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All Journal Jurnal Pendidikan Indonesia Jurnal Informatika dan Teknik Elektro Terapan Jurnal Teknologi Elektro Creative Information Technology Journal INTEGER: Journal of Information Technology Pendas : Jurnah Ilmiah Pendidikan Dasar Best Journal (Biology Education, Sains and Technology) Jurnal Computer Science and Information Technology (CoSciTech) Journal of Soft Computing Exploration Jurnal Informatika Terpadu International Journal of Community Service Journal of Social Research Journal of Innovation Research and Knowledge Jurnal Riset Rumpun Ilmu Teknik (JURRITEK) Jurnal Riset Rumpun Ilmu Kesehatan (JURRIKES) Jurnal Ilmiah Teknik Informatika dan Komunikasi Innovative: Journal Of Social Science Research Indonesian Vocational Research Journal IRA Jurnal Pengabdian Kepada Masyarakat Jurnal Penelitian Teknologi Informasi dan Sains Jurnal Pengembangan Teknologi Informasi dan Komunikasi (JUPTIK) Neptunus: Jurnal Ilmu Komputer dan Teknologi Informasi Dedikasi Nusantara IJENSET Jurnal Teknik Informatika dan Teknologi Informasi
Mufti Ari Bianto
Universitas Muhammadiyah Lamongan
Religion Agriculture, Biological Sciences & Forestry Humanities Automotive Engineering Biochemistry, Genetics & Molecular Biology Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Immunology & microbiology Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mechanical Engineering Medicine & Pharmacology Nursing Public Health Social Sciences Other

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Sistem Pendukung Keputusan Identifikasi Daerah Potensi Banjir Dengan Metode Multi Attribute Utility Theory (Studi Kasus: Kabupaten Lamongan) Bianto, Mufti Ari; Aprillya, Mala Rosa
INTEGER: Journal of Information Technology Vol 8, No 2 (2023): September
Publisher : Fakultas Teknologi Informasi Institut Teknologi Adhi Tama Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31284/j.integer.2023.v8i2.5024

Abstract

Penelitian ini bertujuan untuk membangun Sistem Pendukung Keputusan (SPK) yang dapat memberikan informasi sebaran daerah rawan banjir secara online pada masing-masing daerah di Kabupaten Lamongan. Penelitian ini menggunakan beberapa kriteria antara lain intensitas curah hujan, kemiringan lereng, jenis tanah, dan jarak ke sungai. Dalam penelitian ini data diperoleh dari seluruh kecamatan yang ada di Kabupaten Lamongan yang berjumlah 27 kecamatan. Tahapan dalam pengembangan sistem ini dimulai dengan mengumpulkan data terkait yang meliputi intensitas curah hujan, kemiringan lereng dan jenis tanah di setiap kecamatan. Proses penghitungan daerah potensi banjir menggunakan metode Multi Attribute Utility Theory. Langkah selanjutnya adalah membangun sistem berbasis web dengan menggunakan bahasa pemrograman PHP. Hasil kepuasan responden (pemangku kepentingan) terhadap system rata-rata 80%
Implementasi Convolutional Neural Network (CNN) untuk Klasifikasi Citra Batik Nusantara Zufar Faiil Haq; Mufti Ari Bianto; Afifah Agustin; Moch. Ryan Nurfebrianto
Jurnal Teknik Informatika dan Teknologi Informasi Vol. 5 No. 1 (2025): April: 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.v5i1.5421

Abstract

Batik is a cultural heritage of the nation, with each batik having a unique and diverse pattern motif. The batik culture is very strong in Indonesia, so batik can be found in all regions of the archipelago. Each batik has its own characteristics and traits to distinguish itself in each area. However, many people find it difficult to differentiate the types of batik motif patterns, one of which is the Nusantara Megamendung batik. Therefore, this research aims to introduce the classification process of Nusantara batik motif patterns using one of the Deep Learning methods, namely Convolutional Neural Network (CNN), to differentiate the types of batik motif patterns in each region. The dataset is taken from the numeric representations of Red, Green, and Blue (RGB) values of each pixel, which are used as model learning features to study color patterns and textures. From the results of the experiments conducted, the batik image classification using the CNN method has a high level of accuracy The batik classification model achieved an accuracy of 85%, demonstrating a fairly good ability to identify batik images, one of which is the Mega Mendung batik. The Mega Mendung and Keraton classes showed perfect performance, with precision, recall, and F1-score close to 1.00. However, the Bali class was the main weak point, with a recall of only 60%, indicating that 40% of Bali Batik samples were misclassified, primarily as Keraton.
DESIGN OF AN AI-INTEGRATED RENEWABLE ENERGY SMART ELECTRIC FENCE FOR RAT PEST MITIGATION Bianto, Mufti Ari; Ihsan, M. Nurul; Umam, Khairul
Pendas : Jurnal Ilmiah Pendidikan Dasar Vol. 10 No. 04 (2025): Volume 10 No. 04 Desember 2025 Published
Publisher : Program Studi Pendidikan Guru Sekolah Dasar FKIP Universitas Pasundan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23969/jp.v11i01.43196

Abstract

Rat infestations in rice crops in Indonesia cause losses of approximately 5% of total national production, equivalent to 4 million tons per year, with an estimated value of IDR 18 trillion. Conventional methods such as chemical poisons and electric traps have limitations and pose risks to the environment and human safety. This study develops a Smart Electric Fence powered by renewable energy and integrated with Artificial Intelligence for safe and sustainable rat pest mitigation. The human and rat detection system applies a Convolutional Neural Network (CNN) approach using the YOLOv8 algorithm, implemented on a Raspberry Pi to automatically control the electric fence relay. The system is powered by solar panels. A dataset of 7,712 images was divided into training, validation, and testing sets. Evaluation results show 64.4% precision, 100% recall, and 64.4% accuracy, enabling real-time object detection.
Rancang Bangun Sistem Monitoring Hidroponik NFT Pada Tanaman Selada Menggunakan Fuzzy Mamdani Hanif Azhar Ramadhan; Mufti Ari Bianto; Bagus Dwi Saputra
Jurnal Teknologi Elektro Vol. 17 No. 2 (2026)
Publisher : Electrical Engineering, Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/jte.2026.v17i2.001

Abstract

Budidaya tanaman selada pada sistem hidroponik Nutrient Film Technique memerlukan pengendalian kondisi larutan nutrisi secara tepat agar pertumbuhan tanaman berlangsung optimal. Parameter seperti derajat keasaman, konduktivitas listrik, total padatan terlarut, dan suhu air memiliki pengaruh langsung terhadap kemampuan tanaman dalam menyerap unsur hara. Perubahan nilai parameter tersebut dapat terjadi secara dinamis sehingga pemantauan manual dinilai kurang efektif untuk mendukung pengambilan keputusan secara cepat dan berkelanjutan. Penelitian ini bertujuan merancang dan membangun sistem monitoring kondisi hidroponik berbasis Internet of Things dengan menerapkan metode Fuzzy Mamdani untuk menganalisis kondisi larutan nutrisi dan memberikan rekomendasi tindakan secara adaptif. Sistem dikembangkan menggunakan mikrokontroler ESP32, sensor derajat keasaman, sensor konduktivitas listrik dan total padatan terlarut, sensor suhu air, backend server, Firebase, serta aplikasi bergerak berbasis Flutter. Sistem menganalisis empat parameter utama secara simultan, yaitu derajat keasaman, konduktivitas listrik, total padatan terlarut, dan suhu air. Hasil penelitian menunjukkan bahwa sistem mampu membaca, memproses, dan mengirimkan data sensor secara real-time ke aplikasi pengguna dengan delay pengiriman data berkisar 1–3 detik. Hasil kalibrasi menunjukkan nilai Mean Absolute Error sensor derajat keasaman sebesar 0,050 dan sensor suhu sebesar 0,943. Pengujian pada lima skenario kondisi larutan menunjukkan bahwa metode Fuzzy Mamdani mampu menghasilkan rekomendasi tindakan yang sesuai terhadap perubahan parameter yang terjadi. Sistem yang dikembangkan dinilai mampu mendukung pemantauan kondisi hidroponik secara lebih efektif, adaptif, dan terintegrasi.
Webmap Application Training As An Effort For Flood Mitigation In The Agricultural Sector In Dlanggu Village, Lamongan Regency, East Java, Indonesia Mala Rosa Aprillya; Uswatun Chasanah; Mufti Ari Bianto
International Journal Of Community Service Vol. 2 No. 1 (2022): February 2022 (Indonesia - Malaysia - Philippines)
Publisher : CV. Inara in Colaboration with www.stie-sampit.ac.id

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51601/ijcs.v2i1.65

Abstract

Natural conditions are increasingly uncertain and difficult to predict due to changes in rainfall patterns and climate. Excessive rainfall can cause flooding which is detrimental to the agricultural sector. Flooding is a natural challenge that is often faced in the agricultural sector. This challenge is faced by most of the agricultural land in Lamongan Regency, including in Dlanggu Village. The impact of flooding on rice fields in certain locations which is increasingly widespread and intensive from year to year has caused considerable losses for farmers. The purpose of this activity is to map flood-affected agricultural land in a participatory manner with the help of the WebMap application. The method of implementing this activity includes the preparation stage, implementation stage, and monitoring and evaluation stage. The results of the activity showed that participants were very enthusiastic about this activity program, as evidenced by the positive response in the form of the presence of 96% of the training participants and active discussion activities during the socialization and training took place. After the training, the participants also expected a follow-up in the form of assistance from the service team to improve skills with WebMap applications in other fields. This activity is expected to be a solution that can be offered to provide an early warning system based on mapping so that the delivery of information about floods can be conveyed more quickly to the community, especially people who have agricultural livelihoods to be aware of flood disasters.
Perbandingan Klasifikasi Daun Cabai dengan Metode CNN dan SVM Untuk Deteksi Penyakit Afifah Agustin; Mufti Ari Bianto; Hery Ardiansyah
Jurnal Pengembangan Teknologi Informasi dan Komunikasi (JUPTIK) Vol. 4 No. 1 (2026): JURNAL PENGEMBANGAN TEKNOLOGI INFORMASI DAN KOMUNIAKSI (JUPTIK)
Publisher : Universitas Muhammadiyah Muara Bungo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52060/juptik.v4i1.4403

Abstract

Tanaman cabai (Capsicum frutescens L.) merupakan salah satu komoditas hortikultura yang memiliki nilai ekonomi tinggi, namun produktivitasnya masih sering mengalami penurunan akibat serangan penyakit yang disebabkan oleh bakteri, jamur, dan virus. Proses identifikasi penyakit secara konvensional membutuhkan waktu serta keahlian khusus, sehingga diperlukan suatu sistem deteksi yang mampu memberikan hasil secara cepat dan akurat. Penelitian ini bertujuan mengembangkan sistem klasifikasi penyakit daun cabai sekaligus membandingkan kinerja metode Convolutional Neural Network (CNN) dan Support Vector Machine (SVM). Dataset yang digunakan berjumlah 2.000 citra yang terbagi ke dalam lima kelas, yaitu bakteri, jamur, virus, sehat, dan non-daun. Tahap prapemrosesan meliputi perubahan ukuran citra menjadi 160×160 piksel, normalisasi, augmentasi, pelabelan, serta pembagian data menjadi data latih, validasi, dan data uji. Pada metode SVM, proses klasifikasi diawali dengan ekstraksi fitur menggunakan Histogram of Oriented Gradients (HOG) dan Color Histogram, sedangkan CNN melakukan ekstraksi fitur secara otomatis melalui lapisan konvolusi. Sistem kemudian diimplementasikan dalam bentuk website berbasis Flask. Hasil menunjukkan bahwa metode CNN memiliki kinerja yang lebih baik dari pada metode SVM berdasarkan parameter accuracy, precision, recall, dan F-1 Score, Dengan hasil akurasi CNN 85% dan SVM 78%. Selain itu, sistem mampu membedakan citra daun cabai dan non-daun secara baik sehingga dapat dimanfaatkan sebagai media dalam deteksi penyakit daun cabai.
A Pipe Leak Detection System Using Pressure and Flow Sensors for Residential Water Pipes Using The Sugeno Fuzzy Method Adam Azzamul Husni Huda; Mufti Ari Bianto; Heri Ardiansyah
Journal of Social Research Vol. 5 No. 10 (2026): Journal of Social Research (Issue in Progres)
Publisher : International Journal Labs (AHU-0028405-AH.01.14 Tahun 2022)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55324/josr.v5i10.3437

Abstract

The water loss rate in Indonesia remains at a critical range of 20–45%. The fundamental challenge in addressing this issue at the household scale is the computational difficulty of distinguishing between pressure fluctuations caused by normal water consumption patterns and pressure drops caused by physical pipe damage. Therefore, this study designed a smart pipe leak detection system prototype based on the Internet of Things (IoT) using the Zero-Order Sugeno Fuzzy Logic method. The system utilized an ESP32 microcontroller as a local processing unit based on edge computing, integrated with a water flow sensor (YF-S201) and a pressure sensor to monitor fluid dynamics in real time. The acquired data were classified into three linguistic sets—Normal, Small Leak, and Large Leak—to control a relay actuator as an automatic mitigation mechanism. Based on the system testing results, the instrument measurement error rates were 2.12% for the flow sensor and 2.19% for the pressure sensor. The Sugeno Fuzzy Logic algorithm achieved an inference accuracy rate of 100% in classifying pipe condition status compared with theoretical mathematical calculations. Furthermore, the IoT architecture recorded an emergency notification transmission latency of 1.20 seconds to the Blynk dashboard. The implementation of decentralized control through the microcontroller demonstrated the capability to reduce false alarm risks and provide reliable automatic water supply shutoff mitigation without depending on the stability of cloud server connectivity.
PEMANFAATAN TANAMAN OBAT KELUARGA (TOGA) DAUN SALAM SEBAGAI TEH CELUP HERBAL ALAMI DI DESA WUDI Zahrotun Nisa; Mufti Ari Bianto; Alfina Wijayanti Wibowo; Akbar Ramadhani; Ecki Salma Hapsari
Dedikasi Nusantara: Jurnal Pengabdian Masyarakat Vol. 1 No. 3 (2025): Inovasi Teknologi dan Pemberdayaan Masyarakat Desa
Publisher : IndoCompt Publisher

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

Abstract

Tanaman Obat Keluarga (TOGA) merupakan tanaman yang di budidayakan keluarga, dapat memberikan nutrisi, dan obat tradisional herbal yang aman. Permasalahan kesehatan dapat timbul karena kurangnya kesadaran masyarakat dalam menjaga kesehatan. Upaya dalam mengatasi masalah kesehatan salah satunya yaitu dengan melakukan penyuluhan tentang jenis-jenis tanaman toga dan manfaatnya, serta dengan penanaman toga yang dapat dijadikan sebagai obat herbal alami dan juga dapat bermanfaat sebagai produk jual seperti pembuatan teh herbal celup dari daun salam. Melalui program pengabdian masyarakat Kuliah Kerja Nyata (KKN) yang dilaksanakan di Desa Wudi, Kecamatan Sambeng, Kabupaten Lamongan, Jawa Timur ini masyarakat diperkenalkan tentang tanaman toga dan di latih dalam pemanfaatan tanaman toga sebagai produk jual. Metode pengabdian masyarakat ini menggunakan penyuluhan dan pelatihan sehingga dengan program ini berharap pengetahuan, dan kesadaran masyarakat tentang pentingnya menjaga status derajat kesehatan, serta dapat membantu ekonomi keluarga. Hasil kegiatan menunjukkan peningkatan pengetahuan dan kesadaran masyarakat tentang pentingnya menjaga status derajat kesehatan melalui penanaman toga, meskipun dengan cara yang cukup sederhana tetapi memiliki banyak manfaat. Kegiatan ini juga menunjukkan pentingnya komunikasi yang efektif dan kolaboratif dalam penyuluhan dan pelatihan kesehatan masyarakat.
Rancang Bangun Robot Forklift Menggunakan Computer Vision Berbasis Qr Code dan Navigasi Line Follower untuk Pemindahan Barang M. Rosyibad Rizein; Mufti Ari Bianto; Khairul Umam
Jurnal Penelitian Teknologi Informasi dan Sains Vol. 4 No. 1 (2026): : JURNAL PENELITIAN TEKNOLOGI INFORMASI DAN SAINS (JPTIS)
Publisher : Institut Teknologi dan Bisnis (ITB) Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54066/jptis.v4i1.4838

Abstract

In the advanced era of technology has accelerated automation across various sectors, including the logistics industry, which requires material handling processes to be fast, efficient, and safe. One of the key pieces of equipment supporting these operations is the forklift. However, manual forklift operation remains prone to accidents due to limited visibility, operator fatigue, insufficient skills and concentration, as well as inadequate forklift maintenance. According to the National Safety Council, more than 24,000 forklift-related accidents were recorded in 2022. As an automation solution, Automated Guided Vehicles (AGVs) have been widely developed for material handling applications. Nevertheless, most AGVs still rely primarily on sensor-based navigation and have not yet integrated computer vision for object recognition and destination determination. Therefore, this study proposes the design and development of a forklift robot that integrates YOLOv8-based computer vision with line follower navigation to perform autonomous material handling based on QR Code information. YOLOv8 is employed to detect QR Codes, while the decoded information is used to determine the destination for object placement. The transported object is a square-shaped item measuring 10 × 10 cm, equipped with a 4 × 4 cm QR Code facing the robot to ensure successful detection. System evaluation was conducted in a laboratory environment using a line follower track to simulate an automated material handling process. The experimental results show that the QR Code recognition system achieved a 100% detection accuracy across 40 test trials. The overall material handling effectiveness reached 74%, with 177 successful tasks out of 240 trials. The success rates for object lifting, intersection detection, and object placement were 100%, 98%, and 93%, respectively. Performance degradation occurred during intersection exit, returning to the main path, and returning to the home position due to limitations in line sensor readings, track conditions, and motor speed stability. The results demonstrate that the integration of YOLOv8-based computer vision and line follower navigation is capable of supporting autonomous material handling in a laboratory-scale environment.
SMART GIZI: Buku Saku Interaktif Pencegahan KEK bagi Remaja Putri dan Ibu Hamil di Desa Sendangagung Paciran Lamongan Angela Tiara Marsningrum; Eva Laili Wijayanti; Widuri Octavianunisa; Zuhrotun Nisa; Mufti Ari Bianto
IRA Jurnal Pengabdian Kepada Masyarakat (IRAJPKM) Vol 4 No 2 (2026): Agustus
Publisher : CV. IRA PUBLISHING

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56862/irajpkm.v4i2.528

Abstract

Chronic Energy Deficiency (CED) remains an issue among adolescent girls and pregnant women in Sendangagung Village, Paciran, Lamongan. This community service activity aimed to improve their understanding of CED's causes, consequences, and prevention. Methods included health education and discussions, using the "SMART GIZI" (Smart Nutrition) pocketbook and educational videos accessible via QR codes. We evaluated learning using pre-tests and post-tests, each with 10 questions. The results showed that the proportion of adolescent girls demonstrating a good level of knowledge rose from 51% to 74%. In comparison, the proportion of pregnant women with a good level of knowledge increased from 28% to 78%.
Co-Authors A, Dwi Putra Adam Azzamul Husni Huda Adam Rizky Al’insani Adhani, Hamka Lukmanul Hakim AF Suryaning Ati MZ Afifah Agustin Ahmad Abdullah Fahmi Akbar Ramadhani Alfina Wijayanti Wibowo Angela Tiara Marsningrum Arbiansyah, Lutfi Ardian Hudi Ramadhani Aris Widodo Badriyatul Musyarofah Bagus Dwi Jauhari Bagus Dwi Saputra Bufa Al badi Ecki Salma Hapsari Eko Handoyo Eva Laili Wijayanti Fiqrul Labib Abdullah Hanif Azhar Ramadhan Hanif Azhar Ramadhan Heri Ardiansyah Hery Ardiansyah Hidayah, Septina Alfiani Ihsan, M. Nurul Khairul Umam Kusrini M. Cahyo Kriswantoro M. Rosyibad Rizein Mala Rosa Aprillya Moch. Ryan Nurfebrianto Mohammad Hisyam Romadhon Mohammad Huda Adi Sanjaya Mubaarok, Ahmad Husni Muhammad Syaifuddin Alamsyah Mutsna, Mutsna Pratama, Alif Nanda Ramadhan, Bayu Putra Rifki Noor Rohman Rofiatun Solekha Ryky Ardiansyah Salasun Nisah SAPUTRA, BAGUS DWI Setiyowati, Putri Ayu Ika Sholikha, Hidayatin Sudarmawan Sudarmawan Tsalits Wildan Hamid Uswatun Chasanah Vico Tegar Rawo Wijoyo Widuri Octavianunisa Wijayanti, Lusi Salsabilla Yuni Furoida Maknuna Zafi, Ali Zahrotun Nisa Zamani, Sevian Nadi Zufar Faiil Haq Zuhrotun Nisa