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All Journal Sinkron : Jurnal dan Penelitian Teknik Informatika Jurnal Teknik Informatika UNIKA Santo Thomas Jurnal Mantik Informatika Jurnal Tekinkom (Teknik Informasi dan Komputer) Journal of Computer Networks, Architecture and High Performance Computing International Journal of Business, Technology, and Organizational Behavior (IJBTOB) Majalah Ilmiah UPI YPTK Jurnal Teknik Informatika Unika Santo Thomas (JTIUST) Journal of Computer Science and Information Systems (JCoInS) IKA BINA EN PABOLO : PENGABDIAN KEPADA MASYARAKAT Journal of Student Development Information System (JoSDIS) Jurnal Pendidikan Indonesia (Japendi)
Syaiful Zuhri Harahap
Universitas Labuhanbatu
Aerospace Engineering Humanities Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Public Health Social Sciences Other

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Rancang Bangun Sistem Informasi Anime Premium dan Non Premium Berbasis Web Dengan Menggunakan Metode Waterfall Pasaribu, Nova Tresia; Masrizal, Masrizal; Harahap, Syaiful Zuhri
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.v12i1.5494

Abstract

Anime is a form of Japanese animation that can be created in the traditional way using hand drawing or using computer technology. Anime was introduced in Indonesia in the 1970s, but its popularity only increased in the 1990s after the airing of Doraemon on television stations. With the advancement of Information Technology, the spread of Anime is expanding. The availability of the internet allows viewers to enjoy Anime in streaming, so Anime can be accessed by anyone, anytime, and anywhere according to the wishes of the audience. Currently, Anime has experienced significant progress when compared to the past. Therefore, a number of people consider it more artistic in nature compared to Anime in the previous period. It should be noted that the images in Anime have become more proportional, colors are better, and the presence of HD (High Definition) technology improves the quality of the video, making it more interesting and understandable. Along with the spread of Anime through online platforms, audience interest in exploring various Anime has also increased, so a website-based information system is needed. Therefore, it is necessary to design and build an information system that is able to provide comprehensive access to various types of Anime, both Premium and non-Premium, in an integrated manner. An appropriate method of designing and building software is needed to ensure that this information system can meet the needs of users effectively. One method that can be used is the Waterfall method.
Analisis Perbandingan Algoritma C4.5 Dan Naive Bayes Dalam Menilai Kelayakan Bantuan Program Keluarga Harapan Hasibuan, Taufik Molid Hidayat; Harahap, Syaiful Zuhri; Ah, Rahma Muti
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.v12i3.6154

Abstract

Social assistance is a form of government intervention that aims to help people who are in less fortunate economic conditions. This form of assistance can be in the form of cash assistance, food assistance, or health service assistance. Social assistance programs are often aimed at reducing poverty, addressing hunger, and improving the overall well-being of society. Program Keluarga Harapan (PKH) is a form of conditional social assistance launched by the government of Indonesia to help poor and vulnerable families. The Program aims to improve the quality of life of poor families through the provision of cash assistance accompanied by obligations for recipients to meet certain requirements, such as ensuring their children attend school and regular health checks at health facilities. With the PKH, it is expected to improve the access of poor families to education and health services, which in turn will improve the quality of Indonesian human resources. Thus, the author can evaluate the advantages and disadvantages of each method in the context of the data used. In addition, this comparative analysis also aims to provide more informative recommendations for policy makers. If one of the methods proves to be superior, then it can be adopted to improve the selection process for CCT recipients in the future. However, if both methods have balanced performance, a combination or integration of the two can be the optimal solution. By comparing the performance of Naive Bayes and the C4.5 algorithm, the study not only focused on identifying the right recipients, but also provided valuable insights in choosing the most effective analytical tool for the purpose.
Penerapan Machine Learning Algoritma Regresi Linear Untuk Memprediksi Saham Bank BNI Andini, Novira Dwi; Harahap, Syaiful Zuhri; Nasution, Marnis
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.v12i2.5649

Abstract

Indonesia has been growing rapidly, one of which can be seen from the economy and technology in Indonesia, at this time the community is almost entirely using machine power technology as a helper of daily life, and the community has also processed a lot of its finances by way of stock investment, with stock investment, the community believes that stocks are invested safer and more profitable. Shares are securities that show proof of ownership or capital market participation of investors in a company (BNI) and shares have a value that is up and down (volatile). Stocks are very important in a company and stocks are a trigger for rising profits in the company.  The rise and fall of stock prices in Indonesia has an adverse effect on companies, especially PT Bank Negara Indonesia (Persero), Tbk. the cause of the rise and fall in stock prices is usually caused by several things, namely the condition and performance of the company, risk, dividends, interest rates, economic conditions, government policies, government issues or other issues, the rate of inflation, supply and demand. Machine learning tools used in predicting stocks, using machine learning, 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.      Linear regression algorithm is one of the methods used to predict stock data in Bank Negara Indonesia. Linear regression algorithm tries to model the relationship between two variables by matching the linear equation of the stock data to be studied. One variable is considered the explanatory variable and the other variable is called the dependent variable. Prediction a process for systematically estimating BNI stock data that will appear in the future using data obtained from the past. Thus the company can easily find out the stock data in the future.
Simulasi Kinerja Karyawan di Kantor Pertanahan Labuhanbatu Menggunakan Algoritma C4.5 Nasution, Khodijah; Masrizal, Masrizal; Harahap, Syaiful Zuhri
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.v12i3.6160

Abstract

Employee performance analysis using the C4.5 algorithm in data mining aims to identify and classify employees based on their performance. The analysis process includes several stages, namely data analysis, preprocessing, model design in data mining, and method evaluation. From 47 sample data analyzed, the results show that 40 employees have good characters, while 7 employees have bad characters. Good employee characters are characterized by punctuality and high discipline in carrying out their duties. Conversely, bad employee characters are characterized by unpunctuality and low discipline, which have a negative impact on productivity and efficiency in the workplace. The results of this classification help identify areas that require more attention and intervention to improve overall employee performance. Model evaluation is carried out using two widgets, namely Test and Score and Confusion Matrix. The evaluation results of these two widgets show perfect accuracy of 100%. Meanwhile, the Confusion Matrix widget shows that all predictions are in accordance with the actual data without any errors in classification. These results confirm that the C4.5 algorithm is very effective and accurate in classifying employee performance. The perfection of the evaluation results shows that the C4.5 algorithm is very suitable for use as a classification model in employee performance analysis. The 100% accuracy of both widgets indicates that this algorithm is not only able to predict correctly but also consistently in various evaluation tools.
Application of Apriori and Fp-Growth Methods in Analyzing Book Lending Patterns Penerapan Metode Apriori dan Fp-Growth dalam Analisis Pola Peminjaman Buku Faradilah, Rahma; Harahap, Syaiful Zuhri; Irmayanti, 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.v12i3.6155

Abstract

Clustering of book borrowing patterns in the University of Labuhanbatu library aims to identify and understand student preferences and habits in borrowing books. With this analysis, the library can be more effective in managing book collections, ensuring the availability of frequently borrowed books, and improving the quality of service according to student needs. Using clustering techniques also helps in designing a more targeted book procurement strategy, so that existing resources can be optimally utilized to support the teaching and learning process. In this study, the methods used are Kf-Growth and Apriori to identify book borrowing patterns. Kf-Growth is used to find frequent itemsets or collections of books that are often borrowed together, while Apriori is used to generate association rules that reveal the relationships between borrowed books. Both of these methods allow for a more in-depth and comprehensive analysis of book borrowing patterns in the library, with the ability to handle large amounts of data and identify significant relationships between items. This process involves several stages, including data preprocessing, algorithm application, and evaluation of the results to ensure the validity and accuracy of the resulting clustering. The results of the clustering analysis show a very good confidence value, with many male and female students borrowing the book "Pengantar Akuntansi" consistently. This borrowing pattern shows that books related to economics and accounting have a high level of demand. The Kf-Growth and Apriori methods have proven to be very effective in clustering, providing accurate and reliable results. With these results, the Labuhanbatu University library can take more informative and strategic steps in managing book collections, ensuring that frequently borrowed books are always available, and improving the borrowing experience for students.
Rancang Bangun Sistem Antrian Online Menggunakan Metode Single Channel-Multi Phase Studi Pada Dinas Sosial Kabupaten Labuhanbatu Sirait, Roby Gusmawan; Harahap, Syaiful Zuhri; Ritonga, Irmayanti
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.v12i1.5473

Abstract

Labuhanbatu District Social Office is an institution implementing social affairs of government under and responsible to the head of the region (Regent).  In this case the Labuhanbatu District Social Service Office applies many arrangements in between what happens. The way that is done is very manual, namely by setting the queue NumberOne by one. With a very small limit on the number of passengers, this causes queues to accumulate, coupled with situations that affect his daily life. In the process of service that is done, there is a way of service that must be done because a lot of attention should be paid to the way the service is done now is not very effective. So it is necessary to create a simulation of community service system that can identify community services in the Office of Social Services Labuhanbatu District. During the service takes place the time needed between one another in getting the service to be efficient first came to be served in the service. The reason for the research using this topic is that research on the topic is still not done in the Labuhanbatu District Social Service with Inter-system using Single Channel-Multi Phase method.  So that the Social Service of Labuhanbatu Regency can serve the community to the maximum and the community feels comfortable and fair.
Penerapan Data Mining Untuk Evaluasi Data Penjualan Menggunakan Metode Clustering Dan Agoritma Hirarki Divisive Studi Kasus Toko Sembako Pujo Febriyanti, Ade Eka; Harahap, Syaiful Zuhri; Masrizal, Masrizal
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.v12i3.6161

Abstract

The larger a company, the longer the company stands, the more companies have branches, of course, the greater the data owned. These data can be consumer data, purchase data, sales data, payroll data, and many other data. All data will usually be stored in a database. But many companies, even the Information Technology (IT) division, do not realize how valuable the pile of old data generated by the company in transactions and activities. Data mining is the study of methods for generating knowledge or finding patterns for processing data. So it's not just information, it's knowledge. Data Mining has several methods including clustering. Clustering is a well-known and widely used method in data mining. The main purpose of this clustering method is to Group a number of data/objects into clusters (groups) so that the cluster will contain the same data as each group. In this study, Divisive hierarchy algorithm is used to form clusters. From the pattern obtained is expected to provide knowledge for the company Media World Pekanbaru as a supporting tool to take policy.
Memprediksi Data Saham Bank Mandiri Menggunakan Metode Algoritma Regresi Linear Dengan Bantuan Rapid Miner Sari, Laila; Harahap, Syaiful Zuhri; Ritonga, Irmayanti
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.v12i2.5645

Abstract

Indonesia has been growing rapidly, one of which can be seen from the economy and technology in Indonesia, at this time the community is almost entirely using machine power technology as a helper of daily life, and the community has also processed a lot of its finances by way of stock investment, with stock investment, the community believes that stocks are invested safer and more profitable. A stock can be defined as a mark of participation or ownership of an individual investor or institutional investor or trader on their investment or a certain amount of funds invested in a company. Linear regression algorithm is one of the methods used to predict stock data in Bank Mandiri. Linear regression algorithm tries to model the relationship between two variables by matching the linear equation of the stock data to be studied. One variable is considered the explanatory variable and the other variable is called the dependent variable. Prediction a process for systematically estimating Bank Mandiri stock data that will appear in the future using data obtained from the past. Thus the company can easily find out the stock data in the future.
Analisis Minat Masyarakat Menggunakan Media Sosial Menggunakan Algoritma C4.5 dan Metode Naïve Bayes Panjaitan, Nia Putri; Harahap, Syaiful Zuhri; Ah, Rahma Muti
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.v12i3.6156

Abstract

The analysis of public interest using social media in data mining aims to understand user preferences and interests in various topics or products. By analyzing data from social media platforms, such as posts, comments, and interactions, researchers can identify significant interest patterns and trends, which can be used for more effective marketing strategies or product development that suits the public's desires. Common methods used in this analysis are the C4.5 and Naive Bayes algorithms. The C4.5 algorithm builds a decision tree that makes it easy to visualize and interpret the main factors that influence public interest. Meanwhile, Naive Bayes, with its probabilistic approach, classifies data based on existing features, providing fast and accurate predictions. Both methods are applied to process data from social media and produce in-depth insights into user preferences. The results of the analysis show that the prediction and classification of public interest have good accuracy, with the comparison result values showing very satisfactory performance. Both are able to identify and classify interests accurately, utilizing the advantages of each method to provide a better understanding of what is interesting to the public on social media.
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.
Co-Authors Ah, Rahma Muti Aini, Putri Aisyah Hayati Ali Akbar Ritonga Amin, Mhd. Andini, Novira Dwi Andriani, Nur Putri ANTIKA, DEWI Aprilianto, Muhammad Ardiansyah, Rizaldi Bangun, Budianto Cahya, Susilo Tiadi Christoval, Peter Dalimunthe, Annisa Putri Faradilah, Rahma Fatma, Nurul Febriyanti, Ade Eka Hanif, Khairil Hansyah, Praida Harahap, Vivi Nadenia Hasibuan, Mila Nirmala Sari Hasibuan, Muhammad Adlin Hasibuan, Taufik Molid Hidayat Hermika, Eva Ibnu Rasyid Munthe Irmayani, Deci Irmayanti Irmayanti Irmayanti, Irmayanti Irmayati, Irmayati Iwan Purnama Iwan Purnama JP, Gafar Ilyaz Juledi, Angga Putra Juwita Juwita, Juwita Laila Sari Lestari, Putri Anggraini Lianah Lianah, Lianah Listia, Bella Ayu Lubis, Nadira Jannah Adeni M, Nelvi Nurrizqi Marnis Nasution Masrizal Megawati Pasaribu Meidy Putra Panusunan Siregar Melisa Melisa Melyani, Sri Mira Handayani Siregar Mth, Sri Rezky Aprilawati Br Muhammad Halmi Dar Munthe, Ibnu Rasyid Mushtafa Haris Munandar Muti’ah, Rahma Naibaho, Restu Fauzy Nasution, Fahri Emil Afandi Nasution, Fitri Aini Nasution, Intan Baiduri Nasution, Khodijah Nasution, Marnis Novita, Rini Pane, Dinda Nurinayah Panjaitan, Nia Putri Pasaribu, Nova Tresia Patriya, Angga Prayoga Pransiska, Apprillia Yudha Priyanti Priyanti Purba, Mhd. Rafly Putra, Fasdiansyah Putri Lestari, Putri Rafika, Mulya Rahma Muti’ah Ramadan, Ahmad Ramadhani Ramadhani Rambe, Aida Zahrah Hasanati Br Rambe, Nurhayati Rambey, Khiarul Akhyar Ritonga, Akbar Pramuja Ritonga, Ali Akbar Ritonga, Irmayanti SANDI ARDIANSYAH Sari, Kurnia Tika Sigit Prasetyo Nugroho Sihotang, Diko Pradana Sirait, Roby Gusmawan Siregar, Ade Elvi Rizki Siregar, Siti Kholijah Siregar, Siti Wahdina Sitepu, Melda Betaria Sitompul, Muhammad Sofyan Surbakti, M. Aufa Nayaka Fathan Suryadi, Sudi Suryadi, Sudi Syavitri, Tiara Wardani, Syafira Eka Wijaya, Alief Achmad Yeni Syahfutri S Yenni Syahfutri Sipahutar ZURAIDAH ZURAIDAH