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Journal Of Artificial Intelligence And Software Engineering
Published by Politeknik Negeri Lhokseumawe
ISSN : 2797054X     EISSN : 2777001X     DOI : http://dx.doi.org/10.30811/jaise
Core Subject : Science,
Computer Science & IT
Artificial Intelligence Natural Language Processing Computer Vision Robotics and Navigation Systems Decision Support System Implementation of Algorithms Expert System Data Mining Enterprise Architecture Design & Management Software & Networking Engineering IoT
Arjuna Subject : Ilmu Komputer (semua kategori) - Aplikasi Ilmu Komputer
Articles 215 Documents
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Software Testing in E-Commerce: A Comparison Between Manual and Automated Testing Using Katalon Studio and Python Rakly, Brian Duen; Andriyani, Widyastuti
Journal of Artificial Intelligence and Software Engineering Vol 5, No 1 (2025): March
Publisher : Politeknik Negeri Lhokseumawe

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30811/jaise.v5i1.6448

Abstract

Software testing is a crucial element in software development to ensure quality and reliability. This study compares manual and automated testing using tools like Katalon Studio and Python. Manual testing is effective for scenarios requiring human judgment, such as user experience (UX) evaluation. In contrast, automated testing is more efficient for routine and repetitive tasks, reducing human error and speeding up the process. This study evaluates the effectiveness, efficiency, and costs of both methods in the context of e-commerce software testing. The results indicate that manual testing is superior in detecting defects before release, while automated testing is more cost-effective and time-efficient for repetitive testing. This guide assists developer for selecting the appropriate testing method based on their project needs.
The Implementation of Proof-of-Work Technology in the Security of Job Training by the Surakarta City Manpower Office Agus Putra, Affriza Brilyan Relo Pambudi
Journal of Artificial Intelligence and Software Engineering Vol 5, No 1 (2025): March
Publisher : Politeknik Negeri Lhokseumawe

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30811/jaise.v5i1.6403

Abstract

This study aims to implement Proof-of-Work (PoW) innovation as a security component in the job training system managed by the Surakarta City Manpower Office. In the rapid development of technology, information security is a very important aspect, especially in the implementation of training activities involving sensitive data from participants and instructors. This study uses a prototyping approach to design, implement and test a PoW blockchain technology-based system to ensure information security in job training. The prototyping approach was chosen because it allows a rapid development process that is immediately applied to perfect the system. This system is designed in such a way that every data entered into the training track record is secured through a mining process, which ensures its integrity and security. The results of PoW technology are able to verify new transactions and data entered so that only valid and encrypted information can be received and stored. In conclusion, the implementation of a PoW-based security system on this job training platform has proven to be successful in increasing data protection and preventing manipulation by irresponsible parties. Thus, PoW technology not only provides a higher level of information security, but also increases the trust of participants and job training organizers at the Surakarta City Manpower Office.
Design of a Traditional Clothing Rental Information System Using the First Come First Serve (FCFS) Algorithm Based on a Website Handoyo, Nuh; Nur Laila, Siti
Journal of Artificial Intelligence and Software Engineering Vol 5, No 1 (2025): March
Publisher : Politeknik Negeri Lhokseumawe

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30811/jaise.v5i1.6454

Abstract

This study aims to design and develop a web-based traditional clothing rental information system using the First Come First Serve (FCFS) algorithm to enhance rental management efficiency. The background of this research is based on issues in traditional clothing rental management, which is still conducted manually, leading to booking uncertainties and stock management errors. The research methods include interviews, observations, and literature studies, along with system development using the Waterfall model. The results show that the developed system effectively manages rentals by ensuring orders are processed according to arrival time while providing a responsive and user-friendly interface. The conclusion of this study is that the FCFS-based system improves transparency and fairness in traditional clothing rentals while making it easier for customers to place orders.
Implementation of Cyber Threat Intelligence on Intrusion Detection System using STIX Framework Mahardhika, Yesta Medya; Saputra, Ferry Astika; Syarif, Iwan; Wibowo, Prasetyo; Ardhani, Misbahul
Journal of Artificial Intelligence and Software Engineering Vol 5, No 1 (2025): March
Publisher : Politeknik Negeri Lhokseumawe

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30811/jaise.v5i1.6518

Abstract

Cyber threats are complex and diverse issues. Various types of threats emerge daily on the internet. In this research, we proposed a new Cyber Threat Intelligence platform to deal with the challenges above, using Snort as a tool for detecting anonymous network traffic and STIX as a serialization format and standardization of Cyber Threat Intelligence data. As a result, a Cyber Threat Intelligence based on Snort contains Apache Spark as the processing engine, MongoDB as the database, and STIX as the serialization format and data standardization. We test our platform by using two data sources, the CIC-IDS2017 dataset, and the real traffic. We successfully converted the snort alerts to STIX format and visualized them into graph. The graph shows indication of network traffic suspicious, the country of attacker come from, attribute information and attack pattern. The experiment shows that converting Snort data to STIX requires considerable time if the amount of data processed is getting bigger, Real Traffic needs 16 seconds of data preprocessing and 3 minutes of conversion time, while PCAP needs 35 seconds of preprocessing time and 13 minutes of conversion time.
Prediction of Budget Planning Using the Long Short Term Memory Ambari, Nasser; Puspitasari, Novianti; Septiarini, Anindita
Journal of Artificial Intelligence and Software Engineering Vol 5, No 1 (2025): March
Publisher : Politeknik Negeri Lhokseumawe

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30811/jaise.v5i1.6428

Abstract

Keputusan merupakan elemen kunci dalam manajemen perusahaan, karena perencanaan yang baik menjadi faktor penentu kesuksesannya. Salah satu aspek penting dalam perencanaan adalah prediksi penjualan. Sebuah perusahaan properti dapat mengalami kesulitan aliran kas akibat over budget, sehingga memaksa perusahaan untuk meninjau kembali strategi pemasaran. Penelitian ini menggunakan Long Short Term Memory (LSTM) untuk membantu perusahaan dalam mengurangi risiko over budget di masa depan. Metode Long Short Term Memory (LSTM) mampu menghasilkan model prediksi dengan akurasi tinggi. Data penelitian berupa data pendapatan penjualan properti dari sebanyak 107 data. Hasil pengujian menunjukkan bahwa penggunaan LSTM dengan perbandingan data latih dan data uji sebesar 90:10, 200 epoch, dan learning rate sebesar 0.005 menghasilkan nilai Root Mean Square Error (RMSE) terendah sebesar 0.128883554. Hasil prediksi menunjukkan pendapatan penjualan yang terus menurun selama tiga tahun.
Data Security Management of the Academic Information System at Kuningan University (SIKADUKU) Using the DAMA-DMBOK Framework Khalimi, Toni
Journal of Artificial Intelligence and Software Engineering Vol 5, No 1 (2025): March
Publisher : Politeknik Negeri Lhokseumawe

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30811/jaise.v5i1.6457

Abstract

Data security management is crucial for an information system, considering that data that has been transformed into information can be accessed by any user. Data security management protects information assets in alignment with privacy and confidentiality regulations as well as business needs. Poor data security management can negatively impact ongoing management processes.  Therefore, data management, particularly data security, is necessary as a preventive measure and a solution to data-related issues and their security. Several frameworks can be applied to manage data security, one of which is DAMA-DMBOK. By utilizing two knowledge areas within the DAMA-DMBOK framework, namely Data Governance and Data Security Management, for an academic information system, a proposed recommendation for governance and data security management design can be formulated for the Academic Information System (SIA) of Universitas Kuningan (SIKADUKU).
Implementation of Failover Recursive Gateway and Load Balancing PCC Method on Internet Networks at Universitas Semarang Surono, Surono; Setiarso, Galih; Hadi, Soiful
Journal of Artificial Intelligence and Software Engineering Vol 5, No 1 (2025): March
Publisher : Politeknik Negeri Lhokseumawe

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30811/jaise.v5i1.6337

Abstract

This study implements and analyzes failover recursive gateway and load balancing using the Per Connection Classifier (PCC) method on the internet network at Universitas Semarang to enhance the reliability and efficiency of bandwidth distribution. The methodology involves using Wireshark for network data testing and analysis. The results demonstrate three main achievements: (1) bandwidth from both ISPs is evenly distributed, (2) the failover system functions optimally by automatically switching to the active link if one ISP fails, and (3) the method effectively balances bandwidth and manages connection disruptions. Before implementation, ping tests to www.google.com showed an average response time of 62 ms, with balanced upload/download speeds of 100 Mbps. After implementation, the ping response remained stable at 62 ms, while upload speeds increased to 158 Mbps and download speeds to 144 Mbps. This study proves that failover recursive gateway and PCC-based load balancing improve network stability and efficiency, providing a reliable solution for bandwidth management and connection continuity at Universitas Semarang.
Identification of Groundwater Potential Zones Using Analytic Hierarchy Process (AHP) Based on Webgis in North Central Timor District Susu, Yublina Rambuhana; Kelen, Yoseph Pius Kurniawan; Lestari, Anastasia Kadek Dety; Gelu, Leonard Peter
Journal of Artificial Intelligence and Software Engineering Vol 5, No 1 (2025): March
Publisher : Politeknik Negeri Lhokseumawe

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30811/jaise.v5i1.6459

Abstract

In all kinds of human activities, water is a basic need to carry out various activities. Therefore, water is very functional and plays an important role in the life of living things on this earth. Groundwater is a very important source of water supply, especially in areas where long dry seasons or droughts cause rivers to stop flowing. Geographic information systems (GIS) can be used to help map groundwater. In this study, it was applied in determining the potential zones of groundwater availability in the area with several parameters such as rainfall, lithology, geomorphology. The entire map is then weighted using the analytical hierarchical process (AHP) method to determine the potential zones of groundwater availability, the results will be displayed and informed in the Website system. The combination of AHP and Waterfall methods shows that high water potential areas in North Central Timor Regency are in Noemuti, South Bikomi, Insana, East Noemuti, and West Miomafo Districts, moderate water potential in East Miomafo District, Kefamenanu City, Insana Fafinesu, Central Miomafo, Musi, Mutis, Biboki Feotleu, Biboki Moenleu, North Biboki, Central Bikomi, West Insana, South Biboki, and low water potential in Bikomi Nilulat, Biboki Anleu, Biboki Tanpah, and North Insana Districts.
Irrigation Data Inventory Using Web-Based Geographic Information System to Support the Water Discharge Distribution in Belu Regency Tetik, Fransiskus Rendi; Kelen, Yosep Pius Kurniawan; Lestari, Anastasia Kadek Dety; Manek, Siprianus Septian
Journal of Artificial Intelligence and Software Engineering Vol 5, No 1 (2025): Maret
Publisher : Politeknik Negeri Lhokseumawe

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30811/jaise.v5i1.6451

Abstract

The development of information technology in the era of globalization has become an integral part of human life, especially in providing fast, accurate, and easily accessible information. BeluRegency, located in East Nusa Tenggara Province, has challenges in managing air resources, especially related to agricultural irrigation. Inaccurate and incomplete irrigation data hinders the efficiency of water discharge distribution, which is very important or most of the population who make a living in the agricultural sector. This research aims to apply the Geographic Information System (GIS) in the inventory of distributed data, in order to improve the efficiency and effectiveness of air resource management. By using GIS, it is hoped that accurate mapping of the location of irrigation canals can be carried out, making it easier to make decisions regarding the distribution of water discharge. The results of this research are expected to increase agricultural productivity, maintain environmental curiosity, and improve the welfare of farmers and local communities in Belu Regency. This research is entitled Irrigation Data Inventory Using Web-Based Geographic Information System to Support the Water Discharge Distribution in Belu Regency".
EDA and Tableau Analysis for Identification of Heart Disease Risk Factors Silmina, Esi Putri; Perkasa, Legawan
Journal of Artificial Intelligence and Software Engineering Vol 5, No 1 (2025): Maret
Publisher : Politeknik Negeri Lhokseumawe

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30811/jaise.v5i1.6389

Abstract

Heart disease is one of the leading causes of death worldwide, influenced by various risk factors such as high blood pressure, cholesterol levels, and lifestyle. This study analyzes the risk factors for heart disease using the Heart Disease Dataset which includes more than 1,000 records with variables such as age, blood pressure, cholesterol, and alcohol consumption. Exploratory Data Analysis (EDA) was applied to identify patterns and relationships between variables, while Tableau was used to present the results visually and interactively. The results showed that high blood pressure was the main risk factor, with the majority of patients having blood pressure in the range of 130-135 mmHg, which is considered high risk. In addition, high cholesterol levels (200-205 mg/dL) also contributed significantly to the increased risk of heart disease, while alcohol consumption in the "Heavy" category worsened heart health conditions. Data visualization shows an increasing trend in heart disease cases, especially in individuals with a combination of these risk factors. Therefore, this study emphasizes the importance of routine blood pressure and cholesterol monitoring, implementing a healthy diet, regular physical activity, and health education to reduce the incidence of heart disease in the future.

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