WIND ENERGY POTENTIAL OF GUNUNG KIDUL COASTAL AS A FUNCTION OF PROBABILITY DISTRIBUTION

Gunung Kidul coastal is an area that has varying heights up to 250 meters above sea level, and dealing directly with the Indian Ocean. Based on the location of the height of the sea surface, with Logarithmic formulation of wind speed, Gunung Kidul coastal has a varying energy class. The method used is an analytical model of constant density atmospheric, assuming that the density of the air from sea level to the top of the atmosphere has a fixed value. Furthermore, the value of wind speed is used as a probability distribution function based on the data period of 24.5 years. The results of the average value of wind energy are grouped according to energy class. On the use of the Poisson probability distribution, the class of potential good of energy is reached at a height of over 450 meters above sea level. While the use of the Normal distribution and Weibull reach potential class good at 100 meters above sea level

IMPLEMENTATION OF IMAGE CLASSIFICATION USING CONVOLUTIONAL NEURAL NETWORK (CNN) ALGORITHM ON VEHICLES IMAGES

The use of surveillance cameras for most agencies only relies on video recordings and storing them for a certain time. The use of this surveillance camera can be applied to determine the type of vehicle even if the camera is not in the right position. Regarding the background of the problem, this research will use the Convolutional Neural Network (CNN) algorithm, which is part of Deep Learning with the help of Keras Library and TensorFlow, to carry out the learning process on videos captured by surveillance cameras so that it can detect images from 3 types of vehicles. The dataset used is 100 images of motorcycles, 100 images of cars, and 100 images of buses. The method used is the Image Classification Method, and the model used is the best model selected from several experiments. Researchers used training and test data distribution, namely 80% and 20%. The best results were obtained with an accuracy rate of 96.49% using epoch 100, learning rate 0.001, and batch size 32. Meanwhile, vehicle images produced image accuracy for motorcycle images when using test data from outside the dataset is 78.92%, car image is 81.71%, and bus image is 82.26%

FORECASTING ANALYSIS ON ELECTRICITY DEMAND IN THE SPECIAL REGION OF YOGYAKARTA UNDER THE IMPACT OF THE COVID-19 PANDEMIC

The COVID-19 pandemic as a global pandemic on 2020 has encouraged the Indonesian Government to establish pandemic response policies in many provinces. The policies that had been restricting mobility during the pandemic showed significant impacts in many aspects in the Special Region of Yogyakarta. A shifting pattern in electricity consumption can be seen as the growth of economic sectors in the GDP encountered contraction after the decline of community mobility. Electricity demand forecasting is required to analyze the impact of the COVID-19 pandemic by applying three scenarios, specifically an unlikely pandemic scenario or Business As Usual (BAU), moderate scenario (MOD), and optimistic scenario (OPT). Also, the household, industrial, business, social, and public sectors are analyzed in order to see the shifting pattern in electricity consumption through the scenarios that have been given. Energy modeling is conducted with Low Emission Analysis Platform (LEAP) software to analyze electricity demand forecasting from 2019 to 2030 based on the three scenarios. The results show that the electricity demand in 2030, according to BAU, MOD, and OPT scenarios, in the amount of 5,301.58 GWh, 4,489.11 GWh, and 4,648.12 GWh, respectively. According to the MOD and OPT scenarios, the electricity demands of the household and industrial sectors will increase relative to the BAU scenario. Meanwhile, according to both scenarios, the electricity demands of the business and social sectors will decrease. In the public sector, the MOD scenario shows the decline of electricity demand relative to the BAU scenario, while OPT scenario shows the opposite

BIOREMEDIATION OF TOFU INDUSTRY LIQUID WASTE USING EFFECTIVE MICROORGANISM-4 (EM4) SOLUTION (CASE STUDY OF TOFU SENTOSA INDUSTRY, YOGYAKARTA)

Liquid waste produced from the tofu industry contains high contaminants such as BOD, COD, TDS, pH, and TSS, which can pollute the environment. Therefore, pollutants should be decreased before being discharged into the environment. Tofu waste treatment is constrained by adequate technology and high costs. Biological treatment is one of the best treatments, a waste treatment process by utilizing microorganisms. This research used the intermittent anaerobic-aerobic process and was conducted on a laboratory scale using a tank made of glass 25 cm long, 20 cm wide, 15 cm high, and a tank of 30 cm long and 15 cm wide 15 cm high. The treatment process in this research used samples adding EM4 solution with a concentration of 1/20 and samples without EM4. The stages of the research were carried out consisting of preliminary research, core research, and further research. Preliminary research used 1/20 (5%) concentration of EM4 and was fermented for four days at room temperature. As a result, the pH value decreased from 6 to 4, and the presence of a white layer above the surface. The average pollutant reduction efficiency value in the sample with Effective Microorganism-4 (EM4) and without the Effective Microorganism-4 (EM4) was tested at different duration times for each parameter. The efficiency reduction value of the sample with EM4 of BOD was 87.14%, COD 74.68%, TSS 15.88%, and TDS -17.91%, while in the sample without EM4 of BOD value was 76.54%, COD 67.78%, TSS 22.77%, TDS -16.78% with a time process of 41st day

FACTOR ANALYSIS OF HEALTHY FOOD PHOTOGRAPH

Lockdown is one way to reduce the transmission rate of COVID-19. Nevertheless, on the other hand, lockdowns also increase human psychological problems to cause the emergence of emotional eating. In addition, social media exposure that presents food photos can trigger the desire to eat. However, this only applies to high-fat and high-calorie foods, while healthy foods do not have the same stimuli. Therefore, more research is needed on the properties of healthy food photos desired by consumers in order to be able to create or design healthy food photos with an effect that resembles photos of high-fat and high-calorie foods. This study employed the Kansei Engineering approach in designing healthy food photos. Through Kansei Engineering, we can determine the nature of healthy food photos consumers want. The type of Kansei engineering used in this study was Kansei Engineering Type I and was limited to the Semantic Space stage. The process of factor reduction from the results of the semantic differential was carried out by using factor analysis to obtain the most critical factors related to healthy food photos. The semantic space spanning resulted in 23 pairs of Kansei words that related and represented healthy food photos. Based on the factor analysis results, these Kansei words were then into 6-factor groups. Each of the factor groups was represented by the Kansei word pair with the highest loadings value. The selected pair of Kansei words showed that healthy food photos could be represented by Kansei words attractive, contrast, proper lighting, neat, high-quality image, and straightforward.

POROUS CARBON FROM PINEAPPLE PEEL AS ELECTRODE MATERIAL OF SUPERCAPACITOR

Porous carbon from biomass has a great potential to be developed. Biomass as a resource is renewable, abundantly available, and cheap. One application of porous carbon is as an electrode material of supercapacitor due to its advantageous pore properties such as high specific surface area and pore volume. This research prepared porous carbon material from pineapple peel waste and tested it as a supercapacitor electrode. The research steps were material preparation, conversion of pineapple peel to porous carbon, and characterization, including material characterization and electrochemical characterizations. Pineapple peel (under 80 mesh size) was pre-carbonized by hydrothermal method at 1900C for 2 hours under a subcritical condition. After that, biochar was pyrolyzed at 9000C and activated using CO2/N2 (KB-900-50). As a reference, biochar was also pyrolyzed under a nitrogen atmosphere at 9000C without activation (KB-900). Produced porous carbon was characterized (i) pore structures, e.g., specific surface area, average pore diameter, and total pore volume using N2-sorption analysis, and (ii) electrochemical performance, e.g., cyclic voltammetry and galvanostatic method using 1 M H2SO4 electrolyte solution. The result showed that the activation process effectively increased the porosity of porous carbon. Material (KB-900-50) possesses a high surface area of 648 m2/g and a high capacitance value of 78 F/g

POTENTIAL STUDY OF PHOTOVOLTAIC POWER STATIONS TO MEET ENERGY NEEDS OF FUEL CELL UNITS IN BARU PANDANSIMO BARU BEACH OF BANTUL, YOGYAKARTA

Energy needs are increasing rapidly along with population growth, increasing population activity, and massive development in technology. However, a current energy source is mainly from fossil energy. This condition is inversely proportional to fossil energy stock, decreasing year by year as a natural condition of non-renewable energy. On the other hand, fossil energy damages the environment by its pollution, such as deforestation and air and atmospheric pollution in the form of greenhouse gas emissions. For this reason, the world needs another source of energy that could replace fossil energy as a source and is also environmentally friendly. New and renewable energy could be the solution.Indonesia has plenty amount of new and renewable energy potential. However, renewable energy is weather-dependent, thus requiring storage technology to store the energy. The current common storage technology is battery technology. This technology has some weaknesses: limited capacity, high cost, less flexibility, expensive, and short lifetime. Another storage technology with high flexibility, easy transport, high amount capacity, long lifetime, and wide usage is needed. Hydrogen storage appears to meet all these requirements.This study aimed to calculate the optimum potential of photovoltaic power stations at Baru Pandansimo Beach of Bantul, Yogyakarta, as an energy source to produce hydrogen as a storage energy system. The simulations are done using HOMER software were carried out in three photovoltaic power station scenarios: fixed-tilt, single-axis tracker, and dual-axis tracker, and showed that the fixed-tilt photovoltaic power station scenario is the most optimal design and architecture. With total capacity reaching 7.8 MWp potential to be built at Baru Pandansimo, it could generate 11,657,704 KWh/year electrical energy with an NPC value of USD 8.29 M, and a COE of 0.0420 USD/KWh. This electrical energy could produce 213,288.06 kilograms of H2 at a 2.3 USD/kg production cost.

OPTIMIZATION AND TECHNO ECONOMIC STUDY OF PLASTIC WASTE BENEFICIATION WITH PRODUCTION SIMULATION APPROACH CASE STUDY AT CV. PANDU KENCANA JOMBANG, EAST JAVA

The problem of plastic waste is getting more and more worrying day by day. Meanwhile, the industrial demand for plastics is also increasing. So we need a recycling business that can bridge this. Plastic waste in the environment can be decomposed, and the industry fulfills plastic needs at low prices. This study aims to analyze and optimize the business of recycling plastic waste into plastic ore to reduce the amount of plastic waste in the environment and obtain material benefits. The research method used is a case study in a plastic waste processing company with the collection of data needed to determine the formulation of the problem so that a mathematical model of linear equations can be formed, which then, through production simulations, will be obtained optimization. The results are then analyzed with a techno-economic study to determine the feasibility of the business.After optimization of production from simulations based on a mathematical model of linear equations, if the company wants to get maximum profit, then the company must produce PP Black A of 1022.73 kg, PP Black B of 852.27 kg, PP Gray of 625 kg. Meanwhile, PP Gray Jumbo should not be produced. Based on the techno-economic study, the feasibility analysis before optimization was obtained as ROIa=23.40%, ROIb=23.24%, POTa=2.99 years, POTb=3 years, BEP=36.07%, SDP=23.98% LANG=4.1, DCFRR=18.8 %. Then the feasibility analysis after optimization is ROIa=29.88%, ROIb=29.73%, POTa=2.5 years, POTb=2.51 years, BEP=31.03%, SDP=20.63%, LANG=4.1, DCFRR=24.85%

PRODUCT CLUSTERING ANALYSIS ON THE MARKETPLACE USING K-MEANS APPROACH (CASE STUDY: SHOPEE)

The business world has experienced a paradigm shift towards a more modern concept. Many business processes are carried out through the internet or commonly known as e-commerce, by utilizing a platform known as Marketplace. One of the marketplaces that are quite well-known and in great demand in Indonesia is Shopee. The high online shopping activity in the current marketplace indirectly encourages business actors to understand the online market. However, one of the obstacles that are quite often faced by sellers, especially new sellers who are starting to enter the digital realm, is the emergence of confusion in the selection of products to be sold due to a lack of information regarding the demand for what products are in demand in the market.The process of searching for information related to the demand for products of interest is carried out through clustering analysis to find out the groups of products that are of interest to those that are less attractive to the public. The data used is product data from 6 categories in the Shopee market which was taken using web scraping techniques. The clustering processes used the K-means approach by determining the number of K and the optimal center point through the calculation of Sum Square Error (SSE) by looking at the elbow graph. The final results show the optimal number of K clusters that are different in each category, namely in category women’s clothing, men’s clothing, and electronics are at K=4 then for products in the category of Muslim fashion, care & beauty and household appliances are at K=3. Based on the validation results using the Davies Bouldin Index, values were obtained in6 categories, namely 0.391, 0.438, 0.414, 0.357, 0.387, and 0.377, which means that the cluster structure and the level of information formed in each category using the K-Means method is quite good

THE EFFECT OF RESIDENTIAL ROOM CONFIGURATION ON NATURAL VENTILATION OF RUSUN UNITS TO ACHIEVE LOW ENERGY BUILDING

Rusun is a simple flat categorized as Affordable Housing (AH), which means it requires economic energy efficiency and optimal Natural Ventilation (NV) to manifest and provide comfort for users. This research will review the effect of spatial configuration on NV conditions of Rusun unit in terms of the condition of wind flow (WF) and wind speed (WS) value in each residential room by simulation method.The condition of the unit is on the 10th floor and height of 31.5m with an outdoor WS of 1.62 m/s in three different space configurations. It was found from the simulation that residential space that has direct access from openings both inlet and exit (outlet) has a more optimal WF and WS. From the WF condition and WS value following the needs of residential user activities, it is expected to optimize NV in Rusun units and in line with that, can realize energy-efficient Rusun buildings in terms of occupancy.