Article Per Year (5 Year)
p-Index From 2020 - 2025
0.408
P-Index
This Author published in this journals
All Journal Jurnal Ilmiah Sinus Jurnal TIKOMSIN (Teknologi Informasi dan Komunikasi Sinar Nusantara) Euclid
Wawan Laksito YS
STMIK Sinar Nusantara
Computer Science & IT Education Mathematics Social Sciences

Published : 3 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 3 Documents
Search

 1 
Implementasi Metode Double Exponential Smoothing pada Prediksi Jumlah Penjualan Kain Pantai Nacita Agnes Dorestin; Wawan Laksito YS; Retno Tri Vulandari
Jurnal Teknologi Informasi dan Komunikasi (TIKomSiN) Vol 10, No 1 (2022): Jurnal TiKomSiN, Vol. 10, No. 1, April 2022
Publisher : STMIK Sinar Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30646/tikomsin.v10i1.596

Abstract

Y2K Batik is an SME (Small and Medium Enterprise) engaged in batik. Y2K Batik produces and sells beach wear with various motifs. One of the important things in business is inventory of merchandise, inventory of merchandise is a factor in determining the success of a trading company to achieve its goals, because the goods sold affect the level of income to increase company profits. With these considerations, it is necessary to analyze the production of beach wear for the availability of merchandise in fulfilling customer orders. Based on the above background, the scope of the problem in this study is master data collection obtained from records of selling beach batik cloth periodically from time to time. By utilizing the existing data and applying certain methods, a sales forecasting prediction can be made using the Double exponential Smoothing method. From the results of calculations and testing of forecasting data on the Mandala Motif Beach Fabric variable with the most optimal value using = 0.9 of 2127 with an error value of 19.46% and an accuracy rate of 80.54% (Good). The Canting Motif Beach Wear variable with the most optimal value using = 0.9 of 3174 with an error value of 3.61% and an accuracy rate of 96.39% (Very Good). Double Exponential Smoothing is the most widely used method to determine the trend equation of the second smoothing data through a smoothing process. The programming language uses Microsoft Visual Studio 2013 and the DBMS uses Microsoft SQL Server 2012. The purpose of this research is to create a system that can simplify the process of analyzing the production of beach wear in order to meet the availability of goods ordered by customers.
The Application of the Blowfish Algorithm and the Least Significant Bit Method for Securing Student Transcripts Iwan Ady Prabowo; wawan Laksito YS; Wahyudi Wahyudi
Jurnal Ilmiah SINUS Vol 20, No 2 (2022): Vol. 20 No. 2 Juli 2022
Publisher : STMIK Sinar Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30646/sinus.v20i2.622

Abstract

Academic transcripts are a summary of a student's high-value achievement score and must be guaranteed in their authenticity, as well as the source from which they are issued.  It was found that some universities were using technology to falsify transcripts. An example of a university in yogyakarta's special region that falsified academic transcripts. Several diplomas from makassar have been forged so that a civil servant can pass his exam, whereas in banda aceh evidence of equipment for creating fake diplomas has been found. This study seeks to prevent transcripts from being modified or falsified by locking data into student photos using blowfish and least significant bit algorithms. The purpose of this study is to keep transcripts from being  easily  modified or falsified. The methods of this study are data collection (student code data, gpa value, photo), encryption with blowfish, conversion of encryption results into binary form, insertion of binary values into the least significant bit method into photos, capture of encryption values from least significant bit photos, and returning messages encrypted with blowfish. In this study, the results show that this system was able to secure data and enter information into student photos with an accuracy of 100% after testing on 60 transcript value data. We can conclude that the application of blowfish and least significant bit algorithms to secure data and enter data into student photos is extremely effective in transkrip value.
Perbandingan Prediksi Tinggi Muka Air Bendungan Wonogiri dengan Single Exponential Smoothing dan Brown’s Exponential Smoothing Retno Tri Vulandari; Dwi Rema wati; Yustina Retno W; Hendro Wijayanto; Wawan Laksito YS
Euclid Vol 6, No 2 (2019): Edisi Juli
Publisher : Universitas Swadaya Gunung Jati.

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (564.642 KB) | DOI: 10.33603/e.v6i2.2194

Abstract

Intensitas hujan tahunan di daerah aliran sungai (DAS) Bengawan Solomengakibatkan debit aliran sungai besar di beberapa anak sungai. Debit aliransungai yang besar mengakibatkan tinggi muka air di beberapa pos pemantauanmeningkat. Tinggi muka air di setiap pos pemantauan diukur setiap hari denganperiode yang sama, pagi (06.00), siang (12.00), dan sore (18.00). oleh karena itu data tinggi muka air merupakan data runtun waktu. Salah satu metode peramalan data runtun waktu adalah single exponential smoothing dan Brown’s double exponential smoothing. Dalam penelitian ini akan dilakukan pemodelan data tinggi muka air sungai Bengawan Solo pada pos pemantauan Wonogiri Juni – Desember 2018.
Co-Authors Dwi Rema wati Hendro Wijayanto Iwan Ady Prabowo Nacita Agnes Dorestin Retno Tri Vulandari Wahyudi Wahyudi Yustina Retno W