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All Journal Jurnal Simantec Jurnal SOLMA Jurnal Sisfokom (Sistem Informasi dan Komputer) Jurnal ULTIMATICS Jurnal ULTIMA Computing JURIKOM (Jurnal Riset Komputer) Al-Khidmat : Jurnal Ilmiah Pengabdian Kepada Masyarakat Generation Journal Indonesian Community Journal Eduvest - Journal of Universal Studies Jurnal Informatika Polinema (JIP) Merkurius: Jurnal Riset Sistem Informasi dan Teknik Informatika INOVTEK Polbeng - Seri Informatika Almantiq
Jauhar Vikri, Muhammad
Universitas Nahdlatul Ulama Sunan Giri
Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Library & Information Science Neuroscience Public Health Social Sciences Other

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Absensi Berbasis Pengenalan Wajah Dengan Pendekatan Dua Dimensi Principal Component Analysis (2DPCA) Fitri Damayanti; Ahmad Sahru Romadhon; Muhammad Jauhar Vikri
Jurnal Simantec Vol 1, No 2 (2010): Juni
Publisher : Universitas Trunojoyo Madura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21107/simantec.v1i2.13367

Abstract

Dynamic Ultrasonic Wave Generators as an Alternative Technology to Field Rat Repellents Muhammad Jauhar Vikri; Roihatur Rokhmah
Ultima Computing : Jurnal Sistem Komputer Vol 14 No 2 (2022): Ultima Computing : Jurnal Sistem Komputer
Publisher : Faculty of Engineering and Informatics, Universitas Multimedia Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31937/sk.v14i2.2838

Abstract

The case of crop failure caused by pest attacks is one of the problems in agriculture that is always interesting to study. Apart from weather factors, pest attacks on rice and corn agricultural commodities often occur just before harvest time. Currently, farmers often use toxic materials and even electricity as a means to repel and eradicate rat pests. However, this method can be dangerous for the farmers themselves. There have even been several cases of death due to electrical equipment installed in agricultural areas. Based on these problems, a pest repellent will be made by utilizing ultrasonic waves from a solar-powered power source so that it can be used efficiently, practically and safely. This tool is built using IC NE556C, Solar Panel, LDR Sensor (Light Dependent Resistor), and Ultrasonic Piezo PTC 4000 Speaker. IC NE556C timer and ultrasonic wave multivibrator are used to generate ultrasonic waves randomly according to the program. The purpose of making this tool is as an alternative to field mouse pest repellent using ultrasonic waves by utilizing solar energy in handling pests in agricultural areas.
SOSIALISASI PENERAPAN BERMEDIA INTERNET UNTUK ANAK USIA DINI PADA GURU DAN ORANG TUA DI RA AL FATHIMIYAH SUGIHWARAS BOJONEGORO Roihatur Rohmah; Muhammad Jauhar Vikri; Putri Liana
Al-Khidmat Vol 6, No 1 (2023): Jurnal Al-Khidmat : Jurnal Ilmiah Pengabdian Kepada Masyarakat
Publisher : Pusat Pengabdian kepada Masyarakat LP2M UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/jak.v6i1.15769

Abstract

AbstrakPendidikan usia dini yang banyak diadakan oleh yayasan pendidikan mempunyai konsep yang berbeda-beda. Salah satu yayasan pendidikan anak yang ada di sugihwaras bojonegoro adalah RA Alfathimiyah. Anak-anak yang bersekolah disana dengan berbagai sifat yang berbeda-beda. Ada beberapa anak yang sifatnya dominan temperamen dan introvert. Setelah dikaji, anak-anak tersebut ketika di rumah terlalu banyak melakukan kegiatan screen time tanpa pengawasan yang tepat dari orang tua mereka. Dengan adanya permasalahan tersebut, maka diadakan sosialisasi kepada guru dan orang tua anak mengenai penerapan penggunaan media internet pada pembelajaran anak usia dini di RA Al fathimiyah sugihwaras. Kegiatan pengabdian kepada masyarakat ini bertujuan memberikan pengetahuan kepada guru untuk disosialisasikan kepada orang tua mengenai penerapan media internet yang tepat untuk anak usia dini. Metode yang digunakan yaitu sosialisasi dengan memberikan pre-test, presentasi, dan post-test kepada guru dan orang tua. Kegiatan sosialisasi telah dilakukan pada 18 Desember 2021 dengan peserta 30 orang. Dari hasil pre-test ditunjukkan bahwa orang tua memberikan gadget kepada anak 44% mulai usia 2 tahun, 55% mulai usia 3 tahun, dan 15 mulai usia 4 tahun. Sedangkan dari hasil post-test ditunjukkan bahwa 78% peserta sudah memahami penggunaan gadget dengan durasi waktu yang sesuai dengan usia anak dan semua peserta sudah melakukan pengalihan aktivitas untuk meminimalisir anak bermedia internet. AbstractEarly childhood education held by many educational foundations has different concepts. One of the children's education foundations in Sugihwaras Bojonegoro is RA Alfathimiyah. The children who go to school there are of many different natures. There are some children whose temperament is dominant and introverted. After studied, these children when at home do too much screen time without proper supervision from their parents. With these problems, socialization was held to teachers and parents of children regarding the application of the use of internet media in early childhood learning at RA Al Fathimiyah Sugihwaras. This community service activity aims to provide knowledge to teachers to be socialized to parents regarding the application of appropriate internet media for early childhood. The method used is socialization by giving pre-test, presentation, and post-test to teachers and parents. The socialization activity was carried out on December 18, 2021 with 30 participants. From the results of the pre-test, it was shown that parents gave gadgets to their children 44% from the age of 2 years, 55% from the age of 3 years, and 15 from the age of 4 years. Meanwhile, from the post-test results, it was shown that 78% of participants had understood the use of gadgets with a time duration that was appropriate to the child's age and all participants had diverted activities to minimize children using internet media.
Sistem Otomatisasi Hidroponik Budidaya Sayuran sebagai Upaya Pemberdayaan Mandiri Santri Pondok Pesantren Pacul Bojonegoro Roihatur Rohmah; Muhammad Jauhar Vikri; Mula Agung Barata; Zakki Alawi; Moh. Muhajir; Vita Dwi Rahmawati; Rheyna Anggri Setyani
I-Com: Indonesian Community Journal Vol 4 No 2 (2024): I-Com: Indonesian Community Journal (Juni 2024)
Publisher : Fakultas Sains Dan Teknologi, Universitas Raden Rahmat Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33379/icom.v4i2.4316

Abstract

Vegetables are a source of vitamins and fiber which are very beneficial for student growth. Vegetables can improve human brain performance. Students or santri who are in Islamic boarding schools generally consume minimal vegetables regularly. One of the Islamic boarding schools in the city of Bojonegoro. Community service activities in the form of hydroponic system training are needed by students with the aim of increasing students' knowledge of vegetable cultivation using hydroponics as an effort to empower students to independently consume vegetables. In the training activities that have been carried out, an automatic hydroponic system has been successfully created that uses a water level sensor in a DFT (Deep Flow Technique) pipe for irrigation. Service is carried out using the Rapid Rural Appraisal method and participatory learning and action. The results of the activities in this training were an increase in students' knowledge about hydroponics from 30% to 72%. Apart from that, there is also 1 hydroponic system dedicated to the Al Falah Islamic boarding school from the service team as a means of applying vegetable cultivation to meet the students' vegetable consumption needs.
Penerapan Fungsi Exponential Pada Pembobotan Fungsi Jarak Euclidean Algoritma K-Nearest Neighbor Muhammad Jauhar Vikri; Rohmah, Roihatur
Generation Journal Vol 6 No 2 (2022): Generation Journal
Publisher : Universitas Nusantara PGRI Kediri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29407/gj.v6i2.18070

Abstract

– k-Nearest Neighbor (k-NN) is one of the popular classification algorithms and is widely used to solve classification cases. This is because the k-NN algorithm has advantages such as being simple, easy to explain, and easy to implement. However, the k-NN algorithm has a lack of classification results that are strongly influenced by the scale of input data and Euclidean which treats attribute data evenly, not according to the relevance of each data attribute. This causes a decrease in the classification results. One way to improve the classification accuracy performance of the k-NN algorithm is the method of weighting its features when measuring the Euclidean distance. The exponential function of the optimized Euclidean distance measurement is applied to the k-NN algorithm as a distance measurement method. Improving the performance of the k-NN method with the Exponential function for weighting features on k-NN will be carried out by experimentation using the Data Mining method. Then the results of the performance of the objective method will be compared with the original k-NN method and the previous k-NN weighting research method. As a result of the closest distance decision, taking the closest distance to k-NN will be determined with a value of k=5. After the experiment, the goal algorithm was compared with the k-NN, Wk-NN, and DWk-NN algorithms. Overall the comparison results obtained an average value of k-NN 85.87%, Wk-NN 86.98%, DWk-NN 88.19% and the k-NN algorithm given the weighting of the Exponential function obtained a value of 90.17%.
REAL-TIME TOMATO QUALITY DETECTION SYSTEM USING YOU ONLY LOOK ONCE (YOLOv7) ALGORITHM Muarofah, Isna Ayu; Vikri, Muhammad Jauhar; Sa’ida, Ita Aristia
ULTIMATICS Vol 15 No 2 (2023): Ultimatics : Jurnal Teknik Informatika
Publisher : Faculty of Engineering and Informatics, Universitas Multimedia Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31937/ti.v15i2.3337

Abstract

Real-time object detection is a crucial aspect of computer vision. With the increasing prominence of the big data field, it has become easier to gather data from various sources. Over the past few decades, computer vision inspection systems have become essential tools in agricultural operations, and their usage has seen a significant rise. Computer vision automation-based technology in agriculture is increasingly being employed to enhance productivity and efficiency. Tomato is a widely utilized crop commodity, finding applications in food, cosmetics, and pharmaceuticals. Consequently, tomato farming continues to evolve and has become one of the nation's export commodities. YOLO is an algorithm capable of real-time object detection and recognition. In this study, the YOLOv7-tiny architecture, which has lower computational overhead, was utilized. For quality detection of tomatoes, they were categorized into three classes: ripe, unripe, and defective. The trained model yielded a recall score of 0.97, precision of 1.0, a PR-curve of 0.838, and an F1-score of 0.81, indicating that the model learned effectively. The research achieved an accuracy of 90.6% on original images with an average IoU of 0.90 and a detection time of 2.7 seconds. In images with added light disturbance, the average accuracy was 91.2%. Images with reduced light yielded an average accuracy of 92%, while images with blur disturbance had an average accuracy of 78.2%. In real-time testing, ripe tomatoes were detected up to a maximum distance of 90cm, unripe tomatoes at 90cm, and defective tomatoes at 70cm.
Pengembangan ERP Untuk Digitalisasi Proses Produksi dan Penjualan Pupuk Aries Alfian Prasetyo; Laily Ulfiyah; Achmad  Afandi; Andhi Setiawan; Muhammad Jauhar Vikri
Merkurius : Jurnal Riset Sistem Informasi dan Teknik Informatika Vol. 2 No. 1 (2024): Januari : Merkurius : Jurnal Riset Sistem Informasi dan Teknik Informatika
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/merkurius.v2i1.56

Abstract

Competition in the industrial world after the impact of Covid-19 has become fierce competition. Many companies choose to increase effectiveness and efficiency by implementing digitalization in production and sales activities. PT. Megarhizo Ega Persada is a company that is developing, a company whose main production is liquid organic fertilizer under the brand "Megarhizo". Production activities still use manual bookkeeping processes. So it takes a long time for distribution from the warehouse to the production location. Miscalculations often occur in warehouses resulting in inappropriate production targets, due to insufficient or expired materials due to being in the warehouse for too long. This problem often occurs because the recording process is not thorough and results in stock buildup or stock shortages in the warehouse. So we need a system that can easily and quickly manage data so that these things don't happen again. Digitalization of the sales process is a solution to this problem, fertilizer products are products that are different from other production, because fertilizer is a product that is monitored so the price of fertilizer should not burden the public. By digitizing sales, companies can directly monitor stock and products sold from each distribution location to the resellers. So the number of products sold and prices can still be monitored, besides that the company can also find out the effectiveness of fertilizer production.
Perancangan Sistem Electronic Nose Berbasis Mikrokontroller Sebagai Alat Pengklasifikasi Jenis Teh Murni Barata, Mula; Jauhar Vikri, Muhammad; Pribadi, Teguh
Jurnal Informatika Polinema Vol. 11 No. 1 (2024): Vol. 11 No. 1 (2024)
Publisher : UPT P2M State Polytechnic of Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33795/jip.v11i1.6349

Abstract

Klasifikasi jenis teh murni secara manual sering kali memerlukan waktu yang lama dan bergantung pada kemampuan indera manusia, karena kemampuan ketajaman indera penciuman manusia yang berbeda penciuman anggapan tehradap obyek bersifat subyektif dan rentan terhadap kesalahan. Penelitian ini bertujuan untuk merancang sebuah sistem electronic nose berbasis mikrokontroler yang mampu mengklasifikasikan jenis teh murni secara otomatis dan konsisten. Sistem yang dikembangkan terdiri dari perangkat keras, termasuk mikrokontroler dan sejumlah sensor gas untuk mendeteksi senyawa volatil yang menjadi ciri khas setiap jenis teh. Data dari sensor diolah menggunakan algoritma machine learning untuk menghasilkan model klasifikasi yang akurat. Proses pengembangan melibatkan pengumpulan data aroma dari lima jenis teh murni yang diuji dalam berbagai kondisi lingkungan untuk memastikan robustitas sistem. Data yang diperoleh kemudian dianalisis dan diolah menggunakan algoritma supervised learning, yaitu algoritma Decision Tree. Sistem prototipe yang dihasilkan mampu mencapai akurasi klasifikasi sebesar 93,7%, menunjukkan keandalannya dalam mengenali pola aroma khas dari setiap jenis teh. Selain membahas hasil, penelitian ini juga mengidentifikasi tantangan seperti pengaruh variasi suhu dan kelembaban terhadap performa sensor, serta kebutuhan kalibrasi berkala untuk menjaga konsistensi sistem. Dengan hasil yang menjanjikan, sistem ini menawarkan solusi inovatif untuk mendukung industri teh dalam mengotomatisasi proses pengklasifikasian produk secara lebih efisien dan objektif.
Deteksi Kualitas Buah Sawo dengan Pendekatan Ekstraksi Fitur GLCM dan Algoritma Support Vector Machine Karisma Risma Fidiya; Muhammad Jauhar Vikri; Alif Yuanita Kartini
JURIKOM (Jurnal Riset Komputer) Vol 12, No 2 (2025): April 2025
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/jurikom.v12i2.8519

Abstract

The quality of sapodilla fruit is a crucial factor in ensuring product standards and consumer satisfaction. This study aims to detect the quality of sapodilla fruit using the Gray Level Co-occurrence Matrix (GLCM) method for texture feature extraction and Support Vector Machine (SVM) as the classification algorithm. A dataset of sapodilla fruit images was collected and processed using data augmentation techniques to enhance image variation. Extracted features, including contrast, homogeneity, energy, and correlation, were used as input for the SVM model. The model was developed using a train-test split approach and evaluated based on accuracy, precision, recall, and F1-score. Experimental results show that the proposed method successfully classifies sapodilla fruit into three categories—raw, ripe, and damaged—with an accuracy of 85%. This model was implemented in a MATLAB-based Graphical User Interface (GUI), enabling users to automatically classify sapodilla quality easily and efficiently.
Application of SMOTE-ENN Method in Data Balancing for Classification of Diabetes Health Indicators with C4.5 Algorithm Bakti Putra Pamungkas; Muhammad Jauhar Vikri; Ita Aristia Sa'ida
Jurnal Sisfokom (Sistem Informasi dan Komputer) Vol. 14 No. 2 (2025): MEY
Publisher : ISB Atma Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32736/sisfokom.v14i2.2350

Abstract

Data imbalance in health datasets often leads to decreased performance of classification models, especially in detecting minority classes such as diabetics. This study evaluates the effect of the SMOTE-ENN method on improving the performance of the C4.5 algorithm in the classification of diabetes health indicators. The dataset used is the 2021 Diabetes Binary Health Indicators BRFSS from Kaggle, which consists of 236,378 respondent data with unbalanced class distribution: 85.80% non-diabetic and 14.20% diabetic. The SMOTE method was used to add synthetic data to the minority classes, while ENN was applied to remove data considered noise. After balancing, the C4.5 algorithm was used for classification. Evaluation was conducted using accuracy, precision, recall, and F1-score metrics. The results showed that the application of SMOTE-ENN improved accuracy from 79.49% to 80.33% and precision from 29% to 30%. Although the recall value did not increase, this method proved to be able to improve the overall stability of the prediction, especially in terms of the accuracy of the classification of the positive class. The novelty of this research lies in the specific application of the SMOTE-ENN method on large-scale health datasets with the C4.5 algorithm, which has not been widely explored before. Therefore, further exploration of other balancing techniques and algorithms is needed to obtain more optimal classification results on unbalanced data.
Co-Authors Abdul Faqih Achmad  Afandi Agung Barata, Mula Ahmad Sahru Romadhon Alif Yuanita Kartini Andhi Setiawan Aralia, Shafa Kirana Aries Alfian Prasetyo Bakti Putra Pamungkas Barata, Mula Bassalam, Ahmad Nasih Ulwan Dwi Prastya, Ifnu Wisma Fidiya, Karisma Risma Fitri Damayanti Ita Aristia Sa'ida Karisma Risma Fidiya Kartini, Alif Yuanita Laily Ulfiyah Moh. Muhajir Muarofah, Isna Ayu Mula Agung Barata Nugraha, Krisna Wahyu Pradema Sanjaya, Ucta Putri Liana Rheyna Anggri Setyani Risqi, M. Khoirul Roihatur Rohmah Sunu Wahyudhi Teguh Pribadi Vita Dwi Rahmawati Wisma Dwi Prastya, Ifnu Zakki Alawi