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All Journal JURNAL SISTEM INFORMASI BISNIS Jurnal Simetris Prosiding SNATIF SITEKIN: Jurnal Sains, Teknologi dan Industri Jurnal Teknologi Informasi dan Ilmu Komputer CESS (Journal of Computer Engineering, System and Science) PROSIDING SENATEK FAKULTAS TEKNIK UMP R.E.M (Rekyasa Energi Manufaktur) Jurnal JOIV : International Journal on Informatics Visualization INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi Network Engineering Research Operation [NERO] JITK (Jurnal Ilmu Pengetahuan dan Komputer) Multitek Indonesia : Jurnal Ilmiah KOMPUTEK JuSiTik : Jurnal Sistem dan Teknologi Informasi Komunikasi Jurnal Abdimas PHB : Jurnal Pengabdian Masyarakat Progresif Humanis Brainstorming Journal of Computer Networks, Architecture and High Performance Computing Journal of Computer, Electronic, and Telecommunication (COMPLETE) Insyst : Journal of Intelligent System and Computation Jurnal Rekayasa, Teknologi, dan Sains Indonesian Journal of Networking and Security - IJNS Jurnal Abdimas Dosma SinarFe7 Abdimas Indonesian Journal Jurnal Pengabdian Masyarakat Bangsa Prosiding SEMNAS INOTEK (Seminar Nasional Inovasi Teknologi) Jurnal Pengabdian Kepada Masyarakat Bersinergi Inovatif Jurnal Abdimas Dosma Journal Information System and Computer Application KREATIF: Jurnal Pengabdian Masyarakat Nusantara Mathematics, Informatics, Knowledge, And Information Research
Fauzan Masykur
Universitas Muhammadiyah Ponorogo
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Sistem Deteksi Lokasi Dan Kerusakan Penerangan Jalan Umum Berbasis Internet Of Things Eka, Novie; Masykur, Fauzan; Sulthon Habiby, Jawwad
SinarFe7 Vol. 7 No. 1 (2025): SinarFe7-7 2025
Publisher : FORTEI Regional VII Jawa Timur

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

Abstract

Penerangan Jalan Umum (PJU) memiliki peranan penting dalam menjaga keselamatan pengguna jalan dan mengurangi angka kriminalitas, terutama pada malam hari. Di berbagai daerah termasuk Kabupaten Jombang, proses pemantauan kondisi PJU masih dilakukan secara manual, sehingga memperlambat penanganan kerusakan dan menurunkan efisiensi layanan. Beberapa penelitian sebelumnya telah mengembangkan sistem monitoring berbasis Internet of Things (IoT) untuk pemantauan infrastruktur kelistrikan, seperti pemantauan beban listrik menggunakan sensor PZEM-004T untuk mendeteksi arus dan tegangan [1], serta penggunaan modul GPS untuk pelacakan lokasi perangkat [2]. Platform ThingSpeak telah digunakan secara luas sebagai media visualisasi data IoT secara real-time [3], sementara Telegram dimanfaatkan sebagai media notifikasi cepat kepada petugas lapangan [4]. Penelitian ini mengembangkan sistem deteksi kerusakan dan lokasi PJU berbasis IoT dengan menggunakan mikrokontroler ESP32, sensor arus dan tegangan PZEM-004T, serta modul GPS NEO-6M. Sistem mengirimkan data ke platform ThingSpeak, serta mengirimkan notifikasi kerusakan melalui aplikasi Telegram yang diintegrasikan menggunakan Google Apps Script. Sistem ini dapat mendeteksi kondisi tidak normal seperti pemutusan MCB, dan secara otomatis mengirimkan informasi lokasi titik kerusakan melalui tautan Google Maps. Hasil pengujian menunjukkan sistem dapat memantau parameter listrik secara real-time, serta mengirimkan notifikasi lokasi kerusakan secara akurat dalam waktu kurang dari 1 menit setelah gangguan terdeteksi. Sistem ini terbukti dapat meningkatkan efisiensi pemantauan dan penanganan gangguan PJU secara signifikan, sehingga dapat menjadi solusi teknologi tepat guna bagi Dinas Perhubungan.
PEMANFAATAN MESIN PEMILAH IJUK UNTUK MENINGKATKAN PRODUKTIVITAS PEMBUAT SAPU IJUK Kuntang21; Trisnadi Putra, Wawan; Masykur, Fauzan; Yulio Eka Pratama , Beni
JURNAL ABDIMAS DOSMA (JAD) Vol. 2 No. 1 (2023): JANUARI
Publisher : IKATAN ALUMNI DOSEN MAGANG KEMENRISTEKDIKTI TAHUN ANGKATAN 2017

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70522/jad.v2i1.17

Abstract

The sorting of fibers carried out by home industry players is still traditional, which is still sorting manually by hand. Seeing this situation the author tries to make a tool that makes it easier for the work whose activities are to sort the fibers so that it can be finished quickly with satisfactory results. Work capacity will be prioritized in the work of this machine with the driving energy of the electric motor. The gripping tool or can be referred to as a substitute for the hand in holding the ijut, the chuck will be equipped with a threaded bolt that is useful as a lock so that the fibers cannot move at the time of selection or commonly referred to as sweeping. Based on the data that has been taken, this fiber sorting machine can sort 64 bunches weighing 50 grams and 30 cm in 5 minutes. Using this machine, work safety is guaranteed. In addition, the advantage of using this machine is that the power used is not too much.
Optimalisasi Produktivitas Pertanian melalui Inovasi Mesin Pencacah Pakan dan Pengolahan Limbah Ternak Berbasis Pemberdayaan Masyarakat Ellisia Kumalasari; Fauzan Masykur; Novi Indah Riani
KREATIF: Jurnal Pengabdian Masyarakat Nusantara Vol. 5 No. 3 (2025): Jurnal Pengabdian Masyarakat Nusantara
Publisher : Pusat Riset dan Inovasi Nasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/kreatif.v5i3.8409

Abstract

Banjarejo Village, Pudak Subdistrict, Ponorogo Regency, has agricultural and livestock potential that has not been fully utilized, particularly in the management of animal feed and cattle waste. This community service activity aims to improve agricultural and livestock productivity through the application of appropriate technology, namely a feed chopper machine and the conversion of livestock waste into organic fertilizer. The methods applied included socialization, training, and hands-on practice with farmers and livestock breeders over six months, accompanied by monitoring and evaluation of the technology’s effectiveness. The machine is assembled by utilizing a number of important components, including Diesel Matrix 6.5 G200 with 6.5 Hp power, strip plate, eser concrete, angle plate, hinge, 19 mm and 30 mm threaded axle, filter, B8 pulley system with V-belt, eser plate, and rubber wheels as mobility support. The implementation of this machine is expected to be able to provide a real contribution in increasing agricultural and livestock productivity through the use of appropriate technology that is more efficient, environmentally friendly, and oriented towards sustainability. The results showed an increase in feed efficiency by up to 40%, an average rise of 35% in milk production, and approximately 30% improvement in the quality of organic crops due to the use of compost fertilizer. This activity also enhanced the community’s understanding of sustainable local resource management and opened opportunities for business diversification in the agricultural and livestock sectors.
Fuzzy Method Design for IoT-Based Mushroom Greenhouse Controlling Prasetyo, Angga; Setyawan, Moh. Bhanu; Litanianda, Yovi; Sugianti, Sugianti; Masykur, Fauzan
INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi Vol 6 No 1 (2022): February 2022
Publisher : Universitas Nusantara PGRI Kediri

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (490.632 KB) | DOI: 10.29407/intensif.v6i1.16786

Abstract

The ideal conditions for the oyster mushrooms growth are at a humidity of 65-75% and 29-31C during incubation, while the growth of stems should be at a humidity of 70-90% 29-32C. This ideal ecosystem is maintained by aeration and manual watering. Still, the results are not optimal in preventing damage to the mycelium during the incubation period, resulting in a decrease in crop yields. Automatic control has not created ideal conditions because air temperature and humidity regulation are only based on fans and sprayers that do not directly affect air conditions. Therefore, we need a method to manipulate the mushroom greenhouse space ecosystem, namely fuzzy logic, the application of fuzzy logic integrated with sensors, actuators, and microcontrollers with the Internet of Things to solve this problem. The results of the installation of fuzzy logic in the mushroom's greenhouse in this system can be seen from the fan's modulation response and the pump's duration. The test results of this control feature can manipulate temperature and humidity. Therefore, the oyster mushroom greenhouse produces an ideal state of 29.8C, the humidity of 68.97% RH, and the production has been proven to be optimal with an average daily harvest of 3.8kg.
Pengendalian Suhu dan Kelembapan Kumbung Jamur Dengan Metode Fuzzy Terintegrasi Internet of Things Prasetyo, Angga; Litanianda, Yovi; Setyawan, Moh. Bhanu; Masykur, Fauzan; Sugianti, Sugianti; Sumaji, Sumaji
Prosiding SEMNAS INOTEK (Seminar Nasional Inovasi Teknologi) Vol. 5 No. 1 (2021): Prosiding Seminar Nasional Inovasi Teknologi Tahun 2021
Publisher : Universitas Nusantara PGRI Kediri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29407/inotek.v5i1.841

Abstract

Jamur tiram atau dalam bahasa latin volvariella volvacea budidaya jamur tiram ini, membutuhkan akurasi dan toleransi kepresisian dalam mengendalikan suhu serta kelembapan yang menyerupai ekosistem habitat jamur tiram sebenarnya, fase inkubasi yang membutuhkan suhu udara 23-28C dengan kelembapan 60- 70%, Fase pembentukan Tubuh dan buah membutuhkan suhu udara 28-32C dengan kelembapan 70-90%. Pengelolaan suhu udara dan kelembapan oleh pembudidaya jamur tiram dilakukan dengan cara penyemprotan serta aerasi kumbung yang masih manual, sehingga pada tahapan fase inkubasi dan fase pembentukan tubuh jamur, belum optimal. Akibatnya hasil panen jamur menurun karena banyak miselium yang rusak saat fase inkubasi. perancangan system akan dilakukan dalam dua tahapan, fase pertama pembuatan wiring perangkat keras, kemudian fase kedua pengintegrasian logika fuzzy di perangkat lunak yang secara keseluruhan akan berupa internet of things (IoT) guna memudahkan dalam proses monitoring. Kinerja logika fuzzy pada sistem ini dilihat dari respon PWM kipas, durasi pompa dan kualitas jaringan pada koneksi internetnya. Hasil pengujian menunjukkan nilai PWM kipas berhasil merespon berbagai kondisi suhu. Durasi penyalan pompa juga bisa merespon perubahan kelembaban ruangan jamur. Sedangkan kualitas jaringan dari hasil percobaan diperoleh nilai konektifitas berupa nilai jitter buffering data 0,72 ms, nilai ping jaringan saat kondisi transmitter(Tx) dan received (Rx) 0,29 ms, dan delay sebesar 0,97 ms atau secara keseluruhan rata-ratanya kurang dari 1ms merupakan kondisi yang termasuk baik untuk penyelenggaraan sistem IoT.
PEMANFAATAN MESIN PEMILAH IJUK UNTUK MENINGKATKAN PRODUKTIVITAS PEMBUAT SAPU IJUK Kuntang21; Wawan Trisnadi Putra; Fauzan Masykur; Beni Yulio Eka Pratama
JURNAL ABDIMAS DOSMA (JAD) Vol. 2 No. 1 (2023): JANUARI
Publisher : IKATAN ALUMNI DOSEN MAGANG KEMENRISTEKDIKTI TAHUN ANGKATAN 2017

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70522/jad.v2i1.17

Abstract

The sorting of fibers carried out by home industry players is still traditional, which is still sorting manually by hand. Seeing this situation the author tries to make a tool that makes it easier for the work whose activities are to sort the fibers so that it can be finished quickly with satisfactory results. Work capacity will be prioritized in the work of this machine with the driving energy of the electric motor. The gripping tool or can be referred to as a substitute for the hand in holding the ijut, the chuck will be equipped with a threaded bolt that is useful as a lock so that the fibers cannot move at the time of selection or commonly referred to as sweeping. Based on the data that has been taken, this fiber sorting machine can sort 64 bunches weighing 50 grams and 30 cm in 5 minutes. Using this machine, work safety is guaranteed. In addition, the advantage of using this machine is that the power used is not too much.
Implementasi Algoritma Convolutional Neural Network (CNN) Untuk Identifikasi Jenis Tanaman Rimpang (Zingiberaceae) Rani Dwi Kartikasari; Mohammad Bhanu Setyawan; Fauzan Masykur; Adi Fajaryanto Cobantoro
MIKIR : Mathematics, Informatics, Knowledge And Information Research Vol. 1 No. 1 (2025): OCTOBER
Publisher : PT Mekar Research and Publishing

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Abstract

Rhizomes (Zingiberaceae) are modified plant stems that grow horizontally beneath the soil surface and can produce shoots and new roots from their nodes. Rhizome plants (Zingiberaceae) are known as ginger or spice plants. This research article discusses the identification of rhizome plant species using Convolutional Neural Network (CNN) algorithm with VGG19 architecture, involving a total of 10 classes of data samples. The rhizome images underwent data preprocessing, resizing them from 500 x 500 to 200 x 200 pixels. During the model design phase, three different scenarios were tested, considering variations in dataset proportions, number of epochs, and batch sizes. The results of the three scenarios showed that the second scenario performed the best, achieving an accuracy of 90%, a loss of 0.285, precision of 93%, recall of 89%, and F1-Score of 91%. The first scenario obtained an accuracy of 88%, and the third scenario achieved an accuracy of 82%. However, when applying the model to test images and achieving the highest accuracy of 90% during training, the accuracy dropped to 40% when evaluated on 100 testing data. This drop in accuracy can be attributed to several factors, including noise in the dataset used and insufficient amount of training data, leading to the model being less effective in learning and recognizing data patterns.
Student Engagement Detection Based on Visual Behavior Indicators Using YOLOv8 on a Public Classroom Dataset Mohammad Bhanu Setyawan; Angga Prasetyo; Fauzan Masykur
MIKIR : Mathematics, Informatics, Knowledge And Information Research Vol. 2 No. 2 (2026): JUNE
Publisher : PT Mekar Research and Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.65475/sser8h18

Abstract

Student engagement is an important indicator for evaluating the quality of the learning process; however, its measurement in conventional classrooms still largely relies on subjective and labor-intensive manual observation. This study aims to establish a reproducible baseline for student engagement detection based on visual behavioral indicators using the YOLOv8 model on a public dataset. The working dataset was constructed from two subsets of the Student Class Behavior (SCB) Dataset and restructured into five behavioral classes: hand_raising, reading, writing, bowing_head, and turn_head, resulting in 9,274 image-label pairs split into 6,491 training, 1,854 validation, and 929 test samples. The experiment used YOLOv8n with an image size of 416, a batch size of 8, and 50 effective epochs in Google Colab. Performance was evaluated using precision, recall, mAP@0.5, and mAP@0.5:0.95. The results show that the model achieved a precision of 0.4429, a recall of 0.5393, mAP@0.5 of 0.4630, and mAP@0.5:0.95 of 0.3211. The best class-level performance was observed for writing (AP 0.635) and hand_raising (AP 0.597), while bowing_head (AP 0.288) and turn_head (AP 0.332) remained comparatively weak. These findings indicate that YOLOv8n is feasible as a reproducible baseline for visual student behavior detection, although annotation refinement, comparative experiments, and architectural optimization are still required to strengthen the scientific contribution and the feasibility of real-world classroom deployment
OPTIMASI JARINGAN RT/RW NET MENGGUNAKAN SOFTWARE DEFINED NETWORK DAN LOAD BALANCING Fikri Muhamad; Fauzan Masykur; Adi Fajaryanto Cobantoro
MEKAR : Journal Information System and Computer Application Vol. 1 No. 1 (2025): AGUSTUS
Publisher : PT Mekar Research and Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.65475/nsghad86

Abstract

Meningkatnya kebutuhan akan akses internet yang stabil dan cepat, terutama di lingkungan RT/RW Net yang melayani pelanggan rumah tangga dengan berbagai kebutuhan seperti streaming dan pengunduhan, memunculkan tantangan dalam pengelolaan lalu lintas jaringan, terutama ketika menggunakan lebih dari satu penyedia layanan internet (ISP). Penelitian ini mengusulkan penerapan arsitektur Software Defined Networking (SDN) sebagai solusi untuk mengatasi masalah distribusi trafik yang tidak merata melalui mekanisme loadbalancing. SDN memberikan kontrol PDF dan fleksibel dalam pengelolaan jaringan, memungkinkan pengaturan lalu lintas secara dinamis dan efisien. Implementasi dilakukan dengan menggunakan pengontrol OpenDaylight dan perangkat MikroTik sebagai router yang dikonfigurasi mendukung protokol OpenFlow untuk loadbalancing dua ISP. Hasil pengujian menunjukkan adanya peningkatan pada parameter Quality of Service (QoS) seperti throughput, delay, jitter, dan packet loss. Dengan penerapan SDN dan loadbalancing setelah dilakukan pengujian dengan QoS didapat hasil rata-rata dari masing-masing parameter yaitu, untuk throughput dengan rata-rata 8,36 mbps , untuk parameter packet loss didapat hasil rata-rata 0.09% , untuk delaynya dengan rata-rata 39 ms dan parameter jitter dengan rata-rata 12,67 ms. Dari semua hasil pengujian parameter diatas membuktikan adanya peningkatan kualitas jaringan dibandingkan dengan sebelum penerapan SDN dan loadbalancing.
DETEKSI PENYAKIT DAUN TANAMAN STROBERI MENGGUNAKAN YOLOV8 PENDEKATAN BERBASIS DEEP LEARNING DI TAWANGMANGU Efi Mukaromah; Fauzan Masykur; Adi Fajaryanto Cobantoro
MEKAR : Journal Information System and Computer Application Vol. 1 No. 1 (2025): AGUSTUS
Publisher : PT Mekar Research and Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.65475/9mr3se03

Abstract

Deteksi dini penyakit pada daun stroberi merupakan langkah strategis dalam upaya peningkatan produktivitas pertanian, khususnya di kawasan dataran tinggi seperti Tawangmangu. Penelitian ini bertujuan untuk mengembangkan dan mengevaluasi performa model YOLOv8 untuk mendeteksi lima kelas utama kondisi daun stroberi secara real-time. Dataset lokal dikumpulkan langsung dari kebun stroberi di Tawangmangu dan dianotasi menggunakan format YOLO. Proses pelatihan mencakup augmentasi data dan pembagian dataset, kemudian dievaluasi menggunakan metrik akurasi, presisi, recall, F1-score, dan mean Average Precision (mAP). Pengujian model di Google Colab menunjukkan performa tinggi dengan nilai evaluasi mAP@0.5 sebesar 99.2% dan mAP@0.5:0.95 sebesar 94.5%. Pengujian lapangan menerapkan implementasi website STROBIKA menunjukkan akurasi rata-rata sebesar 84,6%, dan mampu mengidentifikasi tiga penyakit utama daun stroberi (Leaf Blight, Leaf Spot, dan Tipburn) secara cepat dan akurat. Meskipun terdapat tantangan dalam mengklasifikasikan daun sehat dan objek non-stroberi, sistem ini menunjukkan potensi tinggi untuk diterapkan dalam pertanian berbasis deep learning di dunia nyata.
Co-Authors ., Sugianti Ali Mahmudi Ali Mahmudi Aminuddin, Wildan Muhammad Andy Triyanto Angga Prasetyo Angga Prasetyo Arief Rahman Yusuf Arief Rahman Yusuf Astuti, Arin Yuli Beni Yulio Eka Pratama Cobantoro, Adi Fajaryanto Cobantoro, Adi Fajaryanto Desriyanti Devi Kartikasari Eahyu Oktavian, Elang Efi Mukaromah Eka, Novie Ellisia Kumalasari Fajaryanto, Adi Fikri Muhamad Fredin Rimba Saputra Ghulam Asrofi Buntoro Ibnu Makruf Pandu Atmaja Indah Puji Astuti Indah Puji Astuti Irfan Agung Nugroho Jamilah Karaman Karaman, Jamilah Karaman, Lazuardi Irham Kelik Sussolaikah Khoiru Nurfitri Krisna Nurhuda Kuntang Winangun Kuntang21 Kuntang21 M. Malyadi Makruf Pandu Atmaja, Ibnu Miftakhul Arifin Mohammad Bhanu Setyawan Mohammad Bhanu Setyawan Mohammad Rizqi Rosyadi Muhammad Furqon Fadli Muhammad Malyadi nabila solihin zaelani, bintang muhammad Nerissa Nikmatul Qoiriyah Novi Indah Riani Novia Anggraini Pradityo Utomo Prasetiyowati, Fiqiana Prasetyo, Angga Rani Dwi Kartikasari Rendy Cahyono Reza Risky Khamdani Rido Muhamad Nasrudin Riyanto, Didik Rizqi Rosyadi, Mohammad Roikhatul Jannah Setyawan, Moh. Bhanu Sugianti Sugianti, Sugianti Sulthon Habiby, Jawwad Sumaji Trisnadi Putra, Wawan Wawan Trisnadi Putra Windy Octavia Yofhi Fauda Pradana Yofhi Yovi Litanianda Yovi Litanianda, Yovi Yulio Eka Pratama , Beni Yusuf, Arief Rahman Zulkarnain, Ismail Abdurrozaq Zulkarnain, Ismail Abdurrozzaq