Autism is a developmental disorder that affects the normal functioning of the brain, thereby affecting a child's communication and social interaction abilities. This disorder poses a problem for children in communicating and forming relationships with their environment. As the number of individuals with autism increases, public awareness of autism remains very low. Additionally, most psychologists or psychiatrists are located in major cities, limiting access for rural communities. This leads to many parents struggling to obtain information about autism symptoms. The research method used is the naïve Bayes method, it can be drawn from the system is that it will generate the maximum score despite any disturbances in the provided data. The results of this research align with expert knowledge, suggesting that it can be relied upon to accurately diagnose autism based on the symptoms experienced by individuals. The aim of this study is to build an expert system that can provide information and solutions to parents regarding autism disorders based on their knowledge of the symptoms they experience, enabling users to diagnose autism in their children early on without incurring costs.

Build Id is a website and application-based marketplace that provides various construction needs, both products and services. The Build Id design by PT Semen Baturaja Tbk is aimed at the community as a form of implementing digital transformation in Indonesia. But the design process, to requires evaluation and improvement before it is inaugurated. This is done to avoid complaints, which can reduce the performance of applications and companies. This study aims to help design the Build Id user interface so that it is more focused on the features to be implemented so that the results can match the user's needs. In testing, this study uses the Goal Directed Design method which focuses on designing application designs by identifying user goals and needs. The results of the test prove that the Build Id marketplace for Admins is running well and as expected.

The increasing trend and public interest in coffee shops, also known as cafes. One of the cafes named Kopi KurangLebih has great potential to attract customers due to its strategic location, high-quality menu, and aesthetic ambiance. Although Kopi KurangLebih already has an Instagram account to showcase its content and engage with followers, the information provided is limited and lacks proper organization. Visitors to the coffee shop struggle to make menu choices due to the absence of a platform to display the available options. To address these challenges and improve the quality of service, a website is needed to document and present information that assists customers in making menu selections. The current reliance on social media as a source of information for coffee shops is inefficient and temporary, as the information shared only appears briefly on users' timelines. Hence, the development of an attractive and informative website for Kopi KurangLebih becomes necessary. The website should be designed according to user needs and the resources available to Kopi KurangLebih. By utilizing a digital information medium in the form of a website, potential customers can access and obtain information easily, thereby increasing their interest and purchasing power. The research also applies the Three Circles method and incorporates various UX Law principles into the user interface (UI) design. Through observations and analysis, the research identifies the values of Kopi KurangLebih, customer needs, and competitor values. This research successfully built a UI prototype of the KURLEB website, transforming it into an effective digital platform for promoting, storing, and providing information about Kopi KurangLebih. It also achieved a good user experience by providing relevant information, intuitive navigation, and appealing visual aesthetics. With a well-designed UI and the applied principles of UX Law, this website delivers a positive user experience, enhances customer engagement, and contributes to the sustainable marketing of Kopi KurangLebih as a local coffee shop brand.

Ogan Ilir Regional General Hospital (RSUD) tries to maintain the availability of medicines to meet patient needs. The Pharmacy Department of Ogan Ilir Regional Hospital always monitors existing drug stocks before placing orders with distributors of pharmaceutical supplies. The drug procurement process is carried out in a planned manner to reduce the risk of loss from the method of drug procurement and to identify the need for highly used drugs. This research aims to determine the forecasting of drug needs using the Single Exponential Smoothing method. The data used is drug use data for the period 2021 to 2022. Based on the research results, it was found that based on the highest MAPE score it was at 22% for alpha 0.1, and the highest MAPE was at 12% for alpha 0.5. These results show that the prediction of drug use is successful and has good value because the MAPE score does not exceed 20%.

Object identification and recognition in the field of computer vision is undergoing rapid development and is applied to various fields, ranging from industry to the health sector. This is reflected in the amount of research conducted, including a focus on the application and personalization of machine learning, as well as the development of new models to solve specific problems and challenges. In the palm oil industry, fruit maturity is divided into two categories, namely immature and ripe. Traditionally, fruit maturity is determined visually by experienced workers based on the number of fruits falling from the bunch or the color of the bunch. However, this technique has disadvantages such as the reduced amount of oil when many fruits fall from the bunch and the subjective assessment of fruit color. Therefore, the purpose of this research is to create an oil palm fruit maturity classification system based on YOLO v5. The dataset used consists of 1500 photos and the annotation data is created with roboflow. The final result is divided into three categories, namely ripe, immature, and rotten. The YOLOv5s algorithm was used to train the dataset. Based on the model estimation results, mAP reached 92%, accuracy reached 97%, and recall reached 96%. The last step is real-time system testing.

With the development of technology, there are many methods that can be used to analyze various kinds of problems, both in the world of education, social and even the business world. One method that can be used is the data mining method. Fast food is one example of a business that is being built by many people today, especially in the city of Batam. With so many fast food outlets in the city of Batam, this study aims to classify the types of food that are in demand and not in demand in the city of Batam. To assist the writer in classifying the best-selling and not-selling food types, in this study the authors used the data mining method, namely applying the C.45 Algorithm approach. Apart from using the C.45 Algorithm to test the calculation results, the author uses a website-based information system. From the research that has been carried out, the results obtained are that the best-selling food for children is the Original Burger (BO) and for adults the best-selling type of food is Kebab (K), while the less popular type of food for all ages is Burger Crispy.

A comparison between conventional teaching methods and modern technology reveals a significant difference in the effectiveness and efficiency of educating moderately mentally handicapped children or D3 C class. The available learning materials lack innovation. Monotonous material design that doesn't support interactivity can reduce the interest and engagement of mentally handicapped children. Therefore, the development of more engaging materials that meet their needs is required. D3 C class students with intellectual disabilities require special attention in the use of educational media, considering the current learning materials tend to be monotonous and lacking innovation. Therefore, Augmented Reality (AR)-based learning media can be a promising solution to enhance the quality of learning about various modes of transportation. Interactive AR-based applications enable the introduction of various modes of transportation in a more engaging and interactive way, involving visual and auditory aspects in learning. In application testing, it was proven that the speed of displaying 3D objects was very fast, taking only 2.3 seconds. This contributes to smooth and effective learning for D3 C class mentally handicapped children. Surveys conducted with teachers who have used this AR application indicate a tendency towards positive responses, with the majority of teachers responding "Agree" or "Strongly Agree" to the 10 statements provided. The use of AR in the MDLC approach offers significant potential for improving the education of D3 C class mentally handicapped children. Positive responses to AR reflect innovation in this learning approach, which focuses on individual development, integrated support, and inclusive education. However, it is important to always emphasize supervision to ensure effective AR use, so that children can benefit from a more engaging and tailored learning experience. Thus, the use of AR in the education of D3 C class mentally handicapped children has significant potential to provide innovative and effective learning in various modes of transportation, thereby helping them in their educational process. This research creates a learning method for studying means of transportation for moderately mentally handicapped children using AR technology, which provides innovation in modern times.

In today's modern era, cafes serve a variety of food and beverage menus to their customers. However, this high diversity often leads to problems in selecting menus that suit customer preferences. The main problem faced is the difficulty for customers in choosing the menu that best suits their personal tastes and preferences, given the large number and variety of menus offered by the cafe. The purpose of this research is to find a solution to the problem of selecting a cafe menu using the Simple Additive Weighting (SAW) method. The SAW method is applied to analyze cafe menu data and provide the most suitable menu recommendations based on individual preferences. There are 6 criteria applied in this study to match customer preferences, namely price, portion size, level of popularity, quality of ingredients, compatibility with taste, and aesthetic aspects. It is hoped that this research can provide better guidance for cafe customers in choosing a menu that suits their tastes, as well as help cafe owners in increasing customer satisfaction and sales. The results of calculations using the SAW method that has been carried out get the results of 5 menus that become recommendations because they get the top rank, first Alternative A1 menu Oatmeal Protein Shake has the highest rank with a score of 0.86, second alternative A7 menu Pepperoni Pizza with a score of 0.847, third alternative A4 menu Ramen Noodle with a score of 0.813. fourth alternative A1 menu Alfredo Spaghetti with a score of 0.766 and the fifth Alternative A8 menu Seafood Fried Rice with a score of 0.738.

Inventory applications can help companies monitor, manage, and optimize their inventory. However, the large number of existing inventory applications makes it difficult for companies that want to use inventory applications to choose the right application. This is because to choose an inventory application that suits the company's needs, you have to know each application one by one, so it takes a long time and is difficult to make a choice. This research aims to develop a decision support system for selecting inventory applications by applying the WASPAS (Weighted Aggregated Sum Product Assessment) and Rank Sum approaches. The WASPAS method is used to combine the weights for each criterion and calculate the assessment results based on the product of the criteria values with the appropriate weights. Meanwhile, the Rank Sum weighting technique is used to assign weights or rankings to a number of elements or objects based on their level of importance. Based on the case studies that have been carried out, the results obtained for each alternative include: Zoho Inventory (A4) obtained a value of 0.8531; Onstok (A3) obtained a value of 0.8310; Sortly: Inventory Simplified (A2) obtained a value of 0.7735; BoxHero-Inventory Management (A5) obtained a value of 0.7680; and Shelfit-Inventory Management (A2) obtained a value of 0.6613. In usability testing, we got an average score of 91%, and we can say that the system is suitable for use.

The increasing number of internet users and the fact that each user has various needs result in very high and fluctuating internet traffic, which has an impact on the increasing workload on servers and network infrastructure. Due to the large workload experienced by the server, an approach is needed that can distribute the workload evenly among several resources, or what is known as a load balancing technique. Thus, the main objective of this research is to optimize internet network performance by implementing load balancing techniques and measuring the performance improvements that can be achieved. Load balancing methods are used to avoid imbalances that can cause one resource to be overburdened while others may not be used optimally. For testing, connections were made 1000 times with 100 requests/second, then increased gradually up to 11,000 connections with 1100 requests/second. Test results show that at low to medium connection levels (1000/100 to 6000/600), servers without load balancing tend to provide better response times. However, as connection rates increase (from 7000/700 to 11000/1100), servers with load balancing show superiority by having better response times than servers without the technique. Therefore, this research suggests that implementing a load balancing strategy is very important for maintaining optimal performance and system stability under high workload conditions.