Computer Science (CO-SCIENCE)

Peningkatan Jaringan Komunikasi Tertutup Berbasis Seluler Dengan Agregasi Multi Link : Studi Kasus PT. Solusi Media Semesta

Fadlul iman, Elin Panca Saputra, Aryo Tunjung Kusumo, Sismadi Sismadi — Wed, 31 Jul 2024 00:00:00 +0700

The increasing need for cellular-based closed communication networks in corporate environments has increasingly become a major focus for many organizations, including PT. Universal Media Solutions Jakarta. In the face of increasingly complex communication challenges and increasing data demands, the company is working to improve the efficiency and performance of its communications network. This study aims to investigate the potential of using multi-link aggregation as a solution to improve cellular communication networks at PT. Universal Media Solutions Jakarta. The multi-link aggregation method allows combining multiple communication lines to achieve increased network speed, availability, and consistency. The study will involve analyzing and testing various scenarios using multi-link aggregation technology in the company's cellular-based closed network environment. Network performance measurement will be carried out to radiate the effectiveness of the implemented solutions. In addition, technical and financial factors will also be considered to ensure the feasibility and efficiency of the proposed solution. The results of this study are expected to provide valuable insights for PT. Solusi Media Semesta Jakarta and other organizations in optimizing their closed communication network using multi-link aggregation technology. Thus, companies can increase productivity, reduce downtime, and improve service quality for their customers and internal users.

Rancang Bangun SPK Kualitas Air Sungai Metode Fuzzy Tsukamoto (Studi Kasus: 4 Kecamatan Karawang)

Fery Anuar Ramadhan Putra, Ade Andri Hendriadi, Taufik Ridwan — Wed, 31 Jul 2024 00:00:00 +0700

Research reveals that the Citarum River in West Java is seriously polluted, causing problems for humans and the environment, so monitoring of river water quality is necessary. This research proposes the development of a web-based Decision Support System with the SDLC Waterfall model, using the Fuzzy Tsukamoto method based on seven water parameters (EC, TDS, Salinity, pH, ORP, SG, Temperature) to simplify the determination of water quality. This research uses the Research and Development methodology with the SDLC Waterfall model software development approach, which includes the stages of analyzing data requirements and fuzzy logic systems, designing system architecture and features, implementing technology and process results, functional manual testing and model accuracy, and maintenance in the form of documentation and storage. The results showed that the developed DSS can classify water quality based on 7 parameters with a value scale divided into five categories, namely Good, Poor, Medium, Good, and Very Good. Testing was conducted using data from 8 river points in 4 sub-districts in Karawang Regency on April 1, 2024. The accuracy of the DSS model reached 80%. The development of this DSS is expected to provide an initial overview of water quality in a location without requiring an in-depth technical understanding of the water parameters used. This data can also be an initial indicator to determine whether further action or further investigation is required. Suggestions for future research are to integrate the system with IoT to improve its performance and benefits.

Metode Rapid Application Development Dalam Pengembangan Sistem Informasi Perpustakaan Berbasis Web

Syarif Hidayatulloh, Enda Patyani — Wed, 31 Jul 2024 00:00:00 +0700

The information system is crucial for business processes in all fields, including education. A library at SMK Negeri 1 Jawai, Sambas Regency, currently manages its data, borrowing, and book return processes manually, using physical records and writing tools. With such management, the library faces various challenges. Common issues include students having difficulty tracking borrowed books, problems with lost returns, and discrepancies in the number of loans and returns. Therefore, this research aims to improve business processes at SMK Negeri 1 Jawai's library by developing a web-based information system tailored to its needs. Rapid Application Development was chosen as the development method for this library information system due to its ability to quickly produce a high-quality system. The method involves stages such as requirement planning, system design, and implementation. RAD is capable of creating a website that provides objective information. The resulting Information System from this research was tested using Blackbox Testing, which confirmed that all features and processing flows functioned correctly.

Rekomendasi Pemilihan Jenis Tanaman Menggunakan Algoritma Random Forest dan XGBoost Regressor

Abdul Rahman, Daniel Udjulawa, Mulyati Mulyati — Wed, 31 Jul 2024 00:00:00 +0700

Recommendations for plants that suit a particular planting location's environmental conditions and soil nutrients can lead to optimal harvest outcomes. Machine learning applications in agriculture have been widely explored, particularly in enhancing crop yields. In this study, two machine learning algorithms, Random Forest and XGBoost Regressor, were implemented to recommend plants based on environmental conditions and soil nutrient levels. The implementation of both algorithms was compared in terms of accuracy using three accuracy metrics: Mean Absolute Error (MAE), Mean Square Error (MSE), and R2. The results indicated that both algorithms exhibited comparable accuracy levels. The Random Forest algorithm demonstrated superior accuracy in terms of MAE and MSE, with values of 36.73681574 and 1.848396760, respectively. Meanwhile, the XGBoost Regressor algorithm displayed good accuracy, mainly when measured using the R2 accuracy metric, achieving a high accuracy level of 0.98542963509705..

Keywords : Crop Recommendation, Machine Learning, Random Forest, XGBoost

Klasifikasi Kualitas Buah Apel Dengan Algoritma K-Nearest Neighbor (K-NN) Menggunakan Bahasa Pemrograman Python

Puji Astuti — Wed, 31 Jul 2024 00:00:00 +0700

Fruit is an important intake for the human body, apples are included in the fruit favored by the people of Indonesia. For this reason, it is necessary to provide apples of good quality, so that they can benefit the body. By using the k-NN method that is considered able to train data quickly and effectively for training data and testing data in large quantities. This study began from the collection of datasets obtained from https://www.kaggle.com/, then perform a preprocessing process followed by separating the training data and testing data with a composition of 25% testing data and 75% training data. Then the k-NN method is applied to this study to be classified based on several existing criteria, so as to obtain the results of performance evaluation K-NN with the value of accuracy that has been calculated with python programming. In implementing datamining using Python programming language by utilizing the library that has been provided as a process to facilitate the implementation of machine learning. From The Matrix confution test, there are 441 data predicted with true data, and 440 data predicted incorrectly. As for the 54 and 65 data predicted to be less precise than 1000 testing data. So that the accuracy value obtained by the k-NN method is equal to 0.88 or 88%. It is seen that the k-NN method can work well, quickly and efficiently in training large amounts of data.

Penerapan Model Design Thinking Pada Perancangan Aplikasi Informasi Desa Wisata Kabupaten Bantul

Wahyutama Fitri Hidayat, Yesni Malau, Rachmat Adi Purnama, Ahmad Setiadi — Wed, 31 Jul 2024 00:00:00 +0700

Tourism actors in the current technological era have implemented information systems. With the rapid growth of tourist villages in Bantul Regency, there is a need for promotion and digital information delivery media. However, in developing digital media it is also necessary to pay attention to aspects of the users who are the target market. The design of the application called sidewi mobile (mobile tourist village information system) is based on user experience and needs, using the Design Thinking methodology which has five stages as follows: Empathize, Define, Ideate, Prototype, and Test. The design of the Sidewi mobile application was created using FIGMA software. This research has direct benefits, namely that it can be used as a benchmark for design needs before the development process. The results of the design are then tested using the usability testing method. Using a user friendly design approach and conducting testing using usability testing with the results of five users being able to complete the testing proves that when it was created using user experience there were no significant difficulties when used and it covered all needs.

Pengembangan Sistem Self Ordering Berbasis Web Dengan Metode Rapid Application Development (RAD)

Arief Herdiansah, Ryan Zulham Ramadhani, Mahpud Mahpud, Najmah Frithadila — Wed, 31 Jul 2024 00:00:00 +0700

The food order recording system can cause errors in recording orders, lose data and require a lot of time in the process of recording and reporting orders. Product marketing carried out using social media requires sellers to upload product photos one by one so that buyers can see them. This is more troublesome if the ordering process is carried out conventionally. This research is applied research on the development of a food ordering information system with a self-ordering concept which can be an alternative solution to replace conventional food ordering systems. This research was conducted at Mimi Cakes & Cookies MSME, which currently still uses conventional methods in the process of recording pre-orders for the food it sells. This research uses the Rapid Application Development (RAD) development method. The system was developed using the PHP Framework Codelgniter programming language with the VS Code text editor. The system development results were tested using the black box testing method. The results of this research produce a pre-order system with a Web-based self-ordering concept that can provide a solution to the problem of recording and reporting orders for Mimi Cakes & Cookies MSMEs. The system developed has also caused the number of orders for Mimi Cakes and Cookies to increase by 20%

Klasifikasi Perilaku Pemain Game Online Menggunakan Naïve Bayes Berbasis Particle Swarm Optimization

Sujiliani Heristian, Rian Septian Anwar, Hanggoro Aji Al Kautsar — Wed, 31 Jul 2024 00:00:00 +0700

Much research has been conducted to understand player behavior as a result of the rapid growth of online gaming. In this research, we use the Naive Bayes method optimized using Particle Swarm Optimization (PSO) to analyze the behavior classification of online game players. The classification accuracy value of the baseline method is 75.09% and the Area Under the Curve (AUC) value is 0.798. We use PSO-based optimization on Naïve Bayes to improve model performance. The results showed that the combination of Naïve Bayes and PSO increased classification accuracy to 95.28% with an AUC value of 0.990. This is a major advance that shows that combining the PSO algorithm with Naive Bayes can enable better classification of online game player behavior. These findings will make a significant contribution to the process of making plans that can improve the gaming experience.

Prediksi Kualitas Tidur: Pendekatan Machine Learning yang Mengintegrasikan Faktor Kesehatan dan Lingkungan

Jordy Lasmana Putra, Wahyutama Fitri Hidayat — Wed, 31 Jul 2024 00:00:00 +0700

Sleep disorders significantly affect an individual's sleep quality, which can lead to serious health problems. For the elderly, poor sleep quality can drastically reduce life expectancy. The main problem is the lack of effective predictive tools to improve sleep quality among the elderly, compounded by the numerous factors that can influence their sleep quality. Therefore, analysis and prediction are necessary to enhance sleep quality. This study aims to develop and test a predictive model for sleep quality in the elderly by integrating health and environmental factors using a machine learning approach. The dataset used is a new one available on the website Kaggle.com, namely the National Poll on Healthy Aging (NPHA) data, which provides insights into health issues, healthcare, and health policies affecting Americans aged 50 and above. The aim is to improve sleep quality among the elderly. A machine learning method, specifically deep learning with the Random Forest algorithm, was used in this study and showed good results with an accuracy rate of 94.00% and a training data accuracy of 44.44%. The results of this study are expected to provide a predictive tool that can be used by healthcare practitioners to improve the sleep quality of the elderly, thereby positively impacting their health and life expectancy.

Penerapan Algoritma C4.5 Untuk Menentukan Kepuasan Pengguna Aplikasi E-Open Study Kasus : Kelurahan Jati Makmur

Yuli Komalasari, Nabila Rahmah Puspitasari, Chalimatusadiah Chalimatusadiah — Wed, 31 Jul 2024 00:00:00 +0700

To support government administration activities in an area, an application called E-Open is needed. The application was created to support the Bekasi City government, one of which is Jatimakmur Village, which is a government agency in Pondok Gede, Bekasi City. The application has been implemented, evaluation of the administration process using the E Open application is required. The aim is to measure, help, test and analyze the level of satisfaction using the E-Open application for Jatimakmur Village residents. Using data mining in data processing to determine the accuracy of each process, accurately converting information so that information is quickly understood and includes collecting, using historical data, patterns or relationships in large data sets. The research population was taken as 150 samples. Quantitative research using the C4.5 algorithm method is used, because it can make predictions by providing an ideal level of accuracy for prediction. Test this research with RapidMiner version 10.1. The results of the processing have a significant effect in determining the classification of the level of citizen satisfaction with the E-Open application. With an accuracy level of 91.33%, while in manual calculations the accuracy was 90.67% for the Satisfied percentage, or also known as the Very Good category.

Keywords : Accuracy, C4.5 Algorithm,E-Open