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All Journal Jurnal Teknologi Informasi dan Ilmu Komputer Jurnal Informatika dan Teknik Elektro Terapan Jurnal Ilmiah KOMPUTASI Sinkron : Jurnal dan Penelitian Teknik Informatika JOURNAL OF APPLIED INFORMATICS AND COMPUTING Jurnal Inotera Jurnal Sisfokom (Sistem Informasi dan Komputer) ILKOM Jurnal Ilmiah Jurnal Infomedia MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer IJISTECH (International Journal Of Information System & Technology) JOURNAL OF SCIENCE AND SOCIAL RESEARCH JOURNAL OF INFORMATICS AND COMPUTER SCIENCE Jurnal Sistem Komputer dan Informatika (JSON) Journal of Computer Science, Information Technology and Telecommunication Engineering (JCoSITTE) IJISTECH Rambideun : Jurnal Pengabdian Kepada Masyarakat International Journal of Engineering, Science and Information Technology jeti JURNAL ILMIAH GLOBAL EDUCATION JUSTIN (Jurnal Sistem dan Teknologi Informasi) Jurnal Teknik Informatika dan Elektro (JURTIE) TECHSI - Jurnal Teknik Informatika Sisfo: Jurnal Ilmiah Sistem Informasi Jurnal Teknologi Terapan and Sains 4.0 Jurnal Kemitraan Responsif untuk Aksi Inovatif dan Pengabdian Masyarakat Journal Of Artificial Intelligence And Software Engineering Journal of Advanced Computer Knowledge and Algorithms Applied Engineering, Innovation, and Technology Proceedings of International Conference on Multidisciplinary Engineering (ICOMDEN)
Munirul Ula
Universitas Malikussaleh
Agriculture, Biological Sciences & Forestry 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 Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Public Health Social Sciences Transportation Other

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ANALISIS KINERJA TATA KELOLA TEKNOLOGI INFORMASI MENGGUNAKAN FRAMEWORK COBIT 2019 PADA UNIVERSITAS JABAL GHAFUR Salimuddin, Salimuddin; Ula, Munirul; Nurdin, Nurdin
Jurnal Informatika dan Teknik Elektro Terapan Vol. 13 No. 2 (2025)
Publisher : Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jitet.v13i2.6130

Abstract

This research aims to evaluate Information Technology Governance at Jabal Ghafur University (Unigha) using the COBIT 2019 Framework. The focus of the research includes analysis of Information Technology operational processes, measurement of feasibility with the COBIT 2019 Design Factor Toolkit, and performance evaluation on two main process objectives, namely EDM03 (Ensured Risk Optimization) and MEA03 (Managed Compliance with External Requirements). This research involved respondents selected based on RACI Chart analysis, consisting of the Vice Chancellor I, Head of the General Administration Bureau, Head of the Administration Section, Head of PUKSI, Head of the Information Security Section, and Head of the Quality Assurance Agency (LPM) using a questionnaire. The analysis results show that these two process objectives have an average capability value of 100% at Capability Level 1, but only achieved Largely Achieved at Capability Level 2. The gap analysis shows a gap between the current condition (Level 1) and the desired target (Level 4), with a difference of 3. Based on these findings, it is recommended that Unigha strengthen risk management and compliance with external requirements, through updating internal policies, improving HR training and utilizing technology more effectively. This improvement is expected to increase the level of capability and performance of Information Technology Governance in Unigha.
Unjuk Kerja Algoritma Support Vector Machine (SVM) dan Naïve Bayes Dalam Pengklasifikasian Berita Hoaks Pada Twitter Tentang Aksi Cepat Tanggap (ACT) Hasan Dalimunthe, Amir; Munirul Ula; Rini Meiyanti
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.v5i2.400

Abstract

Twitter merupakan satu dari banyaknya media sosial yang populer di kalangan masyarakat.  Terkadang informasi yang beredar di twitter merupakan berita palsu yang tidak dapat dibuktikan kebenarannya (hoaks). Penelitian ini menggunakan algoritma Naïve Bayes dan Support Vector Machine (SVM) untuk menentukan berita yang beredar di platfrom twitter mengenai Aksi Cepat Tanggap (ACT) termasuk ke dalam berita hoaks atau berita faktual. Proses klasifikasi dimulai dengan pengumpulan data dengan Teknik Scraping dan setelah itu dilakukan pelabelan untuk mengklasifikasi data latih. Data yang telah diberi label kemudian diproses melalui text pre-processing dan dilanjutkan dengan klasifikasi menggunakan metode Naïve Bayes dan Support Vector Machine (SVM). Jumlah data yang digunakan dalam penelitian ini sebanyak 1425 data dan dibagi ke dalam kategori fakta dan kategori hoaks. Pada proses klasifikasi algoritma Naïve Bayes mendapat nilai akurasi 66,76%, presisi 70,13%, dan recall 58,38%. Sedangkan hasil evaluasi klasifikasi Support Vector Machine (SVM) memiliki tingkat akurasi 65,22%, presisi 71,37%, dan recall 50,84%. Sehingga dapat disimpulkan performa algoritma Naïve Bayes memiliki performa yang lebih bagus dari algoritma Support Vector Machine.
Clustering of the Best Senior High Schools in Serdang Bedagai Regency Using the K-Means Method Siagian, Tania Annisa; Nurdin, Nurdin; Ula, Munirul
Jurnal Sistem Komputer dan Informatika (JSON) Vol. 6 No. 4 (2025): Juni 2025
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/json.v6i4.8669

Abstract

This study aims to cluster the best Senior High Schools (SMA) in Serdang Bedagai Regency using the K-Means method. Five evaluation indicators were used in the clustering process: accreditation, school status, number of teachers, achievements, and facilities. A total of 41 schools were analyzed using a non-hierarchical approach, with the optimal number of clusters determined through the Elbow Method, resulting in three groups: excellent, good, and fair. Data normalization was performed using the Min-Max method to ensure equal scaling among variables. The clustering results using the K-Means algorithm formed three clusters that represent the quality of schools based on transformed numerical data. The K-Means method proved capable of providing a general overview of school quality grouping, which can serve as a basis for policy-making to improve the quality of education in the region.
A Comparative Study of K-Means and K-Medoids for Clustering Dengue Fever Risk Areas in Medan Fitri, Anisa Amelia; Ula, Munirul; Agusniar, Cut
Jurnal Sistem Komputer dan Informatika (JSON) Vol. 6 No. 4 (2025): Juni 2025
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/json.v6i4.8702

Abstract

Dengue Hemorrhagic Fever (DHF) is a localized disease that continues to contribute to a high number of cases in Medan City. The local health authority faces challenges in identifying priority areas for effective prevention and control. This study applies data clustering techniques to map DHF risk areas by comparing the performance of K-Means and K-Medoids algorithms. The optimal number of clusters was determined using the Silhouette Coefficient, while the clustering quality was assessed using the Davies-Bouldin Index (DBI). The findings indicate that K-Means performs best with four clusters and achieves a lower DBI value compared to K-Medoids. Based on this, the study recommends using K-Means to categorize DHF risk areas into four priority levels: high, medium, low, and very low. This approach is expected to support the Medan City Health Office in implementing more targeted and efficient DHF control strategies.
Beyond Coding: Penguatan Kepemimpinan, Inovasi, dan Kontribusi melalui Kegiatan Training Dasar Organisasi HIMATIF Universitas Malikussaleh Anshari, Said Fadlan; Ula, Munirul; Yasin, Fijri Ahmad; Al-Ghiyats, Said; Dinda, Dinda; Putri, Nazirah Allisya
Jurnal Kemitraan Responsif untuk Aksi Inovatif dan Pengabdian Masyarakat Volume 3 Issue No. 1: July 2025
Publisher : Lontara Digitech Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61220/kreativa.v3i1.20264

Abstract

Kegiatan pelatihan kepemimpinan mahasiswa memiliki peran penting dalam membentuk generasi yang tidak hanya unggul secara akademik, tetapi juga memiliki kapasitas kepemimpinan, inovasi, dan kontribusi nyata dalam organisasi. Artikel pengabdian ini membahas pelaksanaan Training Dasar Organisasi (TDO) HIMATIF Universitas Malikussaleh dengan tema “Beyond Coding: Penguatan Kepemimpinan, Inovasi, dan Kontribusi”. Kegiatan ini dilaksanakan pada 29 Mei 2025 di Gedung Jurusan Informatika Universitas Malikussaleh, dengan dukungan dosen pendamping dan kolaborasi penuh dari Himpunan Mahasiswa Teknik Informatika (HIMATIF). Metode pelaksanaan meliputi penyampaian materi, diskusi interaktif, simulasi kepemimpinan, serta penyusunan rencana tindak lanjut oleh peserta. Hasil kegiatan menunjukkan peningkatan signifikan dalam lima aspek utama, yaitu penguatan kepemimpinan, literasi digital, kemampuan berinovasi, solidaritas organisasi, serta perumusan rencana pengembangan HIMATIF yang lebih progresif. Kegiatan ini membuktikan bahwa penguatan kapasitas mahasiswa melalui pelatihan berbasis sinergi antara teknologi dan kepemimpinan mampu memberikan dampak positif bagi organisasi kemahasiswaan. Kegiatan TDO HIMATIF diharapkan dapat menjadi model berkelanjutan dalam pengembangan organisasi mahasiswa, sekaligus menjadi praktik baik dalam mempersiapkan mahasiswa Informatika agar lebih adaptif, kreatif, dan berkontribusi di era digital.
PERANCANGAN VIRTUAL REALITY TOUR GEDUNG-GEDUNG FAKULTAS DI KAMPUS BUKIT INDAH UNIVERSITAS MALIKUSSALEH BERBASIS WEBSITE Azzikri, Affan Syafiq; Abdullah, ⁠Dahlan; Ula, Munirul
JOURNAL OF SCIENCE AND SOCIAL RESEARCH Vol 8, No 3 (2025): August 2025
Publisher : Smart Education

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54314/jssr.v8i3.3995

Abstract

Kemajuan teknologi informasi mendorong transformasi di berbagai sektor, termasuk pendidikan tinggi. Salah satu inovasi yang berkembang adalah pemanfaatan Virtual Reality (VR) untuk menciptakan pengalaman eksplorasi kampus secara digital. Penelitian ini bertujuan merancang dan mengembangkan aplikasi Virtual Reality Tour berbasis website untuk menampilkan visualisasi gedung-gedung fakultas di Kampus Bukit Indah, Universitas Malikussaleh. Aplikasi ini memanfaatkan 3DVista untuk panorama 360°, serta framework Laravel dengan HTML, CSS, dan JavaScript untuk membangun antarmuka yang responsif. Pengembangan dilakukan menggunakan metode Multimedia Development Life Cycle (MDLC) yang terdiri dari enam tahap. Evaluasi sistem melalui Blackbox Testing dan User Acceptance Testing (UAT) menunjukkan bahwa aplikasi berfungsi baik, mudah digunakan, dan menyenangkan. Hasil ini mendukung konsep smart campus serta berpotensi sebagai media promosi dan orientasi digital yang efektif.
Comparing Long Short-Term Memory and Random Forest Accuracy for Bitcoin Price Forecasting Munirul Ula; Veri Ilhadi; Zailani Mohamed Sidek
MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Vol. 23 No. 2 (2024)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/matrik.v23i2.3267

Abstract

Bitcoin’s daily value fluctuations are very dynamic. Understanding its rapid and intricate price movements demands advanced techniques for processing complex data. This research aims to compare the accuracy of two machine learning methods, Random Forest (RF) and Long Short-Term Memory (LSTM), in predicting Bitcoin price. This research employs RF and LSTM algorithms to forecast Bitcoin prices using a two-year Yahoo Finance dataset. The evaluation metrics used were accuracy based on Mean Absolute Percentage Error (MAPE) and computational power (CPU-Z). As a result of this research, the LSTM model demonstrates higher accuracy compared to the RF model. MAPE reveals LSTM’s precision of 99.8% and RF’s accuracy of 90.1%. Regarding computational time and resources, RF shows slightly better performance than LSTM. The visual comparison further emphasizes LSTM’s better performance in predicting Bitcoin prices, highlighting its potential for informed decision-making in cryptocurrency trading. This research contributes valuable insights into the effectiveness, strengths, and weaknesses of LSTM and RF models in predicting cryptocurrency trends.
Analisis Perbandingan Kinerja Algoritma You Only Look Once (YOLOv8) Dan Single Shot Detector (SSD) dalam Pengenalan Nominal Uang Kertas Ulfah, Julia; Ula, Munirul; Fajriana, Fajriana; Nurdin, Nurdin
Journal of Artificial Intelligence and Software Engineering Vol 5, No 4 (2025): Desember
Publisher : Politeknik Negeri Lhokseumawe

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30811/jaise.v5i4.7471

Abstract

The advancement of technology in the field of image recognition has significantly facilitated and improved the effectiveness of object detection in computer-based banknote recognition systems. This study aims to automatically identify banknotes based on their denominations, with the objective of minimizing human errors—such as lack of concentration, fatigue, and other factors—and enabling its application in ATMs and automated payment systems. This research compares the accuracy levels and detection success rates between the YOLO and SSD algorithms in recognizing the denominations of banknotes. The YOLO model operates by dividing the image into grids and predicting bounding boxes along with object classes in a single step, resulting in fast and consistent detection. In contrast, the SSD model employs a multi-scale approach by utilizing feature maps from multiple levels to generate predictions. The parameters used in this study include 7 classes of Indonesian banknotes: Rp1,000, Rp2,000, Rp5,000, Rp10,000, Rp20,000, Rp50,000, and Rp100,000. A total of 353 images were used in the dataset, and three images from each class were selected for testing purposes. The results of the study indicate a significant performance difference. The YOLO algorithm achieved a 100% accuracy rate under both normal and low-light conditions, while the SSD algorithm achieved an accuracy rate of 87.2% under normal lighting and 91.4% under low-light conditions.
Comparison of the Results of Double Exponential Smoothing Method with Triple Exponential Smoothing for Predicting Chili Prices Nadia Saphira; Munirul Ula; Sujacka Retno
Proceedings of International Conference on Multidisciplinary Engineering (ICOMDEN) Vol. 2 (2024): Proceedings of International Conference on Multidisciplinary Engineering (ICOMDEN)
Publisher : Faculty of Engineering, Malikussaleh University

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Double Exponential Smoothing (DES) is a forecasting method that combines two components level and trend, used for data with a trend pattern that tends to increase or decrease over time. In contrast, Triple Exponential Smoothing (TES) incorporates three components: level, trend, and seasonality, making it suitable for data with trend and seasonal patterns. This study uses historical chili price data from 2020 to 2023, obtained from the Bank Indonesia website, managed by the National Strategic Food Price Information Center (PIHPS), to compare the effectiveness of DES and TES in predicting chili prices in Medan City. Prediction accuracy was evaluated using MAPE (Mean Absolute Percentage Error) and MAE (Mean Absolute Error). The study results show MAPE values for DES as follows: Large Red Chili 1.25%, Curly Red Chili 1.39%, Green Bird’s Eye Chili 1.14%, and Red Bird’s Eye Chili 1.13%. TES produced slightly lower MAPE values: Large Red Chili 1.25%, Curly Red Chili 1.38%, Green Bird’s Eye Chili 1.12%, and Red Bird’s Eye Chili 1.10%. The MAE values for DES are as follows: Large Red Chili 447.9, Curly Red Chili 494.83, Green Bird’s Eye Chili 430.92, and Red Bird’s Eye Chili 423.36. TES showed better accuracy with MAE values of Large Red Chili at 447, Curly Red Chili at 493.02, Green Bird’s Eye Chili at 416.2, and Red Bird’s Eye Chili at 409.36. The results conclude that Triple Exponential Smoothing performs better than Double Exponential Smoothing in predicting chili prices.
Identification of Environmental Security in Relation to Crime Rates in Simeulue Regency Using Density-Based Spatial Clustering of Applications with Noise (DBSCAN) Method Yopy Anfelia; Munirul Ula; Sujacka Retno
Proceedings of International Conference on Multidisciplinary Engineering (ICOMDEN) Vol. 2 (2024): Proceedings of International Conference on Multidisciplinary Engineering (ICOMDEN)
Publisher : Faculty of Engineering, Malikussaleh University

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Criminal offenses are acts that violate criminal law and are punishable by the state, either through imprisonment, fines, or other sanctions. These offenses cause significant distress and harm to the general public, individuals, and the state. In Simeulue Regency, the number of criminal cases has been increasing annually, driven by social, economic, environmental, cultural, legal, technological, and psychological factors. This study aims to analyze the relationship between environmental security and the level of criminal cases in Simeulue Regency using the Density-Based Spatial Clustering of Applications with Noise (DBSCAN) algorithm. The data used includes criminal cases from 2019 to 2023 across 10 districts, along with environmental information such as population density, public facilities, and socioeconomic indicators. The research methodology involves data collection and cleaning, Euclidean distance calculation, parameter selection for DBSCAN, and the application of validation formulas to determine the vulnerability to criminal offenses in Simeulue Regency. The analysis results, using an epsilon parameter of 5 and MinPts of 3, yielded clusters 0, -1, and 1. Cluster 0 includes Salang and Teluk Dalam districts; cluster -1 includes Alafan, Simeulue Tengah, Simeulue Timur, Simeulue Barat, Teupah Barat, and Teupah Selatan districts; and cluster 1 includes Simeulue Cut and Teupah Tengah districts. The validation formula indicates that the highly vulnerable area is in Simeulue Timur district, while the at-risk areas are Teupah Tengah, Teluk Dalam, and Teupah Barat districts. The areas classified as not at risk are Alafan, Salang, Simeulue Tengah, Simeulue Cut, Simeulue Barat, and Teupah Selatan districts. This study provides insights into areas that require increased attention in efforts to address and prevent criminal offenses. Keywords: environmental security, criminal offenses, DBSCAN, clustering, Simeulue Regency
Co-Authors Abdullah, ⁠Dahlan Afif, Muhammad Athallah Afridah, Rita Agustriya, Manda Al-Ghiyats, Said Ananda Faridhatul Ulva Andreansyah, Sabda Arnawan Hasibuan Azzikri, Affan Syafiq Bustami Bustami Cut Agusniar Dahlan Abdullah Dhani, Saniah Dinda, Dinda Fadillah, Rizky Fahruddin Fahruddin Fajriana, F Fajriana, Fajriana Farhiyah, Dara Fasdarsyah Fasdarsyah Fidyatun Nisa Fikhri, Aditya Aziz Fitri, Anisa Amelia Fuddin, Mudhya Hasan Dalimunthe, Amir Husaini Kamaruzzaman, Hilda Zulfira Khalid, M David KURNIAWATI - Kurniawati Kurniawati Lidya Rosnita Lubis, Syahrul Andika Melani, Siska Amelia Muhammad Daud Muhammad Fauzan Muhammad Fikry Muhammad Ikhwanus Muhammad Muhammad Muhammad Yani, Muhammad Mutammimul Ula Muthalib, Muchlis Abd Nadia Saphira Nanda Imanda Nasution, Wahidatunnisa Nurdin Nurdin Nurdin Nurdin Nurdin Nurul Aula Putri Agustina Dewi Putri, Nazirah Allisya Rahman, Ashri Nurhajizah Ridha, Ridha Rini Meiyanti Rizal Rizal Rizal S.Si., M.IT, Rizal Rizki Suwanda Rizky Putra Fhonna Rizky, Rahmat Rozzi Kesuma Dinata Rusadi, Athirah Said Fadlan Anshari Saiful Kiram Salimuddin, Salimuddin Sayed Fachrurrazi Sayuti, Muhammad Siagian, Tania Annisa Sinambela, Reza Syahputra Sitepu, Yuni SariBr Siti Aminah Sudarti, Atrida Sujacka Retno Susanti Susanti Taufiq Taufiq Ulfah, Julia Veri Ilhadi Yasin, Fijri Ahmad Yessi Apprilia Yesy Afrillia Yopy Anfelia Yulisda, Desvina Zailani Mohamed Sidek Zara Yunizar