Trade Effect of Sanitary and Phytosanitary (SPS) and Technical Barriers to Trade (TBT) on Indonesia's Shrimp Export

The development of the implementation of non-tariff measure policy, in the world market which has a trend, increased every year. There are seven (7) NTM policies mostly implemented in the international market. The most policy application is the implementation of Technical Barriers to Trade and Sanitary and Phytosanitary. Agricultural commodities both vegetables and live animal products are commodities mostly become subject to NTM policy in the form of SPS (Sanitary and Phytosanitary) and TBT (Technical Barriers on Trade) in the international market. Indonesia as an agricultural country that has advantages in agriculture and fisheries cannot avoid the implementation of SPS and TBT policies. This research was aimed to analyze the effect of SPS and TBT on Indonesia’s shrimp export using the gravity model. The results showed that the GDP of exporters and the exchange rate have negative influences on Indonesia’s shrimp exports. Meanwhile, the GDP of the importers and trade cost have positive influences on the export of shrimp Indonesia. while the SPS policy and TBT don’t affect Indonesia's exports of shrimp in the international market. This indicates that Indonesian shrimp exporters are able to quickly adjust the SPS and TBT policies applied by importing countries

Export of Indonesian cinnamon in international market: competitiveness and performance

The high level of competition in the world cinnamon market causes a downturn in Indonesian cinnamon exports in international market. In 2019-2020, sales of Indonesian cinnamon in international market have experienced a downward trend. This study aimed to analyse the trend of Indonesian cinnamon’s export value in international market in 2001- 2020 compared to Sri Lanka, Vietnam, and China, as the main exporting countries, then analyse the factors influencing the export value of Indonesian cinnamon in the United States, the Netherlands, Brazil, Germany, and Thailand, as main destination countries in international market by adding spatial and competitiveness variables. This study utilized secondary data and time-series data. The data obtained in this study were collected from various data sources such as International Trade Centre, World Bank, WTO, UN Comtrade, Artnet, UNESCAP, Pacific Exchange Rate Service, and other publications related to this research. Data on the performance of Indonesian cinnamon in international market utilized HS 1996 with HS code 0906 (Cinnamon and cinnamon-tree flower) in the 2001-2020 range. The results showed that the exports of Indonesia\u27s cinnamon in international market had a positive trend. Indonesia had a very strong comparative advantage, so the potential to increase Indonesia\u27s market share was very open in international market. The model estimation results showed that trade costs had an insignificant effect on Indonesian cinnamon exports in international market, while other variables, namely the GDP of the importing countries, the GDP of the exporting countries, the exchange rate, population, and competitiveness had a significant influence

Marketing efficiency perspective of sustainable Andaliman agroforestry in Humbang Hasundutan Regency

Indonesia has so many herbal medicinal plants and spices that are endemic and location-specific since it has a very vast tropical rainforest area. One of them is Andaliman (Zanthoxylum acanthopodium DC). This endemic species is very sensitive to climate and location changes so the farmers only have around 5 Andaliman trees planted in between any other kind of plants in their agroforestry land on average. There is an undeveloped and very promising future for the competitiveness improvement of Indonesia’s herbs and spices. This study was accomplished to investigate the marketing efficiency of Andaliman agroforestry in Humbang Hasundutan Regency to accommodate stakeholders in formulating policies to progress Andaliman's competitiveness. The results showed that all of Andaliman’s marketing channels in the research area were efficient. The most efficient was Channel II, followed by Channel III, and the last position was seated by Channel I. Marketing losses and labour costs were at the top of the list as the largest marketing costs, so they truly needed to be optimized at almost all channel levels and types of marketing channels to improve marketing efficiency. Therefore, referring to these results, we composed a suggestion to improve farmers' welfare by doing simple processing such as processing Andaliman into several dried and packaged products that are easier to use, long-last, and attractive, as well as combining more efficient production with distribution in shorter marketing channels. This will encourage farmers to maintain Andaliman agroforestry as a farming option that is more sustainable and natural

Genetic analysis and selection criteria in Bambara groundnut accessions based yield performance

The knowledge of genetic variability and breeding techniques is crucial in crop improvement programs. This information is especially important in underutilized crops such as Bambara groundnut, which have limited breeding systems and genetic diversity information. Hence, this study evaluated the genetic variability and established the relationship between the yield and its components in Bambara groundnut based on seed weight using multivariate analysis. A field trial was conducted in a randomized complete block design with three replications on 28 lines. Data were collected on 12 agro-morphological traits, and a statistical analysis was conducted using SAS version 9.4 software, while the variance component, genotypic and phenotypic coefficient variation, heritability, and genetic advance values were estimated. A cluster analysis was performed using NT-SYS software to estimate the genetic relations among the accessions. The results showed significant variability among the accessions based on the yield and yield component characteristics. The evaluated lines were grouped into seven primary clusters based on the assessed traits using the UPGMA dendrogram. Based on the overall results, G5LR1P3, G1LR1P3, G4LR1P1, G2SR1P1 and G3SR1P4 performed the best for the yield and yield components. These improved lines are recommended for large-scale evaluation and utilization in future breeding programs to develop high-yield Bambara groundnut varieties

Inheritance and genetic analysis of seed weight and associated traits in bambara groundnut (Vigna subterranea L.) genotypes

Knowledge of genetic variability within species of Bambara groundnut and the nature of breeding techniques are critical in this crop improvement programme. The importance of this information in underutilised crop species that mainly existing as landraces with limited information about their breeding systems and genetic diversity becomes important. Hence, this study was conducted to evaluate the genetic variability and to establish the relation between yield and its components in Bambara groundnut using multivariate analysis based on seed weight. To achieve this objective, firstly, a field trial was conducted in randomized complete block design with three replications on five Bambara groundnut genotypes from Nigeria, namely; Giwa, Duna, Cancaraki, Jatau, and Maiki. Prior to the field evaluation, the seeds of each genotype were grouped into three seed weight categories namely large, medium and small-seed size. In the second experiment, 28 lines were selected based on top grain yield plants from each seed weight category from first generation of the previous field evaluation. Data were collected on 25 agro-morphological traits and statistical analysis was conducted using SAS version 9.4 software for the analysis of variance, while variance component, genotypic and phenotypic coefficient variation, heritability and genetic advance values were estimated. Cluster analysis was performed using NT-SYS software to estimate the genetic relations among the Bambara groundnut lines. The present study revealed significant levels of variability among the genotypes, seed size categories and interaction of genotypes and seed size categories for most of the yield and yield components. High values of genotypic coefficient of variation (GCV≥20%) coupled with genetic advance (GA≥20%) was recorded for the number of medium seed weight per plant (GCV=36.76%, GA=36.15%), total large size seed weight per plant (30.34%, 28.26%), total medium size seed weight per plant (25.25%, 21.42%) and hundred seeds weight (20.02%, 29.29%), while moderate GCV (>10%) value was obtained for the total number of seed per plant (11.34%). Among the genotype and seed size combinations, G5S is the best for yield and yield component traits, while genotypes G3 is the best for yield and yield components, whereas among the seed size categories small seed size showed the high yield and yielding components. It was concluded from the second-generation progenies evaluation indicates that considerable amount of variation exists among Bambara groundnut cultivars for yield and yield components. Moderate broad sense heritability values couple with high genetic variance for growth traits such as wide plant canopy (52.17%) and number of branches (34.36%), while low broad sense heritability values (0 to 30%) were recorded for other traits. Almost all of the traits positively associated with the yield trait except the number of days to emergency, plant height, wide canopy, days to maturity, fresh and dried biomass weight. Finally, the lines evaluated were grouped into seven primary clusters using the unweighted pair group method with arithmetic mean (UPGMA) dendrogram based on the measured traits. Based on genetic diversity results and agronomic traits performance, improved lines, G5LR1P3, G1LR1P3, G4LR1P1, G2SR1P1 and G3SR1P4 performed best in terms of yield and yield components. These improved lines are recommended for large scale evaluation and utilisation in the future breeding programme for development of high yield Bambara groundnut varieties

A Deep Learning Approach To Vehicle Fault Detection Based On Vehicle Behavior

Vehicles and machinery play a crucial role in our daily lives, contributing to our transportationneeds and supporting various industries. As society strives for sustainability, the advancementof technology and efficient resource allocation become paramount. However, vehicle faultscontinue to pose a significant challenge, leading to accidents and unfortunate consequences.In this thesis, we aim to address this issue by exploring the effectiveness of an ensemble ofdeep learning models for supervised classification. Specifically, we propose to evaluate the performance of 1D-CNN-Bi-LSTM and 1D-CNN-Bi-GRU models. The Bi-LSTM and Bi-GRUmodels incorporate a multi-head attention mechanism to capture intricate patterns in the data.The methodology involves initial feature extraction using 1D-CNN, followed by learning thetemporal dependencies in the time series data using Bi-LSTM and Bi-GRU. These models aretrained and evaluated on a labeled dataset, yielding promising results. The successful completion of this thesis has met the objectives and scope of the research, and it also paves the way forfuture investigations and further research in this domain

American option prices and optimal exercise boundaries under Heston Model–A Least-Square Monte Carlo approach

Pricing American options has always been problematic due to its early exercise characteristic. As no closed-form analytical solution for any of the widely used models exists, many numerical approximation methods have been proposed and studied. In this thesis, we investigate the Least-Square Monte Carlo Simulation (LSMC) method of Longstaff & Schwartz for pricing American options under the two-dimensional Heston model. By conducting extensive numerical experimentation, we put the LSMC to test and investigate four different continuation functions for the LSMC. In addition, we consider investigating seven different combination of Heston model parameters. We analyse the results and select the optimal continuation function according to our criteria. Then we uncover and study the early exercise boundary foran American put option upon changing initial volatility and other parameters of the Heston model

A Deep Learning Approach To Vehicle Fault Detection Based On Vehicle Behavior

Vehicles and machinery play a crucial role in our daily lives, contributing to our transportationneeds and supporting various industries. As society strives for sustainability, the advancementof technology and efficient resource allocation become paramount. However, vehicle faultscontinue to pose a significant challenge, leading to accidents and unfortunate consequences.In this thesis, we aim to address this issue by exploring the effectiveness of an ensemble ofdeep learning models for supervised classification. Specifically, we propose to evaluate the performance of 1D-CNN-Bi-LSTM and 1D-CNN-Bi-GRU models. The Bi-LSTM and Bi-GRUmodels incorporate a multi-head attention mechanism to capture intricate patterns in the data.The methodology involves initial feature extraction using 1D-CNN, followed by learning thetemporal dependencies in the time series data using Bi-LSTM and Bi-GRU. These models aretrained and evaluated on a labeled dataset, yielding promising results. The successful completion of this thesis has met the objectives and scope of the research, and it also paves the way forfuture investigations and further research in this domain

Young consumer awareness of halal food in Indonesia

The future of the halal product industry in Indonesia is determined by Indonesian consumers’ demand. Young consumers have a significant role in the development of halal products because 25 percent of consumers in Indonesia are young consumers. Therefore, this research focused on the awareness of young Indonesian consumers to halal products. The purpose of this study was to analyse the factors affecting the awareness of young Indonesian consumers. The data used were cross-section data collected from young consumers of halal products for the 17-25 age group by using 157 respondents. Convenience sampling was used to determine the interview sample. Data were analysed using the Structural Equation Model method. The results show that the young consumer awareness of halal food in Indonesia was high. The factors affecting young consumer awareness were health and religion knowledge