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All Journal JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI International Journal of Engineering, Science and Information Technology JUSTIN (Jurnal Sistem dan Teknologi Informasi) Brilliance: Research of Artificial Intelligence AJAD : Jurnal Pengabdian kepada Masyarakat TECHSI - Jurnal Teknik Informatika Sisfo: Jurnal Ilmiah Sistem Informasi Arcitech: Journal of Computer Science and Artificial Intelligence Journal Geuthee of Engineering and Energy Jurnal Pengabdian Masyarakat Bangsa Journal Of Artificial Intelligence And Software Engineering Jurnal Malikussaleh Mengabdi Jurnal Pengabdian Nasional (JPN) Indonesia Journal of Advanced Computer Knowledge and Algorithms
Sahputra, Ilham
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Forecasting of electrical energy consumption using Autoregressive Integrated Moving Average (Case Study: ULP Meulaboh Kota) Gunandra Siregar, Putri; Sahputra, Ilham; Nisa, Fidyatun
Journal Geuthee of Engineering and Energy Vol 4, No 1 (2025): Journal Geuthee of Engineering and Energy
Publisher : Geuthèë Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52626/joge.v4i1.56

Abstract

Forecasting electricity consumption is one of the solutions that can be implemented by the ULP Meulaboh Kota to ensure the availability of sufficient electricity supply. With the continuous increase in electricity demand, the ULP faces challenges in predicting and managing electricity consumption. Uncertainty in consumption patterns can lead to imbalances between supply and demand, potentially causing various issues such as power outages, high operational costs, and customer dissatisfaction. Therefore, accurate forecasting is essential to support effective decision-making and planning. This study aims to forecast electricity consumption across five different sectors: residential, social, business, industrial, and public, using the ARIMA (Autoregressive Integrated Moving Average) method. The forecasting process involves data collection, stationarity testing using the Augmented Dickey-Fuller (ADF) test, and differencing when necessary to achieve stationarity. The ARIMA model is identified through ACF and PACF plot analysis, estimated, and tested before being used for forecasting. The results indicate that the ARIMA method provides highly accurate forecasts for all sectors, as reflected by the low Mean Absolute Percentage Error (MAPE) values. The residential sector has a MAPE of 4.3957%, the social sector 4.3757%, the business sector 3.1125%, the industrial sector 7.9937%, and the public sector 4.3646%. Overall, the forecasting error produced by the ARIMA model remains below 8%, with an average MAPE of 4.8483% across all sectors.
Automated Recognition of Batik Aceh Patterns Using Machine Learning Techniques Utaminingsih, Eka; Sahputra, Ilham
Brilliance: Research of Artificial Intelligence Vol. 4 No. 2 (2024): Brilliance: Research of Artificial Intelligence, Article Research November 2024
Publisher : Yayasan Cita Cendekiawan Al Khwarizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/brilliance.v4i2.4831

Abstract

This research focuses on the automatic recognition of Aceh batik patterns using machine learning techniques. Utilizing a Convolutional Neural Network (CNN) model based on EfficientNet, a dataset consisting of 1,200 Aceh batik images was processed through various stages, from data collection to model training and evaluation. The images are divided into three main classes: Bungong Jeumpa, Ceplok, and Kerawang. The data processing steps include normalization, resizing, and data augmentation to ensure better variation. The model was trained using 75% of the data as a training set and 25% as a testing set. The results indicate that the model performed excellently, achieving an accuracy rate of 98%. According to the classification report, the model achieved an average precision, recall, and F1-score of 0.98. The Kerawang category achieved the highest precision at 100%, while the Bungong Jeumpa and Ceplok categories had F1-scores of 0.98 and 0.97, respectively. These findings demonstrate the potential of machine learning methods in recognizing Aceh batik patterns with high accuracy, supporting the preservation of local culture through technology.
Development of an Intelligent System to Determine Land Suitability for Horticultural Crops on Vegetable Commodities Sahputra, Ilham; Usnawiah; Fhonna, Rizky Putra; Siregar, Dinda Saima Agustina; Angelina, Difa
Brilliance: Research of Artificial Intelligence Vol. 3 No. 2 (2023): Brilliance: Research of Artificial Intelligence, Article Research November 2023
Publisher : Yayasan Cita Cendekiawan Al Khwarizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/brilliance.v3i2.3100

Abstract

Global climate change has a significant impact on the agricultural sector, including horticulture, with climate fluctuations such as increased temperatures and changes in rainfall patterns potentially affecting crop productivity. Sustainable horticultural agriculture is important for safeguarding natural resources and reducing environmental impacts. However, challenges from climate change and variations in land conditions can affect horticultural crop production. Identifying crops that are suitable for the climate and land conditions is key to agricultural sustainability. An intelligent and adaptive approach is needed in selecting the right crops to grow in the face of climate change. This research develops an artificial intelligence application for the recommendation of horticultural crop types according to land conditions and climate change. The model built involves AHP and MFEP methods. The model takes into account various land parameters with weights determined through the AHP approach, allowing this AI application to provide accurate recommendations based on data and modeling. Based on the tests conducted, the system was able to produce analysis with an accuracy rate of 85%.
Meningkatkan Semangat Literasi Digital Pada Generasi Millenial Dalam Penangkalan Berita Hoaks Sahputra, Ilham; Pratama, Angga; Fachrurrazi, Sayed; Muthmainnah, Muthmainnah; Saptari, Mochamad Ari
Jurnal Malikussaleh Mengabdi Vol. 2 No. 1 (2023): Jurnal Malikussaleh Mengabdi, April 2023
Publisher : LPPM Universitas Malikussaleh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29103/jmm.v2i1.12358

Abstract

Literasi digital banyak digunakan oleh generasi milleneal dalam kemampuan untuk mengakses, memahami dan menciptakan informasi dengan menggunakan teknologi digital. Literasi digital menjadi kemampuan dasar yang sangat penting bagi siswa SMA di era globalisasi dan revolusi industri 4.0 terlebih lagi jika hal tersebut berhubungan dengan hoaks yang semakin marak beredar. Berita hoaks banyak sekali diperoleh pada platform media sosial seperti Facebook, WhatsApp, tiktok dan  melalui browser berita di internet. Fenomena ini menimbulkan keresahan terhadap kebenaran suatu berita tersebut sehinga menimbulkan kebingungan. Namun, masih banyak siswa SMA yang belum memiliki literasi digital yang memadai dalam menagkal berita hoaks yang beredar. Oleh karena itu, sebgai bentuk pengabdian dilakukan kegiatan sosialisasi mengenai literasi digital di SMA Negeri 1 Lhokseumawe. Tujuan pengabdian ini agar siswa memiliki pemahaman yang lebih baik tentang literasi digital dalam penangkalan berita hoaks, generasi milenial khususnya siswa akan memiliki pengetahuan dan keterampilan yang lebih baik dalam menyaring informasi dan meyadari pentingnya menggunakan teknologi informasi dan computer secara bijak untuk selanjutnya digunakan dalam berbagai bidang, seperti komunikasi, bisnis, pendidikan, dan lain-lain. Metode yang digunakan dalam kegiatan sosialisasi ini adalah pemberian materi,diskusi, dan tanya jawab. Hasil kegiatan sosialisasi menunjukkan bahwa siswa SMA Negeri 1 Lhokseumawe memiliki tingkat kesadaran dan motivasi yang rendah tentang literasi digital dan informasi hoaks sebelum mengikuti kegiatan sosialisasi. Setelah mengikuti kegiatan pengabdian ini generasi milleneal menunjukkan peningkatan yang signifikan dalam hal kesadaran dan motivasi tentang literasi digital, serta pengetahuan dan keterampilan dasar tentang literasi digital. Dengan demikian, kegiatan pengbdian ini sangat penting dalam penangkalan berita hoaks dan pengabdian ini dapat dikatakan berhasil dan bermanfaat bagi siswa SMA Negeri 1 lhokseumawe.
Penerapan Teknologi Aplikasi Google Classroom Untuk Meningkatkan Pembelajaran Siswa di Dayah Nurul Iman Sahputra, Ilham; Fuadi, Wahyu; Sofyan, Diana Khairani; Muthmainnah, Muthmainnah; Maryana, Maryana; Zuraida, Zuraida
Jurnal Malikussaleh Mengabdi Vol. 3 No. 1 (2024): Jurnal Malikussaleh Mengabdi, April 2024
Publisher : LPPM Universitas Malikussaleh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29103/jmm.v3i1.16770

Abstract

Penerapan Google Classroom sebagai platform pembelajaran daring telah menjadi solusi efektif dalam mengatasi tantangan pendidikan. Teknologi ini memungkinkan pendidik dan siswa untuk tetap terhubung, memastikan proses pembelajaran berlangsung tanpa hambatan meskipun terpisah secara fisik akan tetapi tetang berjalan pembelajaran. Dengan fitur yang mendukung interaksi dua arah, penugasan, penilaian, dan akses materi pembelajaran dapat terlaksana, Google Classroom telah membantu menjaga kontinuitas Pendidikan dalam mengajar. Selain itu, platform ini juga mendukung adaptasi terhadap perkembangan teknologi dan metode pembelajaran yang inovatif, yang pada akhirnya meningkatkan kualitas pembelajaran dan mempersiapkan siswa untuk menjadi lebih mandiri dalam belajar. Dari hasil pengabdian ini menunjukkan bahwa teknologi memiliki banyak sekali peran dan manfaatnya dalam dunia pendidikan terlebih saat pembelajaran jarak jauh seperti pembelajaran online seperti google classroom hasil pengabdian ini untuk mengetahui penggunaan Penggunaan teknologi dalam pendidikan, khususnya selama pembelajaran jarak jauh, telah menunjukkan peran pentingnya dalam memastikan kontinuitas proses belajar mengajar. Google Classroom, sebagai salah satu platform Learning Management System (LMS), telah menjadi alat yang sangat berharga bagi dosen dan siswa. hasil pengabdian ini dengan adanya teknologi Google Classroom telah terbukti menjadi sumber daya yang sangat berguna dalam Pendidikan dan pembelajaran siswa
Usability testing analysis of the Lhokseumawe district attorney’s office website using nielsen’s metrics for user experience evaluation Alfarisyi, Ahmad; Sahputra, Ilham; Eviyanti, Cut Yuniza; Karima, Annisa
Journal Geuthee of Engineering and Energy Vol 4, No 2 (2025): Journal Geuthee of Engineering and Energy
Publisher : Geuthèë Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52626/joge.v4i2.63

Abstract

The Lhokseumawe district attorney's office is a law enforcement institution that utilizes a website as an essential medium for delivering public information and services. To ensure its optimal function, this research aims to evaluate the website's usability quality level. This study adopts the Usability Testing method with a quantitative descriptive approach , based on the five metrics proposed by Jakob Nielsen: learnability, efficiency, memorability, errors, and user satisfaction. Data collection involved direct observation of 10 users performing core task scenarios, supplemented by questionnaires and interviews. The test results indicate that the website generally meets several usability aspects. However, there are still significant shortcomings in the areas of efficiency and user satisfaction. Quantitatively, the website's total usability score is 87.5% , with the average satisfaction score using the System Usability Scale (SUS) being 65%. Based on these findings, this study recommends improvements to the navigation structure and user interface (UI) design to enhance the quality of digital services and provide a better user experience (UX). The results of this study are expected to serve as a reference for the website administrators of the Lhokseumawe District Attorney's Office for further system development
Pengabdian Kepada Masyarakat: Implementasi Artificial Intelligence Generatif sebagai Upaya Peningkatan Literasi Digital di Sekolah Sahputra, Ilham; Fadasrsyah, Fadasrsyah; Bustami, Bustami; Fauzan, Fauzan; Faridiansyah, T Iqbal; Irwansyah, Defi
Jurnal Pengabdian Masyarakat Bangsa Vol. 3 No. 11 (2026): Januari
Publisher : Amirul Bangun Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59837/jpmba.v3i11.3766

Abstract

Perkembangan teknologi digital, khususnya AI Generatif, telah memotivasi sekolah untuk meningkatkan literasi digital peserta didik. Program pengabdian ini bertujuan mendampingi sekolah dalam memanfaatkan AI Generatif untuk meningkatkan literasi digital dan memperkenalkan prinsip etika penggunaan teknologi secara bertanggung jawab. Metode yang diterapkan meliputi survei kebutuhan, pelatihan, workshop interaktif, pendampingan di kelas, serta evaluasi dampak. Hasil menunjukkan peningkatan pemahaman siswa tentang AI, etika digital, dan kemampuan verifikasi informasi. Siswa dapat mengintegrasikan AI dalam materi ajar dan evaluasi secara lebih efisien, serta mengembangkan keterampilan berpikir kritis. Penggunaan AI juga meningkatkan efisiensi waktu pengerjaan tugas hingga 60-70% dan memperkaya pembelajaran melalui penjelasan kontekstual adaptif. Meskipun ada kendala teknis, program ini memberikan dampak positif signifikan, meningkatkan literasi digital secara holistik dan mendukung pembelajaran yang lebih inklusif dan kreatif.
Pendampingan dan Pemanfaatan Artificial Intelligence Generative untuk Literasi Digital Masyarakat Desa Sahputra, Ilham; 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.
Analisis Komparatif Metode Klasterisasi (AHC-Ward, K-Means, GMM, dan BIRCH) untuk Pengelompokan Sentra Produksi Perkebunan Aceh Utara Sahputra, Ilham; Utaminingsih, Eka; Eviyanti, Cut Yuniza
JATISI Vol 12 No 4 (2025): JATISI (Jurnal Teknik Informatika dan Sistem Informasi)
Publisher : Universitas Multi Data Palembang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35957/jatisi.v12i4.13330

Abstract

This study compares four clustering techniques AHC-Ward, K-Means, GMM, and BIRCH to group sub-districts in North Aceh Regency based on plantation production data. The goal is to find the most effective clustering method for identifying diverse production patterns. Each algorithm's performance was evaluated using three internal metrics: Silhouette, Davies-Bouldin Index (DBI), and Dunn Index. The analysis showed that AHC-Ward had the most consistent and best performance. This method achieved the highest Silhouette score (0.515), the lowest DBI (0.309), and the highest Dunn Index (0.816). In contrast, K-Means performed the worst, while GMM and BIRCH were in between. Based on the optimal AHC-Ward clustering results, three clusters were found that reflect geographical specialization: a cluster with diverse production, a cluster dominated by oil palm, and a cluster focused on Arabica coffee and tobacco. These findings provide crucial insights for local governments to formulate agricultural policies that are more focused and relevant to the specific characteristics of each cluster.
Analisis Performa Website Perpustakaan Universitas Malikussaleh Menggunakan Metode Load Testing dengan Apache JMeter Sahputra, Ilham
JATISI Vol 12 No 4 (2025): JATISI (Jurnal Teknik Informatika dan Sistem Informasi)
Publisher : Universitas Multi Data Palembang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35957/jatisi.v12i4.13652

Abstract

The Universitas Malikussaleh library website plays a vital role in supporting academic activities for students and lecturers. System performance degradation during high traffic periods—such as exam weeks—can disrupt access to essential services. This study aims to evaluate the website’s performance through Load Testing using Apache JMeter. Three test scenarios were conducted under simulated loads of 100, 200, and 300 concurrent users, measuring key performance parameters including response time, throughput, and system stability. Results show that the website remained stable up to 200 users. However, under 300 users, performance significantly declined, marked by increased response times, reduced throughput, and bottlenecks on features like OPAC and online registration. These issues highlight limitations in the current infrastructure, particularly due to shared hosting. Based on the findings, several recommendations are proposed: upgrading server capacity, optimizing resource-intensive features, implementing caching mechanisms, and applying load balancing techniques. With these improvements, the library website is expected to deliver faster, more reliable services and be better equipped to handle traffic surges in the future
Co-Authors A Zohra, Siti Fatimah Abdulllah, Dahlan Afriza, Nadia Aidilof, Hafizh Al Kautsar Alfarisyi, Ahmad Angelina, Difa Angga Pratama ANNISA KARIMA Arief Rahman Arifa, Tiara Minda Badriana, Badriana Bakhtiar Bakhtiar Burhanuddin Burhanuddin Bustami Bustami Cut Agusniar Devi Irwansyah Elvanni, Imelda Elvanni Eviyanti, Cut Yuniza Fadasrsyah, Fadasrsyah Fadliani Fakhrurrazi Faridiansyah, T Iqbal Fauzan . Fauzi, Sri Wahyuni Fidyatun Nisa Fuadi, Wahyu Gunandra Siregar, Putri Herdiyanti, Alya Irwansyah, Defi Jasmin, Nadya Maryana Maryana Maryana Maryana, Maryana Mudawali, Mudawali Muhammad MUHAMMAD HABIB Muhammad Ikhwanus Mukarramah Mukarramah, Mukarramah Mukti Qamal Mutammimul Ula Muthmainnah Muthmainnah Nur Faliza Nurdin Nurdin Putri, Cindy Anindia Rahma Fitria, Rahma Razif, Razif Riki Maulana Rizky Putra Fhonna Rozzi Kesuma Dinata Safitri, Deviyan Safwandi Safwandi, Safwandi Saptari, Mochamad Ari Sari, Indah Maulida Sayed Fachrurrazi Siregar, Dinda Saima Agustina Siti, Nanda Sofyan, Diana Khairani Sujacka Retno Sukia, Sukia Sukiman, T. Sukma Achriadi Syibral Malasyi Syibral Malasyi, Syibral Syukriah Syukriah, Syukriah Tarigan, Anjasmara Teuku Multazam Usnawiah Utaminingsih, Eka Veri Ilhadi Yulisda, Desvina Yurni, Irma Zalfie Ardian Zohra, Siti Fatimah A Zulfia , Anni Zuraida Zuraida