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INDONESIA
IPTEK The Journal for Technology and Science
Published by Institut Teknologi Sepuluh Nopember Surabaya
ISSN : 08534098     EISSN : 20882033     DOI : -
Core Subject : Science,
Computer Science & IT
IPTEK The Journal for Technology and Science (eISSN: 2088-2033; Print ISSN:0853-4098), is an academic journal on the issued related to natural science and technology. The journal initially published four issues every year, i.e. February, May, August, and November. From 2014, IPTEK the Journal for Technology and Science publish three times a year, they are in April, August and December in online version.
Arjuna Subject : -
Articles 6 Documents
 1 
Search results for , issue "Vol 35, No 2 (2024)" : 6 Documents clear
Design and Implementation of Centralized Loan Origination System with Agile Development Method Sudianjaya, Nella Rosa; Yuhana, Umi Laili
IPTEK The Journal for Technology and Science Vol 35, No 2 (2024)
Publisher : IPTEK, DRPM, Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j20882033.v35i2.17603

Abstract

Credit is a core business with the biggest income in the banking industry. Hundreds of customers come to the bank daily to get loan applications. Because there are a lot of customers, the loan application process can take a whole week, and some customers who can’t wait too long go and come to another bank that can provide a quick loan application process. This paper proposes an application called the Loan Origination System that can facilitate the loan application process. Loan Origination System is expected to handle the loan application process from start to finish, including credit verification, risk analysis, document management, and loan processing. Agile methodology is used in developing a Loan Origination System. Agile methodology is expected to be quick and simple and have more iterative development cycles. The proposed method has been tested using functional suitability results combined with Goal Question Metrics consisting of functional appropriateness, functional correctness, and functional suitability compliances. It gets results with 83.02%, 86.43%, and 85.96%, respectively, for functional appropriateness, functional correctness, and functional suitability compliances. The result shows that the Loan Origination System application meets the requirements and is functionally suitable. The result shows that agile methodology gives the application high flexibility and adaptability, so it is possible to make changes and adjustments in a short time. The application is suitable for helping users process and review the loan application. The application is also user-friendly and, time by time can replace the manual processing of loan applications.
Public Transport Integration Challenges of Wira Wiri Suroboyo as a Commuter Train Feeder Susanti, Anita; Supriyatno, Dadang; Dermawan, Dodik Arwin; Wibisono, R. Endro
IPTEK The Journal for Technology and Science Vol 35, No 2 (2024)
Publisher : IPTEK, DRPM, Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j20882033.v35i2.19020

Abstract

Congestion is a problem in most big cities, including Surabaya. One alternative to reduce congestion is to create city transportation with excellent service. Surabaya has had city transportation, city buses and also commuter trains for a long time. However, it is considered that travelers do not have excellent service. In 2023, a new city transportation will be created with the name Wira Wiri Suroboyo (WWS) with the aim of diverting some private vehicle users toWWS. However, until now,WWS has not been able to attract the interest of the public who use private vehicles. So it is necessary to research the operational performance of theWWS and analyze integration opportunities with commuter trains. The research method used was conducting field surveys and interviews with WWS passengers. The results of the survey show that load factor, headway, departure frequency, number of vehicles in operation are still not optimal to divert private vehicle users toWWS and at the same time integrate with commuter trains. Therefore, other efforts are needed to limit private vehicles in order to provide cross-subsidies for public transportation. So that it does not burden operational costs which have been borne by the Government.
Adversarial Training For Robust Defense In Cnn Models For Lung And Colon Histopathological Images Nisa', Chilyatun; Suciati, Nanik; Yuniarti, Anny
IPTEK The Journal for Technology and Science Vol 35, No 2 (2024)
Publisher : IPTEK, DRPM, Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j20882033.v35i2.19630

Abstract

Cancer stands as the world’s second-leading cause of death, arising from abnormal cell growth that invades the body’s cells and tissues. Simultaneous occurrences of lung and colon cancer are not uncommon, with lung cancer often emerging as the second primary cancer in colon cancer patients. While Deep Learning (DL) approaches have shown promise in accurate cancer classification, recent studies highlight the susceptibility of DL models to perturbations in input images. Merely achieving accuracy is insufficient; models must demonstrate resilience against even the slightest perturbations by applying adversarial defence methods. This study aims to enhance the reliability of the Convolutional Neural Network (CNN) algorithm in the face of adversarial attacks by implementing adversarial training. Leveraging the LC25000 dataset and various pre-trainedCNNmodels for classification,we employ adversarial attack methods such as Carlini and Wagner, DeepFool, and SaliencyMap alongside adversarial training for defence. Evaluation metrics include precision, recall, F1-score, accuracy. Our assessment involves scrutinizing adversarial attacks and defences on histopathology images related to lung and colon issues, representing a state-of-the-art endeavour. The results indicate a significant improvement in susceptibility to adversarial attacks on histopathological images of the lungs and colon, from 0% to 81%.
A New Indoor Positioning Approach based on Weighted K-Nearest Algorithm Akanni, Jimoh; Isa, Abdurrhaman Ademola; Abdulrahman, Amuda Yusuf; Alao, Atanda Rasaq; Ogunbiyi, Olalekan
IPTEK The Journal for Technology and Science Vol 35, No 2 (2024)
Publisher : IPTEK, DRPM, Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j20882033.v35i2.20249

Abstract

Many contemporary technological services rely heavily on precise location data within smartphone applications, making accuracy a crucial aspect of indoor positioning systems. However, the variability in received signal strength (RSS) poses a challenge for achieving exact locations in Wi-Fi indoor positioning algorithms. Traditional weighted k-nearest neighbor (WkNN) techniques typically utilize RSS spatial distance for selecting reference points (RPs) to estimate locations. To enhance position accuracy, this study introduces a novel indoor positioning method based on WkNN. By incorporating three geometrical distances of RSS (physical, spatial, and Canberra), this approach selects RPs and conducts position estimation using a fusion weighted strategy based on these distances. Experimental findings indicate that the newly proposed method outperforms the nearest neighbor (NN) technique. Moreover, comparative investigations demonstrate its superiority over k-nearest neighbor (kNN) and weighted k-nearest neighbor (WkNN) algorithms. Compared to NN, kNN, and WkNN algorithms, this novel technique improves positioning accuracy by approximately 49.9%, 32%, and 25%, respectively.
Analysis of Taxpayer Behavior to Predict Motor Vehicle Tax Payments Using the Weighted Majority Voting Ensemble Approach Wahyuwidayat, Raditia; Saikhu, Ahmad; Hidayati, Shintami Chusnul
IPTEK The Journal for Technology and Science Vol 35, No 2 (2024)
Publisher : IPTEK, DRPM, Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j20882033.v35i2.19196

Abstract

Taxpayer non-compliant behavior impacts Motor Vehicle Tax (MVT) revenues not following the predetermined targets. This behavior results in reduced income, and several regional development targets may not be achieved. Therefore, Regional Governments need to predict MVT payments to formulate future targets better. This research aims to analyze taxpayer behavior in predicting future MVT payments, whether the payments are compliant or late or non-payment. The proposed approach starts by analyzing and obtaining a dataset of taxpayer behavioral features. An ensemble classifier method based on Weighted Majority Voting (WMV) is used to predict payments. WMV was developed using the GridSearchCV technique to find optimal hyperparameter values to increase the model accuracy value for individual classifiers. The weight determined from the model accuracy value is converted into a ranking of the number of votes to maximize model performance. Next, feature ablation analysis is carried out to understand the contribution of each feature to model performance. The performance of the proposed system is evaluated using the confusion matrix, accuracy, precision, recall, and f1-score. The research results show that the WMV method performs better, with an accuracy of 96.247%, compared to the proposed individual classifier method in predicting MVT payments based on taxpayer behavior.
Assessing Water Quality in Nigerian Villages: An IoT-Based Monitoring of Three Rivers Osifeko, Martins; Oduwole, Olamide; Kafar, Rasheedat
IPTEK The Journal for Technology and Science Vol 35, No 2 (2024)
Publisher : IPTEK, DRPM, Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j20882033.v35i2.20524

Abstract

Ensuring safe and clean water is crucial for public health, especially in regions with limited access to reliable water quality testing. This study focuses on assessing water quality in three Nigerian villages using an IoT-based system. Traditional water quality monitoring methods are often expensive, time-consuming, and require specialized personnel and laboratory facilities. To overcome these challenges, we propose a low-cost, real-time water quality monitoring system utilizing the ESP32 microcontroller equipped with sensors for temperature, pH, dissolved oxygen, and conductivity. Our system collects and transmits data for continuous monitoring and analysis. The deployment in Nigerian villages along three rivers reveals that while pH levels are within safe limits, turbidity levels in two rivers exceed acceptable drinkingwater standards, highlighting the presence of particulate contamination. The system’s real-time capabilities and cost-effectiveness demonstrate its potential for broader application in resource-constrained areas. This study underscores the importance of IoT technologies in enhancing water quality monitoring and contributes to achieving the Sustainable Development Goals related to clean water and sanitation

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