PEMETAAN MIKROZONASI DALAM MENDUKUNG PERENCANAAN DAN PENGEMBANGAN KELEMBAGAAN LINGKUNGAN HIDUP

Pengembangan kelembagaan lingkungan hidup menjadi prioritas dalam pengurangan tingkat resiko kerusakan lingkungan. Perlunya kajian dan kolaborasi antara kelembagaan akan mempengaruhi keberhasilan dalam pembangunan dan kesejehteraan masyarakat. Dalam hal ini, pengurangan resiko kerusakan lingkungan dapat dilakukan dengan melakukan pemetaan terhadap bencana alam. Penelitian ini berfokus pada pengurangan dampak resiko gempabumi terhadap lingkungan. Penelitian ini juga bertujuan untuk melakukan pendekatan terhadap kelembagaan lingkungan hidup yang memegang peranan dalam kebijakan pembangunan dan perencanaan, khususnya kajian mikrozonasi sebagai upaya pemetaan resiko kerusakan lingkungan di kota Medan, Sumatera Utara

PEMETAAN MIKROZONASI DALAM MENDUKUNG PERENCANAAN DAN PENGEMBANGAN KELEMBAGAAN LINGKUNGAN HIDUP

Pengembangan kelembagaan lingkungan hidup menjadi prioritas dalam pengurangan tingkat resiko kerusakan lingkungan. Perlunya kajian dan kolaborasi antara kelembagaan akan mempengaruhi keberhasilan dalam pembangunan dan kesejehteraan masyarakat. Dalam hal ini, pengurangan resiko kerusakan lingkungan dapat dilakukan dengan melakukan pemetaan terhadap bencana alam. Penelitian ini berfokus pada pengurangan dampak resiko gempabumi terhadap lingkungan. Penelitian ini juga bertujuan untuk melakukan pendekatan terhadap kelembagaan lingkungan hidup yang memegang peranan dalam kebijakan pembangunan dan perencanaan, khususnya kajian mikrozonasi sebagai upaya pemetaan resiko kerusakan lingkungan di kota Medan, Sumatera Utara

Prediction of Domestic Passengers at Kualanamu International Airport Using Long Short Term Memory Network

Domestic passenger forecasting provides key input into decisions of daily operation management and infrastructure planning of airports and air navigation services and for aircraft ordering and design. Planning for the future is one of the most important keys to success, forecasting is the way. The goal of this study to predict the number of domestic passengers at Kualanamu International Airport. The time-series data were employed from Badan Pusat Statistik (BPS). The result is then discussed in the context of the potential use of the proposed for a new perspective for the predicting of domestic passengers at Kualanamu International Airport, Indonesia. The machine learning approach using long short term memory (LSTM) presents a useful way of observing the domestic passenger predict the passenger time series

Characteristics of Extreme Rainfall Events in North Sumatra

Extreme rain is an event that has an impact on various sectors of life. Therefore, this study aims to determine the spatial and temporal characteristics of extreme rain events in North Sumatra Province in the time period between 1991-2020. In accordance with the WMO recommended rain index, the frequency and intensity of rain were calculated using 50 rain stations spread across North Sumatra where the data had passed the quality control test for empty data. Spatial patterns were analyzed by mapping the climatological mean of the indices then for trend patterns were tested using the Mann-Kendal non-parametric test. The results showed that extreme rainfall events with low frequency and intensity occurred on the east coast while high frequency and intensity occurred in mountainous areas. Based on the temporal trend test, it shows that in general an insignificant trend dominates in this area. Significant and consistently increasing trends are only found at several points, namely in the districts of Deli Serdang (5 station), Batu Bara (1 station), Humbang Hasundutan (1 station), Langkat (2 station), Labuhan Batu Utara (1 station), Medan (1 station), Pematang Siantar (1 station) and Serdang Bedagai (1 station). Meanwhile, a significant and consistently decreasing trend was found in Asahan Regency (1 station), Simalungun (2 station), North Tapanuli (1 station), and North Labuhan Batu (1 station)

Design and Manufacture of Formaline Detection in Food Ingredients Based on Arduino

The use of formalin in food is now widely circulated in big cities. Formaldehyde is always chosen by producers so that these products are more durable and also inexpensive to help entrepreneurs reduce production costs. The difficulty of the community in identifying the characteristics of the presence of formaldehyde makes the community restless and feels disadvantaged. Therefore, a tool is designed to detect formaldehyde in arduino-based foods. This arduino-based system can test food ingredients practically and effectively because it doesn't take long to see the results. HCHO sensors are used to detect samples in food ingredients. With the HCHO sensor, humans can know whether the food contains formalin or not. The work process of this tool through the gas released from the food material. The test results will be displayed on the LCD screen, where the output is positive or not which has been detected by the sensor

Classification of Labor Using Support Vector Machine in North Sumatera

Labor markets in Indonesia are key challenges and policy issues. Balai Besar Pengembangan Latihan Kerja (BBPLK) Medan is a services unit to develop and implementation of labor to increase skill and knowledge. The classification of labor in North Sumatera is very interesting to evaluate the performance of the labor in North Sumatera. In this case, we compute the labor data to classify and evaluate the model and performance of the dataset. The computation of the dataset using the support vector machine (SVM) as a model in machine learning or probabilistic approach by training and test data. The data was collected from Badan Pusat Statistik (BPS) Sumatera Utara for 2018 samples. Labor force dataset in North Sumatera had been computed and shown the result, indicates the support vector machine classifier is the good algorithm for this classification problem, offering good values in terms of accuracy, for describe the labor force in North Sumatera and can be recommended to BBPLK to add more development and implementation

Skyquakes phenomenon analysis using geophysical approach in Java Island

Explosions in the sky (Skyquake) like an earthquake are still mysterious. The main purpose of this research is to to provide an overview of the source of the explosion that occurred with a geophysical approach, based on both earthquakes, thunderstorms and earth magnets. In this case, we used the geophysical approach to evaluate and analysis the skyquakes based on the spectral density and magnetic field. The result indicates that the earthquake sequences that occurred simultaneously were not related to crash events at different times, 11 April 2020 and May 11, 2020, as well as the electrical activity of the air and the earth's magnet, the assumption of the 11 April 2020 explosion originating from lightning and magnetic activity is still very weak

A Review of Digital Image Classification Based on Fuzzy Logic

Fuzzy logic has long been an important issue for in the field of computer science, computer vision, image processing, machine learning and control theory and mathematics. In this review paper, we also see that the basics of fuzzy logic as well as fuzzy logic system (Fuzzy Inference System) use as decision making technique under a linguistic view of fuzzy sets. In this study, we focused to review the fuzzy logic to classification of digital image. The aim of this study was to review the fuzzy logic algorithm for classification of image

Design of Microcontroller Course Video Tutorial Application using User Centered Design Method Based on The Android

The Microcontroller course is one of the compulsory courses contained in the Informatics Engineering study program at the Methodist University of Indonesia. The purpose of holding the Microcontroller course is so that students had been an understanding of the basics, architecture, work principles, minimum systems, hardware and software components in the microcontroller system and the application of the microcontroller. Based on experience, there are several difficulties in studying Microcontroller courses such as understanding the circuit images contained in the Microcontroller lesson manual and also applying the series on the Breadboard board. The purpose of this study is to build applications that can help students understand microcontroller courses using the User Centered Design (UCD) method. The system built will later provide video tutorials that can help students understand microcontroller courses

Study of the Utilization of WRF Model Output Data to Produce Daily Flood Forecast Maps in the North Sumatra Region

Flood is a natural disaster that often occurs in Indonesia. Currently, flood events are relatively difficult to predict because floods generally occur suddenly in uncertain periods. Extreme rainfall is a major factor for the occurrence of floods. Considering that floods can be caused by heavy rainfall events within a few hours, it is necessary to produce daily flood forecasts for flood disaster mitigation. This study aims to test the accuracy of utilizing rainfall forecast data from the Weather Research and Forecasting (WRF) model to create daily flood forecast maps. The data used in this study include Global Forecast System (GFS) data, BMKG rainfall measurement data which spread across several points in North Sumatra Province, and flood incident reports from BNPB. Data processing is carried out by Geospatial Information System (GIS) using Quantum-GIS, which includes weighting and scoring the parameters of soil type, slope, land elevation, river density, and land cover to produce Flood Prone Maps, then integrated with rainfall data to produce Daily Flood Forecast Maps. The case studies of flood events in this study are August 28 and November 28, 2022. The results showed that the spatial forecast of flood potential (WRF) has a pattern in accordance with the flood event area. Therefore, the WRF model output rainfall prediction data can be used to create a daily flood forecast map in the North Sumatra region