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All Journal InfoTekJar : Jurnal Nasional Informatika dan Teknologi Jaringan JURNAL TEKNOLOGI DAN ILMU KOMPUTER PRIMA (JUTIKOMP) Jusikom: Jurnal Sistem Informasi Ilmu Komputer Jurnal Sains dan Teknologi Jurnal Tekinkom (Teknik Informasi dan Komputer)
Oloan Sihombing, Oloan
Magister Teknik Informatika, Universitas Sumatera Utara
Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Mathematics Physics Social Sciences

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FRAMEWORK PENGAMANAN DATA DENGAN WHEEL FACTORIZATION PADA ALGORITMA RSA SEBAGAI PEMBANGKIT BILANGAN PRIMA Sihombing, Oloan
InfoTekJar (Jurnal Nasional Informatika dan Teknologi Jaringan) Vol 1, No 1 (2016): InfoTekJar
Publisher : InfoTekJar (Jurnal Nasional Informatika dan Teknologi Jaringan)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (332.279 KB)

Abstract

Keamanan merupakan sebuah factor yang sangat penting di dalam pengiriman data. Banyak teknik keamanan data yang dapat digunakan untuk mengamankan data-data yang bersifat rahasia tersebut. Salah satunya adalah dengan menggunakan teknik kriptografi dengan menggunakan RSA. Akan tetapi di dalam metode tersebut kemungkinan metode tersebut dapat di retas tetap ada. Proses pembangkitan bilangan prima yang dibutuhkan di dalam metode RSA tersebut adalah proses yang paling utama sehingga proses peretasan akan semakin sulit. Di dalam penelitian ini akan memberikan sebuah framework baru di dalam teknik pengamanan data dengan RSA dengan menggunakan wheel factorization sebagai pembangkit bilangan primanya sehingga proses peretasan algoritma tersebut akan semakin sulit.
SISTEM INFORMASI USAHA MIKRO, KECIL, DAN MENENGAH BERBASIS WEB Jeriko Saragih, Jewis; Stephen; Sihombing, Oloan
JURNAL SAINS DAN TEKNOLOGI Vol. 1 No. 2 (2020): Sains dan Teknologi
Publisher : Sisfokomtek

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Abstract

Micro, Small and Medium Enterprise (MSME) is a productive business,  owned by an individual or business entity that has meet a certain condition or criteria as businessmen. Micro, small and medium enterprise (MSME) aims to grow and develop its capability to become a strong and independent business, enhance its role on regional development, providing jobs and promote economic growth.Information technology that is developing fast lately has driven acceleration in various fields of work. Newest and accurate information is needed, that is why the writer tries to design an information system website. This task intends to provide convenience who want to find out the information about all the North Sumatera (MSME) data, especially in Medan. This information system is built using PHP, MySQL, XAMPP, HTML, CSS (Cascading Style Sheets), Javascript, Sublime Text, Adobe Photoshop as layout design and Google Chrome browser. This information system can provide information on MSME products, employee data, basic tasks, vision and mission, organizational structure, galleries and contacts that users can reach if needed
ANALISIS KOMPARASI ALGORITMA C5.0 DAN NAIVE BAYES PENENTUAN PENERIMA BEASISWA UNIVERSITAS PRIMA INDONESIA Fantasy, Carolus Laberto; Simanjuntak, Felix Luther Mateus; Purba, Raja Levi Aldi; Sihombing, Oloan
Jurnal Tekinkom (Teknik Informasi dan Komputer) Vol 6 No 2 (2023)
Publisher : Politeknik Bisnis Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37600/tekinkom.v6i2.926

Abstract

In developing quality human resources, Prima Indonesia University offers a scholarship program to help with educational costs for outstanding students. This research aims to help solve the problem of scholarship recipient selection which requires in-depth analysis using data mining technology. In this research, the use of the C5.0 algorithm and Naive Bayes algorithms was compared in determining scholarship recipients at Prima Indonesia University. The research method involves research locations at Prima Indonesia University using scholarship student data for 2019-2022 as research objects. The research instrument includes the use of the Python programming language with Google Colab as an editor, the Windows 10 operating system, and hardware with certain specifications. Data collection involves observation, literature study, data cleaning, data mining, and exploratory data analysis. The results of research using and comparing the C5.0 and Naive Bayes algorithms show an accuracy of 98.62% and 91.37% respectively. Evaluation involves precision, recall, F1, and confusion matrix values. In conclusion, the C5.0 algorithm is more accurate in determining scholarship eligibility than Naive Bayes, with accuracy increasing by around 8%. This research contributes to the development of data mining and predictive analysis in the context of determining scholarship recipients in higher education institutions.
Analisis Implementasi Metode Fuzzy Tsukamoto Dalam Penentuan Calon Legislatif Salim, Stanley; -, Sutrisno; Laia, Yonata; Ompusunggu, Elvis sastra; Barus, Ertina Sabarita; Sihombing, Oloan
JURNAL TEKNOLOGI DAN ILMU KOMPUTER PRIMA (JUTIKOMP) Vol. 7 No. 1 (2024): Jurnal Teknologi dan Ilmu Komputer Prima (JUTIKOMP)
Publisher : Fakultas Teknologi dan Ilmu Komputer Universitas Prima Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34012/jutikomp.v7i1.4920

Abstract

Being elected as a legislative candidate is a challenging matter. Of course, you must know in the field of politics, both locally and globally, qualified leadership attitudes, moral values, and integrity, financially and financially established in order to carry out campaigns and have a base of followers so that all visions and programs can be conveyed to the public as a whole and clearly. Voters are also required to be wiser and more selective in choosing quality legislative candidates, given that the eligibility rate of candidates in Indonesia is still relatively low, and many participants still need to meet the criteria as ideal legislative candidates. Therefore, a technology and support system is needed that can sort and help the general public in determining quality candidates; in this case, the Tsukamoto Fuzzy method is used, which can be a solution in providing competent candidate recommendations because it has the characteristics of shortening time and simplifying the selection process objectively. This fuzzy method is a support system that is very
Analysis Of E-Commerce Systems To Improve Sales Strategy Using Descriptive Methods In The Sarana Jaya Electronic Company Lim, Albert; Wijaya, Eric; Hendra, Hendra; Mansyur, Reyhand Einstein; Sihombing, Oloan
Jurnal Sistem Informasi dan Ilmu Komputer Vol. 8 No. 1 (2024): JUSIKOM: JURNAL SISTEM INFROMASI ILMU KOMPUTER
Publisher : Fakultas Teknologi dan Ilmu Komputer Universitas Prima Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34012/jurnalsisteminformasidanilmukomputer.v8i1.5449

Abstract

E-commerce includes various activities such as sales, procurement, distribution and promotional transactions carried out via the Internet online network or electronic platforms. PT. Sarana Jaya Elektronik is a company that specializes in the distribution of electronic devices. Currently, PT. Sarana Jaya Elektronik has used an e-commerce system, namely the Tokopedia application, to sell its products. In order to find out the effect of implementing an e-commerce system on improving sales strategies, an analysis process can be carried out using descriptive methods. Descriptive research refers to a methodology in which researchers examine events and phenomena in the lives of individuals, encouraging one or a group of individuals to narrate their experiences.
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.
PENENTUAN PEMBERIAN BONUS KARYAWAN PADA PERUSAHAAN DENGAN MENGGUNAKAN METODE TOPSIS Chandra, Johny; Sipahutar, Santy; Sihombing, Oloan
Jurnal Sistem Informasi dan Ilmu Komputer Vol. 2 No. 2 (2019): JURNAL SISTEM INFROMASI DAN ILMU KOMPUTER PRIMA (JUSIKOMP)
Publisher : Fakultas Teknologi dan Ilmu Komputer Universitas Prima Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (511.894 KB) | DOI: 10.34012/jusikom.v2i2.380

Abstract

Sumber daya manusia merupakan sumber daya yang memiliki akal, perasaan, keinginan, kemampuan, keterampilan, pengetahuan, dorongan, daya, dan karya. Salah satu cara pimpinan perusahaan untuk memotivasi para karyawan yang memiliki kemampuan dan semangat kerja yang tinggi dalam melakukan pekerjaannya adalah dengan memberikan penghargaan berupa bonus kepada karyawan sesuai dengan prestasi kerja yang dihasilkan. Bonus bisa menjadi salah satu pendorong karyawan menunjukkan kinerja lebih baik. PT. Shell merupakan perusahaan yang bergerak dalam bidang bidang pengolahan dan eksplorasi minyak dan gas biasanya juga memberikan bonus atas prestasi kinerja karyawan. Tetapi, proses pemberian bonus tahunan karyawan pada PT. Shell masih dilakukan secara manual, memerlukan waktu yang lama, serta kriteria yang digunakan dalam penilaian hanya berdasarkan kriteria absensi dan penilaian karyawan. Untuk itu, peneliti merancang sebuah sistem pendukung keputusan yang diharapkan mampu menyelesaikan masalah yang dihadapi. Perancangan sistem pendukung keputusan ini dibangun dengan menggunakan bahasa pemrograman Visual Studio 2010dan SQL Server 2008, serta metode yang digunakan adalah metode TOPSIS. TOPSIS akan membantu proses perhitungan dalam pengambilan keputusan terhadap alternatif berdasarkan jarak terhadap solusi ideal positif dan jarak terhadap solusi ideal negatif dengan mengambil kedekatan relatif terhadap solusi ideal positif. Sistem pendukung keputusan menggunakan metode TOPSIS ini dapat memudahkan perusahaan dalam menentukan karyawan yang berhak mendapatkan bonus tahunan.
Comparative Analysis of Indonesian Text Mining News Online Classification Using the K-Nearest Neighbor and Random Forest Algorithm Sihombing, Oloan; Sitorus, Sarah Tri Yosepha; Indra, Evta; Sinurat, Stiven Hamonangan; Juanta, Palma
Jurnal Sistem Informasi dan Ilmu Komputer Vol. 6 No. 1 (2022): JURNAL SISTEM INFROMASI DAN ILMU KOMPUTER PRIMA (JUSIKOMP)
Publisher : Fakultas Teknologi dan Ilmu Komputer Universitas Prima Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34012/jurnalsisteminformasidanilmukomputer.v6i1.2824

Abstract

The rapid development of internet technology today makes many news media grow pretty rapidly. Newspaper companies have utilized internet technology to spread the latest news online through online mass media. Hundreds of thousands of stories are written and published daily on online-based Indonesian news portals, making it difficult for readers to find the news topics they want to read. In making it easier for readers to find the news they are looking for, news needs to be classified according to its respective categories, such as education, current news, finance, and sports. So to classify categories, a text classification method is needed or often called Text Mining. Text mining is a data mining classification technique for processing text using a computer to produce helpful text analysis. In this study, a comparison of 2 methods for developing texts was carried out to get accuracy above 80%.
IMPLEMENTATION OF DATA MINING TO PREDICT THE VALUE OF INDONESIAN OIL AND NON-OIL AND GAS IMPORT EXPORTS USING THE LINEAR REGRESSION METHOD Ompusunggu, Elvis Sastra; Sinaga, Wilson; Siahaan, Mikael; Banjarnahor, Jepri; Winata, Jaspin; Laia, Yonata; Sihombing, Oloan
Jurnal Sistem Informasi dan Ilmu Komputer Vol. 7 No. 1 (2023): JUSIKOM: JURNAL SISTEM INFROMASI ILMU KOMPUTER
Publisher : Fakultas Teknologi dan Ilmu Komputer Universitas Prima Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34012/jurnalsisteminformasidanilmukomputer.v7i1.4081

Abstract

Indonesia's export-import activities in recent years, the value of Indonesia's exports and imports has decreased due to global conditions. The problems that occur are the uncertainty and complexity in estimating the value of international trade in the oil and gas and non-oil and gas sectors, dependence on just one or a few markets, and the problem of unfair competition, unfair competition between business actors can reduce export-import prices. The value of oil and gas and non-oil and gas exports and imports is influenced by several external factors that are difficult to predict, such as fluctuations in oil and gas prices, changes in trade policies, and global economic factors. The prediction results are obtained every month from the export value data using the rapid miner application. From the export data, the value of non-oil and gas exports obtains a very high value compared to the export data of oil and gas values. Then the results from rapid miner using the linear regression algorithm are obtained. The predicted import value of oil and gas and non-oil and gas value data in June is 209,162,268, and the predicted export value of oil and gas and non-oil and gas value data in June is 349,285,781 and non-oil and gas which more are predicted to have the highest value compared to the value of oil and gas in each month.
ANALISIS PENGARUH OVERSAMPLING SMOTE CREDIT CARD FRAUD DETECTION METODE FITUR FORWARD SELECTION Wijaya, Louise Ernest; Fancella, Shevira; Sihombing, Oloan
Jurnal Teknik Informasi dan Komputer (Tekinkom) Vol 8 No 1 (2025)
Publisher : Politeknik Bisnis Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37600/tekinkom.v8i1.1971

Abstract

Credit card is one of the legal payment methods that is still widely used by the society. People use credit cards to buy various needs both in terms of food, clothing and food. Credit cards also present many dis-count and vouchers that can attract more and more users every day. But in the increasingly crowded use of credit cards, there are also cyber threats that are also growing rapidly along with the times. One of them is fraud to obtain data containing credit card information of an individual. To prevent/lower the risk of Cyber Crime, a credit card fraud detection method is needed. This research focuses on the influence of SMOTE oversampling and Forward Selection feature in the performance of a system used.
Co-Authors Banjarnahor, Jepri Barus, Ertina Sabarita Chandra, Johny Devraz, R.W. Eric Wijaya Fancella, Shevira Fantasy, Carolus Laberto Hendra Hendra Indra, Evta Jeriko Saragih, Jewis Juanta, Palma Lim, Albert Mansyur, Reyhand Einstein Marbun, Timo Adelina Ompusunggu, Elvis Sastra Pardede, Eva Damayanti Purba, Raja Levi Aldi Salim, Stanley Siahaan, Mikael Simanjuntak, Felix Luther Mateus Sinaga, Wilson Sinurat, Stiven Hamonangan Sipahutar, Santy Sipayung, Arif Richardo Idola Sitanggang, Jelita Sari Sitorus, Sarah Tri Yosepha Stephen Sutrisno - Telaumbanua, Jeremia Nicholas Wijaya, Louise Ernest Winata, Jaspin Yonata Laia Zendrato, Nur Eni