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This study examines thee regulations governing the post-notification obligation for share acquisitions from the perspective of competition law in Indonesia, as well as efforts to optimise it as an effective supervisory instrument. Indonesia adopts a post-notification system as stipulated in Law No. 5 of 1999 and its implementing regulations, which require business entities to report acquisition transactions to the KPPU after the transaction has taken effect. Although this system provides flexibility for business entities, in practice there are a number of weaknesses, including its reactive nature, low levels of compliance, and limitations in the effectiveness of oversight in preventing anti-competitive effects. This study employs a normative legal method using legislative, conceptual, and comparative approaches, as well as an analysis of KPPU decisions. The research findings indicate that the post-notification system is not yet optimal in maintaining healthy business competition. Therefore, there is a need to strengthen oversight mechanisms, improve business compliance, and update legal policies to be more adaptive, including the possibility of limited integration of pre-notification elements. It is hoped that these optimisations will enhance the effectiveness of acquisition control and prevent monopolistic practices and unhealthy business competition in Indonesia.

Background: Accurate detection of renal cysts on CT urography requires high diagnostic precision, while manual interpretation by radiologists is susceptible to inter-observer variability and potential delays in clinical decision-making. These challenges underscore the need for a reliable automated detection system to support radiological assessment. Objective: This study aims to develop and evaluate the performance of the Neo-ZasAI application based on the YOLOv8 algorithm for the automatic identification of renal cysts. Methods: Employing a Research and Development design using the ADDIE model, the study encompassed needs analysis, model design, software development, system implementation using 200 CT urography images, and diagnostic performance evaluation. Classification results generated by Neo-ZasAI were compared with radiologist readings through confusion matrix analysis and ROC–AUC assessment. Results: The findings indicate that Neo-ZasAI achieved an accuracy of 97,5%, sensitivity of 96%, specificity of 99%, positive predictive value of 98,9%, and negative predictive value of 96,1%. The ROC analysis yielded an AUC of 0.988 (p < 0.001), demonstrating excellent discriminative capability and high concordance with radiologist interpretations as the diagnostic gold standard. Conclusion: These results suggest that Neo-ZasAI is capable of performing rapid, consistent, and accurate renal cyst detection and is thus feasible for implementation as a clinical decision support system in radiology, with potential integration into PACS workflows and further development to enhance model generalizability.

Fine motor development is a fundamental prerequisite for academic readiness and independence in early childhood. Still, currently, challenges such as sedentary behaviour and screen exposure hinder the optimisation of these abilities. This community service program aims to implement a Play-Based Learning model of fine-motor stimulation to improve the physical and academic readiness of children at Tamalate State Kindergarten in Makassar City. The intervention program was conducted over two weeks through three main stimulation zones: Texture Zone (playdough and finger painting), Precision Zone (beading, origami, and cutting), and Manipulative Zone (busy board and puzzles). The target subjects were children in group B with fine-motor impairments, and the study evaluated 20 children using periodic observation checklists. The results showed a significant transformation, with 95% of children (19 out of 20 participants) experiencing an increase in achievement from the Starting to Develop (MB) category to Developing as Expected (BSH) and Developing Very Well (BSB). These findings confirm that a structured intervention through play zones is not only effective in strengthening intrinsic hand muscles and eye-hand coordination but also in building children's resilience and perseverance in learning. The program recommends integrating a micro-curriculum based on stimulation zones into daily learning plans and strengthening partnerships with parents to maintain consistency in children's development.

This study aims to examine the implementation of tax planning for Corporate Income Tax at CV Wira Arya Sejahtera to legally reduce the tax burden in accordance with tax regulations. The approach used is a descriptive qualitative with a case study method. The data analyzed comes from the financial statements and Annual Tax Returns (SPT) of CV Wira Arya Sejahtera in 2023. The results of the analysis show that the implemented tax planning strategy is able to reduce the amount of Taxable Income (PKP), so that the amount of PPh payable can be reduced from Rp 200,119,828 to Rp 182,731,896. Thus, the company succeeded in achieving tax efficiency of Rp 17,387,933. The implementation of tax planning has a positive impact on tax efficiency and helps improve the company's financial condition. This shows that good tax planning can help companies optimize their tax obligations, increase cash flow, and create long-term benefits for the sustainability of their operations.

The development of digital technology has driven major changes in global marketing strategies, particularly in the luxury smartphone industry, where competition is not only based on technological features but also on brand image and exclusivity. This study aims to systematically analyse various digital marketing strategies implemented by luxury smartphone brands using a Systematic Literature Review (SLR) approach. In this study, researchers identified, evaluated, and synthesised 70 related articles, which were filtered into 15 main articles based on inclusion and exclusion criteria between 2020 and 2025. The analysis results indicate that digital marketing strategies such as influencer marketing, search engine optimisation (SEO), visual content on social media, and the use of augmented reality (AR) and virtual reality (VR) technology have proven effective in increasing brand awareness, customer loyalty, and sales conversions. However, the research also reveals the main challenges faced by companies in maintaining exclusivity and premium experiences through digital channels that are mass-market and open in nature. The study recommends that luxury smartphone brands integrate data-driven personalisation approaches and build strong, authentic brand narratives across various digital platforms to maintain their competitive position in the premium segment. The practical implications of this research can serve as a reference for marketers and decision-makers.

This research analyses the optimisation of the electronic performance appraisal system (e-Kinerja) implementation within the context of the Civil Servant (ASN) performance management transformation at the Sidoarjo Regency Regional Civil Service Agency. The e-Kinerja system represents a digital innovation in ASN performance appraisal, developed in accordance with the Minister of State Apparatus Utilisation and Bureaucratic Reform Regulation Number 6 of 2022. This qualitative research, employing a case study approach, utilised purposive sampling for informant selection, with data gathered through participant observation and documentary analysis. Data analysis followed the Miles and Huberman model, encompassing data reduction, data display, and conclusion drawing. The research findings indicate that the e-Kinerja implementation faces challenges regarding system integration with the Personnel Information System (SIMPEG), synchronisation of personnel data, and equitable dissemination of information to all Civil Servants. Nevertheless, the system is proven to enhance accountability, transparency, and work productivity of Civil Servants through measurable daily reporting mechanisms and monthly targets. This study contributes theoretically to the literature on technology-based public sector performance management and practically through recommendations for developing a more integrated e-Government system. Policy implications include the necessity for accelerating the digitalisation of personnel services, strengthening the capacity of civil service human resources in digital literacy, and developing an information technology infrastructure that supports bureaucratic transformation towards a more efficient, accountable, and responsive.  

Decision Support Systems (DSS) can become inaccurate when used with imprecise, incomplete, or dynamically changing data. Fuzzy logic techniques based on conventional methodologies may be strong at handling vagueness, but are unable to adapt their behavior in response to different data distributions on their own. This paper recommends the creation of an Adaptive Fuzzy Logic Integration Framework that dynamically updates membership functions and rule weights in response to data variation to enhance decision accuracy under uncertainty. The described framework combines Fuzzy Inference Systems (FIS) with learning-based parameter update concepts borrowed from adaptive optimisation. The model was simulated and executed on a hybrid algorithmic platform that included gradient-based parameter tuning and iterative feedback learning. Experimental tests were conducted on uncertainty-generated data sets to compare adaptive and conventional fuzzy models in terms of ISME (Root Mean Square Error), convergence stability, and decision accuracy. Previous results show that the adaptive model achieves a 21.4% increase in accuracy and a 28% improvement in convergence rate compared to non-adaptive fuzzy systems. Moreover, the model ensures stable performance even in the presence of random data perturbations, demonstrating its ability to handle uncertainty. This book incorporates a self-tuning fuzzy decision model that converts static inference structures to dynamic evolving decision engines. The outcomes establish a foundation for next-generation smart DSS for real-time optimization in uncertainty.

A research project entitled Optimisation of Gandasil D Use to Increase Kale (Barassica Oleracea Var. Acephala) Productivity in Hydroponic Systems was conducted at the Pakkea Experimental Garden, Faculty of Agriculture, North Toraja Regency, from March to June 2025. This research project aims to determine the response of Ab mix nutrients and Gandasil D fertiliser in the DFT system to the growth and production of kale plants. The method used in this study was a randomised block design (RAK) with 6 levels of Gandasil D concentration. (KO = Control), (K1 = 0.5 grams/litre of water), (K2 = 1 gram/litre of water), (K3 = 1.5 grams/litre of water), (K4 = 2 grams/litre of water), (K5 = 2.5 grams/litre of water) with 3 replications and with AB MIX concentrations, 0 to 7 days after planting = 400 ppm, 8 to 14 days after planting = 600 ppm, 15 to 21 days after planting = 800 ppm, 22 to 28 days after planting = 1000 ppm, 29 to 35 days after planting = 1200 ppm, 36 days and onwards until harvest = 1500 ppm. The variables observed in this study were plant height, leaf length, leaf width, number of leaves, and plant stem diameter. The results showed that a concentration of Gandasil D 2.5 grams/litre of water gave the best results with an average plant height of 37.93 cm, 12.56 leaves, leaf length of 24.16 cm, leaf width of 14.31 cm, stem diameter of 11.69 mm, and harvest weight of 232.89/plant. The data were analysed using analysis of variance (ANOVA) and followed by a post hoc test at a significance level of 0.05. The analysis of the feasibility of farming showed an R/C ratio of 1.03, which means that kale cultivation using a hydroponic system and the aforementioned nutrient concentration is feasible and profitable.

The era of digital transformation and the Indonesia Golden 2045 agenda demands a new paradigm in governance that prioritises inter-institutional collaboration to achieve effective and responsive governance. This transformation has been accelerated by the implementation of the Electronic-Based Government SIstem (SPBE) and the enactment of Law No. 1 of 2024 concerning Information and Electronic Transactions (ITE). This study analyses the implementation of good governance through digital transformation and inter-institutional collaboration, evaluates the challenges and opportunities in the digital era, and formulates optimisation strategies to support the achievement of Indonesia's Golden 2045. The research employs a normative juridical method, incorporating both conceptual and statutory approaches, and is reinforced by a systematic literature review analysis of current regulations and case studies of SPBE implementation in various regions across Indonesia. Data were collected through documentary studies of 35 laws and regulations and analysis of 40 academic literature sources from the period 2020-2025. The implementation of good governance through digital transformation shows positive results with SPBE success at the regional level, a 28% increase in government effectiveness, and the development of integrated service platforms serving 72 million transactions annually. However, challenges remain in regulatory harmonisation (47% overlapping authorities), digital capacity gaps (34% of institutions not yet optimal), and sectoral culture among institutions. Inter-institutional collaboration through digital transformation demonstrates positive trends in realizing good governance, but requires strengthening of digital legal frameworks, development of technological infrastructure, and organizational culture transformation to support the achievement of the Indonesia Golden 2045 vision.

Employee shift scheduling in the hospitality industry remains a critical yet complex task due to fluctuating operational demands, fairness requirements, and labour regulations. Many hotels still rely on manual scheduling methods, which are time-consuming and prone to biases, particularly in ensuring fair workload distribution across employees. Despite numerous studies on workforce scheduling, limited attention has been given to integer linear programming (ILP) models that address gender-based restrictions and operational fairness simultaneously in real-world hotel contexts, especially in developing regions such as Central Java. This study proposes an Integer Linear Programming (ILP) model to generate optimal shift schedules for hotel staff over a 31-day planning horizon. The model incorporates operational constraints, including one shift per day, gender-based restrictions (which prevent female staff from working night shifts), availability, minimum staffing levels, and fairness in workload distribution. Key parameters and binary decision variables were defined to ensure compliance with the hotel's specific requirements. Empirical data were collected from a hotel in Central Java involving 20 employees, and the model was implemented using Python with a Gurobi solver. The ILP model successfully generated optimal schedules in under 10 seconds, significantly outperforming the manual method, which required over 4 hours. While the manual schedule resulted in an imbalance where some employees worked over 27 days and others only 22, the ILP approach enforced a strict maximum of 26 working days for all staff. Furthermore, the fairness index (FI) improved from 19.2% in the manual method to 0% in the ILP-generated schedule, indicating complete equity in workload allocation. The proposed ILP model demonstrates its effectiveness in improving scheduling fairness, operational efficiency, and compliance with labour policies. This work not only addresses a critical research gap in hospitality scheduling practices in Indonesia but also offers a replicable framework for other labour-intensive service sectors. Future research may explore multi-objective extensions incorporating employee preferences, satisfaction, and dynamic demand fluctuations.

Terrestrial digital television transmitter stations are the main facilities in the transmission of digital television broadcasts to the public. The quality of the transmitted signal is expected to reach the Central Java-1 service area well so as to provide optimal and reliable quality of digital television broadcast performance according to the needs of the community, but currently, complaints about signal problems such as service coverage and reception quality still occur a lot, coverage and signal quality received by community-owned television transmitters cannot be separated from the influence of the quality performance of digital television transmission stations. The purpose of this research is to analyse the coverage performance of digital television services of digital television transmitter stations using the K-Means Clustering Method, identify areas with the best signal coverage and group areas based on the level of signal performance. The data used includes field strength parameters collected through field measurements at 25 service area location points, topography factors and transmitter distance were found to be the main causes of signal quality differences. Data analysis shows that the K-Means Clustering method effectively clusters areas with signal reception quality categories of very good cluster 3 areas, good cluster 8 areas, fair cluster 5 areas and poor cluster 9 areas. The results of this study can be recommended in the evaluation and optimisation of tele-transmitting station networks.

This community service program focuses on enhancing digital marketing capabilities for the Kroket Keraton MSMEs in Tohudan Village, Colomadu, Central Java.  Kroket Keraton  MSMEs, which have traditionally relied on conventional sales,  have faced challenges  in reaching  a wider market and increasing sales. Through this program, intensive training and mentoring on digital marketing strategies were provided,  including the use of social media, creating  engaging content, search engine optimisation (SEO), and digital ad management. The results of this program showed a significant increase in the digital marketing knowledge and skills of MSME actors,  as well as  an increase in sales  and  market reach. Additionally, this program helped build brand awareness and customer loyalty through more effective and efficient digital marketing approaches.   Thus,  this community service program is expected to serve as a model for empowering other MSMEs in facing the challenges of the digital era.

The concept of ‘abandoned land’ in the Basic Agrarian Law (UUPA) No. 5 of 1960 faces interpretation challenges that impact the effectiveness of the management of unproductive Cultivation Rights (HGU). This research aims to analyse the reconstruction of the concept of abandoned land in UUPA and its implications for the management of unproductive HGU to support the optimisation of agricultural land use. This research is conducted through normative juridical with qualitative descriptive analysis of laws and regulations, court decisions, and related literature. The research findings show that the concept of abandoned land in the UUPA is still multi-interpretive, especially regarding the criteria of ‘not being cultivated according to the circumstances or nature and purpose of the right’. This has led to inconsistencies in the application of sanctions against HGU holders who leave their land unproductive. Concept reconstruction is needed by clarifying the objective parameters of productivity, the period of neglect, and law enforcement mechanisms. The implications of this research indicate the need for regulatory revisions to strengthen legal certainty in HGU management, as well as the development of more effective policy instruments to prevent abandonment of agricultural land to support national food security and social justice in agrarian reform.

When making a decision to purchase a motorcycle, it is necessary to consider several criteria. These include price, environmental impact, fuel consumption, design and technology, performance and power, availability of spare parts, after-sales service, warranty on spare parts and distance to the nearest service centre. This research aims to help consumers make informed decisions when buying motorbikes by using the Multi-Objective Optimisation by Ratio Analysis (MOORA) method. The MOORA method was selected because it can handle many criteria efficiently and simply, and produce very objective decisions. Nine criteria were used with four alternatives: motor A, motor B, motor C and motor D. The MOORA calculation results ranked motor C as the highest with a value of 1.90, motor B as the second highest with a value of 1.77, motor A as the third highest with a value of 1.25 and motor D as the fourth highest with a value of 1.20. This research proves that the MOORA method can effectively and accurately provide recommendations for making decisions about purchasing motorbikes with many criteria.

The COVID-19 pandemic has had a significant impact on the Small and Medium Enterprises (SMEs) sector, including Kirimi dessert, a home store located on Jalan Noja I, Kesiman Petilan Village, Denpasar. This study aims to identify problems and provide solutions for Kirimi dessert MSMEs in facing challenges during the pandemic. The business, which focuses on making mille crepes and various desserts, faces several main obstacles such as limited production space, inability to fulfil orders when demand is high, and lack of promotion and personal branding. The research methodology used a qualitative approach through interviews and discussions with the business owner. The solutions offered include the development of MSME innovation, business expansion, and increased promotion through logo design, packaging, and social media optimisation. The implementation of this solution is expected to help MSMEs increase market reach and sales during the COVID-19 pandemic.  

This work introduces a novel hybrid conjugate gradient (CG) technique for tackling unconstrained optimisation problems with improved efficiency and effectiveness. The parameter  is computed as a convex combination of the standard conjugate gradient techniques using  and . Our proposed method has shown that when using the strong Wolfe-line-search(SWC) under specific conditions, it achieves global theoretical convergence. In addition, the new hybrid CG approach has the ability to generate a search direction that moves downward with each iteration. The quantitative findings obtained by applying the recommended technique about 30 functions with varying dimensions clearly illustrate its effectiveness and potential.    

White-collar crime has developed to a transnational level that no longer recognises the territorial boundaries of the state. The form of crime is also increasingly sophisticated and neatly organised, making it difficult to detect. Criminals always try to save money from their crimes through various means, one of which ismoney laundering. In this way, they try to launder illegally obtained money into a form that looks legal. With this laundering, criminals can hide the true origin of the funds or money from the crimes they commit. This research is focused on library studies or document studies, because this research is mostly carried out on secondary data, and Primary Data as a complement, the data to be obtained in this study are collected by means of: Library research The library material referred to consists of primary legal materials, namely laws and regulations related to the title of this research and the Criminal Code. Similarly, secondary legal materials are studied in the form of scientific works of experts including research results (including theses and dissertations) related to the title of the researcher and using Qualitative Data.

Inventory control is very important for companies because without proper inventory control the company will experience problems in meeting consumer needs both in the form of goods and services produced by the company. RSUD Dr. Pirngadi is one of the companies that uses conventional methods to calculate the total cost of inventory so that the costs incurred both for ordering syringes and storage costs are still high, therefore it is necessary to control the inventory of syringes which aims to minimise inventory costs so that company goals can be achieved. In solving the problem of controlling inventory costs to minimise total inventory costs, namely using robust optimisation. Robust optimisation is an optimisation model that contains uncertainty data to obtain the right solution using linear program solving. The results of research at the RSUD Dr. Pirngadi obtained the total cost of inventory according to company policy for the use of 3 mL Terumo syringes is Rp.426,104,665 while the robust optimisation method is Rp.319,647,106 so it can be concluded that by applying the robust optimisation method to the company can save inventory costs of Rp.106,987,599 or 25%.  Furthermore, the total inventory cost of using a 5 mL Terumo syringe according to company policy is Rp.208,402,454 while the robust optimisation method is Rp.166,608,139 so it can be concluded that by applying the robust optimisation method to the company can save inventory costs of Rp.41,794,315 or 20%.

There are many residents in Gebang Putih Village who do not have complete population documents, especially in RW 001. Through the MSIB (Certified Independent Study Internship) program, the author conducts community service by optimising population administration services in the village with several methods, namely collecting data, program implementation, and evaluation. After the community service activities carried out by the author, the number of residents who have incomplete population documents has decreased drastically. The decrease in the number of residents who do not have incomplete documents is the result of optimisation efforts that have been made by the author and village officials.