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All Journal Sinkron : Jurnal dan Penelitian Teknik Informatika Informatika Jurnal Tekinkom (Teknik Informasi dan Komputer) IKA BINA EN PABOLO : PENGABDIAN KEPADA MASYARAKAT
Munthe, Ibnu Rasyid
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Aerospace Engineering Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Environmental Science Library & Information Science Public Health Other

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Journal : Informatika

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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 (2024): 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 (2024): 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.
Pengimplementasian Tingkat Ketepatan Waktu Kelulusan Siswa (Studi Kasus Di MTS Nur Ibarhimy) Menggunakan Algoritma C4.5 Amansyah, Rizky; Masrizal, Masrizal; Munthe, Ibnu Rasyid
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.v12i2.5767

Abstract

Education has a very important role in shaping the individual and directing the development of society. As an educational institution, MTS Nur Ibrahimy has a responsibility to improve the quality and efficiency in the implementation of Education. MTS Nur Ibrahimy is located in Rantauprapat, Rantau Selatan district, Labuhanbatu Regency. MTs Nur Ibrahimy has been established since 2000 and has produced a number of students who successfully completed their education at this school. Along with technological advances, pattern exploration can be done by using data classification techniques obtained through the data mining process. Data mining is generally done because of the large amount of data, which can be used to generate patterns and useful knowledge in the business operations of a company. One of the methods developed in data mining is a way to dig up existing data to build a model, and then use the model to recognize other data patterns that are not contained in the stored database. In this context, a classification model is created to identify data patterns related to "Passed" or "not passed" status classes, based on pattern Determination results from training data. The Decision Trees Model is an implementation of the classification model in data mining. This Model builds a decision tree from training data consisting of records in a database. The C4.5 algorithm is one of the data classification algorithms that uses decision tree techniques and is able to manage numerical (continuous) and discrete data, and can handle missing attribute values. This algorithm produces rules that are easy to interpret. C4.5 has been tested in various classification cases, including in medical, trade, personnel, and various other fields.
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.
Co-Authors Aditya, Nanda Amansyah, Rizky Aziz, Tengku Irwan Febriyanti, Ade Eka Gaja, Eggi Ok Pernanda Harahap, Tongku Hamonangan Irmayani, Deci Juledi, Angga Putra Muliani, Sonia Sri Nasution, Marnis Rambe, Bhakti Helvi Sihite, Holong Marhula Sihombing, Volvo Simamora, Rikardo Lasroha Sipahutar, Rizka Nurfatni Sitepu, Melda Betaria Syaiful Zuhri Harahap Tomi Hidayat, Tomi Tompul, Fahreza Br