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Sarida Sirait
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Jl. Sriwijya No. 9 C-E Pematangsiantar, Sumatera Utara
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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 21 Documents
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Search results for , issue "Vol 5 No 1 (2022)" : 21 Documents clear
IMPLEMENTASI ALGORITMA DECISION TREE C4.5 DENGAN IMPROVISASI MEAN DAN MEDIAN PADA DATASET NUMERIK Neni Febiani; Abd. Charis Fauzan; Muhamat Maariful Huda
Jurnal Tekinkom (Teknik Informasi dan Komputer) Vol 5 No 1 (2022)
Publisher : Politeknik Bisnis Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37600/tekinkom.v5i1.435

Abstract

The decision tree is a method of classifying data mining. The decision tree has one type of algorithm model, namely the C4.5 algorithm. The C4.5 decision tree algorithm is easy to understand because it has a tree-like structure in general. The C4.5 algorithm in handling quantitative data is often less efficient and effective. Based on these problems, this study improvised the numerical attribute dataset using the mean and median in the preprocessing of the data. The improvisation is used to obtain a threshold value, thereby minimizing information loss and time complexity when implementing the C4.5 decision tree in predicting training data. Evaluation of the system used in this study using a confusion matrix. The confusion matrix is ​​used as a benchmark in testing the classification method using data testing. In this study, the dataset was partitioned into three scenarios. In scenario 1 with 70% training data and 20% test data, the highest accuracy is 75%. The improvisation of the mean and median on the numerical attributes in the C4.5 algorithm can be used in this scenario.
PREDIKSI PRESTASI MAHASISWA DENGAN MENGGUNAKAN ALGORITMA BACKPROPAGATION Sahat Sonang; Arifin Tua Purba; Sarida Sirait
Jurnal Tekinkom (Teknik Informasi dan Komputer) Vol 5 No 1 (2022)
Publisher : Politeknik Bisnis Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37600/tekinkom.v5i1.512

Abstract

This study aims to overcome the problems in predicting student achievement at the Polytechnic Business Indonesia Pematangsiantar. To predict student achievement is done by applying Backpropagation algorithm and implement it into Matlab software. Backpropagation algorithm is one of the methods on artificial neural networks that is quite reliable in solving problems including prediction. In this study conducted on the object of students semester One with a lot of data samples 26 samples. The data sample is divided into two parts, 70% of the data is used as training data and 30% of the data is used as testing data. This study uses ten architectural models, namely 9-2-1, 9-3-1, 9-4-1, 9-5-1, 9-6-1, 9-7-1, 9-8-1, 9-9-1, 9-10-1, 9-11-1. Of the ten Backpropagation network architecture models implemented in predicting student achievement in Matlab software obtained the best output is 9-2-1 pattern with epoch 8149, time duration for 17 seconds, and MSE (error rate) value of 2.80 e-05 for training and MSE (error rate) of 0.1248 with accuracy of 87.5% for testing. The best architecture obtained is expected to be used as a picture by the academic Polytechnic Business Indonesia (PBI) in predicting student achievement.
PREDIKSI PENETAPAN TARIF PENERBANGAN MENGGUNAKAN AUTO-ML DENGAN ALGORITMA RANDOM FOREST Yakub Anuyuta Zebua; Daniel Ryan Hamonangan Sitompul; Stiven Hamonangan Sinurat; Andreas Situmorang; Ruben Ruben; Dennis Jusuf Ziegel; Evta Indra
Jurnal Tekinkom (Teknik Informasi dan Komputer) Vol 5 No 1 (2022)
Publisher : Politeknik Bisnis Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37600/tekinkom.v5i1.508

Abstract

With so many airlines competing with each other, airlines are competing to become the consumer/market's main choice, but to achieve this, there is no airline strategy that can predict the price of airline tickets according to market needs. To meet the needs of airlines, we need a way to determine the price of airline tickets according to market needs with the help of the influence of technology and information. This research method was carried out using Google Collaboratory as a media to create a data model automated machine learning (AutoML) with the Random Forest, Logistic Regression and Gradient Boosting Regressor algorithms. In this study, the model that produced the highest R2 value and the lowest RMSE was a random forest with an R2 value of 83.91% and an RMSE of $175.9. However, from the three models, Random Forest got a change in accuracy of 1.96% to 85.87. To assist in predicting the determination of flight fares, airline companies can more easily and be alert to determine flight fares that are in accordance with the market. Therefore, Random Forest can be declared better than Logistic Regression and Gradient Boosting models. The Random Forest model that has been created can be used to predict in real-time using Machine Learning.
IMPLEMENTASI ANALISIS STP (SEGMENTATION, TARGETING, POSITIONING) PADA USAHA KUE TRADISIONAL DJAJE Made Irvan Mahendra Putra; Sephy Lavianto; I Made Artana
Jurnal Tekinkom (Teknik Informasi dan Komputer) Vol 5 No 1 (2022)
Publisher : Politeknik Bisnis Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37600/tekinkom.v5i1.482

Abstract

Djaje is a traditional cake business that was founded in 2017. The products that Djaje sells are various wet snacks. The initial strategy used was only offline, such as handing cakes to resellers, but as the number of competitors increased, Djaje's sales declined. This research uses method analysis STP (Segmentation, Targeting, Positioning) the data is then presented with a qualitative descriptive method. The purpose of this study was to determine the results of implementing digital marketing strategies in improving traditional cakes. The results of the implementation of the strategy implemented by adjusting the content of photos, descriptions, posts, and advertisements using STP (Segmentation, Targeting, Positioning) analysis as a basis. By utilizing various digital platforms to reach more potential consumers, Djaje managed to make cake sales increase from October 2021 by Rp. 10,000,000 per month until March 2022 reaching Rp. 25,092,500 with total sales for 6 months of Rp. 105,832,500.
BACK-END SYSTEM DESIGN BASED ON REST API Hendrik Fery Herdiyatmoko
Jurnal Tekinkom (Teknik Informasi dan Komputer) Vol 5 No 1 (2022)
Publisher : Politeknik Bisnis Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37600/tekinkom.v5i1.401

Abstract

Back-End is a logical space with the functionality and operation of a software application or information system. Currently, SMA Xaverius 1 Palembang does not yet have a rest server-based application whose background can be accessed by a multi-platform rest client. Therefore, an application based on the RESTful rest api based back-end was built. This RESTful application or REST Server provides data to be accessed by the REST Client using data exchange in JSON format using the HTTP protocol built using the Laravel Framework. The Laravel framework provides a mechanism for building REST Servers via the Rest Server library that supports a full RESTful server implementation. The results of this research have been successful. A Laravel 7-based REST Server application has been built which provides endpoints in the form of json and status codes which can later be accessed by multi-platform rest clients. Through the application based on the back-end rest api, the results from the endpoint get a response from the server in the form of json that supports interoperability.
IDENTIFIKASI LEVEL KAPABILITAS IT GOVERNANCE MENGGUNAKAN FRAMEWORK COBIT 2019 PADA PT XYZ Cherry Lumingkewas; Maestro Phytagoras; Virjin Fanesa; Michelle Walangitan; Joe Yuan Yulian Mambu; Erienika Lompoliu
Jurnal Tekinkom (Teknik Informasi dan Komputer) Vol 5 No 1 (2022)
Publisher : Politeknik Bisnis Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37600/tekinkom.v5i1.465

Abstract

There are numerous frameworks that can be utilized to develop information technology governance when examining corporate governance. COBIT is an auditing framework that auditors use to control and manage IT governance. PT. XYZ is a newcomer in the paint and coating production industry in Indonesia, and to compete with competitors and accommodate corporate goals, a design in IT Governance is required to determine what must be changed. The research aimed to provide an IT governance design that tailored based on what the company needs. The governance design is compiled by using the latest COBIT 2019 framework, which involved interview and quantification of each Design Factor values from the interview. We conducted interviews with prominent IT personnel within the company using the COBIT 2019 framework Design Factor (DF), which includes: enterprise strategy, enterprise goals, risk profile, and I&T related issues, threat landscape, compliance requirement, role of IT, model of IT, and finally IT implementation methods. The results suggest that five core models, including EDM05, APO06, APO14, MEA03, and MEA04, are advised to have a competency level of 2. There is one core model for which a skill level of 3 is indicated, which is BAI09. This study is only concerned with developing an IT governance design; there is no evaluation of the core model or methodology.
PENERAPAN DATA MINING UNTUK REKOMENDASI PAKET PERNIKAHAN MENGGUNAKAN METODE ALGORITMA APRIORI Delima Sitanggang; Nanchy Adeliana Br S. Muham; Saljuna Hayu Rangkuti; Sion Putri Zalukhu; Evta Indra
Jurnal Tekinkom (Teknik Informasi dan Komputer) Vol 5 No 1 (2022)
Publisher : Politeknik Bisnis Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37600/tekinkom.v5i1.509

Abstract

SM Wedding Decoration is a place that provides services to take care of everything related to weddings. For example, wedding decorations, wedding organizers, and wedding planners. SM Wedding Decoration has several wedding packages that can be offered to customers. The many packages available make the bride and groom or customers confused to determine which wedding package is suitable for their wedding. The a priori algorithm method is used in this study to find recommendations for wedding packages based on existing transaction data and to improve the company's strategy and sales of other wedding packages. The Apriori algorithm is used to help computers learn patterns of association rules. This algorithm looks for a set of things that match the given criteria or sequence and has a certain frequency value. From this research, customers tend to order Photographer & Documentation and MUA → Deluxe packages more often, and these orders account for 44% of all package order transaction data. Package order transaction data for MUA→Deluxe package is 41.3%. Transaction data for the Photographer & Documentation package → Deluxe Package is 41.2%. And the transaction data for ordering the MUA → Premium Deluxe Package package is 41.3%.
PENERAPAN ALGORITMA APRIORI DALAM MENINGKATKAN PRODUKSI BUDIDAYA PERIKANAN MENGGUNAKAN ASSOCIATION RULE Tajrin Tajrin; David Ebenezer Frans; Nadia Damayanti Nainggolan; Jose Agustin Fernando Marbun; Sediaman Julianus Gulo
Jurnal Tekinkom (Teknik Informasi dan Komputer) Vol 5 No 1 (2022)
Publisher : Politeknik Bisnis Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37600/tekinkom.v5i1.510

Abstract

Aquaculture production in North Sumatra needs to be increased in order to meet the increasing demand for aquaculture in the area from time to time. In order to optimize aquaculture production, recommendations are made for what types of aquaculture are most in demand by the community so that the North Sumatra Marine and Fisheries Service can prepare fishery supplies optimally. Recommendations for the provision of fish are carried out by utilizing data mining technology with an association rule algorithm. Processed data is fish sales history data. The result of this data processing is the combination of fish data that is most in demand by the community with a minimum amount of support of 40% to 3 itemset. Furthermore, the a priori algorithm is implemented at the marine and fisheries service to determine associations. By utilizing the results of this a priori algorithm analysis, the Department of Marine and Fisheries of North Sumatra can find out what types of aquaculture are the priorities for increasing production so that they can meet the needs of the community.
PENERAPAN DATA MINING PEMASARAN PRODUK MENGGUNAKAN METODE CLUSTERING Melladia Melladia; Dian Eka Putra; Leila Muhelni
Jurnal Tekinkom (Teknik Informasi dan Komputer) Vol 5 No 1 (2022)
Publisher : Politeknik Bisnis Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37600/tekinkom.v5i1.458

Abstract

This study aims to build a data mining application that is able to classify products marketed by companies to find out the products needed for the following month. This application groups non-hierarchical data which is designed to divide existing data into two or more groups so that the same data can be entered into other groups. In this study, the data used is data from PT Cipta Niaga Semesta Mayora Group and the method used is clustering. Data mining is computer-based data processing to gain knowledge. By using data mining, processing sales data at PT Cipta Niaga Semesta Mayora Group becomes easier and gains useful knowledge to take steps to face competition. For this reason, the company's management foresight is needed in choosing technology to help work so that the costs incurred are proportional to the company's opinion. The development of this framework is completed through several stages starting with the first data collection, followed by the second stage of application design, the third stage of the four stages of program development and program implementation. Using data mining applications can help PT Cipta Niaga Semesta categorize the products it sells so that the company can predict the product inventory needed for the following month. So with the new information the company can find out what products customers want.
ASOSIASI RULE MINING UNTUK REKOMENDASI PADA TRANSAKSI PEMINJAMAN BUKU MENGGUNAKAN FREQUENT PATTERN I Gusti Ayu Sri Melati; Rifky Lana Rahardian; I Made Lanang Putra Pringgadhan
Jurnal Tekinkom (Teknik Informasi dan Komputer) Vol 5 No 1 (2022)
Publisher : Politeknik Bisnis Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37600/tekinkom.v5i1.497

Abstract

The purpose of this study is to provide recommendations for grouping books at the ITB STIKOM Bali library, Jimbaran Campus. Currently, the placement of books in the ITB STIKOM Bali library, Jimbaran Campus, is still using a manual catalog. To make it easier for staff to manage books in the library, especially in terms of book data that can be borrowed, recommendations for grouping and placing books in the library are made based on the data on books that are most often borrowed together by library visitors obtained from previous borrowing data. This is done by data mining using the frequent pattern method. The use of this frequent pattern method is applied to the borrowing data of the ITB STIKOM Bali library at Jimbaran campus so that information or knowledge is obtained about recommendations for placing books that will be loaned to library members. This data mining processing is done using Weka software. The results of processing from the Association Rule data mining obtained 5 itemset combinations with confidence values ​​of 0.97, 0.96, 0.95. With the results of this data mining, the librarian obtains recommendations for grouping and placing books in the library through knowledge of the types of books that are most often borrowed.

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