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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

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KLASIFIKASI DATA TIDAK SEIMBANG MENGGUNAKAN ALGORITMA SMOTE DAN k-NEAREST NEIGHBOR Rimbun Siringoringo
Journal Information System Development Vol 3, No 1 (2018): Journal Information System Development (ISD)
Publisher : UNIVERSITAS PELITA HARAPAN

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

Abstract

Unbalanced data classification is a crucial problem in the field of machine learning and data mining. Data imbalances have a poor impact on classification results where minority classes are often misclassified as a majority class. k-Nearest Neighbor is one of the most popular and simple classification methods but it is not equipped with the ability to work on unbalanced datasets. In this study, the Synthetic Minority Over-Sampling Technique (SMOTE) was applied to solve the class imbalance problem on the Credit Card Fraud dataset. By applying the 10-cross-validation evaluation scheme, it was found that SMOTE increases the mean of  G-Mean by 53.4% to 81.0% and the mean of  F-Measure by 38.7 to 81.8%Keywords: Class imbalance, Synthetic Minority Over-sampling Technique, k-Nearest Neighbor
Text Mining dan Klasterisasi Sentimen Pada Ulasan Produk Toko Online Rimbun Siringoringo; Jamaludin Jamaludin
JURNAL TEKNOLOGI DAN ILMU KOMPUTER PRIMA (JUTIKOMP) Vol. 2 No. 1 (2019): Jutikomp Volume 2 Nomor 1 April 2019
Publisher : Fakultas Teknologi dan Ilmu Komputer Universitas Prima Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34012/jutikomp.v2i1.456

Abstract

Pertumbuhan media sosial dan e-commerce mengubah cara berinteraksi dan menyampaikan pandangan, opini dan mood. Ulasan produk merupakan salah satu bentuk penyampaian opini dan sentimen konsumen terhadap sebuah produk secara online. Ulasan produk saat ini memiliki peranan yang sangat penting dalam mempengaruhi minat konsumen terhadap sebuah produk. Analisis sentimen merupakan pendekatan yang banyak dikerjakan untuk mengekstrak informasi dan menggali opini berkaitan dengan ulasan produk. Analisis sentimen memiliki beberapa tantangan, yang pertama sering sekali hasil analisis sentimen yang dihasilkan oleh model-model prediksi berbeda dengan sentimen yang aktual, tantangan kedua adalah berkaitan dengan cara konsumen mengekpresikan sentimen dan mood selalu berbeda dari satu keadaan ke keadaan berikutnya. Pada penelitian ini dilakukan analisis sentimen berdasarkan ulasan produk sepatu Trendy Shoes merek Denim. Tahapan analisis sentimen terdiri dari pengumpulan data, pemrosesan awal, transformasi data, seleksi fitur dan tahapan klasifikasi menggunakan Suppport Vector Machine. Pemrosesan awal menerapkan tahapan text mining yakni case folding, non alpha numeric removal, stop words removal, dan stemming. Hasil analisis sentimen diukur menggunakan kriteria Akurasi, G-Mean, dan F-Measure. Dengan menerapkan pengujian pada tiga jenis data sentimen diperoleh hasil bahwa Suppport Vector Machine dapat mengklasifikasi sentimen dengan baik. Performa Suppport Vector Machine dibandingkan dengan metode K-Nearest Neighor. Hasil klasifiasi sentimen menggunakan Suppport Vector Machine lebih unggul dari K-Nearest Neighbor.
SEGMENTASI DAN PERAMALAN PASAR RETAIL MENGGUNAKAN XGBOOST DAN PRINCIPAL COMPONENT ANALYSIS Rimbun Siringoringo; Resianta Perangin-angin; Mufria J. Purba
METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi Vol. 5 No. 1 (2021): METHOMIKA: Jurnal Manajemen Informatika & Komputersisasi Akuntansi
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1000.503 KB) | DOI: 10.46880/jmika.Vol5No1.pp42-47

Abstract

The growth of the online retail market in Indonesia is an excellent business opportunity. It is predicted that this growth will continue to move upward due to the increasing internet penetration. With greater exposure to brands, products and offerings, consumers become smarter and wiser in their purchasing decisions. Offering goods and services that match the tastes and behavior of consumers is very important to maintain business continuity. So far, the models developed are divided into two major parts, namely the time series approach and machine learning. In this study, segmentation and forecasting of online retail sector sales were carried out using extreme gradient boosting (XGBoost). The data used in this study is an online retail dataset obtained from the UCI repository. The k-means clustering (KMC) method is applied to determine the target or data class. Principal component analysis (PCA) is applied to reduce data dimensions by eliminating irrelevant features. Model evaluation is based on confusion matrix and macro average ROC curve. Based on the research results, XGBoost can perform retail data classification well, this can be seen through confusion matrix metrics and ROC curves.
KONSEP PENGAMANAN VIDEO CONFERENCE DENGAN ENKRIPSI AES-GCM PADA APLIKASI ZOOM Jamaluddin Jamaluddin; Naikson Fandier Saragih; Roni Jhonson Simamora; Rimbun Siringoringo; Eviyanti Novita Purba
METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi Vol. 4 No. 2 (2020): METHOMIKA: Jurnal Manajemen Informatika & Komputersisasi Akuntansi
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (697.751 KB) | DOI: 10.46880/jmika.Vol4No2.pp109-113

Abstract

The conditions of the Covid-19 pandemic, which began to plague at the end of 2019, brought about major changes to the patterns of interaction in society. Activities that have been carried out directly have begun to shift to activities carried out online. The use of technology, especially in applications for online interaction patterns such as video conferencing applications, is an alternative. The Zoom Cloud Meeting application is widely used by people who initially had doubts about its security system. By implementing end-to-end encryption with AES-256-GCM, it has been able to convince clients on the information security side to keep using the Zoom Cloud Meeting application.
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.
PELATIHAN VIDEO RECORDING DAN EDITING VIDEO PADA SMK SWASTA GELORA JAYA NUSANTARA MEDAN Gortap Lumbantoruan; Marlyna Infryanty Hutapea; Jamaluddin Jamaluddin; Emma Rosinta Simarmata; Eviyanti Novita Purba; Eva Julia Gunawati Harianja; Resianta Perangin-angin; Rimbun Siringoringo; Moris Raichel Sitanggang; Jonathan H. Saragih; Jujur Marentha Nababan
Jurnal Pengabdian Pada Masyarakat METHABDI Vol 1 No 1 (2021): Jurnal Pengabdian Pada Masyarakat METHABDI
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1397.558 KB) | DOI: 10.46880/methabdi.Vol1No1.pp1-4

Abstract

The purpose of community service activities is to implement the “Tri Dharma” of Higher Education as well as to contribute ideas and transfer technology to teaching staff at SMK Gelora Jaya Nusantara Medan. This service activity was carried out for 2 days, with Video Recording and Video Editing Training materials. The topics given in this training are making video editing media and online learning content. The material given is the use of Filmora X software in video editing, and video recording techniques. This topic is very much needed in order to equip teachers in preparing and delivering subject matter during this COVID-19 pandemic. This topic was deliberately chosen considering that currently teachers are having difficulties in delivering subject matter face-to-face.
PENGENALAN BEBERAPA ALTERNATIF MEDIA PEMBELAJARAN DARING PADA MASA PANDEMI COVID-19 DI SMA MASEHI GBKP BRASTAGI, KABUPATEN KARO, SUMATERA UTARA Mendarissan Aritonang; Mufria J. Purba; Fati Gratianus Nafiri Larosa; Nova Soraya Simanjuntak; Rimbun Siringoringo; Indra Kelana Jaya; Helen Fransisca Simanungkalit; Ericho Elovando Surbakti; Widya Ompusunggu
Jurnal Pengabdian Pada Masyarakat METHABDI Vol 1 No 1 (2021): Jurnal Pengabdian Pada Masyarakat METHABDI
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (795.5 KB) | DOI: 10.46880/methabdi.Vol1No1.pp57-60

Abstract

Community Service Activities is a manifestation of the implementation of the Tri Dharma of Higher Education as well as sharing and contributing ideas as well as the transfer of knowledge and technology for teachers and students at SMA Masehi GBKP, Brastagi. This service activity was carried out for a day, with the material Introduction of Several Alternative Online Learning Media During the COVID-19 Pandemic. The material for the activities carried out included an explanation of several alternative online learning media commonly used in education, including Google Classroom, Edmodo, Easy Class, Moodle, Schoology, Cisco Webex, CloudX and Zoom. This topic is very much needed, especially during the COVID-19 pandemic, and provides various alternative online learning media for teachers and students so as to reduce obstacles in the face-to-face learning process.
PELATIHAN DISAIN WEB BERBASIS HTML 5 DAN SCRIPTING, SERTA PELATIHAN DIGITAL MARKETING KEPADA MASYARAKAT PRA-KERJA DI KOTA MEDAN Rimbun Siringoringo; Resianta Perangin-angin; Rasmulia Sembiring; Mahendra Tlapta Sitepu; Roni Jhonson Simamora; Jimmy F. Naibaho; Marlyna Infryanty Hutapea; Rena Nainggolan; Eva Julia G. Harianja; Mufria J. Purba; Jepriyanta N. Brahmana; Petty Exclesia Pardosi; Yohana Angelita Manullang
Jurnal Pengabdian Pada Masyarakat METHABDI Vol 1 No 2 (2021): Jurnal Pengabdian Pada Masyarakat METHABDI
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1833.805 KB) | DOI: 10.46880/methabdi.Vol1No2.pp80-83

Abstract

The aims and objectives of this Community Service are to implement the Tridarma of Higher Education and contribute ideas and transfer technology to the pre-employment force in Medan City. As we all know that the application of information technology, especially websites, has touched all aspects of human life such as business, education, government, health, and other fields. Therefore, skilled personnel is needed in the field of web design in order to meet market needs and employment needs. This community service activity was carried out for fifteen days with training materials on web design and digital marketing. This PkM was carried out in collaboration with partners, namely the Labor Agencies Office of Medan City and with PT. Hagatekno Mediata.
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. Ijonris, Yusuf 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