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Informatika
Published by Universitas Labuhanbatu
ISSN : 23032863     EISSN : 26151855     DOI : 10.36987
Core Subject : Science, Education, Engineering,
Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Library & Information Science Other
INFORMATIKA : Jurnal Ilmiah Fakultas Sains & Teknologi Universitas Labuhanbatu diterbitkan oleh Universitas Labuhanbatu melalui Lembaga Penelitian dan Pengabdian Masyarakat, dimaksudkan sebagai media pertukaran informasi dan karya ilmiah antara staf pengajar, alumni, mahasiswa dan masyarakat pada umumnya yang terbit tiga kali dalam setahun (Januari-Mei-September), yang mulai awal terbit sejak tahun 2013.
Arjuna Subject : Ilmu Komputer (semua kategori) - Aplikasi Ilmu Komputer
Articles 273 Documents
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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.
Perancangan UI/UX Aplikasi Booking Online Pada Elaine Studio Dengan Metode Design Thinking Kasih, Andaristy Mutiara; Ismail, Ismail
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.v12i3.6014

Abstract

Nail art is currently experiencing a significant increase in popularity, driven by beauty trends and growing consumer preferences. The nail art salon industry is undergoing growth and transformation driven by new trends and technological advancements. This makes it an exciting time for salon owners looking for solutions by adopting technology to help businesses attract more customers and also increase customer satisfaction. The process of booking appointments and providing information on Elaine Studio is still done manually, namely booking through social media such as Instagram, Whatsapp or directly face to face to come to the studio and is also still recorded manually to book an appointment. This study aims to design and develop an effective user interface (UI) and User Experience (UX) for the nail art online booking mobile application using the Design Thinking method. The main focus of the study is to create an intuitive and user-friendly design, which is able to increase ease of Use and user satisfaction. After going through a series of design and testing iterations, the application is tested using the system Usability Scale (SUS) method to evaluate its usability level.
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.
Penerapan Metode KNN untuk Menentukan Minat Calon Mahasiswa Riyanto, Tiara; Yanris, Gomal Juni; Hasibuan, Mila Nirmala Sari
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.v12i3.6153

Abstract

This study focuses on the implementation of data mining to determine the interests of prospective male and female students in the Informatics Management Department using the K-Nearest Neighbors (KNN) method. The analysis process is carried out through the Knowledge Discovery in Databases (KDD) stages, which include data selection, pre-processing, transformation, data mining, and pattern evaluation. The KDD stage ensures that the data used has been prepared and processed properly to produce an accurate and relevant model. The KNN method is used to classify sample data consisting of 82 prospective male and female students. The results of this study indicate that 63 out of 82 prospective students are interested in the Informatics Management Department, while 19 other prospective students are not interested. This classification process shows that the KNN method is able to identify the interests of prospective students with a high level of accuracy, providing useful information for universities in understanding the preferences of their prospective students. Evaluation of the research results using two evaluation tools, namely Test and Score and Confusion Matrix, showed perfect results with an accuracy of 100%. Both of these evaluation tools are consistent in assessing the performance of the KNN model, confirming that this model works very well in classifying prospective student interests. In conclusion, the KNN method is proven to be effective and reliable in determining prospective students' interest in the Informatics Management Department, providing a strong foundation for similar applications in the future.
Analisis Faktor-faktor Yang Mempengaruhi Tingkat Pertumbuhan Ekonomi di Provinsi Banten Setiyawardani, Dinda Rindiantika; Nursabrina, Allya; Ramdhani, Rafli Saputra; Desmawan, Deris
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.v12i2.5736

Abstract

The aim of this research is to evaluate the variables that have an influence on the level of economic growth in Banten province in 2022. Employment level, human development index, unemployment rate, poverty level and level of income inequality are some of the variables studied. Using descriptive methodology, secondary data using the SPSS multiple linear regression application method from BPS Banten province is used to describe economic phenomena realistically. It is hoped that the results of the study will broaden insight into various factors that influence economic growth in Banten province. Findings-according to this research, only the labor force participation rate has a meaningful influence on economic development, while the human resource development index, the level of welfare deprivation, the level of lack of employment opportunities, and the level of income inequality are statistically insignificant. Engagement-This research can provide valuable knowledge about the elements that influence economic growth, which can be used to make decisions in the future.
Application Of Data Mining In Selecting Superior Products Using The K-Means And K-Medoids Algorithm Methods Hermika, Eva; Harahap, Syaiful Zuhri; Ritonga, Irmayanti
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.v12i3.5968

Abstract

As a supermarket, we are committed to always improving everything, including selecting the greatest goods. To evaluate which items are more superior or popular and which are less popular, you will want a sizable amount of information sources. To select products and identify those that belong in the superior product cluster, researchers employed the clustering method. The clustering strategy uses two forms of cluster analysis, k-means and k-medoids, which have related techniques. The research results show that the k-means algorithm's Davies Bouldin value is -0.430, whereas the k-medoids algorithm's Davies Bouldin value is -1.392. This suggests that the Davies Bouldin value of the k-medoids approach is the lowest, showing that the grouping findings of the k-means method are  a better method to apply to the issue of choosing better products.
Sistem Informasi Jual Beli Kelapa Sawit Berbasis Web pada Peron Reskianto Yasdomi, Kiki; Utami, Urfi; Maradona, Hendri; Dona, Dona; Rahayu, Susi
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.v12i3.6117

Abstract

In Surau Gading village, the majority of the population is employed as oil palm farmers. Every two weeks, farmers harvest oil palm fruit. After harvesting the oil palm fruit, the farmers sell it to Peron Resdianto, who is a young entrepreneur in the village of Surau Gading. Almost every day, the platform owner purchases agricultural products made from palm oil. Because a large number of customers sell their agricultural products, palm oil platform owners have to make sales to the factory once every two days. Once the palm oil mill receives the sales proceeds, the platform owner disburses payments to the palm oil farmers who sell their agricultural products. As information technology advances, it has now spread to almost all fields and is developing at a rapid pace. Information technology's application is evolving, as evidenced by the constant advancements in the field. The author wants to design a web-based information system for selling and buying palm oil on the Resdianto platform using the PHP and My SQL programming languages. We designed this system using system modeling tools, personal home page (PHP), MYSQL, HTML, data flow diagrams (DFD), Xampp, flowcharts, and entity relationship diagrams (ERD). Peron Reskianto can improve performance by creating a web-based information system for buying and selling palm oil, which will assist platform owners in collecting data on palm oil purchases and sales. This information system guarantees security and reduces errors.
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.
Analisis Sentimen Ulasan Pengguna Aplikasi pada Google Play Store Menggunakan Algoritma Support Vector Machine Lubis, Sanny Khairani; Dar, Muhammad Halmi; Nasution, Fitri Aini
Jurnal Informatika Vol 11, No 2 (2023): INFORMATIKA
Publisher : Fakultas Sains & Teknologi, Universitas Labuhanbatu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36987/informatika.v11i2.5860

Abstract

One of the most popular e-commerce sites in Indonesia is Shopee. As the largest marketplace application in Indonesia, Shopee provides product and service review features to users on the Google Play Store. The review feature is very helpful to find out whether user reviews are positive or negative. Having user reviews will help Shopee improve its services. To identify a very large number of user reviews, it is not possible to do it manually by reading them one by one. This process will take a very long time and is not effective. Therefore, we need a method that is able to identify reviews from users more effectively and efficiently. This research aims to conduct sentiment analysis of user reviews of the Shopee application on the Google Play Store by applying the Support Vector Machine algorithm. The research stages carried out started with dataset collection, dataset labeling, preprocessing, TF-IDF weighting, classification, and evaluation. From the research results, accuracy was 70.88%, precision was 49.49%, recall was 52.55%, and F1-score was 49.84%. From these results, it can be concluded that the performance of the support vector machine algorithm in classifying the sentiment of user reviews of the Shopee application on the Google Play Store is quite good.
Sistem Informasi E-Booking Berbasis Website pada PT. SKI Land Development Dewi, Komang Ratih Sucitya
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.v12i1.5436

Abstract

PT. SKI Land Development is a consulting service company engaged in property buying and selling consultancy services and has a standardized developer listing to avoid problematic property purchases in the future. The projects of PT. SKI Land Development are spread throughout Bali. the product marketing stage, product information, house booking, and company schedules are still done offline.. The solution provided to PT. SKI Land Development is to create a "Web-Based E-Booking Information System at PT. SKI Land Development" using HTML and PHP programming languages with the waterfall method. On the website, potential buyers can search for housing information, and the booking process can be done online. The admin can do online marketing and provide information to potential buyers through the website. While, the owner can see booking data that can be exported and printed as booking report data.The results of this application development will be tested using the black box testing method to ensure that when potential buyers, admins, and owners are using the website, it runs smoothly and is declared successful.

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