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Waste has become a serious environmental problem in Indonesia, which continues to increase along with population growth. The issue of waste management poses serious challenges for the environment, especially in the process of separating organic and inorganic waste. In the field of computer vision, recognising the type and shape of waste through camera images remains a challenge due to variations in shape, colour, and complex lighting conditions. Therefore, this problem utilises Deep Learning technology, which is expected to be widely applied in Indonesia, especially in large cities with high waste volumes. This study aims to distinguish between organic and inorganic waste using the Convolutional Neural Network (CNN) method based on digital images. The developed CNN model was trained to recognise the visual patterns of each type of waste and tested to measure its accuracy. The test results show that the CNN-based classification system is capable of achieving an accuracy rate of 95%, thus proving the effectiveness of this method in supporting artificial intelligence-based automatic waste sorting systems.

This research aims to design and test a genset fuel conversion system from gasoline to HHO gas (brown gas) as a more environmentally friendly alternative. Conventional fossil-fueled generators face challenges in theform of limited resources and the impact of environmental pollution. In this study, HHO gas is produced through a water electrolysis process using an HHO generator that separates water molecules into hydrogen and oxygen using electric current. The test results show that increasing the voltage from 2.58 V to 5.12 V significantly increases the volume of gas produced. At a voltage of 2.58 V, the gas volume reached 110 ml, and increased to 750 ml at a voltage of 4.72 V. The generator set was successfully operated for 1 minute 15 seconds with HHO gas using a separate battery power source. These results demonstrate the potential of HHO gas as an efficient alternative fuel for generator sets. This study recommends further testing with voltage and current variations to find the optimal configuration, as well as the use of a larger power source to increase the efficiency of HHO gas electrolysis.

n today's digital era, customer reviews play a crucial role in purchasing decisions, but the large volume of reviews makes manual analysis difficult. Thus, a fast and accurate sentiment analysis method using Natural Language Processing (NLP) is needed. This research aims to analyze product reviews for the ZALIKA STORE 88 on Shopee using NLP. It involves preprocessing reviews, applying NLP techniques like tokenization, stemming, and lexical analysis, and automatically classifying sentiments. The analysis of ZALIKA STORE 88's reviews reveals mostly positive sentiments, with some negative and neutral reviews. The sentiment analysis achieved an 87% accuracy rate. This research is intended to help ZALIKA STORE 88 make informed decisions based on customer reviews.

The behavior of changing the use of technology for business actors is very rapid. Information of system is form of data that has been processed through a certain model into information that can be used by the recipient in making decisions. Some MSME actors with a Data List of product images and detailed information on their products to be marketed to customers using laminated paper. Marketing information using the Website implements CMS with E-Catalog as an alternative solution. Reader and Viewers can view the Catalog privately or together. The treatment of the Plugin model with the CMS that has been embedded on the website is reliable because it is online. Several list images are displayed on WhatsApp Status and social media to introduce products to the public with the aim of increasing sales volume and selling in the market. This is an obstacle if one day people need pictures but do not have complete detailed information. High purchasing power is expected to be created from the spread of E-Catalog regarding products from MSMEs that have been installed on the E-Catalog website. Websites with online CMS can be opened on any device by requiring an internet connection, making it easier for marketing and complete information for consumers, customers and MSME business players.

Peningkatan pertumbuhan penduduk di Semarang berbanding lurus dengan peningkatan kebutuhan sampah dan listrik. Persoalannya, sampah hanya berpindah dari tempat pembuangan sampah ke tempat pembuangan akhir. Hal ini menyebabkan munculnya dampak buruk terhadap lingkungan kota yang kotor. Di sisi lain, permintaan kebutuhan listrik yang tinggi setiap tahunnya meningkat. Untuk mengatasi masalah ini adalah pemborosan telah dimanfaatkan bahan pembangkit listrik. Dua parameter telah diusulkan untuk memprediksi potensi pembangkit listrik tenaga sampah di kota Semarang seperti populasi dan sampah. Algoritma backpropagation dari JST telah digunakan untuk memprediksi pembangkit listrik tenaga sampah untuk tahun 2020 hingga 2022. Variabel yang digunakan dalam peramalan meliputi ukuran populasi dan volume sampah. Hasil penelitian menunjukkan bahwa produksi listrik WPP adalah 8,8 MWH untuk peramalan 3 tahun. sedangkan pertumbuhan orang ditunjukkan sebagai 1,7 juta selama 3 tahun. Potensi pembangkit listrik sampah PLN telah diberikan 0,29% dari total kebutuhan listrik di Jawa Tengah.

The waste processing and renewable energy are being the issues in the industrial 4.0 era. Kitchen and organic trash in the rural areas will become a disaster if there is no solutions. On the other hand, kitchen and organic waste have a positive side, that they can be converted into biogas which can be converted into electricity. On the Minister of Energy and Mineral Resources Regulation Number 27 of 2014, supports the development of biogas and will buy electricity from the biogas conversion. The potential for biogas that obtained by the organic trash per 1000 people is 7619.8 liters of biogas, it meas that the energy contained is still abundant and the production can still be increased if processed with a modern digester system. This research produces a tool in the form of a portable digester that named GenBIoT (IoT-based Biogas Generator) which can be used by the public to produce biogas that  used by home industries or general factories. This research used the research method that similar to System Development Life Cycle (SDLC), this tool is built with several stages starting from planning analysis, designing, functional testing, data analysis and reporting of the results or implementing this tool that can be used as an alternative, as a cheap and easy source energy. This tool is based on the Internet of Things so that this tool can be monitored regarding gas pressure in the reactor, biogas volume and it will detect if there is a biogas leak so it will displayed on the system. To produce the maximum biogas composition, 50% of cow dung is required, 40% of kitchen trash and 10% of water with a ratio of 5: 4: 1 so it will produce 40 kg of biogas with a volume of methane gas (VGM) 0.11 m3 of biogas for cow dung. and 0.04 m3. The third experiment becomes the basis of future biogas production with energy produced from biogas per day of 716.39 Wh

The Advancement of Science and Technology (Science and Technology) has been widely felt by the general public. Many people enjoy facilities or tools that can simplify and speed up their work. The advancement of science and technology covers various fields, including electronics, automotive machinery, medicine and others. Progress in the electronics sector is growing very rapidly. For example, now many electronic devices are used by the public, such as radio, television, fans and others. The advancement in the electronics field is increasingly sophisticated and modern. For example television, in ancient times we had to press the buttons that were attached to the television, to move the television waves, adjust the volume, and use other adjustment buttons. But now no longer, we can control or regulate the functions that exist on the television from where we sit using the remote control. In modern times like today remote control devices need to be developed so that we can control things from where we sit or from whatever we want, so that human work becomes easier and faster.

Guava is a fruit plant with various benefits for humans. Both the leaves and the fruit can be used to treat various diseases. As an example of the fruit to treat Dengue Hemorrhagic Fever, Tyfus, and so forth. The leaves can be used as traditional medicine to treat cough and diarrhea. In the highlands it is indeed cold and there is little possibility of plantation fires. However, fires can occur as a result of human activity both intentional and unintentional. The location of the plantation land that is relatively far from the residential population makes fires sometimes known too late. Therefore, it is necessary to create a tool to monitor the temperature and concentration of guava plantation smoke from a distance every day so that if the temperature or the density of smoke reaches a certain number that indicates the occurrence of fire then the tool will immediately send a notification via SMS to the plantation owner. In addition, the tool will immediately pour water from the reservoir or water reservoir into the guava plantation. In the water reservoir there is a tool to detect the volume of water. The device to be created uses the LM35 temperature sensor, MQ-2 smoke sensor, HC-SR04 Ultrasonic sensor, Relay, Arduino Uno R3 microcontroller and GPRS Shield along with the GSMSIM Card.