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Journal of Informatics Management and Information Technology
Published by Forum Kerjasama Pendidikan TInggi
ISSN : -     EISSN : 27744744     DOI : -
Core Subject : Science,
Computer Science & IT
Journal of Informatics Management and Information Technology, memiliki kajian pada bidang: 1. Manajemen Informatika, 2. Sistem Informasi, dan 3. Teknologi Informasi
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 8 Documents
 1 
Search results for , issue "Vol. 5 No. 2 (2025): April 2025" : 8 Documents clear
Perbandingan Metode Simple Additive Weighting (SAW) Dan Weighted Product (WP) Dalam Pemilihan Aplikasi Belanja Sayur Online Nisrina Nur Puspanegara; Dwi Asih Haryanti
Journal of Informatics Management and Information Technology Vol. 5 No. 2 (2025): April 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/jimat.v5i2.471

Abstract

The selection of the right online vegetable shopping application is becoming increasingly important as public awareness of a healthy lifestyle grows. The aim of this study is to develop a Decision Support System (DSS) that can help consumers choose the best online vegetable shopping application. This research contributes to the development of a decision support system for selecting an online vegetable shopping application by comparing the performance of two multi-criteria methods: Simple Additive Weighting (SAW) and Weighted Product (WP). A case study was conducted on three applications HappyFresh, Segari, and Sayurbox considering criteria such as price, product quality, application convenience, and promotions. This research is quantitative in nature, aiming to test predetermined hypotheses. The data sources used in this study include both primary and secondary data. The sampling technique applied was purposive random sampling, involving 100 respondents. The selected respondents were users of HappyFresh, Sayurbox, and Segari applications residing in the Jabodetabek area. The analysis results show that both methods produced consistent rankings, with the HappyFresh application consistently ranking first. This indicates that HappyFresh has the best performance in meeting user expectations based on the established criteria. Based on calculations using the SAW and WP methods, HappyFresh obtained the highest score in both methods, with a score of 1 using SAW and 0.3341 using WP. This suggests that HappyFresh is the most recommended application among HappyFresh, Sayurbox, and Segari..
Pemilihan Fitur Menggunakan Chi-Square Untuk Deteksi Serangan Pada Jaringan Internet of Medical Things Menggunakan Random Forest Permatasari, Alfia Tiara; Rusdiyanto; M Agus Syamsul Arifin
Journal of Informatics Management and Information Technology Vol. 5 No. 2 (2025): April 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/jimat.v5i2.478

Abstract

This research discusses the security of the Internet of Medical Things (IoMT) network using the CICIoMT2024 dataset to analyze and detect cyber attacks through the application of Machine Learning (ML) methods. This research uses the Chi-Square feature selection technique to identify important features, and uses the Random Forest algorithm for the data classification process. The utilization of Chi-Square features, especially in the analysis of network traffic of IoT devices, has not been widely explored, so this research makes a new contribution to the field. The result of the Chi-Square feature selection are used to train Machine Learning models to classify data between normal traffic and traffic containing attacks. In the experiments conducted, the Random Forest algorithm showed excellent performance by achieving up to 100% accuracy, as well as high precision, recall, F1-Score values. These results show that Random Forest is able to handle the complexity of IoMT data effectively. Thus, it can be concluded that the Random Forest algorithm is very relevant and effective to use in IoMT network security research.
Pengembangan Sistem Informasi Pengarsipan File Menggunakan Metode R&D Mauludy, Muh Wildan; Fathahillah
Journal of Informatics Management and Information Technology Vol. 5 No. 2 (2025): April 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/jimat.v5i2.484

Abstract

This research adopts the Research and Development method technique or better known as R&D, which is developing a product in the form of a system specifically designed to archive files in the form of documents at PT. THE AGE OF SELF-RELIANCE. The approach used is the ADDIE (Analyze, Design, Develop, Implement, and Evaluate) model. The subject of the study was an employee who used a system with samples taken from 2 employees through a simple random sampling technique, the limitations of the employees made the samples taken few. Data was collected using questionnaires and in-depth interviews, then analyzed based on ISO 25010 criteria which included eight characteristics: functionality, reliability, performance efficiency, portability, maintainability, usability, compatibility, and security. The test results show that the characteristics of functional suitability reach 100%, reliability 97%, performance efficiency 94%, portability 100%, usability 90%, maintainability 100%, security with alert level 0, and compatibility 100%. The conclusion of the study is that this system can be used effectively in the archiving of documents related to corporate archives and has met all the characteristics of ISO 25010. It is recommended that companies conduct periodic evaluations and updates of the system to ensure optimal performance and better data security.
Perbandingan Metodologi SDLC Waterfall dan Agile Dalam Rencana Pengembangan Sistem Informasi Kepatuhan Burhani, Irfan; Juwari, Juwari; Soderi, Ahmad; Diantoro, Karno
Journal of Informatics Management and Information Technology Vol. 5 No. 2 (2025): April 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/jimat.v5i2.489

Abstract

The development of compliance information systems plays a strategic role in the banking industry, particularly in ensuring that every operational activity adheres to continuously evolving regulations. Bank Syariah Indonesia faces challenges in determining the most effective and efficient system development methodology to be applied in developing compliance information systems. This study aims to compare two system development methodologies: Waterfall and Agile. A qualitative approach was used, with data collected through interviews and questionnaires distributed to 60 respondents, determined using the Slovin formula with a 2% margin of error. The results show that 83% of respondents consider the Agile method to be more flexible in responding to regulatory changes due to its iterative nature, ability to adjust backlogs, and open team communication. On the other hand, Waterfall is still considered relevant for projects that require detailed documentation and a strict structure. The main weakness of Waterfall lies in its limited ability to adapt to changes that arise at the end of the development cycle. This study recommends a Hybrid approach that combines the flexibility of Agile and the structured nature of Waterfall, to ensure the development of compliance information systems that are adaptive, well-documented, and aligned with complex and dynamic regulatory requirements.
Forecasting Penjualan Bahan Bangunan Menggunakan Metode Least Square Berbasis Website Menggunakan Framework Codeigniter Febriyan Idil Adha; Asep Toyib; Armanto
Journal of Informatics Management and Information Technology Vol. 5 No. 2 (2025): April 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/jimat.v5i2.491

Abstract

The availability of stock information is crucial at Toko Jogja Bangunan considering the size and price of goods that are quite large and expensive. The problem that is often faced is running out of stock of certain items due to the lack of adequate sales and stock records. This results in decreased profits and high storage costs for unsold goods. This research aims to build a stock forecasting system using the Least Square method implemented through a Python-based application. The forecasting results are displayed in the form of tables and graphs, then validated manually based on previous sales data. The Least Square method was chosen because it is able to analyze random patterns, trends, seasonality, and cyclicality in sales data, and produce predictions with a low error rate. This forecasting system is implemented using the CodeIgniter framework to produce a web-based information system that is easily accessible and can present building material stock prediction reports accurately and quickly. With this system, it is hoped that Toko Jogja Bangunan can overcome shortcomings in stock management, improve operational efficiency, and support better decision making.
Implementasi Penyiraman Tanaman Otomatis dengan Kontrol Jarak Jauh Menggunakan Aplikasi Blynk Taufiqurrahman, Taufiqurrahman; Diantoro, Karno
Journal of Informatics Management and Information Technology Vol. 5 No. 2 (2025): April 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/jimat.v5i2.492

Abstract

Effective and efficient plant watering remains a major challenge in the agricultural sector, especially for farmers with limited time and resources. This study aims to develop an automatic plant watering system based on the Internet of Things (IoT), which can be remotely controlled using the Blynk application. The system utilizes an ESP32 microcontroller as the central controller, a soil moisture sensor to indicate water requirements, and an RTC DS3231 module to ensure scheduled watering continues even if the internet connection is interrupted. The research methodology follows the System Development Life Cycle (SDLC) with the Waterfall model, consisting of requirement analysis, system design, implementation, testing, and maintenance. Test results show that the system is capable of detecting soil moisture in real-time and controlling the water pump based on detected conditions. The Blynk application allows users to monitor soil status and manage watering manually or automatically. When the internet connection is lost, the RTC DS3231 module continues to execute the scheduled watering as configured. The implementation of this system improves water usage efficiency by up to 30% compared to manual methods while providing flexibility and ease in plant management. This research contributes to the application of IoT technology in agriculture, supports more sustainable resource management, and introduces a smart irrigation system that adapts to network conditions and plant needs.
Prediksi Padi Menggunakan Algoritma Long Short Term Memory Adhany, Putri Cheria; Cindi Wulandari; Bunga Intan; Budi Santoso
Journal of Informatics Management and Information Technology Vol. 5 No. 2 (2025): April 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/jimat.v5i2.496

Abstract

Rice is one of the main agricultural commodities in Indonesia, including in Lubuklinggau City, which is a rice-producing area in South Sumatra Province. However, rice production fluctuates every month due to various factors such as planting seasons, land conversion, weather, and pest attacks. This instability can affect food availability and farmer welfare. Therefore, rice production forecasting is important in supporting better decision-making in the agricultural sector. This study uses monthly rice production data from January 2019 to November 2024 obtained from the Lubuklinggau City Agriculture Service. The method used is Long Short-Term Memory (LSTM), which is one of the artificial neural network techniques based on time series data. The optimal parameters used in the model are the number of neurons in the hidden layer of 35, a batch size of 12, and a maximum of 50 epochs. The results showed that the model with optimal parameters produced a Mean Absolute Percentage Error (MAPE) value of 4.44%, which is included in the very good category. These results indicate that the LSTM method can be used effectively to predict rice production in Lubuklinggau City with a high level of accuracy.
Metode Hybrid Dalam Pengelompokkan Kemampuan Calistung Siswa Berbasis Machine Learning Salsabila, Amanda; Andri Anto Tri Susilo; Nelly Khairani Daulay
Journal of Informatics Management and Information Technology Vol. 5 No. 2 (2025): April 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/jimat.v5i2.500

Abstract

Students reading, writing, and arithmetic abilities (reading, writing, and arithmetic) are an important foundation in the academic development of elementary school students. This study aims to group students' reading, writing, and arithmetic abilities using a hybrid method based on machine learning, with grade data from two Elementary Schools in Lubuklinggau City. The method applied combines the K-Means Clustering algorithm for initial grouping and K-Nearest Neighbors (KNN) for classification. The analysis process includes data preprocessing, application of K-Means, cluster validation using Silhouette Score, and classification with KNN to ensure accuracy. As a result, K-Means successfully grouped students into three clusters: Middle (0), Low (1), and High (2). The KNN model with k = 3 which has the highest accuracy of 95% provides very good accuracy in testing the K-Nearest Neighbors (KNN) classification model with an accuracy of 97%, with very good precision, recall, and F1-score values for all clusters. These findings indicate that this hybrid approach is effective in classifying students' reading, writing and arithmetic abilities, which has implications for the development of more targeted learning strategies based on the characteristics of each group of students.

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