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All Journal Sinkron : Jurnal dan Penelitian Teknik Informatika Jurnal Teknik Informatika UNIKA Santo Thomas Building of Informatics, Technology and Science Informatika Jurnal Pengabdian kepada Masyarakat Nusantara International Journal Of Science, Technology & Management (IJSTM) 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 Pengabdian Masyarakat Gemilang (JPMG) Jurnal Pendidikan Indonesia (Japendi) Dike
Nasution, Marnis
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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.
Sistem Informasi Pariwisata Alam di Kabupaten Labuhanbatu Berbasis Web Purba, Cinrewina; Nasution, Marnis; Muti Ah, Rahma
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.v12i2.5650

Abstract

Indonesia is a country rich in natural resources. nature tourism has a unique and interesting natural wealth as the main attraction for people who like to visit nature. Saving the environment and biodiversity becomes very important, and nature tourism can be a means to increase public awareness and involvement in Nature Conservation. Each of these tours has its own beauty and characteristics. Tourism is one of the sectors that has the opportunity to become the largest foreign exchange contributor in Indonesia, tourism growth in indonesia was recorded at 7.2 percent per year, higher than the average world tourism growth of only 4.7 percent. Labuhanbatu Regency is one of the regions of North Sumatra that has a good tourism sector.but in the dissemination of information  about tourism is still a manual, among others, the provision of brochures, posters, pamphlets to tourists who visit. The Office of Youth, Sports, Culture and tourism does have a website about natural tourism in Labuhanbatu but its webiste can not be opened, and the automatic development of natural tourism can not be updated to the website. At the time of the tour, the tourists also must be really tired on the way and want to stay at the tourist attractions. To ensure the presence or absence of lodging in these tourist attractions,it is very necessary for the website to more easily find out information about natural attractions in Labuhanbatu Regency.
Sistem Informasi Pendataan Alat Bantu Bagi Penyandang Disabilitas Pada Dinas Sosial Kabupaten Labuhanbatu Hasibuan, Ardiansyah; Nasution, Marnis; 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.v12i1.5490

Abstract

Introduction the development of technology in recent years is very rapid. The development of technology today is used by many parties in carrying out daily life. The data collection that received a lot of attention was related to the data collection of supplies for people with disabilities at the Labuhanbatu District Social Office. Currently, people with disabilities are getting special attention from various parties, both government and non-governmental organizations. The fulfillment of the rights of persons with disabilities continues to be championed by a number of parties which will then be submitted to the government, in this case the Labuhanbatu District Social Office. Therefore, the Social Service of Labuhanbatu Regency really needs a computerized information system to facilitate the work. Processing large amounts of data is certainly very difficult without a support system in it. This encourages many parties to take advantage of the development of information systems to the fullest, both information that comes from within and information that comes from outside. Based on the observations of the researchers found that employees of the Labuhanbatu District Social Service to collect data on disability aids is still manually by recording and then input into microsoft office either microsoft word or microsoft excel. This makes long work and data accuracy ineffective. Therefore, the researchers felt that a computerized information system is needed that can facilitate and accelerate the work and can make the work of collecting disability aids by employees at the Labuhanbatu District Social Service more effective. Waterfall to implement interface design, user interface design design using a programming language .
Analisa Data Penjualan Pada Apotek Ritonga Farma Menggunakan Data Mining Apriori Lestari, Putri Anggraini; Nasution, Marnis; Harahap, Syaiful Zuhri
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.v12i2.5651

Abstract

A pharmacy is a place or business that is specifically dedicated to providing medicines and other health products to the public. This place is also known as a drugstore or drug store in some countries.  Pharmacies provide medicines both prescribed by doctors and over-the-counter (over-the-counter), to help patients cope with health problems they are experiencing.Some pharmacies also offer additional services such as blood pressure checks, vaccinations, simple health checks, and health counseling to the public.  In applying a priori methods to pharmacy, a deep understanding of data structure and proper product classification is needed to overcome this problem. By knowing the pattern of frequent purchases, pharmacies can place items that are often purchased together close together on shelves or strategic locations. This can increase the convenience of buyers and speed up the purchase process. A priori methods are techniques in data mining that are used to find hidden patterns or associations in large datasets.  A priori methods look for relationships between items in a dataset that often appear together.  The main principle of the a priori method is that if an item-set appears frequently together, then it is likely that the item-set will also appear frequently together in other transactions.
Penerapan Metode Algoritma C4.5 Untuk Memprediksi Loyalitas Karyawan Pada PT.Tolan Tiga Indonesia Perlabian Estate Rambe, Diana Indriani; Nasution, Marnis; Muti Ah, Rahma
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.v12i2.5646

Abstract

The capital market is a place where various financial instruments are sold and bought can be long-term or short-term financial instruments. The Indonesian stock market is regulated by law No. 8 of 1995 capital market. The law clarifies the role of capital markets in the country's economy. The capital market has two functions, namely as a container for corporate financing in collecting funds from investors and as a means of investment. Loyalty is a person's loyalty in serving in a company or institution where there is a dedication and trust given by the company or institution in carrying out tasks in accordance with its expertise. in which there is a sense of love and responsibility to strive to provide the best service and behavior to show good work performance. . Loyalty is needed by companies because if employees do not have loyalty at work, it can harm the company. Thus in order to determine employee loyalty,several assessments are needed such as : employee performance,neatness in work, behavior and frequency of cooperation. Sehinnga from the assessment the company can assess how employee loyalty and if the contract employees include employees who have loyalty to the work it will be adopted as permanent employees at PT. There Are Three Types Of Indonesian Real Estate. The need for information services is very important, in predicting employee loyalty .in predicting employee loyalty can still be done manually but requires a very long processing time can be days.therefore, the author provides convenience with the use of meaching learning method, namely C4. 5 algorithm . C4.5 algorithm can facilitate the company in the process of employee prediction with just a matter of hours. So that it can make it easier for companies to determine employees who have loyalty to PT. There are three types of Indonesian real Estate.
Analisis Data Mining Absensi Siswa SMP Negeri 1 Bilah Barat Dengan Metode Algoritma K-Means Cluestering Sinurat, Shondy Raja Ferdinand; Nasution, Marnis; Ah, Rahma Muti
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.v12i2.5773

Abstract

The presence of students in Junior High School has significant implications in the world of Education. The success of education depends not only on the content of the curriculum and the quality of teaching, but is also strongly linked to the extent to which students are regularly present at school. The problem of student absenteeism in junior high school is an issue that should not be ignored, as it can negatively affect academic achievement, the development of social skills, and the overall educational experience of students. A student's absence from school can be caused by a complex of factors. These factors include personal problems such as lack of motivation, family problems such as domestic conflicts, poor physical or mental health, as well as environmental factors such as school accessibility. A deep understanding of the reasons behind student absenteeism is an important first step to addressing this problem. Student attendance Data that has been accumulated over the past 6 months can be a valuable source of information in analyzing student attendance. However, extracting useful information from large and complex attendance data is a challenging task. This is where Data Mining comes in. Data Mining is an approach that enables the identification of patterns, trends, and valuable information in large and complex data. 
Co-Authors Ah, Rahma Muti Ahmad Habibullah, Imam Akbar Ritonga, Ali Andini, Novira Dwi Bangun, Budianto Cahya, Susilo Tiadi Cahyani, Nilam Christoval, Peter Haris Munandar Hasibuan, Ardiansyah Hasibuan, Mila Nirmala Sari Irmayani, Deci Irmayanti Irmayanti, Irmayanti Juledi, Angga Putra Lestari, Putri Anggraini Muhammad Halmi Dar Munthe, Ibnu Rasyid Musthafha Haris Munandar Muti'ah, Rahma Muti’ah, Rahma Nasution, Fahri Emil Afandi Nilam Sari Nurjannah, Eka Nurpa, Murni Zaliah Petromak Sinaga, Gandhi Naek Pohan, Sentosa Purba, Cinrewina Putri Lestari, Putri Rambe, Diana Indriani Rambe, Inny Rahayu Rasyid Munthe, Ibnu Ray Silaen, Belinda Ritonga, Ali Akbar Ritonga, Irmayanti Rohani Rohani Salsabila, Aulia Santika, Linda Siahaan, Rahma Aulia Sihombing, Volvo Sinurat, Shondy Raja Ferdinand Siregar, Peni Ungkasara Suci Ramadhani, Suci Surasih, Winda Syah, Rahmayuni Syaiful Zuhri Harahap Trisno Trisno Wijaya, Alief Achmad ZURAIDAH ZURAIDAH