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All Journal Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Jurnal CoreIT INOVTEK Polbeng - Seri Informatika Jusikom : Jurnal Sistem Komputer Musirawas JUTIM (Jurnal Teknik Informatika Musirawas) Jurnal Teknologi Dan Sistem Informasi Bisnis Journal of Applied Engineering and Technological Science (JAETS) J-COSCIS : Journal of Computer Science Community Service Internasional Journal of Data Science, Computer Science and Informatics Technology (InJODACSIT) SATIN - Sains dan Teknologi Informasi IndoAI: Journal of Artificial Intelligence and Computational Logic Journal of Community Outreach in Science & Society

Dafwen Toresa

Universitas Lancang Kuning

Author-ID : 3756964

Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Library & Information Science Mechanical Engineering Social Sciences Other

Published : 18 Documents Claim Missing Document

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Penerapan Metode Saw Dalam Pemilihan Pegawai Berprestasi Berdasarkan Evaluasi Kinerja Berbasis Kepada Sistem Pendukung Keputusan Dafwen Toresa; Ahmad Zamsuri; Yogi Yunefri; Nurfika Sari
SATIN - Sains dan Teknologi Informasi Vol 8 No 1 (2022): SATIN - Sains dan Teknologi Informasi
Publisher : STMIK Amik Riau

Kantor Camat Siabu Kabupaten Mandailing Natal memiliki permasalahan dalam penilaian Kinerja pegawai berprestasi yang dilakukan sekarang masih dilakukan secara manual pada lembar penilaian berdasarkan nilai disiplin dan sasaran kerja yang dicapai pegawai itu sendiri. Sehingga pegawai yang berpotensi memiliki kinerja yang berprestasi tidak terlihat secara jelas. Penelitian ini bertujuan untuk merancang sistem pendukung keputusan dalam melakukan pemilihan pegawai berprestasi berdasarkan evaluasi kinerja pegawai dengan metode SAW (Simple Additive Weighting). Berdasarkan penilaian dua puluh enam orang pegawai ASN dan empat orang pejabat penilai atau responden, tahapan implementasi perhitungan SAW dalam sistem pendukung keputusan pemilihan pegawai berprestasi antara lain menentukan kriteria, menentukan kriteria penilaian, menentukan normalisasi bobot kriteria, rating kecocokan dari setiap alternatif pada setiap kriteria, normalisasi matriks, nilai akhir dari alternatif, dan hasil perankingan. Hasil dari penelitian ini adalah aplikasi sistem pendukung keputusan pemilihan pegawai berprestasi berdasarkan evaluasi kinerja dengan metode SAW dan telah memudahkan kecamatan siabu dalam pemilihan pegawai berprestasi

Digitalisasi Pengelolaan Pustaka Sekolah Dafwen Toresa; Taslim; Susi Handayani; Edriyansyah; Rometdo Muzawi
SATIN - Sains dan Teknologi Informasi Vol 9 No 1 (2023): SATIN - Sains dan Teknologi Informasi
Publisher : STMIK Amik Riau

Along with the development of science and the globalization of information that demands the creation of an all-computerized state. At SMA Negeri 4 Tualang, Siak Regency, the process of processing library data to making reports still uses manual bookkeeping. This can cause the process of searching for book data, member data and book borrowing data to take a long time and not to mention if the data is lost so it cannot be used again. Library applications are made according to user needs using the PHP programming language with MySQL database storage and Waterfall modeling. This library application has been tested with the black box method with 100% results then implemented and measured with values and measuring indicators as follows: User Satisfaction = 94%, Data Accuracy = 93%, Speed and convenience = 96%, Application and information security = 93 % and Support = 96%. Thus the digitization of library management is very beneficial for library managers and students as users at SMAN 4 Tualang

Perbandingan Algoritma C4.5 Dan Naïve Bayes Untuk Mengukur Tingkat Kepuasan Mahasiswa Dalam Penggunaan Edlink Dafwen Toresa; Ikhsan Hidayat; Edriyansyah Edriyansyah; Rometdo Muzawi; Taslim Taslim; Lisnawita Lisnawita; Febi Yanto
Jurnal Teknologi Dan Sistem Informasi Bisnis Vol 5 No 3 (2023): July 2023
Publisher : Prodi Sistem Informasi Universitas Dharma Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47233/jteksis.v5i3.855

The Faculty of Computer Science, Lancang Kuning University, as a private university in the city of Pekanbaru, uses the Sevima Edlink platform as a media for academic information systems and online learning. According to some students, there are still some obstacles encountered in understanding, using and functioning this edlink application. The purpose of this study was to measure the level of satisfaction of students of the Faculty of Computer Science in using Edlink using the C4.5 and Naïve Bayes algorithms. To measure the level of accuracy of the C4.5 and Naïve Bayes algorithms in order to measure the level of student satisfaction, the indicators used are the Servqual testing model, namely Tangible, Reability, Responsiveness, Assurance, and Empathy. Based on the level of accuracy of the two methods. In the dataset used there were 91 student respondents who had filled out the questionnaire. From the questionnaire data, it was then processed using both methods and 9 comparisons of the different Training Data and Testing Data were carried out. In general, students are satisfied and understand the use of the edlink application. This satisfaction was tested using the C4.5 Decision Tree Algorithm and the Naïve Bayes Classifier. Based on the comparison that has been carried out using the C4.5 Decision Tree Algorithm, it produces an average accuracy value of 77.78%, which is slightly more accurate than the Naïve Bayes Classifier which produces an average accuracy value of 71.11%.

PELATIHAN APLIKASI CISCO PACKET TRACERT UNTUK MENGATASI KETERSEDIAAN ALAT DAN PRAKTEK PBM JARINGAN KOMPUTER DI SMK MIGAS INOVASI RIAU Dafwen Toresa; Fana Wiza; Ahmad Ade Irwanda; Wenti Sasrapita Abiyus
J-COSCIS : Journal of Computer Science Community Service Vol. 3 No. 2 (2023): J-COSCIS : Journal of Computer Science Community Service
Publisher : Fakultas Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31849/jcoscis.v3i2.13114

Kebutuhan peralatan praktek bagi Sekolah Menengah Kejuruan (SMK) adalah suatu hal yang mutlak, akan tetap beberapa sekolah dengan keterbatasan hal tersebut bisa disiasati dengan pengunaan aplikasi simulasi. Untuk jurusan Teknik Komputer dan Jaringan (TKJ) aplikasi simulasi yang bisa digunakan untuk mengatasi keterbatasan alat praktek jaringan adalah Cisco Packet Tracer. Pelatihan ini ditujukan pada siswa kelas X untuk mengatasi keterbatasan alat praktek di SMK Migas Inovasi Riau kota pekanbaru, semua peserta diberikan pelatihan dasar jaringan, fitur dari aplikasi cisco packet tracer dan praktek merencanakan dan membuat jaringan komputer, pada akhir kegiatan diberikan mini projek mendesain jaringan komputer untuk gedung 2 (dua) lantai. Dalam 1 (satu) hari pelaksanaan peserta antusias mengikuti pelatihan dan mampu menyelesaikan tugas mini projek yang diberikan. Terjadi peningkatan pengetahuan untuk desain jaringan dan konfigurasinya dengan aplikasi simulasi ini sebesar 100%, sementara untuk materi pelatihan 98% peserta dapat menerima dan menerapkannya, sedangkan untuk pemateri menurut peserta 99% menguasai materi dan menyampaikan materi dengan baik serta mudah dimengerti.

Optimization Of Histogram Equation With The Cukcoo Algorithm to Improve Fundus Image Quatlity Dafwen Toresa; Keumala Anggraini; Pandu Pratama Putra; Edriyansyah Edriyansyah; Taslim Taslim
Jurnal CoreIT: Jurnal Hasil Penelitian Ilmu Komputer dan Teknologi Informasi Vol 9, No 1 (2023): June 2023
Publisher : Fakultas Sains dan Teknologi, Universitas Islam Negeri Sultan Syarif Kasim Riau

This study discusses strategies for identifying Diabetic Retinopathy (DR) using fundus images and the efficiency of image pre-processing techniques to improve their quality. Fundus images in medical image processing often experience problems with non-uniform lighting, low contrast, and noise, thus requiring pre-processing of images to improve their quality. This study evaluates the effectiveness of standard histogram equation techniques and optimized histogram equations with cukkoo optimization in order to choose the best technique to improve fundus image quality to identify DR. The proposed technique to produce better image quality improvements will be tested in several performance metrics, such as NIQE, PSNR, and Entropy. the results of this study, the average PNSR before optimization was 50,8, whereas after optimization it became 49,8239. The average entropy before optimization is 4.5514, while after optimization it becomes 3.8577. The average NIQE before optimization was 3,4046, while after optimization it was 4,73. In general, the results of this study indicate that the quality of the fundus image is better using the histogram equation before optimization than after optimization. In other words, Cukcoo optimization is not suitable for increasing the performance of the histogram equation in improving fundus image quality

Perbandingan Metode Peningkatan Gambar untuk Skrining Retinopati Diabetik Dafwen Toresa; Fana Wiza; Keumala Anggraini; Taslim Taslim; Edriyansyah; Lisnawita Lisnawita
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 7 No 5 (2023): October 2023
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v7i5.5193

The most common factor contributing to visual abnormalities that result in blindness is known as diabetic retinopathy (DR). Retinal fundus scanning, a non-invasive method that is integral to the picture pre-processing phase, can be used to identify and monitor DR. Low intensity, irregular lighting, and inhomogeneous color are some of the main issues with DR fundus photographs. Analysis of aberrant characteristics on retinal fundus images to identify diabetic retinopathy is one of the key responsibilities of image enhancement. However, a variety of approaches have been created and it is unknown whether one is best suited for use with images of the retinal fundus. This study investigated various image enhancement methods in order to see aberrant abnormalities on retinal fundus pictures more clearly. This study investigated various image enhancement methods in order to see aberrant abnormalities on retinal fundus pictures more clearly. The contrast-limited adaptive histogram equalization (CLAHE) method, the gray-level slicing method, the median filtering method, and the low light method are image improvement methods used to enhance images of the retinal fundus. The parameters Natural Image Quality Evaluator (NIQE), Mean Squared Error (MSE), Peak Signal-to-Noise Ratio (PSNR), and entropy will be used to assess each image enhancement technique's performance. An ophthalmologist from Sains University Hospital (HUSM) provided the image data. The findings indicate that while each technique has its own benefits, the CLAHE technique, with a standard deviation MSE of 0.0004, is the best.

Klasifikasi Kematangan Buah Kelapa Sawit Berdasarkan Warna Menggunakan Metode K-Nearest Neighbor Nova Elija Barutu; Dafwen Toresa
IndoAI: Journal of Artificial Intelligence and Computational Logic Vol. 1 No. 1 (2026): IndoAI: Journal of Artificial Intelligence and Computational Logic
Publisher : IndoAI: Journal of Artificial Intelligence and Computational Logic

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

The K-Nearest Neighbor (K-NN) algorithm is a simple machine learning algorithm used for classification and regression. This study aims to implement the K-NN algorithm in classifying the ripeness level of oil palm fruit based on color. The data used consisted of 270 images of dura, tenera, and pisifera oil palm fruits taken using a smartphone camera. The results showed that the K value in the K-NN algorithm plays an important role in determining the classification performance. With K = 3, the model achieved the highest accuracy of 93.67%, while the lowest accuracy was 80.05% with a value of K = 25. Compared to previous studies that obtained the highest accuracy of 92% at K = 7, this study shows an increase in classification performance. Classification data analysis showed that 56 image data were correctly classified and 25 image data were incorrectly classified from a total of 81 test image data. This study proves that K-NN with RGB color images can be effectively used for classification of the ripeness level of oil palm fruit.

Pelatihan keakuratan Pengucapan Bahasa Inggris Menggunakan Website Automatic Speech Recognition Indah (ASRI) Siswa Siswi SMK Muhammadiyah 3 Indah Muzdalifah; Dafwen Toresa; Fana Wiza; Asma Alhusna
JCoos: Journal of Community Outreach in Science & Society Vol. 1 No. 1 (2026): Journal of Community Outreach in Science & Society (JCoos)
Publisher : JCoos: Journal of Community Outreach in Science & Society

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

This service activity aims to improve students' English pronunciation skills through the Automatic Speech Recognition Indah (ASRI) website. The platform offers interactive learning with automatic feedback to help students improve pronunciation, especially difficult consonant sounds like /ð/. Students are trained to pronounce various consonant sounds and are directly evaluated by ASRI. The results showed that the sounds /k/ and /dʒ/ were the easiest to pronounce (23/24 correct questions), followed by /tʃ/ and /θ/ (17 and 16), while /g/ (15) and /ð/ (12) were the biggest challenges. The use of ASRI has been shown to help identify specific errors and encourage consistent self-paced learning. Although its effectiveness depends on the difficulty of the sound, regular practice and feedback features from ASRI are expected to improve pronunciation accuracy significantly.

Co-Authors Ahmad Ade Irwanda Ahmad Ade Irwanda Ahmad Zamsuri, Ahmad Asma Alhusna Bayu Febriadi, Bayu Deny Jollyta Des Suryani Edriyansyah Fajrizal Fajrizal, Fajrizal Fana Wiza, Fana Febi Yanto Fuad Renadi Ikhsan Hidayat Keumala Anggraini Lisnawita Lisnawita Musfawati Muzdalifah, Indah Nori Sahrun Nova Elija Barutu Nurfika Sari Pandu Pratama Putra, Pandu Pratama Puspita Sari Rometdo Muzawi RR. Ella Evrita Hestiandari Sabna, Eka Sularno Susi Handayani Syahtriatna Djusar Taslim Malano Taslim Malano Taslim Taslim Taslim Wenti Sasparita Abiyus Wenti Sasrapita Abiyus Yogi Ersan Fadrial Yogi Yunefri, Yogi Yuhelmi Yuhelmi

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