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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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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.
ESTIMASI HARGA SEWA ALATBERAT MENGGUNAKAN LINEAR REGRESSION PADA PT FANBEL JAYA BERSAMA Deason Tanduri; Tri Agus Setiawan
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.v6i1.733

Abstract

PT Fanbel Jaya Bersama is a company engaged in the construction sector, especially heavy equipment rental. The rental price of PT Fanbel Jaya Bersama needs to be implemented to process heavy equipment rental data using a linear regression algorithm. This study uses a simple linear regression method to find the estimated price that is rented out to consumers. For deployment using a chatbot that displays estimates and data in the form of descriptions of suitable datasets displayed to consumers. In this study, 2 independent variables were used, namely the unit of minutes of rent (X) and the dependent variable, namely the rental price (Y). From the 9 processed data, the RMSE value is 3100946.073781. From this study the linear regression algorithm is accurate and precise. The results of this study display prices that have been predicted by chatbots for consumers who want to look for heavy equipment. Further development will be promoted through the website with the same simple linear regression method and more data from other universities.
PENGOLAHAN DATA EKSPOR TERHADAP RAGAM PRODUK KELAPA SAWIT MENGGUNAKAN METODE ASSOCIATION RULES Robert Robert; Siti Aisyah; Sasmita Rahmawati Zebua
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.v6i1.735

Abstract

Palm oil is used as a raw material for producing cooking oil, industrial oil, and fuel. Indonesia is the largest producer of palm oil in Indonesia. One of a company engaged in the production of palm oil is PT Permata Hijau Group. The company produces a wide range of palm oil products from from Palm Oil, Lauric Oil, Biodiesel, and Fatty Acid Oleo. Look at the variety of products palm oil marketed by PT Permata Hijau Group, it is necessary to do so decision making on palm oil product data. Data mining is applied using the Association Rules method to get support and confidence values, where export data processed using this method can determine which particular refined palm oil products are best-selling in the international market. With the Association Rules method, it is hoped that it can help provide an overview for a company in determining the amount of production of certain types of refined palm oil, so crises or excesses of certain processed palm products can be avoided. In this study, the results of data visualization using the Python Library (Matplotlib & Seaborn), products with the item set Glycerine→Stearic Acid and Glycerine-RBDPO→Stearic Acid are the combination of Association Rules that appear most frequently, with 100%. Whereas the combination HPKO→Stearic Acid meets the Association Rules with a value of 94%, RBDPO-HPKO→Stearic Acid and Fatty Acid- HPKO→Stearic Acid with 90%, Glycerine→RBDPO, Glycerine→RBDPO-Stearic Acid, and Glycerine Stearic Acid→RBDPO with 88%, HPKS→Stearic Acid and RBDPO-Fatty Acid→Stearic Acid with 83%. Therefore, processed coconut Palm Glycerine, RBDPO, Stearic Acid, Fatty Acid, HPKO, and HPKS is a product that satisfies the rules of the association so this result can assist the company in determining the amount of product production given the demand for a combination of various processed coconut products of the palm oil, is higher than the variety of refined palm oil other products.
PENERAPAN SISTEM PENDUKUNG KEPUTUSAN TERHADAP PENENTUAN PEMINATAN PADA PROGRAM STUDI TEKNIK INFORMATIKA MENGGUNAKAN METODE ARAS Yuyun Dwi Lestari; Arief Budiman; Dedy Irwan
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.v6i1.885

Abstract

The selection of specialization is carried out by students of the Informatics Engineering study program while still in semester 5, namely Multimedia & Computer Vision, Network & Computer Systems, Robotics & Intelligent Systems. The selection of this specialization is carried out by students so that students focus on 1 specialization only and this specialization is carried out based on elective courses, so that students are not wrong in choosing their interests and do not follow the interests chosen by their friends. The purpose of this study is as an alternative to support students to determine the specialization in accordance with the criteria and calculate the value of each criterion to choose an interest and make a decision support for the selection of specialization to help students choose the right specialization according to the criteria quickly and precisely. Therefore, in the selection of student specialization in the Informatics Engineering study program requires a Decision Support System by applying the ARAS method. The results obtained from this study are the specialization of Network & Computer Systems in rank 1 with a value of 0.83554. Multimedia & Computer Vision ranked 2nd with a value of 0.78358. Robotics & Intelligent Systems ranked 3rd with a value of 0.77223. So that the specialization of Network & Computer Systems will be an alternative.
SISTEM PENDUKUNG KEPUTUSAN REKOMENDASI TEMPAT KOST UNTUK MAHASISWA DI KOTA SAMPIT Lukman Bachtiar; Fendy Fendy
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.v6i1.833

Abstract

The number of students who want to continue their education makes students even leave their hometowns just to get a better education. This can make students look for a temporary place to live while studying or lecturing. There are several factors that make them prefer boarding houses as a temporary residence. A boarding house is a residence that is rented out to other parties with certain facilities at a more affordable price compared to hotels/inns. The number of boarding houses that offer different prices, facilities and have different locations will certainly make students confused in terms of determining the temporary residence they occupy. So, the decision support system by applying the profile matching DSS method is expected to help solve alternative housing problems for students or the general public. And also, with the results of research conducted can show that the profile matching method has good accuracy in providing boarding options for students. From the results of calculations using 5 alternatives, the highest total value or final value is obtained in alternative boarding house 2 with a total value of 9.398.
PERANCANGAN SISTEM INFORMASI MEDICAL CHECK UP BERBASIS WEB DENGAN FRAMEWORK CODEIGNITER 4 MENGGUNAKAN METODE WATERFALL Luqmanul Hakiym Maulana; Nuril Lutvi Azizah; Ade Eviyanti
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.v6i1.760

Abstract

The purpose of this research is to develop a web-based Medical Check-Up information system using CodeIgniter 4 framework and implementing the waterfall development method. This system is designed to facilitate administrative management and provision of medical services to patients. Rsu Al-Islam Hm Mawardi Krian Sidoarjo currently uses manual methods in the administration of medical check-ups, which poses several risks in data processing between hospital units. Therefore, this research is conducted to address these issues. The waterfall method is used for the system development stages, including requirements analysis, design, implementation, testing, and maintenance. The requirements analysis phase involves identifying needs such as patient registration and examination results. System design includes database structure, user interface, and business logic to be implemented in the system. Implementation utilizes the CodeIgniter 4 framework, which provides tools and features for web application development. The results of this research align with the hospital's requirements, including patient registration, recording, and delivery of laboratory, radiology, and doctor examination results, which have been tested using the black box method. It is expected that this developed Medical Check-Up information system can enhance the efficiency of the check-up process, expedite patient examination access, and improve the overall quality of healthcare services.
KLASIFIKASI DAGING SAPI DAN DAGING BABI MENGGUNAKAN ARSITEKTUR EFFICIENTNET-B3 DAN AUGMENTASI DATA Maulana Junihardi; Jasril jasril; Suwanto Sanjaya; Lestari Handayani; Fadhilah Syafria
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.v6i1.845

Abstract

The increasing demand for beef has made its price soar. the traders then mix beef with pork to get more profit. There is a technology in the field of informatics that can be used to differentiate beef, pork and mixed meat. This research was conducted to find out the difference between beef, pork and mixed meat. In this study, a deep learning convolutional neural network with the EfficientNet-B3 architecture is used for image identification to distinguish between beef and pork. 9000 images have been divided into three categories: mixed meat, pork and beef. This study compares the classification results using original data and data augmentation. The data augmentation models used are brightness, rotation, and horizontal and vertical inversion. Data is split 80:20 and 90:10 for training and testing respectively. The best results are achieved by using a division ratio of 90:10 on image data with augmentation which has a learning rate of 0.01 and Adamax Optimizer which has accuracy, precision and recall levels of 98.66%, 98.67% and 98.66%.
ANALISIS DATA MINING UNTUK PENGARUH KUALITAS PELAYANAN, PENGIKLANAN, DAN HARGA TERHADAP KEPUTUSAN KONSUMEN DALAM MEMILIH PENJUAL ONLINE Elfrin Hulu; Yonata Laia; Naomita Sihombing; Wandry Sitorus; Yuliani C. Simanjorang
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.v6i1.878

Abstract

Almost everyone uses this buying option when selling online, for example, home appliances, fabrics, and many other products sold online. Some consumers complain that the service is still ineffective, and scams pretending to sell products sold through the site are common. As this study shows, many of the jobs humans do today can be done by computer systems. This study explores how to identify optimal online sales sites using the K-NN method. The aim is to prevent consumers from making mistakes when shopping online. It is hoped that this system will help visitors find simple and useful websites. All human activity must be innovative. This research has solved this problem and enabled the construction of an easy-to-use system. Based on calculations of load speed 2, page structure 3, interesting titles and content 4, short and recognizable links 5, and the results are useful.
PENERAPAN DATA MINING UNTUK MENENTUKAN PEMBERIAN BANTUAN KELOMPOK TANI MENGGUNAKAN ALGORITMA C.50 PADA DINAS PERKEBUNAN SUMATERA UTARA Saut P Tamba; Jodi Daniel Pransisko Manalu; Villa Delfya Sarumaha; Erika Girsang; Verli Vernando S Colia; Putra Edi Mujahid
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.v6i1.890

Abstract

The Plantation Service is an implementing element of the regional autonomy of the Provincial Government led by a head of service who is domiciled under and responsible to the governor through the regional secretary. The duties of the plantation office include carrying out the function of formulating policies in the fields of plantation production, plantation protection, farming, plantation business facilities, licensing implementation, guidance, assistance in the plantation sector. The plantation office is ready to grow young agricultural entrepreneurs by providing business capital assistance to the community and farmer groups every year. With the existence of farmer group capital assistance, it will create more young farmers who will change the image of farmers, farmer group assistance is one of the activities in order to realize the regeneration of farmers designed for the development, skills, and entrepreneurial spirit of the younger generation in agriculture. problems that occur in providing farmer group assistance, one of which is still the provision of assistance that is not on target, causing the provision of assistance not to people who need help, so that the utilization of this assistance is not optimal. In addition, the provision of assistance is done manually, making it less efficient in any way. To overcome these problems, a system is needed that can help assess real and objective prospective beneficiaries. This assessment uses calculations based on the criteria for prospective beneficiaries with the highest ranking system. In this system, the calculation is done using datamining with the C5.0 algorithm. In testing the methods and algorithms in this study, it produces a decision tree with the first root of information and technology services, then the next root is bookkeeping administration, then the last rood is routine meetings. With the root, researchers can decide which farmer groups receive assistance. the results of the decision tree are implemented into the RStudio programming language.

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