Article Per Year (5 Year)
p-Index From 2021 - 2026
10.281
P-Index
This Author published in this journals
All Journal Teknika Lisanuna: Jurnal Ilmu Bahasa Arab dan Pembelajarannya Jurnal Edukasi dan Penelitian Informatika (JEPIN) 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 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
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

Published : 85 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 85 Documents
Search

 3   4   5   6   7 
Implementation of the Profile Matching Algorithm to Identify Outstanding Students at Pesantren Modern Misbahul Ulum Luthfiah, Moulana; Bustami, Bustami; Fajriana, Fajriana
Journal of Advanced Computer Knowledge and Algorithms Vol 1, No 1 (2024): Journal of Advanced Computer Knowledge and Algorithms - January 2024
Publisher : Department of Informatics, Universitas Malikussaleh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29103/jacka.v1i1.14533

Abstract

This research aims to design a decision support system to identify outstanding students at the Misbahul Ulum Modern Islamic Boarding School. Although determining outstanding students is done by taking the average score from all aspects of the criteria, the evaluation process which is still carried out manually takes quite a long time. Therefore, a computerized decision support system is needed to help make decisions more efficiently and accurately. This system was developed using the PHP programming language. The aim of this research is to overcome obstacles in recognizing outstanding students at the Misbahul Ulum Modern Islamic Boarding School by applying the Profile Matching Algorithm. This method can provide the best data by comparing alternative values and predetermined criteria. This research contributes to the development of educational technology and facilitates the introduction of outstanding students at the Misbahul Ulum Modern Islamic Boarding School. By determining the criteria aspects, determining the weight value of each aspect, finding the GAP value, and carrying out a ranking process, this research produces objective results. Involving 252 students from grades 7-11, this research produced a final grade for each student. The calculation results show that Zikril got the highest score, while Asma Biwi got the lowest score.
Analisa Pola Peminjaman Buku di Perpustakaan Fakultas Teknik Universitas Malikussaleh untuk Menentukan Tata Letak Buku Menggunakan Metode Algoritma Fp-Growth Umaiya, Fazilah; Wahyu Fuadi; Fajriana
Jurnal Elektronika dan Teknologi Informasi Vol 5 No 2 (2024): September 2024
Publisher : LPPM-UNIKI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5201/jet.v5i2.490

Abstract

This study aims to analyze book borrowing patterns in the Faculty of Engineering Library, Malikussaleh University in order to determine the optimal book layout. Book borrowing patterns are analyzed using the FP-growth algorithm method, a data mining technique that is efficient in finding association patterns or relationships between items in large databases. The data used in this study include book borrowing records from January to April 2024. The results of the analysis show that there are several significant borrowing patterns between certain book categories, for example, books on programming are often borrowed together with books on information systems. Based on these findings, book layout recommendations are proposed so that books that are often borrowed together are placed close together, thus facilitating access for users and increasing the efficiency of the library layout. The use of the FP-growth algorithm in this study has proven effective in identifying hidden patterns in book borrowing data. Keywords: Library, Data Mining, FP-growth Algorithm, Web
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

Abstract

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

Abstract

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

Abstract

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

Abstract

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

Abstract

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.
SISTEM PENGUJIAN HAFALAN AL-QURAN SURAH AL-ALA MELALUI SUARA MENGGUNAKAN TRANSFORMASI HAAR WAVELET Izza, Nurul; Zuraida, Zuraida; Fajriana, Fajriana
Jurnal Teknologi Terapan and Sains 4.0 Vol 5 No 3 (2024): Jurnal Teknologi Terapan & Sains
Publisher : Universitas Malikussaleh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29103/tts.v5i3.19681

Abstract

Minat terhadap hafalan Al-Quran saat ini semakin meningkat, dan metode pendekatan dalam menghafal pun mengalami perkembangan pesat. Hal ini ditandai dengan bertambahnya jumlah lembaga tahfidz Al-Quran. Namun, dengan jumlah peserta yang besar dan keterbatasan waktu serta kapasitas pengajar, proses pengujian hafalan sering kali menjadi kurang optimal. Keterbatasan kemampuan pendengaran penguji juga dapat menyebabkan kesalahan dalam menilai akurasi tajwid dan pelafalan hafalan. Masalah ini sering kali membuat proses penilaian hafalan menjadi kurang akurat dan objektif. Untuk mengatasi permasalahan tersebut, diperlukan solusi berbasis teknologi yang dapat mendukung pengujian hafalan secara lebih efisien, akurat, dan objektif. Penelitian ini menggunakan pendekatan Transformasi Haar Wavelet untuk mengembangkan sistem pengujian hafalan surah Al-Ala melalui analisis suara. Sistem ini bertujuan mengevaluasi kesalahan atau kebenaran hafalan dengan membandingkan kemiripan antara suara latih dan suara uji. Pengujian dilakukan dengan menggunakan empat konstanta probabilitas yang berbeda (α = 0,3; 0,4; 0,5; 0,6), serta melibatkan 10 sampel suara latih dan 25 sampel suara uji. Hasil penelitian menunjukkan detection rate yang bervariasi: α = 0,3 menghasilkan 40%, α = 0,4 sebesar 56%, α = 0,5 mencapai 88%, dan α = 0,6 memberikan hasil tertinggi sebesar 96%, dengan total akurasi mencapai 70%. Meskipun sistem ini efektif untuk pengujian hafalan secara real time, kelemahan utama terletak pada sensitivitas terhadap noise, yang membuatnya kurang ideal untuk digunakan di lingkungan yang ramai.Kata Kunci: Transformasi Haar Wavelet, detection rate, real time, hafalan
SISTEM PAKAR DIAGNOSA PENYAKIT PENCERNAAN PADA MANUSIA MENGGUNAKAN METODE CERTAINTY FACTOR DAN PROFILE MATCHING Siregar, M. Ali Akbar; Fadlisyah, Fadlisyah; Fajriana, Fajriana
Jurnal Teknologi Terapan and Sains 4.0 Vol 5 No 3 (2024): Jurnal Teknologi Terapan & Sains
Publisher : Universitas Malikussaleh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29103/tts.v5i3.19851

Abstract

Penyakit pencernaan adalah salah satu masalah kesehatan yang umum dan berbahaya. Untuk mengantisipasi hal tersebut, penelitian ini berfokus pada pengembangan sistem pakar yang dapat mendiagnosa penyakit pencernaan berdasarkan gejala yang diderita oleh pasien. Sistem pakar ini menggunakan metode Certainty Factor dan Profile Matching untuk memprediksi penyakit pencernaan dan menentukan tingkat kepastian diagnosis berdasarkan data gejala yang tersedia. Sistem pakar ini juga dilengkapi dengan fitur untuk mengelola data penyakit dan gejala, sehingga dapat melakukan diagnosa dan pengobatan. Dengan menggunakan metode Certainty Factor dan Profile Matching, sistem pakar ini diharapkan dapat memberikan informasi yang lebih akurat dan tepat waktu kepada user atau pasien tentang penyakit pencernaan. Dengan demikian, sistem pakar dapat menentukan diagnosis yang paling sesuai dengan kondisi gejala yang diderita pasien. Sistem pakar diagnosa penyakit pencernaan pada manusia dalam penelitian ini dibuat berbasis web dan output dari sistem merupakan persentase penyakit. Kata Kunci : Penyakit Pencernaan, Sistem Pakar, Certainty Factor, Profile Matching.
Optimalisasi Lokasi Pembangunan Stasiun Pengisian Kendaraan Listrik Umum (SPKLU) Menggunakan Sistem Informasi Geografis Di Kota Medan Dengan Metode Analisis Buffer Veirrel, Dwi Harsya Ramadhan; Safwandi, Safwandi; Fajriana, Fajriana
TEKNIKA Vol. 19 No. 2 (2025): Teknika Mei 2025
Publisher : Politeknik Negeri Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5281/zenodo.14936546

Abstract

Perubahan iklim global dan kebutuhan yang sangat mendesak untuk mengurangi emisi karbon membuat kendaraan listrik semakin menarik untuk dijadikan sebagai solusi transportasi ramah lingkungan. Namun, salah satu tantangan dalam mendukung penggunaannya ialah kurangnya infrastruktur pengisian daya yang memadai, seperti Stasiun Pengisian Kendaraan Listrik Umum (SPKLU). Penelitian ini bertujuan untuk menentukan lokasi terbaik untuk pembangunan SPKLU di Kota Medan dengan memanfaatkan teknologi Sistem Informasi Geografis (SIG) dan metode analisis buffer. Data geografis dan deimografis Kota Meidan digunakan seibagai dasar analisis, deingan meimpeirtimbangkan faktor-faktor seipeirti keipadatan peinduduk, akseisibilitas, dan keibeiradaan fasilitas umum. Meilalui analisis buffeir, zona strateigis diteintukan beirdasarkan radius peingaruh 100 meiteir, 300 meiteir, dan 500 meiteir dari titik poteinsial. Hasil peineilitian meinunjukkan bahwa peindeikatan ini eifeiktif untuk meineintukan lokasi yang ideial, meimudahkan akseis, dan meindukung eifisieinsi opeirasional. Peineilitian ini beirhasil meingideintifikasi beibeirapa lokasi strateigis untuk peimbangunan SPKLU di Kota Medan, yang diharapkan dapat meningkatkan kenyamanan pengguna kendaraan listrik dan mempercepat pengurangan emisi karbon. Sebagai rekomendasi, pemerintah daerah dan pengembang infrastruktur disarankan untuk memprioritaskan pembangunan SPKLU di zona-zona strategis yang telah ditentukan.
Co-Authors A Halim Ahmad Fahrudin Aklimawati Aklimawati Aklimawati Aklimawati, Aklimawati Alawiyah, Mufidah Alifa, Suci 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 Hayatun Nufus Hayatun Nufus Hendra Sudarso Henni Fitriani Herizal Herizal Hidayat, Amam Taufiq Hidayatsyah Hidayatsyah I Gede Iwan Sudipa Imanda, Riska Iryana Muhammad, Iryana Isfayani, Erna Iwan Adicandra Iwan Pahendra Iwan Pahendra Iwan Pahendra Anto Saputra Izza, Nurul Jannah S, Rauzatul Jimmy H Moedjahedy Jumita Sari 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, 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 Sadewa, Bima Safriana Safriana Safwandi Safwandi Safwandi Safwandi, Safwandi Salama, Umi Samsinar Samsinar Santosa, Tomi Apra Saragih, Novilia Junianti Sinaga, Nurul Afni Sirait, Nur Al Fira Siraj Siraj Siraj Siregar, M. Ali Akbar Sri Setyawati Suryati Suryati Suyatmo, Suyatmo Suzana, Yenny Syahputra, Azhar Syahrina Intan Syamsul Bahri Syarah, Fatmah Syarifah Rita Zahara 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 Zahratul Fitri Zaman, Qamaruz Zara Yunizar Zulfa Zulfa Zulfia , Anni Zuraida Zuraida