waterway…
terway faces environmental challenges like strong currents and heavy siltation, threatening navigational aid integrity. Accurate identification of these submerged hazards is vital for safe shipping and future infrastructure development. Our findings demonstrated the effectiveness of combining these hydrographic methods to accurately map the seafloor and detect anomalies indicative of collapsed structures. Visual diving confirmed extremely poor underwater visibility, necessitating remote sensing. High-resolution bathymetric surveys successfully identified distinct riverbed anomalies, notably a collapsed structure at 00°50'13.29" S / 117°18'24.51" E, exhibiting a 1-1.5 meter elevation change at 4.5 meters depth. Acoustic data supported its man-made origin. These critical findings directly informed recommendations for repositioning affected navigation aids to a safer location at 00°50'16.29" S / 117°18'24.59" E, thus providing essential data for maritime safety and infrastructure management in complex riverine ecosystems
Abstract:The increasing volume of patient visits in primary healthcare facilities (such as community health centers and clinics) demands efficient resource management and scheduling systems. The inability to predict patient arrival…
al patterns often leads to long queues and suboptimal allocation of medical personnel. To overcome these issues, this study proposes the development of an intelligent framework based on Stacking Ensemble Learning to accurately classify and predict patient revisit frequency patterns. The proposed architecture integrates three heterogeneous base classification models (base learners), namely Logistic Regression (LR), Support Vector Machine (SVM) with non-linear Radial Basis Function (RBF) kernel projection, and Random Forest (RF). The probability predictions from these three base models are then combined into a secondary Logistic Regression based meta-learner to optimize the final decision and reduce the predictive bias of single models. Experiments were conducted using a dataset sourced from actual primary healthcare medical records, totaling 499 data entries. Given the highly imbalanced distribution of demographic data, the preprocessing stages were comprehensively designed, encompassing numerical scale feature standardization and the application of the SMOTE (Synthetic Minority Oversampling Technique) class balancing algorithm. Model testing was performed using a 5-fold stratified cross-validation scheme to ensure the robustness of the model's generalization. Comprehensive evaluation results proved that the Stacking Ensemble architecture achieved peak performance with an Accuracy of 88.4%, Precision of 85%, Recall of 90%, and an F1-Score of 0.88. Furthermore, curve analysis revealed an Area Under the Receiver Operating Characteristic (AUC-ROC) score of 0.961 and a Precision-Recall AUC of 0.95, consistently outperforming the capabilities of each individual baseline model. These findings confirm that combining hybrid machine learning models can produce highly stable and reliable predictions while minimizing false negative errors. This architecture holds massive potential for practical implementation as the foundation of a decision support system in managing operational services within primary healthcare facilities.
Abstract:Student mental health disorders have become an increasingly important issue due to their significant impact on academic performance and psychological well-being. Machine learning-based approaches offer a promising alternative…
ative for supporting early detection; however, only a limited number of studies have conducted comprehensive evaluations of various ensemble learning algorithms by simultaneously considering predictive performance, computational efficiency, and statistical significance. This study aims to compare ten classification algorithms, namely Random Forest, Extra Trees, Gradient Boosting, Hist Gradient Boosting, AdaBoost, XGBoost, LightGBM, CatBoost, Logistic Regression, and Stacking Ensemble, using 5-fold Stratified Cross-Validation. Model performance was evaluated using Accuracy, Precision, Recall, F1-Score, Receiver Operating Characteristic–Area Under the Curve (ROC-AUC), training time, inference time, confusion matrix, feature importance, as well as One-Way Analysis of Variance (ANOVA) and post-hoc Tukey’s Honestly Significant Difference (Tukey HSD) tests. The experimental results show that CatBoost achieved the highest classification performance, with an Accuracy of 84.86%, an F1-Score of 87.19%, a Recall of 88.03%, and an ROC-AUC of 0.9220. XGBoost delivered comparable predictive performance with a substantially shorter training time (3.92 seconds), while LightGBM was the most computationally efficient algorithm, requiring an average training time of only 0.85 seconds. In contrast, the Stacking Ensemble required the longest training time (215.41 seconds) without providing a statistically meaningful performance improvement over the boosting-based models. The ANOVA results revealed significant differences in ROC-AUC among the evaluated models (p < 0.001), whereas the Tukey HSD test indicated that most boosting algorithms did not differ significantly from one another. These findings provide practical guidance for selecting classification algorithms by balancing predictive performance and computational efficiency to support early mental health screening systems for university students.
Abstract:Penelitian ini bertujuan untuk menganalisis peran Corporate Social Responsibility (CSR) Starbucks dalam pengelolaan sampah serta keterkaitannya dengan nilai ekonomi kopi di Desa Sait Buttu Saribu, Kecamatan Pamatang Sidamanik,…
manik, Kabupaten Simalungun. Penelitian menggunakan pendekatan kualitatif deskriptif. Data diperoleh melalui wawancara mendalam dengan pengurus bank sampah, petani kopi, dan perangkat desa yang dipilih secara purposive berdasarkan keterlibatan dan pengetahuan mereka terhadap program CSR serta pengelolaan sampah di wilayah penelitian. Hasil penelitian menunjukkan bahwa CSR Starbucks berperan sebagai pendorong awal dalam meningkatkan perhatian masyarakat terhadap persoalan sampah di lingkungan perkebunan kopi melalui pembinaan, pemberian dorongan, serta dukungan terhadap penguatan Bank Sampah Desa Sait Buttu. Dukungan tersebut berkaitan dengan perubahan praktik masyarakat, terutama berkurangnya kebiasaan membakar sampah plastik di lahan pertanian dan meningkatnya perhatian terhadap kebersihan lingkungan perkebunan. Perubahan praktik tersebut kemudian berkaitan dengan meningkatnya pemahaman masyarakat bahwa kebersihan lingkungan merupakan bagian dari upaya menjaga kualitas kopi. Dari aspek ekonomi, informan menyampaikan adanya peningkatan harga cherry kopi dari sekitar Rp4.000 menjadi Rp15.000–Rp20.000 per kilogram. Namun, perubahan harga tersebut tidak dapat dinyatakan sebagai akibat langsung CSR Starbucks karena nilai jual kopi dipengaruhi oleh berbagai faktor lainnya. Dengan demikian, penelitian ini menunjukkan bahwa peran CSR Starbucks pada tingkat desa tidak hanya berkaitan dengan aspek lingkungan, tetapi juga mendorong perubahan praktik masyarakat yang memiliki keterkaitan dengan perhatian terhadap kualitas dan keberlanjutan ekonomi komoditas kopi.
This study aims to analyze the role of Starbucks’ Corporate Social Responsibility (CSR) in waste management and its relationship with the economic value of coffee in Sait Buttu Saribu Village, Pamatang Sidamanik District, Simalungun Regency. This study employed a descriptive qualitative approach. Data were collected through in-depth interviews with waste bank managers, coffee farmers, and village officials selected purposively based on their involvement in CSR programs and waste management practices. The findings indicate that Starbucks’ CSR serves as an initial driver in increasing community awareness of waste issues in coffee plantation areas through mentoring, encouragement, and support for strengthening the Sait Buttu Village Waste Bank. This support is associated with changes in community practices, particularly a reduction in plastic waste burning on agricultural land and increased attention to plantation cleanliness. These changes are also associated with greater awareness that environmental cleanliness contributes to maintaining coffee quality. From an economic perspective, informants reported an increase in coffee cherry prices from approximately IDR 4,000 to IDR 15,000–20,000 per kilogram. However, this increase cannot be attributed directly to Starbucks’ CSR because coffee prices are influenced by various other factors. Overall, Starbucks’ CSR contributes not only to environmental awareness but also to changes in community practices related to coffee quality and economic sustainability.
Abstract:TELISIK+ 2026 merupakan program pengabdian kepada masyarakat berbasis komunitas yang dirancang untuk mengatasi ketimpangan akses persiapan Seleksi Nasional Penerimaan Mahasiswa Baru (SNPMB) sekaligus membekali peserta dengan…
ngan kapasitas akademik dan keterampilan masa depan. Program ini mengusung pendekatan high-tech meets high-touch yang memadukan pembelajaran berbantuan kecerdasan buatan dengan pendampingan tutor secara langsung, dan terdiri atas empat program yang saling terhubung: bantuan buku UTBK, kelas daring UTBK, penulisan ilmiah dan publikasi, serta pengembangan website edukasi berbasis AI. Kegiatan dilaksanakan secara daring pada 16 Januari–20 April 2026 menggunakan kerangka planning, organizing, actuating, controlling (POAC) dan dievaluasi secara deskriptif-evaluatif dengan kerangka RE-AIM. Hasil pelaksanaan menunjukkan 36 peserta menerima bantuan buku persiapan UTBK, 36 sesi pembelajaran terselenggara pada tujuh subtes bersama 18 tutor, serta 24 peserta menyelesaikan seluruh subtes tryout dengan rerata skor 616,3 dan reliabilitas instrumen yang tinggi (Cronbach's alpha 0,897). Sebanyak 34 peserta diterima di perguruan tinggi negeri melalui jalur SNBP 2026. Platform digital yang dikembangkan telah mengarsipkan 2.273 butir soal UTBK dan 1.950 butir soal SKD, serta menjangkau 551 pengguna aktif terverifikasi. Temuan ini menunjukkan bahwa integrasi pemerataan sumber belajar, mentoring humanistik, dan teknologi AI dapat membentuk ekosistem pendidikan komunitas yang inklusif, adaptif, dan berkelanjutan.
TELISIK+ 2026 is a community-based educational initiative designed to address inequality in access to preparation for the National Student Admission Selection (SNPMB) while equipping participants with academic capacity and future-oriented skills. The program adopts a high-tech meets high-touch approach that combines AI-supported learning with direct human mentoring, and comprises four interconnected programs: the UTBK Book Assistance Equity Program, the Online UTBK Learning Program, the Scientific Writing, Research, and Publication Program, and the AI-Based Educational Website Development Program. The activities were conducted online from January 16 to April 20, 2026, following the planning, organizing, actuating, and controlling (POAC) framework and evaluated through a descriptive-evaluative approach using the RE-AIM framework. The implementation resulted in 36 participants receiving UTBK preparation books, 36 learning sessions delivered across seven subtests by 18 tutors, and 24 participants completing all subtests of the practice test with a mean score of 616.3 and high instrument reliability (Cronbach's alpha of 0.897). A total of 34 participants were admitted to public higher education institutions through the 2026 SNBP pathway. The developed platform has archived 2,273 UTBK items and 1,950 SKD items, reaching 551 verified active users. These findings indicate that integrating equitable learning resources, human-centered mentoring, and AI technology can form an inclusive, adaptive, and sustainable community-based educational ecosystem.
Abstract:Environmental education in early childhood plays an important role in developing children’s environmental care character through meaningful real-life experiences. This study aims to analyze the implementation of the Eco-Schools…
o-Schools program in fostering environmental care character among young children at POS PAUD Dahlia Mangli Randudongkal, Pemalang Regency. This research employed a descriptive qualitative approach, with data collected through observations, documentation, and field notes. The research subjects involved young children and teachers as facilitators of environment-based learning activities. The findings indicate that the Eco-Schools program was implemented through various concrete activities, including planting and caring for plants, watering plants, feeding animals, maintaining environmental cleanliness, and developing habits of disposing of waste properly. These activities provided children with direct experiences in understanding the relationship between humans and the environment while fostering values of responsibility, discipline, care, cooperation, and empathy toward living organisms. This study demonstrates that Eco-Schools can serve as an effective character-based learning strategy in early childhood education by integrating environmental education into the daily school culture. Sustainable implementation involving teachers, parents, and the community is essential to strengthen environmental awareness and care from an early age.
Abstract:Siswa dengan disabilitas intelektual sedang memerlukan stimulasi motorik yang sesuai agar perkembangan kemampuan geraknya dapat berkembang secara optimal. Salah satu aktivitas yang berpotensi memberikan stimulasi tersebut…
t adalah permainan bola basket yang melibatkan aspek kekuatan, koordinasi, keseimbangan, kecepatan, dan kelincahan. Penelitian yang dilakukan berfokus pada analisis pengaruh latihan bola basket terhadap peningkatan kemampuan motorik kasar siswa kelas VII SMPLB di SLB Harapan Pelangi Jember. Pendekatan kuantitatif diterapkan dalam penelitian ini melalui metode eksperimen dengan rancangan One Group Pretest-Posttest Design. Empat siswa kelas VII di libatkan sebagai partisipan penelitian dengan teknik sampling jenuh. Pengumpulan data diperoleh dengan memanfaatkan instrumen observasi dan tes kemampuan motorik kasar yang dilakukan pada tahap sebelum dan setelah perlakuan diberikan. Analisis data meliputi statistik deskriptif, uji normalitas Shapiro-Wilk, dan uji paired sample t-test. Perbandingan hasil pretest dan posttest menunjukkan bahwa rata-rata kemampuan motorik kasar meningkat dari 8,75 menjadi 19, dengan peningkatan sebesar 10,25 poin. Adapun analisis paired sample t-test menunjukkan probabilitas (p-value) sebesar 0,001 (<0,05), yang mengindikasikan adanya pengaruh perlakuan terhadap kondisi sebelum diberikan perlakuan dan setelah perlakuan diberikan. Temuan tersebut menunjukkan bahwa penerapan latihan bola basket berkontribusi terhadap peningkatan kemampuan motorik kasar siswa berkebutuhan khusus penyandang disabilitas intelektual sedang.
Students with moderate intellectual disabilities require appropriate motor stimulation to ensure optimal motor development. One activity that has the potential to provide such stimulation is basketball, which involves aspects of strength, coordination, balance, speed, and agility. This research focused on analyzing the effect of basketball training on improving gross motor skills of seventh-grade students at Harapan Pelangi Special Needs School in Jember. A quantitative approach was applied in this study through an experimental method with a One Group Pretest-Posttest Design. Four seventh-grade students were involved as research participants using a saturated sampling technique. Data collection was obtained using observation instruments and gross motor skills tests conducted before and after the treatment was given. Data analysis included descriptive statistics, the Shapiro-Wilk normality test, and a paired sample t-test. Comparison of the pretest and posttest results showed that the average gross motor skills increased from 8.75 to 19, with an increase of 10.25 points. The paired sample t-test analysis showed a probability (p-value) of 0.001 (<0.05), indicating an effect of the treatment on pre-treatment and post-treatment conditions. These findings indicate that the implementation of basketball training contributed to improving the gross motor skills of students with special needs and moderate intellectual disabilities.
Abstract:Transformasi sistem kesehatan membutuhkan pendekatan yang tidak hanya berorientasi pada pelayanan kuratif, tetapi juga pada pencegahan, ketahanan gizi, dan pemanfaatan data secara presisi. Kajian ini bertujuan menganalisis…
is integrasi ketahanan gizi berbasis Precision Public Health dalam memperkuat resiliensi sistem kesehatan. Dengan pendekatan mixed methods sequential explanatory, kajian mengombinasikan analisis kuantitatif dan kualitatif untuk menilai hubungan antara integrasi data gizi, stratifikasi risiko, tata kelola kesehatan, dan kapasitas adaptif sistem. Hasil kajian menunjukkan bahwa ketahanan gizi perlu diposisikan sebagai determinan strategis dalam transformasi sistem kesehatan, bukan sekadar luaran kebijakan pangan. Integrasi data gizi dengan data sosial, lingkungan, epidemiologi, dan spasial memungkinkan intervensi yang lebih tepat sasaran, pengembangan sistem peringatan dini, serta peningkatan kapasitas sistem menghadapi krisis global. Temuan ini memperluas kerangka Precision Public Health dan Health System Resilience dengan menempatkan ketahanan gizi sebagai penghubung antara sistem pangan, data, pencegahan penyakit, dan tata kelola kesehatan. Implikasinya adalah perlunya interoperabilitas data lintas sektor dan kebijakan kesehatan yang lebih prediktif, adaptif, berkeadilan, dan berkelanjutan.
The transformation of the health system requires an approach that focuses not only on curative care, but also on prevention, nutritional resilience, and the precise use of data. This study aims to analyse the integration of nutritional resilience based on Precision Public Health in strengthening the resilience of the health system. Using a sequential explanatory mixed-methods approach, the study combines quantitative and qualitative analyses to assess the relationship between the integration of nutritional data, risk stratification, health governance, and the system’s adaptive capacity. The study’s findings indicate that nutritional resilience must be positioned as a strategic determinant in health system transformation, rather than merely an outcome of food policy. The integration of nutritional data with social, environmental, epidemiological, and spatial data enables more targeted interventions, the development of early warning systems, and an enhancement of the system’s capacity to cope with global crises. These findings expand the frameworks of Precision Public Health and Health System Resilience by positioning nutritional resilience as a link between food systems, data, disease prevention, and health governance. The implications are the need for cross-sectoral data interoperability and health policies that are more predictive, adaptive, equitable, and sustainable.
Abstract:Program Pendaftaran Tanah Sistematis Lengkap (PTSL) merupakan program strategis nasional untuk mempercepat pendaftaran tanah guna mewujudkan kepastian hukum hak atas tanah. Pelaksanaannya yang bersifat massal berpotensi…
menimbulkan ketidaksesuaian data fisik dan data yuridis yang dapat memengaruhi keabsahan sertipikat. Penelitian ini bertujuan menganalisis bentuk-bentuk ketidaksesuaian data fisik dan data yuridis dalam pelaksanaan PTSL, akibat hukumnya terhadap keabsahan sertipikat hak atas tanah, pihak yang berpotensi bertanggung jawab, serta mekanisme penyelesaiannya. Penelitian menggunakan metode yuridis normatif dengan pendekatan perundang-undangan, konseptual, kasus, dan komparatif, melalui penelaahan bahan hukum primer, sekunder, dan tersier yang didukung dokumentasi kasus pada Kantor Pertanahan Kabupaten Serang. Hasil penelitian menunjukkan bahwa ketidaksesuaian data fisik berupa perbedaan luas, batas, dan tumpang tindih bidang, serta ketidaksesuaian data yuridis berupa kekeliruan identitas, alas hak, dan klaim ganda berpotensi menimbulkan cacat administratif maupun cacat yuridis pada sertipikat. Panitia Ajudikasi PTSL berkedudukan sebagai pihak yang bertanggung jawab utama secara kelembagaan, dengan dukungan Satuan Tugas Fisik dan Satuan Tugas Yuridis; Kantor Pertanahan dan pemohon dapat pula dimintai pertanggungjawaban apabila kelalaian atau kesalahan terbukti. Penyelesaian dilakukan secara bertahap sesuai jenis permasalahan, mulai dari pembetulan data dan mediasi hingga pembatalan sertipikat melalui mekanisme administratif atau peradilan.
The Complete Systematic Land Registration (PTSL) program is a national strategic program intended to accelerate land registration and realize legal certainty over land rights. Its mass implementation may result in discrepancies between physical and juridical data that can affect the validity of land title certificates. This study analyzes the forms of physical and juridical data discrepancies in PTSL, their legal consequences for certificate validity, potentially liable parties, and available settlement mechanisms. This normative juridical study employs statutory, conceptual, case, and comparative approaches by examining primary, secondary, and tertiary legal materials supported by case documentation from the Serang Regency Land Office. The findings indicate that discrepancies in physical data, including differences in area, boundaries, and overlapping plots, as well as discrepancies in juridical data, including identity errors, defective bases of title, and multiple claims, may result in administrative and/or juridical defects in certificates. The PTSL Adjudication Committee bears primary institutional responsibility, assisted by the Physical and Juridical Task Forces, while the Land Office and applicants may also be held responsible where negligence or fault is proven. Settlement is conducted progressively according to the nature of the problem, ranging from data correction and mediation to certificate cancellation through administrative or judicial mechanisms.