Claim Missing Document
Check
Articles

Found 20 Documents
Search

Implementation of Clustering Methods to Know Electricity Energy Sold Average Customer Type Reinhard Oktaveri Gultom; Estomih Wau; Jodi Alexsander Laia; Ivan Leonardo Silaban; Yennimar Yennimar
Jurnal Mantik Vol. 5 No. 2 (2021): Augustus: Manajemen, Teknologi Informatika dan Komunikasi (Mantik)
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/jurnalmantik.Vol5.2021.1475.pp1119-1126

Abstract

The need for electrical energy in Indonesia continues to increase from time to time. In realizing the need for electrical energy, it is important to order electrical energy based on the type of customer. In collecting this electrical energy, grouping is needed. The results of the gathering can be utilized by PT. PLN to anticipate disruptions in the supply of electrical energy. This investigation plans to determine the electrical energy sold by type of customer (KWH) in 2016 to 2019 in Indonesia and dissect the power requirements in 2019. The strategy used is group development using rapidminner. The variables that cause the utilization of the tourism industry in Indonesia are Population, Economic and Industrial Developments. To meet the need for the use of electrical energy which continues to increase from year to year, the matters and groupings of the use of electrical energy for the use of electrical energy were completed in 2014 to 2019. The information and targets used in the meeting were gross domestic electricity, group information and power information. (per customer type and power utilization). from 2011 to 2015. The side effect of ordering electrical energy in Indonesia using the fuzzy bunching strategy was 272,630 KWH in 2019, an increase of 85,089 KWH with an annual normal increase of 6.96%. the result group of the strategy has a normal of 18,730 KWH against RUPTL.
Analysis of Sales Vitamins Drugs Covid-19 Pandemic with the Random Forest Method Yennimar Yennimar; Miko Pasaribu; Laila Hendrina; Ayu Widila; Dono Sitinjak
Jurnal Mantik Vol. 5 No. 3 (2021): November: Manajemen, Teknologi Informatika dan Komunikasi (Mantik)
Publisher : Institute of Computer Science (IOCS)

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

Abstract

During the covid-19 pandemic that occurred in Indonesia until the new normal period, consumer demand for a vitamin drug was fast and unpredictable, thus making pharmacies must be able to plan the optimal supply of vitamin drugs based on the graph of public demand during the pandemic and new normal. This means that the pharmacy does not experience a shortage of stock or excess stock. Therefore, all systems that can predict sales of vitamin drugs are needed during the new normal pandemic. To be able to make predictions, an appropriate method is needed to get accurate results. One of them is the Random Forest method. With Random Forest, the data is predicted based on attribute data so as to produce a conclusion about the value of the desired attribute. Based on this study, 200 sales data of vitamin drugs were taken during the pandemic and new normal with categories of vitamin B complex drugs, vitamins C, D, E, K and Multivitamins and the attributes used were vitamin brand, category, sales conditions, price and sales category. and doesn't work. The test results from this study, it was found that the prediction of vitamin drug sales during the new normal pandemic using the Random Forest method obtained 100% accuracy for testing data with a composition of 80:20, 70:30 and 60:40, so that vitamin drugs would still be sold in new normal.
Comparison Analysis of SVM Algorithm with Linear Regression in Predicting used Car Prices Yennimar Yennimar; Kelvin Kelvin; Suwandi Suwandi; Amir Amir
Jurnal Mantik Vol. 5 No. 4 (2022): February: Manajemen, Teknologi Informatika dan Komunikasi (Mantik)
Publisher : Institute of Computer Science (IOCS)

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

Abstract

During the high activity , car has become a basic need. On the other hand, the price of new car is getting higher. To meet these needs, people are looking for alternatives by buying used cars. One of the factors to consider when looking for a used car is price. In this study, two algorithms that are quite popular in terms of prediction will be tested, namely the Support Vector Machine algorithm and the Linear Regression algorithm in predicting used car prices. Support Vector Machine is a supervised learning method that analyzes data and recognizes patterns for regression. Support Vector Machine has the ability to solve linear and nonlinear problems. Linear Regression Algorithm is a modeling and analysis of numerical data consisting of one or more independent variables and the value of the dependent variable, with the aim of using regression analysis to estimate the value of the dependent variable based on the value of the independent variable. The result of this research is that the SVM method can perform better than linear regression. SVM can perform kernel-tricks that can handle non-linear data, thus making the non-linear data appear to be linear. but this cannot be done by Linear regression.
Comparison Of Jenkins Box Method And Multiple Linier Regression In Predicting The Noble Metal Price Bayu Gunara; Yennimar Yennimar
Jurnal Teknik Informatika C.I.T Medicom Vol 11 No 2 (2019): Informatik
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (618.418 KB) | DOI: 10.35335/cit.Vol11.2019.15.pp66-73

Abstract

Nowadays, gold investment practitioners generally use instinct and guess in investing in gold. This is certainly a problem because it has a high error margin. To solve these problems, the forecasting process can be carried out.To be able to forecast gold prices with low error rates, various studies have been conducted. The Box-Jenkins method performs better than other methods in predicting the price of gold, because the Box-Jenkins method applies forecasting by relying on the historical statistics of gold prices beforehand. The Box-Jenkins method is an iterative of choosing the best model for the stationary series of a group of linear time series models called the ARIMA (Autoregressive Integrated Moving Average) model. However, the ARIMA method is a complex method and is not easy to use and requires a long execution time to obtain forecasting results with a high degree of accuracy. To improve the accuracy of prediction results from ARIMA, the ARIMA method can be combined with the multiple regression method into a hybrid method. The Multiple Linear Regression Method is a mathematical technique that minimizes the difference between the actual value and the predicted value.The results of this study are an application of forecasting the price of gold using the ARIMA method and Multiple Linear Regression. The application also provides a facility to test the results of the methods used. Based on the results of testing the accuracy of the prediction results from the hybrid method with 30 data = 48%, 60 data = 40%, and 118 data = 40.81%.
Analisis Wawasan Penjualan Supermarket dengan Data Science Mawaddah Harahap; Fachrul Rozi; Yennimar Yennimar; Saut Dohot Siregar
Data Sciences Indonesia (DSI) Vol. 1 No. 1 (2021): Article Research Volume 1 Issue 1, June 2021
Publisher : ITScience (Information Technology and Science)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (771.16 KB) | DOI: 10.47709/dsi.v1i1.1173

Abstract

Data science atau ilmu data adalah suatu disiplin ilmu yang khusus mempelajari data, khususnya data kuantitatif (data numerik), baik yang terstruktur maupun tidak terstruktur. Pemanfaatkan siklus dalam pengembangan analisis untuk membuat keputusan bisnis yang praktis dan berbasis data, dan menerapkan perubahan berdasarkan keputusan tersebut. Makalah ini menyajikan analisis wawasan yang berguna pada kumpulan transaksi penjualan supermarket selama 3 bulan dari 3 cabang yang berbeda. Berdasarkan hasil analisis nilai rating terting adalah 10, terendah 4 dengan rata-rata rating produk 6.9 dan wanita lebih dominan membeli produk Aksesoris Fashion dan pria Kesehatan & Kecantikan
Estimation Of Drug Stocks In Pharmacies In The Covid-19 Era Using The Fp-Growth Algorithm Yennimar; Johanes T. Gultom; William S. Purba; Dewi S. Sihotang
Jurnal Mantik Vol. 6 No. 2 (2022): August: Manajemen, Teknologi Informatika dan Komunikasi (Mantik)
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/mantik.v6i2.2823

Abstract

In the era of covid-19, the response in controlling covid-19 requires an adequate supply of medicines in hospitals and pharmacies. The supply of these drugs is felt to be very important because seeing the impact of the covid-19 virus is very dangerous for human health. Therefore, the existence of the supply of medicines in pharmacies during this Covid era really needs to be considered. Every transaction of the sale of the drug in pharmacies is always recorded. This sales transaction data can be processed to find certain patterns in selling drugs in a certain period of having so many drug sales transaction activities. If the sales transaction data is analyzed, a pattern can be found out that is very helpful in estimating drug stocks from the drug sales data. To be able to estimate drugs, the right method is needed in order to get accurate results. One of them is the Fp-Growth method. With Fp-Growth, data is entered for calculations based on drug sales data so as to produce conclusions of minimum support and minimum confidence values. Based on this study, 35 data on drug sales transactions were taken. The test results of this study obtained calculation results from simultaneous drug sales data that are often purchased by consumers with the highest accuracy are 17.14% and 50%, namely Paracetamol and CTM.
Implementation of artificial neural network and support vector machine algorithm on student graduation prediction model on time Yennimar Yennimar; M. Rafi Faturrahman; Siwa Nesen; M. Anhar Guci; Samuel Rifaldi Pasaribu
Jurnal Mantik Vol. 7 No. 2 (2023): Agustus: Manajemen, Teknologi Informatika dan Komunikasi (Mantik)
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/mantik.v7i2.3992

Abstract

This research aims to evaluate how Artificial Neural Network (ANN) and Support Vector Machine (SVM)  algorithms can be used to predict student graduation on time. This research uses student data from Universitas Prima Indonesia (UNPRI) Medan to build a prediction model. ANN and SVM methods have been applied and compared to see the performance of each model. The test results show that the SVM model is superior in terms of accuracy and computational speed compared to the ANN model. In addition, the test results also show that the SVM model can be used to predict student graduation on time with an accuracy of 96.34%. This result shows that the SVM model is more effective in predicting student graduation on time compared to the ANN model
Implementasi Cloning Data Menggunakan Aplikasi EaseUS Partition Master Dengan Menerapkan Metode Workflow Yennimar -; Julfan Farman Zebua; Wikesyah Putri Sitorus; Kristina Ginting; Yans Y.M.P. Situmorang
JURNAL TEKNOLOGI DAN ILMU KOMPUTER PRIMA (JUTIKOMP) Vol. 6 No. 2 (2023): Jutikomp Volume 6 Nomor 2 Oktober 2023
Publisher : Fakultas Teknologi dan Ilmu Komputer Universitas Prima Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34012/jutikomp.v6i2.4028

Abstract

Data cloning implementation is an essential process in information technology to duplicate content from one storage device to another. EaseUS Partition Master is a popular software used to implement this data cloning process. This abstract discusses the implementation of data cloning using EaseUS Partition Master. Data cloning is an efficient way to duplicate the entire contents of one hard drive or partition to another storage device. EaseUS Partition Master offers extensive capabilities in performing data cloning with various features that can facilitate users in carrying out the process. One of the most commonly used cloning features is "Disk Clone," which allows users to duplicate an entire hard drive to another hard drive. In this case, EaseUS Partition Master will automatically detect all existing partitions, and users can select the partitions they want to clone. In addition, EaseUS Partition Master also provides a "Partition Clone" feature, which allows users to clone a specific partition from one hard drive to another. This feature is helpful if users only want to duplicate data from a few selected partitions. Once the user has selected the desired type of cloning, EaseUS Partition Master will guide the user through the following steps. This includes selecting a target hard drive or partition to place the cloned data on and customizing the cloning settings according to the user's needs. During the cloning process, EaseUS Partition Master provides a clear and informative view of the cloning progress. Users can track and monitor the process to ensure everything is going well. Overall, implementing data cloning using EaseUS Partition Master provides a reliable and easy-to-use solution for users who need an efficient cloning process. With its comprehensive features and intuitive interface, the software allows users to clone their data without any significant difficulties.
PEMASARAN ROTI JALA UNTUK MENINGKATKAN EKONOMI KELUARGA DI LINGKUNGAN 18 RENGAS PULAU MEDAN Sri Wahyuni Tarigan; Widya Fernanda Putri; Anita Christine Sembiring; Uni Pratama Tarigan; Yennimar Yennimar
Jurnal Pemberdayaan Sosial dan Teknologi Masyarakat Vol 3, No 2 (2023): Desember 2023
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/jpstm.v3i2.1533

Abstract

Abstract: Roti jala is a typical food of the Malay people in North Sumatra. This dish is also often found in Riau. In Medan (Deli) North Sumatra, this food is often served with chicken curry or goat curry mixed with pickled pineapple and can also be served with pickled cucumber and carrots. Roti jala is a combination of Indian and Malay cuisine. Along with the development of the times, roti jala is not only sold by the Malay community, now various tribes have made and marketed it, including the community of Environment 18, Rengas Pulau Subdistrict. People in the 18 district of Rengas Pulau generally sell roti jala as an additional income of 70% and a main income of 30% to improve the family economy.Keyword: delicious bread meshAbstrak: Roti jala adalah makanan khas masyarakat Melayu di Sumatera Utara. Hidangan ini juga banyak di temui di Riau. Di Medan (Deli) Sumatera Utara makanan ini sering disajikan dengan gulai kari ayam atau gulai kari kambing di campur acar nenas dan bisa juga dengan acar timun dan wortel. Roti jala merupakan perpaduan masakan India dengan Melayu. Seiring dengan perkembangan zaman roti jala tidak hanya di jual oleh masyrakat Melayu saja, saat ini berbagai suku telah membuat dan memasarkannya termasuk masyrakat Lingkungan 18 Kelurahan Rengas Pulau. Masyarakat di lingkungan 18 Kelurahan Rengas Pulau umumnya menjual roti jala sebagai penghasilan tambahan sebanyak 70% dan penghasilan utama sebanyak 30% untuk meningkatkan ekonomi keluarga.Kata kunci: jala roti
SOSIALISASI KANDUNGAN ZAT BERBAHAYA PADA PANGAN JAJAN ANAK SEKOLAH DENGAN METODE UJI CEPAT DI SD. NUR FADILLAH Sri Wahyuni Tarigan; Widya Fernanda Putri; Anita Christine Sembiring; Uni Pratama Tarigan; Yennimar Yennimar; Christin Erniati Panjaitan; Dini M. Hutagalung
Jurnal Pemberdayaan Sosial dan Teknologi Masyarakat Vol 4, No 2 (2024): Desember 2024
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/jpstm.v4i2.2546

Abstract

Abstract: Currently, the food circulating in society, especially in elementary schools, mostly consists of processed foods laden with additives, the safety of which for children is unknown.The purpose of this activity is to provide information and knowledge about the dangers of consuming snacks that contain harmful substances such as formalin, borax, and synthetic dyes in the school environment. This initiative also aims to introduce methods for testing children's snacks that contain harmful substances in schools. The participants of the activity are teachers and 6th-grade students at SD Nur Fadhillah Medan. The activity included socialization about the dangers of snacks containing borax, formalin, and textile dyes through a demonstration of rapid testing using a rapid test kit to test for formalin, borax, and synthetic dyes. The results obtained after testing school snacks using the rapid test method showed that 70% of the school children's snacks in Nur-Fadilah contained harmful additives. Keyword: Rhodamin_B Abstrak: Saat ini, makanan yang beredar di masyarakat, khususnya di sekolah dasar, sebagian besar merupakan makanan olahan yang sarat dengan zat aditif,  yang tidak di ketahui keamanannya bagi anak.Tujuan dari kegiatan  ini adalah untuk memberikan informasi dan pengetahuan tentang bahaya mengkonsumsi jajanan  yang mengandung zat berbahaya seperti formalin, boraks, dan pewarna sintetis di lingkungan sekolah. Inisiatif ini juga bertujuan untuk memperkenalkan metode pengujian pangan jajan anak yang mengandung zat berbahaya  di sekolah. Peserta kegiatan adalah guru dan siswa kelas 6 di SD Nur Fadhillah Medan. Kegiatan tersebut meliputi sosialisasi tentang bahaya  jajanan yang mengandung boraks, formalin, dan pewarna tekstil dengan cara  demonstrasi uji cepat  menggunakan rapid tes kit  untuk  menguji formalin, boraks dan pewarna sintetis. Hasil yang di peroleh setelah dilakukan pengujian jajanan sekolah dengan metode uji cepat sebanyak 70 % pangan jajan anak sekolah di Nur-Fadilah mengandung zat aditif yang berbahaya. Kata kunci: Rhodamin_B