Authors Statistics from 3 Countries
| Country | Count of Articles |
|---|---|
| Indonesia | 11 |
| Pakistan | 1 |
| Malaysia | 2 |
Articles
The Influence of Temperature and Drying Time on The Physical and Chemical Characteristics of Cocoa Pod Tea Theobroma (Cacao, L.)
Abstract
Cocoa is one of the plantation products that plays an important role in the Indonesian economic sector because it contains many nutrients that provide health effects on the body, one of which is high antioxidant content. Processing of cocoa shell waste in the food industry can be optimized. One process of utilizing cocoa shell waste is processing it into tea. The drying process affects the resulting cocoa husk tea. In addition, drying temperature also affects the antioxidant content of a food product. The drying process for this research used a food dehydrator. It produces a large driving force of drying air so that it can remove the water content in the ingredients. This research aims to determine the temperature and drying time using a food dehydrator, which produces cocoa husk tea and has characteristics according to Indonesian National Standard (SNI). The research methods used experimental and descriptive analysis. The treatment used in this research employed a food dehydrator temperature, by 50°C, 55°C, 60°C, and 65°C with a drying time of 4.5 hours and 6 hours respectively. The results of this research indicated that the temperature and drying time were 50°C and 4.5 hours to produce cocoa husk tea according to SNI with 8,018% water content and 7,98% ash content.
Read full articleValidity of Environmental Education E-Module Based on Education for Sustainable Development Using Flipcreator Platform to Develop Environmental Awareness in Geography Education Students at Khairun University
Abstract
This research aims to analyze the validity of the environmental education e-module based on Education for Sustainable Development (ESD) to foster environmental awareness of Educational Geography students at Khairun University. The research method used was Research and Development (R&D) with the ADDIE development model. This research was conducted only at three stages of the five stages of the ADDIE model, namely analyze, design and development, while the implementation and evaluation stages were not carried out because this research and development was only limited to the development stage which was focused on the validity test process. The data analysis techniques used in this research were qualitative descriptive and quantitative descriptive analysis techniques. Qualitative descriptive analysis was used to process data reviews from material/content experts and media and design experts which were used to revise the development product. While quantitative descriptive analysis was used to process the data obtained through validation sheets. The results of this research showed that the validity value of the material/content expert validator and media and design experts on the environmental education e-module based on Education for Sustainable Development (ESD) that was developed had very valid, therefore it is suitable to use in the learning process. This can be seen from the validity of the e-module material/content feasibility reaching a score of 91.25% and the validity of the media and design feasibility reaching a score of 90.38%. In addition, the e-module is also packaged using the Flipcreator Platform which displays text, images, animations, and videos so that it is interesting to learn and easy for students to use anytime and anywhere independently in order to foster an attitude of caring for the environment.
Read full articleThe Effect of Feed Rate Variation and Cooling on the Drilling Process of Carbon Fiber and Glass Fiber Composites
Abstract
Carbon Fiber Reinforced Polymer (CFRP) and Glass Fiber Reinforced Polymer (GFRP) composites have extensive applications in the automotive, aerospace, and manufacturing industries due to their high strength and lightweight properties. However, machining processes such as drilling often encounter challenges such as delamination and tool wear due to the anisotropic nature and low thermal conductivity of these materials. This study evaluates the effect of varying feed rates and cooling methods on drilling quality and delamination levels in CFRP and GFRP composites. The cooling methods tested include dry, nanofluid, and cryogenic cooling. Experimental results indicate that cryogenic cooling produces the best hole quality with the lowest delamination levels, even at high feed rates. These findings provide valuable insights into the interaction between machining parameters and cooling methods, offering solutions to enhance the efficiency and quality of composite drilling processes in the manufacturing industry
Read full articleComparison of Naive Bayes Algorithms and Decision Tree for Classifying Hero Fighter Items in the Mobile Legends
Abstract
The classification of hero fighter items in the Mobile Legends Game is a significant challenge due to the complexity of features and the variety of strategies employed by players. This study aims to develop an effective classification model using the Naïve Bayes and Decision Tree algorithms and compare the performance of these two algorithms. The dataset used in this study was obtained from item recommendations during live Gameplay, community sources such as forums, and Game guides. This dataset contains relevant information to support the classification of items for hero fighters, such as hero attributes, roles, and enemy types. The model training process was conducted using the scikit-learn library, with data split into 80% for training and 20% for testing. The study results show that the Decision Tree algorithm consistently delivers better performance than Naïve Bayes. In the evaluation using accuracy metrics, Decision Tree achieved an accuracy rate of 84.78%, significantly higher than Naïve Bayes, which only reached 45.65%. Furthermore, the precision, recall, and f1-score metrics for Decision Tree also showed superior results for almost all classes compared to Naïve Bayes. Based on these findings, the Decision Tree algorithm is recommended as a more suitable choice for classifying hero fighter items in the Mobile Legends Game.
Read full articleFoaming Agents Affect the Physicochemical and Antioxidants in Red Dragon Fruit Powder Drinks from Foam Mat Drying
Abstract
This study investigated the effect of foaming agent type and concentration on foam characteristics during foam mat drying and the physicochemical and antioxidant properties of red dragon fruit powdered drink. Foaming agents, including soy lecithin, fresh egg whites, egg white powder, and whey protein concentrate, were tested at different concentrations (5%, 10%, and 20%). Results showed that soy lecithin produced the most stable foam, effectively preserving bioactive compounds such as phenolics and flavonoids, which contributed to higher antioxidant activity (measured by DPPH and FRAP methods). Whey protein concentrate and fresh egg whites enhanced foam overrun and moisture retention, leading to powders with lower moisture content and higher solubility. The optimal concentration of foaming agent was 10%, which resulted in the best foam stability, antioxidant preservation, and overall product quality. This study highlights the importance of selecting appropriate foaming agents and concentrations to improve the quality and antioxidant properties of red dragon fruit powdered drinks for food applications.
Read full articleDesign and Implementation of Web Service for Laundry Service Payment at RAZ-Q Laundry Samarinda
Abstract
The advancement of technology has facilitated access to information and various applications spanning desktop, web, and mobile platforms, becoming an integral part of everyday life. Among these platforms, websites are the most widely used. The web is widely used for business purposes. One of the common businesses is laundry services, which has become essential for individuals with busy schedules, such as workers and students. Busy daily activities make the need for clean clothes a top priority. However, the existence of many laundry service providers creates intense competition and difficulties for new consumers in finding the right service. This research examines a web services-based laundry service designed to help consumers find and book quality laundry services in their vicinity. It also provides process monitoring features and estimated time for clothes pickup. For laundry service owners, these web services offer opportunities to improve their business. This research uses the Waterfall method of software development, including the stages of analysis, design, coding, and testing. Use case diagrams were used to model the interaction between actors in the application. The web interface is designed according to user needs. The result of this research is web services that can help consumers find and order laundry services easily and efficiently. Blackbox testing is conducted to ensure that all designed functions run properly. This application has the potential to help laundry service owners increase their income. Application development is done using Visual Studi Code with PHP Native programming language and MySQL as database management.
Read full articleFlood Management Study in The Upper Kuncir River: Hydrological Analysis and Watershed Conservation
Abstract
Flooding in the Upper Kuncir River, Nganjuk Regency, is an annual issue causing environmental degradation, infrastructure damage, and economic losses. Increased runoff, erosion, and sedimentation have worsened flood risks due to deforestation and land-use changes. This study analyzes flood factors and conservation strategies through hydrological modeling (HEC-RAS), GIS-based erosion analysis, and watershed simulations. Findings show that high soil erosion (50-80 tons/ha/year) and sediment inflow (18,500 m³ annually) have reduced river capacity by 15%. Peak discharge for a 25-year return period is 125.905 m³/s, exceeding the river’s 85.4 m³/s capacity. Check dams, reforestation, and river normalization are proposed to reduce runoff and control sedimentation. Simulations indicate that structural (check dams, river widening) and non-structural (vegetative cover, soil conservation) measures can reduce peak discharge by 50%. Adaptive reservoir operations at Margopatut Dam can enhance flood control. Integrated watershed management combining engineering and ecohydrological solutions is recommended to ensure sustainable flood mitigation
Read full articleDevelopment and Evaluation of a Cognitive Conflict-Based Physics Learning Module in a Blended Learning Model
Abstract
This study developed and evaluated the effectiveness of a cognitive conflict-based physics learning module within a blended learning environment. The module was designed to enhance high school students' critical thinking skills, which are essential for effective problem-solving and decision-making. The research employed the Research and Development (R&D) method with the 4-D model. The module was tested on two experimental classes, and student performance was assessed through a 5-item essay test and analysis of student worksheets. Results showed significant improvement in all aspects of critical thinking, particularly in basic clarification and inference. This improvement is attributed to the cognitive conflict approach, the blended learning model, and the engaging design of the module. The study concludes that this learning module is effective in fostering critical thinking skills and recommends further testing in other materials and contexts, additional module development, and teacher training.
Read full articleA Bibliometric Exploration of Facebook Marketing Research Trends Using Scopus Database
Abstract
Facebook has developed into much more than just a social media platform since its 2004 launch, changing the way businesses engage with their customers and emerging as a powerful player in the field of digital marketing. Due to the increased attention this evolution has received from academia, extensive research has been conducted on a number of Facebook marketing-related topics, such as customer engagement, brand building, and consumer data collection. Using Scopus as a data source, we conducted a bibliometric analysis in this study to thoroughly review the literature on Facebook marketing and identify important trends, hotspots, and areas in need of further research. 133 pertinent publications from 2009 to 2023 were found by our analysis, underscoring Facebook's significance in digital marketing. This study sheds light on several Facebook marketing research themes, including the efficacy of advertising, consumer behavior on social networks, ethics, and privacy. Furthermore, we found that research is scattered worldwide indicating differences in digital marketing connected to society, economy, and culture. Topics such artificial intelligence, cross-cultural marketing, and the consequences of Facebook algorithm modifications still have more to be discovered even with the wealth of studies. This study supports the relevance of Facebook in digital marketing, indicates areas that demand more research for a better knowledge of the successful use of Facebook in marketing strategies, and provides insight for academics and practitioners.
Read full articleAdvances in Data-Driven Marketing Technologies: A Bibliometric Analysis of Indonesian Research Trends
Abstract
Indonesia, the largest economy in Southeast Asia, has experienced an increase in need for innovative, data-driven marketing research given its fast economic expansion. Business strategy and decision making depend on this study as it let companies adjust to the specificities of local markets affected by socioeconomic, technological, and demographic variables. This study aims to assess the direction and breadth of the research as well as identify any knowledge gaps or underutilized studies in the field of marketing, especially in Indonesia. Bibliometrics is the technique utilized by means of data analysis drawn from the Scopus database in January 2024. Ratih Hurriyati of the Indonesian Education University, with 11 publications to her credit and 209 citations to her works, is the most active writer in this area. The results show the key trends in Indonesian marketing research. Apart from that, the "International Journal of Data and Network Science" is the most often published journal source with 36 papers altogether. Particularly in relation to the use of digital technology to improve consumer satisfaction and promote loyalty in innovative markets, these findings provide new ideas for policy development and more research. Marketing research done in Indonesia has a huge possibility to considerably add to the literature in the globe when one considers both local and global dynamics.
Read full articleBetaSutte: Applying Novelty in Data Forecasting with the Modified Trend-Augmented ?-Sutte Indicator, A Case Study on Bank Mandiri (BMRI) Stock Prices
Abstract
This study assesses the effectiveness of the BetaSutte forecasting model, an enhanced version of the ?-Sutte Indicator, dubbed the Modified Trend-Augmented ?-Sutte Indicator, in forecasting the stock prices of Bank Mandiri (BMRI). Data from investing.com, spanning January 2018 to December 2023, was divided into training and testing subsets to both develop and validate the forecasting model, ensuring it performs well across unseen data. BetaSutte builds on the foundational ?-Sutte by integrating advanced trend analysis, mitigating the influence of outliers, and utilizing automatic parameter optimization to boost forecasting precision. The efficacy of BetaSutte is evaluated against well-established models such as SVR, XGBoost, and ARIMA. ARIMA was chosen for its detailed management of time-series data via autoregressive, differencing, and moving average components. In contrast, SVR and XGBoost are recognized for their strong predictive performance. The performance of these models was gauged using Root Mean Square Error (RMSE) and Mean Absolute Percentage Error (MAPE). These metrics shed light on the extent of forecasting errors and the percentage of relative errors, respectively, providing a comprehensive view of each model’s predictive accuracy for BMRI stock prices. The results demonstrated that BetaSutte outstripped the other models in terms of RMSE and MAPE, highlighting its enhanced ability to accurately reflect the dynamics of BMRI’s stock prices with greater precision and dependability. This establishes BetaSutte as a formidable tool in financial forecasting, particularly valuable in environments characterized by volatile market conditions and unpredictable data patterns.
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