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All Journal Informatika Journal of Computer Science and Information Systems (JCoInS) IKA BINA EN PABOLO : PENGABDIAN KEPADA MASYARAKAT Journal of Student Development Informatics Management (JoSDIM)
Irmayanti Irmayanti
Sistem Informasi, Fakultas Sains dan Teknologi, Universitas Labuhanbatu
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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Sistem Informasi Penjualan Produk Pertanian Pada Toko Triputri Aeknabara Berbasis Web Indry Rizza; Zaitun Ritonga; Dedi Naingolan; Irmayanti Irmayanti; Syaiful Zuhri Harahap
Journal of Student Development Informatics Management (JoSDIM) Vol 1, No 1: JoSDIM | Januari 2021
Publisher : Universitas Labuhanbatu

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (754.958 KB) | DOI: 10.36987/josdim.v1i1.2178

Abstract

Website ini nantinya diharapkan dapat mempermudah pencarianData oleh toko Triputri Aeknabara, mempermudah dalam melihat hasil penjualan dan stok, dan mampu mencakup dunia pasar yang sangat luas dari sebelumnya.Sekaligus sebagai salah satu syarat untuk menempuh Ujian Sidang Tugas Akhir Pada Akademi Manajemen Informatika Komputer (AMIK ) Labuhan Batu. Adapun Bahasa Pemograman yang digunakan dalam pembuatan Sistem yang dimaksud adalah Menggunakan PHP dan MySQL.Aplikasi Pembuatan databasenya menggunakan MySQL, Localhost Phpmyadmin. Penyusunan Tugas Akhir ini dimulai dengan Merumuskan masalah, Mengidentifikasi masalah, Penentuan Tujuan dan Manfaat dalam Mengumpulkan data dari instansi, dan menjelaskan bagaimana proses penjualan yang berlangsung,. Setelah semua data yang di butuhkan di dapatkan, maka dilanjutkan ke Proses Analisis Sistem.Hasil dari pembuatan program yakni ditujukan dengan Terselesaikannya Sistem Informasi Penjualan Produk Pertanian Pada Toko Triputri Aeknabara Berbasis Web. Semoga dengan adanya sistem penjualan ini, dapat meningkatkan Kinerja dalam proses penginputan dan pencarian data penjualan serta proses pemasaran dari pada toko Triputri.
Pelatihan Pengetahuan Teknologi Informasi Desa N7 Aek Nabara Budianto Bangun; Mila Nirmala Sari Hasibuan; Irmayanti Irmayanti; Budi Febriani; Fitri Aini Nasution; Ali Akbar Ritonga
JURNAL PKM IKA BINA EN PABOLO Vol 3, No 2: PENGABDIAN KEPADA MASYARAKAT | JULI 2023
Publisher : IKA BINA EN PABOLO : PENGABDIAN KEPADA MASYARAKAT

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36987/ikabinaenpabolo.v3i2.4722

Abstract

Pelatihan pengetahuan teknologi informasi dalam rangka pengabdian di Masyarakat sangat berperan penting dengan adanya pelatihan  di Desa N-7 Aek Nabara yang dilaksanakan pada hari Senin tanggal 02 Desember 2019, dengan jumlah peserta yang mengikuti pelatihan pengetahuan teknologi berupa internet sebanyak 10 orang. Dalam penyampaian materi yang dipaparkan sangat baik. Sebelum melangsungkan kegitan pelatihan pengetahuan teknologi informasi tersebut di adakan tes, ternyata diketahui yang tidak mengetahui memakaipelatihan pengetahuan teknologi informasi Penggunaan internet dengan tujuan pengabdian kepada masyarakat di Desa N-7 Aek Nabara sangatlah direspon positif dan membawa transformasi terhadap warga Desa N-7 Aek Nabara yang mengikuti pelatihan pengetahuan teknologi informasi tentang intenet tersebut dilakukan post-test disaat akhir pemaparan materi oleh tim pengabdian pada warga oleh dosen dan mahasiswa fakultas sains dan teknologi universitas labuhanbatu diketahui sungguh bagus perubahan warga tersebut ditinjau dari hasil adapun kekurangan yang diperoleh dalam pelatihan serta pembelajaran itu disebabkan dengan adanya faktor- faktor lain misalnya tidak ketersedian alat prasarana disaat pelatihan itu, dan kemampuan peserta yang berbeda-beda maka perlu dicoba pelatihan dan pendidikan Penggunaan internet pada warga Desa N-7 Aek Nabara dimasa-masa-masa yang akan datang.
Analisis Tingkat Kepuasan Mahasiswa Pada Aplikasi Sistem Informasi Terpadu (SITU) di Universitas Labuhanbatu Menggunakan Metode Naïve Bayes Dan Decision Tree Rista Andini Ritonga; Syaiful Zuhri Harahap; Irmayanti Irmayanti; Angga Putra Juledi
Journal of Computer Science and Information System(JCoInS) Vol 7, No 3: JCoIns | 2026
Publisher : Universitas Labuhanbatu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36987/jcoins.v7i3.9708

Abstract

The Integrated Information System (SITU) is an application used to support various academic services at Universitas Labuhanbatu. The quality of services provided by this application needs to be evaluated to determine the level of student satisfaction as its users. This study aims to analyze student satisfaction with the use of the Integrated Information System (SITU) using the Naïve Bayes and Decision Tree methods. The research applies the Knowledge Discovery in Databases (KDD) process, which consists of Selection, Preprocessing, Transformation, Data Mining, Evaluation, and Interpretation. The research data were collected through questionnaires distributed to 50 students of the Faculty of Science and Technology at Universitas Labuhanbatu. The research variables include System Ease of Use, System Access Speed, Information Accuracy, User Interface, and System Reliability, while the target variable is the student satisfaction level, classified into Satisfied and Dissatisfied categories. The classification process was carried out using Orange Data Mining software and evaluated using a Confusion Matrix. The interpretation results based on 27 testing data showed that the Decision Tree algorithm classified 19 instances as Satisfied and 8 instances as Dissatisfied, while the Naïve Bayes algorithm classified 18 instances as Satisfied and 9 instances as Dissatisfied. Furthermore, the Confusion Matrix evaluation indicated that the Naïve Bayes method achieved a 96.8% prediction accuracy for the Satisfied category, outperforming the Decision Tree method, which achieved 81.6%. Based on these results, the Naïve Bayes method demonstrated superior classification performance in analyzing student satisfaction with the Integrated Information System (SITU). The findings of this study are expected to serve as a reference for Universitas Labuhanbatu in evaluating and improving the quality of services provided through the Integrated Information System (SITU).
Perancangan Pembelajaran Media Animasi (Studi Kasus SD Negeri 22 Rantau Utara) Dengan Menggunakan Adobe Flash Devi lestari Hutagalung; Masrizal Masrizal; Irmayanti Irmayanti
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.v12i3.6030

Abstract

Dalam era digital seperti sekarang adalah zaman yang maju. Dalam kemajuan tersebut didukung oleh teknologi yang berkembang pesat. Komputer dapat digunakan sebagai sarana pembelajaran yang menarik dan interaktif, sehingga dapat meningkatkan minat dan antusias peserta didik. Media pembelajaran berbasis komputer dapat menyajikan materi pembelajaran secara visual dan audio yang lebih menarik dan mudah dipahami. Selain itu, media pembelajaran berbasis komputer juga dapat memberikan umpan balik secara langsung kepada peserta didik, sehingga dapat membantu siswa untuk memahami materi pembelajaran dengan lebih baik ,  tempat penelitian SDN 22 Rantau Utara merupakan salah satu sekolah Dasar Negeri di daerah Pulo Padang yang beralamat di Pasir Tinggi, kecamatan rantau utara kabupaten labuhanbatu sumatra utara. SDN 22 Rantau Utara. Penelitian ini menggunakan Adobe Flash sebagai aplikasi perancangan animasi pengenalan huruf dan angka.
Application of Apriori and Fp-Growth Methods in Analyzing Book Lending Patterns Penerapan Metode Apriori dan Fp-Growth dalam Analisis Pola Peminjaman Buku Rahma Faradilah; Syaiful Zuhri Harahap; Irmayanti Irmayanti
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.v12i3.6155

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.
Sistem Pengambilan Keputusan Untuk Pengolahan Data Siswa Penerima Bantuan Belajar Komputer Gratis Anggi Sofiani; Marnis Nasution; Irmayanti Irmayanti
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.v12i3.5992

Abstract

Students play an important role in learning computers, especially in the process of education and learning. According to Law No. 14 of 2005 article 51 paragraph 1 item b states that students are entitled to receive awards for their performance during computer Learning . On the other hand, information technology continues to develop rapidly, one of the developments in information technology is the emergence of Decision Support Systems. Decision support system is a system that helps decision makers in making a decision.There are many methods or algorithms that can be used in decision support systems, including Weighted Product (WP), TOPSIS, Simple Addictive Weighting (SAW), Analytical Hierarchy Process (AHP) methods and others. Analytical Hierarchy Process (AHP) method is one method that has been widely used in Decision Support Systems. This method has the ability to measure the degree of consistency of the decisions to be made. One of the consistency calculations performed in the AHP method is the calculation of the consistency ratio, which in this calculation is done using the value of the random index (IR). Over time, many researchers have conducted research on the value of the Analytical Hierarchy Process random index, so there are many new random index values in addition to the AHP random index found by students.
Implementasi Metode Naive Bayes dan Neural Network Untuk Menentukan Minat Masyarakat Pada Handphone Samsung Nelvi Nurrizqi M; Syaiful Zuhri Harahap; Irmayanti Irmayanti
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.v12i3.6163

Abstract

Naive Bayes and Neural Network methods are used in analyzing people's interest in Samsung mobile phones to gain a better understanding of consumer preferences. Naive Bayes is a simple but very effective probability-based classification method. This method generates possible consumer interests by analyzing features such as price, specifications, and brands, and calculating the probability of different categories. Naive Bayes is very useful in situations where data has independent features, and can provide accurate results at high speed. By identifying patterns of people's preferences, this method can help Samsung adjust marketing and product strategies that are more in line with consumer needs. On the other hand, Neural Network offers more complex analytical capabilities by imitating the way the human brain works through a network of neurons. This method is used to process larger and more complex data in understanding consumer interest patterns in Samsung mobile phones. Neural Network can identify deeper relationships between various factors, such as the interaction between camera features and user needs, using deep learning processes. The purpose of using Neural Network is to capture nuances and trends that cannot be identified with simple methods, thereby providing a more comprehensive view of what drives consumer interest. The use of these two methods of analysis in public interest in Samsung mobile phones has provided very satisfactory results. The calculation values obtained from both methods show a high level of accuracy in the classification of consumer interest. The results of this analysis provide valuable insights for Samsung in understanding consumer preferences and needs, as well as helping the company in designing more effective products and marketing strategies. Thus, the combination of the use of Naive Bayes and Neural Networks not only provides stron g results, but also provides a more holistic approach to consumer data analysis.
Analisis Pola Pembelian Melalui Ponsel Menggunakan Algoritma Apriori dan Fp–Growth Pada Millenium Ponsel Nur Putri Andriani; Syaiful Zuhri Harahap; Irmayanti Irmayanti
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.v12i3.6158

Abstract

The purpose of this research is to understand the main factors that influence consumer decisions in purchasing the device. By exploring information about consumer preferences, needs, and behavior, this study seeks to identify purchasing trends and understand how aspects such as mobile phone features, price, and brand influence consumer choices. The main objective of this study is to provide in- depth insights to technology industry players so that they can develop more effective and relevant marketing and product strategies to meet dynamic market needs. To achieve this goal, this study uses the Apriori and FP-Growth methods, which are data mining algorithms that are effective in finding associations and patterns in transaction data. The Apriori method focuses on identifying the frequency of occurrence of itemsets and forming association rules based on support and confidence values, while FP- Growth uses a tree approach to store and extract frequently occurring patterns more efficiently. Both methods allow for in-depth analysis of mobile phone purchase data, so that complex patterns can be revealed more accurately and quickly. The results of this study indicate that there is a very clear mobile phone purchasing pattern among consumers, with confidence values reaching 90% for some association rules. For example, consumers who purchase phones with AMOLED displays tend to also choose large battery capacities from certain brands. These patterns indicate strong and consistent preferences across consumer groups, providing manufacturers with opportunities to target specific market segments with tailored product offerings. These findings not only provide valuable insights into consumer behavior but also help companies optimize their marketing strategies and increase their competitiveness in the technology industry.
Klasifikasi Tingkat Stres Mahasiswa Dalam Penyelesaian Tugas Akhir Menggunakan Naïve Bayes Dan K-Nearest Neighbor Lenni Pefrianti; Ibnu Rasyid Munthe; Irmayanti Irmayanti; Masrizal Masrizal
Journal of Computer Science and Information System(JCoInS) Vol 7, No 1: JCoInS | 2026
Publisher : Universitas Labuhanbatu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36987/jcoins.v7i1.9060

Abstract

This study aims to analyze the stress levels of final-year students and compare the performance of Naïve Bayes and K-Nearest Neighbor (KNN) algorithms in stress classification. Data were collected from 82 respondents through a questionnaire consisting of seven variables (S1–S7) measuring factors contributing to stress, which were classified into low, moderate, and high stress levels. The results show that both algorithms can classify student stress effectively, with Naïve Bayes achieving the highest accuracy (90.15%) compared to KNN (87.72%). Distribution analysis by study program indicates that Agrotechnology has the highest proportion of students with high stress (42.86%), followed by Information Systems (40.63%) and Information Technology (13.64%). This study provides insights for the university to offer targeted support through counseling or stress management workshops.
Rancang Bangun Sistem Informasi Penjualan Sepatu Menggunakan Bahasa Pemograman PHP Dan MySQL Pada Aman Store Rantau Prapat Nia Edi Putri; Syaiful Zuhri Harahap; Irmayanti Irmayanti; Angga Putra Juledi
Journal of Computer Science and Information System(JCoInS) Vol 7, No 1: JCoInS | 2026
Publisher : Universitas Labuhanbatu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36987/jcoins.v7i1.9025

Abstract

The rapid development of information technology has pushed various business sectors, including Aman Store Rantau Prapat, to adapt digital technology to enhance operational efficiency and market reach. Currently, Aman Store still relies on a manual system, which results in inefficiencies in monitoring transactions and stock, as well as a limited market reach. This research aims to design and build a web-based shoe sales information system using PHP and a MySQL database. The system development follows the Waterfall method, which includes stages of requirement analysis, system design, implementation, testing, and maintenance. System modeling is represented using the Unified Modeling Language (UML), including Use Case, Activity, and Sequence Diagrams, to visualize actor-system interactions and business processes. The result of this research is a web-based application that provides digital product catalogs, online ordering and payment features, and automated stock management. Implementation of this system is expected to accelerate the transaction process, reduce human error, and expand market coverage beyond the local area, thereby increasing the store's competitiveness.
Co-Authors Ali Akbar Ritonga Angga Putra Juledi Anggi Sofiani Bangun, Budianto Budi Febriani Dedi Naingolan Devi lestari Hutagalung Fitri Aini Nasution Ibnu Rasyid Munthe Indry Rizza Lenni Pefrianti Marnis Nasution Masrizal Masrizal Mila Nirmala Sari Hasibuan Nelvi Nurrizqi M Nia Edi Putri Nur Putri Andriani Rahma Faradilah Rista Andini Ritonga Syaiful Zuhri Harahap Zaitun Ritonga