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All Journal International Journal of Electrical and Computer Engineering TELKOMNIKA (Telecommunication Computing Electronics and Control) Semesta Teknika Register: Jurnal Ilmiah Teknologi Sistem Informasi Journal of Electrical Technology UMY Indonesian Journal of Information System Jurnal Surya Masyarakat Emerging Information Science and Technology Prosiding Seminar Nasional Program Pengabdian Masyarakat Scientific Journal of Informatics
Slamet Riyadi
Universitas Muhammadiyah Yogyakarta
Religion Agriculture, Biological Sciences & Forestry Humanities Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Electrical & Electronics Engineering Energy Engineering Environmental Science Library & Information Science Medicine & Pharmacology Public Health Social Sciences

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Estimation of tertiary dentin thickness on pulp capping treatment with digital image processing technology Slamet Riyadi; Laila Ma’rifatul Azizah; Fauri Hakim; Cahya Damarjati; Sartika Puspita; Erma Sofiani
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 1: February 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (565.897 KB) | DOI: 10.11591/ijece.v10i1.pp521-529

Abstract

Dentists usually observe the tertiary dentin formation after pulp capping treatment by comparing periapical radiograph before and after treatment visually. However many dentists find difficulties to observe tertiary dentin and also they can’t measure exactly the thickness of the tertiary dentin. The aims of this study is to assist the dentists to measure the area of tertiary dentin and calculate the dentin formation using b-spline image processing. The dental radiograph of 38 patients of pulp capping in the Dental Hospital Universitas Muhammadiyah Yogyakarta, Indonesia. Each of patient visited dental hospital 3 times. First, the patient got an application of pulp capping material. Second, after one-week treatment and temporary restoration and the third, after more than one month with the composite as the final restoration. Every visited the patient take a radiograph. Dentist placed the dot from the patient's radiograph. The dots were combined and processed with digital image processing. The b-spline method changed the dot to one area. After the calculation, the dentist can see whether there was dentin formation which means it is one of the treatment success indicators. Dentist has the better view to measure the dentin formation by providing area value of its tertiary dentin thickness calculation. We compare the result to the program calculation using the b-spline method and visual observation from the dentist. This study indicated the thickness of tertiary dentin can be measured by this program with an accuracy of 94.2%. Therefore, dentist can make tertiary dentin thickness prediction from patient’s radiograph.
Development of Leaf Area Meter Using Open CV for Smartphone Application Tony K. Hariadi; Zulfan Fadholi; Anna NN Chamim; Nafi A Utama; Indira Prabasari; Slamet Riyadi
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 16, No 4: August 2018
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v16i4.8608

Abstract

This study aimed to design an accurate and practical system of leaf area determination using a smartphone. A software application for leaf area computation was developed using Open CV (Open Source Computer Vision) library. Open CV software was tested to estimate the accuracy of leaf area calculation. Leaf area calculations were undertaken using three different image resolutions to compare their accuracy. The results of the software calculations were then compared with the results of the laboratory leaf area meter to identify any errors. The results showed that higher image resolutions improved accuracy by reducing errors. High resolution image gave higher accuracy, however processing speed decreased. Leaf measurement in this project resulted in accuracy range between 92.8% to 99.0%. It was concluded that the Open CV algorithm gave fast and adequate accuracy for leaf area calculation, and that the smartphone mobile application system was practical for field use.
Perkiraan Masa Tunggu Alumni Mendapatkan Pekerjaan Menggunakan Metode Prediksi Data Mining Dengan Algoritma Naive Bayes Classifier Asroni Asroni; Nadiyah Maharty Ali; Slamet Riyadi
Semesta Teknika Vol 21, No 2 (2018): NOVEMBER 2018
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/st.212225

Abstract

Student and Alumni data Universitas Muhammadiyah Yogyakarta is very common, and one of these is the alumni data obtained from work after the completion of undergraduate studies. Former students are given jobs caused or influenced by a range of factors. This research aims to have the grace period Classification or old alumni gain positions by triggering a process of data extraction and using the Bayes naïve classification algorithm. The algorithms used later succeeded in predicting sooner or later to get a job, the predictive results alumni can be used to make decisions to improve the quality of a university. Research on the support system using several parameters, i.e., gender, faculty, GPA, year of graduation, and job status. The data used are as much as 435, including seven years of 2011-2014 volume. The results of this study have the accuracy level of former students having the grace period come to 71% and of the calculated results of the predictions of the former students obtaining a job at Universitas Muhammadiyah Yogyakarta of the year 2011-2014 the Ensure that the work is carried out more quickly with the status of the slow to deliver the work
Penerapan Algoritma C4.5 untuk Klasifikasi Jenis Pekerjaan Alumni di Universitas Muhammadiyah Yogyakarta Asroni Asroni; Badrahini Masajeng Respati; Slamet Riyadi
Semesta Teknika Vol 21, No 2 (2018): NOVEMBER 2018
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/st.212222

Abstract

The development of education in Indonesia has increased very rapidly. One of the things that have become a benchmark for success in the quality of education at the university is the kind of job getting graduates after graduation. This research aims to identify factors that have an impact on the type of job classification method based on the C 4.5 alumni algorithm. The methodology of this research begins with the study of literature, the identification of a process of data extraction, data selection, data collection, data processing, data testing, and DA conclusion. This research uses some features of the data on a few faculty members, the year of graduation, the annual completion rate, and the strength as a classification performance parameter. Graduates data used up to 259, and consisted of 3 faculties of Economics, medicine and engineering forces from 2001-2013 and graduated from 2011-2016. The research results that have been done is if it comes from the Faculty of Economics, in 2011 and 2012 the majority of work in the private sector has passed, if it comes from the Faculty of Medicine with the years 2011 and 2012 graduated with a cumulative labor rate of between 3 to 3.5 majority working in The private sector, 2012 with a GPA between 3 and 3.5 working in the Private Sector. Finally, the C4.5 algorithm is suitable for the classification of alumni work types.
Implementasi Arsitektur Operational Data Store (ODS) dan Dimensional Data Store (DDS) dalam Pembangunan Data Mart Lulusan Rohmana Zulfa Bakhtiar; Slamet Riyadi; Asroni Asroni
Semesta Teknika Vol 18, No 1 (2015): MEI 2015
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/st.v18i1.706

Abstract

Universitas Muhammadiyah Yogyakarta (UMY) is a big and high-grade educational institution. During the period of 1998-2014, UMY has produced about 20550 graduates. But, the big number of graduates is not supported by a good data storage system. Whereas those data are needed in filling up the accreditation form. For that reason, we have to build an integrated data storage system to provide graduates data as needed, that is graduate data mart. The development of graduate data mart uses SDLC Model Waterfall method. This method involves several types, there are requirement analysis, design system, implementation system, testing system, and maintenance system and those must be done sequentially. If there is an error, the process must be repeated from the beginning to fix the error. Development of graduate data mart uses Operational Data Store (ODS) and Dimensional Data Store (DDS) architecture. Those architectures are selected because they support transactional level. By using those architectures, graduate data mart is capable to display the data of graduates on the academic year, GPA, educational years, and the status of the student transfers. As the result, those data are able to help the management of university in filling up the accreditation form.
Renewable Energy Investment for Middle and Upper Class Housing Sector in Indonesia: Investigating the Scope for a Change in Policy Tony K. Hariadi; Milou Derks; Agus Jamal; Slamet Riyadi
Journal of Electrical Technology UMY Vol 2, No 1 (2018)
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jet.2129

Abstract

The household sector plays an important role in the energy demand in Indonesia. Households consume more than 50% of total energy in many major cities in Indonesia and account for 34% of the total energy demand. The main share of capital allocation and attention, however, has gone to rural electrification programs over the past years with mixed results, due to an abundance of problems during the operation phase. We propose that government attention and capital should be broadened to policy development for solar home systems for urban areas. The problems that are encountered by rural electrification projects are mainly due to a lack of resources and unclear task allocation between involved parties and difficulties of addressing problems in remote environments. These risks are insignificant in urban areas where maintenance services are available and where solar home systems can be commercially interesting for higher income consumers without the need for subsidy. By means of a cost benefit analysis, this paper shows that solar home systems can be commercially interesting for households in urban areas. Different investment scenarios were worked out with systems costing 5%, 10%, and 15% of the total average house price. The analysis indicates that the policy is feasible when solar systems are coupled to the grid but not for off-grid systems. This is because the battery leads to high investment and maintenance cost. From a government point of view, developing policy towards renewable energy usage in urban households could help to reach national  electrification and environmental targets without extra capital allocation as well as relieve pressure on the already overburdened state electricity company, the PLN. 
PENINGKATAN LAYANAN ADMINISTRASI PEMERINTAH DESA MELALUI PEMBANGUNAN JARINGAN LOKAL Haris Setyawan; Slamet Riyadi
Prosiding Seminar Nasional Program Pengabdian Masyarakat 2020: 11. Teknologi Informasi dalam Pemberdayaan Masyarakat
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (397.808 KB) | DOI: 10.18196/ppm.311.176

Abstract

Layanan administrasi pemerintah desa merupakan layanan utama dan berhubungan langsung dengan kebutuhan masyarakat. Layanan administrasi dapat berupa penerbitan surat keterangan, surat pengantar, surat rekomendasi, legalisir dan surat-surat lainnya. Sekarang ini, layanan administrasi di Desa Bendungan, Cawas, Klaten hanya bisa dilayani dengan satu komputer karena data hanya tersimpan pada satu komputer dan printer juga terhubung pada komputer tersebut. Hal ini mengakibatkan pemprosesan dokumen harus mengantri dan lambat. Komputer lain tidak bisa digunakan untuk melayani. Untuk mengatasi permasalahan ini, program ini bertujuan meningkatkan layanan administrasi dengan membangun jaringan komputer lokal. Dengan pembangunan jaringan lokal, semua komputer dan perangkat terhubung dan dapat saling berkomunikasi sehingga bisa digunakan untuk melakukan pelayanan secara bersamaan. Metode pelaksanaan program ini terdiri dari beberapa tahapan yaitu persiapan kebutuhan rinci jaringan, perencanaan jaringan, pembangunan dan pengujian jaringan, training penggunaan jaringan, dan evaluasi program. Program telah dilaksanakan sehingga jaringan komputer lokal di Balai Desa Bendungan telah dipasang dan digunakan. Pelayanan yang sebelum ini hanya bisa menggunakan satu komputer telah meningkat dengan menggunakan beberapa komputer yang terhubung jaringan. Kesimpulannya, program ini telah berhasil meningkatkan layanan administrasi pemerintahan desa melalui penggunaan jaringan komputer lokal
PENDAMPINGAN TATA KELOLA UMKM UD PEDHARINGAN BERBASIS TEKNOLOGI INFORMASI DAN KOMUNIKASI Dyah Mutiarin; Sakir Ridho Wijaya; Slamet Riyadi
Prosiding Seminar Nasional Program Pengabdian Masyarakat 2021: 4. Kapasitas Daya Saing Usaha Mikro, Kecil, dan Menengah (UMKM) dan Badan Usaha Milik Desa( BU
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (799.684 KB) | DOI: 10.18196/ppm.44.896

Abstract

Artikel ini bertujuan untuk mendeskripsikan dan menganalisis proses pemberdayaan terhadap UMKM di masa pandemik covid-19. UD Pedharingan sebagai mitra yang didampingi dalam pemberdayaan ini memiliki permasalahan kurangnya pemahaman mengenai digital marketing yaitu promosi dan penjualan secara online (daring) dengan memanfaatkan jejaring sosial atau platform. Permasalahan lainnya adalah packaging yang kurang menarik serta perlunya sumber daya manusia (SDM) yang memahami digital marketing dan marketplace. Pendampingan Digitalisasi UMKM UD Pedharingan berbasis Teknologi Informasi dan Komunikasi ini bertujuan membantu meningkatkan kegiatan perekonomian desa berbasis digital atau Digitalisasi UMKM. Metode yang dilakukan adalah melalui pendampingan dan pelatihan marketing berbasis digital. Hasilnya ada peningkatan kapasitas UD Pedharingan dalam melakukan digital marketing, pengetahuan tentang marketplace, pembuatan media sosial UMKM dan pembuatan kemasan ulang produk UMKM.
Performance Comparison of Deep Learning Models to Detect Covid-19 Based on X-Ray Images Slamet Riyadi; Yunita Lestari; Cahya Damarjati; Kamarul Hawari Ghazali
Indonesian Journal of Information Systems Vol. 4 No. 2 (2022): February 2022
Publisher : Program Studi Sistem Informasi Universitas Atma Jaya Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24002/ijis.v4i2.5491

Abstract

The SARS-Cov-2 outbreak caused by a coronavirus infection shocked dozens of countries. This disease has spread rapidly and become a new pandemic, a serious threat and even destroys various sectors of life. Along with technological developments, various deep learning models have been developed to classify between Covid-19 and Normal X-ray images of lungs, such as Inception V3, Inception V4 and MobileNet. These models have been separately reported to perform good classification on Covid-19. However, there is no comparison of their performance in classifying Covid-19 on the same data. This research aims to compare the performance of the three mentioned deep learning models in classifying Covid-19 based on X-ray images. The methods involve data collection, pre-processing, training, and testing using the three models. According to 2,169 dataset, the InceptionV3 model obtained an average accuracy value of 99.62%, precision value 99.65%, recall value 99.5%, specificity value 99.5%, and f-score value 99.52%; while the InceptionV4 model obtained an average accuracy value of 97.79%, precision value 98.11%, recall value 90.18%, specificity value 90.18%, and f-score value 97.25%; and the MobileNet model obtained an average accuracy value of 99.67%, precision value 99.77%, recall value 99.38%, specificity value 99.38%, and f-score value of 99.67%. The three models can classify the Covid-19 and Normal X-ray images based on research results, while the MobileNet model achieved the best performance. The model has stable performance in achieving graphic results and has extensive layers; the more layers there are to achieve better accuracy results.
Classification of Mangosteen Surface Quality Using Principal Component Analysis Slamet Riyadi; Amelia Mutiara Ayu Ratiwi; Cahya Damarjati; Tony K. Hariadi; Indira Prabasari; Nafi Ananda Utama
Emerging Information Science and Technology Vol 1, No 1: February 2020
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (529.94 KB) | DOI: 10.18196/eist.115

Abstract

Mangosteen (Garcinia mangostana L) is one of the primary contributor for Indonesia export. For export commodity, the fruit should comply the quality requirement including its surface. Presently, the surface is evaluated by human visual to classify between defect and non- defect surface. This conventional method is less accurate and takes time, especially in high volume harvest. In order to overcome this problem, this research proposed images processing based classification method using principal component analysis (PCA). The method involved pre-processing task, PCA decomposition, and statistical features extraction and classification task using linear discriminant analysis. The method has been tested on 120 images by applying 4-fold cross validation method and achieve classification accuracy of 96.67%, 90.00%, 90.00% and 100.00% for fold-1, fold-2, fold-3 and fold-4, respectively. In conclusion, the proposed method succeeded to classify between defect and non-defect mangosteen surface with 94.16% accuracy.
Co-Authors Abdul Eriawan Nahar Abyiyansyah Meidy Laksono Agus Jamal Amelia Mutiara Ayu Ratiwi Anna NN Chamim Aprilia Kurnianti Arif Ahmad Fadlil Arif Bintoro Johan Asnor Juraiza Ishak Asroni Asroni Badrahini Masajeng Respati Cahya Damarjati Cut Maya Putri Audilla Dwijoko Purbohadi Dyah Mutiarin Fadhan Anwarodin Fauri Hakim Haris Setyawan Indira Prabasari Kamarul Hawari Ghazali Kurnianti, Apriliya Laila Ma’rifatul Azizah Lusiana Ning Saputri Milou Derks Muhammad Aldi Joko Satria Perdana Muhammad Habil Muhammad Rizki Frebian Nadiyah Maharty Ali Nafi A Utama Nafi Ananda Utama Nasrul Saefullah Naufal Gita Mahardika Nisrina Akbar Rizky Putri Nurfahmi Nurfahmi Rammadhany Rammadhany Ricki Irawan Ridho Novradinata Rohmana Zulfa Bakhtiar Ronald Adrian Ronald Adrian Sakir Ridho Wijaya Sartika Puspita Siti Khotimah Sofiani, Erma Sudiwijaya, Erwan Suparman Suwadi Suwadi Suzaimah Ramli Tony K Hariadi Yunita Lestari Zulfan Fadholi