JiTEKH

Potensi Bendung Irigasi Sebagai Pembangkit Listrik Tenaga Mikrohidro

Ahmad Taufik — 2024-09-26

Sei Padang Dam is a dam that dams the flow of the Padang River specifically to meet the needs of 3 irrigation areas, namely Paya Lombang, Langgau and Bajayu. Sei Padang Dam is currently only used as an irrigation channel and the potential energy that can be produced is not yet known. This study utilizes dam structures that have been completed such as intake channels, headrace channels, forebays and tailrace channels. This potential analysis was carried out using several methods, such as measuring the head using Google Earth, and using irrigation water discharge data from BWS Wil II Sumatra. The results of the study showed that Sei Padang Dam has a PLTMH potential of 50 kW with a water discharge of 2 m3/second and a water fall height/head reaching 4 meters. The most optimal turbine type is the Archimedes screw turbine type.

Implementasi Recurrent Neural Network Sebagai IDS Terhadap Serangan Jaringan

Fransko Gultom — 2024-09-30

In recent years, a new term has emerged which is now widely applied as IDS (Intrusion Detection System), namely Deep Learing. One type of Deep – Learing is RNN (Recurrent Neural Network) which has recently been applied to IDS. Cyber attacs cannot be avoided, but they can be anticipated by building a system than can detect the performance of network data flows so that users can avoid all kinds of attacks and intrusion attempts from unknown parties. This research aims to test and analyse the accurary and speed of the Recurrent Neural Network in detecting attacks. The method used for this research is RNN, which is operated through the Python and Google Colab programs. Based on the results, the model was trained with 50 epochs resulting in an accurary of 92%. Meanwhile, a model with 30 epochs produces an accurary of 99%. So, the model can work well on training data with a total of 30 epochs.

Implementation of MABAC Method and Entropy Weighting in Determining the Best E-Commerce Platform for Online Business

Junhai Wang — 2024-09-30

The main problem in choosing an e-commerce platform for an online business is finding the one that best suits the specific needs of the business. Each platform has its advantages and disadvantages, such as ease of use, cost, features offered, as well as support for inventory management, shipping, and payments. Other challenges include ensuring that the platform can support future business growth, offer good scalability, and provide flexibility in terms of customization and integration with digital marketing tools. In addition, data security and a good user experience are also important considerations for long-term success. The purpose of this study is to implement the MABAC method and Entropy weighting in determining the best e-commerce platform for online businesses, so that this research can provide clear and data-driven recommendations to stakeholders regarding the most effective e-commerce platform. The application of the MABAC method combined with Entropy weighting in determining the best e-commerce platform for online business people offers a comprehensive and objective approach in decision-making. This combination not only improves decision-making accuracy, but also ensures that the most important criteria are weighted accordingly, resulting in more reliable results in choosing the best platform for business needs. The final result of the MABAC Platform A score is the first choice, considering the highest score of 0.82, which indicates its optimal performance in meeting the criteria that have been set. In addition, Platforms B and C, with scores of 0.78 and 0.75, respectively.