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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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Journal : METHOMIKA: Jurnal Manajemen Informatika

 1 
MODEL HIBRID GENETIC-XGBOOST DAN PRINCIPAL COMPONENT ANALYSIS PADA SEGMENTASI DAN PERAMALAN PASAR Siringoringo, Rimbun; Perangin-angin, Resianta; Jamaluddin, Jamaluddin
METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi Vol. 5 No. 2 (2021): METHOMIKA: Jurnal Manajemen Informatika & Komputersisasi Akuntansi
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (533.828 KB) | DOI: 10.46880/jmika.Vol5No2.pp97-103

Abstract

Extreme Gradient Boosting(XGBoost) is a popular boosting algorithm based on decision trees. XGBoost is the best in the boosting group. XGBoost has excellent convergence. On the other hand, XGBoost is a Hyper parameterized model. Determining the value of each parameter is classified as difficult, resulting in the results obtained being trapped in the local optimum situation. Determining the value of each parameter manually, of course, takes a lot of time. In this study, a Genetic Algorithm (GA) is applied to find the optimal value of the XGBoost hyperparameter on the market segmentation problem. The evaluation of the model is based on the ROC curve. Test result. The ROC test results for several SVM, Logistic Regression, and Genetic-XGBoost models are 0.89; 0.98; 0.99. The results show that the Genetic-XGBoost model can be applied to market segmentation and forecasting.
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.
PENGONTROLAN KEAMANAN SISTEM KOMPUTER CLIENT DARI SERANGAN HACKER DAN VIRUS KOMPUTER SECARA JARAK JAUH (REMOTE SERVER) DENGAN MENGGUNAKAN SSH Jamaluddin Jamaluddin; El Rahmat Jaya Hulu; Rimbun Siringoringo
METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi Vol. 7 No. 1 (2023): METHOMIKA: Jurnal Manajemen Informatika & Komputersisasi Akuntansi
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/jmika.Vol7No1.pp123-127

Abstract

Computer system security is very important to be considered by computer users to protect their computers from attacks such as hackers and computer viruses that can take data and damage the user's computer system. Hacker is a person or party who has the skill in breaking through and sneaking to access a computer without the user's permission and can take data and even damage the system on the user's computer. And a Computer Virus is a computer program that copies and inserts copies into the program and can damage the computer system. So that by using SSH (Secure Shell) can control and check computer security from hacker attacks and computer viruses without having to come to the location where there is a client computer or done remotely (Remote Server).
MODEL BIDIRECTIONAL LSTM UNTUK PEMROSESAN SEKUENSIAL DATA TEKS SPAM Siringoringo, Rimbun; Jamaluddin, Jamaluddin; Perangin-angin, Resianta; Harianja, Eva Julia Gunawati; Lumbantoruan, Gortap; Purba, Eviyanti Novita
METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi Vol. 7 No. 2 (2023): METHOMIKA: Jurnal Manajemen Informatika & Komputersisasi Akuntansi
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/jmika.Vol7No2.pp265-271

Abstract

This study examines the LSTM-based model for processing spam in text data. Spam poses several dangers and risks, both for individuals and organizations. Spam can be a nuisance that hampers both individual and organizational productivity. Much spam contains fraudulent or phishing attempts to obtain sensitive information. Spam detection using deep learning involves the utilization of algorithms and deep neural network models to accurately classify messages as either spam or not spam. Typically, spam detection systems use a combination of these methods to improve the accuracy of identifying spam messages. This study applies the Bi-LSTM deep learning model to sequentially process text (sequencing). The performance of the model is determined based on the loss and accuracy. The data used are the Spam SMS and Spam Email datasets. The test results show that the Bi-LSTM model demonstrates better performance on all tested datasets. Bi-LSTM is able to capture textual patterns from both the context and the text itself, as it can combine information from both directions. The test results prove that the Bi-LSTM model is more effective in text comprehension. So we need to use Snort to maintain network security. Snort is a useful software for observing activity in a computer network. Snort can be used as a lightweight Network Intrusion Detection System (NIDS). Detection is carried out based on the rules that have been described by the administrator in the directory rules contained in the configuration file. Snort can analyze real time alerts, where the mechanism for entering alerts can be in the form of a user syslog, file or through a database. So we can detect attacks on computer networks early.
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