Article Per Year (5 Year)
p-Index From 2020 - 2025
6.15
P-Index
This Author published in this journals
All Journal Jurnal TIMES Jurnal Teknologi Informasi dan Ilmu Komputer Sinkron : Jurnal dan Penelitian Teknik Informatika Journal Information System Development METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi METHODIKA: Jurnal Teknik Informatika dan Sistem Informasi KOMPUTA : Jurnal Ilmiah Komputer dan Informatika JURNAL TEKNOLOGI DAN ILMU KOMPUTER PRIMA (JUTIKOMP) Jurnal Informatika Kaputama (JIK) Jurnal Pengabdian Masyarakat Borneo Jurnal Pengabdian Pada Masyarakat METHABDI Majalah Ilmiah METHODA TAMIKA: Jurnal Tugas Akhir Manajemen Informatika & Komputerisasi Akuntansi
Rimbun Siringoringo, Rimbun
Universitas Methodist Indonesia
Religion Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Engineering Immunology & microbiology Languange, Linguistic, Communication & Media Medicine & Pharmacology Physics Public Health Social Sciences Other

Published : 54 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 3 Documents
Search
Journal : METHODIKA: Jurnal Teknik Informatika dan Sistem Informasi

 1 
ANALISIS PSNR PADA STEGANOGRAFI LEAST SIGNIFICANT BIT DENGAN PESAN TERENKRIPSI ADVANCED ENCRIPTION SYSTEM Rimbun Siringoringo
METHODIKA: Jurnal Teknik Informatika dan Sistem Informasi Vol. 2 No. 1 (2016): Maret 2016
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/mtk.v2i1.26

Abstract

Steganography is the art of hiding data on a medium other. Today, steganography is used to secure data by hiding it in other media so that the existence of the message is unintelligible. LSB steagnografi is the simplest method among other methods. LSB steganographic techniques susceptible to steganalisis. In this study the authors combine this with the LSB steganography method by cryptographic techniques. Cryptographic algorithm used is AES. Messages will be inserted first encrypted using the AES method. There are five image dataset being tested. Overall proficiency level datasets have different capacities. There are five types of hidden text with a capacity of 1K, 5K, 10K, 15K and 20K. Testing the quality of the imagebefore and after the embedding process was conducted by PSNR and MD. From the test is known that embedding the message affects the pixel values at specific coordinates on the cover image, the more the characters are pasted on the cover image PSNR value of its smaller, it indicates that the image quality is getting lower and berdanding PSNR value proportionalto the value of MD image.
KAJIAN KINERJA METODE FUZZY k-NEAREST NEIGHBOR PADA PREDIKS CACAT SOFTWARE Rimbun Siringoringo
METHODIKA: Jurnal Teknik Informatika dan Sistem Informasi Vol. 2 No. 2 (2016): Nopember 2016
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/mtk.v2i2.49

Abstract

This research examines the model of Fuzzy k-Nearest Neighbor (Fk-NN) to predict software defects. Software defects based on three dataset, CM1, JM1 and KC1. Datasets are derived from the promise repository. Feature selection and data normalization applied at the stage of data pre-process. Feature selection based on Correlation-Based Feature Selection (CFS), and data normalized based on min-max method. This research applies Fk-NN method to predict software defects. Performance prediction consisted of five aspects: accuracy, sensitivity and precision. Testing techniques applied in this study is 10-fold Cross Validation. To get the best performance, we applying the varied value of k and m. Range for K value is [1, 9] and m values [1.0, 1.9]. The best performance for CM1 dataset was obtained on a combination of value [k, m] = [9, 1.0]. For JM1 dataset, the best performance was obtained on a combination of value [k, m] = [9, 1.9]. For KC1 dataset, the best performance was obtained on a combination of value [k, m] = [9, 1.5]. The results of this study indicate that the results andperformance classification with Fk-NN method highly depends on the parameters k and m, the selection of appropriate parameters will yield the expected performance
SISTEM PEREKOMENDASI DENGAN SINGULAR VALUE DECOMPOSITION DAN TEKNIK SIMILARITAS PEARSON CORRELATION Rimbun Siringoringo; Jamaluddin; Gortap Lumbantoruan
METHODIKA: Jurnal Teknik Informatika dan Sistem Informasi Vol. 7 No. 1 (2021): Maret 2021
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/mtk.v7i1.257

Abstract

The growth of e-commerce has resulted in massive product information and huge volumes of data. This results in data overload problems. In the case of e-commerce, consumers or users spend a lot of time choosing the goods they need. The urgent question to be answered at this time is how to provide solutions related to intelligent information restrictions so that the existing information is truly information that is by preferences and needs. This research performs information filtering by applying the singular value decomposition method and the Pearson similarity technique to the book recommendation system. The data used is the Book-Crossing Dataset which is the reference dataset for many research recommendation systems. The resulting recommendations are then compared with e-commerce recommendations such as amazom.com. Based on the results of the study obtained data that the results of the recommendations in this study are very good and accurate.
Co-Authors Angely Sinaga Apriani Magdalena Sibarani Arina P. Silalahi Aritonang, Mendarissan Br Nadapdap, Askeline Ruthkenera Br. Hombing, Betseba Br. Siagian, Rut Magdalena Darwis Robinson Manalu Dedy Arisandi Delvi Natalina Br Tarigan Donda Sari Tiur Maida Situmorang Edi Kurniawan El Rahmat Jaya Hulu Emma Rosinta Simarmata Ericho Elovando Surbakti Erna Budhiarti Nababan Eva Julia G. Harianja Eva Julia Gunawati Harianja Eva Julia Gunawati Harianja, Eva Julia Gunawati Fati Gratianus Nafiri Larosa Gea, Asaziduhu Giska Yufani Gortap Lumbantoruan Harianja, Eva J. G. Harianja, Eva Julia G. Helen Fransisca Simanungkalit Hutagalung, Estri Aprilia Hutapea, Marlyna I. Imelda S. Dumayanti Indra Kelana Jaya Ira Mirantika Br. Ginting Jamaluddin Jamaluddin Jamaluddin Jepriyanta N. Brahmana Jimmy F. Naibaho Jonathan H. Saragih Jujur Marentha Nababan Junika Napitupulu Laia, Sadarman Lyna M. N. Hutapea Mahendra Tlapta Sitepu Marpaung, Flora Merry Anna Napitupulu, Merry Anna Moris Raichel Sitanggang Mufria J. Purba Nababan, Maria Tesalonika Naikson Fandier Saragih Nainggolan, Rena Napitupulu, Thomson Januari Ndruru, Yufita Friska Nduru, Yiska Sonia Kristin Nova Soraya Simanjuntak Panjaitan, Calvin Nicolas Perangin Angin, Resianta Perangin-angin , Resianta Petty Exclesia Pardosi Posma S. M. Lumbanraja Purba, Eviyanti N. Purba, Eviyanti Novita Rajagukguk, Marshanda Febyola Rasmulia Sembiring Reka Tini Sipayung Sipayung Rena Nainggolan Resianta Perangin Angin Resianta Perangin-Angin Rijois I. E. Saragih Rumahorbo, Benget Sibagariang, Roida Ferawati Sidabutar, Dewi Purnama Silalahi, Calvin Matius Simanjuntak, Stevani L. Z. Sitindaon, Ester Sitorus, Hegi Audria Stevani L. Z. Simanjuntak Sutarman Thomson J. Napitupulu Tobing, Putra Halomoan Widya Ompusunggu Winda Sari Sitanggang Yessy Dearni C. Saragih Yohana Angelita Manullang Yosephine Sembiring Zakarias Situmorang Zalukhu, Delianus