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All Journal Lontar Komputer: Jurnal Ilmiah Teknologi Informasi e-Jurnal Arus Elektro Indonesia Scientific Journal of Informatics ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika JURNAL NASIONAL TEKNIK ELEKTRO Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Jurnal Penelitian Pendidikan IPA (JPPIPA) Faktor Exacta Techne : Jurnal Ilmiah Elektroteknika Elektrika International Journal of New Media Technology MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer MIND (Multimedia Artificial Intelligent Networking Database) Journal KOMPUTIKA - Jurnal Sistem Komputer Applied Technology and Computing Science Journal Jurnal Teknologi Informasi dan Terapan (J-TIT) Dielektrika : Jurnal Ilmiah Kajian Teori dan Aplikasi Teknik Elektro JISA (Jurnal Informatika dan Sains) JTIULM (Jurnal Teknologi Informasi Universitas Lambung Mangkurat) Djtechno: Jurnal Teknologi Informasi Jurnal Ilmu Komputer dan Informatika Algoritme Jurnal Mahasiswa Teknik Informatika Jurnal Pengabdian Masyarakat Bangsa Jurnal Rekayasa elektrika Journal of Educational Engineering and Environment Jurnal ilmiah teknologi informasi Asia
Arizal Mujibtamala Nanda Imron
Teknik Elektro, Fakultas Teknik, Universitas Jember, Indonesia
Agriculture, Biological Sciences & Forestry Arts Humanities Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry 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 Health Professions Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Nursing Physics Public Health Social Sciences

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Identifikasi Penyakit Daun Jeruk Siam Menggunakan K-Nearest Neighbor Rifqi Hakim Ariesdianto; Zilvanhisna Emka Fitri; Abdul Madjid; Arizal Mujibtamala Nanda Imron
Jurnal Ilmu Komputer dan Informatika Vol 1 No 2 (2021): JIKI - Desember 2021
Publisher : CV Firmos

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (543.804 KB) | DOI: 10.54082/jiki.14

Abstract

Jeruk siam adalah salah satu jeruk local yang mempunyai nilai jual yang tinggi di Indonesia. Tahun 2020, tingkat produksi jeruk siam mengalami penurunan menjadi 712.585 ton di Jawa Timur. Salah satu faktor utama yang menyebabkan menurunnya tingkat produksi jeruk siam yaitu serangan penyakit pada daun jeruk siam. Dua penyakit yang sering menyerang daun jeruk siam adalah penyakit kanker yang disebabkan oleh patogen Xanthomonas axonopodis pv.citri dan penyakit ulat peliang. Selama ini, pengamatan pada penyakit daun jeruk siam dilakukan secara manual menggunakan mata sehingga penentuan penyakit tersebut bersifat subyektif. Untuk mengatasi masalah tersebut dibuatlah sistem otomatis identifikasi daun jeruk siam sehat dan daun jeruk siam terserang penyakit dengan bantuan teknik computer vision. Tahapan penelitian yaitu pengumpulan citra daun jeruk, konversi warna, ekstraksi fitur warna dan tekstur serta klasifikasi K-Nearest Neighbor (KNN). Parameter fitur yang digunakan yaitu fitur warna GB, fitur tekstur (ASM, entropi dan kontras). Metode KNN mampu mengklasifikasi dan mengidentifikasi penyakit daun jeruk siam dengan akurasi sebesar 70% dengan variasi nilai K = 21.
Klasifikasi Kerusakan Mutu Tomat Berdasarkan Seleksi Fitur Menggunakan K-Nearest Neighbor NISKE ELMY PAULINA; ZILVANHISNA EMKA FITRI; ABDUL MADJID; ARIZAL MUJIBTAMALA NANDA IMRON
MIND (Multimedia Artificial Intelligent Networking Database) Journal Vol 6, No 2 (2021): MIND Journal
Publisher : Institut Teknologi Nasional, Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26760/mindjournal.v6i2.144-154

Abstract

AbstrakTomat (Lycopersicum esculentum Mill.) merupakan satu komoditas unggulan pertanian karena penjualan jangka panjangnya baik. Menurunnya jumlah produktivitas dan mutu tomat disebabkan oleh curah hujan yang tinggi, cuaca dan budidaya yang tidak baik sehingga buah tomat menjadi busuk, retak, dan timbul bercak. Penyuluhan terkait peningkatan mutu tomat dinilai kurang efektif sehingga dibutuhkan sebuah sistem identifikasi kerusakan mutu buah tomat yang mampu memberikan edukasi kepada petani. Penelitian ini adalah pengembangan penelitian sebelumnya, untuk mendapatkan citra segmentasi dan ekstraksi fitur digunakan penggunaan contrast stretching dan deteksi tepi sobel. Namun kedua teknik tersebut diganti penggunaan operasi citra negatif. Didapatkan fitur yang optimal adalah gabungan fitur morfologi dan pada masing-masing sudut berdasarkan seleksi fitur. Persentasi akurasi metode KNN pada pelatihan sebesar 86.6% sedangkan akurasi pengujiannya sebesar 70%.Kata kunci: kerusakan mutu, tomat, seleksi fitur, K-Nearest NeighborAbstractTomato (Lycopersicum esculentum Mill.) is one of the leading agricultural commodities because of its good long-term sales. The decrease in the amount of productivity and quality of tomatoes is caused by high rainfall, bad weather and cultivation so that the tomatoes become rotten, cracked, and have spots. Counseling related to improving the quality of tomatoes is considered ineffective so that a system for identifying damage to the quality of tomatoes is needed that is able to provide education to farmers. This study is a development of previous research, to obtain segmented images and feature extraction using contrast stretching and sobel edge detection. However, both techniques were replaced by using negative image operations. The optimal feature is a combination of morphological features and correlations at each angle based on feature selection. The percentage of accuracy of the KNN method in training is 87%, while the accuracy in the testing is 70%.Keywords: quality damage, tomato, feature selection, K-Nearest Neighbo
Application of Feature Selection for Identification of Cucumber Leaf Diseases (Cucumis sativa L.) Lalitya Nindita Sahenda; Ahmad Aris Ubaidillah; Zilvanhisna Emka Fitri; Abdul Madjid; Arizal Mujibtamala Nanda Imron
JISA(Jurnal Informatika dan Sains) Vol 4, No 2 (2021): JISA(Jurnal Informatika dan Sains)
Publisher : Universitas Trilogi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31326/jisa.v4i2.1046

Abstract

According to data from BPS Kabupaten Jember, the amount of cucumber production fluctuated from 2013 to 2017. Some literature also mentions that one of the causes of the amount of cucumber production is disease attacks on these plants. Most of the cucumber plant diseases found in the leaf area such as downy mildew and powdery mildew which are both caused by fungi (fungal diseases). So far, farmers check cucumber plant diseases manually, so there is a lack of accuracy in determining cucumber plant diseases. To help farmers, a computer vision system that is able to identify cucumber diseases automatically will have an impact on the speed and accuracy of handling cucumber plant diseases. This research used 90 training data consisting of 30 healthy leaf data, 30 powdery mildew leaf data and 30 downy mildew leaf data. while for the test data as many as 30 data consisting of 10 data in each class. To get suitable parameters, a feature selection process is carried out on color features and texture features so that suitable parameters are obtained, namely: red color features, texture features consisting of contrast, Inverse Different Moment (IDM) and correlation. The K-Nearest Neighbor classification method is able to classify diseases on cucumber leaves (Cucumis sativa L.) with a training accuracy of 90% and a test accuracy of 76.67% using a variation of the value of K = 7. 
PENERAPAN ANALYTICAL HIERARCHY PROCESS UNTUK PEMILIHAN PAKET WEDDING ORGANIZER DI KABUPATEN JEMBER Zilvanhisna Emka Fitri; Arizal Mujibtamala Nanda Imron; Ulandari Susika; Yanuar Ridwan Hisyam
Jurnal Teknologi Informasi Universitas Lambung Mangkurat (JTIULM) Vol. 6 No. 2 (2021)
Publisher : Fakultas Teknik Universitas Lambung Mangkurat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20527/jtiulm.v6i2.81

Abstract

Persiapan pernikahan sering ditangani oleh jasa wedding organizer dan permasalahan yang terjadi adalah ketersediaan dana yang dimiliki oleh client sehingga akan mempengaruhi pemilihan paket pernikahan, lokasi dan tema pernikahan. Selama ini penyesuaian dana dan kebutuhan pernikahan dilakukan secara manual sehingga membuang waktu, tenaga dan kurang efisien bagi penyedia jasa wedding organizer. Untuk menyelesaikan permasalah tersebut maka dibuatlah sebuah sistem pen-dukung keputusan untuk pemilihan paket pernikahan pada Wedding Organizer di Kabupaten Jember dengan metode Analyti-cal Hierarchy Process (AHP). Berdasarkan hasil perhitungan, didapatkan bahwa kriteria dana memiliki bobot prioritas terbesar bila dibandingkan kriteria tamu undangan, lokasi pernikahan, tema pernikahan dan catering pernikahan. Bobot prioritas dari kriteria dana sebesar 0.335, kemudian kriteria dana tersebut dibandingkan dengan kriteria pemilihan paket wedding organizer. Hasil perhitungan dengan metode AHP didapatkan bahwa bobot prioritas terbesar pada kriteria Paket E Menengah yaitu 0.203, maka paket pernikahan yang direkomendasikan adalah Paket E Menengah dengan nilai consistency ratio (CR) sebesar 0.098.
Motorized Driving Safety System Using Eye Detection Analysis Method Sumardi Sumardi; Sudarti Sudarti; Wahyu Muldayani; Arizal Mujibtamala Nanda Imron
Jurnal Penelitian Pendidikan IPA Vol. 8 No. 3 (2022): July
Publisher : Postgraduate, University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jppipa.v8i3.1747

Abstract

Traffic accident, particularly two-wheeled vehicles, is a problem for the Government, especially the Resort Police Traffic Unit (Satlantas Polres). The factor that causes the traffic accident incident is divided into three types, namely human factor, vehicle factor, and road or environment factor. The human factor is the most common factor for an accident. Fatigue factor that causes someone to feel sleepy while driving often results in a traffic accident. Based on the problem, the researcher wanted to create a technology innovation of a motorized driving safety system in the form of a helmet. The researcher made an innovation of a helmet that can detect drowsiness through the driver's eye blink duration. The drowsiness will be detected by using a camera sensor. The camera sensor used was Open MV camera. The method used in detecting sleepy drivers was the eye detection analysis method. The method enable detection based on the data of the duration of eye condition when it is closed and open. The closed eye has a low RBG mean value of 110-113 and an RBG median value of 99-109. Whereas opened eye has a higher RGB mean value of 179-206 and RGB median value of 178-206. The result of the research showed that someone's sleepy condition occurred when closing their eyes for more than 0.4 seconds to 4 seconds. The helmet is also equipped with GPS to monitor the position in the event of an accident as an emergency response effort.
Blind Cane Using 2 Axis Servo with Fuzzy Logic Method Sumardi Sumardi; Sudarti Sudarti; Arizal Mujibtamala Nanda Imron; Wahyu Muldayani
Jurnal Penelitian Pendidikan IPA Vol. 8 No. 3 (2022): July
Publisher : Postgraduate, University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jppipa.v8i3.1748

Abstract

Based on data from the Ministry of Health and the Central Bureau of Statistics, it is known that the number of people with disabilities, especially the visually impaired, is 1-1.5% of the total 237 million Indonesian population, which is around 3.75 million blind people. A tool often used to accommodate them is a cane used to feel the ground if there are downgrade and obstructions in front of them. In this study, researchers developed the previous research on blind cane using a 2 axis servo. It was classified using the Fuzzy Logic programming method, which was processed using the Arduino Nano 328P microcontroller. The results of the test on respondents with visual impairments were that they feel accommodating with the tool because the cane users can easily find obstructions with the Navigation Instruction so that they can easily avoid Static obstructions (Static Objects).
Red Dragon Fruit (Hylocereus costaricensis) Ripeness Color Classification by Naïve Bayes Algorithm Zilvanhisna Emka Fitri; Mega Silvia; Abdul Madjid; Arizal Mujibtamala Nanda Imron; Lalitya Nindita Sahenda
TEKNOLOGI DITERAPKAN DAN JURNAL SAINS KOMPUTER Vol 5 No 1 (2022): June
Publisher : Universitas Nahdlatul Ulama Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33086/atcsj.v5i1.3690

Abstract

Dragon fruit is a unique fruit that is popular in Indonesia. besides having a sweet taste, this fruit also contains fiber, vitamins and minerals that are good for health. Dinas Pertanian Kabupaten Banyuwangi noted that the total dragon fruit production was 906,511.61 tons and the total productivity was 261.14 Kw/Ha in 2018. This shows that Kabupaten Banyuwangi is one of the largest producers of red dragon fruit in East Java Province. One of the problems in determining the quality of dragon fruit is choosing the harvest time, considering that dragon fruit is a non-climatic fruit. Non-climateric fruit is when we harvest fruit in its raw state, the fruit will never become ripe, so determining the harvest time for dragon fruit is very important. The determination made by paying discoloration and sizes of dragon fruit that is considered less effective. To overcome this, a system was created that was able to determine the level of dragon fruit maturity automatically by utilizing digital image processing techniques and intelligent systems. The parameters used are color features and GLCM texture features using angles 0°, 45°, 90° and 135° These features are parameters in the classification process using the Naïve Bayes method. Naïve bayes is able to classify the level of maturity of red dragon fruit (Hylocereus costaricensis) with an accuracy rate of 87.37%.
Perancangan Inverter Satu Fasa Berbasis Arduino Menggunakan Metode SPWM Lia Santoso; Arizal Mujibtamala Nanda Imron; Bambang Sri Kaloko
Techné : Jurnal Ilmiah Elektroteknika Vol. 22 No. 1 (2023)
Publisher : Fakultas Teknik Elektronika dan Komputer Universitas Kristen Satya Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31358/techne.v22i1.351

Abstract

Pada era berkembangnya teknologi saat ini, manusia tidak dapat terlepas dari kebutuhan energi listrik yang dapat menunjang pemakaian peralatan elektronik untuk setiap kegiatan rumah tangga maupun industri. Sebagian besar kebutuhan listrik memerlukan tegangan ac untuk mengidupkan peralatan listrik. Untuk tempat yang tidak terjangkau tegangan ac dapat menggunakan inverter sebagai alat konversi tegangan. Pada beberapa kasus, saat inverter melakukan konversi tegangan ditemukan beberapa kerusakan pada komponen dan penurunan kualitas output. Rancangan inverter pada paper ini menggunakan komponen yang menyesuaikan spesifikasi alat yang akan mengurangi timbulnya kerusakan pada rangkaian inverter. Arduino Nano digunakan sebagai pembangkit sinyal Pulse-Width Modulation (PWM). Penggunaan metode Sinusoidal Pulse-Width Modulation (SPWM) digunakan untuk menghasilkan tegangan dengan karakteristik gelombang sinus. Dari hasil yang didapatkan, inverter dapat bekerja dengan baik dan tidak mengalami kerusakan, namun output yang dihasilkan belum mencapai target spesifikasi, output tegangan dan arus yang dihasilkan memilki nilai kenaikan yang lebih stabil dan lebih tahan terhadap adanya tegangan jatuh.
A Combination of Forward Chaining and Certainty Factor Methods for Early Detection of Fever : Dengue Hemorrhagic Fever, Malaria and Typhoid Fitri, Zilvanhisna Emka; Ramadania, Elsa Manora; Wibowo, Nugroho Setyo; Lesmana, I Putu Dody; Imron, Arizal Mujibtamala Nanda
Scientific Journal of Informatics Vol 9, No 1 (2022): May 2022
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v9i1.33007

Abstract

Abstract. Purpose: Dengue Hemorrhagic and Malaria fevers are the most common arthropod-borne diseases caused by mosquito bites and they also have similar signs and symptoms. Based on the problems, the researcher makes an expert system that aims to help people early detect fever diseases. This system is expected to help and support the infectious disease prevention and control program by the Ministry of Health of the Republic of Indonesia.Methods: This study uses an expert system with a combination of Forward Chaining and Certainty Factor to detect the symptoms of fever. Forward Chaining is a technique that begins with gathering information related to known facts, then combining rules to produce conclusions. The certainty Factor method is used to define a measure of certainty against a fact or rule and to describe the level of expert confidence in dealing with problems. There are 32 symptoms of the disease consisting of dengue fever, malaria and typhoid, it was obtained based on the literature and interviews with internal medicine specialist with 20 case datasets.Result: Based on 20 test data, obtained one data that does not match the test results and the desired target so that the system accuracy obtained is 95%. In addition, the combination of Forward Chaining and Certainty factor has better accuracy when compared to expert systems in previous studies.Novelty: Forward Chaining to find three rules and assigning weights to the Certainty Factor that has been set by the expert makes the combination of the two methods produce better accuracy.
Comparison of Neural Network Methods for Classification of Banana Varieties (Musa paradiasaca) Zilvanhisna Emka Fitri; Wildan Bakti Nugroho; Abdul Madjid; Arizal Mujibtamala Nanda Imron
Jurnal Rekayasa Elektrika Vol 17, No 2 (2021)
Publisher : Universitas Syiah Kuala

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (411.849 KB) | DOI: 10.17529/jre.v17i2.20806

Abstract

Every region in Indonesia has a very large diversity of banana species, but no system records information about the characteristics of banana varieties. The purpose of this research is to make an encyclopedia of banana types that can be used for learning by classifying banana varieties using banana images. This banana variety classification system uses image processing techniques and artificial neural network methods as classification methods.The varieties of bananas used are pisang merah, pisang pisang mas kirana, pisang klutuk, pisang raja and pisang cavendis. The parameters used are color features (Red, Green, and Blue) and shape features (area, perimeter, diameter, and length of fruit). The intelligent system used is the Backpropagation method and the Radial Basis Function Neural Network. The results showed that both methods were able to classify banana varieties with an accuracy rate of 98% for Backpropagation and 100% for the Radial Basis Function Neural Network.
Co-Authors Abdul Madjid ABDUL MADJID Abdul Madjid Abdul Madjid Abdul Madjid Abdul Madjid Abdul Madjid Ahmad Aris Ubaidillah Ainun Nurkharima Noviana Ali Rizal Chaidir Anam, M. Khairul Ari Baskara Atmadji, Ery Setiyawan Jullev Atmadji, Ery Setiyawan Jullev Bahtiar Adi Prasetya Bambang Sri Kaloko Bambang Sujanarko Brilyan Andi Syahbana Brilyan Andi Syahbana Candra Putri Rizkiyah Ramadhani Dananjaya Endi Pratama Dyah Laksito Rukmi Erwinda, Yudha Teja Faisal Alif Hidayat Fitri, Zilvanhisna Emka Fitri, Zilvanhisna Emka Guido Dias Kalandro I Putu Dody Lesmana Immawan Wicaksono Intan Permatasari Irawan, Ahmad Dandi KOMARIAH, SITI INGEFATUL Lalitya Nindita Sahenda Lia Santoso Mega Silvia NISKE ELMY PAULINA Nugroho Setyo Wibowo Panji Eka Prasetya Parahita, Syavina Octavia Pramuditha Shinta Dewi Puspitasari Prawidya Destarianto Putri, Desti Fitri Aisyah PUTRI, DESTI FITRI AISYAH Rahmawati, Siska Yulia Ramadania, Elsa Manora Reski Yulina Widiastuti, Reski Yulina Rifqi Hakim Ariesdianto Riska Aprilia Rizkiyah Rizkiyah Slamet Riyadi Sudarti Sudarti Sulton Mubarok Sulton Mubarok Sumardi . Sumardi Sumardi Syahputri, Lindri Nalentine Yolanda Ulandari Susika Ully Nuhanatika Wahyu Muldayani Widiastuti, Reski Yulina Widjonarko . Widyono Hadi Wildan Bakti Nugroho Yanuar Ridwan Hisyam Zilvanhisna Emka Fitri Zilvanhisna Emka Fitri