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All Journal International Journal of Electrical and Computer Engineering Elektron Jurnal Ilmiah TELKOMNIKA (Telecommunication Computing Electronics and Control) Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) Explore: Jurnal Sistem Informasi dan Telematika (Telekomunikasi, Multimedia dan Informatika) SITEKIN: Jurnal Sains, Teknologi dan Industri Riau Journal of Computer Science JOIV : International Journal on Informatics Visualization Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Jurnal Komputer Terapan Jurnal Mantik Penusa Rang Teknik Journal Digital Zone: Jurnal Teknologi Informasi dan Komunikasi Jurnal Teknologi Informasi dan Pendidikan Systematics Jurnal Teknologi Dan Sistem Informasi Bisnis Jurnal Sistem informasi dan informatika (SIMIKA) Jurnal Sistim Informasi dan Teknologi Jurnal Informasi dan Teknologi Jurnal Informatika Ekonomi Bisnis Journal of Applied Engineering and Technological Science (JAETS) JSR : Jaringan Sistem Informasi Robotik Jurnal Teknik Informatika C.I.T. Medicom Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Journal of Applied Data Sciences Jurnal Computer Science and Information Technology (CoSciTech) Journal of Computer Scine and Information Technology Jurnal Teknoif Teknik Informatika Institut Teknologi Padang Jurnal Komtekinfo Jurnal Sistim Informasi dan Teknologi Innovative: Journal Of Social Science Research Jurnal Informatika Ekonomi Bisnis RJOCS (Riau Journal of Computer Science) Jurnal Elektronika dan Teknik Informatika Terapan Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen)
Gunadi Widi Nurcahyo
Universitas Putra Indonesia YPTK Padang
Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Public Health Other

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Kompetensi yang Optimal Terhadap Penilaian Kinerja Guru dengan Metode Simple Additive Weighting Alfarisdon, A; Sumijan, S; Nurcahyo, Gunadi Widi
Jurnal Sistim Informasi dan Teknologi 2021, Vol. 3, No. 3
Publisher : Rektorat Universitas Putra Indonesia YPTK Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/jsisfotek.v3i3.154

Abstract

Professional teachers should be able to improve their quality to achieve the vision and mission of the school where the teacher is carrying out their duty. The main task of an educator is to provide students with the process of learning, educating, training and giving directions to create a better learning process. Besides carrying out the task of teaching, an educator also needs to be able to develop themselves sustainably in order to increase self-competencies. There are four competencies should be owned by an educator they are pedagogic, personality, social and professional. To measure those competencies, school head master have to conduct teacher assessment by pointed assessors. Teacher performance assessment functions to analyses teachers ' professionalism in learning processes at a school, teachers participation on self-empowerment activities as well as capacity building. This study aims to calculate the value of teacher performance assessment optimally based on competence through a decision support system. Simple Additive Weighting method is used in this decision support system. By using Simple additive weighting, the sum of weight ratings performance on each alternative in all the attributes can be collected. This decision support system used to make it easier to take a decision and a supporter of decision in performance evaluations. Dataset treat in this research was collected in SMP Negeri 25 Padang. The data consisting of four different criteria in accordance with teacher competence. The result of the study reaches the level of accuracy of 93%. This study is expected to bring benefits for school leaders as the reference in order to optimize the teacher performance evaluation objectively.
Sistem Pakar dalam Menganalisis Defisiensi Nutrisi Tanaman Hidroponik Menggunakan Metode Certainty Factor Febrina, Yerri Kurnia; Defit, Sarjon; Nurcahyo, Gunadi Widi
Jurnal Sistim Informasi dan Teknologi 2021, Vol. 3, No. 4 (Accepted)
Publisher : Rektorat Universitas Putra Indonesia YPTK Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/jsisfotek.v3i4.170

Abstract

Saat ini sistem Pakar telah menjadi bidang penelitian bagi ilmuwan komputer juga ilmuwan pertanian untuk aplikasi dalam berbagai pengembangan informasi. Sistem Pakar dapat dirancang untuk mensimulasikan satu atau lebih dari cara seorang ahli pertanian menggunakan pengetahuan dan pengalamannya dalam membuat diagnosis dan meneruskan rekomendasi yang diperlukan terkait defisiensi nutrisi. Defesiensi nutrisi adalah kekurangan bahan makanan untuk kelangsungan hidup pada tanaman. Kandungan hara pada bagian tanaman, terutama didaun, sangat relevan digunakan untuk mengidentifikasi defisiensi nutrisi. Memberikan hasil diagnosis defisiensi nutrisi kepada petani untuk dapat menjadi patokan perbaikan hara tanaman serta pemberian nutrisi yang baik untuk tanaman hidroponik. Data yang digunakan adalah data defisiensi nutrisi dan gejala serta solusi pemberian nutrisi yang diperoleh dari data petani pada Dinas Pertanian Kota Payakumbuh. Metode yang dipakai dalam system pakar ini adalah metode Certainty Factor (CF). Metode ini memberikan diagnosis berupa kepastian atau ketidakpastian kondisi dalam rule yang digunakan untuk menyimpulkan. Hasil dari pengujian terhadap metode ini menunjukan sebanyak 12 defisiensi nutrisi yang terdeteksi dengan 41 gejala yang dialami. Sehingga dapat mengukur tingkat defisiensi nutrisi yang terjadi. Sistem Pakar dalam Menganalisis Defisiensi Nutrisi Tanaman Hidroponik Menggunakan Metode Certainty Factor dapat menunjukkan bahwa prediksi hamper 94% akurat.
Sistem Pakar dalam Mengidentifikasi Gejala Stroke Menggunakan Metode Naive Bayes Karim, Fajri; Nurcahyo, Gunadi Widi; Sumijan, S
Jurnal Sistim Informasi dan Teknologi 2021, Vol. 3, No. 4 (Accepted)
Publisher : Rektorat Universitas Putra Indonesia YPTK Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/jsisfotek.v3i4.173

Abstract

Stroke is a disease caused by brain damage caused by disruption of the blood supply to the brain. At this time in general, people are still not very familiar with how this stroke disease or do not realize the symptoms that may have appeared from the start. People also tend to be hesitant to visit the hospital to check their symptoms and feel they are delaying further examinations. This is certainly a scourge that continues to make the number of strokes increase. In assisting the community in identifying stroke disease, an expert system is needed that is able to identify the type of stroke based on the symptoms felt. The data used in this study were obtained from Brain Hospital. Dr. Drs. M. Hatta Bukittinggi which was later developed into a website-based system using the PHP Framework Laravel programming language and MySQL as the database. The system is built based on the Naive Bayes method which is one of the Expert System methods that has a high accuracy value. The use of this system is expected to be able to provide knowledge to the public about the symptoms that might lead to what type of stroke the user might suffer, so that the user can use the results of the system as a reference to visit the hospital and immediately get more targeted help. This system can perform calculations that match the results of the doctor's diagnosis with an accuracy value of 100% in identifying the type of stroke from 10 data samples used.
TEXT MINING DALAM MEMBANDINGKAN METODE NAÏVE BAYES DENGAN C.45 DALAM MENGIDENTIFIKASI BERITA HOAX PADA MEDIA SOSIAL Handika, Yola Tri; Defit, Sarjon; Nurcahyo, Gunadi Widi
Rang Teknik Journal Vol 5, No 1 (2022): Vol. 5 No. 1 Januari 2022
Publisher : Fakultas Teknik Universitas Muhammadiyah Sumatera Barat

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (243.712 KB) | DOI: 10.31869/rtj.v5i1.2855

Abstract

Hoax news (hocus to trick) has a very big influence in disseminating information, especially in the world of social media. News has an important impact on social and political conditions, and news can move the economy of a country. For this reason, it is necessary to have an analysis to classify hoax news and not hoaxes, and have high accuracy in classifying the news. In this study, two methods were used as a comparison in achieving high accuracy, namely the Naïve Bayes method which is famous for having high accuracy in classification with little data, and the C.45 method which can minimize noise in the data. The data used are 300 articles with 10 topics which contain hoax and non-hoax news. The data is obtained from the internet through social media, such as Twitter, Instagram and Facebook. Testing using the Naïve Bayes method has a higher accuracy than the C.45 method. The amount of data used has a major influence on the test results, if more data enters the training stage, then this study will have higher accuracy. However, the results of this test can be recommended to increase accuracy in the construction of a hoax news detection system.
Enlarge Medical Image using Line-Column Interpolation (LCI) Method Jufriadif Na'am; Julius Santony; Yuhandri Yuhandri; Sumijan Sumijan; Gunadi Widi Nurcahyo
International Journal of Electrical and Computer Engineering (IJECE) Vol 8, No 5: October 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (548.955 KB) | DOI: 10.11591/ijece.v8i5.pp3620-3626

Abstract

Quality of medical image has an important role in constructing right medical diagnosis. This paper recommends a method to improve the quality of medical images by increasing the size of the image pixels. By increasing the size of pixels, the size of the objects contained therein is also greater, making it easier to observe. In this study medical images of Brain CT-Scan, Chest X-Ray and Panoramic X-Ray were processed using Line-Column Interpolation (LCI) Method. The results of the treatment are then compared to Nearest Neighbor Interpolation (NNI), Bilinear Interpolation (BLI) and Bicubic Interpolation (BCI) processing results. The experiment shows that Line-Column Interpolation Method produces a larger image with details of the objects in it are not blurred and has equal visual effects. Thus, this method is expected to be a reference material in enlarging the size of the medical image for ease in clinical analysis.
Detection of Infiltrate on Infant Chest X-Ray Jufriadif Na'am; Johan Harlan; Gunadi Widi Nurcahyo; Syafri Arlis; Sahari Sahari; Mardison Mardison; Larissa Navia Rani
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 15, No 4: December 2017
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v15i4.3163

Abstract

Currently, Chest X-ray is still widely used around the world for disease examination. This is due to its low cost, low radiation and a lot of disease information. The commonly detected disease using chest x-rays is lung disease. The characteristic of this disease is infiltrate. However, the accuracy of Chest X-ray observations is still low. Therefore, this research offers a method to perform Chest X-ray image processing in clarifying the information contained therein. This research used Chest X-ray of infant patients who treated at Central Public Hospital (RSUP) Dr. M. Djamil Padang. The total of the images tested were 17 images. In these images, there were some suspected infiltrates after being analyzed by doctors. Software used was Matlab which is conducted by applying image processing method. The method used consisted of 4 parts, that was Cropping, Filtering, Detecting Edge, and Sharpening Edge. The results of the research showed that the method could clarify edge detection of the objects contained in the image, so that the infiltrate could be more easily recognized. With this easiness, it will help the doctor to remove doubts for infiltrate observations in the Infant's lungs.
IMPLEMENTASI JARINGAN SYARAF TIRUAN DALAM MEMPREDIKSI FREKUENSI RESONANSI ANTENA MIKROSTRIP Khairi Budayawan; Yuhandri Yuhandri; Gunadi Widi Nurcahyo
Jurnal Teknologi Informasi dan Pendidikan Vol 12 No 1 (2019): Jurnal Teknologi Informasi dan Pendidikan
Publisher : Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/tip.v12i1.174

Abstract

The resonant frequency of an antenna is determined by the dimensional parameters and permittivity of the antenna substrate. Generally, to get the resonant frequency, a complex mathematical formula is needed to solve. For this reason, an intelligent method is offered to determine the resonant frequency more easily. In this study, an artificial neural network method with Backpropagation algorithm is used to overcome the problem. The data used were consisting of 80 training data and 15 testing data. The results have shown that the artificial neural network learning method with the backpropagation algorithm was successfully utilized to calculate the resonant frequency of microstrip antennas, where the precision of the resonant frequency obtained of 93.33% at an error of ≤ 1%, and 100% at an error of ≤ 2%.
Sistem Pakar Mengidentifikasi Penyakit Ayam Buras Menggunakan Metode Forward Chaining (Studi Kasus : Dinas Peternakan Kabupaten Pasaman Barat) Aulia Mardhatilla; Julius Santony; Gunadi Widi Nurcahyo
Jurnal Teknologi Dan Sistem Informasi Bisnis Vol 2 No 2 (2020): Juli 2020
Publisher : Prodi Sistem Informasi Universitas Dharma Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47233/jteksis.v2i2.146

Abstract

Sistem pakar (Artifical Intelligence) merupakan aplikasi berbasis komputer yang digunakan untuk menyelesaikan masalah sebagaimana yang dipikirkan oleh para pakar, salah satu penerapan sistem pakar adalah dalam mengidentifikasi penyakit ayam. Menurunnya produksi telur ayam dipengaruhi oleh beberapa faktor diantaranya umur, musim, penyakit, dan sistem pemeliharaan. Minimnya pengetahuan tentang penyakit dan penyebaran dokter hewan yang tidak merata, maka diperlukan suatu sistem yang dapat memberikan rekomendasi tentang penyakit ayam buras. Data penyakit ayam buras yang diolah dalam penelitian ini bersumber dari Dinas Peternakan Kabupaten Pasaman Barat.
Sistem Pakar Menggunakan Metode Certainty Factor untuk Mengidentifikasi Penyakit pada Hewan Peliharaan Fortia Magfira; Gunadi Widi Nurcahyo
Jurnal Informasi dan Teknologi 2020, Vol. 2, No. 3
Publisher : SEULANGA SYSTEM PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/jidt.v2i3.68

Abstract

Large domesticated types of ruminants such as goats, buffalo and cows are animals that are commonly kept and used as food sources and as assistants to human work in rural areas. Knowledge about pets, especially animal health, is something owners really need to keep their pets healthy. The owner's lack of knowledge about diseases and early handling of diseases in pets and the difficulty of seeing a veterinarian in urgent situations prevent pets from getting proper first aid. This study aims to identify the types of diseases suffered by pets based on the symptoms experienced by pets precisely. The method used is themethod Certainty Factor to accommodate the uncertainty of an expert's thinking on 12 diseases and 47 disease symptoms in pets. The results of this study can identify diseases in pets and produce certainty values ​​for the types of diseases in the form of diseases suffered by pets. So that this research can be a reference in identifying diseases in pets and providing knowledge to owners about first aid and disease management in pets.
Sistem Pakar Menggunakan Metode Certainty Factor dalam Akurasi Mengidentifikasi Penyakit Gingivitis pada Manusia Cyntia Lasmi Andesti; Sumijan Sumijan; Gunadi Widi Nurcahyo
Jurnal Informasi dan Teknologi 2020, Vol. 2, No. 3
Publisher : SEULANGA SYSTEM PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/jidt.v2i3.69

Abstract

Gingivitis is a common inflammatory disease of the gums, which is a condition where bacteria develop in the mouth that causes damage to the connective tissue cells that are attached to the teeth. Lack of awareness in caring for teeth will have a negative impact not only on dental health but also on the health of the body. At present many people do not know how to accurately identify gingivitis in humans so that the condition is worsened and can even cause the paralysis of the existing connective tissue. This study aims to determine the level of accuracy in identifying gingivitis by using the Certainty Factor method precisely and accurately. The data processed in this study are fifty data sourced from expert interviews at Rahmatan Lil Alamin Clinic, Padang Indonesia. There are several types Symptoms refer to gingivitis in humans. The data is obtained from the results of medical records of patients who carry out examinations in the clinic. The data will be processed to identify the type of gingivitis based on the direction of the expert. The processing steps are solving rules, determining the weight value of each symptom and calculating the Certainty Factor value. The results of the processing were continued by calculating the level of accuracy. The results of the testing of this method were that 96% of them had gingivitis, the type most often suffered by marginal gingivitis patients. Based on the signs entered by the user. The results of this test have been able to specifically identify gingivitis, using the Certainty Factor method, the results of the accuracy level obtained are quite accurate and can be recommended to help dentists improve their accuracy in identifying gingivitis in humans.
Co-Authors A Alfarisdon AA Sudharmawan, AA Abdi Rahim Damanik Afifah Cahayani Adha Afriosa Syawitri Agung Ramadhanu Ahmad Zamsuri, Ahmad Alexyusandria alexyusandria Alfarisdon, A Ali Djamhuri Andi, Muhammad Yusril Haffandi Anggraini, Siska Dwi Anita Sindar Apriade Voutama Ardia Ovidius ardialis Asyhari, Ahmad Aulia Mardhatilla Ayudia, Dina Ayunda, Afifah Trista Bayu Rianto Billy Hendrik Boy Sandy Dwi Nugraha.H Breinda, Engla Budayawan, Khairi Budiarti, Lela Bufra, Fanny Septiani Candra Putra Cyntia Lasmi Andesti Cyntia Trimulia Damanik, Abdi Rahim Daniel Theodorus Darma Yunita Darmawi Darnis, Rahmi Dedi Irawan Deri Marse Putra Dina Ayudia Dinda Permata Sukma DWI JULISA UTARI Dwi Utari Iswavigra Dyan Mardinata Putra Eka Putra, Dian Elfina Novalia Erizke Aulya Pasel Faisal Roza Fajri Karim Fanny Septiani Bufra Fauzan Azim Fauzi Erwis Febriani, Widya Febrina, Yerri Kurnia Fernando Ramadhan Fitriani, Yetti Fortia Magfira Gaja, Rizqi Nusabbih Hidayatullah Hafid Dwi Adha Handika, Yola Tri Hartati, Yuli Hasni, Salmi Hazlita, H Hendrik, Billy Honestya, Gabriela Humairoh, Putri Idir Fitriyanto Idir Ilham Effendi Indah Savitri Hidayat INTAN NUR FITRIYANI Ipri Adi Ira Nia Sanita Jefri Rahmad Mulia Johan Harlan Jufri, Fikri Ramadhan Jufriadif Na`am, Jufriadif Jufriadif Na’am Juliantho, Dwana Abdi Julius Santoni Julius Santony Julius Santony Julius Santony Julius Santony Julius Santony Karim, Fajri Khelvin Ovela Putra Kholil, Muhammad Irvan Larissa Navia Rani Leony Lidya Lidia Sutra Lova Endriani Zen Lubis, Fitri Amelia Sari Lusi Kestina Luth Fimawahib M Mutia M, Mutia M. Almepal Wanda M. Ibnu Pati Mardayatmi, Suci Mardison Mardison Marfalino, Hari Meilinda Sari Meilinda Sari Melissa Triandini Miftahul Hasanah Miftahul Hasanah, Miftahul Miftahul Mardiyah Mike Zaimy Muhammad Irvan Kholil Nabila, Tuti Nadia, Nadia Aini Hafizhah Nadya Alinda Rahmi Nasution, Amir Salim Khairul Rijal Nia Nofia Mitra Nissa, Ika Ima Nst, Ely Nurhalizah Nur Azizah Nur, Rofil M Nurdini, Siti Pati, Muhammad Ibnu Pebriyanti, Defi Petti Indrayati Sijabat Puji Chairu Sabila Putra, Akmal Darman Putra, Deri Marse Putra, Dyan Mardinata Putri Humairoh Putri, Stefani Putut Wicaksono, Putut Radillah, Teuku Rafiska, Rian Rahmad Supriadi Rahman, Zumardi Ramadhanu, Agung Riati, Itin Rika Apriani Rika Apriani, Rika Ririn Violina Ritna Wahyuni Rizka Hafsari Rizki Mubarak Roby Nurbahri Roni Salambue Rovidatul Rozakh, Muhammad Rusnedy, Hidayati Rustam, Camila S Sumijan Sabil, Muhammad Sahari Sahari Sahri, Alfi Sajida, Mayang Sandi Alam Sandrawira Anggraini Sani, Rafikasani Santriawan, Aji Sari, Fitri P. Sarjon Defit Sarjon Defit Sarjon Defit Septiana Vratiwi Sharon Sintia Sintia Siregar, Fajri Marindra Sisi Hendriani Siska Dwi Anggraini Siti Nurdini Sovia, Rini Sri Handayani Sri Layli Fajri Stefani Hardiyanti Putri Suci Mardayatmi Sumijan Sumijan Sumijan Sumijan Sumijan Sumijan Sumijan Sumijan Sumijan, S Suri, Melati Rahma Sutra, Lidia Syafri Arlis Tesa Vausia Sandiva Ulfa, Ulia Ulfatun Hasanah Ulia Ulfa Verdian, Ihsan Vratiwi, Septiana W Wahyudi Wahyu, Fungki Wahyudi Wahid Wahyudi Wahyudi Wendi Robiansyah Weri Sirait Widya Febriani Yeng Primawati Yerri Kurnia Febrina Yetti Fitriani Yolla Rahmadi Helmi Yoni Aswan Yuhandri Yuhandri Yuhandri Yuhandri Yuhandri Yuhandri Yuhandri, Yuhandri Yuhandri Yunus Yuhandri, Y Yuli Hartati Yunita Cahaya Khairani Yunus, Yuhandri Yuyu, Yuhandri