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All Journal International Journal of Electrical and Computer Engineering Jurnal Media Infotama JSI: Jurnal Sistem Informasi (E-Journal) Jurnal Informatika dan Teknik Elektro Terapan Jurnal Informatika Upgris PROCESSOR Jurnal Ilmiah Sistem Informasi, Teknologi Informasi dan Sistem Komputer JSAI (Journal Scientific and Applied Informatics) Journal of Technopreneurship and Information System (JTIS) JATI (Jurnal Mahasiswa Teknik Informatika) Just TI (Jurnal Sains Terapan Teknologi Informasi) Djtechno: Jurnal Teknologi Informasi Jurnal Sistem Informasi Dan E-Bisnis Jurnal Ilmu Komputer Dan Informatika Jurnal Media Computer Science JIMAKUKERTA Jurnal Pengabdian Kolaborasi dan Inovasi IPTEKS Jurnal Pendidikan dan Pengabdian Masyarakat Jurnal Rekayasa Sistem Informasi dan Teknologi JPMTT (Jurnal Pengabdian Masyarakat Teknologi Terbarukan) Riau Jurnal Teknik Informatika Jurnal Komputer, Informasi dan Teknologi
Yuza Reswan
Universitas Muhammadiyah Bengkulu
Agriculture, Biological Sciences & Forestry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Social Sciences Other

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Perbandingan Metode Naive Bayes dan Bayesian Regularization Neural Network Untuk Klasifikasi Jenis Penyakit Diabetes Mellitus Filda Rahayu; Erwin Dwika Putra; Yuza Reswan; Agung Kharisma Hidayah
Jurnal Komputer, Informasi dan Teknologi Vol. 5 No. 2 (2025): Desember
Publisher : Penerbit Jurnal Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53697/jkomitek.v5i2.2985

Abstract

Diabetes Mellitus is associated with long-term damage, dysfunction, and failure of various organs, especially the eyes, kidneys, nerves, heart, and blood vessels. Naive Bayes is a classification method that can predict the probability of a class, thus generating decisions based on learning data. The Naive Bayes method is used to classify Diabetes Mellitus. To predict a disease using a data mining approach, symptoms accompanied by clinical data are required. Therefore, the problem is formulated how the Naive Bayes method compares with Bayesian regularization neural networks for classifying types of Diabetes Mellitus. With the RapidMiner tool, it becomes educational information in providing information on Diabetes Mellitus based on Type 1 Diabetes, Type 2 Diabetes, and Gestational Diabetes
Analysis of Face Detection with Head Accessories Using Haar Cascade in Image Processing Heru Susanto; Yuza Reswan; Nuri Veronika; Rozali Toyib
Jurnal Komputer, Informasi dan Teknologi Vol. 5 No. 2 (2025): Desember
Publisher : Penerbit Jurnal Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53697/jkomitek.v5i2.3146

Abstract

This research is entitled Analysis of Face Detection With Accessories On The Head Using Haar Cascade In Image Processing. The problem faced is how accurate the haar cascade algorithm is in detecting faces with accessories on the head, whether the haar cascade algorithm can still detect faces even though there are accessories that are felt around the face, therefore a study was conducted on face detection with accessories on the head using the haar cascade algorithm in several facial conditions such as facial angles and in several lighting conditions in the detection process. This study aims to analyze the accuracy of the haar cascade algorithm in detecting faces with accessories on the head, whether haar cascade can still detect faces even though there are accessories around the face that block, and 20 facial data sets were taken with a real-time laptop camera. The facial data obtained was taken in several places such as campus areas, houses and boarding houses and with various lighting conditions. From 20 face data taken in real time, researchers obtained 2 face data that were not detected due to poor lighting when taking face data and obtained 18 face data that were successfully detected even though using accessories around the face and it is certain that haar cascade has very good accuracy in detecting faces even though they were blocked by accessories. The testing methods applied are precision, recall and accuracy for calculating the results obtained. The results of the study obtained a precision of 100%, recall 90% and accuracy of 90%.
IDENTIFIKASI JENIS DAUN MENGGUNAKAN EKSTRASI FITUR Ahmad Nur Habibullah Chan; Yovi Apridiansyah; Yuza Reswan; Harry Witriyono
Journal of Technopreneurship and Information System (JTIS) Vol 8 No 3 (2025): Desember
Publisher : Fakultas Teknik Universitas Muhammadiyah Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36085/jtis.v8i3.10024

Abstract

Penelitian ini membahas implementasi dan evaluasi sistem identifikasi jenis daun menggunakan metode ekstraksi fitur berbasis pengolahan citra digital. Sistem dikembangkan menggunakan Graphical User Interface (GUI) Matlab dan melalui beberapa tahapan utama, yaitu pemrosesan citra, ekstraksi fitur, dan identifikasi. Dataset citra daun diproses dengan teknik pra-pemrosesan seperti cropping dan resizing untuk meningkatkan akurasi sistem. Metode ekstraksi fitur yang digunakan dalam penelitian ini meliputi analisis bentuk, tekstur, dan warna untuk membedakan jenis daun secara akurat. Hasil pengujian menunjukkan bahwa sistem ini memiliki tingkat akurasi sebesar 80%, presisi 90%, dan recall 86%. Hasil ini menunjukkan bahwa metode yang digunakan cukup efektif dalam mengidentifikasi jenis daun. Penelitian ini diharapkan dapat dikembangkan lebih lanjut dengan meningkatkan jumlah dataset dan menerapkan metode optimasi fitur yang lebih kompleks guna meningkatkan akurasi identifikasi.
KLASIFIKASI JENIS JERUK GERGA DAN JERUK KALAMANSI MENGGUNAKAN METODE CONVOLUTIONAL NEURAL NETWORK (CNN) : PENDAHULUAN,METODE PENELITIAN,HASIL DAN PEMBAHASAN Khoiriah nur aisyah; Yuza Reswan; Ardi Wijaya; Harry Witriyono
Journal of Technopreneurship and Information System (JTIS) Vol 8 No 3 (2025): Desember
Publisher : Fakultas Teknik Universitas Muhammadiyah Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36085/jtis.v8i3.10222

Abstract

Oranges are one of the tropical fruits widely cultivated and consumed in Indonesia. This study aims to develop a digital image classification system to distinguish between Gerga and Kalamansi oranges using the Convolutional Neural Network (CNN) method. The system is designed to assist the automatic identification of fruit types based on visual characteristics found in digital images.The dataset consists of 836 images, including 746 training images, 90 validation images, and 24 testing images. Before the training process, the images undergo preprocessing and data augmentation to increase data variation. The CNN model used in this study consists of several convolutional layers, ReLU activation, pooling, flatten, and fully connected layers for classification.The testing results show an accuracy of 83%, precision of 75%, recall of 100%, and an F1-score of 85%. Overall, the CNN method proves to be sufficiently effective in classifying orange types based on digital images and has the potential to be further developed for automation in the agricultural sector.
Sistem Pendukung Keputusan Penyaluran Bantuan Pemerintah Menggunakan Algoritma Weigted Product Reno Septia Erlangga; Yuza Reswan
Jurnal Media Infotama Vol 18 No 1 (2022): April
Publisher : UNIVED Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37676/jmi.v18i1.1746

Abstract

One factor that is strongly suspected to have contributed to reducing the number of poverty in Indonesia is the existence of a social assistance program by the central government. The social assistance program provided by the government on a regular basis to the community is very helpful if the distribution is right on target. The distribution of government assistance in Lunjuk Village, Seluma Barat District, Seluma Regency is still carried out conventionally, namely by providing assistance to all residents who are considered poor by the staff on duty without going through a selection process first. The amount of assistance provided by the government is limited so that not all residents can get this assistance. To facilitate the process of grouping residents, we need a system that can provide the right conclusions based on predetermined criteria. One of them uses a decision support system application. A system that can provide conclusions on the priority of beneficiaries based on the data that has been inputted. The conclusion generated by the application requires the right method to be implemented into the system and one of them is the weighted product method which can provide optimal solutions in the rating system. 1. The Decision Support System for the Distribution of Government Assistance Using the Weighted Product Algorithm in Lunjuk Village was built using the PHP programming language and MySQL database. The application can provide a priority list of beneficiaries based on the calculation results of the Weighted Product Algorithm using criteria weight data and data from Lunjuk Village residents.
Implementasi Metode Cepat Kompresi File Document Otomatis Pada Aplikasi Berbasis Web Menggunakan Algoritma Additive Code Yuza Reswan; Leo Tri Anggoro
Jurnal Media Infotama Vol 20 No 1 (2024): April 2024
Publisher : UNIVED Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37676/jmi.v20i1.5620

Abstract

Online data entry systems have largely replaced manual file submission in modern data transmission. Data is often very large. Therefore, a method is needed to reduce the size of the data. File compression, or compression in general, is the name of this method. Compressing files involves transforming multiple document files into a standard encoding format to reduce storage space requirements or increase upload speed. The results of this research inform the use of the Additive Code technique application for file compression, which makes it easier to upload document files automatically and is useful for users. Therefore, the author conducted research with the aim of developing a web-based application. This system can make it easier to upload document files so that it can reduce processing time. Using this method in online applications is useful for creating large document files that can be compressed into smaller ones by following the compression procedure. Data compression test results were obtained by running 10 samples of each document and PDF data file at a speed of less than 3 seconds, with accuracy ranging from 27% to 67% for each sample. We successfully tested ten Word documents and ten PDFs that were uploaded and compressed.
Deteksi Gizi Buruk Pada Balita Menggunakan Metode Fuzzy Logic (Studi Kasus Puskesmas Kecamatan Semidang Alas Kabupaten Seluma) Yuza Reswan; Yulia Darnita; A.R Walad Mahfuzhi; Yonaldo Putra
Jurnal Media Infotama Vol 20 No 1 (2024): April 2024
Publisher : UNIVED Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37676/jmi.v20i1.5626

Abstract

Nutrition plays a crucial role in maintaining health and well-being throughout the life cycle, especially in toddlers. Malnutrition can affect the physical growth, intelligence, and productivity of children. Factors such as economic conditions, parental attention, and unsupportive environments can contribute to cases of malnutrition in toddlers. Suboptimal monitoring of toddler development can increase the prevalence of malnutrition cases. This research aims to develop a Fuzzy Logic-based Decision Support System (DSS) application to detect malnutrition in toddlers, with a focus on the Semidang Alas Community Health Center in Seluma Regency. This study discusses variables for assessing malnutrition in toddlers, applies the Fuzzy Logic method to detect these conditions, and designs an application to diagnose malnutrition in toddlers. The research also includes community education on weight changes in malnourished toddlers and general nutritional status, providing input to improve services for malnourished toddlers. Assessment criteria involve the child's weight, height, and age, using Fuzzy Logic and DSS Application for data processing. Information handling related to malnutrition is limited to visible symptoms. Software development focuses on recognizing malnutrition diagnoses in children aged 0-5 years. A case study was conducted at the Semidang Alas Community Health Center using direct observation, nurse/midwife interviews, questionnaires, and literature reviews. System needs analysis used the Fuzzy Sugeno method. The malnutrition detection application was successfully built using Fuzzy Logic, providing detection results based on age, weight, and height. The defuzzification process produced detection values as a reference for further treatment. Application development involved both display and data aspects, with testing conducted with relevant parties to ensure the accuracy of detection results. User criticisms and suggestions provided valuable input for the improvement and development of this application.
Aplikasi Pengolahan Data Permintaan dan Pengeluaran Material Teknik di Perusahaan Umum Daerah Tirta Hidayah Kota Bengkulu Berbasis Web Yuza Reswan; Muntahanah Muntahanah; Eka Sahputra; Yolan Pagestu
Jurnal Media Infotama Vol 20 No 1 (2024): April 2024
Publisher : UNIVED Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37676/jmi.v20i1.5673

Abstract

Tirta Hidayah, Bengkulu City, distributes water to customers using pipes and engineering materials designed to work properly. However, this does not always run smoothly, because technical and non-technical problems often occur. To carry out the process of handling and correcting problems that occur in the field, each department must order goods in the warehouse. However, the problem is that the location between offices is quite far and the administration is quite long, making the demand and expenditure of goods not optimal and has an impact on customer service. Of course, this situation can hamper service to customers, because the currently available applications can only be accessed offline. Therefore, the author is interested in creating a web-based application for the PHP programming language and Mysql database. The system development was carried out using the waterfall SDLC model, with the result that the application for processing data on demand and expenditure of engineering materials with a web-based system at the Tirta Hidayah Regional Public Company, Bengkulu City, which was built has been running well, and this application is useful and helps the Service Unit (Processing, Transmission and Distribution Installation, New Installation) and Warehouse Sub Division and Tirta Hidayah General Section of Bengkulu City in the process of requesting and releasing technical materials to be more effective and efficient
Implementasi Metode Certainty Factor Dalam Diagnosa Penyakit Gigi Yuza Reswan; Pahrizal Pahrizal; Khairullah Khairullah; Mat Agus
Jurnal Media Infotama Vol 20 No 1 (2024): April 2024
Publisher : UNIVED Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37676/jmi.v20i1.5688

Abstract

This study aimedd to build an application program that can aid plant experts provide knowlwdge in the form of an expert system.so it can be employed to treat diseases of the teeth. The system can forecast diseases.the method usedd was the expert system which is built using a certainty value called certainty factor. The resulting values can be utilized to infer the types of diseases and pests on the grapes. The results achieved from this study are the implementation of the Certainty Factor method in the diagnosis of dental disease. The conclusion of this study is to produce a website-based expert system that can help doctors diagnose dental diseases based on the symptoms caused.
Klasifikasi Tingkat Kematangan Buah Nanas Berdasarkan Fitur Warna Menggunakan Metode K–Nearest Neighbor (KNN) Yuza Reswan; Rozali Toyib; Harry Witriyono; Ani Anggraini
Jurnal Media Infotama Vol 20 No 1 (2024): April 2024
Publisher : UNIVED Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37676/jmi.v20i1.5689

Abstract

This study aims to determine the extent to which the KNN algorithm is able to classify pineapple fruit based on color features with high accuracy and determine the best k value in the KNN algorithm to achieve optimal accuracy in the classification of pineapple maturity levels. In the process of classifying pineapple fruit manually by using the human eye is a very difficult thing to do. This is evidenced by the inconsistency and subjective nature that causes a low level of accuracy. Therefore, to increase the level of accuracy and reduce the subjectivity of the human eye, this research proposes an algorithm that can be used to classify the maturity level of pineapple fruit, namely with K-Nearest Neighbor based on the color of the skin on the fruit. The k value used in this research is 1, 3, 5, 7, and 9 to test the Euclidean distance search on images with a size of 300x300 pixels. The research conducted proves that with Euclidean distance k = 5 and k = 9 has a percentage value of 73%. Based on the level of accuracy, color features k = 5 and k = 9 show the best k value on the classification of pineapple ripeness level.
Co-Authors A.R Walad Mahfuzhi A.R Walad Mahfuzi A.R. Walad Mahfuzhi A.R. Walad Mahfuzhi Mahfuzhi Abdullah, Dedy Achmad Rajes Adelia, Serlina Adinda Trisista Ahmad Nur Habibullah Chan Anggraini, Laura Ani Anggraini Anugrah Ilahi, Puja Apridiansyah, Yovi Ar. Walad Mahfuzi Arevo Syahputra Ari Satrio Wibowo Arif Permana Ariksa Abdul Lasin Arnoldi Arnoldi Baihaqi, Ikhwan Bobi Tri Yuliansyah cantika Cecep Saputra Dandi Sunardi Darnita, Yulia Dedy Abdullah Dedy Abdullah Dedy Agung Prabowo Dena, Yunita Meli Diana Diana Diana Diana Dyah Parmitha Pertiwi Eka Sahputra Elviani Elviani Elviani, Elviani Erwin Dwik Putra Evan Jayusta Fajar Ramadianto Feby Ayu Sahputry Filda Rahayu Geri Melano Evandra Ghepri Haikal Giova Giova Giova Giova Gunawan Gunawan Gunawan Gunawan Guntur Alam Handayani, Kurnia Marga Harry Witriyono Heru Susanto Hidayah, Aditia hidayah, agung kharisma Hidayat, Roki Imanullah, Muhammad Jery Rohmadan Wahari Juansen, Monsya Juhardi, Ujang Khairullah Khairullah Khairullah khairullah Khairullah Khairullah Khairullah, Khairullah Khoiriah nur aisyah Kurnia Marga Handayani Lambardo Adesio Laura Anggraini Leo Tri Anggoro M Taufik Ma'ruf M. Taufik Ma’ruf Mahfuzhi, A.R. Walad Mahfuzhi, A.R. Walad Mahfuzhi Mahfuzi, A.R Walad marhalim, marhalim Marton Marton Mat Agus Ma’ruf, M. Taufik Monsya Juansen Muhammad Husni Rifqo Muhammad Husni Rifqo Muhammad Imanullah Muhammad Immanullah Muhammad Soelaiman Rasyid Muntahanah Muntahanah Muntahanah, Muntahanah Nazuta Rolleys Nuri David Maria Veronika Nuri Veronika Padli, Zeko Pahrizal Pahrizal, Pahrizal Paulina, Yanti Putra, Erwin Dwik Putra, Erwin Dwika Putra, Yonaldo PUTRI WAHYUNI R.S, Penti Septian Raffles, Richard Rajes, Achmad Rasyid, Muhammad Soelaiman Reno Septia Erlangga Reza Julianti Ricardo, Ryo Rifqo, Muhammad Husni Ristontowi, Ristontowi Ronny Saputra Ronny Saputra, Ronny Rozali Toyib Ryo Ricardo Sahputra, Eka Sahputry, Feby Ayu Sahrudin Sahrudin Sapitri, Tari Juita Seprianti, Widia Sonita, Anisya Sundari Sundari Surya Ade Saputera Syahputra, Arevo Tari Juita Sapitri Tirta Sari, Puput Toyib, Rozali Trisista, Adinda ujang juhardi Ujang Juhardi Wahidah, Alifah Nur Wibowo, Ari Satrio Widia Seprianti Wijaya, Ardi Witriyono, Harry Yolan Pagestu Yonaldo Putra Yulia Darmi Yuliy Gusnitasari Simanjuntak Yunita Meli Dena Yusa Virginiawan Guntara