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J-Intech (Journal of Information and Technology)
Published by Sekolah Tinggi Informatika dan Komputer Indonesia Malang
ISSN : 23031425     EISSN : 2580720X     DOI : https://doi.org/10.32664/j-intech
Core Subject : Science, Engineering,
Computer Science & IT Decision Sciences, Operations Research & Management Engineering Library & Information Science
J-INTECH merupakan jurnal yang diterbitkan oleh Lembaga Penelitian & Pengabdian kepada Masyarakat (LPPM), Sekolah Tinggi Informatika dan Komputer Indonesia Malang. Ruang lingkup jurnal ini pada bidang Teknik Informatika, Sistem Informatika, dan Manajemen Informatika. Tujuannya guna mengakomodasi kebutuhan akan perkembangan Teknologi Informasi. J-Intech terbit setahun dua kali, yaitu Juni dan Desember.
Arjuna Subject : Ilmu Komputer (semua kategori) - Sistem Informasi
Articles 288 Documents
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Peningkatan Keamanan Jaringan Virtual Private Network Menggunakan Protokol IKE/IPSEC Berbasis Mikrotik Prameswari, Annisa Dwi; Marcus, Ronald David
J-INTECH (Journal of Information and Technology) Vol 12 No 02 (2024): J-Intech : Journal of Information and Technology
Publisher : LPPM STIKI MALANG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32664/j-intech.v12i02.1493

Abstract

This research discusses protocols VPN (Virtual Private Network), namely PPTP, SSTP, L2TP, and IPsec, analyzes the authentication methods used in each protocol. The method used in this research is qualitative and involves testing the connectivity, authentication and configuration used in each VPN protocol. The parameters used in this research are configuration complexity, flexibility, security and the time required to connect to the VPN network. In the IKE/IPsec protocol, a comparison authentication analysis between Pre-Shared Key and certificate is carried out. Authentication using certificates is proven to be more secure even though it requires more complicated configuration compared to Pre-Shared Key. . The result of this research is the use of IKE / IPsec protocol has flexibility and good security. The algorithms in this protocol can be selected according to the needs and desired security.
Manajemen Dan Keamanan Jaringan Nirkabel Berbasis Wireless Gateway Security Controlling System Marcus, Ronald David; Prameswari, Annisa Dwi
J-INTECH (Journal of Information and Technology) Vol 12 No 02 (2024): J-Intech : Journal of Information and Technology
Publisher : LPPM STIKI MALANG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32664/j-intech.v12i02.1494

Abstract

Along with the development of the internet today, especially the use of WiFi Networks that are already available in various places, forcing network owners or admins to be able to optimize and maintain network traffic to remain stable and secure. Where the security system used must consider the number of users and the area of ​​the network needed. In this study, the author implemented a system that collaborates the UniFi Unify Wireless Controller and Mikrotik Router to optimize Wireless Services to make it easy and safe for users. The approach used in this study is a qualitative approach. The steps that have been taken for the qualitative method approach are conducting a location survey, designing the topology based on the results of the location survey and implementing it directly into a wireless network system with support from the Unify UniFi Wireless Controller and Mikrotik Router, where in this topology it can monitor, manage and control wireless devices in large numbers and controlled in one Controlling System and Gateway. The results of this study are the ease of managing Wifi Networks on a large scale. Management of large numbers of wireless devices in a centralized UniFi wireless controller system and monitoring and setting services to users centrally, both Access Rights, namely bandwidth quotas and access times which are also centralized. Of course, this will make it easier for admins to manage wireless networks on a large scale.
Sistem Informasi Profil Kelompok Pertanian Terpadu Berbasis Web dengan Integrated Farming (Studi Kasus: Desa Dawuhan, Malang) Soebroto, Arief Andy; Hidayat, Nurul; Perdana, Rizal Setya; Indriati, Indriati; Darmawan, Hendra; Brilliansyach, Raihan Fikri; Ibnu, Mohammad; Nurannisa, Nadhira; Vasya, M Azka Obila
J-INTECH (Journal of Information and Technology) Vol 12 No 02 (2024): J-Intech : Journal of Information and Technology
Publisher : LPPM STIKI MALANG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32664/j-intech.v12i02.1501

Abstract

Dawuhan Village in Poncokusumo District, Malang Regency, is an evolving village with significant potential in the livestock sector. However, livestock data management in this village is still done manually, facing various challenges such as limited access, data integrity issues, and time-consuming processes. To address these issues, this research aims to develop a Web-Based Integrated Livestock Group Profile Information System. The primary objectives of this study are to improve accessibility, streamline the livestock data management process, and enhance data accuracy and security. The system is designed using the Next.js framework, chosen for its ease of use and security in implementing authentication and authorization, as well as its capability for future integration. The research results show that the developed system functions according to the requirements, providing a more efficient platform, reducing errors, and enhancing the user experience for farmers involved in data management. The implementation of this system is expected to improve operational efficiency and livestock data management in Dawuhan Village comprehensively.
Model Klasifikasi Penyebab Turnover Karyawan Menggunakan Kerangka Kerja CRISP-DM Fernando, Daud; Guntara, Rangga Gelar
J-INTECH (Journal of Information and Technology) Vol 12 No 02 (2024): J-Intech : Journal of Information and Technology
Publisher : LPPM STIKI MALANG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32664/j-intech.v12i02.1502

Abstract

The problem of high employee turnover in a company has several negative impacts in terms of cost, energy, and time and one of them is felt by the fictitious Company “XYZ”. The purpose of this research is to classify the causes of employee turnover in the industry using a classification machine learning model on two different algorithms namely Random Forest and Decision Tree. In addition, this study addresses the implications of previous classification research, employee classification in the education industry, which suggests comparing the evaluation of two machine learning model performances. There are 10 variables and 9,540 historical employee data used in the research. The research technique or method used is Cross-industry Standard Process for Data Mining (CRISP-DM). The results of this study show that the Random Forest classification model is the optimal machine learning model with an AUC - ROC value reaching 0.9988. RapidMiner was used to revalidate the performance of the machine learning model using the same parameters and resulted in the highest accuracy value of 85.04% for the Random Forest model compared to the Decion Tree model.
Klasifikasi Cuaca Berbasis Citra dengan Model CNN LeNet-5 yang Dimodifikasi Tuna, Miranda Sahfira; Kristianto, Aries
J-INTECH (Journal of Information and Technology) Vol 12 No 02 (2024): J-Intech : Journal of Information and Technology
Publisher : LPPM STIKI MALANG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32664/j-intech.v12i02.1515

Abstract

The development of technology in the field of weather information is needed especially for all aspects of life. To recognize, study, and detect weather conditions that occur, classification techniques with the help of artificial intelligence are needed. The classification model used is a convolutional neural network (CNN) with a modified LeNet-5 architecture. The purpose of this study is to test the performance of the model for the classification of sunny, cloudy, cloudy and rainy weather conditions, as well as to determine the resulting accuracy and its application. With this model. The image size used is 224x224, batch size 32, learning rate 0.0001 and trained with 50 epochs. In the model training process, 8 different scenarios were created involving augmentation and no augmentation techniques, as well as the use of one of the callbacks functions in the form of earlystopping. The CNN model that uses augmentation and earlystopping with a patience value of 5 produces the best performance because it achieves an accuracy of up to 94%. The model is implemented on a locally hosted website and produces predictions that match the weather conditions that occur
Aplikasi Kontrol Barang Habis Pakai Berbasis Web sebagai Solusi Manajemen Inventaris Annisa, Riski; Rahayuningsih, Panny Agustia; Anna, Anna
J-INTECH (Journal of Information and Technology) Vol 12 No 02 (2024): J-Intech : Journal of Information and Technology
Publisher : LPPM STIKI MALANG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32664/j-intech.v12i02.1544

Abstract

Inventory management is an important element for agencies as physical economic resources whose existence and maintenance are needed to support the smooth work process. At the Kubu Raya BAPPEDA Office, administrative activities involving the use of consumables are still carried out conventionally, so they are prone to file damage and data loss due to paper-based manual recording. This research aims to overcome these problems by developing a web-based consumable control application that can manage data on goods, employees, requests, rooms, users, incoming transactions, incoming goods reports, and handover of goods pick-up. The research method uses a waterfall software development model, supported by the CodeIgniter framework and MySQL database. The result is an innovative application that enables centralized, automated, and real-time data management by all parts of the organization. The main advantages of this application over conventional systems are its ability to reduce the risk of data loss, improve recording efficiency, and simplify the reporting process. It also supports more transparent and accurate inventory management, while reducing the time it takes to process requests and report consumables. Thus, this application has a real impact in increasing the efficiency and effectiveness of goods management in the government agency environment.
Halaman Awal J-Intech Volume 12 No 2 Desember 2024
J-INTECH (Journal of Information and Technology) Vol 12 No 02 (2024): J-Intech : Journal of Information and Technology
Publisher : LPPM STIKI MALANG

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Halaman Awal J-Intech Volume 12 No 2 Desember 2024
Combination of Response to Criteria Weighting Method and Multi-Attribute Utility Theory in the Decision Support System for the Best Supplier Selection Ulum, Faruk; Wang, Junhai; Megawaty, Dyah Ayu; Sulistiyawati, Ari; Aryanti, Riska; Sumanto, Sumanto; Setiawansyah, Setiawansyah
J-INTECH ( Journal of Information and Technology) Vol 13 No 01 (2025): J-Intech : Journal of Information and Technology
Publisher : LPPM STIKI MALANG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32664/j-intech.v13i01.1810

Abstract

Choosing the right supplier is a strategic factor in supporting operational efficiency and a company's competitive advantage. This process requires a decision support system that is able to assess various alternatives objectively and in a structured manner. This study aims to develop a decision support system in the selection of the best supplier by combining the Response to Criteria Weighting (RECA) and Multi-Attribute Utility Theory (MAUT) methods. The RECA method is used to objectively determine the weight of each criterion based on the variation of data between alternatives, so as to reduce subjectivity in the weighting process. Meanwhile, the MAUT method functions to calculate the total utility value of each supplier based on the normalization value and weight that has been obtained. The results of the RECA method show the objective weight of each criterion, which is then used in the MAUT calculation process. The results of the analysis, obtained in the best supplier selection based on the total score of each candidate, it can be seen that PT Global Niaga Mandiri ranks first with the highest score of 0.6512, this shows that this company is the best choice in the supplier selection process. In second place is UD Anugrah Bersama with a score of 0.399, followed by PT Indo Logistik Prima in third place with a score of 0.3451. The combination of the RECA and MAUT methods has been proven to be able to produce accurate, rational, and accountable decisions. This system provides a measurable approach in filtering supplier alternatives efficiently and is relevant to be applied to various other multi-criteria decision-making contexts.
Designing a Web-Based Laundry Service Application For Strala Laundry Mutia, Cut; Fauziah, Fauziah; Meiditra, Irzon; Yuda, Fitra; Rahmansyah, Rizky
J-INTECH ( Journal of Information and Technology) Vol 13 No 01 (2025): J-Intech : Journal of Information and Technology
Publisher : LPPM STIKI MALANG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32664/j-intech.v13i01.1820

Abstract

As daily activities become more hectic, the need for efficient laundry services is increasing. Currently, Starla Laundry relies on a manual system for operations, leading to challenges such as storing customer data in logbooks, creating complex reports, and slow transaction processes due to manual calculations. These issues make it difficult for the owner and admin to manage the business effectively amidst growing competition. To address this, a new application is proposed using PHP programming, a MySQL database, and Microsoft Visual Studio Code for data processing. The application aims to improve operational efficiency, simplify data management, and support business growth. It is expected to enhance customer satisfaction and open opportunities to optimize the business in the digital era. This study focuses on designing a laundry service information system using the System Development Life Cycle (SDLC) methodology, which includes planning, analysis, design, and implementation. The system was tested using Black Box Testing to ensure the software meets its requirements. The results confirm that all application functions work as intended, making it ready to streamline Starla Laundry’s operations efficiently and professionally.
Analysis of the Effectiveness of Traditional and Ensemble Machine Learning Models for Mushroom Classification Sulistianingsih, Neny; Martono, Galih Hendro
J-INTECH ( Journal of Information and Technology) Vol 13 No 01 (2025): J-Intech : Journal of Information and Technology
Publisher : LPPM STIKI MALANG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32664/j-intech.v13i01.1851

Abstract

The classification of edible versus poisonous mushrooms presents a critical challenge in the domains of applied biology and public health, particularly due to the serious implications of misidentification. This research employs the UCI Mushroom Dataset to evaluate and compare the effectiveness of several machine learning models, including traditional algorithms like Logistic Regression, Decision Tree, Random Forest, Support Vector Machine, K-Nearest Neighbors and Naïve Bayes, as well as advanced ensemble techniques such as Stacking and Voting Classifier. Notably, both Random Forest and Stacking achieved flawless accuracy, reaching 100%, underscoring the high predictive capacity of these models in complex categorical scenarios. Conversely, Naïve Bayes exhibited significantly weaker performance—achieving only 59.8% accuracy—likely due to its underlying assumption of feature independence, which does not hold for this dataset. The ensemble learning approaches, including the combination of Stacking and Bagging, not only preserved but also enhanced model robustness and generalization. These methods effectively leverage the complementary strengths of individual learners to yield more accurate and stable predictions while mitigating overfitting risks. Comparative analysis with previous research confirms the consistency of these findings and reinforces the viability of ensemble strategies for handling intricate classification tasks. Overall, this study highlights the importance of algorithm selection tailored to data characteristics and supports the use of ensemble learning to boost predictive reliability.

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