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User reviews on the Shopee e-commerce platform represent an important source of information for understanding consumer perceptions of products and services. Sentiment analysis is commonly applied to classify user opinions into positive, neutral, and negative sentiment categories based on textual data. This study aims to analyze the performance of the Long Short-Term Memory (LSTM) method in sentiment classification of Shopee user reviews. The dataset used in this study consists of Indonesian-language user reviews that have undergone preprocessing stages, including case folding, text cleaning, tokenization, and stopword removal. The LSTM model was trained using preprocessed text represented as word sequences. Model performance was evaluated using overall accuracy and class-wise classification results. The experimental results indicate that the LSTM method achieved an overall accuracy of 87.62%. In addition, the classification performance for the positive sentiment class reached 95.27%, the neutral class achieved 4.96%, and the negative class reached 74.26%. These results demonstrate that the LSTM method performs well in classifying sentiment in Shopee user reviews, particularly for positive sentiment. This study is expected to provide insights and references for the application of deep learning methods in sentiment analysis of Indonesian e-commerce review data.

This research aims to develop a multiclass flower image classification system using the Convolutional Neural Network (CNN) algorithm with the EfficientNet architecture. The main problem addressed is the difficulty of manual identification of flower species that share high visual similarity. The research stages include collecting 17,299 flower images across 19 classes, performing data preprocessing such as image resizing, pixel normalization, and augmentation, followed by model training using the EfficientNet transfer learning approach. The model was trained for 10 epochs with an 80:20 training-validation data split. The evaluation results show that the model achieved a validation accuracy of 98.05% with a loss value of 0.0968, and an average precision, recall, and F1-score of 0.98. The trained model was then implemented into a web-based application built using the Next.js framework, enabling users to upload flower images and obtain real-time classification results via the Hugging Face API. The system successfully identified flower species with a confidence level of 99.87%. These findings demonstrate that combining a modern CNN architecture with transfer learning provides efficient and highly accurate flower classification performance, which can be effectively implemented for educational and digital conservation purposes.

The development of social media platforms like TikTok has created new spaces for digital economic activities, including the practive of thrifting, which has now become a trend among the public. However, government policies that block these activities have sparked various public reactions. This study aims to analyze public sentiment regarding the issue of thrifting bans on the TikTok platform using the Bidirectional Long Short-Term Memory (Bi-LSTM) method. This method was chosen because it can understand text context from both directions, allowing it to capture deeper semantic meaning. The dataset consist of 4,000 TikTok user comments collected through a crawling process. The research stages include data preprocessing, sentiment labeling, splitting training and test data, training the Bi-LSTM model, and evaluating performance using accuracy, precision, recall, and F1-score metrics. The research results show that the Bi-LSTM model achieved an accuracy of 86.15%, with stable classification performance and minimal error rate. These findings indicate that Bi-LSTM is effective for sentiment analysis of public opinions on Indonesian language social media, particularly on context specific policy issues. Further development can be carried out by adding pre-trained embeddings or attention mechanisms to improve the model’s performance.

The development of renewable energy, particularly Solar Power Plants (PV), requires a reliable, real-time, and easily accessible electrical energy monitoring system to ensure optimal system performance. This study aims to design and implement an Internet of Things (IoT)-based electrical energy monitoring system for PV using the NodeMCU ESP32 microcontroller, the PZEM-004T sensor for measuring electrical parameters, and the Node-RED platform as the data visualization interface. The developed system is designed to monitor voltage, current, power, energy, frequency, and power loss in real time, and then display the data in the form of numerical values, graphs, and indicators on a dashboard accessible through a local network. The research method includes hardware design, software development (sensor reading, data processing, and communication), integration with Node-RED, and system testing on a small-scale PV installation. The test results show that the system is capable of monitoring electrical parameters in a stable and responsive manner. Variations in sunlight intensity were found to affect the current and power produced by the solar panels, whereas the inverter output voltage tended to remain within normal operating ranges. The Node-RED dashboard display was considered informative and helpful for users in monitoring and analyzing PV performance. Based on these results, it can be concluded that the IoT-based electrical energy monitoring system designed in this study functions well and is feasible for application in residential or educational-scale PV installations. The system still has the potential for further development through cloud service integration, the addition of environmental sensors, and enhancements to data analysis features and user interface design.

PAMTIRTA Tempino is an institution that provides clean water services in the Tempino area. The process of recording water use and monitoring water turbidity is still done manually, making it prone to recording errors and making it difficult to monitor the water quality distributed to the community. This study aims to design a website-based water turbidity recording and monitoring system by focusing on User Interface (UI) and User Experience (UX) aspects using the Design Thinking method. The research follows five stages of Design Thinking: empathize, define, ideate, prototype, and test. Data collection involves observation and in-depth interviews with PAMTIRTA officers. The results include a design with key features such as digital water meter recording, turbidity monitoring dashboards, and complaint services. The prototype was tested using Maze and the System Usability Scale (SUS), achieving a score of 80.1 and falling into the "Good" category (grade B). These results demonstrate that the UI/UX design effectively provides an easy-to-understand, operationally suitable, and efficient solution for PAMTIRTA Tempino's water recording and turbidity monitoring needs. This design offers a ready-to-implement solution to improve the efficiency, accuracy, and quality of clean water services in the Tempino area.

Penelitian ini bertujuan merancang dan mengembangkan Sistem Informasi Penjualan berbasis web untuk Gerai Oleh-Oleh Bali yang selama ini masih menggunakan pencatatan manual dengan buku besar dan perhitungan menggunakan kalkulator. Sistem manual tersebut menyebabkan risiko kesalahan pencatatan, lambatnya proses pencarian data, serta kesulitan dalam pengarsipan data penjualan, pembelian, pemesanan, dan pengelolaan stok barang. Penelitian menggunakan metode pengembangan perangkat lunak Waterfall dengan pendekatan pemodelan Unified Modeling Language (UML). Tahapan yang dilakukan meliputi analisis kebutuhan melalui wawancara dengan pemilik gerai, perancangan sistem (Use Case Diagram dan Class Diagram), implementasi, pengujian unit, pengujian sistem menggunakan metode black-box testing, serta tahap pemeliharaan (maintenance). Sistem yang dibangun mencakup fitur login, dashboard, pengelolaan data master (supplier dan barang), transaksi penjualan dengan dukungan scan barcode, transaksi pembelian, laporan penjualan dan pembelian, serta pengelolaan user. Hasil pengujian black-box menunjukkan seluruh test case berstatus Valid dan sistem berfungsi sesuai harapan. Pada tahap maintenance dilakukan contoh corrective maintenance dengan perbaikan bug pada query laporan penjualan harian.Sistem informasi penjualan berbasis web yang dihasilkan mampu mempercepat proses transaksi, mengurangi kesalahan manusia, meningkatkan akurasi data, serta memudahkan pengelolaan stok dan pembuatan laporan secara real-time. Implementasi sistem ini memberikan solusi efektif bagi Gerai Oleh-Oleh Bali dalam meningkatkan efisiensi operasional dan interaksi dengan pelanggan.

Indonesian Sign Language (BISINDO) serves as a primary communication medium for the deaf community; however, limited public understanding often creates barriers during daily interactions. This study aims to develop a real-time BISINDO word-level translation system using hand landmark extraction and temporal modeling with Long Short-Term Memory (LSTM). The system employs MediaPipe Hands to detect 21 hand landmarks per frame, which are then processed as sequential motion patterns to classify five BISINDO words: saya, terima kasih, maaf, nama, and kamu. A total of 250 gesture samples were recorded under controlled lighting conditions as the primary dataset. The processed sequences were used to train the LSTM model, which was subsequently integrated with an ESP32 microcontroller and a DFPlayer Mini module to produce direct audio output. Experimental results show that the model achieved an average accuracy of 86%, with precision and recall values ranging from 0.81 to 0.94. The confusion matrix analysis indicates that most gestures were correctly classified, although some errors occurred in gestures with similar initial motion trajectories. Integration testing demonstrated an average system latency of 3.8 seconds and an audio output success rate of 85%. These findings indicate that the proposed system is capable of translating BISINDO word-level gestures accurately, responsively, and consistently in real-time conditions. This study provides a strong foundation for the broader development of sign language translation systems, with potential enhancements in vocabulary expansion, multi-user datasets, and hardware optimization for deployment in real-world environments.

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.

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.

Digital transformation in government bureaucracy has become a strategic step to improve efficiency, accountability, and transparency, including in the management of regional legal products. In the Regional Secretariat of Tegal Regency, the process of submitting legal products is still done manually, which causes inefficiencies, delays, and a lack of document traceability. To address these issues, a web-based legal product submission application has been developed with document tracking features. This research uses the Waterfall system development method, and implements a FIFO (First In First Out) queuing system in the submission process, along with Role-Based Access Control (RBAC) for managing user access rights. The goal of this system is to create a faster, more transparent, and digitally documented application process. The implementation results show that the application is able to systematically and integratively manage the flow of submissions, corrections, verification, and the ratification of legal products. Features such as a Login page with CAPTCHA, analysis dashboards, tracking, and monthly reports enhance the monitoring and security functions of the system. This application can be an effective solution in supporting the digitization of regional legal bureaucracy, as well as providing ease and efficiency for regional officials in preparing and submitting drafts of legal products digitally.

The coffee farming sector in Gunungmanik Village, Indonesia, plays a significant role in the local economy. However, the monitoring and management of coffee crops remain largely manual and conventional, making it difficult for farmers to respond quickly to environmental threats such as drought, pests, or sudden temperature shifts. This research presents the development of iotgm.id, a web-based monitoring system integrated with Internet of Things (IoT) devices designed to provide real-time environmental data for coffee plantations. The system measures key parameters including temperature, soil moisture, and motion detection (as a proxy for pest activity), and delivers this data via a user-friendly web interface. It also features digital farm record management, real-time alerts for abnormal conditions, and data visualization through interactive dashboards. Field testing with local farmers showed that the system improves decision-making, speeds up responses to environmental changes, and reduces the need for direct field visits. Unlike earlier systems that often required technical expertise or focused on single parameters, this system offers multi-parameter monitoring and is accessible to farmers without advanced digital literacy. The system bridges the gap between sophisticated agricultural technologies and practical field-level application. It contributes to the adoption of precision agriculture in rural areas, offering a scalable model for broader implementation in similar contexts

The Message Queue Telementary Transport (MQTT) protocol is able to adjust the sending and receiving of messages to monitor in accordance with the user's preferences because the sending and receiving of messages is topic based on a specified topic, making it necessary to routinely monitor the condition of patients who have been diagnosed with heart problems from a distance. With the aim to perform a Quality of Service (QoS) analysis with throughput, delay, and packet loss parameters using Unshielded Twisted Pair internet transmission media (UTP) and Wireless, the goal of this research is to design and implement (MQTT) a heart rate monitoring device with an EKG module as a sensor and ESP32 as a microcontroller. On the Ubidots website, EKG signals are transmitted over the internet and shown in real time. QoS analysis is performed using the Wireshark application. Data was collected on two scenarios at intervals of 30 minutes, 1 hour, 2 hours, 5 hours, 8 hours, 12 hours, 18 hours, and 23 hours. The throughput, latency, and packet loss metrics used in this study's results cause different value variations; these are influenced by the weather, internet bandwidth, computer, and router specifications. According to testing, the tool is portable and has a 3000mAh battery, but it has the restriction that it can only be used with reliable internet and bandwidth.

State Senior High School 7 Surakarta is one of the public schools located in Surakarta City. The library activities, including member data management, book processing, and book borrowing and returning, are still conducted manually using physical logbooks. This manual process is considered inefficient and prone to errors. The purpose of this study is to develop a book borrowing system at State Senior High School 7 Surakarta that serves as a tool to assist officers in recording, loans, and returning books. This system is designed using the CodeIgniter framework to support WEB displays, programming in PHP, and using MySQL for database management. This system is created using the System Development Life Cycle (SDLC) method with a waterfall model that includes the stages of analysis, design, implementation, testing, and maintenance. System testing was conducted using Black-Box Testing and the System Usability Scale (SUS). The Black-Box Testing results showed that all features and functions operated correctly. The SUS evaluation produced a score of 75.68%, indicating that users generally agreed with the implementation of the system, which falls under the "acceptable" classification.

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.

This study focuses on developing a web-based Research and Community Service Information System (SIPPMAS) for Politeknik Takumi Bekasi, utilizing the Waterfall methodology. The aim is to create an integrated platform that streamlines the management of research and community service activities, from proposal submission and budget allocation to project execution and final reporting. The Waterfall method was chosen for its structured, sequential approach, ensuring a systematic development process through distinct phases: requirements analysis, design, implementation, testing, and maintenance. This approach is expected to enhance data accuracy, improve operational efficiency, and provide real-time project monitoring, ultimately facilitating better collaboration among stakeholders and increasing the overall impact of research and community service initiatives at Politeknik Takumi Bekasi. The system is designed to address current manual administrative challenges, offering a centralized and accessible solution for all users.

The digital transformation in education has encouraged the adoption of computer-based tests (CBT) using video content, which demands stable and efficient network performance. This study aims to evaluate the performance of two queue management algorithms, namely Random Early Detection (RED) and Per Connection Queue (PCQ), in maintaining the quality of service (QoS) of school networks during online video-based examinations. A case study approach was applied using a real network topology in a school environment, and QoS parameters such as throughput, delay, packet loss, and jitter were measured. The implementation was conducted using a MikroTik RB450Gx4 router configured with simple queue settings for each algorithm. The results show that PCQ provides more consistent performance under high user loads, achieving an average throughput of 56,482 bps and lower delay compared to RED. Conversely, RED performs better in scenarios with a small number of users. The study recommends using PCQ for networks with dynamic and dense user environments, while RED is more suitable for low-traffic conditions where latency stability is crucial. These findings offer practical guidance for managing bandwidth and improving the quality of CBT delivery in educational settings.

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.

Information systems can be technically defined as a set of interconnected components designed to support decision-making and drive organizational operations. PT Asuransi Takaful Keluarga utilizes an information system in the form of the Takaful eCard mobile application, which facilitates registration and access to outpatient and inpatient insurance services at partner hospitals. Over time, several usability issues have emerged related to the application's user interface (UI) and user experience (UX). To evaluate user satisfaction and comfort levels, usability testing was conducted using the Heuristic Evaluation method. This method assesses UI design flaws based on 10 established usability principles. The evaluation revealed design issues in (H2) question Q6, (H3) question Q7, and (H10) questions Q27 and Q28. These issues are primarily related to the absence of new feature additions, ineffective message dialog boxes, and the lack of a user guidance module. The findings highlight the need for UI/UX improvements to enhance user interaction with the Takaful eCard application.

Kemajuan teknologi telah menciptakan peluang baru dalam bidang pendidikan, terutama bagi anak usia dini. Penelitian ini mengembangkan sebuah game edukatif berbasis Android yang ditujukan untuk anak berusia 4 hingga 6 tahun, dengan materi pengenalan huruf, angka, buah, dan hewan. Pengembangan aplikasi ini menggunakan model Waterfall yang mencakup analisis kebutuhan, perancangan, implementasi, pengujian, serta pemeliharaan. Game dirancang menggunakan Flutter dan bahasa Dart untuk menghasilkan tampilan yang interaktif dan responsif, serta dilengkapi dengan fitur audio-visual yang menarik. Berdasarkan hasil pengujian Blackbox dan User Acceptance Testing (UAT), sebanyak 87% anak menunjukkan ketertarikan terhadap game ini, dan 82% mampu mengingat materi yang disampaikan. Para guru juga memberikan respon positif, menilai permainan ini efektif sebagai media pembelajaran. Meski demikian, masih diperlukan penambahan variasi soal serta peningkatan kinerja aplikasi guna meningkatkan pengalaman pengguna secara keseluruhan.

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%.