Publication Search

The rapid development of network infrastructure demands high Quality of Service (QoS), especially in Metro Ethernet networks widely utilized by telecommunication service providers. A primary challenge is efficient bandwidth management to ensure network stability and performance. This research aims to optimize bandwidth management by implementing the Y.1731 method based on Ethernet Operations, Administration, and Maintenance (OAM) on Raisecom devices. The methodology employed is a quantitative experimental approach based on technical simulation within an Professional Network Emulator Tool Lab (PNET Lab), where real-time network performance measurements are conducted using the ITU-T Y.1731 protocol for key parameters such as delay, jitter, and packet loss on Raisecom devices (represented by Cisco routers). The expected outcomes include increased efficiency in bandwidth utilization through more adaptive allocation, comprehensive and accurate real-time network performance monitoring capabilities, validation of OAM functions on Raisecom devices, improved Quality of Service (QoS) and better Service Level Agreement (SLA) attainment, and the provision of technical recommendations for network management. The implementation of Y.1731 is anticipated to quickly detect and respond to service degradation, thereby providing a strong basis for decision-making in network management and contributing to the enhancement of service quality in Metro Ethernet networks through optimization based on proactive monitoring.

This study aims to analyze the reward system in improving the performance of educators at State Islamic Senior High Schools (Madrasah Aliyah) in Jambi Province. The research focuses on the reward mechanism, its implementation, and the factors that determine its effectiveness in improving educator performance. This study uses a descriptive qualitative approach with data collection techniques through observation, in-depth interviews, and documentation. The research locations include three madrasas: MAN 1 Tanjung Jabung Barat, MAN 1 Kota Jambi, and MAN 1 Merangin. The results show that the implemented reward system includes financial rewards (such as incentives and allowances) and non-financial rewards (such as certificates, training, and job promotions). Rewards have been shown to play an important role in improving educator motivation, discipline, loyalty, and performance. However, the implementation of the reward system has not been optimal due to several obstacles, such as budget constraints, lack of transparency in assessments, and the incompatibility of the types of rewards with the needs of educators. On the other hand, madrasas that implement the reward system appropriately and fairly show an increase in the quality of educator work, marked by increased participation, work performance, and professional responsibility. This study concludes that an effective reward system is one that has clear criteria, is transparent, and responsive to the needs of educators. Recommendations are directed to madrasah principals and the Ministry of Religious Affairs to build a strong culture of appreciation and allocate an adequate reward budget to improve the quality of education in madrasahs.

This study aims to analyze the influence of performance appraisal, supervision, and non-physical work environment on employee performance at PT Pos Indonesia (Persero) Kediri Branch Office. A quantitative approach was employed with saturated sampling, in which all 64 employees were included as respondents. The research instrument was a questionnaire based on validated theoretical and empirical indicators. Data were analyzed using multiple linear regression, t-test, F-test, and the coefficient of determination. The findings indicate that, partially, performance appraisal, supervision, and non-physical work environment have a positive and significant effect on employee performance. Simultaneously, these three variables contribute 70% to the variation in employee performance, with the non-physical work environment being the most dominant factor. These results highlight the importance of integrating transparent performance appraisal systems, consistent supervision, and a supportive organizational climate to improve employee productivity. This research contributes academically by reinforcing the Goal Setting theory and Perceived Organizational Support, and provides practical implications for PT Pos Indonesia’s human resource management.

This research is motivated by the decline in employee performance at PT Tracon Industri which is allegedly caused by weak teamwork and low work motivation. The main objective of this study is to analyze the influence of teamwork and work motivation on employee work performance, both partially and simultaneously. This study uses a quantitative approach with a descriptive method. A total of 53 respondents from the operational division were involved through saturated sample techniques. Data collection was carried out using a questionnaire, then analyzed through validity, reliability, classical assumptions, multiple linear regression, as well as t-test and F-test with the help of SPSS software version 25. The results of the study show that teamwork and work motivation have a positive and significant influence on employee work performance. Partially, teamwork had a tcal value of 4.337 and work motivation of 5.511, both greater than the ttable of 1.674, with a significance value of 0.000 < 0.05. Simultaneously, the two variables contributed 84.3% to work performance. These findings indicate that increased team synergy and work motivation are key factors in driving productivity and achieving organizational goals. Based on these results, companies are advised to strengthen the culture of cooperation and create an effective motivation system to continuously improve work performance and support the company's operational success.

This study aims to analyze the influence of job satisfaction and productivity on hybrid work performance at PT Asuransi Jiwa Generali Indonesia, especially in the Finance department. The method used is descriptive quantitative with data collection techniques through questionnaires and documentation. The research sample amounted to 66 respondents. There are three main variables: X1 (Job Satisfaction), X2 (Productivity), and Y (Work Performance). The results of the analysis showed that partially, job satisfaction had a significant effect on work performance, as evidenced by a probability value of 0.000 < 0.05 and a Thcal value of 5.437 > Ttable 1.99834. Productivity also showed a partially significant influence on work performance, with a probability value of 0.000 < 0.05 and a Thcount of 4.213 > Ttable 1.99834. Simultaneously, job satisfaction and productivity have a significant effect on work performance, as shown by the results of the F test with a probability value of 0.000 < 0.05 and Fcal 998.377 > Ftable 3.14. These findings confirm that increasing job satisfaction and productivity simultaneously can drive more optimal work performance in a hybrid work system. The practical implication of this research is the need for a managerial strategy that focuses on improving employee well-being and work efficiency to support organizational performance on a sustainable basis.

The digital transformation in education has encouraged the adoption of computer-based tests (CBT) using video content, which demands stable and efficient network performance. This study aims to evaluate the performance of two queue management algorithms, namely Random Early Detection (RED) and Per Connection Queue (PCQ), in maintaining the quality of service (QoS) of school networks during online video-based examinations. A case study approach was applied using a real network topology in a school environment, and QoS parameters such as throughput, delay, packet loss, and jitter were measured. The implementation was conducted using a MikroTik RB450Gx4 router configured with simple queue settings for each algorithm. The results show that PCQ provides more consistent performance under high user loads, achieving an average throughput of 56,482 bps and lower delay compared to RED. Conversely, RED performs better in scenarios with a small number of users. The study recommends using PCQ for networks with dynamic and dense user environments, while RED is more suitable for low-traffic conditions where latency stability is crucial. These findings offer practical guidance for managing bandwidth and improving the quality of CBT delivery in educational settings.

Wireless networks have become an important part of modern communication infrastructure. However, their performance is often influenced by various environmental factors, including extreme weather conditions. This study aims to analyze the impact of various weather conditions such as heavy rain, high humidity, and extreme temperatures on the stability and quality of wireless networks. The method used is a quantitative approach with data collection of network performance under various weather conditions over a certain period of time. The parameters analyzed include latency, jitter, throughput, and packet loss rate. Initial results show that extreme weather, particularly heavy rain and high humidity, can lead to a significant decrease in network connection stability. These findings are expected to contribute to the planning and optimization of network systems, especially in areas with unpredictable climates.

This study aims to analyze the influence of Organizational Citizenship Behavior (OCB) and Adversity Quotient on employee performance at CV. Mitra Pratiwi. OCB refers to employee voluntary behavior that goes beyond their formal duties, while Adversity Quotient describes an individual's ability to face challenges and work pressures. The research method used is quantitative with data collection techniques through questionnaires. The sample of this study consisted of 50 employees selected using purposive sampling techniques. The results of the study indicate that OCB and Adversity Quotient have a positive and significant influence on employee performance, both simultaneously and partially. This finding confirms that employees with high levels of OCB and good resilience in facing difficulties are more likely to have superior work performance. Therefore, companies need to improve a work culture that encourages positive voluntary behavior and builds employee mental resilience in facing work challenges.                              

This study aims to analyze the influence of Organizational Citizenship Behavior (OCB) and Adversity Quotient on employee performance at CV. Mitra Pratiwi. OCB refers to employee voluntary behavior that goes beyond their formal duties, while Adversity Quotient describes an individual's ability to face challenges and work pressures. The research method used is quantitative with data collection techniques through questionnaires. The sample of this study consisted of 50 employees selected using purposive sampling techniques. The results of the study indicate that OCB and Adversity Quotient have a positive and significant influence on employee performance, both simultaneously and partially. This finding confirms that employees with high levels of OCB and good resilience in facing difficulties are more likely to have superior work performance. Therefore, companies need to improve a work culture that encourages positive voluntary behavior and builds employee mental resilience in facing work challenges.

This study aims to evaluate the effectiveness of employee training at PT XYZ, particularly in enhancing work performance and motivation. The research employs a descriptive qualitative method using purposive sampling. Informants consist of one team leader and three staff members selected through in-depth interviews, observation, and documentation. The results indicate that the training provided remains one-way, lacks interactivity, and is not entirely relevant to employees’ daily tasks. This leads to low motivation and minimal effectiveness in improving performance. Several challenges were also identified, including the absence of post-training follow-up, monotonous delivery methods, and limited time due to workload constraints. The study suggests that organizations should improve their training systems by aligning materials with job relevance, adopting more engaging methods, and ensuring continuous support from management.    

Cybersecurity is continuously challenged by increasingly sophisticated and dynamic cyber-attacks, necessitating advanced adaptive defense mechanisms. Deep Reinforcement Learning (DRL) has emerged as a promising approach, offering significant advantages over traditional intrusion detection methods through real-time adaptability and self-learning capabilities. This paper presents an advanced adaptive cybersecurity framework utilizing five prominent DRL algorithms: Deep Q-Network (DQN), Proximal Policy Optimization (PPO), Twin Delayed DDPG (TD3), Soft Actor-Critic (SAC), and Asynchronous Advantage Actor-Critic (A3C). The effectiveness of these algorithms is evaluated within complex, realistic simulation environments using live-streaming data, emphasizing key metrics such as accuracy (AUC-ROC), response latency, and network throughput. Experimental results demonstrate that the SAC algorithm consistently achieves superior detection accuracy (95% AUC-ROC) and minimal disruption to network performance compared to other approaches. Additionally, A3C provides the fastest response times suitable for real-time defense scenarios. This comprehensive comparative analysis addresses critical research gaps by integrating both traditional and novel DRL techniques and validates their potential to substantially improve cybersecurity defense strategies in realistic operational settings.

The background of this research is the employee performance of the Inspectorate Office in Sikka Regency has not been maximized. This research aimed to (1) determine the decription of work performance, work load, and work stress at the Inspectorate Office In sikka Regency and (2) analyze the influence of workload and work stress on the employee performace of the Inspectorate Office in Sikkaregercy both partially and simultaneously. The population in this research were employess of the Inpectorate Office in Sikka Regency totaling 43 people . This research was carried out by continuing to census or saturated sampling because the population was limited. Data were coocted though questionnaires and analyzed thoghdescriptive  and inferential statistical methods, namely multiple linear regression. Hypothesis testing was done though the F and t-tests. The result of descriptive analysis indicatend that the employe performance, workload,and work stress variables  were categorized as good. The statistical results of the F-test showed that together ( simultaneously ) all independemt variables consisting of workload variable (X1) and work stress variable ( X2) had a significant influence on employee performance.The statistical result of the t-test showed that individually (partially ) the workload variable ( X1) had a significant influence on the employe performance variable and then partially the work stress variable had a significant influence on the employee performance variable at the Inspectorate Office in Sikka Regency . The results of the determination analysis showed that the two independent variables in this research were able to explain the variation in the variation in the ups and downs of employee performance of 28.2%.

The hotel industry is a service sector that relies heavily on the quality of human resources, so internal communication has a central role in maintaining smooth operations and improving staff performance. This study examines the implementation of Human Resource Development (HRD) communication through the General Manager Table Program at XHotel Mojokerto, which is designed as a medium for direct dialogue between management and employees. The program aims to accelerate the distribution of information, accommodate the aspirations of staff, and build more open and effective two-way communication. The research method uses a descriptive qualitative approach, with data collection techniques through in-depth interviews, observations, and documentation studies. The study participants included General Managers, HRD, and hotel staff who participated in the program for a six-month period in 2025. Data analysis was carried out with reference to Mintzberg's organizational communication theory, which emphasizes the managerial role in the functions of monitoring, information dissemination, facilitation, and negotiation. The results of the study show that the General Manager Table Program contributes positively to the effectiveness of internal communication. Through this program, HRD not only plays the role of conveying information, but also as a dialogue facilitator that encourages active employee involvement. The program has been proven to improve communication transparency, speed up conflict resolution, and strengthen a sense of belonging among staff. The impact can be seen in increasing motivation, discipline, and more consistent work performance, while strengthening the harmonious relationship between management and employees in the work environment. The implication of this research is the need for sustainability and the development of similar programs as innovative HRD communication strategies. The application of this model can be a reference in building a positive work culture that supports productivity, service quality, and competitiveness of the hospitality industry amid global dynamics.

Telkomsel has introduced 5G technology in Padang City, evaluated through drive tests using G-Nettrack Pro software to measure Reference Signal Received Power (RSRP) and Signal to Interference plus Noise Ratio (SINR). The tests revealed RSRP values ranging from -44 dBm to -100 dBm and SINR values between -12 dB and 26 dB. While high RSRP does not always guarantee high throughput, higher SINR consistently improves throughput, with the highest throughput reaching 153,053 kbps at SINR levels between 10 and 30 dB. Modulation and Carrier Aggregation (CA) also play a significant role, with 64-QAM modulation combined with CA achieving throughput up to 31,500 kbps, compared to 6,300 kbps without CA. Although CA bandwidth decreased from 100 MHz to 50 MHz, throughput remains higher compared to 20 MHz bandwidth without CA. CA proves highly effective in enhancing throughput through larger bandwidth and more efficient modulation. Additional factors such as handover, interference, and physical and weather conditions also impact network performance. Overall, Telkomsel’s 5G network in Padang City meets the company’s Key Performance Indicators (KPI), despite some areas with suboptimal signal quality.

As 6G networks promise unprecedented speeds and ultra-low latency, AI-based resource allocation plays a crucial role in optimizing network performance. This study explores AI-driven techniques for spectrum management, energy efficiency, and real-time data processing. By leveraging machine learning and deep learning models, AI enhances network adaptability, reduces congestion, and improves overall efficiency. The proposed approaches enable intelligent decision-making, dynamic resource allocation, and predictive analytics to meet the growing demands of future wireless communication. The findings highlight the potential of AI in revolutionizing 6G networks, ensuring seamless connectivity, and maximizing network capacity while minimizing power consumption. These advancements contribute to the development of more sustainable and intelligent telecommunication infrastructures.  

Decision Support System (DSS) is a system used to assist decision makers in determining the best alternative based on certain criteria. Determining retirement eligibility for ASN (State Civil Apparatus) employees is one of the important aspects in human resource management, where this decision affects the future of employee careers, their welfare, and state budget management. This study proposes the development of a decision support system for determining retirement eligibility for ASN employees using the Multi-Attribute Decision Making (MADM) method. The MADM method is a decision-making technique that considers several criteria and alternatives to produce optimal decisions. In this study, the criteria used to determine retirement eligibility include retirement age, length of service, work performance, health, and other factors relevant to the applicable pension policy. The method used in this system includes several steps, namely identifying criteria, assigning weights to each criterion, and evaluating alternatives based on these criteria using calculation techniques such as AHP (Analytical Hierarchy Process) or TOPSIS (Technique for Order Preference by Similarity to Ideal Solution). The results of this evaluation will provide recommendations on whether an employee is eligible for retirement or can still continue his career. The developed system is expected to facilitate the decision-making process regarding ASN employee retirement by providing objective and transparent analysis, so that the decisions taken are more appropriate and in accordance with applicable policies. Thus, this system can improve efficiency and effectiveness in human resource management in government agencies.