Potential Usage of Solar Energy as a Renewable Energy Source in Petukangan Utara, South Jakarta

Indonesia is a tropical country located on the equator. The average intensity of solar radiation in Indonesia is 4.8 kWh/m2. This makes Indonesia a country with new and ren ewable energy potential, one of which is solar panel technology. The first step that must be done in the process of installing solar panels in a place is to analyze the potential of solar energy. In this study, an analysis of the potential of solar energy as a new renewable energy source has been carried out at Budi Luhur University, North Petukangan, South Jakarta. Based on the research results, the maximum photovoltaic efficiency that can be achieved is 21.45%. During the day, the efficiency of the solar panels increases along with the ncrease in the value of the voltage obtained. However, the higher the panel temperature, the lower the efficiency of the solar panel. Therefore, a cooling system is needed to anticipate this.

Discourse for Transition toward Sustainability Development in Industrial Ecology Context in Kutai Kartanegara

A rich ecological value area within East Kalimantan, Kutai Kartanegara, represents a specific-particular ecological system of an island in a tropical country. Covered by the evergreen forest in the past, it has a closed-loop system formed naturally due to its metabolism. This system maintains the high diversity of nature which provides abundant resources both renewable and non-renewable. Owing to its ecological system value, the earth has been numerous beneficial the economic sector both for country and region for decades. Let say coal is one of the attractive resources for the energy sector, which has been contributing over 80% of the GDRP of Kutai Kartanegara in 2010.

Faktor Risiko Demam Berdarah di Negara Tropis

Tropical countries are the largest contributor to the incidence of Dengue HemorrhagicFever (DHF), but research on risk factors is still independent in various countries, it cannot beconcluded holistically. Through the research design, a systematic review is able to summarize andanswer the causes of DHF in this tropical country. This research method is a systematic review withguidelines following the 2009 PRISMA Checklist. In the initial search, 1,680 articles were foundusing the keyword “risk factors for Dengue Hemorrhagic Fever”, reduced to 274 article titles afteradding the keyword “tropical country”. Furthermore, the relevant abstracts were fi ltered and found37 selected article items. Through critical appraisal of the full text of the article, it was found that 17articles met the selection criteria for further review in this study. The results showed that there were5 major groups of risk factors that were widely studied, namely sociodemography, climatology, placeof dwelling, environment, and behavior. The sociodemographic factor associated with the incidenceof DHF in tropical countries is age. In terms of climatology, temperature and rainfall are importantfactors in the vector breeding process. Rural areas (rural areas) are the place of dwelling with the mostcases of DHF found. The environmental aspect that has been widely studied is mosquito breeding. Themost signifi cant risk behavior factor in transmission was the behavior of hanging clothes. Of the 17articles, it was found that 77.8% of the articles examined environmental variables.

Hybrid Models for Weather Parameter Forecasting

The objective of the paper is to compare hybrid conjunction models with conventional models for the reduction of errors in weather forecasting. Besides the simple models like RBF model, SMO model, and LibSVM model, different hybrid conjunction models have been used for forecasting under different schemes. The forecasts from these models are further compared on the basis of errors calculated and time taken by the hybrid models and simple models in order to forecast weather parameters. In this paper, conjunction models over the convectional models are designed for forecasting the weather parameters for the reduction of error. India is a tropical country with variations in weather conditions. The objective is to build a conjunction model with less error to forecast weather parameters. A hybrid conjunction model is developed and analysed for different weather parameters for different metropolitan cities of India. Performance measurement is analysed for weather parameters. It is observed that, on the basis of error comparison and time taken by the models, the hybrid wavelet-neuro-RBF model gives better results as compared to the other models due to lower values of determined errors, better performance, and lesser time taken. The study becomes significant as weather forecasting with accuracy is a complex task along with the reduction of prediction error by the application of different models and schemes. It is concluded that the proposed hybrid model is helpful for forecasting and making policies in advance for the betterment of the human being, farmers, tourists, and so on as in all these activities, weather forecast plays an important role.

Assessing cooling energy of insulated building built in tropical country

Global warming is a huge issue and has become a global concern lately. The global warming issue is gaining more attention on reducing fossil energy since fossil energy has significantly exacerbated global warming. Since housing sectors are consuming significant fossil fuel energy, reducing housing energy consumption is necessary. One option discussed in this paper is to reduce the load on the air conditioner (AC) by applying insulation to the building. Reducing the AC energy will reduce the total energy consumption in the buildings. Building practice in a mild climate has shown that good insulation can reduce heating or cooling energy in the building. But using insulation in housing is not a common practice in Indonesia’s construction sectors. Simulating the use of insulation in housing will show how much energy reduction will be obtained, especially for air conditioning energy. The analysis in this study found that thermal comfort is related to air temperature and relative humidity in the room. This article will study the reliability of using insulation in buildings to reduce energy consumption and provide thermal comfort for the occupant.

Current status of taro (Colocasia esculenta) utilization as local food diversification toward climate resilience in Indonesia

Indonesia is a tropical country that experiences the impact of climate change. The utilization of taro as an amphibian crop might sustain the food availability for the most vulnerable farmers against the negative impact of climate change. The study aims to evaluate the current status of taro utilization and production as local food concerning food diversification, sustainable agriculture, and climate change issues. Data were obtained from a focus group discussion with primary stakeholders of the taro value chain and literature review. Results show that taro is an important secondary food in some regions with three main uses as local consumption, local trading, and export. Prominent taro consumers existed in West Papua, Papua, Maluku, and Central Sulawesi Provinces with consumption rates 10.6, 5.3, 2.2, and 2.0 kg/capita/year, respectively. Taro was intensively cultivated in Banten, West Java, and South Sulawesi provinces, for fresh and processed products. The respondents agree with taro as a prospective adaptive crop to climate change of both drought and excess precipitation. There are some issues in the biodiversity conservation, crop improvement, link-match industry, and stakeholder capacity building for competitive, quality, quantity, and sustainable production, as future works in the taro value chain in Indonesia.

Forecasting approach for solar power based on weather parameters (Case study: East Kalimantan)

Solar Energy is the most popular among several clean energies. As a tropical country, Indonesia has big opportunity to develop solar power, particularly in East Kalimantan which spans around the equator. Solar energy generation, however, is influenced by weather parameters which give uncertain values of the amount of the captured energy. Therefore, this research is conducted to overcome the effect of weather towards solar energy. The aim of this research is to examine the model for sun power forecasting based on the data. The Artificial Neural Network (ANN) and Multiple Linear Regression have taken as the approach models to determine energy forecasting. This study used five input variables; temperature, precipitation level, humidity, wind speed, and surface pressure, while the solar radiation was taken as the output variable. Moreover, the daily solar power and weather data from East Kalimantan has been taken along the period of 27th July 2018 – 28th July 2021. The result of this study showed that the RMSE of ANN was slightly similar with the multiple linear regression methods which were calculated by 160.26 and 160.46 respectively. However, the ANN is preferable to use in the solar energy forecasting since the tendency of nonlinearity of the climate data.

Bioprospection of Enggano Macroscopic Fungi as Antibacterial and Antioxidant Agents

Macrofungi in Indonesia have not been widely studied for their pharmacological activity, especially as a source of antibacterial and antioxidant properties, even though Indonesia as a tropical country has quite a high diversity of macrofungi. This study aims to reveal the potential of macrofungi from the Enggano forest as a source of antibacterial and antioxidant compounds. Four types of macrofungi were collected and their metabolites were extracted using four types of organic solvents. Antibacterial and antioxidant activity assay of the extract was carried out using the TLC Bioautography method. From the sixteen macrofungal extracts, there is one extract that has the strongest antibacterial activity compared to the others, namely n-hexane Coriolopsis polyzona. It showed moderate antibacterial activity against Staphylococcus aureus and Escherichia coli with MIC values of 256–128 μg/mL, respectively. Meanwhile, the antioxidant activity of the macrofungal extracts showed weak activity with IC50 values of 3080–7370 μg/mL (AAI values of 0.033–0.079).