Article Per Year (5 Year)
p-Index From 2020 - 2025
5.154
P-Index
This Author published in this journals
All Journal Sinkron : Jurnal dan Penelitian Teknik Informatika Jurnal Teknik Informatika UNIKA Santo Thomas Informatika Jurnal Sistim Informasi dan Teknologi Jurnal Tekinkom (Teknik Informasi dan Komputer) MEANS (Media Informasi Analisa dan Sistem) Jurnal Sistem Informasi, Teknik Informatika dan Teknologi Pendidikan (JUSTIKPEN) Jurnal Pengabdian Masyarakat : Pemberdayaan, Inovasi dan Perubahan Jurnal Teknik Informatika Unika Santo Thomas (JTIUST) Journal of Computer Science and Information Systems (JCoInS) IKA BINA EN PABOLO : PENGABDIAN KEPADA MASYARAKAT Internet of Things and Artificial Intelligence Journal
Juledi, Angga Putra
Unknown Affiliation
Religion Aerospace Engineering Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mechanical Engineering Public Health Social Sciences Other

Published : 37 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 37 Documents
Search

 1   2   3   4 
Implementation of Data Mining to Determine Sales Patterns Using the Apriori Method Ritonga, Muhammad Zakuan; Juledi, Angga Putra; Mutia, Rahma
Sinkron : jurnal dan penelitian teknik informatika Vol. 8 No. 2 (2024): Article Research Volume 8 Issue 2, April 2024
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v8i2.13621

Abstract

Research on the Implementation of Data Mining to Determine Sales Patterns Using the Apriori Method is an effort to understand and utilize sales data in making more informed and strategic business decisions. The main goal of this research is to extract hidden patterns from large sales data sets, which cannot be discovered by manual analysis alone. This research process is divided into several key stages, namely Data Selection, Preprocessing, Transformation, and Data Mining. The research results show that the Apriori method is effective in finding purchasing patterns. In terms of the frequency of 2 itemsets, the highest support value was found to be 1, which indicates that the combination of the two products is always purchased together in all transactions. For 3 itemsets and 4 itemsets, the high support value of 0.9 also indicates the existence of product combinations that are often purchased together. In terms of confidence, 2 itemsets show the highest value of 1.25, indicating that purchasing one product has a high tendency to be followed by purchasing other products. For 3 itemsets and 4 itemsets, the confidence values show a slightly lower trend but are still significant. Furthermore, lift analysis provides additional insight into the strength of association between itemsets, with 4 itemsets showing the highest lift value of 1.30, indicating the product combination has a very strong association compared to random expectations. This research confirms the potential of the Apriori method in finding valuable sales patterns, which can help companies make strategic decisions for increasing sales and customer satisfaction.
Comparative Analysis of Machine Learning Algorithm Performance in Predicting Stunting in Toddlers Syahfitri, Nur’aini Indah; Juledi, Angga Putra; Muti’ah, Rahma
Sinkron : jurnal dan penelitian teknik informatika Vol. 8 No. 3 (2024): Research Artikel Volume 8 Issue 3, July 2024
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v8i3.13698

Abstract

Stunting is a condition where the growth of children and toddlers is stunted, which causes children to be shorter than they should be. In the long term, stunting can reduce reproductive health, study concentration, and work productivity, thereby causing significant state losses. The prevalence of stunting in Indonesia, which is still above 20 percent, shows that there are still chronic nutritional problems among toddlers. To prevent this from happening, identification as early as possible can be done using machine learning for predictions. The aim of this research is to conduct a comparative analysis of the performance of machine learning algorithms for predicting stunting in toddlers. Random Forest, K-Nearest Neighbors, and Extreme Gradient Boosting are the algorithms that are compared for their performance. The performance of each algorithm is measured using evaluation matrices such as accuracy, precision, recall, and f1-score. The research method starts with data collection, data preprocessing, data splitting, application of machine learning algorithms, evaluation of algorithm performance, and comparison of results. The performance evaluation matrix measurement results show that Random Forest has an accuracy of 99.95%, precision of 99.89%, recall of 99.94%, and f1-score of 99.91%. K-Nearest Neighbors has an accuracy of 99.93%, precision of 99.87%, recall of 99.88%, and f1-score of 99.88%. Meanwhile, Extreme Gradient Boosting has an accuracy of 99.36%, precision of 98.86%, recall of 98.95%, and f1-score of 98.90%. From the results of all performance evaluation matrices, it can be concluded that the random forest algorithm is the best algorithm for predicting stunting in toddlers.
Sales Trend Analysis With Machine Learning Linear Regression Algorithm Method Sipahutar, Alwidahyani; Munthe , Ibnu Rasyid; Juledi, Angga Putra
Sinkron : jurnal dan penelitian teknik informatika Vol. 8 No. 3 (2024): Research Artikel Volume 8 Issue 3, July 2024
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v8i3.13809

Abstract

The development of online business in Indonesia is now very rapid, with the process being done by ordering goods through resellers or distributors using one of the social media. Item purchases are made based on product information, prices, discounts and inventory quantities using a decision model. In the sales process, Toko Serbu Aek Batu usually releases several different items to be offered to the market at different prices, but not all items are in high demand. Multiple linear regression is an analysis that describes the relationship between dependent variables and factors that affect more than one independent variable. The purpose of this study is to analyze sales trends using a linear regression method using rapidminer. The results of this study are prediction calculations using manual calculations with rapidminer the same results, predicting the price desired by buyers using a linear regression algorithm with the original price is not much different and rapidminer is very accurate to be used in predicting sales trends at the price desired by customers, so that sellers can pay more attention to things that are very influential in the sales process.
Analisis Faktor Yang Mempengaruhi Kepuasan Pegawai Dinas Pangan: Pendekatan Menggunakan Algoritma C4.5 Harahap, Tongku Hamonangan; Munthe, Ibnu Rasyid; Juledi, Angga Putra
Jurnal Informatika Vol 12, No 3: INFORMATIKA
Publisher : Fakultas Sains & Teknologi, Universitas Labuhanbatu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36987/informatika.v12i3.6118

Abstract

The level of satisfaction is an important measure in evaluating the extent to which the needs and expectations of a person or group are met by a product, service, or experience. The concept is often used in a business context to measure how well a product or service meets customer expectations. The level of satisfaction can be measured through various methods such as surveys, interviews or analysis of consumer behavior data. The results of this satisfaction level evaluation provide valuable insights for companies in improving the quality of their products or services, as well as maintaining customer loyalty. Therefore, the author will conduct a study on the level of employee satisfaction Department of food using machine learning approach with C4.5 method. This study aims to explore the patterns and factors that significantly affect the level of employee satisfaction in the context of the Department of food. The C4.5 method was chosen because of its ability to handle complex and diverse data, as well as being able to provide insight into the relationship of complex and non-linear variables.
Analisis Data Penjualan Menggunakan Algoritma Apriori pada Analisis Kopi Hidayat, Tomi; Munthe, Ibnu Rasyid; Juledi, Angga Putra
Jurnal Informatika Vol 12, No 3: INFORMATIKA
Publisher : Fakultas Sains & Teknologi, Universitas Labuhanbatu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36987/informatika.v12i3.6064

Abstract

Data Mining is a technique for finding, searching, or extracting new information or knowledge from a very large set of data, by integration or merging with other disciplines such as statistics, artificial intelligence, and machine learning, making Data Mining as one of the tools to analyze data and then produce useful information. Association Rule is a process in Data Mining to determine all associative rules that meet the minimum requirements for support (minsup) and confidence (minconf) in a database. In Association Rule, there are 2 methods that can be used, namely a priori method and FP-Growth method, where FP-Growth method is the development of a priori method where a priori method there are still some shortcomings such as there are many patterns of data combinations that often appear (many frequent patterns), many types of items but low minimum support fulfillment, it takes quite a long time because database scanning is done repeatedly to get the ideal frequent pattern. In this study the method used is a priori algorithm method, a priori algorithm method is one of the alternative ways to find the most frequently appearing data sets (frequent itemset) without using candidate generation that is suitable for analyzing a transaction data. Coffee analysis is a Cafe Shop engaged in the sale of food and beverages that many food and beverage sales transactions. Open on November 7, 2021 coffee analysis penetrates 245 sales transactions and this transaction data continues to grow every day.
Membangun Layanan Telepon Voice Over Internet Protocol Dengan Menggunakan Server Trixbox Di Smk Pemda Rantauprapat Pratama, Zakaria; Juledi, Angga Putra; Muti Ah, Rahma
Jurnal Informatika Vol 11, No 3 (2023): INFORMATIKA
Publisher : Fakultas Sains & Teknologi, Universitas Labuhanbatu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36987/informatika.v11i3.5010

Abstract

SMK Swasta Pemda Rantauprapat is one of the schools in Labuhanbatu Regency which is one of the oldest vocational schools in Labuhanbatu Regency, where communication has been carried out using paid telephones so that it becomes an additional cost that burdens the school's finances. Along with the rapid development of technology, it has resulted in free telephone services, one of which is VoIP (Voice Over Internet Protocol) technology with VoIP technology which can be used as the right solution to solve this problem. In building a VoIP system, a voip server is needed, namely Trixbox. Trixbox is a Voip Server built on the Linux CentosOs operating system which is open source so it can be developed. Communication using VoIP technology only requires a computer/leptop, microphone, speakers, smartphone and a LAN network using both wired and wireless. With VoIP technology in schools, school principals, vice principals, heads of departments and teachers can communicate without incurring telephone costs.
Implementasi Data Mining Menggunakan Metode Algoritma FP-Growth Dan Algoritma Apriori Pada Toko IBR Jaya Untuk Meningkatkan Penjualan Naibaho, Restu Fauzy; Harahap, Syaiful Zuhri; Juledi, Angga Putra
Jurnal Informatika Vol 12, No 3: INFORMATIKA
Publisher : Fakultas Sains & Teknologi, Universitas Labuhanbatu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36987/informatika.v12i3.6128

Abstract

Dian trading business is one of the grocery stores engaged in buying and selling the main household needs of nine basic ingredients which have been doing a lot of grocery sales transactions. This transaction Data continues to grow every day and in the IBR Jaya store sales transaction data is only presented as an archive or report and it is not mentioned what the benefits of these data are. Nah, the problem at the IBR Jaya store is the improvement of improvements due to the shortage of basic food stocks that are often purchased by consumers are not available which results in improvements and usability improvements then the FP-Growth algorithm is used to analyze patterns of improvement and a priori algorithms for comparison through archived transaction data goods that will be purchased later as a reference to increase food stocks so as to increase sales at the IBR Jaya Food Store in the hope that this increase can help this is one of many ways to make money online. Association rules are a process in Data Mining to establish all associative policies that meet the minimum requirements for support (minsup) and trust (minconf) in a database . In association rules, there are 2 methods that can be used, namely a priori method and FP-Growth method. In this study the method used is FP-Growth algorithm and a priori algorithm, FP-Growth algorithm and a priori method is a method to find the most frequently appearing data set (frequent itemset) without using candidate generation that is suitable to analyze a data transaction.
Rancang Bangun Sistem Informasi Persediaan Barang Pecah Belah Berbasis Web (Studi Kasus Toko Podomoro) Dengan Metode Fifo Dan Lifo Patriya, Angga Prayoga; Harahap, Syaiful Zuhri; Juledi, Angga Putra
Jurnal Informatika Vol 12, No 1 (2024): INFORMATIKA
Publisher : Fakultas Sains & Teknologi, Universitas Labuhanbatu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36987/informatika.v12i1.5493

Abstract

Toko Podomoro is a glassware store that requires a fast and accurate data processing information system to facilitate the work. In modern times like today, Podomoro stores still use recording on books that have not been computerized. Purchase of goods and expenditure of goods is still manual by recording the data of incoming goods and goods out of the warehouse, hence the frequent occurrence of errors in the processing of incoming and outgoing goods data. While making a report that will be made is also still using expenditure records manually by writing in the book, not to mention the record of the purchase of lost goods, which is very important because of the evidence of the reports made. Therefore, it is necessary to have a system of goods investment in Podomoro stores to make it easier for store owners to input goods and stock reports, purchase and expenditure reports.
Optimisasi Penilaian Kinerja Karyawan PT. Tolan Tiga Indonesia Estate Perlabian Dengan Algoritma C4.5 Sipahutar, Rizka Nurfatni; Munthe, Ibnu Rasyid; Juledi, Angga Putra
Jurnal Informatika Vol 12, No 2 (2024): INFORMATIKA
Publisher : Fakultas Sains & Teknologi, Universitas Labuhanbatu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36987/informatika.v12i2.5677

Abstract

In the face of fierce competition in the current global era, companies are required to prepare and always adjust their strategies to the changes that occur so that the company remains able to compete and survive. Employees who are in a company are workers which is the most important asset that must be owned and indispensable in the company and of course must be considered by all parties in order to create good performance as well as have goals to be achieved in the assessment of employee performance at PT. There Are Three Types Of Indonesian Real Estate. Employee performance appraisal in the company is seen as the driving force of the company because human resources play an active role in the running of an organization or company and the decision-making process. Machine learning tools used in predicting the assessment, using the C4.5 algorithm, the data obtained is more accurate. Machine learning is an artificial intelligence that can process data that is useful for consideration in making decisions and solving problems. C4.5 algorithm is one of the algorithms in data mining that serves to classify a class. This algorithm is a development of the ID3 algorithm. How the C4.5 algorithm works by forming a decision tree to produce a decision.
Peningkatan Efisiensi dan Penjualan Toko Fashion Outlet Rantauprapat di Jalan Sisingamangaraja Melalui Implementasi E-Commerce PrestaShop Nasution, Intan Baiduri; Harahap, Syaiful Zuhri; Juledi, Angga Putra
Journal of Computer Science and Information System(JCoInS) Vol 5, No 4: JCoInS | 2024
Publisher : Universitas Labuhanbatu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36987/jcoins.v5i4.6805

Abstract

The purpose of this study is to assess the impact of implementing the PrestaShop e-commerce platform on the efficiency and sales of Fashion Outlet Rantauprapat on Sisingamangaraja. Using a case study approach using quantitative and qualitative data, this study analyzes purchase data before to and after PrestaShop implementation, as well as conducts research with store owners. The results of the study show that PrestaShop significantly improves operational efficiency, reduces market volatility, and increases sales. However, challenges such as a lack of technical knowledge and skills must be addressed. This study found that PrestaShop has a large potential to become an effective tool for Fashion Outlet Rantauprapat in terms of increasing sales in the digital era.
Co-Authors Ah, Rahma Muti Alam, Dewi Pathimah Andriyani, Wahyu Fitri Angreani Hulu, Linca Elma Popi Anjar, Agus ANTIKA, DEWI Aris Munandar Aurianda, Rieke Dini Hariyati Adam Harahap, Tongku Hamonangan Harefa, Sinema Harist N, Abdul Hasibuan, Elysa Rohayani Hia, Faomaha Irmayani, Deci Lubis, Rapida Hanim Manullang, Dosma Parningotan Munthe , Ibnu Rasyid Munthe, Ibnu Rasyid Muti'ah, Rahma Mutia, Rahma Muti’ah, Rahma Naibaho, Restu Fauzy Nasution, Fitri Aini Nasution, Intan Baiduri Nasution, Marnis Nazliah, Rahmi Patriya, Angga Prayoga Pransiska, Apprillia Yudha PRATAMA, ZAKARIA Putri, Kirana Dwi Rambe, Aida Zahrah Hasanati Br Rambe, Inny Rahayu Rambey, Khiarul Akhyar Rezeki, Imam Dwi Ritonga, Muhammad Zakuan Rohani Rohani Sarjon Defit Sihombing, Volvo Sipahutar, Alwidahyani Sipahutar, Rizka Nurfatni Subianto, Roby Suryadi, Sudi Syahfitri, Nur’aini Indah Syaiful Zuhri Harahap Syaputra, Panca Tomi Hidayat, Tomi Yuhandri Yuhandri, Yuhandri Yunus, Yuhandri ZURAIDAH ZURAIDAH