cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
Sarida Sirait
Contact Email
saridasrt@gmail.com
Phone
+6281319494217
Journal Mail Official
saridasrt@gmail.com
Editorial Address
Jl. Sriwijya No. 9 C-E Pematangsiantar, Sumatera Utara
Location
Kota pematangsiantar,
Sumatera utara
INDONESIA
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 33 Documents
 1   2   3   4 
Search results for , issue "Vol 6 No 1 (2023)" : 33 Documents clear
ANALISIS MACHINE LEARNING ALGORITMA REGRESI LINEAR UNTUK MEMPREDIKSI SAHAM DI BANK BRI DI BURSA SAHAM INDONESIA Yenni Syahfutri Sipahutar; Ibnu Rasyid Munthe; Syaiful Zuhri Harahap
Jurnal Tekinkom (Teknik Informasi dan Komputer) Vol 6 No 1 (2023)
Publisher : Politeknik Bisnis Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37600/tekinkom.v6i1.747

Abstract

Stocks are securities that have fluctuating characteristics. Therefore stock predictions are needed to determine stock prices in the future. The data used is actual data obtained from the Indonesian Stock Exchange. This study uses the CRISPDM model and uses the Linear Regression method in processing the data. Data processing is carried out using several techniques, namely manually (exel) and by application testing. The application used is Rapid Miner. And after testing, get the test results of a difference of 0 to 3%. And get a root mean square error (RMSE) value of 62.592. and based on the research, it was decided that the share price on January 4 2021 - December 9 2022 will experience stock price fluctuations in the future with a difference of 0 to 3% from the previous share price.
PENERAPAN DATA MINING METODE APRIORI DALAM ANALISIS KECENDRUNGAN PEMBELIAN KONSUMEN GROCERY SHOP Erlin Elisa; Tukino Tukino; Koko Handoko
Jurnal Tekinkom (Teknik Informasi dan Komputer) Vol 6 No 1 (2023)
Publisher : Politeknik Bisnis Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37600/tekinkom.v6i1.817

Abstract

Wholesale stores are a promising retail business today, judging from the movement of their businesses which are increasingly loved by the public because prices are relatively cheaper compared to supermarkets, supermarkets and minimarkets, this business must be able to meet consumer demand so that they are not inferior to similar businesses, including In managing the placement of types of goods on shelves, so far transaction data has been left unattended without being utilized to obtain new information. This study aims to apply the Apriori algorithm datamining technique in analyzing consumer purchasing tendencies at one of the Grocery Shops in Cipta Asri housing, the method used is an in-depth analysis of customer transactions on data that is already owned and data comes from various sources of information. The results obtained from processing sales transaction data in the form of itemset with the application of the concept of datamining association analysis are known to have a support value of 20% and 80% confidence, the results obtained where the combination of goods that are often purchased with Milk, Rice and snacks with each support value of 22.39 %, 83.33% confidence then Rice, Soft drink and Snack support value of 20.90%, Confidence 73.68%.
PENGONTROLAN LAMPU DENGAN ANDROID BERBASIS MIKROKONTROLER VIA HOTSPOT MENGGUNAKAN VOICE RECOGNITION Yusran Yusran; Dwi Winarti; Ellbert Hutabri; Koko Handoko
Jurnal Tekinkom (Teknik Informasi dan Komputer) Vol 6 No 1 (2023)
Publisher : Politeknik Bisnis Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37600/tekinkom.v6i1.827

Abstract

Smart living is a living concept that is based on practicality and efficiency but still upholds comfort. In line with the high mobility of big city people who have a fast-paced and practical lifestyle, smart living is the solution, especially by utilizing technology in housing. One of the uses of residential technology is controlling lights using hardware and designing software using the Arduino IDE so that later the lights can be controlled using a smartphone owned by the user using voice recognition. Voice recognition is the concept of controlling electronic equipment using the user's voice. The application of this control system becomes more efficient in saving time and effort because you don't have to walk to every room to turn off or turn on the lighting, users can use the Google Assistant application on an Android-based smartphone with the turn on the light one command. The results of the designed tool are able to provide practicality and efficiency for its users because it can control the lights remotely.
ANALISIS METODE TREND MOMENT DALAM FORECASTING UNTUK MEMPREDIKSI JUMLAH PENJUALAN PADA RESTORAN AYAM GEPREK GOKIL Rizky Prayoga; Anita Anita; Josua Silaban; Saut Parsaoran Tamba
Jurnal Tekinkom (Teknik Informasi dan Komputer) Vol 6 No 1 (2023)
Publisher : Politeknik Bisnis Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37600/tekinkom.v6i1.892

Abstract

Predictions are things that might be done so that actions taken in the future are more effective and efficient. Predictions in sales are absolutely necessary so that companies / institutions can avoid big losses. Gokil Chicken Resto is a company engaged in the culinary field. Even though it is a Resto brand, it must have a business license in the form of a CV so that it can be said to be a company. The Gokil Chicken Resto has a problem, namely in the loss of procuring raw materials to be produced in a culinary menu called Gokil Geprek Chicken. In a condition, sometimes the procurement of these materials will be left quite a lot or even run out. This causes losses in terms of cost and also consumer disappointment as well. For this reason, research is needed in the form of sales predictions so that it can help minimize losses by procuring materials that are more effective and efficient. This study uses the trend moment method in analyzing sales to produce predictive numbers. The method of precise prediction accuracy uses MAPE (Mean Absolute Percentage Error). The accuracy of the prediction accuracy obtained is 99.36%.
IMPLEMENTASI FRAMEWORK COBIT 2019 PADA AUDIT TATA KELOLA SISTEM INFOMASI PADA DINAS PENANAMAN MODAL DAN PTSP KOTA X Ni Luh Putu Yuliandri; I Gede Putu Krisna Juliharta; Ni Made Estiyanti
Jurnal Tekinkom (Teknik Informasi dan Komputer) Vol 6 No 1 (2023)
Publisher : Politeknik Bisnis Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37600/tekinkom.v6i1.713

Abstract

Investment Service and PTSP City X information technology governance audit aims to map the maturity level of IT processes. Information system governance should be evaluated to determine the institution conditions regarding IT performance management to control quality. The framework is one that can assist in assessing the performance of the underlying information technology. The development of information system governance is supported by a governance information system framework. The audit in this study uses the 2019 COBIT framework which focuses on the use of IT systems, the maturity level of available services, and administrative services through information systems. Based on the maturity obtained, the EDM04, APO07, APO11, and DSS03 processes are carried out. The EDM04 process is at level 3 (established process), APO07 is at level 2 (managed process), APO11 is at level 2 (managed process), and DSS03 is at level 4 (predictable process) with an average capability gap of 2.25. The results of these procedures can be said that the services provided by Investment Service and PTSP City X have been carried out with largely achieved status, but not yet in the best condition, allowing for the implementation of suggestions and improvements as well as the level of ability to be measured again as a comparison tool.
PENERAPAN DATA MINING CLASSIFICATION UNTUK DATA PASIEN COVID- 19 MENGGUNAKAN METODE NAÏVE BAYES Tessalonika Siahaan; Yonata Laia; Manusun Silitonga; Friska Claudia Pasaribu
Jurnal Tekinkom (Teknik Informasi dan Komputer) Vol 6 No 1 (2023)
Publisher : Politeknik Bisnis Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37600/tekinkom.v6i1.879

Abstract

Covid-19 is an infectious disease caused by a new coronavirus discovered in 2019, hereafter Sars-Cov 2 (Severe Acute). Coronavirus Respiratory Syndrome 2). This virus is very small in size (120-Knowledge is participants' understanding of a given topic. Knowledge is the ability to receive, store and use information, influenced by experience and skills. This research creates a system that can help anyone who wants to know what causes are behind the increasing spread of bacteria in the form of viruses. Therefore, it is necessary to find out what factors have caused the increase in the number of people infected with this deadly virus. Using the Naive Bayes method, researchers identified the factors causing the increase in the number of medical records for Covid-19 patients. The results obtained are based on attributes that have values, so the Bayesian value is 19.8714.
SISTEM INFORMASI MANAJEMEN MLIJO BERBASIS WEBSITE DAN MOBILE Fery Febbyanto; Irwan Alnarus Kautsar; Uce Indahyanti
Jurnal Tekinkom (Teknik Informasi dan Komputer) Vol 6 No 1 (2023)
Publisher : Politeknik Bisnis Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37600/tekinkom.v6i1.825

Abstract

The term "Bakul Mlijo" is used by the people in Mojokerto to refer to itinerant vegetable traders because they generally use carts or baskets (baskets) as a place to put their wares. The term "Mlijo" probably comes from the Javanese language which means "profit". Mobile vegetable traders are a retail business that is included in the non-store retailer category (direct selling) which sells basic necessities such as vegetables, fruits and fish which are sold directly to the end consumer. The main purpose of development research is the development of new products or innovations and their effectiveness in achieving the goals set. Therefore, the R&D method is a very useful research method in product or tool development, including in tool design research and tool testing as described in the question. Bakul Mlijo uses information system technology for customer satisfaction. Mlijo customers shop easily and without much time and can make purchases using payment methods. This system can facilitate mlijo operations such as answering questions about prices and so on, because all information related to goods has been prepared in the mlijo application. This research contributes to the development of services to customers and facilitates the marketing of Bakul Mlijo merchandise.
PREDIKSI MATA UANG KRIPTO MENGGUNAKAN METODE ALGORITMA LINEAR REGRESSION Matthew Oullanley Lee; Delima Sitanggang; Evta Indra
Jurnal Tekinkom (Teknik Informasi dan Komputer) Vol 6 No 1 (2023)
Publisher : Politeknik Bisnis Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37600/tekinkom.v6i1.757

Abstract

Cryptocurrencies are advanced monetary standards planned to operate as a medium of exchange over a arrange that's free of a central specialist, such as a government or bank. Cryptocurrencies have a tendency for price changes to occur which fluctuate like conventional currencies which can cause shifts in the market. This shift can affect cryptocurrencies, especially asset owners. The goal in this research is to predict data and provide accurate results to help cryptocurrencies players. In the process, web scraping is used to retrieve data This study will visualize the data in the form of a line chart by employing the linear regression algorithm to forecast the price movement of cryptocurrencies. nonetheless, digital forms of money costs can't be isolated from outside elements, for example, the conversion standard of rupiah against unfamiliar monetary forms. There are a lot of influencing factors, like when there is more demand than there is supply. The rise in bitcoin's price from $ 19,616.81 to $ 25,995.91 is evidence of this. A rise in market capital from $ 375,367,382,007.85 to $ 504,341,343,850 also helped. A cryptocurrency's demand is proportional to its market capitalization, which indicates how dominant it will be in the stock market. The daily return is another indicator that cryptocurrency movements can be either positive or negative.
ANALISIS KESEHATAN MENTAL MAHASISWA UNIVERSITAS KRISTEN SATYA WACANA MENGGUNAKAN METODE CLUSTERING ALGORITMA K-MEANS Timothy Garry Van Solang; Adi Nugroho
Jurnal Tekinkom (Teknik Informasi dan Komputer) Vol 6 No 1 (2023)
Publisher : Politeknik Bisnis Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37600/tekinkom.v6i1.641

Abstract

Mental health and machine learning technology that are trending among students provide a presentation that mental health awareness and technology use will have an impact in the future. This research aims to provide awareness of Satya Wacana Christian University data about mental health that can be identified using machine learning technology. The use of K-Means Clustering in clustering has been done in various types of research. Mental health scale that can recognize the state felt by Satya Wacana Christian University students based on answers to questions. The answers are in the form of a numeric scale, so the data is used in Orange3 for clustering using the K-Means algorithm. Analysis on the scale data of UKSW students who have 32 data has a silhouette k = 3 in cluster 1 of the depressed category has the results of 11 students seen in the 2018 batch and above in the depressed category and 1 data of 2020 batch students. In cluster 2 has 12 data which has the results of the 2018, 2019 and 2020 generations in the prosperous category. Cluster 3 of the harmonious category has data on 9 students whose classes are various in 2017, 2018 and 2019. The results in each cluster provide an overview of the effect of batch on mental health where many of the early year batches are in the prosperous category then the depressed category with the 3rd year batch and there are students who are able to balance their mental health with harmonious categories scattered in each batch.
ANALISIS PEMBERIAN INSENTIF TENAGA MEDIS MENGGUNAKAN ALGORITMA K-MEANS CLUSTERING Dwi Cahya Prana Ginting; Jonggi Samuel Parluhutan Sihombing; Nia Natalia Aritonang; Ribka Patricia Sinaga; Winda Nia Purba
Jurnal Tekinkom (Teknik Informasi dan Komputer) Vol 6 No 1 (2023)
Publisher : Politeknik Bisnis Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37600/tekinkom.v6i1.858

Abstract

Intensive funds are very important for health workers in caring for Covid-19 patients. Researchers conducted research using a dataset from a list of names of health workers at the puskesmas who were proposed to get intensive handling of Covid-19 in the city of Medan. One of the stages for preprocessing the data set is carried out using the application of the linear regression method. The researcher uses several k means clustering algorithms so that from this process the results can be obtained for anyone who deserves intensive handling of the Covid-19 pandemic. The algorithms used include Decision Tree C4.5, K-Nearest Neighbor, Naive Bayes, C4.5 Algorithm, K-Means clustering, Online Analytical Processing. The researcher conducted a test using a data mining tool, namely with RapidMiner version 9.0 using the K-means Clustering Algorithm method, data results from RapidMiner that have been connected to the K-Means Clustering method and obtained predictive results from data obtained from health workers 2019-2022. In this study using a dataset from a list of names of health workers at the puskesmas who were proposed to get incentives for handling the Covid-19 disease pandemic in Medan City. The data was obtained from the results of the list of names of health workers at the puskesmas from 2019-2022. The dataset preprocessing stage is carried out using the application of the Linear Regression Method. Based on the results of Cluster officers, the total number of data is 279, there are 5 clusters, which consist of Cluster 0, Cluster 1, Cluster 2, Cluster 3 results. There are 6 officers who get incentives of Rp. 3,000,000, 44 officers get incentives of Rp. 4,000,000 and 229 officers who received Rp. 5,000,000. The results of this analysis obtained Cluster 0: 93 items, Cluster 1: 83 items, Cluster 2: 91 items, Cluster 3: 2 items, Cluster 4: 10 items and a total number of times 279.

Page 2 of 4 | Total Record : 33

 1   2   3   4 

Filter by Year

2023 2023


Reset
Filter By Issues
All Issue Vol 8 No 1 (2025) Vol 7 No 2 (2024) Vol 7 No 1 (2024) Vol 6 No 2 (2023) Vol 6 No 1 (2023) Vol 5 No 2 (2022) Vol 5 No 1 (2022) Vol 4 No 2 (2021) Vol 4 No 1 (2021): Jurnal Tekinkom Vol 3 No 2 (2020) Vol 3 No 1 (2020) Vol 2 No 2 (2019) Vol 2 No 1 (2019) Vol 1 No 2 (2018) Vol 1 No 1 (2018) More Issue