OJS UNPATTI Publication Center (Universitas Pattimura)
Not a member yet
8549 research outputs found
Sort by
TAX HAVEN DAN ILUSI TRANSPARANSI: BAGAIMANA PERUSAHAAN MENGAKALI PELAPORAN KEUANGAN?
Get PDFPenelitian ini mengkaji peran tax haven dalam menciptakan ilusi transparansi melalui manipulasi pelaporan keuangan oleh perusahaan multinasional. Dengan menggunakan pendekatan Systematic Literature Review, artikel ini menyintesis berbagai studi yang mengungkap strategi pengalihan laba, pemanfaatan struktur kepemilikan offshore, dan penerapan teknik transfer pricing guna mengurangi beban pajak. Temuan penelitian menunjukkan bahwa perusahaan mengoptimalkan struktur perpajakannya dengan memindahkan aset dan pendapatan ke yurisdiksi yang menawarkan tarif pajak rendah serta regulasi yang longgar, sehingga menghasilkan kesan transparansi yang menutupi praktik penghindaran pajak yang sesungguhnya. Selain itu, keterbatasan dalam pertukaran informasi antarnegara semakin memperburuk ketimpangan fiskal antara negara maju dan berkembang. Analisis ini menegaskan bahwa penggunaan tax haven tidak hanya memberikan manfaat fiskal jangka pendek bagi perusahaan, tetapi juga menimbulkan dampak signifikan terhadap keadilan ekonomi global. Penelitian ini memberikan kontribusi teoretis dan praktis dalam mengidentifikasi celah regulasi yang memungkinkan manipulasi tersebut, serta menekankan urgensi pembenahan sistem perpajakan global
Pengaruh Investasi Hijau Terhadap Kepatuhan Akuntansi Pajak di Perusahaan Manufaktur
Get PDFPenelitian ini bertujuan untuk menganalisis pengaruh investasi hijau terhadap kepatuhan akuntansi pajak di perusahaan manufaktur. Investasi hijau, yang berfokus pada penggunaan sumber daya secara berkelanjutan dan ramah lingkungan, diharapkan dapat meningkatkan kesadaran perusahaan untuk mematuhi peraturan perpajakan yang berlaku. Kepatuhan akuntansi pajak merupakan salah satu faktor penting dalam keberlanjutan operasional perusahaan, di mana kewajiban perpajakan yang dipenuhi dengan baik dapat meningkatkan reputasi dan citra perusahaan. Penelitian ini menggunakan pendekatan kuantitatif dengan analisis regresi untuk menguji hubungan antara investasi hijau dan kepatuhan pajak pada perusahaan manufaktur yang menerapkan praktik ramah lingkungan. Hasil penelitian menunjukkan bahwa terdapat pengaruh positif antara investasi hijau dengan tingkat kepatuhan pajak, yang mengindikasikan bahwa perusahaan yang berinvestasi pada keberlanjutan cenderung memiliki kesadaran yang lebih tinggi terhadap kewajiban perpajakan mereka. Penelitian ini memberikan implikasi penting bagi perusahaan manufaktur untuk lebih mengintegrasikan investasi hijau dalam strategi bisnis mereka, serta bagi pembuat kebijakan untuk merumuskan insentif yang mendorong kepatuhan pajak melalui praktik keberlanjutan
PENERAPAN METODE HANDLUNGSORIENTIERUNG DALAM PEMBELAJARAN BAHASA JERMAN PADA SMA DI KOTA SORONG
Get PDFThis study aims to describe the implementation of the Handlungsorientierung approach in German language teaching at the senior high school level. The research employed a qualitative descriptive method using questionnaires distributed to German language teachers in various high schools. The findings indicate that although most teachers are not academically familiar with the theory of Handlungsorientierung, they have implemented its principles through learning activities such as role-playing, product creation (videos, emails, posters), and other collaborative tasks. Teachers consider this approach effective, enjoyable, and capable of increasing student engagement. However, its implementation is challenged by limited instructional time and insufficient facilities. Based on these findings, it is recommended that teacher training be enhanced and supporting infrastructure be improved to enable the more optimal application of this approach
The Performance of the Regional Disaster Management Agency of North Maluku Province in Disaster Logistics Distribution Services in Central Halmahera Regency
Get PDFThe purpose of this research is to understand and explain the performance of the BPBD of North Maluku Province in the logistics distribution service in Messa Village and Kotalo Village, East Weda District, Central Halmahera Regency. This research uses a qualitative descriptive method aimed at describing events or activities within an institution and then elaborating on the issues being studied through several relevant indicators. Data collection techniques through; observation, interviews, documentation, data analysis techniques through; data reduction, data presentation, and conclusion, drawing, or verification. Based on the research results; first, the productivity of the BPBD of North Maluku Province in the logistics distribution service in Messa and Kotalo Villages has not been effectively implemented due to limited resources, Second, the quality of service has not been optimally carried out because the distribution of logistics does not yet have SOPs that are by field conditions, and the logistics distribution in terms of timeliness is still not appropriate because it takes about 4 days to reach the disaster-affected location. Third, the responsiveness of the BPBD of North Maluku Province in the logistics distribution service process in Messa Village and Kotalo Village has been very good. The team from the BPBD of North Maluku Province consistently responds well to the needs of the disaster-affected community, and fourth, the accountability of the BPBD of North Maluku Province's performance has been carried out and accounted for by the regulations and is reported through SAKIP and LKIP
MODEL SELECTION FOR B-SPLINE REGRESSION USING AKAIKE INFORMATION CRITERION (AIC) METHOD FOR IDR-USD EXCHANGE RATE PREDICTION
Get PDFExchange rate data is a collection of information about the exchange rate the foreign currency which collected by time. Autoregressive Integrated Moving Average (ARIMA) is a well-known time series analysis. Several assumptions that need to be checked before running the ARIMA model are stationarity, normality, and white noise. B-spline regression is a method of modeling time series data without considering assumptions. This research aims to create a forecasting model for Rupiah exchange rate against US Dollar using B-spline regression. The B-spline regression model was generated with a combination of degrees two to four and a maximum of four knots. After that, the optimal model is selected using the Akaike Information Criterion (AIC) score. The performance of the selected model is validated using Mean Absolute Percentage Error (MAPE) values. The optimal degree is 3 (quadratic) and the optimal number of knot points is two-knot points with an AIC value of 857.8322 and a MAPE value of 0.0148376. The best model is
HOLT-WINTER METHOD FOR FORECASTING LIQUID ALUMINIUM SULFATE USAGE FOR PROBABILISTIC INVENTORY MODELING Q WITH ERLANG DISTRIBUTION
Get PDFWater is a natural resource important for life and daily activities. Water distributed by the Regional Drinking Water Company (PDAM) should include a coagulation process using liquid aluminum sulfate as a coagulant before it can be consumed. Therefore, this research aims to predict the need for liquid aluminum sulfate in PDAM from 2023 to 2024 using Holt-Winter's method. It also aims to evaluate the optimum liquid aluminum sulfate chemical inventory policy using Q probabilistic inventory model with Normal and erlang probabilistic distributions in PDAM. The data was obtained from Tirta Musi PDAM in Palembang City, Indonesia. The results of forecasting liquid aluminum sulfate demand level data with the Holt-Winter multiplicative method provide the smallest MAPE value. The erlang probability distribution assumption has been met through the Kolmogorov Smirnov test method. The erlang probabilistic inventory model provides a more optimal policy solution than the normal probabilistic inventory model, with minimum total cost and higher service level
CONSUMER PRICE INDEX MODELING USING A MIXED TRUNCATED SPLINE AND KERNEL SEMIPARAMETRIC REGRESSION APPROACH
Get PDFSome semiparametric regression model approaches include spline, kernel, Fourier series, and wavelet. Semiparametric regression modelling can involve more than one independent variable (multivariable), a parametric approach is usually combined with one of the nonparametric approaches, such as combining a parametric approach with a nonparametric kernel. If a consumer price index model can be built based on the variables that influence it, predictions of consumer price percentages can be made, which it is hoped will help the government determine policies to control consumer price inflation, especially in NTB Province. The data used in this research includes the consumer price index and the factors that influence it according to districts/cities in NTB Province from 2022 to April 2024. The data source was obtained from secondary data at BPS NTB Province. This research design uses a mixed semiparametric approach of truncated spline and kernel regression. Based on calculations, the predicted results of the consumer price index in NTB Province show that the predicted data graph is very close to the actual data . Modelling the consumer price index in NTB Province is a model with 2 knot points, where the model efficiency has the smallest GCV value of 0.001507. The model goodness value is 0.99, meaning that the variables used can explain 99% of the model variability
Exploring the Lazy Witness Complex for Efficient Persistent Homology in Large-Scale Data
No full textIn this paper, topological data analysis (TDA) techniques have been explored, with a focus on the selection of the Witness Complex and Persistent Homology of some nested families of Lazy Witness Complex as approximations for analyzing complex datasets. The Witness Complex was chosen for its efficiency and scalability, as it constructs a simplicial complex using landmark points, reducing computational load compared to methods like the Vietoris-Rips and Čech complexes. This makes it suitable for large, high-dimensional datasets, accurately representing the dataset's intrinsic geometry even with varying data densities. Persistent Homology was then reviewed with the aim of calculating it on some nested families of the Witness Complex. Subsequently, the nested families of the Lazy Witness Complex were introduced mathematically, with an example of the entire construction process for a well-known point cloud dataset. For this purpose, 50 points were generated randomly from a circle, and persistent diagrams of the point cloud data were analyzed to understand and compare the behavior among the approximations of the Witness Complex after choosing 10 landmarks using the Maxmin method. Since the families are nested, the filtration process became faster for each successive family, thus reducing computational complexity. For all three cases , the persistent barcodes indicated the same shape of the dataset. This study may help in choosing the suitable family of the Witness Complex over Persistent Homology to balance computational feasibility with topological accuracy, enabling efficient handling of large datasets while preserving important topological features. This approach allows for extracting meaningful insights from complex data while effectively managing computational resources
Penyelesaian Unit Commitment Problem (UCP) Menggunakan Algoritma Genetika
No full textThe purpose of this research is to solve the Unit Commitment Problem (UCP), which is a critical task in power system optimization. The UCP involves determining the optimal scheduling of power generating units over a specified time horizon to meet the electricity demand while minimizing costs and satisfying operational constraints. In this study, a Genetic Algorithm (GA) method is proposed to solve the UCP efficiently. GA is inspired by the process of natural selection and evolution and is often used to solve complex optimization problems where traditional methods may be inefficient. The algorithm proceeds through several steps, namely parameters initialization, generating population, modification, calculating fitness function, parent selection, crossover, and mutation. The implementation of GA to solve UCP using C++ includes four different scenarios: a system with 4 units, 5 units, 10 units, and 26 units. The results obtained from the implementation of the GA on the different data sets indicate that the more iterations and the bigger initial population, the smaller the solution in the form of the total cost incurred
