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Jurnal Tekinkom (Teknik Informasi dan Komputer)
Published by Politeknik Bisnis Indonesia
ISSN : 26211556     EISSN : 26213079     DOI : https://doi.org/10.37600/tekinkom
Core Subject : Science,
Computer Science & IT
Jurnal TEKINKOM merupakan jurnal yang dimaksudkan sebagai media terbitan kajian ilmiah hasil penelitian, pemikiran dan kajian analisis-kritis mengenai isu Ilmu - ilmu komputer dan sistem informasi, seperti : Pemrograman Jaringan, Jaringan Komputer, Teknik Komputer, Ilmu Komputer/Informatika, Sistem Informasi, dan Multi Disiplin Penunjang Domain Penelitian Komputasi, Sistem dan Teknologi Informasi dan Komunikasi, dan lain-lain yang terkait. Artikel ilmiah dimaksud berupa kajian teori (theoritical review) dan kajian empiris dari ilmu terkait, yang dapat dipertanggungjawabkan serta disebarluaskan secara nasional maupun internasional.
Arjuna Subject : Ilmu Komputer (semua kategori) - Aplikasi Ilmu Komputer
Articles 407 Documents
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MODEL KLASTERISASI DATA PENDUDUK MENGGUNAKAN ALGORITMA K-MEANS UNTUK MENGETAHUI PRIORITAS PENERIMA BANTUAN SOSIAL DI DESA BAPINANG HULU Yunita, Selviana; Bachtiar, Lukman; Saputri, Dewi
Jurnal Tekinkom (Teknik Informasi dan Komputer) Vol 7 No 2 (2024)
Publisher : Politeknik Bisnis Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37600/tekinkom.v7i2.1588

Abstract

Central Kalimantan has a poor population of 140.04 thousand people with a poverty percentage of 5.16%. The poverty severity rate reaches a value of 0.15, with a poverty line of 506,982 IDR/Capita/Month. Bapinang Hulu Village in Central Kalimantan has around ±428,895 people in 2021. This large population makes it difficult to determine the priority of social assistance recipients, coupled with limited human resources in the village office. Data collection on social assistance recipients is still carried out based on the proposal of the RT head without proper validation, often causing social jealousy. This study aims to optimize the distribution of social assistance in Bapinang Hulu Village using the K-Means algorithm for grouping population data. The dataset consists of 246 records with 14 attributes that reflect the conditions of the head of the family in the village. The K-Means algorithm was chosen because of its ability to group data based on attribute similarities. Testing was carried out 12 times with variations in the K value to determine the optimal clustering. The results show that in the 12th test with a value of K = 13, the lowest Davies-Bouldin Index (DBI) value of 0.072 was obtained. This shows that clustering at K = 13 is optimal in terms of separation between clusters and density within clusters. Clustering helps identify community groups that need social assistance the most, provides more accurate recommendations for the priority of social assistance recipients, so that the distribution of assistance is more targeted and effective.
ANALISIS BUSINESS INTELEGENSI PENGARUH KECERDASAN EMOSIONAL TERHADAP KINERJA KARYAWAN ALGORITMA REGRESI LINIER Sitorus, Zulham; Syahputri, Maulisa; Nainggolan, Andreas Ghanneson; Sibarani, Dina Marsauli; Nahampun, Natalia; Putra, Khairil
Jurnal Tekinkom (Teknik Informasi dan Komputer) Vol 7 No 2 (2024)
Publisher : Politeknik Bisnis Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37600/tekinkom.v7i2.1215

Abstract

Prima Indonesia University is a leading private university in the city of Medan, operating in the education sector which applies Business Intelligence to its management system. This research was conducted using the Linear Regression Algorithm to measure the influence of Emotional Intelligence on Employee Performance at Prima Indonesia University, totaling 212 data. The data used in this research is employee performance history data for the last 5 years. Next, the Linear Regression Algorithm is applied to the processed dataset. The research results will later show that the Linear Regression Algorithm is able to produce quite accurate measurements. The results of this research can show how much emotional intelligence influences an employee's performance. Thus, the Linear Regression Algorithm can be a solution in evaluating the influence of Emotional Intelligence on Employee Performance, and can provide long-term recommendations for increasing the productivity of Employee Performance at Prima Indonesia University.
PENERAPAN TEKNOLOGI BUSINESS INTELLIGENCE DALAM MENINGKATKAN STRATEGI PENJUALAN DENGAN METODE OLAP PADA CAFÉ LE KAHVE Sipayung, Arif Richardo Idola; Zendrato, Nur Eni; Marbun, Timo Adelina; Telaumbanua, Jeremia Nicholas; Sihombing, Oloan
Jurnal Tekinkom (Teknik Informasi dan Komputer) Vol 7 No 2 (2024)
Publisher : Politeknik Bisnis Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37600/tekinkom.v7i2.1529

Abstract

This research aims to develop a data warehouse system and information dashboard based on Business Intelligence (BI) technology with the OLAP method to improve sales strategies at Le Kahve, a coffee shop company. The BI implementation uses Pentaho Data Integration for the ETL (Extract, Transform, Load) process and Microsoft Power BI for dashboard visualization. The ETL process is carried out to collect, process, and link sales data obtained from the Point of Sales (POS) system in Excel format. The data is then processed into a data warehouse using a star schema, which facilitates multidimensional analysis. Through the OLAP method, sales data is analyzed across various dimensions such as product, time, and payment method. The data visualization results in the form of a dashboard enable the company to quickly view sales performance and make more effective decisions. This dashboard provides information on best-selling products, product categories, and sales trends over time. The research results show that by implementing BI and OLAP, the company can improve operational efficiency, accelerate analysis, and support decision-making to enhance sales strategies and company competitiveness.
PENERAPAN METODE FORECASTING DENGAN ALGORITMA SUPPORT VECTOR MANCHINE UNTUK MEMPREDIKSI PENERIMAAN PESERTA DIDIK BARU PADA SMA ULUN NUHA Tajrin, Tajrin; Sembiring, Sinly Helpingky Sulam; Ndruru, Sabar Krismonata
Jurnal Tekinkom (Teknik Informasi dan Komputer) Vol 7 No 2 (2024)
Publisher : Politeknik Bisnis Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37600/tekinkom.v7i2.1525

Abstract

This study aims to develop a prediction model for new student admissions at Ulun Nuha High School using the Support Vector Machine (SVM) algorithm. Ulun Nuha High School faces the challenge of fluctuating numbers of applicants every year, which affects resource allocation and strategic planning. The SVM algorithm was chosen because of its ability in classification and regression, so it can identify patterns and trends from historical student admissions data. This study uses data from 100 students with 20 data as the main sample, covering four main variables: Indonesian, Mathematics, Science and Social Studies scores, and memorization. The application of the SVM algorithm in Python obtained prediction accuracy results of 100% from 20 data samples and the results of testing the prediction data resulted in students with registration number 23021 getting a pass result and students with registration number 23022 getting a failure result. The results of the study show that the SVM model can predict the number of new students with high accuracy, close to the real results from historical data. This model provides significant benefits in planning more effective, efficient, and measurable student admissions.
ANALISIS GERAKAN MATA UNTUK DETEKSI ALZHEIMER: STUDI KOMPARATIF LIMA METODE UTAMA Ziegel, Dennis Jusuf; Indra, Evta
Jurnal Tekinkom (Teknik Informasi dan Komputer) Vol 7 No 2 (2024)
Publisher : Politeknik Bisnis Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37600/tekinkom.v7i2.1598

Abstract

In the digital era, eye-tracking technology has emerged as a valuable non-invasive tool for assessing neurological and cognitive functions. This review explores five key methods for evaluating Alzheimer’s Disease (AD) using eye-tracking: fixation and saccade analysis, pupil size measurement, task-specific eye-tracking, reading task analysis, and novelty preference scores. Fixation and saccade metrics reveal significant disruptions in visual scanning and information processing in AD patients, characterized by longer fixation durations and reduced saccade frequency. Pupil size measurements indicate diminished cognitive load and emotional responsiveness. Task-specific eye-tracking, including tasks such as image description, shows difficulties in maintaining focus and interpreting visual stimuli. Reading task analysis highlights increased fixation durations and backward saccades, reflecting challenges in text comprehension and information retention. Novelty preference scores suggest reduced interest in new stimuli, correlating with cognitive decline. These findings underscore the potential of eye-tracking metrics for early detection and monitoring of AD, though variability in eye movement patterns and additional factors like sleep disorders emphasize the need for comprehensive diagnostic approaches.
PERANCANGAN BASIS DATA SISTEM PENENTUAN HARGA OPTIMAL DASTER DENGAN FUZZY LOGIC Runtukahu, Winona Charisda; Trisnawarman, Dedi
Jurnal Tekinkom (Teknik Informasi dan Komputer) Vol 7 No 2 (2024)
Publisher : Politeknik Bisnis Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37600/tekinkom.v7i2.1834

Abstract

Optimal pricing in the fashion industry can affect product competitiveness in the market such as sales levels and profits earned by the company. This research develops a web-based decision support system using the Fuzzy Logic method to determine the optimal price of negligee. The purpose of this research is to design and implement a decision support system that can help daster business actors in determining the optimal selling price. The research method used is based on the System Development Life Cycle (SDLC) with a prototyping model to develop a decision support system for analyzing the optimal pricing of daster products and analyzed using fuzzy logic methods to manage uncertainty and provide more flexible decisions based on existing data. Based on the research that has been done, it is concluded that the Fuzzy Logic-based Decision Support System (DSS) is an effective solution for managing these uncertainties, using linguistic variables such as “cheap”, “medium”, and “expensive”. As a result, this system is able to provide price recommendations that are evidence-based, fast, and responsive to market changes, thus helping businesses increase profitability and product competitiveness.
PERANCANGAN APLIKASI PERPUSTAKAAN BERBASIS MOBILE DENGAN LAYANAN FAQ MENGGUNAKAN CHATBOT Pramudya, Fillah Aby; Aji, Adam Sekti
Jurnal Tekinkom (Teknik Informasi dan Komputer) Vol 7 No 2 (2024)
Publisher : Politeknik Bisnis Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37600/tekinkom.v7i2.1336

Abstract

This study explores the development of a mobile-based library application equipped with an FAQ chatbot to enhance the efficiency of library management at SMA Negeri 2 Tumijajar. The application is designed to facilitate user access to library services such as book searches, borrowing, and returning, while also providing automated responses to frequently asked questions. The research employs the Research and Development (R&D) method, encompassing several stages: needs analysis, design, development, testing, and evaluation. Testing results indicate that the application features an intuitive interface, functions effectively across various devices, and is regarded as user-friendly by both library staff and students. Furthermore, the chatbot service has proven to be effective in addressing common inquiries, thereby reducing the workload of library staff. The study concludes that the mobile-based library application with an FAQ chatbot significantly improves the efficiency of information services and library management. Recommendations for future research include optimizing chatbot algorithms and enhancing application compatibility with various devices.
SISTEM PENDUKUNG KEPUTUSAN PENERIMAAN PEGAWAI BIRO AKADEMIK MENGGUNAKAN MOOSRA Pertiwi, Nur Fajar Kurnia; Munthe, Ibnu Rasyid; Sihombing, Volvo
Jurnal Tekinkom (Teknik Informasi dan Komputer) Vol 7 No 2 (2024)
Publisher : Politeknik Bisnis Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37600/tekinkom.v7i2.1538

Abstract

This study aims to design and develop a decision support system (DSS) for the employee selection process at the academic bureau of Labuhan Batu University using the MOOSRA method. The main issue faced is the use of subjective and non-standardized traditional selection methods, which can reduce the accuracy and efficiency in selecting the right candidates. The method applied in this study is MOOSRA, which can process various selection criteria such as educational qualifications, work experience, information technology skills, communication skills, and discipline. The results of the calculation of values ​​and rankings indicated that alternative A4 was the best candidate, followed by A9 and A1. The results of the study indicate that the use of the MOOSRA method in the decision support system can provide more objective and efficient recommendations in the employee selection process at the academic bureau of Labuhan Batu University.
IMPLEMENTASI SISTEM ANTRIAN ONLINE PADA DUKCAPIL KLATEN MENGGUNAKAN METODE USER CENTERED DESIGN (UCD) Raharjo, Agus Budi; Aji, Adam Sekti
Jurnal Tekinkom (Teknik Informasi dan Komputer) Vol 7 No 2 (2024)
Publisher : Politeknik Bisnis Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37600/tekinkom.v7i2.1748

Abstract

The Population and Civil Registration Office (Dukcapil) has an important role in providing public services related to the processing of population documents. In Klaten Regency, people often face problems in taking care of legal identity documents at the Dukcapil, such as long and disorganized queues. The queuing system that is still done manually is considered less efficient and prone to fraud. The community also has difficulty in monitoring the order of the queue, so they have to wait a long time without certainty when they will be served. To overcome these problems, an integrated and computerized online queue information system is needed. This research aims to design and build an online queue information system at the Klaten Regency Dukcapil using the User Centered Design method. This system can provide better, efficient, and transparent services to the community. System development uses the Kotlin programming language and MySQL database. Black box testing is also carried out to find out the errors that exist in the system. Through the online queuing system, people can take queue numbers online and monitor the queue sequence in real time, thus providing convenience and comfort in accessing Dukcapil services. Thus, the quality of public services, especially in the processing of population documents, can be improved.
PERBANDINGAN PENERAPAN ALGORITMA K-MEANS DAN FUZZY C-MEANS DALAM ANALISIS CLUSTERING TERHADAP PERGERAKAN HARGA HISTORIS SAHAM BANK RAKYAT INDONESIA Purba, Winda Nia; Hartanto, Ricky
Jurnal Tekinkom (Teknik Informasi dan Komputer) Vol 7 No 2 (2024)
Publisher : Politeknik Bisnis Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37600/tekinkom.v7i2.1214

Abstract

This study aims to analyze and compare the application of K-Means and Fuzzy C-Means algorithms for clustering historical stock price movements of Bank Rakyat Indonesia (BRI). Clustering is a method that groups data based on similarities, crucial in stock data analysis to aid more precise investment decision-making. The K-Means algorithm deterministically assigns each data point to a single cluster, while Fuzzy C-Means allows partial membership across multiple clusters, offering greater flexibility. The research findings indicate that the K-Means algorithm forms three primary clusters with a Silhouette Score of 0.4667, which defines clusters more clearly than Fuzzy C-Means, which has a score of 0.4199. The clusters produced by K-Means provide better-defined separations among stocks with medium, high, and low prices, based on price movements and transaction volume. In contrast, Fuzzy C-Means, despite its ability to handle overlapping data, results in less clearly defined clusters compared to K-Means. Based on these results, the K-Means algorithm is deemed more effective for clustering analysis in the context of BRI stocks. This research is expected to contribute to the development of more comprehensive stock movement analysis models and support investors in making better-informed investment decisions.

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