Scientia: Journal of Multi-Disciplinary Science
SCIENTIA: Journal of Multi-Disciplinary Science refer on: Agricultural Science: Agronomy (cash crops, cereal crops, fodder crops, & weed science), Animal Science (husbandry & veterinary), Computer in Agriculture, Crop Ecology, Crop Science, Entomology, Environment in Agriculture, Fisheries, Forestry, Genetics & Plant Breeding, Genomics, Horticulture (fruits, vegetables, flowers, spice, & condiments), Packaging, Plant Biotechnology, Plant Pathology, Plant Physiology, Plant Science, Postharvest (physiology & technology), Soil Science, Storage & Shelf Life, and Water Management. Biological Science: Botany, Cell Biology, Chemical Biology, Chrono Biology, Computational Biology, Conversion Biology, Developmental Biology, Ecology, Evolutionary Biology, Marine Biology, Microbiology, Microbial Ecology, Microbial Genetics, Molecular Biology, and Zoology. Chemical Science: Analytical Chemistry, Biochemistry, Catalysis, Chemical Biology, Combinatorial Chemistry, Computational Chemistry, Crystal Chemistry, Energy & Environmental Chemistry, Geochemistry, Green Chemistry, Material Science, Molecular Chemistry, Nano Science, Organic Chemistry, Physical Chemistry, and Proteomics. Engineering and Technology: Agricultural Engineering, Bioinformatics, Biological Engineering, Cement & Concrete, Chemical Engineering, Computer-aided Materials Design, Computer Science & Engineering, Civil Engineering, E-Business, E-Commerce, E-Government, Electrical Engineering, Electronics & Communication Engineering, Graphics & Multimedia, Industrial Engineering, Information Technology, Infrastructure Engineering, Machine Learning, Manufacturing Engineering, Mechanical Engineering, Mobile & Wireless Networks, Optical Networks, Remote Sensing & Information System, Software Engineering, and Transportation & Logistics. Social Science: anthropology, archeology, economics, political science, gender studies, regional and cultural studies, population, psychology, state administration, tourism and sociology. Health Science: pharmacology, nurse, toxicology, pharmaceutical science, veterinary science occupational therapy, physiotherapy, nutrition, and related disciplines will be considered to be reviewed.
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<![CDATA[A Comprehensive Analysis of Indonesia's Coffee Exports to the Global Market from 1991 to 2021 ]]>
<![CDATA[Permana, Vebri Dwi]]>;
<![CDATA[Patiung, Markus]]>;
<![CDATA[Wisnujati, Nugrahini Susantinah]]>
<![CDATA[ SCIENTIA: Journal of Multi Disciplinary Science Vol. 3 No. 2 (2024): July-December ]]>
Publisher : <![CDATA[PT. Sangadji Media Publishing ]]>
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DOI: 10.62394/scientia.v3i2.122
<![CDATA[This study aims to analyze the factors influencing the decline in Indonesia's coffee exports and to formulate strategies to enhance these exports. Using a quantitative methodology, data from 1991 to 2021 were analyzed via regression analysis employing SPSS software. The independent variables considered included coffee production volume, harvested coffee land area, the GDP of the United States, and the exchange rate of the Indonesian Rupiah to the US Dollar. The results indicate that Indonesia's coffee production and harvested area significantly influence export volumes. The regression model developed demonstrated a moderate explanatory power with an R² value of 53%, indicating that the model explains 53% of the variance in coffee exports. The Analysis of Variance (ANOVA) test confirmed the model's significance, highlighting that the included variables collectively impact coffee exports. Partial t-test analysis revealed that the harvested area, producer coffee prices, and exchange rates are significant factors. The study concludes that enhancing the quality and competitiveness of Indonesian coffee, improving infrastructure, and adopting supportive government policies are crucial strategies to boost coffee exports. These efforts must address the challenges posed by global market dynamics, competition, and environmental factors to ensure the sustainable growth of Indonesia's coffee sector.]]>
<![CDATA[Exploring Consumer Preferences: Attribute Analysis and Satisfaction with Cavendish Bananas ]]>
<![CDATA[Maulana Sudrajat, Prama Hasta Aditya]]>;
<![CDATA[Wisnujati, Nugrahini Susantinah]]>;
<![CDATA[Sastryawanto, Hary]]>
<![CDATA[ SCIENTIA: Journal of Multi Disciplinary Science Vol. 3 No. 2 (2024): July-December ]]>
Publisher : <![CDATA[PT. Sangadji Media Publishing ]]>
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DOI: 10.62394/scientia.v3i2.123
<![CDATA[The Cavendish banana is known for its quality attributes, including price, taste, skin color, cleanliness, and more. These attributes, when meeting consumer expectations, can lead to high consumer satisfaction. Improving these quality attributes can enhance consumer satisfaction and encourage increased consumption of the fruit. This study aims to analyze the impact of the quality attributes of Cavendish bananas on consumer satisfaction in Sidoarjo. The research was conducted on consumers who purchase directly from small vendors and supermarkets in Sidoarjo using the Accidental Sampling technique. Data were collected through interviews and observations, with a sample size of 12 individuals from street vendors and supermarkets in Sidoarjo. The data analysis method used was qualitative, specifically Qualitative Cross Section data. The results indicate that the majority of Cavendish banana consumers in Sidoarjo responded positively to the attributes of the bananas, including price, taste, quality, and the cleanliness of the display areas.]]>
<![CDATA[Demand Analysis of Young Coconuts in Pasar Pedati Village, Central Bengkulu ]]>
<![CDATA[Syafitri, Aida]]>;
<![CDATA[Yumiati, Yossie]]>;
<![CDATA[Yulihartika, Rika Dwi]]>
<![CDATA[ SCIENTIA: Journal of Multi Disciplinary Science Vol. 3 No. 2 (2024): July-December ]]>
Publisher : <![CDATA[PT. Sangadji Media Publishing ]]>
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DOI: 10.62394/scientia.v3i2.126
<![CDATA[Pasar Pedati Village in Central Bengkulu Regency is one of the regions with a relatively high production of young coconuts. The demand for young coconuts has been increasing yearly, driven by various factors, including population growth. This study aims to analyze the level of demand for young coconuts and assess the influence of factors such as the price of young coconuts, watermelon prices, traders' income, seasons, and sales systems on the demand for young coconuts in Pasar Pedati Village. This research employs a quantitative approach, utilizing questionnaires and interviews conducted with 65 young coconut traders selected using the census sampling technique. Data were analyzed using multiple coefficient of determination analysis (R²) with the assistance of SPSS Statistics 25 software. Hypotheses were tested using both simultaneous regression analysis (F-test) and partial regression analysis (T-test). The findings reveal that the demand for young coconuts is high, with 60% of respondents reporting strong demand. Partial analysis indicates that the price of young coconuts and traders' income significantly influence demand, while simultaneous testing shows that all independent variables collectively have a significant impact on the dependent variable. The adjusted R-square value is 0.856, indicating that 85.6% of the variance in young coconut demand is explained by the independent variables, namely, the price of young coconuts, watermelon prices, traders' income, seasons, and sales systems, while the remaining 14.4% is explained by other factors not included in this study.]]>
<![CDATA[Mobile-Based Marketing Innovation as an Effort to Increase Tourist Interaction and Engagement in the Tourism Industry ]]>
<![CDATA[Iswanto, Dedy]]>;
<![CDATA[Irsyad, Ziqrurrahman]]>;
<![CDATA[Istiqlal, Istiqlal]]>
<![CDATA[ SCIENTIA: Journal of Multi Disciplinary Science Vol. 3 No. 2 (2024): July-December ]]>
Publisher : <![CDATA[PT. Sangadji Media Publishing ]]>
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DOI: 10.62394/scientia.v3i2.145
<![CDATA[This research aims to evaluate the influence of mobile-based marketing strategies on tourists' interaction with digital platforms in the tourism industry through a Systematic Literature Review (SLR) approach. The research process involved selecting literature from various academic databases, such as Google Scholar, Scopus, and DOAJ, with the keywords “mobile marketing,” “tourist interaction,” and “tourism” in the period 2014-2024. The research findings show that mobile technology significantly strengthens travelers' engagement with digital marketing tools, eases information access, and enhances a more personalized travel experience. Despite challenges related to data privacy and technological disruption, these strategies provide a competitive advantage for tourism destinations. This research also highlights the gaps in the application of mobile-based marketing in certain demographic segments, and the need for further research to formulate strategies that are inclusive and sustainable. Future research should focus on integrating digital marketing with traditional methods to create more meaningful and relevant tourism interactions.]]>
<![CDATA[The Role of Artificial Intelligence and Big Data in Improving Personalization of Tourism Marketing Campaigns to Maximize Tourist Experience ]]>
<![CDATA[Irsyad, Ziqrurrahman]]>;
<![CDATA[Iswanto, Dedy]]>;
<![CDATA[Istiqlal, Istiqlal]]>
<![CDATA[ SCIENTIA: Journal of Multi Disciplinary Science Vol. 3 No. 2 (2024): July-December ]]>
Publisher : <![CDATA[PT. Sangadji Media Publishing ]]>
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DOI: 10.62394/scientia.v3i2.146
<![CDATA[This study aims to explore the integration of Artificial Intelligence (AI) and big data in the tourism industry to improve real-time interaction and traveler engagement on digital platforms through a Systematic Literature Review (SLR) approach. The study was conducted by selecting literature from academic databases such as Google Scholar, Scopus, and DOAJ, using keywords such as “AI,” “big data,” “tourism,” and “real-time interaction” within the time span of 2014-2024. The results showed that AI and big data significantly improved service personalization, accelerated decision-making, and increased operational efficiency in the tourism industry. Although the benefits are great, challenges in terms of data privacy, ethical use of consumer information, and shortage of skilled labor are still major barriers to implementation. This research highlights the gaps related to the integration of AI and big data alongside other technologies such as the Internet of Things (IoT) and robotics, and the importance of strategies to overcome organizational resistance to change. Future research should focus on professional skills development and solutions to data privacy challenges to accelerate the widespread adoption of these technologies in the tourism industry.]]>
