The Importance of Creating Artificial Intelligence Supported Future Scenarios in Decision Making Processes

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Artificial intelligence technologies are rapidly developing and having a major impact on the business world. Decision-making processes play an important role for the success of an organization. However, in today’s business world with its complexity and uncertainty, it becomes difficult to manage decision-making processes. At this point, creating future scenarios supported by artificial intelligence and working on different scenarios helps businesses to be more prepared for uncertainty.

Artificial intelligence-supported scenarios can be utilized across various sectors and fields of work. AI enables businesses to analyze past data, predict trends, and consequently work on future scenarios to make more informed decisions. The significance of future scenarios lies in identifying risks and opportunities in advance, adapting to future changes, and being proactive in competition. By evaluating potential developments, shaping your business strategy, you can gain a competitive advantage and make more reliable decisions.

Qualitative methods were employed in the research. Interviews were conducted with managers from 6 different professional groups (software, biomedical, public, construction, university, e-commerce). Data was collected and analyzed using semi-structured interview forms consisting of 4 questions. When the findings were evaluated, no concerns or negative expressions regarding the use of artificial intelligence were expressed. Except for public institutions, everyone has AI in their planning. Each sector believes it is important. No negative concerns were expressed. The prominent concepts in the findings are: Speed, big data, gaining competitive advantage, personalized customer experience, risk analysis, cost advantage, technology adaptation, optimization, accurate and fast situation detection, efficiency, etc.

It is thought that the research will create significant awareness for businesses in the turbulent period of the 21st century, where uncertainties are greater than ever. Despite all the positive aspects, AI-supported decision-making processes also carry some risks. The most prominent risks include the applicability of AI-supported scenarios, security concerns, the existence of ill-trained AI models, ethical issues and data privacy.

Students’ Perception of The Implementation of Running Dictation in Teaching Reading

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This study examines students’ perceptions of using Running Dictation as a teaching strategy in reading applied by the teacher in the seventh grade of Junior High School in Bandar Lampung. A descriptive quantitative approach was employed, with data collected through a structured questionnaire. The sample included 20 students. The data collection technique involved distributing a closed-ended questionnaire to gather quantitative data on students’ perceptions including awareness, past experiences, motivation, knowledge, and social interaction. The questionnaire consists of 10 positive and 10 negative statements to assess students’ perception of the Running Dictation strategy. The responses were measured using a Likert scale, ranging from “Strongly Agree” to “Strongly Disagree.” The results are categorized into two main types of perceptions: positive and negative. The results indicate that most students positively perceived running dictation in reading instruction. Specifically, 10 students agreed, 7 strongly agreed, and 3 were neutral in response to statements about these benefits. Conversely, the negative statements in the questionnaire, designed to assess any difficulties or drawbacks of Running Dictation, received limited agreement. Overall, the results suggest that most students found Running Dictation beneficial, noting increased engagement and comprehension through its active and collaborative approach to reading.

Impacts of climate variability on the spatio-temporal dynamics of plant formations in the forest-savannah transition zone: the case of the Lamto Scientific Reserve, Central Côte d’Ivoire

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Understanding climatic variability’s effects on land and biodiversity is vital for guiding sustainability, conservation, and climate impact predictions in fragile ecosystems like Côte d’Ivoire’s forest-savanna transition zone. This study aims to analyse the impact of climate variability on the spatio-temporal dynamics of land use in the Lamto Scientific Reserve. To do this, a set of monthly climate data covering the period from 1990 to 2022 was used, including indicators such as rainfall, maximum, minimum and average temperatures, drought and standardised rainfall indices. The study also involved the classification of Landsat images dating from 1990, 2002, 2012 and 2022, enabling changes in land use to be observed. The corresponding areas were correlated with the climatic variables using a Spearman correlation test. The results show a transition from savannah to denser tree cover in the reserve. In addition, an increase in rainfall, varying between 900 and 1687 mm, suggests that Lamto could be classified as a humid region. The analysis highlights the complex interactions between climate change, particularly high temperatures, and land-use dynamics. Gallery and semi-deciduous forests show resilience in the face of rising temperatures, favouring their expansion. On the other hand, pre-forest formations, such as open forests and wooded savannahs, are more affected by these temperatures, which hinders their development. Tree savannahs also show a certain resilience, while shrub savannahs and bare land are often associated with ecological degradation processes in response to high temperatures. Finally, although rainfall plays a role, its influence seems minor, suggesting that other environmental or climatic factors, such as watercourses or microclimate, play a more significant role in land use/land cover dynamics.

Holistic Management of Diabetic Ulcer in Construction Worker with Low-Risk Neuropathy Symptoms Score and Proximal Phalanx Diggiti III-IV Pedis Dextra Amputation History

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Diabetic ulcers are the most common complication of uncontrolled Diabetes Mellitus (DM), characterized by high blood glucose levels that lead to complications such as neuropathy (motor, sensory, autonomic) and vascular abnormalities, making infections more likely. According to research in Indonesia, the incidence of diabetic ulcers ranges from 15-25% of the total number of diabetes mellitus patients, with an annual prevalence of 2% to 5-7.5% in patients with neuropathy. Application of evidence-based medicine-based family doctor services to patients by identifying risk factors, clinical problems, and patient management based on a patient-centered and family problem-solving framework. This case report taken by primary data through auto-anamnesis, physical examination and home visits. Secondary data was obtained from the patient’s medical record. The assessment is based on a holistic diagnosis from entire of the study qualitatively and quantitatively. Patient Mr. E, 61 years old has internal factor risks such as elderly age, curative treatment patterns, inappropriate eating habits, lack of knowledge about the disease which, and external risk factors in the form of curative family treatment patterns and lack of family support related to patient’s disease. Patient’s management is holistic and comprehensive, patient-centered, family approach, and community-based in the literature based on EBM. Patient was intervened with media posters about DM, diet, proper diabetic ulcer care and educating families to support patients. Results of the intervention evaluation are increase in patient and family’s knowledge, controlled blood sugar, and eating behavior according to Adequacy of Nutrition Level.

Management of School Finance in a Depressed Economy Society: Imperative for Academic Performance of Students in Selected Secondary Schools

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The study examined the management of school finance in a depressed economy in selected schools in Ado Local Government, Ekiti State.  The study examined academic performance of students. The study adopted descriptive survey research design. The study population comprised all private schools in Ado local government, Ekiti State. The sample consisted of 12 administrators, 60 parents and 240 students selected for the study through multistage sampling procedure using simple random and purposive sampling technique. Three instruments were used for the study titled “School Finance Management Questionnaire” (SFMQ), “Parents Methods of School Fees Payment Questionnaire” (PMSFPQ) and inventory for collection of data on students’ academic performance. The questionnaires were validated and tested for reliability by employing split-half method which yielded 0.83 and 0.85 for SFMQ, PMSFPQ respectively.  The study revealed that students’ academic performance was low. The study revealed that the majority of the school owners generate fund through loan, school fees and other grants. The study also found a significant relationship between depressed economy and academic performance of students. Based on the findings, it was recommended among others that government should see to the needs of private schools in terms of finance, since they pay tax to the government. This would reduce the burden of the parents and improve the performance of the students as well.

The Ratio of Fermented Mother Liquor and Molasses as Additives in Making Elephant Grass Silage (Pennisetum purpureum Cv. Thailand) and Corn Cob (Zea Mays. L) on the Quality of Ensilage Results

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This study aims to determine the effect of the ratio of fermented mother liquor (FML) and molasses as additives in the manufacture of elephant grass (Pennisetum purpureum cv. Thailand) and corn stalks (Zea mays) silage on the quality of ensilage results in terms of nutrient concentration and in vitro digestibility. The research materials were elephant grass of the Pakchong variety and corn stalks. FML and molasses were added to elephant grass and corn stalks in the processing of ensilage. This study used a Completely Randomized Design with 4 treatments and 3 replications in total elephant grass and corn stalks so that 24 experimental research units were obtained. The treatments were P1 = corn cob+ additive (FML 0% + 6% Molasses), P2: (FML 2% + 4% Molasses), P3: (FML 4% + 2% Molasses) P4: (FMl 6% + 0% Molasses) and P1: R. Gajah + additive (FML 0% + 6% Molasses), P2: (FML 2% + 4% Molasses), P3 (FML 4% + 2% Molasses), P4 (FML 6% + 0% Molasses). Data were analyzed using Analysis of Variance (ANOVA), if the results obtained were significantly different, then continued with Duncan’s Multiple Test. The results showed that the treatment had a very significant effect (P <0.01) on the content of BO, PK and LK as well as KCBK and KCBO. The study concludes that the use of the Ratio at P4: (FMl 6% + Molasses 0%) can produce silage in the very good category of ensilage on elephant grass and corn stalks in terms of green forage preservation with a pH below 4.2 and has good nutritional value with a PK content of around 12% and BO digestibility above 60%.

Physicochemical Characteristics of Mocaf Flour and Rice Flour-Based Gluten-Free Cookies

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This study investigated the effects of mocaf flour (modified cassava flour) concentration and baking temperature on the surface structure, color, moisture content, and hardness of gluten-free cookies. Cookies were prepared using mocaf flour and rice flour, with mocaf concentrations of 30%, 50%, and 70%, and baking temperatures of 150°C, 160°C, and 170°C. The results demonstrated that higher mocaf flour concentrations and increased baking temperatures significantly influenced the cookies’ physical properties. Higher mocaf concentrations and baking temperatures resulted in greater hardness values and lower moisture content. Specifically, cookies with 50% mocaf flour baked at 170°C exhibited the highest hardness (3.08 kgf) and the lowest moisture content (4.53%). Color analysis revealed that lightness (L*) decreased as both mocaf concentration and baking temperature increased, while redness (a*) and yellowness (b*) values rose, indicating darker cookies due to the Maillard reaction and caramelization. Additionally, the surface analysis showed that the inclusion of mocaf flour contributed to a rougher texture compared to the smoother surface of control cookies. These findings suggest that mocaf flour is a promising alternative to wheat flour in gluten-free cookie formulations, providing enhanced shelf stability, distinct textural characteristics, and appealing color properties. Future studies could optimize mocaf flour usage to improve product quality while addressing consumer preferences for gluten-free baked goods.

The Impact of Burnout and Compensation on Turnover Intention Mediated by Job Satisfaction in a Private Hospital in Tangerang

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The purpose of this study was to find that burnout and compensation have a significant effect on job satisfaction and turnover intention, and job satisfaction can function as a mediator between burnout, compensation, and turnover intention in health workers and health support staff at One of the Private Hospitals in Tangerang. This study uses a descriptive quantitative approach with a cross-sectional study design. The accessible population in this study were health workers and health support staff from January to May 2024 with a total accessible population of 1,030 health workers and health support staff. This study uses a non-probability purposive sample, the selected subjects meet the inclusion and exclusion requirements, so that based on the formula and requirements, 288 samples were obtained. The data analysis technique uses path analysis with testing and data analysis in this study assisted by using SMART PLS 3.0 software. The results of the analysis show that burnout has a negative and significant effect on job satisfaction. and a positive and significant effect on turnover intention. Compensation has a positive and significant effect on job satisfaction, and a negative and significant effect on turnover intention. Job satisfaction has a negative and significant effect on turnover intention. In addition, burnout negatively and significantly affects turnover intention through the mediation of job satisfaction, while compensation also negatively and significantly affects turnover intention through the mediation of job satisfaction.

Stock Price Forecasting on Time Series Data Using the Long Short-Term Memory (LSTM) Model

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Stock price forecasting on time series data is a complex task due to the dynamic and uncertain nature of financial markets. This research aims to forecast stock prices by applying an advanced machine learning model, namely Long Short-Term Memory (LSTM), a deep learning architecture that excels in capturing long-term dependencies in time series data. The dataset used in this study consists of 1221 daily ANTM.JK stock price data over the period April 30, 2019 to April 30, 2024. The model was trained and evaluated using performance metrics such as Mean Absolute Percentage Error (MAPE) and Root Mean Squared Error (RMSE) in measuring the level of forecasting accuracy. The results show that the LSTM model can accurately predict stock prices on time series data, as evidenced by the MAPE accuracy evaluation value of 2.52% and RMSE of 54.64. These findings indicate that the LSTM model is effective in predicting stock prices on time series data and can be used as a supporting tool in making the right investment decisions.

Analysis of the Effectiveness of Internal Control as Fraud Prevention in the Kupang City Government

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This study aims to evaluate the effectiveness of the implementation of the Internal Control System (ICS) in financial management and Government Regulation (PP) No. 06 of 2008 as a fraud prevention measure. This study employs a qualitative descriptive approach. Primary data were gathered through questionnaire about internal control system, completed by relevant officials, which where supplemented by additional insights obtained from interviews.

Meanwhile, secondary data were sourced from the Summary of Audit Results (IHPD) for the East Nusa Tenggara Province. Given the paucity of research on internal control-based auditing in the government sector and the rising instances of corruption in public financial accountability and operations, it is critical to delve deeper into this issue to investigate the effectiveness of internal controls in preventing fraud within the government. This study identifies the causes of compliance findings in the Financial Statements of the Regional Government of Kupang City for the 2023 Fiscal Year, analyzed them in relation to the effectiveness of the Internal Control System (ICS). The findings reveal that ineffective implementation of internal control is a significant factor contributing to compliance violations of regulations, which result in state or regional losses that require recovery.