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All Journal International Journal of Electrical and Computer Engineering IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Seminar Nasional Aplikasi Teknologi Informasi (SNATI) Majalah Ilmiah Teknologi Elektro Jurnal INKOM Jurnal Simetris Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) Prosiding Seminar Nasional Sains Dan Teknologi Fakultas Teknik Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Jurnal Teknologi JURNAL ELEKTRO International Journal of Advances in Intelligent Informatics Majalah Ilmiah MOMENTUM ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika JOIV : International Journal on Informatics Visualization Jurnal Elementer (Elektro dan Mesin Terapan) JMM (Jurnal Masyarakat Mandiri) KACANEGARA Jurnal Pengabdian pada Masyarakat Jurnal Inovasi Hasil Pengabdian Masyarakat (JIPEMAS) MIND (Multimedia Artificial Intelligent Networking Database) Journal JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) TEKTRIKA - Jurnal Penelitian dan Pengembangan Telekomunikasi, Kendali, Komputer, Elektrik, dan Elektronika Journal of Electronics, Electromedical Engineering, and Medical Informatics Jurnal Teknologi Informasi dan Multimedia JMECS (Journal of Measurements, Electronics, Communications, and Systems) Indonesian Journal of electronics, electromedical engineering, and medical informatics Journal of Applied Engineering and Technological Science (JAETS) Indonesian Journal of Electrical Engineering and Computer Science Aiti: Jurnal Teknologi Informasi Prosiding Konferensi Nasional PKM-CSR INTECH (Informatika dan Teknologi) Jurnal Nasional Teknik Elektro dan Teknologi Informasi eProceedings of Engineering Community Service Seminar and Community Engagement (COSECANT) Indonesian Journal of Electronics, Electromedical Engineering, and Medical Informatics
Achmad Rizal
Telkom University
Humanities 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 Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mechanical Engineering Nursing Public Health Social Sciences Other

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PEMENUHAN KEBUTUHAN MEDIA PEMBELAJARAN DI SEKOLAH ALAM DENGAN MENGIMPLEMENTASIKAN SISTEM PEMANTAUAN KOLOM IKAN DI BEBERAPA TITIK BERBASIS IOT Istiqomah Istiqomah; Arif Abdul Aziz; Achmad Rizal; Muhammad Fahriza Bahrudin; Soediponegoro Soediponegoro; Azriansyah Azriansyah; Achmad Ibnu Abas; Muhammad Yusuf Salman
JMM (Jurnal Masyarakat Mandiri) Vol 7, No 4 (2023): Agustus
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jmm.v7i4.16318

Abstract

Abstrak: Di sekolah alam process pembelajaran mengedepankan interaksi dengan alam. Terkadang sekolah alam memiliki beberapa fasilitas sebagai media pembelajaran yang berhubungan dengan alam seperti kolam. Tidak terkecuali di Sekolah Alam Gaharu sebagai mitra di pengambdian masyarakat ini. Sekolah Alam Gaharu yang memiliki beberapa kolam ikan yang digunakan untuk fasilitas observasi alam. Untuk mempermudah fasilitas tersebut digunakan sebagai media pembelajaran, Sekolah Alam Gaharu membutuhkan satu sistem pemantauan semua kolam dan media belajar. Oleh karena itu, untuk memenuhi kebutuhan tersebut, dikembangkan satu sistem pemantauan kolam ikan dibeberapa titik untuk parameter keasaman dan temperature air kolam yang terintegrasi oleh satu sistem IoT. Sistem yang diterapkan sebagai solusi di Sekolah Alam Gaharu adalah dua sensor node yang digunakan untuk mengakuisisi data PH dan temperatur dan satu sistem gateway sebagai sistem integrasi kedalam satu sistem IoT. Kemudia semua parameter PH dan temperatur kolam dapat dipantau di aplikasi android. Untuk mengetahui apakah sistem berjalan sesuai kebutuhan Sekolah Alam Gaharu, dilakukan survei umpan balik ke guru sekolah tersebut. Dari Umpan balik yang dilakukan ke lima belas guru, didapatkan respon bahwa seluruh guru sangat setuju bahwa semua komponen sistem yang telah diimplementasikan sangat membantu dalam process pembelajaran. Seluruh responden menyatakan sangat setuju 100% bahwa sistem mampu membantu process pembelajaran di Sekolah Alam Gaharu. Abstract: In natural schools, the learning process emphasizes interaction with nature. Sometimes natural schools have several facilities as learning media related to nature, such as ponds. Gaharu Natural School is no exception as a partner in this community service. Gaharu Nature School has several fish ponds used as natural observation facilities. Gaharu Natural School requires a monitoring system for all ponds and learning media to make it easier for these facilities to be used as learning media. Therefore, to meet these needs, a fish pond monitoring system has been developed at several points for the parameters of acidity and pond water temperature, which are integrated by an IoT system. The system implemented as a solution at the Gaharu Natural School is two sensor nodes used to acquire PH and temperature data and a gateway system as an integration system into an IoT system. Then all PH and pool temperature parameters can be monitored in the Android application. A feedback survey was conducted on the school's teachers to determine whether the system is running according to the needs of the Gaharu Natural School. From the feedback provided to the fifteen teachers, the responses were obtained that all teachers strongly agreed that all the components of the system that had been implemented were very helpful in the learning process. All respondents strongly agreed 100% that the system could assist the learning process at Gaharu Natural School. 
Pengenalan Individu Berdasarkan Gait Menggunakan Sensor Giroskop Muhammad Satya Annas; Achmad Rizal; Ratri Dwi Atmaja
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 6 No 2: Mei 2017
Publisher : Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1112.465 KB)

Abstract

Every persons have their own unique way of walking which is called gait. Gait can be used to identify a person. Gyroscope is a sensor used to detect vibration and measure acceleration based on direction or orientation. This paper presents an individual recognition based on gait using gyroscope sensor embedded in smartphone. The gait data is processed and analyzed by implementing Linear Predictive Coding (LPC) and k-Nearest Neighbour (k-NN). LPC is used to extract features from gait data. It produces feature vector based on combination of p-previous signal and takes only important value of the feature data. Then, k-NN is used for classification, using some calculation methods such as Euclidean, Cityblock, Cosine, and Correlation distance. The gait signals contain x,y,z axis and the signal magnitude. In this paper x,y,z axis and the signal magnitude are also combined to improve the accuracy. The highest accuracy of 99.58% is achieved using signal combination x-y-z-m. Overall, this person detection system produces accuracy between 50% to 99.58%.
Heart Disease Prediction based on Physiological Parameters Using Ensemble Classifier and Parameter Optimization Agung Muliawan; Achmad Rizal; Sugondo Hadiyoso
Journal of Applied Engineering and Technological Science (JAETS) Vol. 5 No. 1 (2023): Journal of Applied Engineering and Technological Science (JAETS)
Publisher : Yayasan Riset dan Pengembangan Intelektual (YRPI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37385/jaets.v5i1.2169

Abstract

This study describes the prediction of heart disease using ensemble classifiers with parameter optimization. As input, a public dataset was taken from UCI machine learning repository, which refers to the dataset at UCI Machine learning. The dataset consists of 13 variables that are considered to influence heart disease. Particle swarm optimization (PSO) was used for feature selection and principal component analysis (PCA) for feature extraction to reduce the features' dimensions. The application of parameter optimization on several machine learning methods such as SVM (Radial Basis Function), Deep learning, and Ensemble Classifier (bagging and boosting) to get the highest accuracy comparison. The results of this study using PSO dimensionality reduction in the public dataset of heart disease resulted in the slightest accuracy compared to PCA. In contrast, the highest accuracy was obtained from optimizing Deep Learning parameters with an accuracy of 84.47% and optimization of SVM RBF parameters with an accuracy of 83.56%. The highest accuracy in the ensemble classifier using bagging on SVM of 83.51%, with a difference of 0.5% from SVM without using bagging.  
Pengoptimalan Potensi Wisata di Desa Laksana Melalui Pelatihan Pembuatan Paket Wisata Priharti, Wahmisari; Rahmawati, Dien; Rizal, Achmad; Aziz, Burhanuddin
Prosiding Konferensi Nasional Pengabdian Kepada Masyarakat dan Corporate Social Responsibility (PKM-CSR) Vol 6 (2023): INOVASI PERGURUAN TINGGI & PERAN DUNIA INDUSTRI DALAM PENGUATAN EKOSISTEM DIGITAL & EK
Publisher : Asosiasi Sinergi Pengabdi dan Pemberdaya Indonesia (ASPPI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37695/pkmcsr.v6i0.1938

Abstract

Desa Laksana telah dinobatkan menjadi salah satu desa wisata di Kabupaten Bandung sejak 2011. Akan tetapi, hingga saat ini, geliatnya sebagai desa wisata belum terlalu ketara meskipun memiliki potensi wisata yang memadai. Salah satu kendalanya adalah kurangnya organisasi serta pemasaran yang baik terkait informasi mengenai objek wisata yang ada di desa ini. Untuk mengatasi permasalahan ini, tim dosen Telkom University mengadakan suatu pelatihan terkait pembuatan paket wisata yang dibungkus sebagai kegiatan pengabdian masyarakat. Pada pelatihan ini, disampaikan kepentingan membuat paket wisata, komponen, strategi serta best practice yang diperlukan untuk menghasilkan paket wisata. Berdasarkan survey dari pelatihan ini, peserta sangat antusias dan berharap kegiatan serupa dapat dilanjutkan dan ditambah durasinya. Selain itu, pada pelatihan ini juga disosialisasikan aplikasi wisata yang dapat digunakan untuk mempromosikan paket wisata ini. Diharapkan dari kegiatan ini, akan muncul paket-paket wisata yang dapat menarik lebih banyak wisatawan dan secara tidak langsung meningkatkan ekonomi masyarakat Desa Laksana.
Comparison of the Adaboost Method and the Extreme Learning Machine Method in Predicting Heart Failure Muhammad Nadim Mubaarok; Triando Hamonangan Saragih; Muliadi; Fatma Indriani; Andi Farmadi; Rizal, Achmad
Journal of Electronics, Electromedical Engineering, and Medical Informatics Vol 6 No 3 (2024): July
Publisher : Department of Electromedical Engineering, POLTEKKES KEMENKES SURABAYA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35882/jeeemi.v6i3.440

Abstract

Heart disease, which is classified as a non-communicable disease, is the main cause of death every year. The involvement of experts is considered very necessary in the process of diagnosing heart disease, considering its complex nature and potential severity. Machine Learning Algorithms have emerged as powerful tools capable of effectively predicting and detecting heart diseases, thereby reducing the challenges associated with their diagnosis. Notable examples of such algorithms include Extreme Learning Machine Algorithms and Adaptive Boosting, both of which represent Machine Learning techniques adapted for classification purposes. This research tries to introduce a new approach that relies on the use of one parameter. Through careful optimization of algorithm parameters, there is a marked improvement in the accuracy of machine learning predictions, a phenomenon that underscores the importance of parameter tuning in this domain. In this research, the Heart Failure dataset serves as the focal point, with the aim of demonstrating the optimal level of accuracy that can be achieved through the use of Machine Learning algorithms. The results of this study show an average accuracy of 0.83 for the Extreme Learning Machine Algorithm and 0.87 for Adaptive Boosting, the standard deviation for both methods is “0.83±0.02” for Extreme Machine Learning Algorithm and “0.87±0.03” for Adaptive Boosting thus highlighting the efficacy of these algorithms in the context of heart disease prediction. In particular, entering the Learning Rate parameter into Adaboost provides better results when compared with the previous algorithm. Our research findings underline the supremacy of Extreme Learning Machine Algorithms and Adaptive Improvement, especially when combined with the introduction of a single parameter, it can be seen that the addition of parameters results in increased accuracy performance when compared to previous research using standard methods alone.
PENERAPAN PANEL SURYA SEBAGAI MEDIA PEMBELAJARAN ENERGI TERBAHARUKAN DAN ENERGI LISTRIK TAMBAHAN DI SEKOLAH ALAM GAHARU Istiqomah Istiqomah; Arif Abdul Aziz; Achmad Rizal; Muhammad Fahriza Bahrudin; Soediponegoro Soediponegoro; Azriansyah Azriansyah; Naufal Widad Sundawa; Abdillah Nur Isnaini; Vincentius Adisurya Fransisco Antu
JMM (Jurnal Masyarakat Mandiri) Vol 8, No 2 (2024): April
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jmm.v8i2.21562

Abstract

Abstrak: Sekolah Alam mengedepankan alam sebagai aspek utama objek pembelajaran, sehingga kewajiban menjaga alam menjadi hal penting untuk diajarkan ke peserta didik. Salah satu upaya untuk menjaga alam adalah dengan menggunakan energi baru dan terbarukan sebagai alternatif energi bersih. Sehingga hal tersebut menjadi misi yang sedang digiatkan di Sekolah Alam Gaharu. Pada pelaksanaan kegiatan pengabdian masyarakat ini, tim berusaha memenuhi kebutuhan sekolah alam yaitu penerapan EBT berupa panel surya sebagai media pembelajaran dan energi listrik tambahan untuk kegiatan outdoor di sekolah alam tersebut. EBT yang diterapkan adalah panel surya yang kiranya mudah dirancang menyesuaikan kebutuhan Sekolah Alam Gaharu. Panel surya yang menghasilkan listrik DC diintegrasikan dengan sistem lain seperti Aki dan inventer DC ke AC agar catu daya bisa langsung digunakan perangkat elektronik di Sekolah Alam Gaharu. Diharapkan kegiatan masyarakat ini menjadi media pembelajaran EBT di Sekolah Alam Gaharu. Diakhir kegiatan akan ada survei kepada 15 guru di Sekolah Alam Gaharu untuk melihat keefektifan penerapan panel surya sebagai media pembelajaran di sekolah alam. Dari hasil survei yang dilakukan tersebut disimpulkan 100% kegiatan memenuhi kebutuhan dari Sekolah Alam Gaharu.Abstract: The Nature School prioritizes nature as the main aspect of learning objects, so the obligation to protect nature is an important thing to teach to students. One effort to protect nature is to use new and renewable energy as a clean energy alternative. So this has become a mission that is being carried out at the Gaharu Nature School. In carrying out this community service activity, the team tried to meet the needs of the natural school, namely the application of new renewable energy in the form of solar panels as a learning medium and additional electrical energy for outdoor activities at the natural school. The new renewable energy implemented is solar panels which can be easily designed to suit the needs of the Gaharu Nature School. Solar panels that produce DC electricity are integrated with other systems such as batteries and DC to AC inverters so that the power supply can be directly used by electronic devices at Alam Gaharu School. It is hoped that this community activity will become a medium for new renewable energy learning at Gaharu Nature School. At the end of the activity there will be a survey of 15 teachers at Gaharu Nature School to see the effectiveness of implementing solar panels as a learning medium in natural schools. From the results of the survey conducted, it was concluded that 100% of the activities met the needs of the Gaharu Nature School.
PELATIHAN PEMILAHAN SAMPAH PADA USIA DINI DI JAWA BARAT Muhammad Fahriza Bahrudin; Rifka Aulia Natasya; Fahira Deviana Putri Pasaribu; Aura Awaliani Puteri; Raudhatul Jannah; Andi Arini Hidayanti; Fadhlul Amar; Achmad Rizal; Istiqomah Istiqomah
JMM (Jurnal Masyarakat Mandiri) Vol 8, No 2 (2024): April
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jmm.v8i2.21889

Abstract

Abstrak: Pelatihan pemilahan sampah menjadi salah satu cara untuk menuju gerakan zero waste, dengan pemberian pelatihan ini sejak usia dini dapat menumbuhkan kepekaan para siswa terhadap pentingnya menjaga lingkungan. Pengabdian masyarakat ini bertujuan untuk memberikan pelatihan pemilahan sampah kepada siswa kelas 3 Madrasah Ibtidaiyah yang berjumlah 20 siswa di Sekolah Alam Gaharu sebagai mitra pada pengabdian masyarakat ini, dimana sekolah Alam Gaharu menerapkan konsep sekolah alam yang berarti pembelajaran berorientasi pada alam. Sesuai dengan visi sekolah yang dapat memberikan mafaat bagi masyarakat maka salah satunya yaitu dengan menerapkan sekolah zero waste dan sebagai langkah awal penerapan yaitu dengan pembelajaran pemilahan sampah. Pelatihan dilaksanakan melalui penyampaian materi, permainan, dan daur ulang sampah plastik. Pelatihan ini juga dapat meningkatkan kemampuan softskill yaitu meningkatkan kerjasama tim para siswa, serta melatih kreativitas para siswa dalam mendaur ulang sampah. Evaluasi dilakukan melalui survei terhadap guru dengan pertanyaan terkait manfaat, pemahaman siswa, penerapan 3R, dan dampak pelatihan. Hasil menunjukan bahwa 100% responden menyatakan pelatihan bermanfaat, siswa dapat memahami materi, dan mampu melakukan 3R. Pelatihan juga memberikan dampak signifikan dalam pembelajaran siswa.Abstract: Training on waste sorting is one of the ways to promote the zero-waste movement, and providing this training from an early age can cultivate awareness among students about the importance of environmental conservation. Community service in this regard aims to provide waste sorting training to 20 third-grade students at Gaharu Nature School as partners in this community service initiative. Gaharu Nature School adopts the concept of nature-based education, where learning is oriented towards nature. Aligned with the school's vision of benefiting the community, one of its initiatives is to implement a zero-waste school model, with waste sorting education being the initial step. The training is conducted through lectures, games, and plastic waste recycling activities. This initiative also enhances students' soft skills by fostering teamwork and nurturing creativity in waste recycling endeavors. Evaluation is carried out through surveys administered to teachers, focusing on the benefits, students' comprehension, implementation of the 3Rs (Reduce, Reuse, Recycle), and the overall impact of the training. Results indicate that 100% of respondents affirm the beneficial nature of the training, stating that students grasp the material well and are capable of practicing the 3Rs. Moreover, the training has shown significant positive impacts on student learning. 
Selection EEG Electrode Positions for Epilepsy Seizure Detection Using Total Power Spectrum and Machine Learning Afifah, Khilda; Istiqomah, Istiqomah; Rizal, Achamd; Nugraha, Ramdhan
Indonesian Journal of Electronics, Electromedical Engineering, and Medical Informatics Vol. 6 No. 4 (2024): November
Publisher : Jurusan Teknik Elektromedik, Politeknik Kesehatan Kemenkes Surabaya, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35882/ijeeemi.v6i4.9

Abstract

Detecting epileptic seizures poses significant challenges due to the complex and variable nature of EEG signals, particularly when aiming for implementation in wearable devices. The use of 64-channel EEG electrodes, while comprehensive, is impractical for wearable applications due to their size, cost, and the high computational load required for processing. The use of a single-channel EEG wearable device offers notable advantages, including reduced size and cost, making it more practical and comfortable for continuous monitoring in daily life. Additionally, the lower computational load enhances battery life and allows for real-time data processing, which is critical for timely seizure detection and intervention. This research investigates the detection of epileptic seizures using various machine learning algorithms and the power spectrum feature extraction method from EEG signals, aiming for application in wearable devices with a single-channel electrode. The study applied random forest (RF), K-nearest neighbor (KNN), decision tree (DF), support vector mechine (SVM), and logistic regression algorithms to assess their effectiveness. Results revealed that the power spectrum extraction method notably improved seizure detection accuracy, with RF and KNN achieving 93% and 92% accuracy respectively when using all EEG channels. When limited to a single channel, SVM demonstrated the highest accuracy of 82% with channel 3. These findings underscore the efficacy of the power spectrum method for EEG signal processing, providing significant improvements in accuracy and computational efficiency. The study concludes that the proposed approach is promising for enhancing epileptic seizure detection, suggesting further optimization for real-time application in wearable devices to develop accurate and efficient diagnostic tools.
Combination of Multidistance Signal Level Difference and Time Domain Features for Epileptic Seizure Classification Amalia, Qoriina Dwi; Beu, Donny Setiawan; Rizal, Achmad; Ziani, Said
JOIV : International Journal on Informatics Visualization Vol 9, No 2 (2025)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.9.2.2692

Abstract

Epileptic seizures are neurological disorders characterized by abnormal electrical activity in the brain, causing a series of seizures or episodes of temporary loss of consciousness. This research aims to develop a method of detecting and classifying epileptic seizures using one-dimensional EEG signals with the Multidistance Signal Level Difference (MSLD) approach and time domain feature extraction. The goal is to improve accuracy in distinguishing normal, interictal, and ictal conditions in EEG signals. The dataset from Bonn University consists of one-dimensional EEG signals that include normal, interictal, and ictal states. The analysis method includes extracting time domain features from EEG signals, such as Integrated EMG (IEMG), Mean Absolute Value (MAV), and others. The next step is the application of three classification algorithms, namely linear SVM, quadratic SVM, and cubic SVM, to classify the three conditions. Testing is done by measuring the accuracy of the classification results. The results of this study show that by using 14-time domain features and the MSLD approach, the most significant classification accuracy achieved was 98.7%. This result demonstrates the effectiveness of the proposed method in distinguishing normal, interictal, and ictal conditions. This research provides a foundation for further study in developing EEG signal classification analysis models. Future research can expand the scope by considering larger datasets, using more sophisticated feature extraction techniques, and exploring more complex classification algorithms to improve the accuracy and reliability of the model in real-world applications, particularly in the medical field for the diagnosis of epileptic seizures.
Rancang Bangun Alat Ukur Kelembaban, pH, Suhu, dan NPK (Natrium, Phospat, Kalium) Pada Tanah Menggunakan Wireless Sensor Network Aditya, Muhammad Billy; Wibawa, IG. Prasetya Dwi; Rizal, Achmad
eProceedings of Engineering Vol. 12 No. 3 (2025): Juni 2025
Publisher : eProceedings of Engineering

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

Abstract

Abstrak — Penelitian ini bertujuan untuk merancangsuatu alat yang dapat mengukur kandungan pada tanah sepertikelembaban, suhu, pH, dan NPK (Nitrogen, Fosfor, Kalium).Alat ini dapat membantu para petani dalam memberikaninformasi mengenai kondisi tanah dalam pengelolaan lahanpertanian mereka. Perancangan alat ini menggunakanbeberapa sensor untuk mengukur kandungan pada tanah yaitu,sensor SEN0193, sensor DS18B20, sensor pH Tanah, dan sensorNPK. sensor tersebut mendeteksi kandungan hara yang adapada tanah dan menampilkan secara real time pada LCD danakan dikirim ke cloud untuk melakukan monitoring jarak jauhsecara real time. Kalibrasi dari tiap sensor pada alat inidilakukan untuk memastikan tingkat akurasi pengukuran danmenghasilkan nilai R2 mendekati 1 yang menandakan bahwamodel regresi yang digunakan memiliki efektivitas yang cukupbesar. Nilai perhitungan RMSE pada sensor kelembabanSEN0193 menunjukkan nilai sebesar 0.82356. Pada sensor Lalupada sensor DS18B20 hasil dari perhitungan RMSE bernilai2.1. Selanjutnya pada sensor pH Tanah hasil yang didapatkandalam perhitungan RMSE sebesar 0.2. Pembacaan kadarnitrogen pada sensor NPK memiliki nilai R2 sebesar 0.9988sedangkan dalam pembacaan kadar fosfor nilai yangdidapatkan dalam perhitungan RMSE sebesar 0.9997. Lalupada pembacaan kadar kalium memiliki R2 sebesar 0.9985.Proses pengujian pada alat ini menunjukkan bahwa sensorresponsif dalam pembacaan saat melakukan pengukurankandungan pada tanah. Informasi yang didapat dari alatdiharapkan dapat membantu para petani maupun masyarakatdalam pengambilan keputusan yang bijak dalam pengelolaanlahan pertanian. Kata kunci— Kualitas Tanah, Root Mean Square Error,Sensor NPK, Sensor SEN0193, Sensor DS18B20
Co-Authors Abdillah Nur Isnaini Achmad Ibnu Abas Aditya, Muhammad Billy Agung Muliawan Agung Surya Wibowo Agustina Trifena Dame.S Akhmad Alfaruq Alfian Akbar Gozali Alvin Oktarianto Alvy Suhandi Nataprawira Amalia, Qoriina Dwi Andi Arini Hidayanti Andi Farmadi Andi Wahyu Adi Arryansyah Andjar Pudji Andro Harjanto Anggit Syorgaffi Anita Miftahul Maghfiroh Arif Abdul Aziz Arifah Putri Caesaria Aura Awaliani Puteri Aurick Daffa Muhammad Ayu, Devina Dara Aziz, Burhanuddin Azriansyah Azriansyah Azriansyah Azriansyah Bambang Guruh Irianto Bambang Hidayat Bandiyah Sri Aprillia Bella Fatonah Nur Anisya Beu, Donny Setiawan Bhagas Nugroho Brahmantya Aji Pramudita Burhanuddin Aziz Chandra Purna Darmawan Chandraditya Aridela Deni Saepudin Deny Sugiarto Wiradikusuma Desri Kristina Silalahi Devi Anggraini Dien Rahmawati Djoko Kurnia Putra Dyah Ayu Pratiwi Eka Nuryanto Budi Susila Elfrida Ratnawati Ellia Nurazizah Endro Yulianto Enzel D. S. Situmorang Estananto Fadhlul Amar Fadlillah Muharam Saeful Fahira Deviana Putri Pasaribu Fajra Octrina Faqih Alam FARDAN FARDAN Fathul Fajar Fatma Indriani FAUZI FRAHMA TALININGSIH Fiky Y. Suratman Fively Darmadi Freyssenita Kanditami P Hanan, Hafizh Khoirul Hanung Adi Nugroho Hanung Tyas Saksono Hasbian Fauzi Perdana Hezron Eka Lattang Hilman Fauzi, Hilman I Nyoman Apraz Ramatryana Ig. Prasetya Dwi Wibawa Ilham Edwian Berliandhy Ilham Rabbani Des Chandra Aziz Inung Wijayanto Istiqomah Istiqomah Istiqomah Istiqomah Istiqomah Istiqomah Iswahyudi Hidayat Jafar Hifdzullisan Jatmiko Kuntoro Nugroho Jidan Sandika Hidayat Jondri Jondri Junartho Halomoan Khilda Afifah Koredianto Usman La Bamba Puang P T S Kami Lestari, Rahma Dania Aleem Liliek Soetjiatie M. Ary Murti Mazaya 'Aqila Meidiana Ajeng Lestari Mohamad Ramdhani Mohamad Sofie Mohamad Sofie Mohamad Sofie, Mohamad MUHAMMAD ADNAN PRAMUDITO Muhammad Afif Ridwansyah Muhammad Al Makky Muhammad Ary Murti Muhammad Fahriza Bahrudin Muhammad Fahriza Bahrudin Muhammad Hablul Barri Muhammad Hasbi Ashshiddieqy MUHAMMAD JULIAN, MUHAMMAD Muhammad Nadim Mubaarok Muhammad Nashih Rabbani Muhammad Rafiqy Zulfahmi Muhammad Ridha Makruf Muhammad Satya Annas Muhammad Thariq Machaz Muhammad Yusuf Salman Muliadi Naufal Widad Sundawa Ni Wayan Ratna Juami Novi Prihatiningrum Nur Afifah Nuril Hidayanti Nurina Listya Hakim Nursanto Nursanto NURSANTO NURSANTO, NURSANTO Nurul Fathanah Muntasir Philip Tobianto Daely Purba Daru Kusuma Putri Famela Azhari R. Yunendah Nur Fu’adah Radian Sigit Raditiana Patmasari Ramdhan Nugraha Ratri Dwi Atmaja Raudhatul Jannah Reza Budiawan, Reza Rheza Faurizki Rahayu Rifka Aulia Natasya Risanuri Hidayat Rita Magdalena Rizkia Dwi Auliannisa Ruri Octari Dinata Sang Made Lanang Prasetya Sania Marcellina Bryan Saragih, Triando Hamonangan Sari Luthfiyah Sigit, Radian Soediponegoro Soediponegoro Soediponegoro Soediponegoro Sofia Naning Hertiana Sony Sumaryo Sugondo Hadiyoso Suryani Alifah Suryo Wibowo Syamsul Rizal Tedy Gumilang Sejati Triwiyanto Triwiyanto Unang Sunarya Vania Rei Syifa Vera Suryani Viko Adi Rahmawan Vincentius Adisurya Fransisco Antu Wahmisari Priharti Widiawan, Babel Willy Anugrah Cahyadi Wisudantyo Wahyu Priambodo, Wisudantyo Wahyu YULI SUN HARIYANI Ziani Said Ziani, Said