Analysis of Mechanical Properties of Zn-0.5Fe-0.5Ag Alloy for Body Absorbed Implant Applications

Implants that can be absorbed by the body may be developed using alloy materials based on zinc (Zn), iron (Fe), copper (Cu), and silver (Ag). Zn-based alloys are known for their faster biodegradation rates, making them particularly suitable for biodegradable implant applications. The aim of this study is to determine the corrosion rate and hardness of Zn-0.5Fe-0.5Ag alloy specimens, as well as to examine the effects of heat treatment and the addition of Fe and Ag elements. The research utilizes a direct experimental observation method to analyze the mechanical properties of the Zn-0.5Fe-0.5Ag alloy. The microstructural analysis reveals differences between pure Zn specimens and Zn-0.5Fe-0.5Ag alloy specimens. In pure Zn, the largest grain size is observed in specimens without annealing treatment, while the smallest grain size is found in specimens annealed at 350°C. For the Zn-0.5Fe-0.5Ag alloy, the smallest grain size is observed in specimens annealed at 400°C, while the largest grain size appears in those annealed at 350°C. The addition of Fe and Ag to pure Zn significantly increases the hardness, with the hardness value rising from 33.77 HV (pure Zn) to 61.64 HV. In terms of corrosion, the highest corrosion rate in pure Zn was found in specimens without annealing. In contrast, the highest corrosion rate in the Zn-0.5Fe-0.5Ag alloy was observed in specimens annealed at 400°C. In conclusion, the addition of Fe and Ag elements, along with heat treatment, significantly affects the mechanical properties of the Zn-0.5Fe-0.5Ag alloy, improving both its hardness and influencing its corrosion behavior.Implants that can be absorbed by the body may be developed using alloy materials based on zinc (Zn), iron (Fe), copper (Cu), and silver (Ag). Zn-based alloys are known for their faster biodegradation rates, making them particularly suitable for biodegradable implant applications. The aim of this study is to determine the corrosion rate and hardness of Zn-0.5Fe-0.5Ag alloy specimens, as well as to examine the effects of heat treatment and the addition of Fe and Ag elements. The research utilizes a direct experimental observation method to analyze the mechanical properties of the Zn-0.5Fe-0.5Ag alloy. The microstructural analysis reveals differences between pure Zn specimens and Zn-0.5Fe-0.5Ag alloy specimens. In pure Zn, the largest grain size is observed in specimens without annealing treatment, while the smallest grain size is found in specimens annealed at 350°C. For the Zn-0.5Fe-0.5Ag alloy, the smallest grain size is observed in specimens annealed at 400°C, while the largest grain size appears in those annealed at 350°C. The addition of Fe and Ag to pure Zn significantly increases the hardness, with the hardness value rising from 33.77 HV (pure Zn) to 61.64 HV. In terms of corrosion, the highest corrosion rate in pure Zn was found in specimens without annealing. In contrast, the highest corrosion rate in the Zn-0.5Fe-0.5Ag alloy was observed in specimens annealed at 400°C. In conclusion, the addition of Fe and Ag elements, along with heat treatment, significantly affects the mechanical properties of the Zn-0.5Fe-0.5Ag alloy, improving both its hardness and influencing its corrosion behavior

Problematic Analysis of the National Free School Lunch Policy on Vocational Education

Free school lunch policies have been shown to improve student health and well-being in many countries. However, the implementation of these policies in low- and middle-income countries faces significant challenges, including logistical issues, budget constraints, and coordination among stakeholders. This study aims to analyze the challenges faced by countries that have already implemented free lunch programs, with a focus on the lessons learned by Indonesia in preparing a similar policy. This research is a literature review, utilizing a Systematic Literature Review (SLR) method in accordance with the PRISMA guidelines. The study focuses on the 10 highest-cited articles from the Scopus database published between 2019 and 2024 that discuss the implementation of free lunch programs in various countries. Document analysis was employed to extract and synthesize key challenges and solutions. Findings show that the main challenges include difficulties with food distribution in remote areas, lack of sustainable budgets, and suboptimal coordination between the government and schools. The implications of the study highlight the importance of strengthening logistics infrastructure and improving coordination across sectors in Indonesia to ensure smooth implementation of the school lunch policy. Future research needs to focus on the long-term impact of the lunch program on academic achievement and innovative logistics models that can be adapted for remote areas in Indonesia.Free school lunch policies have been shown to improve student health and well-being in many countries. However, the implementation of these policies in low- and middle-income countries faces significant challenges, including logistical issues, budget constraints, and coordination among stakeholders. This study aims to analyze the challenges faced by countries that have already implemented free lunch programs, with a focus on the lessons learned by Indonesia in preparing a similar policy. This research is a literature review, utilizing a Systematic Literature Review (SLR) method in accordance with the PRISMA guidelines. The study focuses on the 10 highest-cited articles from the Scopus database published between 2019 and 2024 that discuss the implementation of free lunch programs in various countries. Document analysis was employed to extract and synthesize key challenges and solutions. Findings show that the main challenges include difficulties with food distribution in remote areas, lack of sustainable budgets, and suboptimal coordination between the government and schools. The implications of the study highlight the importance of strengthening logistics infrastructure and improving coordination across sectors in Indonesia to ensure smooth implementation of the school lunch policy. Future research needs to focus on the long-term impact of the lunch program on academic achievement and innovative logistics models that can be adapted for remote areas in Indonesia

Pyrolyzer Modification for Making Coconut Shell Charcoal with Isolation from a Mixture of Clay, Sand, and Rice Straw

Currently, many charcoal makers use drums as pyrolyzers, this is because the oxygen (O2) entering the combustion chamber is controlled, the oxygen level entering the combustion chamber must be low so that the shell does not burn out. The aim of this research is to calculate the heat loss rate of the pyrolyzer for making coconut shell charcoal and to analyze the effect of a mixture of clay, sand and rice straw insulator on the charcoal yield and quality of the charcoal produced. This research focuses on reviewing pyrolyzer modifications based on aspects of mixed variations of clay, sand and rice straw insulating materials in dealing with heat loss. Testing of furnace performance is carried out using comparisons of several parameters or components including temperature, time and insulator material. The final stage of the research is to draw conclusions and draw conclusions based on the results of material variations and the factors that influence them. The research results show that the best insulator is the TP3 pyrolyzer with an insulator mixed with clay, sand and rice straw in a ratio of 2:1:0.3 with a heat loss of 7,378.992 W and ΔT of 195°C. The addition of rice straw to a mixture of clay and sand insulators provides significant benefits in increasing ΔT and reducing heat loss. The addition of rice straw to a mixture of clay and sand insulators has a significant impact on the carbonization process of coconut shell charcoal. Even though the charcoal yield decreases with the addition of rice straw to the insulator, the quality of the charcoal produced increases, especially in terms of fixed carbon content with the best insulator being the TP3 pyrolyzer with a carbon content value of 78.54%.Currently, many charcoal makers use drums as pyrolyzers, this is because the oxygen (O2) entering the combustion chamber is controlled, the oxygen level entering the combustion chamber must be low so that the shell does not burn out. The aim of this research is to calculate the heat loss rate of the pyrolyzer for making coconut shell charcoal and to analyze the effect of a mixture of clay, sand and rice straw insulator on the charcoal yield and quality of the charcoal produced. This research focuses on reviewing pyrolyzer modifications based on aspects of mixed variations of clay, sand and rice straw insulating materials in dealing with heat loss. Testing of furnace performance is carried out using comparisons of several parameters or components including temperature, time and insulator material. The final stage of the research is to draw conclusions and draw conclusions based on the results of material variations and the factors that influence them. The research results show that the best insulator is the TP3 pyrolyzer with an insulator mixed with clay, sand and rice straw in a ratio of 2:1:0.3 with a heat loss of 7,378.992 W and ΔT of 195°C. The addition of rice straw to a mixture of clay and sand insulators provides significant benefits in increasing ΔT and reducing heat loss. The addition of rice straw to a mixture of clay and sand insulators has a significant impact on the carbonization process of coconut shell charcoal. Even though the charcoal yield decreases with the addition of rice straw to the insulator, the quality of the charcoal produced increases, especially in terms of fixed carbon content with the best insulator being the TP3 pyrolyzer with a carbon content value of 78.54%

Sales Segmentation Analysis of Tobacco Products Using the K-Means Clustering Method

Technological advancements have encouraged businesses to optimize data utilization, including in sales analysis. This study analyzes sales transaction data of tobacco products at Tobacco Shop Taste using the K-Means Clustering method. By implementing the Cross-Industry Standard Process for Data Mining (CRISP-DM) framework, the sales data were categorized into three groups: highly sold, moderately sold, and less sold. These clustering results support stock management, marketing strategies, and data-driven decision-making. A web-based system was developed, providing real-time monitoring of analysis results, which distinguishes this study from existing solutions by enabling store management to promptly respond to sales trends. This study significantly contributes to the application of data mining technology in the tobacco retail sector, despite being limited to a single store and basic variables. Future development opportunities include integrating broader datasets and analyzing external variables to enhance the accuracy and relevance of the findings.Technological advancements have encouraged businesses to optimize data utilization, including in sales analysis. This study analyzes sales transaction data of tobacco products at Tobacco Shop Taste using the K-Means Clustering method. By implementing the Cross-Industry Standard Process for Data Mining (CRISP-DM) framework, the sales data were categorized into three groups: highly sold, moderately sold, and less sold. These clustering results support stock management, marketing strategies, and data-driven decision-making. A web-based system was developed, providing real-time monitoring of analysis results, which distinguishes this study from existing solutions by enabling store management to promptly respond to sales trends. This study significantly contributes to the application of data mining technology in the tobacco retail sector, despite being limited to a single store and basic variables. Future development opportunities include integrating broader datasets and analyzing external variables to enhance the accuracy and relevance of the findings

Application of K-Means Data Mining to Measure the Level of Satisfaction of KITA Car Driving Course

KITA Driving Course, located in Kisaran, North Sumatra, faces challenges in maintaining service quality amidst increasing student enrollment. Despite operating since 2013, the institution lacks a structured, data-driven evaluation system to assess student satisfaction. This study applies a quantitative descriptive approach using the K-Means clustering algorithm to classify student satisfaction levels. Data were collected from 100 respondents through a questionnaire based on the five SERVQUAL dimensions: tangibles, reliability, responsiveness, assurance, and empathy. The K-Means algorithm grouped the satisfaction data into three categories: highly satisfied, satisfied, and dissatisfied. The majority of students were classified as satisfied (18 students), followed by highly satisfied (11 students), and dissatisfied (10 students). The findings indicate that the K-Means algorithm provides valuable insights into student satisfaction patterns, enabling targeted service improvements. The analysis also reveals that responsiveness and assurance were key areas of dissatisfaction, suggesting that instructor response time and safety assurance should be prioritized. These insights can help improve service strategies and can be adapted by other educational institutions for quality optimization through data analysis.KITA Driving Course, located in Kisaran, North Sumatra, faces challenges in maintaining service quality amidst increasing student enrollment. Despite operating since 2013, the institution lacks a structured, data-driven evaluation system to assess student satisfaction. This study applies a quantitative descriptive approach using the K-Means clustering algorithm to classify student satisfaction levels. Data were collected from 100 respondents through a questionnaire based on the five SERVQUAL dimensions: tangibles, reliability, responsiveness, assurance, and empathy. The K-Means algorithm grouped the satisfaction data into three categories: highly satisfied, satisfied, and dissatisfied. The majority of students were classified as satisfied (18 students), followed by highly satisfied (11 students), and dissatisfied (10 students). The findings indicate that the K-Means algorithm provides valuable insights into student satisfaction patterns, enabling targeted service improvements. The analysis also reveals that responsiveness and assurance were key areas of dissatisfaction, suggesting that instructor response time and safety assurance should be prioritized. These insights can help improve service strategies and can be adapted by other educational institutions for quality optimization through data analysis

Application of Rescaled Adjusted Partial Sums (RAPS) Method in Validation of Traffic Management Risk Analysis Data in Large Cities in Indonesia

This study examines the application of the Rescaled Adjusted Partial Sums (RAPS) method in validating traffic management risk analysis data in the category of large cities in Indonesia. The RAPS method is used to test the consistency and reliability of data that is the basis for traffic management risk analysis, so that it can ensure the validity of the risk assessment results. Data validation is very crucial in traffic management risk analysis to ensure the accuracy and reliability of the analysis results that are the basis for decision making. In order for the implementation of traffic management to be in accordance with the goals and objectives, traffic management analysis is needed to minimize the risk of failure of the implementation. Traffic management risk analysis in this study uses the Failure Modes, Effects and Criticality Analysis (FMECA) method. The data used are based on the results of filling out questionnaires from respondents, in the form of an assessment of three components, namely severity, occurrence, and detection for four indicators (road capacity, side obstacles, traffic conflicts, and traffic signs/markings) which have sub-indicators of the existing negative impacts. The data were validated to see the consistency of the data provided by respondents using the RAPS method. The results of the validation test using the RAPS method show that the data from the assessment of three components for four indicators that have sub-indicators of negative impacts are valid. And the test results show that the RAPS method is effective in identifying consistent and inconsistent data, thereby improving the quality of risk analysis data validation. With better validation, traffic management risk analysis can be carried out more precisely and efficiently.This study examines the application of the Rescaled Adjusted Partial Sums (RAPS) method in validating traffic management risk analysis data in the category of large cities in Indonesia. The RAPS method is used to test the consistency and reliability of data that is the basis for traffic management risk analysis, so that it can ensure the validity of the risk assessment results. Data validation is very crucial in traffic management risk analysis to ensure the accuracy and reliability of the analysis results that are the basis for decision making. In order for the implementation of traffic management to be in accordance with the goals and objectives, traffic management analysis is needed to minimize the risk of failure of the implementation. Traffic management risk analysis in this study uses the Failure Modes, Effects and Criticality Analysis (FMECA) method. The data used are based on the results of filling out questionnaires from respondents, in the form of an assessment of three components, namely severity, occurrence, and detection for four indicators (road capacity, side obstacles, traffic conflicts, and traffic signs/markings) which have sub-indicators of the existing negative impacts. The data were validated to see the consistency of the data provided by respondents using the RAPS method. The results of the validation test using the RAPS method show that the data from the assessment of three components for four indicators that have sub-indicators of negative impacts are valid. And the test results show that the RAPS method is effective in identifying consistent and inconsistent data, thereby improving the quality of risk analysis data validation. With better validation, traffic management risk analysis can be carried out more precisely and efficiently

Evaluation Inclusive Education in Higher Education: Development and Implementation of Assessment Indicators

The 1945 Constitution of Indonesia ensures education access for all citizens. Law No. 19 of 2011 ratifies the Convention on the Rights of Persons with Disabilities (CRPD), emphasizing inclusive education. Despite efforts by several universities, including Universitas Andalas, challenges remain. A preliminary survey with five students with disabilities at Universitas Andalas identified barriers such as communication difficulties, limited library resources for the visually impaired, and inadequate public facilities. However, no formal research or evaluation indicators have been developed to assess the university's inclusivity. This study aims to develop self-evaluation indicators for improving inclusive education at Universitas Andalas. Using qualitative and quantitative methods, it examines challenges, formulates evaluation indicators, and assesses implementation. The proposed indicators cover seven aspects: institutional policies, admissions, learning, socio-psychological support, physical accessibility, graduate preparedness, and teaching methods. The evaluation results highlight institutional policies, social support, and learning methods as the strongest aspects, whereas physical accessibility scores the lowest. Universitas Andalas attained a self-evaluation score of 483, categorizing it as "Moderately Inclusive." Key recommendations include improving infrastructure such as accessible dining areas, specialized learning tools, laboratories, and libraries. Additional measures include career training programs, inclusive teaching workshops for faculty, periodic policy updates, and enhanced counseling services. These improvements aim to establish Universitas Andalas as a more disability-friendly institution, ensuring equal opportunities for all students.The 1945 Constitution of Indonesia ensures education access for all citizens. Law No. 19 of 2011 ratifies the Convention on the Rights of Persons with Disabilities (CRPD), emphasizing inclusive education. Despite efforts by several universities, including Universitas Andalas, challenges remain. A preliminary survey with five students with disabilities at Universitas Andalas identified barriers such as communication difficulties, limited library resources for the visually impaired, and inadequate public facilities. However, no formal research or evaluation indicators have been developed to assess the university's inclusivity. This study aims to develop self-evaluation indicators for improving inclusive education at Universitas Andalas. Using qualitative and quantitative methods, it examines challenges, formulates evaluation indicators, and assesses implementation. The proposed indicators cover seven aspects: institutional policies, admissions, learning, socio-psychological support, physical accessibility, graduate preparedness, and teaching methods. The evaluation results highlight institutional policies, social support, and learning methods as the strongest aspects, whereas physical accessibility scores the lowest. Universitas Andalas attained a self-evaluation score of 483, categorizing it as "Moderately Inclusive." Key recommendations include improving infrastructure such as accessible dining areas, specialized learning tools, laboratories, and libraries. Additional measures include career training programs, inclusive teaching workshops for faculty, periodic policy updates, and enhanced counseling services. These improvements aim to establish Universitas Andalas as a more disability-friendly institution, ensuring equal opportunities for all students

The Influence of the Team-Based Learning Model on Students’ Procedural Knowledge Learning Outcomes in Information and Communication Technology Subjects

Improving students' learning outcomes in terms of procedural knowledge in the subject of Information and Communication Technology (ICT) remains a significant challenge in the field of education. This is due to the limitations of traditional teaching methods, which are less effective in promoting active student engagement and are not optimal in developing critical thinking and problem-solving skills. To address this issue, this study aims to explore the implementation of the Team-Based Learning (TBL) model as an innovative instructional strategy that focuses on teamwork and active participation in the learning process. The TBL model is designed to enhance both conceptual understanding and procedural skills through group discussions, individual and team quizzes, and real-world applications. This study employs a quasi-experimental design involving two groups: an experimental group that applies the TBL model and a control group that uses conventional teaching methods. The results indicate that the implementation of TBL significantly improves students' procedural knowledge, encourages active interaction between teachers and students, and receives positive feedback from learners. These findings highlight the great potential of TBL as an effective approach to improving the quality of ICT learning in schools.Improving students' learning outcomes in terms of procedural knowledge in the subject of Information and Communication Technology (ICT) remains a significant challenge in the field of education. This is due to the limitations of traditional teaching methods, which are less effective in promoting active student engagement and are not optimal in developing critical thinking and problem-solving skills. To address this issue, this study aims to explore the implementation of the Team-Based Learning (TBL) model as an innovative instructional strategy that focuses on teamwork and active participation in the learning process. The TBL model is designed to enhance both conceptual understanding and procedural skills through group discussions, individual and team quizzes, and real-world applications. This study employs a quasi-experimental design involving two groups: an experimental group that applies the TBL model and a control group that uses conventional teaching methods. The results indicate that the implementation of TBL significantly improves students' procedural knowledge, encourages active interaction between teachers and students, and receives positive feedback from learners. These findings highlight the great potential of TBL as an effective approach to improving the quality of ICT learning in schools

Evaluation of the Impact of Governor-less Control on the Transient Response of Hydraulic Load Frequency Control Systems

This study evaluates the transient performance of a hydraulic Load Frequency Control (LFC) system configured with a single controller and without a governor. The analysis focuses on rise time, peak time, settling time, and overshoot, using various controllers including PI, PD, PID, PDF, and PIDF. Simulation results indicate that eliminating the governor significantly enhances system responsiveness and reduces overshoot, particularly when using the PDF controller. Quantitative analysis shows that the PDF controller achieves 85% faster rise time (0.101s vs 0.607s for P controller) and maintains system stability with minimal overshoot (1.765% for PID vs 59.263% for P controller). This configuration enables for a more direct and efficient control response to load fluctuations, improving system stability. Thus, employing a single controller without a governor presents a promising alternative for frequency regulation in hydraulic LFC systems under dynamic load conditions. The findings of this study offer valuable insights for optimizing controller selection and configuration in practical implementations, providing guidance for engineers and researchers to enhance grid reliability, operational efficiency, and stability in various real-world hydraulic power system scenarios.This study evaluates the transient performance of a hydraulic Load Frequency Control (LFC) system configured with a single controller and without a governor. The analysis focuses on rise time, peak time, settling time, and overshoot, using various controllers including PI, PD, PID, PDF, and PIDF. Simulation results indicate that eliminating the governor significantly enhances system responsiveness and reduces overshoot, particularly when using the PDF controller. Quantitative analysis shows that the PDF controller achieves 85% faster rise time (0.101s vs 0.607s for P controller) and maintains system stability with minimal overshoot (1.765% for PID vs 59.263% for P controller). This configuration enables for a more direct and efficient control response to load fluctuations, improving system stability. Thus, employing a single controller without a governor presents a promising alternative for frequency regulation in hydraulic LFC systems under dynamic load conditions. The findings of this study offer valuable insights for optimizing controller selection and configuration in practical implementations, providing guidance for engineers and researchers to enhance grid reliability, operational efficiency, and stability in various real-world hydraulic power system scenarios

Performance of Automatic Temperature Control System in Pyrolysis Reactor of LDPE Plastic Waste

Pyrolysis is a process of decomposing material at high temperatures without or with limited air and is an alternative waste treatment which is considered quite prospective to be developed. Plastic waste treatment as pyrolysis fuel, is strongly influenced by operating conditions, which consist of the thermal properties of plastics such as the LDPE type, which are still massively used in society. This research processes LDPE type plastic waste using technology fixed bed pyrolysis type batch reactor with a capacity of 0.01 m³ with initial heating from external heat of LPG energy source. The pyrolysis process takes in a closed reactor and the mass flow rate of the condensate flows naturally to the condenser for the condensation process to become pyro-oil product. Optimization of the reactor pyrolysis was carried out by adding insulated heat cover to reduce heat losses during the heating process. The addition of automatic temperature control to regulate the heating rate, makes operation control easier and reducing fluctuations in temperature distribution during pyrolysis process. The research was carried out with three operating temperature variations of 250, 275, and 300 °C using 0.8 kg LDPE plastic waste for batch test. The performance of automatic temperature control was observed using a digital thermometer and a comparison of the results before and after installation was carried out at a temperature of 300 °C. The results showed that heating temperature control which was previously done manually gives fluctuating results with a temperature difference of up to 50 °C. With the addition of an automatic temperature control system, the operating temperature during the pyrolysis process shows relatively lower fluctuations with a maximum difference of 20 °C. The initial heating energy consumption from LPG and the fuel consumption rate (FCR) show an increase along with the increase in the pyrolysis operating temperature setting.Pyrolysis is a process of decomposing material at high temperatures without or with limited air and is an alternative waste treatment which is considered quite prospective to be developed. Plastic waste treatment as pyrolysis fuel, is strongly influenced by operating conditions, which consist of the thermal properties of plastics such as the LDPE type, which are still massively used in society. This research processes LDPE type plastic waste using technology fixed bed pyrolysis type batch reactor with a capacity of 0.01 m³ with initial heating from external heat of LPG energy source. The pyrolysis process takes in a closed reactor and the mass flow rate of the condensate flows naturally to the condenser for the condensation process to become pyro-oil product. Optimization of the reactor pyrolysis was carried out by adding insulated heat cover to reduce heat losses during the heating process. The addition of automatic temperature control to regulate the heating rate, makes operation control easier and reducing fluctuations in temperature distribution during pyrolysis process. The research was carried out with three operating temperature variations of 250, 275, and 300 °C using 0.8 kg LDPE plastic waste for batch test. The performance of automatic temperature control was observed using a digital thermometer and a comparison of the results before and after installation was carried out at a temperature of 300 °C. The results showed that heating temperature control which was previously done manually gives fluctuating results with a temperature difference of up to 50 °C. With the addition of an automatic temperature control system, the operating temperature during the pyrolysis process shows relatively lower fluctuations with a maximum difference of 20 °C. The initial heating energy consumption from LPG and the fuel consumption rate (FCR) show an increase along with the increase in the pyrolysis operating temperature setting