cover
Contact Name
Sucipto
Contact Email
sucipto@unpkediri.ac.id
Phone
+6285711111864
Journal Mail Official
intensif@unpkediri.ac.id
Editorial Address
Kampus II Universitas Nusantara PGRI Kediri Prodi Sistem Informasi Jl. Mojoroto Gg.I No.6 Mojoroto Kediri
Location
Kota kediri,
Jawa timur
INDONESIA
INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi
ISSN : 2580409X     EISSN : 25496824     DOI : https://doi.org/10.29407/intensif
Core Subject : Science,
INTENSIF Journal is a publication container for research in various fields related to information systems. These fields includeInformation System, Software Engineering, Data Mining, Data Warehouse, Computer Networking, Artificial Intelligence, e-Bussiness, e-Government, Big Data, Application Development, Geograpic Information System, Information Retrieval, Information Technology Infrastructure, Knowledge Management System, Enterprise Architecture.Published periodically in February and August.
Arjuna Subject : -
Articles 168 Documents
Analysis and Design of Customer Relationship Management System on the SMEs Using Iconix Process Fitri, Anindo Saka; Wati, Seftin Fitri Ana; Najaf, Abdul Rezha Efrat; Kartika, Dhian Satria Yudha; Widodo, Suryo; Nabila, Achmad Wildan
INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi Vol 8 No 2 (2024): August 2024
Publisher : Universitas Nusantara PGRI Kediri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29407/intensif.v8i2.21043

Abstract

Background: 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' 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.
Augmented Rice Plant Disease Detection with Convolutional Neural Networks Hairani, Hairani; Widiyaningtyas, Triyanna
INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi Vol 8 No 1 (2024): February 2024
Publisher : Universitas Nusantara PGRI Kediri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29407/intensif.v8i1.21168

Abstract

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.
Evaluation of Governance in Information Systems Security to Minimize Information Technology Risks Darmi, Yulia; Fernandez, Sandhy; Fathoni, M Yoka; Wijayanto, Sena
INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi Vol 8 No 1 (2024): February 2024
Publisher : Universitas Nusantara PGRI Kediri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29407/intensif.v8i1.21221

Abstract

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.
Smart Drip Irrigation System Based on IoT Using Fuzzy Logic Walid, Miftahul; Ashar, Muhammad; Wahyudi, Muhammad Hasan
INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi Vol 8 No 1 (2024): February 2024
Publisher : Universitas Nusantara PGRI Kediri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29407/intensif.v8i1.21351

Abstract

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%
Water Management Zone Mapping on Peatland in Limbung Village Sungai Raya District Alyaminy, Qishtamy Wahyu; Nusantara, Rossie Wiedya; Krisnohadi, Ari
INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi Vol 8 No 1 (2024): February 2024
Publisher : Universitas Nusantara PGRI Kediri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29407/intensif.v8i1.21357

Abstract

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.
Analyzing the Quality of Academic Information Systems on System Success Melgis, Sayyidatul Abqoriyyah; Aryani, Reni; Lestari, Dewi; Abdulnazar, Mohamed Naeem Antharathara
INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi Vol 8 No 1 (2024): February 2024
Publisher : Universitas Nusantara PGRI Kediri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29407/intensif.v8i1.21512

Abstract

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.
Recommendation System for Determining the Best Banner Supplier Using Profile Matching and TOPSIS Methods Vitianingsih, Anik Vega; Firmansyah, Deden; Maukar, Anastasia Lidya; Kacung, Slamet; Zangana, Hewa Majeed
INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi Vol 8 No 2 (2024): August 2024
Publisher : Universitas Nusantara PGRI Kediri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29407/intensif.v8i2.21635

Abstract

Background: Choosing a banner supplier is a significant challenge for digital printing companies due to the various advantages offered by each supplier, often leading to selections based on subjective aspects such as price and quality. Objective: This research aims to develop a system that determines the best banner supplier to minimize production inefficiencies and maximize profits by comparing two calculation methods, Profile Matching and TOPSIS. Methods: A quantitative study was conducted using transaction data from the last six months. The parameter criteria used in this system include price, quality, delivery, availability, and payment terms. The study compares the effectiveness of Profile Matching and TOPSIS methods in identifying the best supplier. Results: The study results show that the TOPSIS method is superior, yielding 100% accuracy, 84% recall, and a 92% F1-score, outperforming the Profile Matching method. This demonstrates that the correct method and algorithm effectively provide the best alternative recommendations. Conclusion: The results indicate that using the TOPSIS method leads to more accurate and objective decisions based on predetermined criteria. The findings suggest that further research should focus on refining these methods to enhance decision-making in supplier selection.
Optimizing the Personnel Position Monitoring System Using the Global Positioning System in Hostage Release Irmanto, Dodo; Sujito, Sujito; Aripriharta, Aripriharta; Widiatmoko, Dekki; Kasiyanto, Kasiyanto; Omar, Saodah
INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi Vol 8 No 1 (2024): February 2024
Publisher : Universitas Nusantara PGRI Kediri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29407/intensif.v8i1.21665

Abstract

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.
Optimization of Machine Learning-Based Automatic Target Detection and Locking System on Robots Syafaat, Mokhammad; Sendari, Siti; Zaeni, Ilham Ari Elbaith; Setumin, Samsul
INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi Vol 8 No 2 (2024): August 2024
Publisher : Universitas Nusantara PGRI Kediri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29407/intensif.v8i2.21688

Abstract

Background: 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.
Comparative Analysis of Transformer-Based Method In A Question Answering System for Campus Orientation Guides Dartiko, Fedryanto; Yusa, Mochammad; Erlansari, Aan; Basha, Shaikh Ameer
INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi Vol 8 No 1 (2024): February 2024
Publisher : Universitas Nusantara PGRI Kediri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29407/intensif.v8i1.21971

Abstract

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.