In the Kutai Basin area, seasonal changes such as high rainfall can significantly increase groundwater content, so that the effect of water content on the shear strength of claystone, increasing water content in rocks tends to decrease shear strength. Water in the pores or fractures can increase pore water pressure and reduce effective normal stress. Shear strength is one of the most important mechanical parameters used to assess soil and rock stability, this parameter is very important in slope stability analysis, foundation planning, and various civil engineering and mining applications. Therefore, this study was conducted to determine whether the water content in rocks can affect the strength of rocks in receiving shear forces. The method used in this study is more quantitative and specific to the effect of water content on the shear strength of claystone in this area. Increasing water content in rocks tends to reduce shear strength. This study was conducted by taking claystone samples from several locations in the Kutai Basin. Data collection in the form of primary data and secondary data for testing physical properties and testing mechanical properties, in testing physical properties, the water content value will be taken as supporting data which is one of the factors that affect rock strength, in testing mechanical properties, claystone shear strength data will be taken. From the results of the physical properties test calculations, the air content in each Formation is obtained, namely, in the Kampungbaru Formation the minimum air content value is 15.54% and the maximum is 20.17%, in the Balikpapan Formation the minimum air content value is 10.21% and the maximum is 12,88%, in the Palaubalang Formation the minimum air content value is 10.49% and the maximum is 22.87%. The results of the strength of the claystone in receiving shear forces in the Kutai Basin are the Muara Jawa location 0.486MPa, Tanah Datar location 0.500 MPa, Sanga-sanga location 0.333 MPa, Muara Badak location 0.269, Air Putih location 0.711MPa, Mugirejo location 0.021 MPa and Lempake location 0.092 MPa.

Durability is defined as a measure of a rock's resistance to weathering and disintegration when the rock undergoes weathering processes over a short period of time. The susceptibility of rocks to disintegration is related to their low durability. Rock durability is often measured using the slake durability test. The slake durability test is widely used to assess physical changes resulting from wetting-drying processes (Franklin and Chandra, 1972). Therefore, slake durability testing is conducted to understand the weathering of rocks caused by heat and water, particularly clay stones which are one of the constituent rocks on a slope. The sampling location is around Sanga-sanga and Muara Badak. Sampling was conducted with coordinate points and the Balikpapan and Kampungbaru formations. The claystone samples taken were then brought to the Mineral and Coal Technology Laboratory of the Engineering Faculty of Mulawarman University for Slake Durability tests. In this study, the lowest index value obtained was 45.7% and the highest value was 93%, indicating high to very high durability. The difference in the durability index values of claystone at the research locations indicates the presence of variables that can affect the slake durability index values of the claystone in the Balikpapan and Kampungbaru formations, including grain size and mineral content as well as geological conditions at the research site. Based on the results of the claystone durability tests, the durability index value (Id2) was obtained, indicating that the sandstone at the research location falls into the classification of high to low.

Kantor Imigrasi Kelas I TPI Jambi adalah lembaga pemerintah yang bertugas melayani masyarakat terkait masalah imigrasi, seperti pengajuan paspor, izin tinggal, dan pengawasan lalu lintas orang antar negara. Saat ini, pencatatan nomor surat keluar masih dicatat secara manual menggunakan buku agenda, yang sering menyebabkan duplikasi nomor surat, kesalahan pencatatan, dan keterlambatan dalam pengambilan data. Untuk mengatasi masalah ini, dirancang sebuah sistem informasi yang bekerja melalui situs web yang mengelola penomoran surat keluar secara otomatis dan terstruktur. Sistem ini menggunakan metode pengembangan prototipe dan alat pemodelan UML (Unified Modeling Language). Hasil dari desain ini adalah sistem informasi yang mampu mengelola penomoran surat keluar secara otomatis, terintegrasi, dan disimpan dalam database yang mudah dan cepat untuk diakses. Fitur utama dari sistem ini mencakup pembuatan format penomoran otomatis sesuai dengan jenis dan klasifikasi surat, penyimpanan arsip digital surat, pencarian data berdasarkan berbagai kriteria, dan manajemen pengguna. Dengan implementasi sistem ini, diharapkan proses administrasi korespondensi di Kantor Imigrasi Kelas I TPI Jambi menjadi lebih cepat, efisien, dan akurat.

Pemerintah Indonesia secara berkelanjutan menjalankan berbagai program bantuan di sektor peternakan sebagai bagian dari upaya meningkatkan ketahanan pangan dan kesejahteraan peternak. Namun, implementasi program tersebut masih menghadapi sejumlah tantangan, seperti kurangnya integrasi data, ketidaktepatan sasaran, dan terbatasnya alat bantu pengambilan keputusan berbasis data. Penelitian ini bertujuan untuk mengintegrasikan data peternakan ke dalam sebuah Sistem Pendukung Keputusan (Decision Support System) yang dapat digunakan oleh pemerintah dalam perencanaan dan pelaksanaan program bantuan secara lebih efektif. Metode penelitian yang digunakan adalah Mixed Method dengan pendekatan Exploratory Sequential Design, yang dimulai dengan pengumpulan data kualitatif melalui wawancara dan studi kasus untuk menggali kebutuhan serta tantangan yang dihadapi oleh pemangku kepentingan di sektor peternakan. Hasil dari tahap eksploratif ini digunakan sebagai dasar dalam pengembangan sistem berbasis data kuantitatif yang mengintegrasikan informasi peternakan dari berbagai sumber. Hasil penelitian ini diharapkan dapat memberikan kontribusi nyata dalam optimalisasi penyaluran bantuan pemerintah di bidang peternakan, sekaligus mendukung transformasi digital dalam pengelolaan data sektor pertanian. Implikasi dari penelitian ini juga membuka peluang untuk pengembangan sistem serupa di sektor lain yang membutuhkan pengambilan keputusan berbasis data dan spasial.

The rapid evolution of Generative AI has opened up numerous possibilities to enhance organizational decision-making through improved operational efficiency, innovation, and data analysis accuracy. However, companies in developing countries face challenges such as underdeveloped digital infrastructure, labor shortages, data security risks, and regulatory uncertainty. These factors create a gap between theoretical benefits and practical implementation. This study explores opportunities, key risks, and organizational readiness for Generative AI adoption in business decision-making within developing countries. Using a mixed-method sequential design, phase I involved a quantitative survey of 120 companies across five nations, while phase II included interviews with 15 key informants. Data were analyzed using Structural Equation Modeling and NVivo, with interactive visualization aiding in framework development. Findings indicate that Generative AI could improve decision-making efficiency by 89% and reduce operational costs by 15%. Top risks include data security (score: 4.41) and regulatory ambiguity (score: 4.27). Organizational readiness was high in managerial support (score: 4.01) but low in internal regulation (score: 3.67). The proposed Strategic Generative AI Adoption Framework integrates innovation diffusion, risk management, and readiness, offering practical insights for adaptive AI adoption in developing countries.

Digital transformation drives manufacturing companies to adopt artificial intelligence (AI) as a strategy to improve operational efficiency and competitiveness. However, the effectiveness of AI integration is influenced not only by technological readiness but also by internal organizational capabilities and external environmental pressures. This study aims to analyze how technological, organizational, and environmental factors contribute to the successful implementation of AI in the manufacturing sector, emphasizing the unique dynamics in developing countries such as Indonesia. This study uses a mixed methods approach with a sequential explanatory design. Quantitative data were collected through surveys of 85 respondents from various manufacturing companies in Indonesia, including operational managers, information technology managers, and professionals related to AI implementation. Analysis was conducted using PLS-SEM to test the relationships between variables. Subsequently, qualitative data were obtained through in-depth interviews with 10 key informants who have direct experience in AI planning and integration in their companies. The results show that organizational factors, especially managerial support and human resource competence, play the most significant role in driving the success of AI integration. Aspects of transformational leadership and work culture readiness also emerge as determining factors for the sustainability of adoption. This study expands the application of TOE and RBV theories in the context of developing countries and provides practical implications for the industry in formulating more adaptive and contextual technology adoption strategies.

On the one hand, amid the digital transformation of the financial sector, opportunities have increased for Micro, Small, and Medium Enterprises (MSMEs); on the other hand, challenges remain in technology adaptation and sustainable financial management, especially in a post-crisis era. Thus, given the ongoing push toward strengthening economic resilience, an urgent need arises to examine how far digital financial intelligence may act as a key for the survival and growth of MSMEs. The focus of this study is to examine the impact of digital financial intelligence-the financial literacy, attitude toward financial technology, and capability to use digital financial applications-on MSME economic resilience. Data were collected for the survey using a quantitative approach, which consisted of an online questionnaire administered to 220 MSME actors in Indonesia, who were digital financial services users for a minimum of one year. Participants were selected based on purposive sampling, while data analysis was performed using Structural Equation Modeling (SEM) based on Partial Least Squares (SmartPLS) supported by SPSS, Tableau, and MonkeyLearn. The results of the analysis reveal that all dimensions of digital financial intelligence have a significant relationship with economic resilience, particularly in the tactile domains of crisis adaptation, recovery, and strategic decision-making. Overall, these results now show life documents the need for greater emphasis on literacy and digital readiness as the bedrock of MSME sustainability. This academic contribution is theoretically developing an integrated model of technology and finance while practically implementing the policy implications that would strengthen an inclusive and adaptive MSME digital ecosystem.

The development of digital technology has transformed the work landscape, especially with the increasing prevalence of remote work systems in Indonesia’s digital sector. However, the high intensity of technology use in the remote work context also poses the risk of digital burnout, which is mental and emotional exhaustion due to excessive exposure to technological demands. This phenomenon potentially affects employee behavior, including extra-role behaviors known as Organizational Citizenship Behavior (OCB). This study aims to explore the relationship between digital burnout and OCB among remote workers in the digital sector, while also understanding how technological pressure influences work dynamics and employee contributions beyond formal tasks. The research method uses a quantitative approach with purposive sampling technique, targeting 150 to 300 remote workers who work at least three days per week and heavily rely on digital platforms such as Zoom, Slack, and Google Workspace in their daily activities. Data were collected through online surveys and analyzed using SmartPLS to test the relationships between variables with Partial Least Squares Structural Equation Modeling (PLS-SEM). The results indicate that although digital burnout is quite prevalent, employees still demonstrate positive OCB, indicating the presence of adaptation mechanisms and strong organizational commitment. These findings enrich the understanding of how remote workers manage technological pressure while maintaining extra contributions in a dynamic digital work environment. The contribution of this study lies in providing new insights into the interaction between digital burnout and OCB in the digital work era, as well as practical implications for human resource management in designing strategies to support the well-being and productivity of remote employees. This study encourages the development of more humane and sustainable work policies in facing the challenges of digital transformation.

Penelitian ini bertujuan untuk menganalisis pengaruh sistem informasi akuntansi dan motivasi kerja terhadap kinerja pegawai pada Badan Pendapatan Daerah (Bapenda) Kota Kendari. Metode penelitian yang digunakan adalah kuantitatif dengan teknik analisis regresi linear berganda. Data diperoleh melalui kuesioner yang disebarkan kepada 50 responden yang memenuhi kriteria purposive sampling. Hasil penelitian menunjukkan bahwa sistem informasi akuntansi dan motivasi kerja berpengaruh positif dan signifikan terhadap kinerja pegawai, baik secara parsial maupun simultan. Koefisien determinasi menunjukkan bahwa 58,3% variasi dalam kinerja pegawai dapat dijelaskan oleh kedua variabel bebas tersebut. Temuan ini mengindikasikan bahwa penguatan sistem informasi dan peningkatan motivasi kerja menjadi strategi efektif dalam meningkatkan kinerja pegawai di lingkungan birokrasi daerah.

Purpose: This study aims to estimate and evaluate per capita expenditure at the subdistrict level in Garut Regency by employing unit-level Small Area Estimation (SAE) techniques, specifically utilizing the Empirical Best Linear Unbiased Predictor (EBLUP) and the Empirical Best Predictor (EBP) methods.
Methods: The data used in this study are socio-economic data, specifically per capita household expenditure in Garut Regency. Socio-economic data generally skew positively rather than the normal distribution, so a method that can approximate or come close to the normal distribution is needed, for example, log-normal transformation. To improve the performance of EBLUP, which may lead to inefficient estimators because of violation of the assumption of normality, this study proposes the Empirical Best Predictor (EBP) method. It handles positively skewed data by applying log-normal transformation to sample data so that it more closely conforms to the desired distribution.
Result: The EBP results are more stable than EBLUP since EBLUP is highly sensitive to outliers, and in cases where the normality assumption is violated, it produces a significant mean square error and inefficient estimators. Evaluating the estimates with both EBLUP and EBP shows Relative Root Mean Squared Error (RRMSE) values above 25%, especially in the subdistricts of Pamulihan, Sukaresmi, and Kersamanah. This is probably due to the household samples being taken in these three subdistricts being comparatively small compared to the other.
Novelty: In this research, we use EBP to improve the performance of EBLUP, which produces inefficient estimators when the normality assumption is violated.