Abstract:Abstract: The rice plant, Oryza sativa, is a major food source in Indonesia. This plant is processed into rice, a staple food for the Indonesian people. Rice growth is crucial to ensure the rice produced is of good quality.…
ty. One part of the rice plant that is susceptible to disease is the leaves, which can inhibit growth and reduce rice quality. Therefore, early detection and accurate classification of rice diseases are crucial to minimize these negative impacts. This has driven the development of a Deep Learning model capable of high-performance automatic classification. This study aims to create a rice leaf classification model using the CNN algorithm and several transfer learning architectures such as ResNet101, VGG16, and Xception. A dataset of 859 rice leaf images collected from the Kaggle website was then processed using augmentation techniques to a total of 2,439 images, plus 215 smartphone photos for external data validation. Thus, the total dataset increased to 2,656 images, covering four categories: leafblast, brownspot, healthy, and hispa. The model was processed in two stages: on the initial dataset (Non-Augmented Dataset) and the Augmented Dataset. The best experimental results were obtained using the ResNet architecture, with a training accuracy of 96.17% and a validation accuracy of 95.22%. Based on the research results, the rice plant disease classification model using deep learning demonstrated good performance.
Keywords: convolutional neural network; deep learning; fine-tuning; image classification; resnet; rice plant
Abstract:Abstract: YouTube is one of the most popular video streaming platforms, but it has constraints that can cause problems when clients have difficulty finding content according to their wishes. The main objective of this study…
udy is to increase user capacity in viewing content specifically in the field of women's empowerment. By using content-based filtering techniques, the system will analyze user preferences and interests through recommendations for women's empowerment content. The data source is via the YouTube API and is analyzed using PHP programming content-based filtering techniques. The system's recommendations provide a list of women's empowerment content with a user request display. The results of the research evaluation obtained a precision value of 62%, meaning that the recommendations match the topic being searched for, namely women's empowerment. The recall value of 84% indicates that the system has succeeded in finding relations from the database. The f1-score value of 72% indicates that there is a balance between precision and recall, meaning that a system is needed that is not only accurate but also complete. While the cosine value shows a score of 0.7071 approaching the maximum value (1.0). The recommendation of the content-based filtering method produces quite effective women's empowerment content.
Keywords: content-based filtering, recommendations, women Empowerment, youtube
Abstract:Abstract: Land registration in Indonesia often encounters challenges in transparency, data integrity, and centralized bureaucracy. Manual and semi-digital systems remain vulnerable to manipulation and delays. The National…
l Land Agency has initiated digitalization, but several challenges remain, particularly in ensuring transparency, efficiency, and security of land ownership data. Blockchain technology offers a potential solution through its decentralized and immutable characteristics. This study adopted a design and development method consisting of system analysis, requirements identification, architecture design, implementation, and black-box testing. The developed decentralized application (DApp) integrates smart contracts, NFTs, and IPFS to manage land certificates. Core functions such as minting, transfer, splitting, and self-custody were implemented and successfully tested, with all scenarios producing expected results. The findings demonstrate that blockchain integration can enhance security, reduce duplication, and streamline land administration. The study contributes a functional prototype with practical implications for modernizing land registration in Indonesia while identifying scalability and regulatory adaptation as areas for further research.
Keywords: blockchain; decentralized application; land registration; NFT; smart contract.
Abstract:Abstract: Ineffective drug demand management can lead to problems such as imbalanced drug distribution, excess stock, or shortages in community health centers. To address this, data mining can be utilized to support the…
planning and control process of drug inventory. Clustering techniques were chosen because they are able to group drug data based on certain characteristics, thus identifying stable and unstable drug supply patterns. This study aims to group drug data at Simpang Kawat Community Health Center in Jambi City, which can be used as a reference in planning drug needs in the next period. Data grouping is divided into three categories: slow-moving, medium-moving, and fast-moving. The research data includes attributes of drug name, initial stock, receipt, inventory, usage, and final stock, with a total of 1758 data sets, which were processed using the CRISP-DM framework through the RapidMiner application. Cluster quality evaluation was carried out using the Davies-Bouldin Index (DBI). The results showed that the K-Means algorithm obtained a DBI value of 0.175, smaller than K-Medoids which obtained a value of 0.354. Because a smaller DBI value indicates better cluster quality, K-Means provides more optimal clustering results than K-Medoids. Through these clustering results, community health centers can utilize drug cluster information to support more efficient drug procurement planning, as well as reduce the risk of excess or shortage of stock.
Keywords: data mining; clustering; k-means; k-medoids; davies-bouldin index
Abstract: Abstract: The Ombudsman of the Republic of Indonesia is an institution tasked with supervising the administration of public services and handling community complaint reports related to allegations of maladministration.…
on. The purpose of this research is to create a decision support system using the Analytic Hierarchy Process (AHP) method, which facilitates the determination of priority handling of community complaint reports at the Ombudsman of the Republic of Indonesia Bengkulu Representation. This decision support system is built on a web-based platform using PHP programming language with a MySQL database that can be accessed offline by the admin of the Ombudsman. With the existence of this priority recommendation, it is expected that work will become more effective and efficient, as resources can be focused on reports that most need attention. Based on the test data used, which consists of 12 Community Complaint Reports from July 2024, it was found that the priority handling recommendations for community complaint reports were derived from 3 reports with the highest final AHP values. The recommended priority handling reports are registration number 0021/LM/VII/2024/BKL with a final AHP value of 2.074, registration number 0020/LM/VII/2024/BKL with a final AHP value of 1.964, and registration number 0018/LM/VII/2024/BKL with a final AHP value of 1.866.
Keywords: decision support system; priority recommendation; public complaint report; AHP Method (analytic hierarchy process method)
Abstract:Abstrack: This research aims to improve battery performance and safety on the ECGO2 electric motorcycle by re-assembling the battery system using 18650 lithium cells, Daly BMS 13S/7A battery management system, and XH-M604…
4 module. The configuration used is 13S5P (65 cells), resulting in a total voltage of 48.1 V and a capacity of 14 Ah, or equivalent to 673.4 Wh of energy. Compared to the ECGO2 built-in battery that requires 4-7 hours of charging time, this system is able to speed up charging to ±1.6 hours using a 7 A current charger. Test results using an oscilloscope show that the voltage of the assembled battery is more stable under load than that of a single battery, with minimal ripple. The estimated operating time of an 800 W electric motor using a 673.4 Wh battery is about 50 minutes. To achieve 2 hours of operation, the 13S10P configuration or energy-saving mode (400-500 W) can be used. The system is also more cost-effective at Rp2,678 per Wh compared to the manufacturer's version of Rp4,464 per Wh, as well as improved safety against leakage and overheating.
Keywords: 18650 lithium battery; daly bms; electric motorcycle; fast charging.
Abstrak: Penelitian ini bertujuan untuk meningkatkan performa dan keamanan baterai pada sepeda motor listrik ECGO2 dengan merakit ulang sistem baterai menggunakan sel lithium 18650, sistem manajemen baterai Daly BMS 13S/7A, dan modul XH-M604. Konfigurasi yang digunakan adalah 13S5P (65 sel), menghasilkan tegangan total 48,1 V dan kapasitas 14 Ah, atau setara dengan energi 673,4 Wh. Dibandingkan baterai bawaan ECGO2 yang memerlukan waktu pengisian 4–7 jam, sistem ini mampu mempercepat pengisian menjadi ±1,6 jam menggunakan charger arus 7 A. Hasil pengujian menggunakan osiloskop menunjukkan bahwa tegangan baterai rakitan lebih stabil di bawah beban dibandingkan baterai tunggal, dengan ripple minimal. Estimasi lama pengoperasian motor listrik 800 W menggunakan baterai 673,4 Wh adalah sekitar 50 menit. Untuk mencapai 2 jam pengoperasian, dapat digunakan konfigurasi 13S10P atau mode hemat energi (400–500 W). Sistem ini juga lebih hemat biaya dengan efisiensi harga Rp2.678 per Wh dibandingkan Rp4.464 per Wh versi pabrikan, serta meningkatkan keamanan terhadap kebocoran dan panas berlebih.
Kata kunci: baterai lithium 18650; daly bms; sepeda motor listrik; pengisian daya cepat.
Abstract:Abstract: INET Computer Palembang, as a computer training institution, faces difficulties in understanding participant characteristics due to variations in age, educational background, and chosen course packages. This study…
udy aims to analyze participant criteria and group them based on similarities using the K-Means Clustering algorithm. The data used were historical records of course participants from 2022 to 2025. The research process followed the CRISP-DM stages, starting from data cleaning and transformation, determining the optimal number of clusters using the Elbow Method, to evaluating cluster quality with the Davies-Bouldin Index. The implementation was carried out using Python and the scikit-learn library. The results show that the optimal number of clusters is k=5 with a Sum of Squared Errors (SSE) value of 1064.66 and a Davies-Bouldin Index (DBI) score of 0.820, indicating good cluster quality. The resulting clustering provides a structured profile of participants and demonstrates that K-Means is effective in segmenting course participants. These findings are expected to assist the institution in designing more targeted training programs.
Keywords: clustering; data mining; elbow method; k-means; computer course
Abstract:Abstract: Hospitals play an important role in examining the scan results of patient data infected with the Covid 19 virus. However, there are problems when processing the scan results, namely that sometimes errors occur…
in the scan data, causing many failures and delays in sending data to the Health Office. The purpose of this study is to build a Desktop-based decision support system application that can facilitate hospitals in selecting the eligibility of the scan results of Covid 19 patient data. The urgency in examining the scan results of Corona patient data is a very pressing public health issue, because the long-term impact is very significant for patients. Thus, a scientific discipline is needed that can support the decision-making process, namely the Decision Support System using the Preference Selection Index (PSI) method. PSI is a simple and easy calculation method, based on statistical concepts without having to determine attribute weights. The results of this method are clear and firm values based on the level of strength of the rules applied. The results of the research conducted on the PSI process can be concluded that valid Covid 19 patient data is Recap File I with a value of 0.2042 which is declared valid and accepted.
Keywords: covid-19; decision support system; PSI
Abstract:Abstract: The global transition towards sustainable food systems faces significant challenges in vegetarian food supply chains, including transparency issues, distribution inefficiencies, and quality verification problems.…
s. This research proposes VegeChain development, a decentralized marketplace ecosystem based on smart contracts designed to transform vegetarian food supply chains and accelerate Meatless, Balanced, Green (MBG) program adoption. Using mixed-method methodology integrating blockchain system design, stakeholder analysis, and economic simulation, this research develops a comprehensive technology framework combining blockchain transparency, smart contract automation, and sustainable tokenomics with novel mathematical models. The system implements dynamic pricing algorithms based on Automated Market Maker (AMM) mechanisms, multi-objective optimization for supply chain efficiency, and reputation-based consensus protocols. Simulation results demonstrate that VegeChain implementation can improve supply chain efficiency by 35%, reduce food waste by 28%, and increase consumer trust by 42% measured through validated stakeholder satisfaction surveys (n=456) using 5-point Likert scales with statistical significance p<0.001. Technical innovations include Byzantine Fault Tolerant consensus with 99.9% reliability, gas optimization achieving 67% cost reduction, and real-time quality verification algorithms with 98.7% accuracy.
Keywords: smart contracts; supply chain optimization; automated market makers; blockchain technology; sustainable tokenomics
Abstract:Abstract: In agriculture, irrigation systems are vital for enhancing water management and maximising plant growth. Effective irrigation management involves distributing sufficient quantities of water evenly to condition…
soil fertility for plants. This study aims to design a prototype that can be monitored via the Telegram app. The research methodology employs a thinking framework approach. The system is implemented using an Arduino Uno microcontroller and supporting devices, including an ESP8266 Wi-Fi module, an ultrasonic sensor, a soil moisture sensor, a stepper motor and a servo motor. Telegram serves as the monitoring tool, sending notifications connected to the Arduino via a Wi-Fi network. Test results showed that the system operates effectively: the HC-SR04 ultrasonic sensor functions as a water level reader, and the stepper motor opens and closes the water gate. Soil moisture monitoring uses a soil moisture sensor to measure the water content in the soil. If the sensor detects dry soil conditions or a moisture level below 60%, the servo motor will rotate 15° to close the water channel. Conversely, if the sensor detects wet or moist soil conditions, the servo motor will rotate 0° to close the water channel.
Keywords: arduino uno; irrigation system; soil moisture; ultrasonic sensor;