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Tourism is one of the sectors that plays an important role in boosting economic growth through travel activities and destination exploration. Tourists' preferences for nature-based tourism options, such as mountain hiking or beach tourism, are influenced by various factors, ranging from personal experiences and recreational interests to social characteristics. Therefore, a technology-based approach is needed to predict destination choice tendencies more accurately. As artificial intelligence technology develops, deep learning methods have been widely used in classification processes due to their ability to process large amounts of data and recognize complex patterns. In this study, a Multilayer Perceptron (MLP) model is used to classify tourists' preferences between mountain or beach destinations based on a survey dataset. The research stages include data processing, data splitting using a train-test split, model training, and performance evaluation using accuracy, precision, recall, and F1-score. The test results show that the MLP model is capable of achieving an accuracy rate of 99%, confirming that deep learning methods are effective in automatically mapping tourism preference trends. This research is expected to serve as a basis for the development of more personalized travel destination recommendation systems, as well as to support tourism management in formulating targeted promotional strategies.

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.

Information technology is currently developing and growing rapidly in all fields, supported by the advancement of computer technology. The application of information systems can also be applied to the financial services sector, including cooperatives like K.S.P Al Hudori. The loan service system remains ineffective due to the manual data management process, which involves writing data into ledgers, which are easily lost or damaged due to the paper-based nature of the data. This research aims to implement a loan information system at K.S.P Al Hudori that can assist with loan data verification, search, and report generation. This information system was designed using Embarcadero XE2 and Microsoft Access 2007 as its database. This system has been implemented at KSP Al Hudori. It is hoped that this information system will simplify the loan management process at K.S.P Al Hudori

Information technology is currently developing and growing rapidly in all fields, supported by the advancement of computer technology. The application of information systems can also be applied to the financial services sector, including cooperatives like K.S.P Al Hudori. The loan service system remains ineffective due to the manual data management process, which involves writing data into ledgers, which are easily lost or damaged due to the paper-based nature of the data. This research aims to implement a loan information system at K.S.P Al Hudori that can assist with loan data verification, search, and report generation. This information system was designed using Embarcadero XE2 and Microsoft Access 2007 as its database. This system has been implemented at KSP Al Hudori. It is hoped that this information system will simplify the loan management process at K.S.P Al Hudori.

The advancement of information technology has had a significant impact across various sectors, including healthcare. The digitalization of healthcare services has become a solution to improve efficiency, effectiveness, and accessibility for the public. Puskesmas Selindung still uses a manual patient registration system, which leads to several issues such as long queues, extended waiting times, and the risk of lost or damaged patient records. Based on visit data, the number of patients coming to Puskesmas Selindung has increased each year. Therefore, a digital queue system is needed to optimize the patient registration process. This research aims to analyze and design an Android-based patient registration queue application to improve service efficiency at Puskesmas Selindung. The research methods include system requirements analysis, user interface design, and the development of core features to support the online patient registration process. The implementation of this application is expected to reduce long queues, speed up administrative processes, and make it easier for patients to access healthcare services more effectively and accurately. With this Android-based system, the quality of healthcare services at Puskesmas Selindung is expected to improve significantly.

The main problem with the water heating system on offshore platforms is the absence of water level monitoring and automatic overflow detection. This has the potential to cause hot water spills that endanger workplace safety and operational efficiency. This research designs and implements a water level monitoring system based on the Arduino Uno microcontroller with HC-SR04 ultrasonic sensors. The system is equipped with LED indicators, a buzzer alarm, and a 16x2 LCD to display water level status in real-time. Water levels are classified into three zones (low, medium, high), and overflow is detected if the water is within 3 cm of the sensor. Testing was conducted on a 5-liter simulation tank representing actual 500-liter tank conditions. Test results showed a reading accuracy of 96% and a quick system response to overflow conditions (<1 second). This system is economical, easy to develop, and highly applicable for offshore environments. In addition, this system can be integrated with IoT technology for remote monitoring.

Penelitian ini bertujuan untuk mengembangkan sistem pendukung keputusan yang dapat membantu tim Marketing Officer (MO) PT. Alvarel Technology Innovation dalam menentukan status pelanggan secara objektif dan terstruktur. Sistem ini dirancang menggunakan kombinasi metode Analytical Hierarchy Process (AHP) dan Weighted Sum Model (WSM). Metode AHP digunakan untuk menentukan bobot kriteria yang meliputi Potensial Pasar, Urgensi, Finansial, serta Hubungan dan Reputasi, dengan memastikan konsistensi matriks perbandingan berpasangan. Hasil pembobotan kemudian digunakan dalam metode WSM untuk melakukan perhitungan skor total pelanggan dan menyusun pemeringkatan status berdasarkan nilai tertinggi hingga terendah. Data penelitian diperoleh dari catatan internal perusahaan dan wawancara dengan Marketing Officer, dengan jumlah sampel 30 pelanggan. Hasil pengujian menunjukkan bahwa sistem dapat menghasilkan peringkat status pelanggan dalam lima kategori, yaitu potensial, prospek, pending, pasif, dan skip. Temuan utama memperlihatkan bahwa kategori prospek memperoleh skor tertinggi dan menjadi prioritas tindak lanjut. Dengan demikian, sistem pendukung keputusan berbasis AHP–WSM ini mampu mengurangi subjektivitas, meningkatkan efisiensi, serta memberikan rekomendasi yang lebih akurat dan terukur untuk mendukung pengambilan keputusan strategis perusahaan dalam pengelolaan pelanggan.

Drug abuse (Narcotics, Psychotropics, and other Addictive Substances) is a serious problem that can threaten the younger generation, especially in the Panggung Kidul Village area. The lack of public understanding, especially teenagers, regarding the dangers and negative impacts of drug abuse is one of the factors that influence the high risk of substance abuse. Therefore, innovative and interactive educational media are needed to increase public awareness and understanding regarding the prevention of drug abuse. This study offers a solution by designing and developing educational media based on Augmented Reality (AR) technology as a visual and interactive tool that conveys information in an interesting and easy-to-understand manner. The use of smartphones as the main device in AR applications makes this media more easily accessible to various groups of people. The test results using the System Usability Scale (SUS) method showed a user satisfaction level of 96% which is included in the Acceptable category. Thus, this AR-based educational media is expected to be an effective means of increasing public understanding of the dangers of drug abuse and encouraging early preventive efforts.

Information technology is a technology used to manage data, including processing, acquiring, organizing, storing, and manipulating data in various ways to produce high-quality information—namely, information that is relevant, accurate, and timely. This information is used for personal, business, and governmental purposes, serving as strategic information in decision-making. To anticipate changes in weather conditions, particularly rainfall, a valid and accurate report is needed that can be useful for the public. So far, the correlation or relationship between the factors influencing weather conditions—especially rainfall—has not been precisely determined, making it mathematically difficult to create a model that can describe the correlation among all these factors. This is where Artificial Neural Networks (ANN) come into play: to create such models and map out the existing problems purely based on the input data provided. One of the capabilities of neural networks is to make predictions based on previously learned data using the backpropagation method.

Mental health is a crucial aspect of modern life, with stress and anxiety being among the most common and impactful psychological disorders. This research proposes a stress and anxiety monitoring system based on the Internet of Things (IoT), integrating biometric sensors and Deep Neural Networks (DNN) for early detection and in-depth analysis. The system is designed using MAX30102 (heart rate and SpO₂), GSR (Galvanic Skin Response), and DS18B20 (body temperature) sensors, managed by an ESP32 microcontroller and communicating through the MQTT protocol. Physiological data is collected in real-time, formatted in JSON, and transmitted to both Android and web-based applications for visualization. The DNN model is developed using the TensorFlow framework with a layered architecture and ReLU activation functions to classify four mental states: relaxed, calm, anxious, and highly stressed. The training dataset comprises both primary and secondary data, including the WESAD dataset. Model performance is evaluated through k-fold cross-validation, showing high accuracy and strong generalization capabilities. The results indicate that the integration of sensor technology and deep learning significantly improves the effectiveness of stress and anxiety detection compared to traditional methods. This system demonstrates great potential for the development of AI-based wearable devices for autonomous, real-time, and adaptive mental health monitoring.

The food security program involving chili cultivation in Pentur Village is hindered by inefficiencies in water use and suboptimal plant growth, primarily due to traditional irrigation methods that fail to consistently maintain ideal soil moisture and temperature. This issue is exacerbated by unpredictable environmental shifts, such as fluctuating weather patterns, and a lack of precise irrigation control stemming from technological limitations. To address this, a system for monitoring and regulating chili plant irrigation using IoT technology was developed. This system employs humidity and temperature sensors connected to an IoT platform like Blynk, enabling real-time observation of plant and environmental conditions. Data on soil moisture, air temperature, and humidity are stored in a database, and irrigation is automated based on soil moisture levels. The goal is to enhance water efficiency, minimize risks associated with over or under-watering due to environmental variations, and improve both yield and quality of the chili crop. This IoT-based system aims to simplify chili plant management for Pentur Village farmers and significantly boost agricultural output.

The insurance business in an insurance company offers insurance products owned by insurance companies. There are many transactions such as the purchase of insurance products and the application of disbursement of insurance benefits to customers, so that disputes occur in the reports generated every month and this does not become effective and time-efficient as needed. This study aims to evaluate the effectiveness of a website-based real-time insurance transaction reporting monitoring system. This research method involves the development of a web-based system designed to monitor and report insurance transactions directly, as well as the evaluation of system performance using quantitative and qualitative approaches. The research stages include needs analysis, system design and development, implementation, and system testing and evaluation in insurance companies. The results of the study show that a website-based system can facilitate evaluation Monitoring the results of reports on ongoing transactions, so that reports every month can be formed digitally through the system that has been created.  

Due to the busy activities outside the home, some people do not have time or forget to water their plants, so when they return home they find that the plants have died from drought. Therefore, to overcome this problem by conducting research using Internet of Things technology. The aim of this research is to design an automatic watering tool to overcome manual watering and support learning. This prototype uses a NodeMCU ESP8266 as the main controller, a soil moisture sensor is used to read soil moisture.  Soil moisture sensors are used to detect soil moisture. If the soil humidity is below the minimum limit, the watering process will be active and the watering process will be active if the NodeMCU ESP8266 receives commands from the smartphone.

The advancement of information technology has had a profound impact on education, including at the Universitas Bina Sarana Informatika (UBSI), where My Best, an elearning application, was created. With this program, users may participate in a variety of academic tasks, including online attendance, discussions, assessments, assignments, and course materials. But pupils continue to face usability difficulties. The System Usability Scale (SUS) technique is used in this study to assess the usability of the My Best program. The approach included 35 current UBSI students who have been using the My Best software for more than seven semesters. According to the assessment, the average SUS score was 70, which is considered to be rather high but still needs work in terms of interface usability and user-friendliness. As a result, although the My Best app is thought to be helpful in fostering learning, improvements are needed to enhance the whole user experience.

CV. Apris Expressindo is a private company engaged in the construction and distributor of U-PVC frames. In its business process activities, CV. Apris Expressindo still does not utilize technology optimally, so that the transfer of information regarding offers, sales, purchases, product stock, suppliers, customers, and financial reports is still done manually. This causes inefficient business processes including: slow fulfillment of customer orders, product pricing errors between divisions, product marketing that is not optimal, financial reports that cannot be seen and controlled by company leaders. Therefore, it is necessary to implement Enterprise Resource Planning (ERP) which aims to overcome these problems. The methodology used in this study was carried out in several stages, namely, data collection: interviews, observation and literacy studies, business process analysis: activity diagrams and use case diagrams, implementation: installation, configuration and module customization, testing: blackbox and UAT (User Acception Test) . The results of this study indicate that the ERP software that has been selected and implemented, namely the Odoo application, can improve and simplify business process activities and can minimize any problems faced today. It is hoped that with this ERP system business operations can be more effective and efficient so that it is expected to provide more financial benefits for CV Apris Expressindo.

One of the museums found in Bali is Subak museum in Tabanan Regency. The establishment of this Museum aims to preserve the traditional institution called Subak as a noble national cultural heritage, and to introduce to the younger generation and foreign tourists about the unique traditional irrigation system in Bali. Lack of supporting facilities in delivering information, making tourists who visit Subak Museum have minimal information. The solution needed in Subak museum is an Android-based E-Tourism application that is supported by Qr-Code technology so as to provide an interesting presentation of data. In making this application using the development of the Waterfall method and designed using the Unified Modeling Language (UML) with the Java programming language for Android and PHP for web services, and MySQL as a database. So that produced an android-based system in Subak museum Tabanan Regency. Based on the results of the tests carried out it can be concluded that the black box testing system functions have been running according to the planning. Then the result of the testing of users using questionnaires generated Application Benefits scores 90.8%, Ease of 86.93%, Interface 82% and Content 90.2%. 

  Utilization of new renewable energy is a solution to meet the increasing electricity demand, one of which is solar power generation technology. Solar panels are a renewable power generator that is environmentally friendly. The relatively low and unstable output voltage of PV is affected by solar irradiation, which becomes a constraint. Therefore, by utilizing a boost converter, the solar panel system is able to work 25% more optimally compared to without using a boost converter. The performance of solar panels when using a boost converter is around 83.3% and without using it, the performance is only about 58.3%. The average output power when using the boost converter is 1,521 W, whereas without using the boost converter, the average output power is 1,172 W. This indicates that the output power is more stable when using the boost converter compared to not using it. This research focuses on a boost converter with PID control as a support, optimizer, and voltage stabilizer where the output power on the solar panel is expected to be more optimal and the output from the solar panel is more stable with more optimal results in various conditions. In this study, 12 solar panels of 125 WP with a capacity of 1.5 KW are used in series-parallel to obtain the required power. If the output from the solar panel is insufficient due to weather conditions, the voltage will be increased by the boost converter towards the inverter so that the voltage remains stable into the inverter with the boost converter. This boost converter uses PID control to keep the output voltage stable.  

Current technological advances have made the need for information technology very necessary. With the existence of web-based geographic information system technology, it can help PT. Telkom Indonesia Tbk Prabumulih City Branch to digitize every Indibiz customer and target area for Indibiz products. The aim of this research is to create a web-based Indibiz customer mapping information system and to improve technician performance in matters concerning Indibiz. The research method used is descriptive qualitative, the Waterfall method as a system development method and UML as a design tool. The application was built using a website with the php programming language, a mysql database, and printing data using pdf files.

Milk consumption and the need for beef cattle for food purposes or sacrificial purposes continue to increase from year to year. This increase is in line with the increasing level of the economy and awareness of the need for nutritious food. However, the increase in demand still faces many production constraints due to the difficulties faced by farmers, the decline in cattle production from year to year in Indonesia. This causes Indonesia to have to import beef for 35.95% of the total national beef consumption. With many factors that affect the decline in the production rate of dairy cows or beef cattle every year, one of them is air pollution and poor air quality in cages. Along with the development of technology, a monitoring and detection system for air cleanliness in cattle pens was created, using the MQ-7 sensor as the concentration of carbon monoxide, the MQ-135 sensor as the concentration of ammonia gas, the MQ-2 sensor as the smoke detection, and When the air pollution value of each sensor input is according to the air pollution standard index (ISPU), the outputs namely indicator lights, buzzers and blowers will be on, then there will be temporary air neutralization in the cage. This tool is made easier by internet of things technology, so that it can send notifications via telegram and can see the level of air pollution levels through the web.

E-Learning becomes a platform which supports technology-based learning on many aspects. The usage of E-Learning becomes the main choice especially in education world. SMK TI Bali Global Jimbaran, which is a middle level vocational school, utilizes this platform in its learning process. In its implementation process, there needs to be a precise and thorough supervision to ensure that the system runs according to business goals. This mapping is conducted to know the process used for measurements. This mapping is done by framework with COBIT 5 by applying PAM (Process Assessment Model), which is adjusted with the condition on research place. The activity measurement are derived from several domains on COBIT 5 with mapping process based on the business goals and institution goals. The domains used are EDM03, AP003, BAI07, DSS05 and MEA01. The results of governance measurement process on current capability level is on level 4 (predicable process) and the expected capability level is on level 5 (Optimizing Process) which has gap value of 2 level.