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Nusantara Science and Technology Proceedings
Published by Future Science
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Articles 1,542 Documents
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Utilization of Corn Husk Waste as Raw Material for Making Biobutanol Dyah Suci Perwitasari; Graciella Yerrica Nathania; Abid Alghifari
Nusantara Science and Technology Proceedings 4th International Conference Eco-Innovation in Science, Engineering, and Technology
Publisher : Future Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11594/nstp.2023.3639

Abstract

Corn husk waste is a biomass raw material that can be processed into biobutanol. Making biobutanol to reduce the use of fossil fuels. This research used anaerobic microorganisms, namely Clostridium acetobutylicum, which can survive at low pH between 4,5 and 5 at a temperature of 30°C. Corn husk contains 36.218% cellulose; 25.212% hemicellulose; 15.807% lignin. The cellulose raw material content can be used for fermentation because it meets the fermentation content requirements of 36 – 50%. The research methods used include raw material preparation, delignification, dilute acid hydrolysis, and anaerobic fermentation. The research results showed that optimum condition was obtained at the 72-hour fermentation time with the addition of a 5% Clostridium acetobutylicum bacteria volume of 7.0160%. At the 72 hour fermentation time, it showed that the bacteria grew optimally and entered the stationary phase. Biobutanol levels after 72-hour decreased due to reduced nutrients in the fermentation media. The increase in the volume of bacteria affects the final results, the volume of bacteria is added, the final results biobutanol levels will decrease because the nutrients added have been used up. The results of the analysis of butanol levels were determined using Gas Chromatography, the standard for butanol formation obtained at a retention time of 3.598%. The low butanol content (7,0160%) does not require industry standards (96.5 – 99%) to be used as environmentally friendly fuel, due to obstacles in maintaining anaerobic fermentation conditions and not carrying out fermentation filtrate sterilization, which has an impact on the final result of biobutanol content.ly and requires improvement, particularly in the quest for zero defects.
Feature Reduction of Lung Cancer Microarray Data Using Mutual Information Selection and PyCaret-Supported Recursive Feature Elimination Andrew Jonathan Brahms Simangunsong; Valha Tsabita Hidayat
Nusantara Science and Technology Proceedings Multi-Conference Proceeding Series E
Publisher : Future Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11594/nstp.2023.3701

Abstract

Lung cancer remains a leading cause of cancer-related mortality worldwide, and Indonesia's ever-increasing amount of pollution signals an urgency for improvement in lung cancer early detection. One of the methods to detect lung cancer is molecular diagnosis using DNA microarray, which has been proven to be effective. However, the complexity of microarray data with a vast number of features hinders the timely and accurate detection of lung cancer. This study seeks to optimize the features of the data to improve classification performance. Our approach combines Mutual Information Feature Selection with Recursive Feature Elimination, leveraging the PyCaret library to train and evaluate machine learning models. The process involves initial feature reduction using Mutual Information to enhance computational efficiency, followed by training machine learning models with PyCaret. The two best-performing models for each dataset are used to perform recursive feature elimination to search for the most optimal feature. A support vector machine is also used for comparison. The final output will be three subsets of features and another subset that consists of combined features of the rest of other subsets. Finally, PyCaret will be utilized again to train machine learning models with all feature subsets. The study shows that other models can select fewer features compared to the Support Vector Machine and still maintain a powerful predictive power with high accuracy (95% - 98%). In conclusion, our research offers a new approach to selecting optimal features for microarray analysis, with implications for more effective and timely cancer diagnosis.
Arrhythmia Classification Using the Deep Learning Visual Geometry Group (VGG) Model Rudolf Bob Martua B.; Alhadi Bustamam; Hermawan
Nusantara Science and Technology Proceedings Multi-Conference Proceeding Series E
Publisher : Future Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11594/nstp.2023.3702

Abstract

Cardiovascular disease (CVD) is one of the non-communicable diseases (NCDs) and 32% of the world's people die prematurely due to cardiovascular disease (WHO, 2022). The development of computing technology and artificial intelligence (AI), especially Deep Learning (DL), has contributed significantly to helping medical personnel carry out initial pre-diagnosis and classification of heart disease. In this study, we limit heart rhythm detection research into two categories, namely, Normal (N) and Abnormal (An) which are visualized in a standardized amplitude vs time diagram on the PTBDB dataset. The classification model in this research uses the 1-dimensional Deep Neural Network (1D-DNN) Visual Geometry Group, namely, VGG11, VGG13, VGG16, and VGG19. The denoising technique presented in this study on each ECG data sample thereby improving the quality of training data for the AI detection model. The performance of the VGG16 model shows the best training and validation accuracy with the lowest loss, which is 97.85% accuracy; 97.99% precision; 99.75% recall; and 98.52% f1-score. In this way, medical personnel will be helped more quickly in efforts to prevent and control heart disease that occurs in society, especially in the lower middle class. Further research needs to be done to use VGG with more blocks if the structure of the dataset to be classified is much more complex.
Factors Associated with Joint Diseases in The Coastal Community of Laha Village in Ambon, Indonesia Augie Desvie Klausya Kadun; Christiana Rialine Titaley; Annastasia Eklesia Ohoiulun; Filda Vionita Irene de L ima; Ninik Ma’athia Sallatalohy; Fadila Tri Starlia; Maxwell Landri Vers Malakauseya; Etrin Zulqarnain Eka Saputra Linggar; Noviyanter Siahaya
Nusantara Science and Technology Proceedings 1st International Conference on Health and Medicine
Publisher : Future Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11594/nstp.2023.3522

Abstract

Joint diseases have remained a public health concern in the world for decades. These conditions are not only experienced by the elderly but can also occur at a relatively young age. The research objective was to analyze the factors associated with joint disease in the Laha Village in Ambon City. Data were derived from a household health survey in the Laha Village, Ambon City coastal area, in 2022. The dependent variable in this study was the occurrence of joint disease, with the independent variables consisting of demographic status, lifestyle, and dietary patterns. Data analysis used the multivariate logistic regression method. In this study, the prevalence of joint disease in coastal communities in Laha Village was 14.8%. The results of data analysis showed that demographic factors that were significantly related to joint disease were: respondents’ age of 60-71 years (aOR=19.74; 95CI%:7.01-16.66; p<0.001) and those who did not work outside the house (aOR=2.00; 95 CI%: 1.0 -3.94;p=0.041). A significant association was found between joint diseases and those who did not smoke cigarettes (aOR=3.85; 95%CI: 1.65-8.98; p=0.002). We also found that joint disease was also associated with dietary patterns, which were the habit of rarely consuming meat (aOR=2.77; 95 CI%: 1.26-6.10; p=0.011) and the habit of not consuming soft drinks (aOR=2.86; 95 CI%: 1.19-6.86; p=0.012). However, not consuming salty foods reduced the likelihood of developing joint disease (aOR=0.35; 95% CI: 0.13-0.94; p=0.038). The results of this study demonstrated the importance of having a healthy lifestyle and balanced diet to reduce the incidence of joint disease.
Anti Inflammatory and Wound Healing Potential of Liverwort Extract and Collagen-Transdermal Patch in Diabetic Rats Ilmany, Pasha Zaki; Wiratara, Muhammad Rafi Althaf; Fatimah, Ratu
Nusantara Science and Technology Proceedings Multi-Conference Proceeding Series F
Publisher : Future Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11594/nstp.2024.4604

Abstract

Patients with diabetes often experience impaired wound healing, which is associated with intense inflammation. Liverwort extract is rich in secondary metabolites with anti-inflammatory properties, while collagen is crucial for skin regeneration and wound healing. This study investigated the effect of a transdermal patch containing liverwort extract and collagen derived from tilapia bones on inflammation and wound healing in diabetic rats. A completely randomized design was used, consisting of eight groups in total: a normal control group (C) on a standard diet, a negative control group (NC) injected with alloxan at a dose of 120 mg/kg body weight, a positive control group (PC) injected with alloxan and treated with a transdermal patch containing an antibiotic, and five groups injected with alloxan and treated with transdermal patches containing different ratios of liverwort extract and collagen for 14 days. An analysis of variance was used for all data with 5% significance levels (p<0.05). The results showed that alloxan significantly increased blood sugar levels, confirming that the rats were in a diabetic condition. Wound healing was compared among the non-diabetic group, the diabetic group, and the diabetic-treated groups, with significant differences observed. The percentage of white blood cells observed in peripheral blood smear examinations was significantly lower in the diabetic-treated groups compared to the diabetic group, indicating substantial improvement. An increased number of white blood cells is associated with greater inflammation. The topical application of the liverwort and collagen transdermal patch reduced this effect. These findings indicate that the liverwort and collagen transdermal patch has the potential for reducing inflammation and promoting wound healing.
Relationship Marketing among Coconut Sugar Traders, Main Suppliers, and Main Customers Salam, Rudhiana; Primary, Metty Agustine; Rahmat
Nusantara Science and Technology Proceedings Multi-Conference Proceeding Series F
Publisher : Future Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11594/nstp.2024.4605

Abstract

This study aims to analyze relationship marketing among coconut sugar traders in Tonjongsari Village, Cikalong District, Tasikmalaya Regency, West Java, and their main suppliers and customers. The analytical method used is the Wilcoxon Signed Ranks Test, which is suitable for paired ordinal data. Data were collected through questionnaires and analyzed using SPSS 26 software. The analysis results show significant differences in the dimensions of trust, satisfaction, and dependence between suppliers and customers, with significance values of 0.038, 0.018, and 0.031, respectively, while the commitment dimension did not show a significant difference (0.713). The categorization results indicate that all relationship marketing dimensions are in the high category, both for the traders' perceptions of the main suppliers and customers. This study concludes that traders have better relationships with customers than with suppliers in terms of trust, satisfaction, and dependence, although commitment did not show significant differences. These findings provide insights for improving relationship marketing strategies in the future.
Hematopoietic Stem Cell Transplant as Symptomatic Treatment for Myasthenia Gravis: A Literature Review Sutrisno, Jessica Amadea; Andryani, Yani; Devinda, Ni Luh Airin Gita
Nusantara Science and Technology Proceedings Multi-Conference Proceeding Series F
Publisher : Future Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11594/nstp.2024.4606

Abstract

Myasthenia gravis (MG) is an autoimmune neurological disorder that impairs communication at the neuromuscular junction. Over the past seven decades, its global incidence has steadily increased. Approximately 10–20% of MG patients do not respond adequately to or cannot tolerate conventional treatments. Hematopoietic stem cells (HSCs), which are multipotent cells capable of producing all blood cell types and restoring the hematopoietic system, are being explored as a therapeutic option. Hematopoietic stem cell transplantation (HSCT) is under investigation as a potential treatment for severe and refractory MG, with ongoing research aimed at enhancing its safety, and efficacy, and identifying optimal candidates for the therapy. This paper aimed to evaluate the efficacy of hematopoietic stem cell transplantation (HSCT) as a therapeutic option for managing symptomatic myasthenia gravis (MG), especially in cases unresponsive to conventional therapies. A systematic search identified five studies, comprising two cohort studies and three case reports. Most patients in these studies demonstrated promising improvement following HSCT treatment, as indicated by a reduction in MGFA scores and improved clinical manifestations during follow-up assessments. This treatment approach has demonstrated significant potential. However, the current studies are susceptive to bias, and more preclinical research along with high-quality clinical trials, large-scale are required to determine if this emerging treatment can meet the anticipated outcomes.
Access to Zero-Emission Vehicles for Low-Income and Disadvantaged Communities: Evidence from California Yogaswara, Galih Bramudyas; Guan, Yanzhen
Nusantara Science and Technology Proceedings Multi-Conference Proceeding Series F
Publisher : Future Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11594/nstp.2024.4607

Abstract

This study assesses California's Clean Cars for All (CC4A) program, which seeks to improve access to clean-energy vehicles for low-income residents and reduce emissions. The research examines two questions: (1) How effective is CC4A in reducing greenhouse gas emissions and improving air quality? and (2) What factors influence participants' choice of vehicle type—conventional, hybrid, plug-in hybrid (PHEV), or zero-emission vehicle (ZEV)? Using participant data from the California Air Resources Board (n=3,497) from January 2022 to June 2023, the study applies multinomial logistic regression to identify car choice determinants. Findings indicate that CC4A effectively reduces emissions. Higher-income participants are more likely to choose ZEVs or PHEVs, while larger households tend to select conventional vehicles, likely due to limited ZEV options for larger family needs. Participants in disadvantaged communities show a preference for PHEVs over ZEVs, with notable geographic variation—Bay Area residents prefer ZEVs, whereas Central Valley residents favor PHEVs. Key limitations include data gaps, such as missing participant age and education data, and underrepresented geographic areas. The study concludes that while CC4A promotes clean transportation, further steps could enhance program impact. Recommendations include reducing cost barriers for ZEVs, expanding charging infrastructure in low-income areas, and increasing affordable ZEV options for larger households. These insights support policymakers in improving clean transportation access for underserved communities.
Social Sustainability in the Management Zones of Mounts Timpoong-Hibok Hibok Natural Monument, Philippines Morados, Alexander N.
Nusantara Science and Technology Proceedings Multi-Conference Proceeding Series F
Publisher : Future Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11594/nstp.2024.4608

Abstract

Social sustainability is an interdisciplinary approach that ensures human needs are attainable by all and resources are available to all in the community. The study aims to assess the sustainability of social aspects in the multiple-use zone and the buffer zone of Mts Timpoong-Hibok Hibok Natural Monument, Camiguin, Philippines to serve as the basis for sustainable management of the area. The main methods used are descriptive surveys, focus group discussions, and key informant interviews. It also utilized the Basic Social Sustainability Assessment System using 5 criteria and 9 indicators with the Sustainability Index from 0 (lowest level) to 1 (highest level). Among the criteria considered for social sustainability in the upland farming communities, the infrastructure of 0.88 is considered sustainable; Access to basic services reached 0.71 and Population 0.81 at a fairly sustainable level, economic criteria reached 0.411 at an average sustainable level, the lowest was the criterion on educational conditions at 0.273 at a less sustainable level. Based on the analysis of social sustainability factors, a comprehensive, and participatory development plan should be put into place by all stakeholders.
Diversity of Crustaceans in Intertidal Zone at Kukup Beach, Gunungkidul Setyaningrum, Sri; Pangestuti, Azwa Yuliananda; Pasaribu, Callista Nadya Noel; Munajib, Ibnu Ainun; Camelia, Naely Muna; Azahra, Safaa; Judith, Tiara Putria; Eprilurahman, Rury
Nusantara Science and Technology Proceedings Multi-Conference Proceeding Series F
Publisher : Future Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11594/nstp.2024.4609

Abstract

Indonesian waters are famous for their diversity of marine biota. Crustaceans are one of the many marine biota found, especially in the coastal intertidal zone. The waters off the south coast of Java are characterized by large waves and currents. Kukup Beach is one of the beaches located in the area of D. I. Yogyakarta with a flat and undulating beach shape with a narrow intertidal zone. Crustaceans have an important role in coastal ecosystems as bioindicators and omnivore predators. However, not many studies have been conducted to determine the diversity of crustaceans in Kukup Beach. The purpose of this research was to study and determine the diversity of crustaceans in the intertidal zone of Kukup Beach. Sampling and collection were conducted on March 11, 2023, with a systematic sampling method through a belt transect approach. The results showed that 8 families of Crustacea were found in Kukup Beach, namely Alpheidae, Majidae, Pilumnidae, Grapsidae, Portunidae, Oziidae, Xanthidae, and Diogenidae. The result of the calculation of the spesies richness index (R) of Crustacea in the intertidal zone at Kukup Beach was 3,69.

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