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All Journal Jurnal Informatika dan Teknik Elektro Terapan JIEET (Journal of Information Engineering and Educational Technology) JOURNAL OF APPLIED INFORMATICS AND COMPUTING METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi Jurnal Informasi dan Teknologi Jurnal Sistem Komputer dan Informatika (JSON) Jurnal Computer Science and Information Technology (CoSciTech) International Journal of Engineering, Science and Information Technology Jurnal Informatika dan Teknologi Komputer ( J-ICOM) Jurnal Minfo Polgan (JMP) Sisfo: Jurnal Ilmiah Sistem Informasi Jurnal Teknologi Terapan and Sains 4.0 Jurnal Informatika Polinema (JIP) Jurnal Malikussaleh Mengabdi Journal of Advanced Computer Knowledge and Algorithms Gameology and Multimedia Expert
Cut Agusniar
Universitas Malikussaleh
Religion Humanities Astronomy Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Social Sciences Transportation Other

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Naive Bayes Classification Model Analysis of Livable Housing Model Based on Physical Characteristics Burhanuddin Burhanuddin; Emi Maulani; Syarifah Asria Nanda; Cut Agusniar; Fadhliani Fadhliani
Sisfo: Jurnal Ilmiah Sistem Informasi Vol. 10 No. 1 (2026): Sisfo: Jurnal Ilmiah Sistem Informasi, Mei 2026
Publisher : Universitas Malikussaleh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29103/sisfo.v10i1.26974

Abstract

Analysis of Naive Bayes Classification Model of Livable Housing Model Based on Physical Characteristics is one of the crucial aspects in improving the quality of life and welfare of the community. This study aims to examine the application of the Naive Bayes classification method in determining the level of livability based on the physical characteristics of the building. The dataset used is house data that includes several variables, namely roof condition (good, damaged), wall type (wall, semi-permanent, wood), floor condition (ceramic, cement, soil), building area (<36 m², ≥36 m²), ventilation (adequate, inadequate), and sanitation access (adequate, inadequate). The target variable in this study is the housing category, namely livable and uninhabitable. The research stages include data collection, data preprocessing, dividing the dataset into training data and test data, and implementation of the Naive Bayes algorithm. The posterior probability calculation is carried out based on the probability distribution of each variable against the class with a maximum likelihood approach. Model performance evaluation is carried out using a confusion matrix with indicators of accuracy, precision, and recall. The results of the analysis show that the variables of floor condition and sanitation access have the highest probability value against the livable category, thus playing a dominant role in the classification process. Furthermore, these two variables were also shown to have the most significant influence in determining whether housing is habitable or uninhabitable.
Classification of Tourist Attractions in Central Aceh District using the C4.5 Decision Tree Algorithm Amny Yasira; Dahlan Abdullah; Cut Agusniar
Jurnal Informasi dan Teknologi 2025, Vol. 7, No. 4
Publisher : SEULANGA SYSTEM PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60083/jidt.vi0.715

Abstract

Central Aceh Regency is a region with rapidly growing tourism potential, characterized by lakes, mountains, and cultural sites typical of the Gayo people. Although the available tourist attractions are quite diverse, the presentation of unstructured information often makes it difficult for tourists to determine destinations that suit their needs and preferences. To address this problem, this study implemented the C4.5 decision tree algorithm to classify tourist attractions in Central Aceh Regency. The study used five main attributes: type of tourism, accessibility, facilities, ticket prices, and the Number of annual visitors. Data were obtained through field observations, interviews, and online reviews, with a total of 54 tourist attractions being sampled. The analysis process began with data preprocessing, entropy calculations, and information gain and gain ratio to construct a decision tree. The modelling results showed that the accessibility attribute produced the highest gain ratio and became the root node in the tree. Furthermore, the Number of visitors attributed became the dominant factor in the next branch, consistently distinguishing the classes. The classification system resulted in three recommendation categories: Highly Recommended, Recommended, and Not Recommended. Model evaluation using a confusion matrix showed 92% accuracy, 90% precision, and 90% recall, indicating that the C4.5 algorithm is effective at grouping tourist attractions based on their characteristics. This research contributes to a data-driven model that can help tourists obtain more systematic information, while also supporting local governments and tourism stakeholders in developing more targeted destination development strategies.
Pendampingan dan Pemanfaatan Artificial Intelligence Generative untuk Literasi Digital Masyarakat Desa Ilham Sahputra; Cut Agusniar; Muhammad Ikhwanus; Fadliani; Syibral Malasyi; Muhammad
Jurnal Malikussaleh Mengabdi Vol. 5 No. 1 (2026): Jurnal Malikussaleh Mengabdi, Januari 2026
Publisher : LPPM Universitas Malikussaleh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29103/jmm.v5i1.25195

Abstract

Perkembangan pesat teknologi Artificial Intelligence (AI), khususnya sub-bidang AI generatif, telah menciptakan disrupsi signifikan dalam berbagai aspek kehidupan, mulai dari interaksi sosial, proses kreasi, hingga mekanisme akses dan pengelolaan informasi. Namun, diseminasi dan pemanfaatan teknologi transformatif ini belum terdistribusi secara merata, khususnya di area pedesaan yang seringkali dihadapkan pada tantangan kesenjangan infrastruktur dan keterbatasan Literasi Digital. Oleh karena itu, inisiasi program pendampingan dan pelatihan yang berfokus pada pemanfaatan AI generatif. Program ini dirancang sebagai upaya sistematis untuk meningkatkan kompetensi Literasi Digital masyarakat desa agar mampu beradaptasi secara proaktif dengan dinamika perkembangan teknologi terkini. Dengan mengadopsi pendekatan edukatif dan partisipatif, kegiatan ini mengantar masyarakat untuk memahami konsep AI generatif, menguasai metode penggunaannya secara produktif dan bertanggung jawab, serta mengaplikasikannya dalam konteks praktis sehari-hari. Dukungan pendampingan yang berkelanjutan, bertujuan untuk menjamin terbentuknya pemahaman yang aplikatif dan kompetensi yang lestari. Hasil dari pengabdian adanya peningkatan kapabilitas yang signifikan dalam hal pemahaman masyarakat terhadap ekosistem digital, kemampuan berpikir kritis dalam menyaring informasi, serta daya kreativitas dalam memanfaatkan AI generatif untuk kepentingan personal dan komunal. Pengabdian ini menegaskan bahwa adopsi AI generatif dapat berfungsi sebagai katalisator pemberdayaan masyarakat desa menuju terciptanya transformasi digital yang bersifat inklusif, adaptif, dan berkelanjutan. Dengan demikian, kegiatan ini merupakan langkah fundamental dalam memperkuat ekosistem Literasi Digital di tingkat akar rumput, sekaligus memposisikan masyarakat desa untuk siap menghadapi tantangan dan peluang era teknologi cerdas.
Sistem Informasi Surat Perintah Perjalanan Dinas Pada Bagian Umum Sekretariat Daerah Kabupaten Bireuen Cut Agusniar; Leni Aryanti
Sisfo: Jurnal Ilmiah Sistem Informasi Vol. 6 No. 2 (2022): Sisfo: Jurnal Ilmiah Sistem Informasi, Oktober 2022
Publisher : Universitas Malikussaleh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29103/sisfo.v6i2.10138

Abstract

Sistem informasi Surat Perintah Perjalanan Dinas (SPPD) adalah sebuah sistem yang dibuat untuk proses surat menyurat mengenai perintah perjalanan dinas (SPPD), Surat ini dibutuhkan sebagai bukti seorang pegawai dalam melaksanakan tugas. Proses Pengelolaan SPPD di bagian umum sekretariat daerah kabupaten bireuen masih secara manual dan hanya dikerjakan melalui bantuan aplikasi Microsoft office, sehingga dalam menghasilkan seluruh laporan dirasakan masih belum akurat dan masih membutuhkan waktu yang lama. Untuk melengkapi data pelaporan pada penelitian ini, maka dilakukan observasi dan analisa kebutuhan sistem di bagian umum sekretariat daerah kabupaten bireuen, selain itu dilakukan studi pustaka untuk memperoleh data data yang relavan. Perancangan website ini merupakan salah satu alternative yang efektif untuk pengelolaan laporan perjalanan dinas pada bagian umum sekretariat daerah kabupaten bireuen dan setelah itu diharapkan mampu menghasilkan laporan perjalanan dinas dengan cepat dan akurat. hasil dari penelitian ini adanya sistem informasi surat perintah perjalanan dinas ini, staff akan lebih mudah dan efesinsi dalam pengelolaan Surat Perintah Perjalanan Dinas (SPPD).
Sistem Pendataan Inventaris Barang Pada Program Studi Teknik Informatika Universitas Malikussaleh Sujacka Retno; Cut Agusniar; Ilmi Suciani Sinambela
Sisfo: Jurnal Ilmiah Sistem Informasi Vol. 7 No. 2 (2023): Sisfo: Jurnal Ilmiah Sistem Informasi, Oktober 2023
Publisher : Universitas Malikussaleh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29103/sisfo.v7i2.13944

Abstract

Sistem pendataan inventaris barang adalah sebuah alat bantu untuk mencatat dan mendata seluruh barang-barang dengan cara yang terstruktur. Sistem ini dibangun untuk mengatasi permasalahan yang ada di Program Studi Teknik Informatika yang mana dalam mendata inventaris masih bersifat manual, dimana hal ini sangat tidak efesien karena berkas yang disusun cenderung lama dan tidak efektif untuk dikelola secara berkala. Oleh karena itu sangat perlu untuk merubah sistem pendataan inventaris yang manual menjadi sistem berbasis komputer supaya membantu proses penyimpanan data menjadi lebih efektif. Sehingga dapat meningkatkan kualitas sistem pada layanan pengelolaan data inventaris. Hasil penelitian ini dapat mendata inventaris barang di prodi Teknik Informatika. Sistem informasi yang akan dibuat ini menggunakan database secara terpusat dan berbasis desktop.
Penerapan Logika Fuzzy Tsukamoto pada Rancang Bangun Sistem Deteksi Kekeruhan Air Budi Daya Ikan Lele Muhammad Rizki; Eva Darnila; Cut Agusniar
METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi Vol. 9 No. 1 (2025): METHOMIKA: Jurnal Manajemen Informatika & Komputersisasi Akuntansi
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/jmika.Vol9No1.pp112-120

Abstract

This study develops a water quality monitoring system for catfish farming using the Internet of Things (IoT) and Fuzzy Tsukamoto logic. This system consists of a Turbidity Sensor to measure turbidity levels, a DS18B20 sensor to monitor temperature, and a pH meter to measure water acidity levels. Data from the sensors is sent in Realtime to Firebase and displayed in an Android application based on Kodular. The Fuzzy Tsukamoto method is used to analyze data, determine the water quality status whether the water value is Clean, Normal, or Turbid based on predetermined parameters. Based on 14 tests, the system showed an accuracy level of 85.7%, with 12 matching results. In addition, this system is able to provide automatic notifications to users if there are significant changes in water conditions. As a result, this system can help fish farmers monitor water quality efficiently, as well as make decisions about when is the right time to change pond water.
Gold Price Prediction Using Long-Short Term Memory Algorithm Based on Web Application Rodiatul Adawiyah Dalimunthe; Rizal Tjut Adek; Cut Agusniar
International Journal of Engineering, Science and Information Technology Vol 5, No 1 (2025)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v5i1.724

Abstract

Gold is a significant investment asset, particularly in times of economic instability. Various factors, including decisions by financial authorities, inflation, and global economic dynamics, influence the fluctuations in gold prices. Accurately predicting gold prices is valuable for investors when making investment decisions. This study aims to utilize the Long Short-Term Memory (LSTM) algorithm for predicting gold prices and develop a web-based application connected to Yahoo Finance to acquire real-time gold price data. The LSTM algorithm was chosen because it handles time series data with long-term dependencies. LSTM has an architecture that allows the model to retain relevant information over long periods and forget irrelevant data. In this study, the developed LSTM model produced a Mean Absolute Error (MAE) of 19.81, indicating that the average prediction deviates by approximately 19.81 units from the actual value. Furthermore, an average Mean Absolute Percentage Error (MAPE) of 0.83% demonstrates the high prediction accuracy. The results of this study show that LSTM is an effective method for predicting gold prices. The resulting web application allows users to access gold price projections interactively, thereby assisting investors in making more accurate and data-driven decisions with easy access. Additionally, the web application offers customizable features such as adjusting prediction parameters and visualizing results in real time.  These features not only enhance user engagement but also improve decision-making processes. This research provides a practical tool for optimizing investment strategies in a dynamic economic environment by leveraging machine learning and seamless web integration.
The Decision Support System for Feasibility Testing of Healthy Canteens at Universitas Malikussaleh Using the Multi-Attribute Utility Theory Method Nur Saufani Ulfa; Dahlan Abdullah; Cut Agusniar
International Journal of Engineering, Science and Information Technology Vol 5, No 2 (2025)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v5i2.815

Abstract

This research aims to develop a decision support system based on the Multi-Attribute Utility Theory (MAUT) method to evaluate the feasibility of healthy canteens at Malikussaleh University. The system is designed to assess the feasibility of canteens based on six main criteria: Selection of Raw Materials, Storage of Food Ingredients, Food Processing, Food Storage, Food Transportation, and Food Serving. This study evaluated 20 canteens on campus, with feasibility values calculated based on the weights assigned to each Criterion. The results showed that the canteen with the alternative code A11 (Kopita BI) received the highest score of 0.956, followed by A6 (Umi), with a score of 0.798, and A10 (Alisha), with a score of 0.620. Out of the 20 canteens evaluated, only three canteens were categorized as "Feasible," 3 as "Sufficiently Feasible," and the remaining 14 were deemed "Not Feasible." These findings highlight the urgent need to improve the quality of most canteens. The criteria for Selection of Raw Materials and Food Processing had the highest weights, emphasizing the importance of these two aspects in maintaining food quality and health standards. Implementing this system simplifies data management and analysis and provides clear recommendations for canteen managers to improve service and health standards. Thus, this system is expected to promote healthier and higher-quality campus canteens. This research enhances canteen service quality in university environments and can serve as a reference model for other educational institutions in evaluating and improving their canteen facilities.
Performance Analysis of SVM and Linear Regression for Predicting Tourist Visits in North Sumatera Andriyan Ginting; Nurdin Nurdin; Cut Agusniar
International Journal of Engineering, Science and Information Technology Vol 5, No 1 (2025)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v5i1.667

Abstract

Indonesia, an archipelago rich in cultural diversity, historical heritage, and stunning natural scenery, offers an extraordinary travel experience to visitors who make this country their vacation destination. Tourism in Indonesia plays an essential role in the domestic economy, contributing to Gross Domestic Product. With its abundant natural and cultural resources, North Sumatra has long been recognized as an attractive destination for foreign tourists. However, the tourism sector faces significant challenges related to fluctuations in the number of visits, mainly due to the impact of the COVID-19 pandemic, which has disrupted global travel patterns and caused considerable uncertainty in tourism forecasting. Therefore, predicting the number of tourist visits becomes crucial for effectively planning and managing tourist destinations. This research aims to compare the performance of two forecasting algorithms, SVM and linear regression, in predicting foreign tourist visits in North Sumatra using historical data from 2019 to 2023. The dataset was subjected to a preprocessing phase to ensure data cleanliness and consistency, focusing on key variables such as seasonal trends, external factors, and market dynamics. Both models were evaluated based on two commonly used accuracy metrics, MAPE and RMSE, to assess how well the models could predict actual tourist arrivals. The results of the study indicate that Linear Regression outperforms SVM in terms of prediction accuracy, with a MAPE of 42.40% and an RMSE of 6735.6, compared to SVM with a MAPE of 46.65% and an RMSE of 8020.42. These findings provide valuable insights for local government authorities and tourism industry stakeholders to enhance destination planning, resource allocation, and strategies to attract more foreign tourists in the post-pandemic era.
Co-Authors Alaiya, Azna Amny Yasira Andriyan Ginting Asran Asran b, bustami Burhanuddin Burhanuddin Cesilia, Yolinda Cut Ita Erliana Dahlan Abdullah Della Adelia, Della Emi Maulani Eva Darnila Ezwarsyah Ezwarsyah Fadhliani, Fadhliani Fadliani Fazira, Ira Fidyatun Nisa Fitri, Anisa Amelia Gemasih, Husna Herfia Rhomadhona ilham - sahputra Ilmi Suciani Sinambela Khaira, Raziatul laili wahyunita, laili Leni Aryanti Maryana Mochamad Ari Saptari Muhammad Muhammad Ikhwanus Muhammad Muhammad Muhammad Rizki Muhammad Rizki Mulya Ulfa, Septia Munauwarah, Munauwarah Munirul Ula Muslimah Siregar, Khanifa Mutammimul Ula Muthmainnah Muthmainnah Nisa Ul Fadila Nur Saufani Ulfa Nurdin Nurdin Qasos, Lailil Rahma Fitria, Rahma Ramadan, Rifki Rasmiati Rasyid Rini Meiyanti Rizal S.Si., M.IT, Rizal Rodiatul Adawiyah Dalimunthe Safwandi Safwandi Sahputra, Ilham Sujacka Retno Sukiman, T. Sukma Achriadi Suryati Suryati Syarifah Zahra Syibral Malasyi Syibral Malasyi Syukriah Syukriah, Syukriah Veri Ilhadi Yurni, Irma Zubaedah, Reza Zuraida