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All Journal Jurnal TIMES Sinkron : Jurnal dan Penelitian Teknik Informatika Journal Information System Development METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi METHODIKA: Jurnal Teknik Informatika dan Sistem Informasi Jurnal Informatika Kaputama (JIK) Jurnal Pengabdian Pada Masyarakat METHABDI TAMIKA: Jurnal Tugas Akhir Manajemen Informatika & Komputerisasi Akuntansi

Resianta Perangin-Angin

Universitas Methodist Indonesia

Author-ID : 2546611

Religion Agriculture, Biological Sciences & Forestry 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

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Analisa Alokasi Memori dan Kecepatan Kriptograpi Simetris Dalam Enkripsi dan Dekripsi Resianta Perangin-angin; Indra Kelana Jaya; Benget Rumahorbo; Berlian Juni R Marpaung
Journal Information System Development Vol 4, No 1 (2019): Journal Information System Development (ISD)
Publisher : UNIVERSITAS PELITA HARAPAN

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Currently the focus of cryptography is on the security and speed of data transmission. Cryptography is the study of how to secure information. This security is done by encrypting the information with a special key. This information before being encrypted is called plaintext. After being encrypted with a key called ciphertext. At present, AES (Advanced Encryption Standard) is a cryptographic algorithm that is safe enough to protect confidential data or information. In 2001, AES was used as the latest cryptographic algorithm standard published by NIST (National Institute of Standard and Technology) in lieu of the DES (Data Encryption Standard) algorithm that has expired. The AES algorithm is a cryptographic algorithm that can encrypt and decrypt data with varying key lengths, namely 128 bits, 192 bits, and 256 bits. From the results of tests carried out for speed and classification memory, it can be concluded that the AES cryptographic algorithm is superior or faster if the size or size of the plaint text is not so large, because for the smaller AES algorithm the speed ratio in terms of encryption will become more fast, it becomes very different for the Blowfish algorithm itself where for large sizes plaint text can be encrypted faster than AES but for smaller sizes Blowfish is certainly slower in that case, for memory allocation in this case from the tests performed it can be concluded that AES requires more storage space or larger memory allocation compared to the blowfish algorithm

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

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.

APLIKASI PENGADUAN MASYARAKAT BERBASIS MOBILE WEB DI KECAMATAN TARUTUNG Sofya C. Sitompul; Jamaluddin Jamaluddin; Roni Jhonson Simamora; Resianta Perangin-angin
METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi Vol. 3 No. 2 (2019): METHOMIKA: Jurnal Manajemen Informatika & Komputersisasi Akuntansi
Publisher : Universitas Methodist Indonesia

Public complaints are an important element in government agencies because complaints aim to improve the shortcomings of activities carried out by the government. Complaints from the Tarutung Subdistrict community have not been fully maximized regarding administrative activities in the sub-district including the schedule for distributing Raskin, taking family card files, ID cards, and others. Based on the background of the above thoughts can be identified as a problem that is how to design an application for public complaints services and information that can be felt directly by the community without having to spend much time on the complaints process. The purpose of this study is to build a mobile web-based application that can be accessed through a web browser. This application is built with the PHP programming language and uses the MySQL database as a database server. The results of this research are complaints applications that provide convenience in terms of online public complaints.

PENERAPAN ALGORITMA SAFE-LEVEL-SMOTE UNTUK PENINGKATAN NILAI G-MEAN DALAM KLASIFIKASI DATA TIDAK SEIMBANG Resianta Perangin-angin; Eva Julia Gunawati Harianja; Indra Kelana Jaya; Benget Rumahorbo
METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi Vol. 4 No. 1 (2020): METHOMIKA: Jurnal Manajemen Informatika & Komputersisasi Akuntansi
Publisher : Universitas Methodist Indonesia

Klasifikasi data yang tidak seimbang merupakan masalah yang krusial pada bidang machine learning dan data mining. Ketidakseimbangan data memberikan dampak yang buruk pada hasil klasifikasi dimana kelas minoritas sering disalah klasifikasikan sebagai kelas mayoritas. Dimana kelompok kelas minoritas (minority) adalah kelompok kelas yang memiliki data lebih sedikit, dan kelompok kelas mayoritas (mayority) adalah kelompok kelas yang memiliki jumlah data lebih banyak. Data tidak seimbang adalah suatu kondisi dimana jumlah contoh dari salah satu kelas jauh lebih banyak dari kelas yang lain. Alasan buruknya kinerja metode klasifikasi biasa yang digunakan pada data tidak seimbang adalah bahwa tujuan metode klasifikasi dalam meminimumkan galat secara keseluruhan tidak dapat tercapai karena kelas minoritas hanya sedikit memberikan kontribusi, selain itu keputusan akhir yang dihasilkan tidak tepat karena terjadinya bias. Hal ini disebabkan oleh salah satu kelas mendominasi dalam hal jumlah. Dalam penelitian ini akan berfokus pada peningkatan nilai G-Mean dari dataset yang digunakan, dengan menerapkan algoritma Safe-Level-Smote. Dari hasil ujicoba yang dilakukan terhadap dua dataset yakni Abalon dan Vowel, untuk skema Smote + k-NN nilai G-Mean yang didapat yakni 0,47 untuk dataset Abalon dan 0.94 untuk dataset Vowel. Seletah dilakukan ujicoba terhadap dataset yang sama menggunakan skema Safe-Level-Smote menggunakan algoritma klasifikasi k-NN didapat hasil G-Mean 0,59 untuk dataset Abalon dan 1.00 Untuk dataset Vowel, rerata dari kenaikan nilai G-Mean terhadap algoritma Smote sebesar 12,68%. Hal ini membuktikan bahwasanya algoritma Safe-Level-Smote dapat meningkatkan nilai G-Mean pada klasifikasi data tidak seimbang menggunakan algoritma klasifikasi k-Nearst Neighbors.

EVALUASI CLUSTER SOCIAL MEDIA DATA IN TOURISM DOMAIN MENGGUNAKAN K-MEANS CLUSTERING Rena Nainggolan; Fenina Adline Twince Tobing; Emma Rosinta Simarmata; Resianta Perangin-angin
METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi Vol. 4 No. 1 (2020): METHOMIKA: Jurnal Manajemen Informatika & Komputersisasi Akuntansi
Publisher : Universitas Methodist Indonesia

Clustering adalah salah satu teknik Data Mining. Clustering bekerja dengan cara menggabungkan sejumlah data atau objek kedalam satu klaster, dengan tujuan setiap data dalam satu klaster tersebut akan mempunyai data yang semirip mungkin dan berbeda dengan data atai objek yang berada pada kelompok lain. K-Means Clustering memiliki kemampuan untuk melakukan komputasi yang relatif cepat dan efisien dalam mengabungkan data dalam jumlah yang cukup besar. Dalam penelitian ini, peneliti akan menggunakan metode K-mean clustering yang diterapkan pada data mining pada Online Reviews pada data TripAdvisor. Implementasi proses K-Means Clustring menggunakan Weka, Atribut yang digunakan adalah galeri seni, klub dansa, bar jus, restoran, museum, resor, taman atau tempat piknik, pantai, teater, dan lembaga keagamaan. Menghasilkan jumlah cluster 4 (k=4) dengan cluster pertama sebanyak 178 (18%) reviews traveler, cluster kedua 243 (25%) reviews traveler, cluster ketiga 228 (23%) reviews traveler, cluster keempat 331(34%) reviews traveler.

SIMULASI MONTE CARLO DALAM MEMPREDIKSI PEMAKAIAN OBAT PENYAKIT GIGI DAN MULUT PADA RUMAH SAKIT Resianta Perangin-angin; Ika Yusnita Sari; Elvika Rahmi; Roni Jhonson Simamora
METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi Vol. 6 No. 2 (2022): METHOMIKA: Jurnal Manajemen Informatika & Komputersisasi Akuntansi
Publisher : Universitas Methodist Indonesia

The use of drugs in patients with dental disease is a necessity that needs to be considered by the hospital in providing medical services to patients. Adequate and well-managed drug supply prevents shortages or excess drug stocks. So it needs good planning in managing and monitoring drug stocks appropriately. This study aims to make predictions in the use of dental disease drugs by using a monte carlo simulation. The data used is data on the use of drugs for dental diseases from 2020 to 2022. The data on drug use processed were 12 types of drugs. The data will be processed based on the Monte Carlo simulation stages. The results of using the Monte Carlo Simulation are to obtain predictions of the use of dental disease drugs with an accuracy value reaching 89.14%. Based on the accuracy value obtained, the Monte Carlo simulation can be used to predict drug use in the future. So that the supply of dental disease medicine is maintained.

TEXT MINING DAN KLASIFIKASI MULTI LABEL MENGGUNAKAN XGBOOST Rimbun Siringoringo; Jamaluddin Jamaluddin; Resianta Perangin-angin
METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi Vol. 6 No. 2 (2022): METHOMIKA: Jurnal Manajemen Informatika & Komputersisasi Akuntansi
Publisher : Universitas Methodist Indonesia

The conventional classification process is applied to find a single criterion or label. The multi-label classification process is more complex because a large number of labels results in more classes. Another aspect that must be considered in multi-label classification is the existence of mutual dependencies between data labels. In traditional binary classification, classification analysis only aims to determine the label in the text, whether positive or negative. This method is sub-optimal because the relationship between labels cannot be determined. To overcome the weaknesses of these traditional methods, multi-label classification is one of the solutions in data labeling. With multi-label text classification, it allows the existence of many labels in a document and there is a semantic correlation between these labels. This research performs multi-label classification on research article texts using the ensemble classifier approach, namely XGBoost. Classification performance evaluation is based on several metrics criteria of confusion matrix, accuracy, and f1 score. Model evaluation is also carried out by comparing the performance of XGBoost with Logistic Regression. The results of the study using the train test split and cross-validation obtained an average accuracy of training and testing for Regression Logistics of 0.81, and an average f1 score of 0.47. The average accuracy for XGBoost is 0.88, and the average f1 score is 0.78. The results show that the XGBoost classifier model can be applied to produce a good classification performance.

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

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.

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

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.

SISTEM INFORMASI TRACER STUDY ALUMNI PROGRAM STUDI D-III MANAJEMEN INFORMATIKA DAN KOMPUTERSASI AKUNTANSI UNIVERSITAS METHODIST INDONESIA Robert Simangunsong; Roni Jhonson Simamora; Resianta Perangin-angin
TAMIKA: Jurnal Tugas Akhir Manajemen Informatika & Komputerisasi Akuntansi Vol 1 No 1 (2021): TAMIKA: Jurnal Tugas Akhir Manajemen Informatika & Komputerisasi Akuntansi
Publisher : Universitas Methodist Indonesia

Tracer Study or alumni tracking is one of the methods used by several universities in Indonesia, to obtain input and feedback from alumni. Input and feedback obtained from alumni can be an improvement and development of the quality of the education system implemented at the university. Tracer studies are also useful in providing important information about the relationship between institutions and the world of work. The Tracer Study of the Indonesian Methodist University is still using a form (Paper Based), one of which is the D-III study program of Informatics Management and Computerized Accounting. The D-III study programs from previous years have produced many alumni who are ready to work, alumni data and the management system have not been saved to the database, so the stored data can be damaged, lost and it will take time to find alumni data. Therefore, a web-based tracer study information system is needed so that the system can be computerized. The website is built using the HTML, PHP, Bootstrap and MYSQL programming languages as a data storage system or commonly called a database. The existence of this alumni tracer study website can facilitate the process of implementing the alumni tracer study. The system built is expected to improve and develop the quality of the current system.

Co-Authors Bangun, Joy Erivan Pratama Berlian Juni R Marpaung Br. Batubara, Anggi Natasya Br. Karo, Selli Afnita Br. Sembiring Pelawi, Pindi Alpioninta Darwis Robinson Manalu Delvi Natalina Br Tarigan Elisabeth, Duma Megaria Elvika Rahmi Emma Rosinta Simarmata Eva Julia G. Harianja Eva Julia Gunawati Harianja Eva Julia Gunawati Harianja, Eva Julia Gunawati Eviyanti N. Purba Fenina Twince Tobing Ginting Babo, Aris Franata Giska Yufani Gortap Lumbantoruan Harianja, Eva J. G. Harianja, Eva Julia G. Hutagalung, Estri Aprilia Hutagaol, Ryan Philip Hutapea, Marlyna I. Ijonris, Yusuf Ika Yusnita Sari Indra Kelana Jaya Jamaluddin Jamaluddin Jamaluddin Jepriyanta N. Brahmana Jimmy F. Naibaho Jonathan H. Saragih Jonathan Hamonangan Saragih Jujur Marentha Nababan Junika Napitupulu Lyna M. N. Hutapea Mahendra Tlapta Sitepu Marpaung, Berlian Juni R Marpaung, Flora Moris Raichel Sitanggang Mufria J. Purba Nainggolan, Rena Napitupulu, Thomson Januari Paiman Nababan Panjaitan, Calvin Nicolas Petty Exclesia Pardosi Purba, Eviyanti N. Purba, Eviyanti Novita Rasmulia Sembiring Rena Nainggolan Reynaldi Pantun Sianturi Rijois I. E. Saragih Rimbun Siringoringo Rimbun Siringoringo, Rimbun Robert Simangunsong Rumahorbo, Benget Siboro, Yohana Natalia Sidabalok, Valentino Sihaloho, Senta Egrioni Simanjuntak, Stevani L. Z. Simanullang, Sanco Siringoriongo, Rimbun Sitepu, Fernanda Jekita F. Sitorus, Hegi Audria Sofya C. Sitompul Tobing, Fenina A. T. Torong, Yepta Efraim Yohana Angelita Manullang Zalukhu, Delianus

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