INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi
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Analysis and Design of Customer Relationship Management System on the SMEs Using Iconix Process
Full text linkBackground: Integrating Customer Relationship Management (CRM) systems is crucial for small and medium enterprises (SMEs) to enhance customer relations and profitability. Many SMEs in Indonesia, including Go-Sumber Plastik, still need to fully utilize CRM systems, which are essential for managing customer data, improving satisfaction, and retaining customers. Objective: The purpose of this research is to analyze and design a web-based CRM system for Go-Sumber Plastik using the Iconix Process methodology to enhance user interaction and overall system effectiveness. Methods: The study employed the Iconix Process methodology, which includes a use case, robustness, sequence diagrams, a GUI prototype, and a test plan. The design was tested using Maze to measure user interaction efficiency and satisfaction. Results: The research revealed significant challenges in user understanding of the CRM system, particularly in managing activities and adding customer information. Tasks such as reporting and logging in had good user performance. The overall user interaction score was 81.1, indicating moderate effectiveness of the initial design. Conclusion: The results underscore the necessity for a more intuitive and streamlined CRM system interface for Go-Sumber Plastik. Implementing an effective CRM system can improve SMEs\u27 competitiveness and profitability by systematically enhancing communication, managing customer data, and boosting business performance. Future research should focus on refining the user interface to reduce error rates and improve task completion efficiency. Enhanced visibility and user guidance are recommended to optimize system usability and customer satisfaction.Go-Sumber Plastik merupakan salah satu UKM yang menyediakan plastik wrap atau kemasan untuk pelanggan. Salah satu bagian terpenting dari UKM ini adalah menjual dan mempertahankan pelanggan. Proses penjualan pada UKM ini melalui aplikasi chat atau dengan mengunjungi toko secara langsung. Selain itu, belum adanya sistem informasi yang terintegrasi menyebabkan proses bisnis di dalam perusahaan relatif lambat. Salah satu inovasi yang dapat digunakan UKM adalah sistem informasi yang menerapkan strategi Customer Relationship Management (CRM) untuk mempertahankan pelanggan. Pada penelitian ini dilakukan analisis dan perancangan sistem informasi CRM berbasis website dengan menggunakan metode Iconix Process. Proses Iconix digunakan untuk pendekatan yang lebih efisien dan berfokus pada model. Proses Iconix memanfaatkan UML seperti Sequence, Robustness, Use Cases, Domain Model, dan Class Diagram untuk menghasilkan gambaran alur kerja sistem yang jelas dan mudah dilakukan. Hasil analisis dan perancangan sistem ini diharapkan dapat menjadi dasar penelitian selanjutnya dalam membangun sistem dengan bahasa pemrograman yang sesuai. Kemudian, dapat membantu UKM meningkatkan pemasaran, mempertahankan pelanggan setia, memiliki daya saing dalam persaingan pasar UKM, dan meningkatkan keuntungan bisnis secara keseluruhan
Optimizing the Personnel Position Monitoring System Using the Global Positioning System in Hostage Release
Full text linkIn the contemporary era of globalization, maintaining public order depends on strong security measures. Addressing security challenges, particularly in hostage release scenarios, requires rapid and appropriate responses, highlighting the need for efficient personnel deployment. This research proposes an advanced solution using a GPS Tracking System which uses a sequential method by utilizing digital photos from GPS satellites to monitor the movement of individuals and objects. Specifically applied to the Sandra rescue mission, our research uses the NodeMCU ESP8266 component, which integrates GPS and Wi-Fi functions while considering wind direction. Tests performed demonstrated an impressive success rate of 98.6%, demonstrating the effectiveness of our real-time personnel positioning approach.In the contemporary era of globalization, maintaining public order depends on strong security measures. Addressing security challenges, particularly in hostage release scenarios, requires rapid and appropriate responses, highlighting the need for efficient personnel deployment. This research proposes an advanced solution using a GPS Tracking System which uses a sequential method by utilizing digital photos from GPS satellites to monitor the movement of individuals and objects. Specifically applied to the Sandra rescue mission, our research uses the NodeMCU ESP8266 component, which integrates GPS and Wi-Fi functions while considering wind direction. Tests performed demonstrated an impressive success rate of 98.6%, demonstrating the effectiveness of our real-time personnel positioning approach
Augmented Rice Plant Disease Detection with Convolutional Neural Networks
Full text linkThe recognition and classification of rice plant diseases require an accurate system to generate classification data. Types of rice diseases can be identified in several ways, one of which is leaf characterization. One method that has high accuracy in identifying plant disease types is Convolutional Neural Networks (CNN). However, the rice disease data used has unbalanced data which affects the performance of the method. Therefore, the purpose of this research was to apply data augmentation to handle unbalanced rice disease data to improve the performance of the Convolutional Neural Network (CNN) method for rice disease type detection based on leaf images. The method used in this research is the CNN method for detecting rice disease types based on leaf images. The result of this research was the CNN method with 100 epochs able to produce an accuracy of 99.7% in detecting rice diseases based on leaf images with a division of 80% training data (2438 data) and 20% testing data (608 data). The conclusion is that the CNN method with the augmentation process can be used in rice disease detection because it has very high accuracy.The recognition and classification of rice plant diseases require an accurate system to generate classification data. Types of rice diseases can be identified in several ways, one of which is leaf characterization. One method that has high accuracy in identifying plant disease types is Convolutional Neural Networks (CNN). However, the rice disease data used has unbalanced data which affects the performance of the method. Therefore, the purpose of this research was to apply data augmentation to handle unbalanced rice disease data to improve the performance of the Convolutional Neural Network (CNN) method for rice disease type detection based on leaf images. The method used in this research is the CNN method for detecting rice disease types based on leaf images. The result of this research was the CNN method with 100 epochs able to produce an accuracy of 99.7% in detecting rice diseases based on leaf images with a division of 80% training data (2438 data) and 20% testing data (608 data). The conclusion is that the CNN method with the augmentation process can be used in rice disease detection because it has very high accuracy
Sentiment Analysis of YouTube Users on Blackpink Kpop Group Using IndoBERT
Full text linkBackground: The Korean Pop (K-Pop) phenomenon has become an important part of popular culture worldwide, with Blackpink being one of the most influential groups. Analyzing sentiment toward Blackpink is urgent, given its growing popularity and wide influence among fans worldwide. In the present technological era, social media platforms such as YouTube have evolved into a space where artists and their fans may interact with each other. As a consequence, social media has become a powerful tool for assessing the emotional tone and sentiment conveyed by individuals. Objective: This research aims to explore the trend of public sentiment towards Blackpink and evaluate how well the IndoBERT model analyzes the sentiment of Indonesian texts. Methods: The objective of this study is to examine the pattern of public sentiment towards Blackpink and assess the proficiency of the IndoBERT model in analyzing the sentiment of Indonesian writings. Results: The findings demonstrated that the IndoBERT model had an exceptional level of precision, achieving a 98% accuracy rate. In addition, it obtained a f1, recall, and accuracy score of 95%. The remarkable results demonstrate the efficacy of the IndosBERT technique in evaluating the emotion of Indonesian-language literature towards Blackpink. Conclusion: This study enhances the knowledge of how fans and audiences react to K-pop material and establishes a foundation for future research and advancement. The impressive precision of the IndoBERT model showcases its capacity for sentiment analysis in Indonesian literature, making it a useful tool for future research endeavors.Fenomena Korean Pop (K-Pop) telah menjadi bagian penting dari budaya populer di seluruh dunia, dimana Blackpink menjadi salah satu kelompok yang paling berpengaruh. Analisis sentimen terhadap Blackpink penting mengingat popularitas dan pengaruh luasnya di kalangan penggemar di seluruh dunia. Penelitian ini menggunakan IndoBert, sebuah model bahasa pra-latih yang telah terbukti efektif dalam menganalisis sentimen. Meskipun banyak penelitian telah dilakukan dalam analisis sentimen, tidak ada penelitian yang secara khusus mengkaji sentimen terhadap Blackpink. Oleh karena itu, penelitian ini mengisi kesenjangan dalam literatur dengan fokus pada kelompok yang sangat populer ini. Tujuan utama studi ini adalah untuk mengeksplorasi tren sentimen publik terhadap Blackpink dan mengevaluasi seberapa baik model IndoBert menganalisis sentiment teks Indonesia. Dataset yang digunakan dalam penelitian ini diambil dari komentar pengguna dari platform media sosial YouTube pada Shut Down Music Video. Penelitian ini menunjukkan bahwa model IndoBert sangat akurat, dengan nilai akurasi 98%, f1, recall, dan skor presisi di atas 95%. Hasilnya menunjukkan bahwa metode IndoBert efektif untuk menganalisis perasaan teks bahasa Indonesia terhadap Blackpink. Dengan hasil yang mengesankan ini, penelitian ini berkontribusi untuk memahami bagaimana penggemar dan penonton bereaksi terhadap konten K-pop
Water Management Zone Mapping on Peatland in Limbung Village Sungai Raya District
Full text linkThis study focuses on mapping peatland water management zones, which have not been mapped in previous research. These water management zones serve as crucial reference points for the development and implementation of the National Peatland Ecosystem Protection and Management Plan. The research applied various methods, including soil survey, drilling, soil sampling, measuring groundwater level and canal, matching methods, and create a peat water management zone map. Based on research and map overlays, five water management zones were obtained, these zones include Zone I (F2.B1.K1.C2) covering 1.39 ha (11.58%), Zone II (F1.B1.K1.C2) covering 0.82 ha (6. 83%), Zone III (F2.B1.K1.C3) covering 1.93 ha (16.08%), Zone IV (F1.B1.K1.C3) covering 3.86 ha (32.17%) and Zone V (F1.B1.K2.C3) covering 4.00 ha (33.33%). These water management zones will be related to conservation activities to maintain the quality of soil and water on peatlands. Peatland restoration management activities in Zone I can be accomplished by canal blocking and maximum planting patterns, in Zone II by canal filling and maximum planting patterns, in Zone III by canal blocking and enrichment plants, in Zone IV by canal backfilling and maximum planting patterns, and in Zone V by canal backfilling and deep wells.This study focuses on mapping peatland water management zones, which have not been mapped in previous research. These water management zones serve as crucial reference points for the development and implementation of the National Peatland Ecosystem Protection and Management Plan. The research applied various methods, including soil survey, drilling, soil sampling, measuring groundwater level and canal, matching methods, and create a peat water management zone map. Based on research and map overlays, five water management zones were obtained, these zones include Zone I (F2.B1.K1.C2) covering 1.39 ha (11.58%), Zone II (F1.B1.K1.C2) covering 0.82 ha (6. 83%), Zone III (F2.B1.K1.C3) covering 1.93 ha (16.08%), Zone IV (F1.B1.K1.C3) covering 3.86 ha (32.17%) and Zone V (F1.B1.K2.C3) covering 4.00 ha (33.33%). These water management zones will be related to conservation activities to maintain the quality of soil and water on peatlands. Peatland restoration management activities in Zone I can be accomplished by canal blocking and maximum planting patterns, in Zone II by canal filling and maximum planting patterns, in Zone III by canal blocking and enrichment plants, in Zone IV by canal backfilling and maximum planting patterns, and in Zone V by canal backfilling and deep wells
A Prototype Design of a Vertical Axis Wind Turbine as One of the Renewable Energy Sources in Brunei
Full text linkBackground: According to the Asia Wind Energy Association, Brunei can harness the power of wind energy to meet its future demands for a reliable energy source that is both renewable and non-polluting. Objective: A preliminary study to design and manufacture wind turbines needs to be initiated earlier especially in the Brunei with has potential wind energy. Methods: This preliminary study compares several Vertical Axis Wind Turbine (VAWT) types and examines the optimal design in terms of mechanical parts for wind speed characteristics in Brunei. The project focuses on the engineering design stages to obtain a selected design that differs from other available designs. Results: The preliminary study successfully generated a small amount of electricity from the mechanical rotation of the VAWT. Conclusion: Although the preliminary study can generate a small amount of electricity, several design parameters need to be improved in further study. Proper manufacturing technologies are also needed to fabricate a better VAWT
The Empirical Study On Algorithm Optimization In Expert Systems For Diagnosing Rice Plant Diseases
Full text linkRice is one of the most important cultivated plants for human survival. The activity of cultivating rice plants becomes a livelihood for most of these residents, so the success rate of the amount of rice harvested becomes very important because they depend on how much rice can be harvested, disease diagnosis is very important for farmers, this is very important to reduce economic losses due to diseases that cause crop failure. Therefore, when dealing with rice diseases, an expert is needed to make diagnoses or solutions to rice diseases. However, an expert does not know when to come to the village, and farmers also do not understand all rice diseases. Therefore, a web-based expert system application using the forward chaining method is proposed to represent an expert to help farmers diagnose and solve diseases of rice plants with existing symptoms.Rice is one of the most important cultivated plants for human survival. The activity of cultivating rice plants becomes a livelihood for most of these residents, so the success rate of the amount of rice harvested becomes very important because they depend on how much rice can be harvested, disease diagnosis is very important for farmers, this is very important to reduce economic losses due to diseases that cause crop failure. Therefore, when dealing with rice diseases, an expert is needed to make diagnoses or solutions to rice diseases. However, an expert does not know when to come to the village, and farmers also do not understand all rice diseases. Therefore, a web-based expert system application using the forward chaining method is proposed to represent an expert to help farmers diagnose and solve diseases of rice plants with existing symptoms
Electronic Driving License-based for Secure Sharing Vehicles in Wireless IoT Networks
Full text linkIn this paper we study electronic driving license (EDL) for secure sharing of vehicles in wireless IoT networks. The process of authentication and data transmission to the server is a very challenging problem to solve. To solve this problem, we propose the use of a wireless IoT network to overcome the transmission speed from the vehicle to the server, and the use of EDL for the driver authentication process. Two devices are installed on the vehicle side and on the server side while the wireless IoT network is used to make data transmission efficient. EDL is used to authenticate drivers who rent vehicles. When the device authentication process on the vehicle will send geographic information obtained through the global positioning system (GPS) to the server. The server will verify the user, if it matches then the server will send a command to the vehicle to be used. To run the considered system, we proposed Algorithm 1 and 2 to run the vehicle device and server, respectively. Experiment result shows the proposed system has maximum accuracy in 95.5%, packet delivery ratio 90%, delay propagation less than 60 seconds. Thus, the security of the shared vehicle will be increases.In this paper we study electronic driving license (EDL) for secure sharing of vehicles in wireless IoT networks. The process of authentication and data transmission to the server is a very challenging problem to solve. To solve this problem, we propose the use of a wireless IoT network to overcome the transmission speed from the vehicle to the server, and the use of EDL for the driver authentication process. Two devices are installed on the vehicle side and on the server side while the wireless IoT network is used to make data transmission efficient. EDL is used to authenticate drivers who rent vehicles. When the device authentication process on the vehicle will send geographic information obtained through the global positioning system (GPS) to the server. The server will verify the user, if it matches then the server will send a command to the vehicle to be used. To run the considered system, we proposed Algorithm 1 and 2 to run the vehicle device and server, respectively. Experiment result shows the proposed system has maximum accuracy in 95.5%, packet delivery ratio 90%, delay propagation less than 60 seconds. Thus, the security of the shared vehicle will be increases
Analyzing the Quality of Academic Information Systems on System Success
Full text linkSince the needs for academic management are always changing, the creation of academic information systems must focus on user benefits and satisfaction in order to gauge how successful academic management systems are. This research uses the Delone and McLean IS Success Model which is known as one of the system success models, so the aims to ascertain the effects of system, information, and service quality, as well as usage rate, on benefits and user satisfaction SIAKAD system. Respondents were determined using the Slovin formula and taken using proportionate stratified random sampling techniques as many as 100 people. Descriptive analysis was carried out to explain respondents\u27 perceptions and evaluate the success of the system using Three levels of communication were used to measure the success of the system: technical, semantic, and effectiveness levels. The Delone and Mclean IS Success Model\u27s variable relationships were investigated using SEM-PLS analysis. Hypothesis testing results indicate that User Satisfaction is significantly impacted by Information; System; and Service Quality, then Information Quality also significantly affects Usage; and Net Benefits are significantly impacted by User Usage and Satisfaction; however, neither System Quality nor Service Quality significantly affects Use or Use on User Satisfaction.Since the needs for academic management are always changing, the creation of academic information systems must focus on user benefits and satisfaction in order to gauge how successful academic management systems are. This research uses the Delone and McLean IS Success Model which is known as one of the system success models, so the aims to ascertain the effects of system, information, and service quality, as well as usage rate, on benefits and user satisfaction SIAKAD system. Respondents were determined using the Slovin formula and taken using proportionate stratified random sampling techniques as many as 100 people. Descriptive analysis was carried out to explain respondents\u27 perceptions and evaluate the success of the system using Three levels of communication were used to measure the success of the system: technical, semantic, and effectiveness levels. The Delone and Mclean IS Success Model\u27s variable relationships were investigated using SEM-PLS analysis. Hypothesis testing results indicate that User Satisfaction is significantly impacted by Information; System; and Service Quality, then Information Quality also significantly affects Usage; and Net Benefits are significantly impacted by User Usage and Satisfaction; however, neither System Quality nor Service Quality significantly affects Use or Use on User Satisfaction
Optimization of Machine Learning-Based Automatic Target Detection and Locking System on Robots
Full text linkBackground: In recent years, the world of robotics has made significant progress in improving the operational capabilities of robots through target detection and locking systems. These systems play a crucial role in improving the efficiency and effectiveness of critical applications such as defense, security, and industrial automation. However, the main challenge faced is the limitations of the existing system in adapting to unstable environmental conditions and dynamic changes in targets. Objective: This research aims to overcome these challenges by developing a more adaptive and responsive target detection and locking system by integrating two leading machine learning technologies: Convolutional Neural Networks (CNN) for target detection and Long Short-Term Memory (LSTM) for target tracking. Methods: This study uses a quantitative approach to evaluate the effectiveness of the integration of CNNs and LSTMs in target detection and locking systems. Results: The results of the study showed a detection accuracy rate of 95% and a locking accuracy of 90%. The system is proven to be able to adapt to changing operational conditions in real-time and provide consistent performance in a variety of complex and dynamic scenarios. Conclusion: The conclusion of this study is that the integration of CNN and LSTM technologies in target detection and locking systems in robots significantly improves the performance and efficiency of the system, enabling a wider and more complex application