INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi <div style="background: #6BB9F0; border-bottom: none; border-left: 6px solid #2574A9; border-right: none; border-top: none; box-shadow: rgba(0, 0, 0, 0.5) 0px 5px 8px -6px; padding: 0.875rem 1.5rem 0.875rem 0.875rem !important; text-align: justify;"><span style="color: #000000;">INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi is a scholarly periodical. INTENSIF publishes research papers, technical papers, conceptual papers, and case study reports. This Journal discusses the latest trends in the science of computer science, especially information systems. These fields include Information Systems, Software Engineering, Data Mining, Data Warehouses, Computer Networks, Artificial Intelligence, e-Business, e-Government, Big Data, Application Development, Geographic Information Systems, Information Retrieval, Information Technology Infrastructure, Systems Knowledge Management, and Company Architecture, IoT, and other relevant with computer science and Information system</span></div> <p>&nbsp;</p> Universitas Nusantara PGRI Kediri en-US INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi 2580-409X <p>Authors who publish with this journal agree to the following terms: <br>1. Copyright on any article is retained by the author(s).<br>2. The author grants the journal, right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgment of the work’s authorship and initial publication in this journal. <br>3. Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal’s published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this journal.<br>4. Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work.<br>5. The article and any associated published material is distributed under the&nbsp;<a href="" rel="license">Creative Commons Attribution-ShareAlike 4.0 International License</a></p> The Empirical Study On Algorithm Optimization In Expert Systems For Diagnosing Rice Plant Diseases <p>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.</p> Ahmad Habib Muhamat Sunan Roenardi Koesdijarto Sajiyo Sajiyo Elsen Ronando Copyright (c) 2024 Ahmad Habib, Muhamat Sunan, Roenardi Koesdijarto, Sajiyo Sajiyo, Elsen Ronando 2024-02-01 2024-02-01 8 1 1 12 10.29407/intensif.v8i1.20493 Electronic Driving License-based for Secure Sharing Vehicles in Wireless IoT Networks <p>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.</p> Aad Hariyadi Amalia Amalia Rieke Adriati Wijayanti Amalia Eka Rakhmania Nurul Hidayati Hudiono Hudiono Copyright (c) 2024 Aad Hariyadi, Amalia Amalia, Rieke Adriati Wijayanti, Amalia Eka Rakhmania, Nurul Hidayati, Hudiono Hudiono 2024-02-01 2024-02-01 8 1 13 26 10.29407/intensif.v8i1.20957 Augmented Rice Plant Disease Detection with Convolutional Neural Networks <p>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.</p> Hairani Hairani Triyanna Widiyaningtyas Copyright (c) 2024 Hairani Hairani, Triyanna Widiyaningtyas 2024-02-01 2024-02-01 8 1 27 39 10.29407/intensif.v8i1.21168 Evaluation of Governance in Information Systems Security to Minimize Information Technology Risks <p>Information system security within XYZ University constitutes a vital component of its IT framework, exerting significant influence over security levels across all facets of the information systems. Among the numerous implemented information system services at the university, a considerable portion lacks active security measures within operational systems. In pursuit of achieving uniform governance, this study adopts the most recent COBIT 2019 framework. The primary objective of this research is to evaluate the degree to which current information system security management aligns with the process achievement values stipulated in the COBIT 2019 standard. This evaluation entails the calculation of maturity level values that gauge performance levels in managing information system security. Findings from the COBIT 2019 Design assessment conducted at XYZ University's LTIK reveal that individuals scoring above 80 or those requiring Capability Level 4 include APO12 and BAI10. Moreover, the calculation outcomes for each subdomain reveal the presence of 2 subdomains at Level 4, 4 subdomains at Level 3, 15 subdomains at Level 2, and 19 subdomains at Level 1. The identification outcomes underscore the existence of gaps within each domain. Particularly, the APO12 and BAI10 domains exhibit a gap spanning 2 levels.</p> Yulia Darmi Sandhy Fernandez M Yoka Fathoni Sena Wijayanto Copyright (c) 2024 Yulia Darmi, Sandhy Fernandez, M Yoka Fathoni, Sena Wijayanto 2024-02-01 2024-02-01 8 1 40 51 10.29407/intensif.v8i1.21221 Smart Drip Irrigation System Based on IoT Using Fuzzy Logic <p>The absence of a water drip rate control system in drip irrigation systems has impacted water use efficiency and normalization of soil moisture. Therefore, this research aims to develop an intelligent system using the fuzzy logic method to control the rate of water droplets in a drip irrigation system and maintain soil moisture in normal conditions. The DHT22 sensor is used to obtain temperature and humidity values, which are then used as input data and processed by the ESP32 microcontroller, which includes a fuzzy system. The Internet of Things (IoT) is also used to send data from the microcontroller to the Thingspek web server. The Blynk application is used to make it easier to monitor temperature, humidity, and water droplet rate values. The results of this research show that the temperature accuracy values produced using the MSE evaluation were 6.66667 and RMSE were 2.58199, while for temperature, the values for MSE were 0.128333 and RMSE were 0.358236. The average value of soil moisture produced in the planting medium is 44.46%; this value is within normal conditions for chili plants, where normal soil moisture conditions range between 40% - 60%</p> Miftahul Walid Muhammad Ashar Muhammad Hasan Wahyudi Copyright (c) 2024 Miftahul Walid, Muhammad Ashar, Muhammad Hasan Wahyudi 2024-02-01 2024-02-01 8 1 52 67 10.29407/intensif.v8i1.21351 Water Management Zone Mapping on Peatland in Limbung Village Sungai Raya District <p>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.</p> Qishtamy Wahyu Alyaminy Rossie Wiedya Nusantara Ari Krisnohadi Copyright (c) 2024 Qishtamy Wahyu Alyaminy, Rossie Wiedya Nusantara, Ari Krisnohadi 2024-02-01 2024-02-01 8 1 68 90 10.29407/intensif.v8i1.21357 Optimizing the Personnel Position Monitoring System Using the Global Positioning System in Hostage Release <p>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.</p> Dodo Irmanto Sujito Sujito Aripriharta Aripriharta Dekki Widiatmoko Kasiyanto Kasiyanto Saodah Omar Copyright (c) 2024 Dodo Irmanto, Sujito Sujito, Aripriharta Aripriharta, Dekki Widiatmoko, Kasiyanto Kasiyanto, Saodah Omar 2024-02-10 2024-02-10 8 1 91 107 10.29407/intensif.v8i1.21665 Unveiling Insights: A Knowledge Discovery Approach to Comparing Topic Modeling Techniques in Digital Health Research <p>This paper introduces a knowledge discovery approach focused on comparing topic modeling techniques within the realm of digital health research. Knowledge discovery has been applied in massive data repositories (databases) and also in various field studies, which use these techniques for finding patterns in the data, determining which models and parameters might be suitable, and looking for patterns of interest in a specific representational. Unfortunately, the investigation delves into the utilization of Latent Dirichlet Allocation (LDA) and Pachinko Allocation Models (PAM) as generative probabilistic models in knowledge discovery, which is still limited. The study's findings position PAM as the superior technique, showcasing the greatest number of distinctive tokens per topic and the fastest processing time. Notably, PAM identifies 87 unique tokens across 10 topics, surpassing LDA Gensim's identification of only 27 unique tokens. Furthermore, PAM demonstrates remarkable efficiency by swiftly processing 404 documents within an incredibly short span of 0.000118970870 seconds, in contrast to LDA Gensim's considerably longer processing time of 0.368770837783 seconds. Ultimately, PAM emerges as the optimum method for digital health research's topic modeling, boasting unmatched efficiency in analyzing extensive digital health text data.</p> Siti Rohajawati Puji Rahayu Afny Tazkiyatul Misky Khansha Nafi Rasyidatus Sholehah Normala Rahim R.R. Hutanti Setyodewi Copyright (c) 2024 Siti Rohajawati, Puji Rahayu, Afny Tazkiyatul Misky, Khansha Nafi Rasyidatus Sholehah, Normala Rahim, R.R. Hutanti Setyodewi 2024-02-10 2024-02-10 8 1 108 121 10.29407/intensif.v8i1.22058 Comparative Analysis of Transformer-Based Method In A Question Answering System for Campus Orientation Guides <p>The campus introduction process is a stage where new students acquire information about the campus through a series of activities and interactions with existing students. However, the delivery of campus introduction information is still limited to conventional methods, such as using guidebooks. This limitation can result in students having a limited understanding of the information needed during their academic period. The one of solution for this case is to implement a deep learning system with knowledge-based foundations. This research aims to develop a Question Answering System (QAS) as a campus introduction guide by comparing two transformer methods, namely the RoBERTa and IndoBERT architectures. The dataset used is processed in the SQuAD format in the Indonesian language. The collected SQuAD dataset in the Indonesian language consists of 5046 annotated data. The result shows that IndoBERT outperforms RoBERTa with EM and F1-Score values of 81.17 and 91.32, respectively, surpassing RoBERTa with EM and F1-Score values of 79.53 and 90.18.</p> Fedryanto Dartiko Mochammad Yusa Aan Erlansari Shaikh Ameer Basha Copyright (c) 2024 Fedryanto Dartiko, Mochammad Yusa, Aan Erlansari, Shaikh Ameer Basha 2024-02-10 2024-02-10 8 1 122 139 10.29407/intensif.v8i1.21971 Analyzing the Quality of Academic Information Systems on System Success <p>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' 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's 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.</p> Sayyidatul Abqoriyyah Melgis Reni Aryani Dewi Lestari Mohamed Naeem Antharathara Abdulnazar Copyright (c) 2024 Sayyidatul Abqoriyyah Melgis, Reni Aryani, Dewi Lestari, Mohamed Naeem Antharathara Abdulnazar 2024-02-10 2024-02-10 8 1 140 161 10.29407/intensif.v8i1.21512