Input Components Research Articles

Technical Efficiency of Smallholder Dairy Farms in Rural Assam: A Double Bootstrap Data Envelopment Analysis Approach

Analysing a sample of 245 smallholder rural dairy farms in Assam, it is found that most dairy farms operate at technically inefficient level. The analysis of input-oriented conventional and bias-corrected data envelopment analysis (DEA) procedure entails that most farms produce milk below the production frontier with underlying scope of reducing variable input component up to 50% to retain the same level of output. Further, exploring the bias-corrected efficiency score determinants, it is found that input use decision is superior for male-headed households, farms that are involved in fodder cultivation, farms with proximity to markets and resource poor farmers whose dairy farming is mostly a principal source of income. The findings of the study indicate presence of ample scope and potential to leverage the technical efficiency (TE) and thereby increase the socio-economic wellbeing of the smallholder dairy farm households in the state. The study also points towards the need for sensitising farmers about the improved dairy farm technologies such as artificial insemination to produce more crossbred cattle along with building a strong network of extension machineries.

Evaluation of Librarian Competency Improvement Training in Utilizing SLIMS 9

This study aims to determine the application of each component of the CIPP evaluation, namely; (1) Context, (2) Input, (3) Process, and (4) Product on the results of training to increase librarian competency in using Slims 9 at SMA Negeri 1 Bengkulu Tengah. This study uses a qualitative using the context, input, process, product evaluation model. The data collection techniques used in this research are through interviews, observation and documentation studies. Data analysis techniques are carried out by condensing data, presenting data, and drawing conclusions. The results of the research show that the application of the context component is used to collect information regarding the needs that will be needed, the input component is used to collect information and input regarding how best to organize decisions and how to manage available resources, the process component is used to collect information on how to implement the training program, provide an overview of the smooth running of the program being implemented, as well as the application of product components used to collect information about the results of the training program being implemented.

Spatio-Temporal Analysis of Net Anthropogenic Phosphorus Inputs (NAPIs) and Their Impacts in Ningxia Hui Autonomous Region Using Monte Carlo Simulations and Sensitivity Analysis

This study employed the Net Anthropogenic Phosphorus Inputs (NAPI) model to assess the impact of human activities on phosphorus input in a watershed, analyzing county-level statistical data and NAPI model parameters from 1991 to 2020. The Monte Carlo method was used for a quantitative analysis of the model parameters’ effects on each NAPI component and the overall simulation results. The sensitivity index method identified each component’s sensitive parameters. The study found that the lowest NAPI value was 454 kg/(km2·a) in 1991 and the highest was 1336 kg/(km2·a) in 2003. NAPI in Ningxia showed an overall upward trend from 1991 to 1999, a slight decrease from 1999 to 2003, and a slight increase from 2003 to 2020, with fertilizer being the main contributing factor, accounting for 77.4% of the total input. On a spatial scale, NAPI in Ningxia was significantly correlated with land use patterns, showing higher values in the northern and southern regions compared to the central part. The NAPI values derived from Monte Carlo simulations with appropriate parameters ranged from −24.83% to 31.49%. The study highlighted the net food and feed imports component as having the highest uncertainty, impacting simulation results within a range of −23.89% to 53.98%. It was observed that the larger a component’s proportion in the NAPI model, the more sensitive its parameters, with the phosphorus fertilizer (Pfer) component’s parameters being notably more sensitive than those of the food/feed phosphorus input and the non-food phosphorus input (Pnf) components. These findings can inform phosphorus pollution control policies in Northwest China, while the selection of sensitive parameters provides a useful reference for future NAPI research in other regions.

Implementation of Drug Logistics Management in The Pharmacy Installation of Surya Insani Hospital Pasir Pangaraian Rokan Hulu Regency

Background: The availability of drugs currently creates demand for medical services. Drug logistics management in hospitals includes stages such as planning, procurement, storage, distribution, processing, evaluation and monitoring, and are interdependent on each other so that they must be well coordinated so that each stage can run optimally. Objectives: Knowing the Implementation of Drug Logistics Management in Hospital Pharmacy Installations Surya Insani Research method: Qualitative descriptive research with a cross-sectional approach. Results: In the input component, There is a positive and significant relationship between training and employee performance. To ensure the quality of supplies and extend the life of equipment, there must be a sufficient budget for purchasing drugs and maintaining drug storage facilities and other related equipment. Guaranteed to be sensitive to measurements and meet requirements, lighting, and calibrate certain equipment annually. In the Process component, planning, procurement, storage, distribution, processing, control. The composition of output, the availability of drugs at the Surya Insani is in accordance with demand, but there are still some drugs that are sometimes not available because the distributor or PBF warehouse runs out of stock. The results of the study also showed that the adequacy of planned drugs and the number of drugs available during the inventory period are important and appropriate when needed. In addition, at the Surya Insani Pasir Pangaraian Hospital. There are still many damaged or expired drugs. This shows that drug management, both input and drug administration processes, still need to be evaluated so that drug management at the Surya Insani Pasir Pangaraian Hospital can be effective and efficient. Conclusion: The availability of drugs at the Pharmacy Installation of Surya Insani Hospital is in accordance with needs.

Evaluation of the Character Education Strengthening Program in Elementary Schools in View from CIPP (Context, Input, Process, Product)

This research aims to evaluate the context, input, process, and products in the character education strengthening program at SD Muhammadiyah 05 Pekanbaru. The approach used in this research was qualitative with descriptive methods. Data collection techniques were carried out through observation, interviews, and documentation. Meanwhile, data analysis techniques included reduction, data presentation, and drawing conclusions. The results of this research showed that the character education program at SD Muhammadiyah 05 Pekanbaru had proven to be effective. This can be seen from several aspects: First, the context aspect, where most of it has been fulfilled well. Program procedures, which include a clear and detailed vision, mission, goals, and background, were in accordance with community needs. It is evidenced by the increasing number of students studying and student participation in extracurricular activities, as well as student enthusiasm in carrying out character education programs. Second, is the input aspect, where most of the input components have been fulfilled properly. The majority of teachers implemented character education programs effectively. Third, the process aspect, where all components had been implemented quite well. This can be seen from the value of students' discipline and curiosity, as well as the enthusiasm of educators in guiding and directing students in implementing character education, both in the classroom and outside the classroom. Fourth, the product aspect, where most of the product components of the character education program at SD Muhammadiyah 05 Pekanbaru had shown satisfactory results. This can be seen from the instillation of character values carried out, as well as the implementation or habituation of character education carried out by each student in activities at school. Apart from that, the achievements achieved, both in the academic and non-academic fields, also showed the success of this program.

Evaluation of the Implementation of theMerdeka Curriculum at Vocational High School Using CIPP Model

As per the directive of the head of the ministry of education, culture, research, and technology (number 044/H/KR/2022) regarding educational units implementing Merdeka Curriculum implementation, the Merdeka Curriculum is scheduled to be implemented beginning with the 2022/2023 school year. Researchers employ Stufflebeam's CIPP evaluation approach, which includes context, input, process, and product components, to determine whether the new curriculum has been implemented appropriately and successfully. In Sumbawa, 310 students from vocational schools and 303 teachers participated in this study. The Merdeka Curriculum has been applied well in terms of context, input, process, and outcomes, according to this study, which used survey technique and a quantitative research approach. Researchers discovered that the average context score for instructors was 4.08, the average input score for teachers was 4.03, the average process score for teachers was 3.89, the average output score for teachers was 4.16, and the average student score was 4.00. It was discovered that, aside from that, there were statistically significant values in terms of the context of the teacher (Md = 4.00, n = 303) and the student (Md = 3.56, n = 310), the process of the teacher (Md = 3.86, n = 303) and the student (Md = 4.00, n = 310), the value of U = 38310.000, ρ =.000, r =.000 while the Product of the instructor (Md = 4.29, n = 303) and the pupil (Md = 4.00, n = 310), U = 30985.000, ρ =.000, and r =.000 are obtained. The results of the Mann Withney U-test, however, indicated that the teacher's (Md = 4.00, n = 303) and student's (Md = 4.00, n = 310) inputs were not statistically significant (U = 44775.000, ρ =.307, r =.041). To ensure that teachers and students have the same understanding of context, input, process, and product, it is intended that the Merdeka Curriculum may be implemented more effectively.

Adaptive physical education learning: evaluation by teachers of deaf students at special elementary schools

PurposeThis research aims to evaluate adaptive physical education learning in deaf students at special elementary schools.MethodsThis study employs an evaluation model approach to assess the efficacy of adaptive physical education instruction. Specifically, this research utilizes the CIPP (Context, Input, Process, and Product) model for evaluation. The participants in this study were teachers who taught physical education in West Sumatra, with a sample size of 60 teachers in West Sumatra, Indonesia. Data collection was carried out using a research instrument in the form of a questionnaire administered via Google Forms. The results showed that all statement items of the questionnaire were valid for reliability testing.ResultsThe results of this research showed that the evaluation using the context and input components of the CIPP scored 74.32% and 70.71%, respectively, indicating both as good. However, the process and product aspects attained a score of 50.83% and 48.10% indicating them as enough.ConclusionsThis research concluded that the implementation of adaptive physical education learning for deaf students was good. Based on the results, this research recommends that evaluations be conducted at the school level for students with special needs. Additionally, evaluation is also needed using participants involved in education.

Impacts of an intensive traditional mariculture model on offshore environments as evidenced by dissolved organic matter and bacterial communities

Mariculture is a key protein source and economic driver but traditional methods pollute coastal waters, hindering sustainable development. Current research on the ecological impacts of mariculture mainly focuses on specific pollutants and lacks an assessment of the biogeochemical impacts of mariculture discharge. This study examined Xiangshan Bay, a representative intensive mariculture area in China, to explore the impact of mariculture tailwater discharge on water quality, focusing on dissolved organic matter (DOM) and bacterial communities. Based on the fluorescence excitation-emission matrix combined with parallel factor analysis, a characteristic fluorescence component C4 was identified in mariculture tailwater (intensity of 40 ± 4 %, n = 8), while higher C4 components (47 ± 3 %, n = 15) were found throughout the bay. Humic-like components from riverine input (C1 + C2: 32 ± 3 %, n = 15) and protein-like components from domestic sewage (C5: 2 ± 1 %, n = 15) were significantly lower in the seawater samples, indicating the strong influence of mariculture tailwater on the entire DOM structure of the bay. The bacterial community structure showed a response consistent with DOM, as revealed by nonmetric multidimensional scaling analysis. This showed that bacterial communities in mariculture tailwater and bay water samples clustered together, independent of riverine input. The SourceTracker model indicated that mariculture tailwater (91 ± 5 %) predominantly contributed to the bacterial community, with minimal contributions from riverine input (< 5 %). Co-occurrence network analysis further showed that under long-term high-intensity mariculture discharge, the C4 component became the core DOM and was closely associated with the bacterial community. The results here demonstrate the profound impact of traditional mariculture on coastal water quality and show that riverine input is not the primary pollution source in this region, providing clear directions for coastal environmental restoration efforts.

EVALUATION OF READING PARK MANAGEMENT BASED ON THE CIPP MODEL IN INCREASING CHILDREN'S INTEREST IN READING

Reading parks play an important role in increasing children's interest in reading. This study aims to measure the effectiveness of reading park management in Bogor Regency, using the CIPP (Context, Input, Process, Product) model qualitatively. The instruments used include document studies, interviews, questionnaires, observations, and focus group discussions. Data analysis is an interactive analysis that is presented in its entirety. The results of the study describe that the evaluation of the context component is classified as good with a score of 4.03, the input component is sufficient - 3.29, the process component is sufficient - 3.40, and the product component is sufficient - 3.55. It is concluded that the evaluation of the management of reading parks in Bogor Regency is classified as "quite effective", with an average score of 3.56. There are three challenges faced by reading parks, namely 1) minimal government attention, 2) low public awareness, and 3) a small collection of books. The management of reading parks must ensure that there are readers, books, and commitment from the managers. So that reading parks can increase children's interest in reading, in addition to being a catalyst for improving the quality of human resources to boost Indonesia's Human Development Index (HDI).

Growth and nitrogen uptake modeling in composite and hybrid corn varieties

Corn is a strategic commodity in Indonesia's agricultural and economic development. The problem of corn production can be overcome with proper usage of nitrogen fertilization. Dynamic modeling can be used as a tool to solve this problem. This study aimed to develop a dynamic model for the growth and nitrogen uptake of composite and hybrid corn varieties. Stages in the model construction: (1) identifying system components, (2) model construction, (3) simulation, and (4) validation. The growth model is a construction of the plant's ecophysiological response to solar radiation and temperature in photosynthesis. A growth model in composite and hybrid corn varieties with simulated dry weight as output has been constructed validly. The model input components, such as light use efficiency, extinction coefficient, specific leaf area, and carbohydrate partition coefficient varied at each development phase for each variance. The actual total dry weight on the Pioneer 27 variety was 6,406 kg ha-1 with a simulated total dry weight was 6,228 kg ha-1, and the actual total dry weight on the Bisma variety was 5,127 kg ha-1 with a simulated total dry weight was 4,864 kg ha-1. The level of validity of the Pioneer 27 variety growth model reached 83.5% and the Bisma variety reached 80%. Keywords: Bisma; dry weight; growth model; nitrogen uptake; Pioneer 27; simulation; validation

Manhaj al-Lugah al-‘Arabiyyah fi Madāris al-Ṡānawiyyah al-Islamiyyah: Taqwīm al-Taṭbīq Binaan ‘ala Qarar Wazīr al-Syuūn al-Dīniyyah

The formulation of evaluation tools needed to apply the curriculum in the process of evaluating the application of the curriculum at the practical level in education units. The objectives of this scientific research are: 1) Describe the curriculum application evaluation model with specifications for the formulation of components, aspects, context indicators, inputs, process, product, and outputs (CIPPO). Based on the decision of the Minister of Religious Affairs No. 183, 184, 189 and the theory of linguistic performance. 2) Analyzing the evaluation results of the implementation of the Arabic language curriculum. This scientific research utilized a research and development (R&amp;D) design) with the ADDIE model (Analysis, Design, Development, Implementation, and Evaluation). Data collection tools using interview, questionnaire, and documents. The data collection techniques are Dhelpi techniques; consultative discussions with experts as validators in preparing the instruments, group discussion forum; discussions with Arabic language teachers to analyze the needs and formulate the components, aspects, and indicators to achieve Arabic language curriculum application. And qualitative data analysis using triangulation method; data reduction, presentation, and conclusion. The results of the research indicated that; 1) Implementing the evaluation of the Arabic language education curriculum in the Islamic high school using the CIPPO evaluation model with representative formulas and criteria from KMA 2019 No. 183, 84, and 189 with Dell Hymess' language performance theory Furthermore, CIPPO becomes an evaluation model in the form of curriculum achievement evaluation tools that include components on; context, inputs, process, outcomes, and learning outcomes with all aspects and indicators. The results of the evaluation of the implementation of the Arabic language curriculum for Ma'arif Islamic Secondary Schools Jepara are as follows; 1) Context aspects are at a very good level. 2) Aspects of the input components of the curriculum at a good level. 3) Aspects of the process components of the curriculum at a very good level. 4) The product component aspects of the curriculum are at a good level. 5) The learning outcomes aspects of language performance are at a poor level.

A machine learning-based prediction model for architectural heritage: The case of domed Sinan mosques

This study presents a machine learning-based prediction model (PM) customized to predict missing components of historical mosques. Domed mosques built by Architect Sinan during the Classical Ottoman Period (16th century) are selected due to their distinctive features and stylistic similarities. The model development process includes data collection (46 domed Sinan mosques), data preparation and refinement, training, testing, and validation. The Pix2Pix method is used to train and validate the machine learning models, and the Structural Similarity (SSIM) metric is used to objectively evaluate the outcomes. Preliminary results indicate that the success of the PMs is not directly proportional to the number of input components. Instead, factors such as overall mass organization, the curvature of the dome, and the number of balconies on the minaret play crucial roles in determining the success of the outcomes.

Input hypotheses for developing EFL/ESL learners’ listening comprehension skills

The objective of this study is to examine the significance of the input hypothesis in enhancing the listening comprehension abilities of EFL/ESL learners. The methodology employed in this study is a critical literature review. This entailed a comprehensive search for relevant articles and other sources, a meticulous reading of the material, the categorization of data, a thorough analysis, and the synthesis of findings. The findings of this study indicate that the input hypothesis plays an essential role in developing ESL/EFL learners' listening comprehension abilities through the acquisition of comprehensible inputs. The activation of linguistic background knowledge enables EFL/ESL learners to develop pronunciation skills, understanding of grammatical accuracy, lexical resources, and meaning. Optimizing the inputs of the listening strategy (cognitive, metacognitive, socio-affective) assists EFL/ESL learners in activating their memory about listening materials. This is achieved through making inferences, elaborations, summaries, translations, observations, assessments, and becoming involved in the community. Inputs from media, audio (visual), and practices can develop EFL/ESL learners' cognition, motivation, stimulating perception, activating prior knowledge. In conclusion, the components of the comprehensible inputs must be integrated and developed in a coordinated manner during the teaching and learning process of listening skills.

Higher-Dimensional Communications Using Multimode Fibers and Compact Components to Enable a Dense Set of Communicating Channels

Higher-dimensional communications are of interest for multiple reasons, including increasing the classical transmission capacity and, more recently, the quantum state transfer through fibers using the many modes within the fiber. For quantum communications, this enables an increase in the number of bits per photon, increasing quantum fidelity, increasing error thresholds and enabling hyperentanglement transfer, among other possibilities. A high-dimensional quantum state transfer can be transported through multimode fiber using the many modes available. However, this transfer of information through multimode optical fiber is limited by attenuation and mode coupling among the various spatial and polarization modes. Here, we consider how this mode coupling impacts the transfer process. We consider the fiber’s modal properties, including orbital angular momentum, modal group numbers, and principal modes. We also investigate and propose input and output optical components, as well as fiber properties, which better mitigate the deleterious effects of mode coupling. We use the WKB approximation to the scaler wave equation as a guidance to quantify this coupling and then implement corrections to this approximation using exact solutions to the scaler wave equation. We consider methods to circumvent this mode coupling using optical fiber designs, holographic optical components and devices that are commercially available today. Some of these components, such as the holographic gratings and lenses, could be implemented using flat optics.

Memory’s gatekeeper: The role of PFC in the encoding of congruent events

Theoretical models conventionally portray the consolidation of memories as a slow process that unfolds during sleep. According to the classical Complementary Learning Systems theory, the hippocampus (HPC) rapidly changes its connectivity during wakefulness to encode ongoing events and create memory ensembles that are later transferred to the prefrontal cortex (PFC) during sleep. However, recent experimental studies challenge this notion by showing that new information consistent with prior knowledge can be rapidly consolidated in PFC during wakefulness and that PFC lesions disrupt the encoding of congruent events in the HPC. The contributions of the PFC to memory encoding have therefore largely been overlooked. Moreover, most theoretical frameworks assume random and uncorrelated patterns representing memories, disregarding the correlations between our experiences. To address these shortcomings, we developed a HPC-PFC network model that simulates interactions between the HPC and PFC during the encoding of a memory (awake stage), and subsequent consolidation (sleeping stage) to examine the contributions of each region to the consolidation of novel and congruent memories. Our results show that the PFC network uses stored memory "schemas" consolidated during previous experiences to identify inputs that evoke congruent patterns of activity, quickly integrate it into its network, and gate which components are encoded in the HPC. More specifically, the PFC uses GABAergic long-range projections to inhibit HPC neurons representing input components correlated with a previously stored memory "schema," eliciting sparse hippocampal activity during exposure to congruent events, as it has been experimentally observed.

Review paper on applications of the HEC-RAS model for flooding, agriculture, and water quality simulation

ABSTRACT The Hydrologic Engineering Center (HEC) of the United States Army Corps of Engineers (USACE) has developed the HEC-River Analysis System (RAS) hydraulic channel flow model as part of its portfolio of hydrologic and hydraulic modeling tools. HEC-RAS is a new version with capabilities to model flooding, modeling for agriculture production computations for water quality, and many more related to hydraulic modeling. The analysis components of the HEC-RAS system include one-dimensional steady flow water surface profile computations, one-dimensional and or two-dimensional unsteady flow simulation, one-dimensional and two-dimensional computations of quasi-unsteady or fully unsteady flow movable boundary sediment transport, and one-dimensional water quality analysis. The main objective of this paper is to review the use of HEC-RAS on flooding, agriculture, and water quality. The three primary components of the data input are plan data, geometry data, and flow data. Three of these scenarios applied to HEC-RAS and were proven by previous reviewers.

Evaluating Integrated Social Studies Learning Programs in Indonesian Middle Schools: An Application of the Stufflebeam Model

Many studies have been conducted to evaluate the nonintegrated approach. Each model claimed to have certain advantages, but the current research used a combined social science learning model called Stufflebeam's CIPP (context, input, process, and product) model, which included input, process, and product components due its comprehensiveness in assessment and students’ interest based. The assessment model appropriate for Integrated Social Studies learning programs in public middle schools because it could fulfil pedagogical aspects for students in schools. The research group included respondents from eight public middle schools, as well as school administrators, 16 instructors, and 350 pupils. Documentation, questionnaires, and tests are examples of data gathering methods. Content validity is tested using expert opinion, construct validity is tested using a limited test and evaluated using Product Moment correlation, and reliability is tested using Cronbach Alpha. The SPSS software is used to perform data analysis methods such as descriptive statistics. 20. The development of a combined social study learning program evaluation model for public middle schools yielded outstanding assessment criteria. The quality of integrated social studies learning inputs includes: teachers’ competence, students’ motivation, and infrastructure, which are all very good categories; the quality of integrated social studies learning processes, which include initial activities, core activities, and closing activities, which are all excellent categories; and product quality (results) integrated social studies learning includes: attitude competencies, knowledge, and skills.

Case Study of Economic Growth with the Act of Monopoly on Food Control in the Field of Poultry Farming from Upstream to Downstream by PT. Charoen Pokphand Indonesia Tbk

This study discusses economic growth, that economic growth does not only provide positive impacts but also negative impacts such as the existence of monopoly crimes that grow because unfair competition practices are based on tight business competition because they are required to increase profits as much as possible. The company PT. Charoen Pokphand Indonesia Tbk (CPIN) is indicated to have committed a monopoly violation in controlling food in the poultry sector in its business activities. The purpose of this study is that the government is expected to be truly present in trying, and anticipating, and or overcoming crimes in the field of monopoly practices and unfair business competition. Namely in overcoming the practice of controlling products from upstream to downstream, the authority in this case is the Business Competition Supervisory Commission (KPPU). This research method uses Normative Juridical analysis using secondary data with primary materials in the form of laws and expert opinions. The results of this study are that Business actors must implement Law No. 5 of 1999 Regarding Their Business Activities, and also the Business Competition Supervisory Commission (KPPU) must take a legal approach to PT Charoen Pokphand Indonesia (CPIN). In this study it can be concluded that all independent farmers are in a very weak position. Because they do not have a bargaining position against suppliers who supply input components such as seeds, feed and medicine, and do not have bargaining power from the sales side, because the market is controlled by poultry integrators such as in this study PT. CPIN. So that monopoly practices occur in product control from upstream to downstream.

Decomposition-based Synthesis for Applying Divide-and-Conquer-like Algorithmic Paradigms

Algorithmic paradigms such as divide-and-conquer (D&amp;C) are proposed to guide developers in designing efficient algorithms, but it can still be difficult to apply algorithmic paradigms to practical tasks. To ease the usage of paradigms, many research efforts have been devoted to the automatic application of algorithmic paradigms. However, most existing approaches to this problem rely on syntax-based program transformations and thus put significant restrictions on the original program. In this article, we study the automatic application of D&amp;C and several similar paradigms, denoted as D&amp;C-like algorithmic paradigms, and aim to remove the restrictions from syntax-based transformations. To achieve this goal, we propose an efficient synthesizer, named AutoLifter , which does not depend on syntax-based transformations. Specifically, the main challenge of applying algorithmic paradigms is from the large scale of the synthesized programs, and AutoLifter addresses this challenge by applying two novel decomposition methods that do not depend on the syntax of the input program, component elimination and variable elimination , to soundly divide the whole problem into simpler subtasks, each synthesizing a sub-program of the final program and being tractable with existing synthesizers. We evaluate AutoLifter on 96 programming tasks related to six different algorithmic paradigms. AutoLifter solves 82/96 tasks with an average time cost of 20.17 s, significantly outperforming existing approaches.

Deep learning-driven hybrid model for short-term load forecasting and smart grid information management

Accurate power load forecasting is crucial for the sustainable operation of smart grids. However, the complexity and uncertainty of load, along with the large-scale and high-dimensional energy information, present challenges in handling intricate dynamic features and long-term dependencies. This paper proposes a computational approach to address these challenges in short-term power load forecasting and energy information management, with the goal of accurately predicting future load demand. The study introduces a hybrid method that combines multiple deep learning models, the Gated Recurrent Unit (GRU) is employed to capture long-term dependencies in time series data, while the Temporal Convolutional Network (TCN) efficiently learns patterns and features in load data. Additionally, the attention mechanism is incorporated to automatically focus on the input components most relevant to the load prediction task, further enhancing model performance. According to the experimental evaluation conducted on four public datasets, including GEFCom2014, the proposed algorithm outperforms the baseline models on various metrics such as prediction accuracy, efficiency, and stability. Notably, on the GEFCom2014 dataset, FLOP is reduced by over 48.8%, inference time is shortened by more than 46.7%, and MAPE is improved by 39%. The proposed method significantly enhances the reliability, stability, and cost-effectiveness of smart grids, which facilitates risk assessment optimization and operational planning under the context of information management for smart grid systems.