cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
Mesran
Contact Email
mesran.skom.mkom@gmail.com
Phone
+6282161108110
Journal Mail Official
tin.journal@fkpt.org
Editorial Address
Jalan Sisingamangaraja No. 338, Medan, Sumatera Utara
Location
Kota medan,
Sumatera utara
INDONESIA
TIN: TERAPAN INFORMATIKA NUSANTARA
Published by Forum Kerjasama Pendidikan TInggi
ISSN : -     EISSN : 27227987     DOI : -
Core Subject : Economy, Health, Science, Education, Art, Social, Engineering,
Aerospace Engineering Arts Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management Dentistry Earth & Planetary Sciences Economics, Econometrics & Finance Energy Engineering Environmental Science Health Professions Immunology & microbiology Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Neuroscience Nursing Physics Social Sciences Veterinary Other
Jurnal TIN: TERAPAN INFORMATIKA NUSANTARA memuat tentang Kajian Bunga Rampai dari berbagai ide dan hasil penelitian para peneliti, mahasiswa, dan dosen yang berkompeten di bidangnya dari berbagai disiplin ilmu seperti: Komputer, Informatika, Industri, Elektro, Telekomunikasi, Kesehatan, Agama, Pertanian, Pembelajaran, Pendidikan, Teknologi Pendidikan, Ekonomi dan Bisnis, Manajemen, Akuntansi, dan Hukum
Arjuna Subject : Umum - Umum
Articles 10 Documents
 1 
Search results for , issue "Vol 1 No 9 (2021): Februari 2021" : 10 Documents clear
Analisa Pola Gadai BPKB Kendaraan dengan Menerapkan Algoritma FG-Growth Ningsih, Fitri Pratiwi
TIN: Terapan Informatika Nusantara Vol 1 No 9 (2021): Februari 2021
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Data Mining is a series of processes to explore added value in the form of information that has been known manually from a database by extracting patterns from data with the aim of manipulating data into more valuable information obtained by extracting and recognizing patterns important or interesting from the data contained in the database. The data mining technique has various algorithms and techniques for solving problems related to data, one of which is the FP-Growth algorithm and the technique of association rules. Information displayed using association rules technique, which displays the value of support and confidence from each data mining process. With the FP-Growth algorithm, it is evident from the results of the tests carried out, the FP Growth algorithm and association rules technique run as expected and can be implemented in this Data Mining.
Segmentasi Citra Spektrum Menggunakan Algoritma Region Growing Marbun, Riccy Erwandy
TIN: Terapan Informatika Nusantara Vol 1 No 9 (2021): Februari 2021
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Image segmentation is a process shown to get the objects contained in the image or to divide the image into several areas with each object or area having similar attributes. The Region growing algorithm is a procedure that groups pixels or sub-regions into larger areas based on defined criteria. The basic approach starts from the set of starting points, then the area is enlarged by adding each neighboring pixel point that has similar properties to that point, for example the range specification intensity or color. The purpose of region-based segmentation (region) is to divide an image into several regions, this is done by grouping parts of the image that have the same characteristics in the form of color changes between adjacent points. The application of the Region Growing algorithm can be used in analyzing the segmentation of Infrared Spectrum Image in detecting image edges based on the growth area with the image segmentation process using the Region Growing algorithm
Implementasi Algoritma Skipjack Dalam Pengamanan File Video Gaol, Rina Wanty Lumban
TIN: Terapan Informatika Nusantara Vol 1 No 9 (2021): Februari 2021
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

The problem that lies within the scope of the video is where the privacy video can be watched by unauthorized people if the video file is unsecured. In the event of a burglary and theft of important data information in a video file, it will be detrimental to interested parties. Therefore, we need an application system to be able to secure the video file. To minimize this, a second level of security is needed by scrambling the video so that the visual information from the video cannot be seen by people who do not have a key. Then the information in the video file is changed in the form of codes or signals where this code will be manipulated. Thus the authors feel the video files need to be secured with good security. So it is necessary to make encryption and decryption on video files. The skipjack algorithm is one of the cryptographic algorithms that can be used to secure video files. The skipjack algorithm is a 64-bit codebook electronic algorithm that changes a 64-bit input block to a 64-bit output block. The parameters used for encryption are 80-bit keys, and have 32 rounds for the encryption and description process. This study describes how to secure video files based on the skipjack algorithm.
Implementasi Algoritma FP-Growth Pada Pengenalan Pola Penjualan Nurasiah, Nurasiah
TIN: Terapan Informatika Nusantara Vol 1 No 9 (2021): Februari 2021
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Data Mining is a series of processes to extract additional value in the form of information that has been known manually from a database by extracting patterns from data with the aim of manipulating data into more valuable information obtained by extracting and extracting patterns important or pull the data contained in the database. Data Mining technique has various kinds of algorithms and techniques for solving problems related to data, one of which is the FP-Growth algorithm and the association rule technique. The information displayed using the association rule technique, which displays the value of support and confidence from each data mining process. With the FP-Growth algorithm, it is proven from the results of the tests carried out, the FP-Growth algorithm and the association rule technique run as expected and can be implemented in this Data Mining
Penerapan Metode Gost Untuk Mendeteksi Keaslian File Dokumen Anggriani, Lia
TIN: Terapan Informatika Nusantara Vol 1 No 9 (2021): Februari 2021
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Humans have the ability to be able to detect the authenticity of document files. This capability will be very useful when applied to machines such as computers. The purpose of this research is to implement the GOST algorithm (Gosudarstennyi Standard or often called the Government Standard. The gost method is a block cipher algorithm developed by a national of the USSR. GOST cryptography is a 64-bit block cipher with a key length of 256 bits. This algorithm iterates over the algorithm. simple encryption of 32 rounds (round), to encrypt the 64-bit plaintext first broken down into 32 bits on the left, L and 32 bits on the right R. Design is a process that aims to analyze, assess, improve, and compile a system, both physical and non-physical systems that are optimal for the future by utilizing existing information Design is the process of developing a new system specification based on analysis recommendations system.Application is a noisy program n commands to perform data processing. Application in general is a manual process that is informed to the computer by creating a system or program to make it more optimally efficient
Sistem Pendukung Keputusan Penerima Bantuan Covid-19 Menggunakan Metode Simple Additive Weighting (SAW) Simanullang, Rahma Yuni; Melisa, Melisa; Mesran, Mesran
TIN: Terapan Informatika Nusantara Vol 1 No 9 (2021): Februari 2021
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

This study aims to determine the acceptance of covid19 assistance. The COVID 19 pandemic is devastating, resulting in a lot of unemployment. The poverty rate is increasing, and there are also cases of rampant mortality, the mobility of the community itself and security insecurity. With that, the government plans to provide special assistance for people who cannot afford to face the COVID 19 pandemic. The distribution of social assistance as a realization of the social safety net program during the COVID 19 pandemic has worried many homeworkers, starting from reduced income, setting targets to distribution. However, the mechanism for distributing aid often becomes very complicated, or the nominal amount decreases and there is often an inaccurate point of view because the criteria for beneficiaries do not match the data that is inaccurate / does not match the reality in the field, resulting in misunderstandings between the community. In essence, the Simple Additive Weighting (SAW) method is often known as the weighted method. The basic concept of the Simple Additive Weighthing (SAW) method is to find the weighted sum of the performance branches for each alternative on all criteria. The Simple Additive Weighting (SAW) method requires a decision matrix normalization process. So the author uses the Simple Additive Weighting method or it is often said with the term SAW. To solve this problem, namely by using one of the methods to obtain a multiple and complete assessment of criteria with a conferential thinking framework to carry out hierarchical considerations, then calculate the weight of each criterion to determine the priority recommendations for receiving COVID 19 assistance according to the data. On the results of this study.
Penerapan Metode SAW (Simple Additive Weighting) Dalam Pemilihan Siswa-Siswi Berprestasi Pada Sekolah SMK Swasta Mustafa Ramadhan, Muhammad Rizky; Nizam, Muhammad Khairul; Mesran, Mesran
TIN: Terapan Informatika Nusantara Vol 1 No 9 (2021): Februari 2021
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

In the face of the times and the era of technology that is rapidly developing at any time, the development of human resources is a top priority in the national development of the state, the position and position of students, has a very important role in teaching and learning activities for students to improve. Student achievement in academics and non-academic fields, one of the things that motivates students to always develop themselves is to give an award as an outstanding student with the criteria determined by the school. Temporary observations at Mustafa Private Vocational High School in determining outstanding students were done manually. This method is still considered ineffective and inefficient. Based on this, a model for determining outstanding students at Mustafa Private Vocational School is needed with a more efficient and effective system. This system is designed using a decision support system through the Simple Additive Weighting (SAW) method. This system can display the results of the ranking of outstanding students based on the calculation results of the SAW method
Sistem Pendukung Keputusan Penerimaan Calon Karyawan Menggunakan Metode Simple Additive Weighting Simanullang, Siska Kristiana; Simorangkir, Andreas Gerhard
TIN: Terapan Informatika Nusantara Vol 1 No 9 (2021): Februari 2021
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Companies really need a professional and enthusiastic workforce to help in the progress of the company. Prospective employees must be able to reach the location of the company, both prospective employees who are in villages or cities. Prospective employees who can be selected are employees who can perform the criteria which are weighted to the criteria set by the owner / leader of the company. Therefore, the Company is making efforts to improve the quality of recruitment of prospective employees. To facilitate the recruitment of prospective employees, the HRD has implemented a conventional system, namely using Microsoft Excel. However, at the recruitment of prospective employees, there are weaknesses faced, namely the HRD has an idea that in assessing prospective employees still using intuition or subjective elements. Because in terms of this assessment it does not consider every criteria and benchmarks for the assessment of prospective employees. So it seems that there is no clear reference or criteria for the assessment standard. For this reason, in order to assist HRD in the recruitment process of prospective employees, a decision support system is needed that can provide information for prospective employees who are accepted or not accepted. So the method used in this decision support system is the Simple Additive Weighting (SAW) Method. The recruitment process for prospective employees with a decision support system using the Simple Additive Weighting (SAW) method is carried out by entering the weight values ​​for each of the criteria and the value of the assessment criteria for each prospective employee. Then the process of calculating the value is carried out, to be able to find out the final results and rank of each prospective employee, either the one with the highest score or the lowest score. So that it can help HRD in making decisions about whether to accept prospective employees or not.
Implementasi Jaringan Syaraf Tiruan (JST) Untuk Memprediksi Jumlah Penjualan Gas 3Kg Menggunakan Metode Backpropagation B. Tambunan, Holpan Torang; Hartama, Dedy; Gunawan, Indra
TIN: Terapan Informatika Nusantara Vol 1 No 9 (2021): Februari 2021
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

In a service company, there are customers who become company consumers. Customer satisfaction is formed from the level of performance and service of the company. One level of customer satisfaction can be measured from the level of gas sales of 3 Kg. Therefore, the 3 kg LPG gas pankalan Pematangsiantar needs to overcome the problem of overcoming the amount of 3 kg gas sales at each LPG base in order to improve their performance and service. So research is needed to predict the amount of gas sales of 3 Kg through the Neural Network method with the backpropagation algorithm to find the best results that will be used to solve the problems faced.
Implementasi Jaringan Syaraf Tiruan Backpropagation Untuk Memprediksi Jumlah Pemasangan Instalasi Air Pada PDAM Tirtauli Sianipar, Markus Parulian; Sumarno, Sumarno; Tambunan, Heru Satria
TIN: Terapan Informatika Nusantara Vol 1 No 9 (2021): Februari 2021
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

In a service company, there are customers who become company consumers. One level of customer satisfaction can be measured from the level of installation of water installations to the customer's house. Therefore, the Regional Drinking Water Company (PDAM) Tirtauli Pematangsiantar needs to solve the problem in overcoming the number of water installations. Artificial Neural Network with backpropagation algorithm is used to predict the number of new water installations. The test results obtained a prediction accuracy of 89% with a 2-10-1 architecture

Page 1 of 1 | Total Record : 10

 1 

Filter by Year

2021 2021


Reset
Filter By Issues
All Issue Vol 6 No 9 (2026): February 2026 Vol 6 No 8 (2026): January 2026 Vol 5 No 12 (2025): May 2025 Vol 5 No 11 (2025): April 2025 Vol 5 No 10 (2025): March 2025 Vol 6 No 7 (2025): December 2025 Vol 6 No 6 (2025): November 2025 Vol 6 No 5 (2025): October 2025 Vol 6 No 4 (2025): September 2025 Vol 6 No 3 (2025): August 2025 Vol 6 No 2 (2025): July 2025 Vol 6 No 1 (2025): June 2025 Vol 5 No 9 (2025): February 2025 Vol 5 No 8 (2025): January 2025 Vol 4 No 12 (2024): May 2024 Vol 4 No 11 (2024): April 2024 Vol 4 No 10 (2024): March 2024 Vol 5 No 7 (2024): December 2024 Vol 5 No 6 (2024): November 2024 Vol 5 No 5 (2024): October 2024 Vol 5 No 4 (2024): September 2024 Vol 5 No 3 (2024): August 2024 Vol 5 No 2 (2024): July 2024 Vol 5 No 1 (2024): June 2024 Vol 4 No 9 (2024): February 2024 Vol 4 No 8 (2024): January 2023 Vol 3 No 12 (2023): May 2023 Vol 3 No 11 (2023): April 2023 Vol 3 No 10 (2023): March 2023 Vol 4 No 7 (2023): December 2023 Vol 4 No 6 (2023): November 2023 Vol 4 No 5 (2023): October 2023 Vol 4 No 4 (2023): September 2023 Vol 4 No 3 (2023): August 2023 Vol 4 No 2 (2023): July 2023 Vol 4 No 1 (2023): June 2023 Vol 3 No 9 (2023): February 2023 Vol 3 No 8 (2023): January 2023 Vol 2 No 10 (2022): Maret 2022 Vol 3 No 7 (2022): December 2022 Vol 3 No 6 (2022): November 2022 Vol 3 No 5 (2022): October 2022 Vol 3 No 4 (2022): September 2022 Vol 3 No 3 (2022): August 2022 Vol 3 No 2 (2022): July 2022 Vol 3 No 1 (2022): June 2022 Vol 2 No 9 (2022): Februari 2022 Vol 2 No 8 (2022): Januari 2022 Vol 1 No 12 (2021): Mei 2021 Vol 1 No 11 (2021): April 2021 Vol 1 No 10 (2021): Maret 2021 Vol 2 No 7 (2021): Desember 2021 Vol 2 No 6 (2021): November 2021 Vol 2 No 5 (2021): Oktober 2021 Vol 2 No 4 (2021): September 2021 Vol 2 No 3 (2021): Agustus 2021 Vol 2 No 3 (2021): Agustus 2021 (in press) Vol 2 No 2 (2021): Juli 2021 Vol 2 No 1 (2021): Juni 2021 Vol 1 No 9 (2021): Februari 2021 Vol 1 No 8 (2020): Januari 2021 Vol 1 No 7 (2020): Desember 2020 Vol 1 No 6 (2020): November 2020 Vol 1 No 5 (2020): Oktober 2020 Vol 1 No 4 (2020): TIN: September 2020 Vol 1 No 3 (2020): TIN: Agustus 2020 Vol 1 No 2 (2020): TIN: Juli 2020 Vol 1 No 1 (2020): Juni 2020 More Issue