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Journal of Intelligent Software Systems
Published by Universitas Teknologi Digital Indonesia
ISSN : -     EISSN : 29627702     DOI : https://doi.org/10.26798/jiss
Core Subject : Science,
Computer Science & IT
Journal of Intelligent Software Systems (JISS) is open access, peer-reviewed international journal that will consider any original scientific article that expands the field of Intelligent Software Systems. The journal publishes articles in all Intelligent Software Systems specialities of interest to Intelligent Software Systems, physicians, and researchers.
Arjuna Subject : Ilmu Komputer (semua kategori) - Kecerdasan Buatan
Articles 5 Documents
 1 
Search results for , issue "Vol 3, No 2 (2024): December 2024" : 5 Documents clear
BUSINESS INTELLIGENCE FOR DETERMINING PROMOTIONAL MEDIA Alvianingrum, Ante Wahyu; Sari, Dini Fakta; Syadziliy, Abil Hasan Ali Asy; Supriatin, Supriatin; Nur’aini, Nur’aini
Journal of Intelligent Software Systems Vol 3, No 2 (2024): December 2024
Publisher : LPPM UTDI (d.h STMIK AKAKOM) Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26798/jiss.v3i2.1505

Abstract

Abstract—In 2021-2022, SMK Dirgantara Putra Bangsa experienced a decrease in the number of prospective students who registered. This condition encourages schools to innovate and be creative in choosing effective promotional media in disseminating information on New Student Admissions (PPDB) to the public widely and routinely, with the aim of attracting more new students. This promotional effort involves the use of various types of promotional media. Business intelligence plays a role in processing organizational data into useful information to improve performance, by analyzing historical data which is then used to support decision making and planning. The K-Means algorithm is one of the clustering methods that is often used because of its ease of implementation and its ability to minimize the sum of squared error (SSE) value between data and the specified centroid. The collaboration between Business Intelligence and K-Means clustering is expected to help SMK Dirgantara Putra Bangsa in choosing the right promotional media and creating new innovations in disseminating PPDB information to the public.Keywords— PPDB, Business intelligence, K-Means clustering, Media Promosi
Lecture Scheduling Using Genetic Algorithm Method Liyan, Sur; Kriestanto, Danny; Ramadhan, Alfitra; Haries, Muhammad; Lukman, Lukman
Journal of Intelligent Software Systems Vol 3, No 2 (2024): December 2024
Publisher : LPPM UTDI (d.h STMIK AKAKOM) Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26798/jiss.v3i2.1501

Abstract

Lecture scheduling at a university is a very important element, because it determines the progress of the lecture activity process. At the Indonesian Digital Technology University, the lecture scheduling process still uses Microsoft Excel, this is considered less than optimal because it takes a relatively long time, the process is long and requires a high level of accuracy, which is something that often becomes an obstacle in the scheduling process. The genetic algorithm is an algorithm that can be used to solve problems on a large scale and with a high level of complexity, such as lecture scheduling. Genetic algorithms have advantages over other optimization methods, namely that genetic algorithms can optimize problems with complex problems and a very wide search space. There are several stages in a genetic algorithm, namely: initial population initialization, fitness evaluation, selection, crossover and mutation. The results of this research show that scheduling lectures using the genetic algorithm method results in faster and more accurate results, because the process is carried out by the program by finding the best solution from each generation iteration and the process will stop when the required solution is obtained. Meanwhile, scheduling lectures using MS Excel takes longer because it is done manually with the help of the VLOOKUP formula and requires a high level of accuracy so that there are no conflicting lecture schedules. From the test results, using Python software with a genetic algorithm takes 0.609356 seconds with an accuracy level of 100%. Meanwhile, testing using MS Excel with VLOOKUP takes around 20 minutes with an accuracy rate of 95%.Keywords— Scheduling, Lectures, Genetic Algorithm
Performance Assessment of Branch Office Assistant (KCP) Leaders Using the Simple Additive Weighting Method Wibowo, Dwi; Astuti, Femi Dwi; Astuti, Yuli; Widayani, Wiwi; Fauzi, Arma
Journal of Intelligent Software Systems Vol 3, No 2 (2024): December 2024
Publisher : LPPM UTDI (d.h STMIK AKAKOM) Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26798/jiss.v3i2.1502

Abstract

Abstract— Performance Appraisal is a process that allows organizations to know, evaluate, measure and assess the performance of their members appropriately and accurately. This activity is closely related and influences the effectiveness of the implementation of human resource activities in the company, such as promotion, compensation, training, career management development and others. This is because the performance appraisal function can provide important information to the company to improve decisions and provide feedback to employees about their actual performance.The implementation of the achievement and performance appraisal of KCP leaders at KSPPS Tunas Artha Mandiri Nganjuk Branch has so far still used manual and has not used a decision support sistem so that the data generated is not accurate and takes a long time. As a result, if used in decision making, it is not appropriate and causes problems such as non-transparent management, decreased quality and performance of KCP leaders. The author applies and implements the Additive Weighting method (SAW) to measure the achievement and performance assessment of the Sub-Branch Office leadership at KSPPS Tunas Artha Mandiri Nganjuk Branch. With the aim of this decision support sistem can provide information and recommendations as well as accurate and efficient performance appraisal data.Keywords-Decision Support Sistem, Simple Additive Weighting, Employee Appraisal
Metadata Forensic Analysis as Support for Digital Investigation Process by Utilizing Metadata-Extractor Arizona, Nanda Diaz; Nugroho, Muhammad Agung; Syujak, Ahmad Rois; Saputra, Rizqi Kurniawan; Sulistyowati, Istri
Journal of Intelligent Software Systems Vol 3, No 2 (2024): December 2024
Publisher : LPPM UTDI (d.h STMIK AKAKOM) Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26798/jiss.v3i2.1503

Abstract

Abstract — The rapid development of technology in the current era, in addition to providing positive impacts, certainly also has negative impacts. In Indonesia, based on data from the Cyber Crime Directorate (Dittipidsiber) website, the crime rate related to the ITE Law (Information and Electronic Transactions) is increasing day by day. This encourages digital forensic investigators to be able to develop a concept or method that can be adjusted to digital cases, for example cases of digital data manipulation such as photos or documents. Metadata is an information structure that describes, explains, places in a place or makes it easier to find something, use or manage and sources of information. Metadata can also be interpreted as data about data or information about information. One method or approach that can be done in cases of digital files (photos, videos or documents) can be done using forensic metadata analysis. This is because metadata stores information related to a file. By developing a library from java (metadata-extractor) based on open source and developed in the Netbeans 8.0 application, it will make it easier for an investigator or forensic investigator to conduct a forensic metadata approach, which is expected from the results can be used as valid evidence in the digital forensic investigation process. Keywords – Metadata, Digital Forensics, Cyber Crime, Metadata Analysis, Digital Evidence
BUILDING DATA WAREHOUSE FOR EMPLOYEE TRAINING MINISTRY OF LAW AND HUMAN RIGHTS Nugroho, Ari Fauzi Mukti; Kartadie, Rikie; Handayani, Latifah Nurrohmah; Isnaeni, Nenen; kholik, Moh. Abdul
Journal of Intelligent Software Systems Vol 3, No 2 (2024): December 2024
Publisher : LPPM UTDI (d.h STMIK AKAKOM) Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26798/jiss.v3i2.1500

Abstract

In order to improve and expand each employee's competency and knowledge, education and training are crucial for the Ministry of Law and Human Rights. They may also be utilized for employee mapping. In the past, it was necessary to gather data on things like the number of employees who attended a particular training, which training had reached its participant quota, and the number of graduates in each training. This required extensive processing and repeated cross-checking of data sources to make sure the data was accurate and legitimate before it could be compiled into a table for analysis. Information technology may be used to immediately process employee competence data and education and training results into information. Therefore, it is expected that the Nine Step method, which is part of the Kimball & Ross (2010), methodology will simplify and accelerate the process of processing training data into information presented for analysis and reporting purposes at the leadership level in each work unit. Keywords: data warehouse, OLAP, ETL, pentaho, kemenkumham, training 

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