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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Jurnal Teknologi Informasi dan Komunikasi JTERA (Jurnal Teknologi Rekayasa) JOURNAL OF APPLIED INFORMATICS AND COMPUTING JURNAL REKAYASA TEKNOLOGI INFORMASI JMM (Jurnal Masyarakat Mandiri) JITTER (Jurnal Ilmiah Teknologi Informasi Terapan) ILKOM Jurnal Ilmiah METHODIKA: Jurnal Teknik Informatika dan Sistem Informasi EXPLORE Jurnal Mantik Unram Journal of Community Service (UJCS) Journal of Computer Science and Informatics Engineering Prosiding Seminar Nasional Sisfotek (Sistem Informasi dan Teknologi Informasi) EXPLORE Jurnal Bangun Abdimas Jurnal Teknik Informatika dan Teknologi Informasi Formosa Journal of Computer and Information Science Jurnal Ilmiah Pengabdian dan Inovasi Journal Of Computer Science And Technology Semar : Jurnal Sosial dan Pengabdian Masyarakat Jurnal Rekayasa Sistem Informasi dan Teknologi Faedah: Jurnal Hasil Kegiatan Pengabdian Masyarakat Indonesia Jurnal Penelitian Teknologi Informasi dan Sains Journal of Computer Science and Information Technology Jurnal Kecerdasan Buatan dan Teknologi Informasi Journal of Data Analytics, Information, and Computer Science (JDAICS) Explore E-Amal: Jurnal Pengabdian Kepada Masyarakat Green Engineering: Journal of Engineering and Applied Science Journal of Information Technology and its Utilization Jurnal Teknik Informatika dan Teknologi Informasi Jurnal Karya untuk Masyarakat (JKuM) Jurnal Manajemen Bisnis Krisnadwipayana Jurnal Publikasi Teknik Informatika
Lalu Delsi Samsumar, M.Eng.
Universitas Teknologi Mataram
Agriculture, Biological Sciences & Forestry Arts Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Mathematics Mechanical Engineering Public Health Social Sciences Other

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Rancang Bangun Smart Pet Feeder Pada Kandang Kucing Berbasis Internet of Things Silpa Rani Zain; Zaenudin; Ardiyallah Akbar; Lalu Delsi Samsumar
Journal of Computer Science and Technology (JOCSTEC) Vol 2 No 3 (2024): JOCSTEC - September
Publisher : PT. Padang Tekno Corp

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59435/jocstec.v2i3.415

Abstract

Memeliahara kucing merupakan hal yang sangat digemari, namun tidaklah mudah untuk memonitoring penyimpanan pakan dan  minum kucing secara real-time, dalam hal ini para pemelihara memerlukan sistem  yang dapat memonitoring kondisi pakan dan minum kucing mereka tanpa harus berada dirumah. Pada penelitian ini menggunakan Metode Prototype untuk mengembangkan sistem. Hasil penelitian menunjukkan bahwa sistem ini bekerja secara otomatis menggunakan RTC untuk penjadwalan waktu pemberian pakan, Sensor Load Cell sebagai alat untuk menimbang berat pakan yang akan dibaca oleh servo untuk menarik tali pintu penampung pakan dan Sensor Water Level untuk mengukur  ketinggian air. Kemudian data pada kedua sensor tersebut akan di tampilkan pada aplikasi telegram untuk mengetahui kondisi dari wadah pakan dan minum kucing.
IoT Innovation and Entrepreneurship Education: Sustainable Tilapia Cultivation Optimization Strategy Samsumar, Lalu Delsi; Kembang, Lale Puspita; Akbar, Ardiyallah; Sriasih, Sriasih; Zaenudin, Zaenudin; Kalbuadi, Amiruddin
Unram Journal of Community Service Vol. 5 No. 4 (2024): December
Publisher : Pascasarjana Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/ujcs.v5i4.781

Abstract

Tilapia cultivation in Teratak Village, Central Lombok, faces problems in feed efficiency and limited market access. Lack of automation technology causes feed waste, while limited marketing knowledge limits farmers' competitiveness. This community service activity aims to overcome these problems through the application of Internet of Things (IoT) technology in the form of automatic feeders (smart feeders) and entrepreneurship training focused on digital marketing. The methods applied include the manufacture and installation of smart fish feeders that are controlled via an application to regulate the amount and frequency of feed. In addition, entrepreneurship training focuses on digital marketing strategies through social media and e-commerce platforms to expand market reach. The results of the activity show that smart feeders increase feed efficiency by up to 20%, reduce waste, and support more optimal fish growth. Digital marketing training helps farmers improve their online promotion skills, expand market networks, and significantly increase sales. In conclusion, the application of IoT technology and digital marketing-based entrepreneurship training has proven effective in increasing the efficiency of cultivation and market competitiveness of tilapia farmers in Teratak Village
RANCANG BANGUN PROTOTYPE SISTEM PENDETEKSI GEMPA BERBASIS IOT MENGGUNAKAN NOTIFIKASI TELEGRAM Rini Pratiwi Lalu Delsi Samsumar Zaenudin Ardiyallah Akbar, Rini Pratiwi Lalu Delsi Samsumar Zaenudi
Journal of Computer Science and Information Technology Vol. 1 No. 4 (2024): September
Publisher : Yayasan Nuraini Ibrahim Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70248/jcsit.v1i4.1269

Abstract

Gempa bumi merupakan bencana alam yang sering terjadi di Indonesia karena letak geografisnya yang berada di daerah pertemuan lempeng tektonik. Tujuan penelitian Untuk mengasilkan rancang bangun prototype sistem informasi pendeteksi gempa berbasis Internet of things menggunakan notifikasi telegram. Pada penelitian ini, pendekatan yang di gunakan adalah metode prototype. metode ini melibatkan pembuatan model atau prototype sederhana yang menggambarkan fitur dan fungsi utama dari sistem yang sedang dikembangkan. Metodologi pembuatan prototype adalah pendekatan dalam pengembangan sistem yang bertujuan untuk menciptakan sebuah sistem yang dapat digunakan untuk menguji dan menyempurnakan sistem yang di hasilkan. Hasil dari penelitian ini adalah sistem pendeteksi gempa berbasis IoT menggunakan sensor SW420 dan Buzzer berserta LED digunakan sebagai tanda peringatan bahaya terjadinya gempa dengan notifikasi telegram adalah sebuah alat yang di rancang untuk dapat mendeteksi adanya guncangan atau getaran yang di sebabkan oleh gempa bumi. Sistem ini terdiri dari beberapa komponen utama, yaitu ESP32 yang berfungsi untuk mengolah data output dari sensor yang digunakan.
Implementation of Smart Feeder Based on Internet of Things (IoT) for Fish Aquarium Misniati, Misniati; Delsi Samsumar, Lalu; Zaenudin, Zaenudin
Journal of Computer Science and Informatics Engineering Vol 5 No 1 (2026): January
Publisher : Ali Institute of Research and Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55537/cosie.v5i1.1292

Abstract

Household aquarium maintenance is generally performed manually, including feeding, monitoring temperature and turbidity, and water replacement, which is time-consuming and may reduce water quality, leading to stress or fish mortality. Although Internet of Things (IoT) technology has developed, its application in household aquariums remains limited. This study designed and implemented an IoT-based smart feeder with automatic feeding, water quality monitoring, and automatic water replacement using ESP32, DS18B20 temperature sensor, turbidity sensor, ultrasonic sensor, RTC, servo motor, water pump, and the Blynk application, applying a prototyping method. Tests showed the DS18B20 sensor had an average error of ±1.55% with 98.45% accuracy and ±1.5 s response time; the turbidity sensor distinguished clear and turbid conditions with 99% accuracy and ±2 s response; the ultrasonic sensor reached 92%; feed distribution achieved 98.6% with 1.2 s servo response; and water replacement achieved 66.7%–90% depending on turbidity threshold, with Blynk latency <2 s. Overall, the system achieved an average success rate of 91.5%, reducing manual workload, maintaining optimal water quality, and improving user convenience, while providing opportunities for further IoTbased aquarium automation development at the household scale
Design of Sustainable Smart Water Distribution Systems with Machine Learning-Based Leak Detection and Pressure Control to Conserve Water Resources Lalu Delsi Samsumar; Zaenudin Zaenudin; Supardianto Supardianto; Bahtiar Imran
Green Engineering: International Journal of Engineering and Applied Science Vol. 1 No. 4 (2024): October: Green Engineering: International Journal of Engineering and Applied Sc
Publisher : International Forum of Researchers and Lecturers

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70062/greenengineering.v1i4.248

Abstract

The global clean water crisis is exacerbated by significant losses in water distribution networks (WDNs), resulting in inefficient use of both water and energy resources. Traditional methods of leak detection and pressure management often fail to address these inefficiencies, leading to substantial water wastage and high operational costs. This research aims to design a sustainable, smart water distribution system using advanced technologies such as Machine Learning (ML) for leak detection and automated pressure control. The system employs real-time monitoring through IoT sensors, which continuously gather data on water pressure, flow rates, and other critical parameters. This data is analyzed using various ML algorithms, including supervised and unsupervised learning models, to detect anomalies indicative of leaks. Additionally, the system integrates automated pressure control mechanisms that dynamically adjust pressure to prevent over-pressurization, reducing both water loss and energy consumption. By combining leak detection and pressure control, the proposed system offers a more efficient, sustainable solution to water resource management compared to traditional methods. The expected outcomes include a significant reduction in water loss, enhanced energy efficiency, and improved water service quality. However, the implementation of such a system in rural or small-town infrastructure faces challenges, including sensor maintenance, algorithm reliability, and regulatory issues. A cost-benefit analysis suggests that while the initial investment in smart technologies may be high, the long-term savings in water and energy costs outweigh these costs. This study underscores the potential of ML-based systems in enhancing water conservation, operational efficiency, and sustainability in water management.
ANALISIS KUALITAS LAYANAN PENYIMPANAN CLOUD PADA NEXTCLOUD DAN PYDIO Lalu Delsi Samsumar; Beni Ari Hidayatulloh; Zaenudin Zaenudin; Putri Novia Dyah Pitaloca
Journal of Information Technology and Its Utilization Vol 6 No 1 (2023): June 2023
Publisher : Sekolah Tinggi Multi Media

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56873/jitu.6.1.5015

Abstract

The development of information technology has greatly influenced the development of current storage media, such as cloud-based storage (cloud). Nextcloud and pydio storage are part of an open based cloud computing system. Measuring service quality can be seen from the aspects of throughput, delay, jitter, and packet loss. This research was conducted to compare the upload and download speeds between the nextcloud server and the pydio server. Of the two cloud storage servers, five trial upload and download respectively. Based on the test results showing that the upload and download processes produce final cloud storage data which has the highest average throughput in terms of uploading files of different types and capacities, the next cloud server is 1,934.6 kbps. The cloud storage that has the lowest average packet loss value is balanced, because the two cloud storages get the same packet loss value of 0%. The cloud storage that has the lowest average file upload delay is the nextcloud server at 222,585 ms. The cloud storage that gets the lowest jitter value is the pydio server of 160.56 ms. Meanwhile, for downloading cloud storage files that have the highest average throughput value, nextcloud server is 1,332 kbps. The cloud storage that has the lowest average packet loss value is balanced, because the two cloud storages get the same packet loss value of 0%. The cloud storage that has the lowest average download delay is the nextcloud server at 132,057 ms, while the cloud storage that has the lowest jitter is the nextcloud server at 132,139 ms.
Expert System for Pest Diagnosis on Local Black Rice Plant in East Kalimantan Using the Naive Bayes Method Novianti Puspitasari; Anindita Septirini; Rian Bintang Paripurna; Lalu Delsi Samsumar
Journal of Information Technology and Its Utilization Vol 6 No 2 (2023): December 2023
Publisher : Sekolah Tinggi Multi Media

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56873/jitu.6.2.5271

Abstract

Rice plant is a food crop that produces rice as the staple food for the majority of Indonesian people. Local rice which significantly contributes to fulfill the national rice consumption is black rice produced in East Kalimantan. However, local black rice often experiences crop failure due to pest attacks and environmental factors. The amount of local black rice production also continues to decrease due to limited human resources who have the skills and knowledge to diagnose pests in black rice plants. Therefore, one effort that can be made to overcome this problem is to create an expert system that can diagnose pests and diseases in black rice plants. The expert system in this research uses the Naive Bayes method, which identifies 11 types of pests that attack black rice plants and 34 symptoms caused by these pest attacks. Naive Bayes can provide information about the percentage of pests that rice plants might experience. Based on the results of the test cases, an accuracy value of80% was obtained, so the expert system built in this research can diagnose pests on black rice plants quite well.
PELATIHAN DAN PENDAMPINGAN DIGITAL MARKETING SEBAGAI STRATEGI TRANSFORMASI BRANDING DAN PEMASARAN UMKM Kembang, Lale Puspita; Maryanti, Sri; Wardani, Laila; Samsumar, Lalu Delsi
JMM (Jurnal Masyarakat Mandiri) Vol 9, No 5 (2025): Oktober
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jmm.v9i5.34674

Abstract

Abstrak: UMKM merupakan sektor penting dalam perekonomian Indonesia, namun masih banyak yang menghadapi keterbatasan dalam pemanfaatan teknologi digital. Kegiatan Pengabdian kepada Masyarakat ini dilaksanakan untuk memberdayakan 25 pelaku usaha di Kota Mataram melalui pelatihan dan pendampingan digital marketing serta teknologi informasi. Metode pelaksanaan kegiatan meliputi sosialisasi, pelatihan intensif, implementasi teknologi, pendampingan, dan evaluasi. Hasil pre-test menunjukkan rata-rata pemahaman peserta adalah 48 dari 100, yang kemudian meningkat secara signifikan menjadi 82 dari 100 pada post-test. Sebanyak 100% peserta berhasil mengaktifkan akun media sosial bisnis, 80% mengelola akun marketplace dengan rata-rata 10 produk terunggah, dan 10 UMKM berhasil membangun identitas branding baru. Dampak kegiatan ini terlihat dari peningkatan engagement media sosial sebesar 45%, penambahan pengikut rata-rata 200 akun, serta kenaikan omzet rata-rata 28% dalam dua bulan pasca program. Kegiatan ini membuktikan bahwa transformasi digital melalui pelatihan dan pendampingan berkelanjutan efektif meningkatkan literasi digital, daya saing, dan kemandirian UMKM.Abstract: Micro, Small, and Medium Enterprises (MSMEs) are a crucial sector in the Indonesian economy, yet many still face limitations in utilizing digital technology. This Community Service activity was implemented to empower 25 business owners in Mataram City through digital marketing and information technology training and mentoring. The implementation method included outreach, intensive training, technology implementation, mentoring, and evaluation. Pre-test results showed an average participant understanding of 48 out of 100, which then increased significantly to 82 out of 100 in the post-test. A total of 100% of participants successfully activated their business social media accounts, 80% managed marketplace accounts with an average of 10 uploaded products, and 10 MSMEs successfully established new branding identities. The impact of this activity was seen in a 45% increase in social media engagement, an average increase of 200 followers, and an average increase in turnover of 28% in the two months following the program. This activity proves that digital transformation through continuous training and mentoring is effective in increasing digital literacy, competitiveness, and independence of MSMEs.
Sistem Monitoring dan Kontrol Rumah Pintar Berbasis Internet Of Things Untuk Peningkatan Efisiensi Energi Lalu Delsi Samsumar; Zaenudin Zaenudin; Ardiyallah Akbar; Emi Suryadi; Beni Ary Hidayatullah
Jurnal Teknik Informatika dan Teknologi Informasi Vol. 3 No. 2 (2023): Agustus: Jurnal Teknik Informatika dan Teknologi Informasi
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/jutiti.v3i2.3541

Abstract

The urgency of research with the theme of designing and implementing a smart home monitoring and control system based on the Internet of Things (IoT) to improve energy efficiency and quality of life is very important to carry out, in general it can be described as being able to increase energy efficiency; improve the quality of life where the system can regulate temperature, humidity and lighting to create a comfortable and healthy environment; encourage innovation; providing solutions to environmental challenges; optimizing energy availability where the smart home IoT system can regulate the use of available energy. Thus, it is very important to carry out this research to face environmental challenges and improve people's quality of life. The main objective of this research is to develop a system that can monitor and control energy use in the home efficiently, so as to improve energy efficiency and the quality of life of home residents, to overcome weaknesses and develop a holistic and effective smart home monitoring and control system. IoT based. The method used in this research is the Research and Development method, where this method is a process or steps to develop a new product or improve an existing product, which can be accounted for. The research results show that the IoT system can be designed and function well based on the results of the tests that have been carried out.
Anomaly-Based DDoS Detection Using Improved Deep Support Vector Data Description (Deep SVDD) and Multi-Model Ensemble Approach Imran, Bahtiar; Samsumar , Lalu Delsi; Subki, Ahmad; Wahyuni, Wenti Ayu; Muahidin, Zumratul; Karim, Muh Nasirudin; Yani, Ahmad; M. Zulpahmi
Journal of Applied Informatics and Computing Vol. 10 No. 1 (2026): February 2026
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v10i1.11863

Abstract

Distributed Denial-of-Service (DDoS) attacks remain a critical threat to network infrastructure, demanding robust and efficient detection mechanisms. This study proposes an enhanced Deep Support Vector Data Description (Deep SVDD) model for unsupervised DDoS detection using the UNSW-NB15 dataset. The approach leverages a deep encoder architecture with batch normalization and dropout to learn compact latent representations of normal traffic, minimizing the hypersphere volume enclosing benign flows. Only normal samples are used during training, adhering to the unsupervised anomaly detection paradigm. The model is evaluated against five established baselines—Isolation Forest, Local Outlier Factor (LOF), One-Class SVM, Autoencoder, and a simple ensemble—using AUC, F1-score, and recall as primary metrics. Experimental results demonstrate that Deep SVDD significantly outperforms all baselines, achieving superior class separation, high detection sensitivity, and computational efficiency (0.0004 GFLOPs). Notably, while LOF exhibited a deceptively high F1-score, its AUC near 0.5 revealed poor discriminative capability, highlighting the risk of relying on single metrics. The ensemble approach failed to improve performance, underscoring the limitation of naive score averaging when weak detectors are included. Visualization of score distributions and ROC curves further confirms Deep SVDD’s ability to effectively distinguish DDoS from benign traffic. These findings affirm that representation learning in latent space offers a more reliable foundation for anomaly detection than traditional distance-, density-, or reconstruction-based methods. The proposed model presents a promising solution for real-time, low-overhead intrusion detection systems in modern network environments. Future work will explore adaptive ensembles, self-supervised pretraining, and deployment on edge devices.
Co-Authors Ahmad Khairul Anam Ahmad Subki ahmad yani Aini Husnida Wulandari Akbar , Ardiyallah Akbar, Ardiyallah Amalia Rahman Amiruddin Kalbuadi Amirudin Kalbuadi Anindita Septirini Ardiyallah Akbar Ardiyallah Akbar Ardiyallah Akbar Aspari, Roni Astutik Zaerani Aulia, Asma Ayu Awanda Aerin Maesyarani Ayuni Azhuri Baiq Hanna Kurratul Aini Beni Ari Hidayatulloh Beni Ary Hidayatullah Beni Ary Hidayatullah Beni Iskandar Firdaus Lubis Biaq Widari Datu Samara Buchtami, Lalu Reza Dedi Arman Dedi Supriadi Dewi Rispawati Dewi Rispawati Efendi, Muhamad Masjun Erfan Wahyudi Fadhillah Hasbi Ilyas Fadia Karunia Utami Fasya, Muhammad Rafli Feni Ayu Putri Fira Ria Sutardi Gunawati, Junita Haidar, Muhammad Zul Hambali Hambali Hambali Hambali Hamzan Wadi Ika Mayang Sari Ilyas, Fadhillah Hasbi Imran, Bahtiar Ismayani Jaelani, Lalu Rizki Juma’in, Juma’in Juniyardi, Lalu Kalbuadi, Amirudin Karim, Muh Nasirudin Karim, Muh. Nasirudin Karya Gunawan Kembang, Lale Puspita Kristy, Rhama Aziz Aulia Kusuma, Ali Pandu Laela Uziah Lale Puspita Kembang Lale Puspita Kembang Lalu Darmawan Bakti, Lalu Darmawan Lalu Isnaeni Rahman Lihana M. Budiamin M. Yusuf M. Zulpahmi M. Zulpahmi M.Zulpahmi Mahmud Mahmud Mahmud Misniati Misniati, Misniati Moh. Subli Moh. Subli Muahidin, Zumratul Muh. Nasirudin Muhamad Miskar Muhammad Nasirudin Karim Muhammad Rijal Alfian Mulyadi, M. Erwin Mutaqin, Zaenul Ni Wayan Adelia Mutiara Asri Novianti Puspitasari Panji Wijayanto Paripurna, Rian Bintang Puspita Kembang, Lale Puspitasari, Novianti Putri Novia Dyah Pitaloca ratih ratih Rian Bintang Paripurna Riandi Akbar Ramiz Rudi Muslim Rudi Muslim Sahida, Nirmala Said, Syukroni Salman Salman Salman Salman Salman Salman Sapitri, Nurul Septirini, Anindita Silpa Rani Zain Sofian Hadi Sri Maryanti Sriasih, Sriasih Subki, Ahmad Sugeng Widodo Suja’i, Ahmad Supardianto Supardianto Suryadi, Emi Sutrisno, Sutrisno Tony Gunawan wahyuni, wenti ayu Wardani, Laila Wijaya, I Gusti Ngurah Satria Yumarlin MZ Zaenaldi, Firki Zaeniah Zaeniah Zaenudin Zaenudin Zaenudin Zaenudin Zaenudin Zaenudin Zaenudin Zaenudin Zaenudin Zaenudin Zaenudin Zaenudin Zaenudin Zaenudin Zaenul Mutaqin Zaenul Muttaqin Zulpahmi, M