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All Journal Teknika Lisanuna: Jurnal Ilmu Bahasa Arab dan Pembelajarannya Jurnal Edukasi dan Penelitian Informatika (JEPIN) Jurnas Nasional Teknologi dan Sistem Informasi CESS (Journal of Computer Engineering, System and Science) ITEj (Information Technology Engineering Journals) Sistemasi: Jurnal Sistem Informasi Jurnal CoreIT Jurnal Penelitian Pendidikan IPA (JPPIPA) Hasil Pengabdian Kepada Masyarakat BAREKENG: Jurnal Ilmu Matematika dan Terapan Techno Nusa Mandiri : Journal of Computing and Information Technology JOURNAL OF APPLIED INFORMATICS AND COMPUTING SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan Malikussaleh Journal of Mathematics Learning (MJML) KOMIK (Konferensi Nasional Teknologi Informasi dan Komputer) Journal of Humanities and Social Studies JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Jurnal Dedikasi Pendidikan Jurnal Pendidikan dan Konseling Jurnal Penelitian Pembelajaran Matematika Sekolah Mulia International Journal in Science and Technical Jurnal Ilmiah Kanderang Tingang At-Tarbawi : Jurnal Pendidikan, Sosial dan Kebudayaan Community Development Journal: Jurnal Pengabdian Masyarakat Journal of Computer Science, Information Technology and Telecommunication Engineering (JCoSITTE) JINAV: Journal of Information and Visualization International Journal of Engineering, Science and Information Technology jeti Jurnal Saintekom : Sains, Teknologi, Komputer dan Manajemen TRANSFORMASI : JURNAL PENGABDIAN PADA MASYARAKAT International Journal of Humanities Education and Social Sciences TECHSI - Jurnal Teknik Informatika JAMAIKA: Jurnal Abdi Masyarakat Jurnal Pendidikan Matematika Malikussaleh Jurnal Energi Elektrik Jurnal Teknologi Terapan and Sains 4.0 Estungkara: Jurnal Pengabdian Pendidikan Sejarah International Journal of Trends in Mathematics Education Research (IJTMER) Jurnal Pendidikan Sains Indonesia (Indonesian Journal of Science Education) Jurnal Pendidikan Matematika Journal Of Artificial Intelligence And Software Engineering Journal of Advanced Computer Knowledge and Algorithms Jurnal Ecotipe (Electronic, Control, Telecommunication, Information, and Power Engineering) International Journal of Community Service Implementation Jurnal Solusi Masyarakat Dikara Jurnal Elektro dan Teknologi Informasi INOVTEK Polbeng - Seri Informatika Jurnal Komtika (Komputasi dan Informatika) Journal of Industrial Engineering and Management

Fajriana, Fajriana

Universitas Malikussaleh

Author-ID : 784137

Agriculture, Biological Sciences & Forestry Arts Humanities Astronomy Automotive Engineering 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 Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Nursing Physics Public Health Social Sciences Transportation Other

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Design of A Real-Time Object Detection Prototype System with YOLOv3 (You Only Look Once) Chichi Rizka Gunawan; Nurdin Nurdin; Fajriana Fajriana
International Journal of Engineering, Science and Information Technology Vol 2, No 3 (2022)
Publisher : Master Program of Information Technology, Universitas Malikussaleh, Aceh Utara, Indonesia

Object detection is an activity that aims to gain an understanding of the classification, concept estimation, and location of objects in an image. As one of the fundamental computer vision problems, object detection can provide valuable information for the semantic understanding of images and videos and is associated with many applications, including image classification. Object detection has recently become one of the most exciting fields in computer vision. Detection of objects on this system using YOLOv3. The You Only Look Once (YOLO) method is one of the fastest and most accurate methods for object detection and is even capable of exceeding two times the capabilities of other algorithms. You Only Look Once, an object detection method, is very fast because a single neural network predicts bounded box and class probabilities directly from the whole image in an evaluation. In this study, the object under study is an object that is around the researcher (a random thing). System design using Unified Modeling Language (UML) diagrams, including use case diagrams, activity diagrams, and class diagrams. This system will be built using the python language. Python is a high-level programming language that can execute some multi-use instructions directly (interpretively) with the Object Oriented Programming method and also uses dynamic semantics to provide a level of syntax readability. As a high-level programming language, python can be learned easily because it has been equipped with automatic memory management, where the user must run through the Anaconda prompt and then continue using Jupyter Notebook. The purpose of this study was to determine the accuracy and performance of detecting random objects on YOLOv3. The result of object detection will display the name and bounding box with the percentage of accuracy. In this study, the system is also able to recognize objects when they object is stationary or moving.

Acehnese Traditional Clothing Recognition Prototype System Design Based On Augmented Reality Chicha Rizka Gunawan; Nurdin Nurdin; Fajriana Fajriana
International Journal of Engineering, Science and Information Technology Vol 2, No 3 (2022)
Publisher : Master Program of Information Technology, Universitas Malikussaleh, Aceh Utara, Indonesia

Acehnese traditional clothing is one of the cultural heritages in Indonesia. In today's modern era, the problem faced is the lack of media to introduce cultural heritage in Aceh. Therefore, a media was formed that could introduce Aceh's traditional clothing, namely Southeast Aceh. The press utilizes Augmented Reality (AR) technology so that users can add virtual objects to the natural environment that are easy to use. In this study, a system design using Unified Modeling Language (UML) diagrams has been carried out, including use case diagrams, activity diagrams, and sequence diagrams. This system is built using the C++ language using the Unity application and the vuforiaSDK platform. Then the test results were obtained on the Southeast Aceh traditional clothing recognition application. Namely, the minimum distance that can display 3d objects is a distance of 5 cm, and the maximum distance that can be detected is 80 cm. Based on the test results in the distance test table, the best distance obtained, which results in the detection of markers that are still clear and bright, is at a distance between 5 cm to 70 cm. Meanwhile, at a distance of more than 80 cm, the marker cannot detect markers to display 3D objects because the distance between the camera and the marker is too far. Likewise, with the angular slope, the minimum angle of inclination detected is an angle of 0°, while the maximum angle of inclination detected is an angle of 75°. Based on the test results on the angle slope table, the best angle is obtained, which results in detecting markers that are still clear and bright at a distance between 0-60°. After that, testing is also carried out based on the lighting, where if the light is too bright or too dark, the camera cannot detect the marker.

Information and Communication Technology Competencies Clustering For Students For Vocational High School Students Using K-Means Clustering Algorithm Muhammad Faisal; Nurdin Nurdin; Fajriana Fajriana; Zahratul Fitri
International Journal of Engineering, Science and Information Technology Vol 2, No 3 (2022)
Publisher : Master Program of Information Technology, Universitas Malikussaleh, Aceh Utara, Indonesia

The k-Means Clustering algorithm is intended to partition data into one or more groups, where data that has similarities in one group and data has differences in another. Information and Communication Technology (ICT) Competency data clustering in educational units is considered necessary to facilitate educational facilitation based on the differences in student abilities, determine advanced ICT guidance groups and become a reference in determining the place of Industrial Work Practices (Prakerin). This study aims to find out how the K-Means Clustering algorithm can be applied in clustering the ICT competencies of students at the State Vocational High School (SMK) 3 Lhokseumawe. The benefits generated in this study are in the form of visualization of data clustering that can help teachers and school management in formulating ICT policies at SMKN 3 Lhokseumawe. The data used in this study is the Information and Communication Technology (ICT) competency test score data for the 2021/2022 academic year. The data was obtained through a competency test process that refers to the Minister of Education and Culture Regulation Number 45 of 2015 concerning the Role of ICT/KKPI Teachers in the Implementation of the 2013 Curriculum where ICT competence includes the skills to search, store, process, present and disseminate data and information. Data processing in this study uses the K-means Clustering method and the RapidMiner application. Data processing using the RapidMiner application starts with data preparation, determining the number of clusters, and configuring the method. This study uses 3 (three) cluster configurations, namely the Very Competent, Competent, and Less Competent clusters. Testing data processing using the RapidMiner application resulted in 80 (eighty) students in cluster_0 with a Very Competent rating, 64 (sixty-four) students in cluster_1 with a Competent rating, and 10 (ten) students in cluster_2 with a Less Competent rating.

Sentiment Analysis of Free Online Novel Applications Using the Support Vector Machine Method Yulidayanti, Yulidayanti -; Safwandi, Safwandi; Fajriana, Fajriana
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.v5i1.732

Sentiment analysis is a study to analyze opinions and perceptions of various topics, products, or services. With the advancement of technology, people now have easier access to literary works online, including novels. The shift from offline to online reading has resulted in a large volume of review data, necessitating an automated system to classify this data. This research aims to analyze the sentiment of reviews for online novel applications using the Support Vector Machine (SVM) algorithm. The data used in this study was gathered from user reviews of the Wattpad, Noveltoon, and Joylada applications downloaded from the Google Play Store. The results show that the Wattpad application achieved 63% accuracy, 50% precision, 64% recall, and 56% F1-score, with a 41% positive and 59% negative sentiment distribution. The Noveltoon application achieved 70% accuracy, 69% precision, 73% recall, and 71% F1 score, with a 48% positive and 52% negative sentiment distribution. The Joylada application recorded 67% accuracy, 55% precision, 92% recall, and 69% F1-score, with a 57% positive and 43% negative sentiment distribution. The results of this analysis can help understand user preferences towards online novel applications and provide insights into their impact on the application's image and user interactions.

Implementation of Simple Exponential Smoothing and Weighted Moving Average in Predicting Netflix Stock Prices Sadewa, Bima; Safwandi, Safwandi; Fajriana, Fajriana
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.v5i1.708

This study aims to develop a stock price prediction system for Netflix using the Simple Exponential Smoothing and Weighted Moving Average methods and evaluate the accuracy of both methods. The system provides future stock price estimates based on historical data and includes evaluation metrics such as Mean Absolute Error and Mean Absolute Percentage Error. The implementation results show that SES achieved an MAE of 4.40 and a MAPE of 1.08%, while WMA resulted in an MAE of 8.65 and a MAPE of 2.11%. These findings indicate that SES is more effective in predicting stock prices with lower error rates, particularly for stable historical data. In contrast, WMA is more responsive to short-term trends but less accurate overall. Based on the results, SES is recommended as the developed system's primary method for stock price prediction.

Predicting Electricity Consumption in Aceh Province Using the Markov Chain Monte Carlo Method Gavinda, Virza; Nurdin, Nurdin; Fajriana, Fajriana
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.v5i1.678

Electricity is essential to nearly every aspect of modern life, from industrial sectors to household needs. In Aceh Province, the demand for electricity has consistently increased along with economic growth, urbanization, and population expansion. Various studies indicate that rising electricity consumption is closely linked to economic growth and industrialization. This study uses the Markov Chain Monte Carlo (MCMC) method with the Metropolis-Hastings algorithm to predict electricity consumption in Aceh Province. The research addresses the significant increase in electricity consumption driven by economic growth and urbanization in the region. Electricity consumption data from January 2018 to December 2022 was utilized as the basis for modeling. The results indicate a 32.4% increase in electricity consumption over the past five years. The predictive model achieved high accuracy with a Mean Absolute Percentage Error (MAPE) of 2.41%, demonstrating its reliability in forecasting future electricity needs. Projections through 2030 show a continuous increase, reaching 482 GWh by the end of the period. These findings are expected to support decision-making in sustainable energy planning and providing adequate electricity infrastructure in Aceh. This study highlights the effectiveness of the Me-tropolis-Hastings algorithm in handling complex data with high variability, providing valuable insights for long-term energy planning

Identification of Papaya Ripeness Using the Support Vector Machine Algorithm Maito, Rizki Minta; Qamal, Mukti; Fajriana, Fajriana
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.v5i1.710

Papaya is a tropical fruit that is commonly consumed and found in Indonesia. The ripeness level of papaya is typically assessed based on its colour. However, farmers and consumers often make mistakes identifying the fruit's ripeness. This research aims to design an application capable of determining the ripeness level of papaya based on colour images using Red, Green, Blue (RGB) and Hue, Saturation, Value (HSV) features and applying the Support Vector Machine (SVM) algorithm for ripeness classification. The dataset consists of images of California papayas, with 150 samples. The outcome of this study is a digital image application that can classify papaya ripeness into three categories: raw, half-ripe, and fully ripe. The evaluation used 80% of the data for training and 20% for testing. The results show an accuracy of 80%. With this relatively high level of accuracy, it can be concluded that the SVM algorithm is reliable for classifying papaya ripeness levels of Papayas.

Supporting Application Fast Learning of Kitab Kuning for Santri' Ula Using Natural Language Processing Methods Zaman, Qamaruz; Safwandi, Safwandi; Fajriana, Fajriana
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.v5i1.713

Education in Islamic boarding schools is one of Indonesia's traditional forms of education that teaches Islamic religious teachings, including studying the yellow classic books as the primary source of spiritual learning. However, learning the Yellow classic book is often complicated by 'ula students (early level students) because Arabic is without harakat or lines, and the material studied is very complex. To overcome these challenges, this research aims to develop a yellow Islamic classic book learning support application for 'ula students using the Natural Language Processing (NLP) method. This application has an interactive chatbot feature that helps students understand the contents of the yellow book more effectively and enjoyably. The research method includes literature study, data collection, data processing, and system development using the Sparse Categorical Cross Entropy algorithm in Natural Language Processing to improve the accuracy of chatbot responses. This application provides an innovative solution by presenting an interactive learning experience that can be accessed anytime and anywhere, thus facilitating Santri learning outside the boarding school environment. The results show that learning for 'ula students with the Natural Language Processing method is very good and easy to understand. The test shows that the accuracy of the application reaches 100% with a low error value (loss), which is 0%. It can be recognized that the effectiveness of Natural Language Processing in supporting yellow book learning, maintaining the tradition of Islamic education in the digital era, and helping teachers and parents monitor the development of students.

Development of Integrated Audiovisual Digital Handout Through Flipbook Application Based on Realistic Mathematics Education Fajriana, Fajriana; Mahmuzah, Rifaatul; Ningtiyas, Fitri Ayu; Sinaga, Nurul Afni; Aufa, Zurra Yusally; Saragih, Novilia Junianti
International Journal of Engineering, Science and Information Technology Vol 5, No 3 (2025)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v5i3.990

Effective learning media that prioritizes digitalization in the learning process and curriculum development are needed to improve students' numeracy literacy skills. One type of digital learning media is digital handouts, which are expected to provide positive changes in the world of education. Digital learning media that prioritizes audiovisual is expected to provide new learning experiences for students. This study will determine whether students' numeracy literacy skills increase after studying digital audiovisual handouts through the Realistic Mathematics Education-Based Flipbook Application. This research method uses the modified Borg and Gall model with stages of needs analysis, planning, initial product development, initial field trials, revision of test results, field trials of the main product, product revision, and final product and implementation. The research was conducted at SMPN 1, SMPN 2, and SMPN 3 Dewantara. The subjects of this study were students of grade VIII. The object of the research was Integrated Audiovisual Digital Handouts Assisted by Flipbook Application Based on Realistic Mathematics Education. The results of the validity test by material experts and media experts showed that the media that had been developed was feasible to be tested on students. The results of the small group trial stated that the press created was valid in appearance, ease of use, and usefulness so that it could be used in the media effectiveness trial through evaluation.

Application of Data Mining with the Least Square Meth-od to Predict Web-Based Drug Inventory Halim, Abdul; Safwandi, Safwandi; Fajriana, Fajriana
International Journal of Engineering, Science and Information Technology Vol 5, No 3 (2025)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v5i3.897

Drug supplies are an important aspect because of their large value and large quantity and are an important factor in supporting health services in community health centers. Ineffective drug management, especially in terms of needs planning, can lead to excess or shortage of stock. Both conditions have negative impacts, such as budget waste, drug expiration, or even disruption of patient services due to unavailability of drugs. At the Pante Bidari Health Center UPTD, the drug needs planning process is still carried out manually or based on rough estimates without using sophisticated technology. This study aims to design and build a web-based drug inventory prediction system using the Least Square method. The Least Square method was chosen because it is able to carry out the forecasting process quickly and with good results. In this study, the type of data obtained is drug usage data, data is grouped based on each supplier, from the health center information system during a certain period. After going through the pre-processing and calculation stages, the predicted values are calculated and displayed through a web-based system designed to be easy to use by health center officers. The web system developed in this study uses PHP as the programming language and MySQL as the database, implementing the Least Square method effectively. The results of this study are a drug usage prediction application for the future, applying the Least Square method, which displays drug usage data over a certain period. The system will present the data in the form of a table. Based on testing the drug usage data for Acyclovir Cream 5 mg from January 2023 to August 2024, the prediction result for the following month, September 2024, is estimated to be 38.415, which is rounded to 38 units of the drug.

Co-Authors A Halim Ahmad Fahrudin Aklimawati Aklimawati Aklimawati Aklimawati, Aklimawati Alawiyah, Mufidah Alifa, Suci Almira Amir Amalia, Nova Amalia, Wildi Aminuyati Andri Kurniawan Ariani, Dini Aris Munandar Aryandi, Aryandi Aryandi, Aryandi Asrianda Asrianda Asrillah Asrillah Atikah Fitriani Atta Illah Aufa, Zurra Yusally Aulia, Riva Aynun, Nur Ayu Ningtiyas, Fitri Ayu Rahmi Azhari Azhari Azlika, Lulu Baso Intang Sappaile, Baso Intang Bustami Bustami Chicha Rizka Gunawan Dabet, Abubakar Dahlan Abdullah Darmansyah, Arif Deassy Siska Dessy Putri Wahyuningtyas Ermatita - Ermatita Ermatita Ermatita Ermatita Eva Darnila Fachrur Rozi Fadlisyah Fadlisyah Fakhrah Febrianti, Fadila Firman Aziz Fitri Ayu Ningtiyas Fitri Ayu Ningtiyas, Fitri Ayu Fuadi, Wahyu Gavinda, Virza gunawan, chicha rizka Gunawan, Chichi Rizka Halimatus Sakdiah Hamdhana, Defry Hayatun Nufus Hayatun Nufus Hendra Sudarso Henni Fitriani Herizal Herizal Hidayat, Amam Taufiq Hidayatsyah Hidayatsyah I Gede Iwan Sudipa Imanda, Nanda Imanda, Riska Isfayani, Erna Iwan Adicandra Iwan Pahendra Iwan Pahendra Iwan Pahendra Anto Saputra Izza, Nurul Jannah S, Rauzatul Jimmy H Moedjahedy Jumita Sari Khaidar, Al Khairunnisa Khairunnisa Khairunnisa Khairunnisa Laksono Trisnantoro Listiana, Yeni Lolia Lusiana Rahayu Luthfiah, Moulana M Mursalin M.nasir, Safinatun Najar Maha, Dedi Torang P Mahera, Ulfa Maito, Rizki Minta Mardhatillah, Mona Marhami, Marhami Marwan Marwan Maryana Maryana Maryana Maryana, Maryana Maulida, Maulida Miranda, Firdatul Mona Mardhatillah Muhammad Chairil Abnu Muhammad Faisal Muhammad Fikry Muhammad Muhammad Muhammad Sadli Muhammad Sadli Muhammad Sadli, Muhammad Muhammad, Iryana Muhammad, Muhammad Mukti Qamal Mukti Qamal Muliana Muliana, Muliana Muliana, Muliana Muliani, Eva Munawarah Munawarah, Munawarah Munirul Ula Mursalin . Mutammimul Ula Muthmainnah Muthmainnah Muthmainnah Muthmainnah Mutia Fonna Nanda Novita Nasrah, Sayni Nasrah, Sayni NinaUlfauza NinaUlfauza Niswatul Khaira Novia Hasdyna Nur Elisyah Nurahma, Syahfitri Nuraina, Nuraina Nurdin Nurdin Nurdin Nurdin Nurul Afni Sinaga NURUL HAYATI Nurzannah Nurzannah Nurzannah, Nurzannah Nusantara, Badai Charamsar Oktiawati, Unan Yusmaniar Pane, Syamsul Buchori Pasaribu, Jaza Anil Husna Puji Sabrini Qusaiyen, Qusaiyen Rahayu, Lolia Lusiana Rahmawati M Rahmawati M, Rahmawati Rahmia, Rahmia Rasyada, Reza Dian Ratna Unaida, Ratna Retno Ayu Trisnawati Richki Hardi Rifaatul Mahmuzah Riri Syafitri Lubis Rizal Rizal Rizki Akmalia Rizkiana Akmalia Robbi Rahim Rofi’i, Agus Rohantizani Rohantizani Rohantizani, Rohantizani Rozzi Kesuma Dinata Ruth Mayasari Simanjuntak Sadewa, Bima Safriana Safriana Safwandi Safwandi Safwandi Safwandi, Safwandi Salama, Umi Samsinar Samsinar Santosa, Tomi Apra Saragih, Novilia Junianti Sirait, Nur Al Fira Siraj Siraj Siraj Siregar, M. Ali Akbar Sri Setyawati Suryati Suryati Suyatmo, Suyatmo Suzana, Yenny Syahputra, Azhar Syahrina Intan Syahtira, Meisya Syamsul Bahri Syarah, Fatmah Syarifah Rita Zahara Taufiq Taufiq Tjut Adek, Rizal Ulfah, Julia Ulvityatni Umaiya, Fazilah Veirrel, Dwi Harsya Ramadhan Via Yustitia Wahyu Fuadi Wahyu Fuadi Wahyu Fuadi Wulandari Wulandari Wulandari Wulandari Yulia Zahara Yulidayanti, Yulidayanti - Yundari, Yundari Zahedi . Zahratul Fitri Zaman, Qamaruz Zara Yunizar Zulfa Zulfa Zulfia , Anni Zuraida Zuraida

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Journal : International Journal of Engineering, Science and Information Technology