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Jurnal Sisfotek Global
Published by Institut Teknologi dan Bisnis Bina Sarana Global
ISSN : 20881762     EISSN : 27213161     DOI : http://.doi.org/10.38101/jsg
Core Subject : Science, Education, Engineering,
Computer Science & IT Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering
Jurnal Sisfotek Global is a peer-reviewed open access journal published twice a year (March and September), a scientific journal published by Institut Teknologi dan Bisnis Bina Sarana Global. Jurnal Global Sisfotek aims to provide a national forum for researchers and professionals to share their ideas on all topics related to the field of computer science. It is published in online version (e-ISSN 2721-3161) and printed version (p-ISSN 2088-1762). Jurnal Global Sisfotek has been indexed and abstracted in Index Copernicus, GOOGLE Scholar, BASE (Bielefeld Search Engine), Crossref Search, One Search, PKP-Indexed, Neliti search, Garuda, Dimensions, Scilit. Jurnal Sisfotek Global accepts quality manuscripts produced from research projects within the scope of the field of computer science, which include, but are not limited to the following topics: information systems, image processing, multimedia, mobile computing, artificial intelligence, expert systems, computer systems. The manuscript must be original research and written in English (from 2021).
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 11 Documents
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Search results for , issue "Vol 13, No 2 (2023): JURNAL SISFOTEK GLOBAL" : 11 Documents clear
Rational Unified Process as a Software Development Method in Decision Support Systems Design with Simple Additive Weighting in Determining Priority Rehabilitations of Classrooms Willy Prihartono; Sri Farida Utami
JURNAL SISFOTEK GLOBAL Vol 13, No 2 (2023): JURNAL SISFOTEK GLOBAL
Publisher : Institut Teknologi dan Bisnis Bina Sarana Global

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38101/sisfotek.v13i2.9678

Abstract

Rational Unified Process (RUP) as a development method in Decision Support System (DSS) is suitable for decision-making processes due to its possibility to show iterative and incremental processes in RUP. The decision-making process takes several phases, which are the intelligence phase, the design phase, the choice phase, and the implementation phase. In Decision Support System has many management models. Simple additive weighting (SAW), also known as the weighted summing method, is used as a management model in this paper. The basic concept of the SAW method is to find the weighted sum of performance ratings for each alternative on all attributes. The RUP Approach, which has an iterative and incremental nature, is expected to become a solution in a decision support system. The RUP project has four phases: inception, elaboration, construction, and transition to the software product. RUP divides software development into a number of "disciplines" that are iterations or phases. Each discipline has associated goals and outputs that are accomplished through planned activities. Complete documentation for every stage of development is also emphasized by RUP. The fundamental of RUP are architecturally based approaches, iterative and incremental development, object-oriented modeling, risk management, and a focus on software quality. Collaboration between the software development team and relevant stakeholders is also encouraged by this methodology.
Implementation of a Business Intelligence Model for Analysis Banking and Credit Management Nilo Legowo; Achmad Yodan Gimpalas
JURNAL SISFOTEK GLOBAL Vol 13, No 2 (2023): JURNAL SISFOTEK GLOBAL
Publisher : Institut Teknologi dan Bisnis Bina Sarana Global

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38101/sisfotek.v13i2.7298

Abstract

The 2008 global financial crisis affected the pace of the economy by reducing the level of public trust in banks. Seeing these conditions, Bank XYZ needs to know and analyze the factors that influence bank lending. Debtor data processing at Bank XYZ is well integrated, but in fact, Bank XYZ still needs to pay attention to the principle of prudence in making decisions to provide credit facilities to debtors with minimal risk so that credit can be extended consistently and based on sound credit principles. In monitoring and analyzing the credit system at Bank XYZ, there is one factor that serves as a reference for measuring a bank's ability to bear the risk of credit failure by debtors through NPLs (non-performing loans). In addition to NPLs, the growth in the number of debtors, the amount of credit disbursement, the amount of outstanding credit provided in various sectors, and the amount of collectibility of debtors also play an important role in decision-making by management; therefore, the author proposes a business intelligence model to analyze credit data at XYZ Bank in the form of data visualization in dashboard form. The dashboard was built using the Tablue for Students software. The results of this study are a business intelligence model in the form of a dashboard application to be able to monitor debtor data growth, analyze loans extended in various economic sectors, and analyze outstanding loans using the NPL value as a reference based on credit quality as a decision support tool.
Expert System for Corn Disease Identification Using Case Based Reasoning Method Nurhaeka Tou; Putri Mentari Endraswari; Nur Annisa
JURNAL SISFOTEK GLOBAL Vol 13, No 2 (2023): JURNAL SISFOTEK GLOBAL
Publisher : Institut Teknologi dan Bisnis Bina Sarana Global

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38101/sisfotek.v13i2.9716

Abstract

Corn is the second type of food after rice. However, currently, the level of corn productivity is experiencing problems, with pests and corn diseases. The process of controlling these pests and diseases, if not handled as early as possible, will result in crop failure for corn farmers. Identifying the types of pests and diseases that attack corn plants, is carried out by experts in the field of agriculture, but this process requires quite a long time. Therefore, we need a system that can help farmers diagnose diseases in corn plants, so that the control process can be carried out optimally, quickly and on target. This study aims to build an expert system to identify diseases in corn plants by implementing the Case-Based Reasoning (CBR) method. CBR is a reasoning method on a computer that utilizes old cases to solve new cases. The process of identifying the type of disease with the CBR method is carried out by the user inputting the symptoms experienced by the corn plant into the system, then the system calculates the value of similarity between new cases and old cases using the nearest neighbor method. The system is made with 17 diseases and 56 symptoms, each symptom has a weight. Based on the test results, shows that the system can identify the types of diseases in corn plants following the rule of 100% with a similarity accuracy rate of 75.00%.
Utilizing Machine Learning For Identifying Potential Beneficiaries of Family Hope Program Muhammad Abdurrohim; Lena Magdalena; Muhammad Hatta
JURNAL SISFOTEK GLOBAL Vol 13, No 2 (2023): JURNAL SISFOTEK GLOBAL
Publisher : Institut Teknologi dan Bisnis Bina Sarana Global

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38101/sisfotek.v13i2.9718

Abstract

In identifying families who are entitled to PKH assistance there are often obstacles such as RTSM identification errors, this is caused by the negligence of officials so that they are not accurate in making confirmations in large numbers. An automated system that can predict RTSM can be a solution to this problem, a system based on a machine learning model. This study aims to analyze the machine learning model Decision Tree C45 (DT C45), K-Nearest Neighbor (KNN), and Naive Bayes (NB). The results showed that Decision Tree C45 was the optimal model to implement with an accuracy value of 70%.
Designing a Network Using Network Intrusion Detection System (NIDS) for Detecting Attacks on the Server in the Computers Laboratory at Suryakancana University Mohamad Kany Legiawan; Muhamad Rifki Arisagas
JURNAL SISFOTEK GLOBAL Vol 13, No 2 (2023): JURNAL SISFOTEK GLOBAL
Publisher : Institut Teknologi dan Bisnis Bina Sarana Global

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38101/sisfotek.v13i2.9624

Abstract

The escalating reliance on technology and network systems has given rise to mounting concerns regarding digital asset security. This journal presents the design and implementation of a Network Intrusion Detection System (NIDS) intended to detect potential attacks on servers within the Computers Laboratory at Suryakancana University. The research follows the Network Development Life Cycle (NDLC) methodology, encompassing phases from analysis to simulation prototyping. Despite successful implementation challenges were encountered due to server maintenance issues and continuous updates, leading to a partial implementation of NIDS using the Snort tool. The journal provides insights into the significance of cybersecurity in educational environments and underscores the importance of vigilant network security measures
Analysis Sentiment of Twitter User on Indonesia's 2024 Presidential Election Using K-Means Algorithm Leny Tritanto Ningrum; Dwi Rahmiyati
JURNAL SISFOTEK GLOBAL Vol 13, No 2 (2023): JURNAL SISFOTEK GLOBAL
Publisher : Institut Teknologi dan Bisnis Bina Sarana Global

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38101/sisfotek.v13i2.9609

Abstract

The General Election is a five-year agenda of the Indonesian people in order to fulfill the political rights of every citizen for the election of the president and the legislature. In every election, especially during the campaign period, differences of opinion often occur between certain groups or factions, this often creates an atmosphere of political uproar in various parts of Indonesia. The purpose of this study is to see the level of sentiment of social media users towards the implementation of elections in Indonesia so as to minimize political upheaval that occurs in society during the elections to be held in 2024. The data that will be used in this research is data on Twitter users who have large volumes and are taken from all regions of Indonesia. To suit the data model used, this study will use the data mining method with the K-Means algorithm. The results of this study show the percentage level of public sentiment of Twitter users towards the 2024 election and presidential election. Public sentiment is positive, neutral and negative. Based on these results, it can provide input to the government so that it can make appropriate policies ahead of elections and presidential elections so as to create a peaceful atmosphere.
Prototype of the MPSO (Modified Dimension Particle Swarm Optimization) Algorithm Method in Searching for Computer Equipment Data inventory Nasril Sany; Ari Asmawati; Syafnidawati Syafnidawati
JURNAL SISFOTEK GLOBAL Vol 13, No 2 (2023): JURNAL SISFOTEK GLOBAL
Publisher : Institut Teknologi dan Bisnis Bina Sarana Global

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38101/sisfotek.v13i2.9608

Abstract

cIn the development of information technology and computerization today, it encourages humans to create systems that can help their lives. Especially in the case of inventory of goods, especially if the location of these items is unknown due to their large number and large and large storage space. The PSO (Particle Swarm Optimazation) algorithm method is a suitable method for dealing with problems, namely searching for inventory data on computer equipment. This method is very useful, especially where the inventory stock of computer equipment is already huge, thousands of them. Especially with the small components. Equipment or computer data whose location was previously unknown, it is hoped that with this PSO algorithm method the inventory can be known which is then put in the data and managed properly. The reporting of computer equipment inventory data can be conveyed properly so that the company management can determine the steps to be taken with the data obtained.
Application of the AHP-TOPSIS Method As Best Employee Decision Support System Nunung Nurmaesah; Detin Sofia; Savitri Octavia
JURNAL SISFOTEK GLOBAL Vol 13, No 2 (2023): JURNAL SISFOTEK GLOBAL
Publisher : Institut Teknologi dan Bisnis Bina Sarana Global

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38101/sisfotek.v13i2.9712

Abstract

In every company, employees are an essential element. To be able to find out whether employees are competent or not, an employee performance appraisal is needed. Employee appraisal is critical, not only because it is a determining factor in employee wage increases and promotions but also because it can evaluate skills. However, the current employee appraisal process still needs to be more objective and accurate, and it takes a long time, and there are many possibilities for human error. This study aims to design a decision support system in determining the best employees using the Analytical Hierarchy Process (AHP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) methods. The AHP method is used to calculate the weight of each parameter, and TOPSIS is used to perform the ranking process based on the parameter weighting results. The results of this study found that the best employees were employees with the alternative code A3, with a value of 0.74271.
Implementation of the Composite Performance Index and Rank Order Centroid Weighting Methods in E-Wallet Selection Susana Dwi Yulianti; Rini Nuraini; Arisantoso Arisantoso; Mursalim Tonggiroh
JURNAL SISFOTEK GLOBAL Vol 13, No 2 (2023): JURNAL SISFOTEK GLOBAL
Publisher : Institut Teknologi dan Bisnis Bina Sarana Global

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38101/sisfotek.v13i2.9720

Abstract

Nowadays, e-wallets have become a popular alternative for non-cash financial transactions. More and more e-wallet companies and service providers are emerging with various features and benefits. To determine the choice of using an e-wallet, users must know each e-wallet's various features and services; of course, this takes time and makes it difficult for decision-makers. This research aims to implement the Composite Performance Index (CPI) and Rank Order Centroid (ROC) approaches in a decision support system for choosing an e-wallet to produce easy and fast decisions. The ROC method is used to determine the weight value based on the order of importance of the criteria. Meanwhile, the CPI approach has the ability to combine information from various criteria into one index and evaluate differences in criteria to obtain alternative rankings. This research produces a website-based DSS application that recommends the best alternative by displaying alternative rankings. The system built produces valid calculation output; this is proven by the results of calculations by the system and manual calculations showing the same results. For software testing with usability testing, an average value of 86% was obtained. This means that the software developed is feasible to implement and considered easy to use.
Customer Segmentation Based on RFM Value on the Sale of Electronic Kopmen BMI Using K-Means Clustering Algorithm Zainul Hakim; Detin Sofia; Annida Rosna Fadhilah
JURNAL SISFOTEK GLOBAL Vol 13, No 2 (2023): JURNAL SISFOTEK GLOBAL
Publisher : Institut Teknologi dan Bisnis Bina Sarana Global

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38101/sisfotek.v13i2.9693

Abstract

At present, the development of information technology is increasing rapidly. The need for information and data processing in various aspects of human life is critical, as well as customer data processing in BMI Consumer Cooperatives. This situation can impact information providers in an organization or company that requires fast, precise, and accurate data processing. The customer segmentation clustering system at the BMI Consumer Cooperative has yet to be implemented. A K-means clustering system is needed to increase customer loyalty, which can simplify the process of grouping customer segmentation. In this thesis, researchers use a descriptive method as a research methodology, which is used to get an overview and explanation of the state of the research object based on facts. As for the data collection method, researchers used interviews, observation, and literature study. In developing the system, researchers use prototyping. The customer segmentation information system application prototype describes the implementation of Astah's UML (Unified Modeling Language) and program planning used by Python. The conclusion of this prototype application can make it easier for managers to get information about customer segmentation data.

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