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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

Author-ID : 6052120

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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Simulasi dalam Optimalisasi Pengadaan Barang menggunakan Metode K-Mean Clustering Indah Savitri Hidayat; Sarjon Defit; Gunadi Widi Nurcahyo
Jurnal Sistim Informasi dan Teknologi 2021, Vol. 3, No. 4
Publisher : Rektorat Universitas Putra Indonesia YPTK Padang

Products provided by a store have an influence on store sales. Consumers will be attracted to stores that provide products according to their wants and needs. The purpose of this research is to find out what ornamental flower products are most in demand by consumers, in demand by consumers and less desirable to consumers. Keywords: inventory of goods, K-Mean Clustering, Data Mining, cluster, optimal. Store managers can get information about goods that have been depleted of inventory stock to be updated immediately. The method used in this study is the K-Mean Clustering method which belongs to one of the branches of Data Mining. The data used in the study is data from January 2020 to December 2020 as many as 100 pieces taken from naafilah official shop, Padang. The data variables used in the entry of goods are the year, product name, price and amount sold. Furthermore, the data is processed using Rapid Miner software. The first stage of processing is to determine the value of clusters randomly, in this study researchers divided the cluster values into 3 groups. Next, the centroid value of each group will be determined. Centroid is derived from the minimum value, middle value and maximum value of the data provided. Then, the cluster process is calculated using the euclidean distance formula. Cluster calculations are done by calculating the closest distance to the data. The final result of this study is to find out the best-selling, best-selling and less-selling ornamental flowers, so that sellers can optimize the provision of ornamental flowers for the future.

Sistem Pakar dalam Mendiagnosis Gizi Buruk pada Balita dengan Menggunakan Metode CBR Sandi Alam; Gunadi Widi Nurcahyo
Jurnal Sistim Informasi dan Teknologi 2022, Vol. 4, No. 4
Publisher : Rektorat Universitas Putra Indonesia YPTK Padang

Limited information makes people have little knowledge of the early symptoms of Malnutrition in Toddlers. This disease must be treated quickly from an early age otherwise it will not get worse. This study aims to accurately diagnose the symptoms to provide fast, precise and accurate information in classifying the types of Malnutrition in Toddlers. This research is an expert system using Case Based Reasoning (CBR) method. The CBR method makes decisions from new cases based on solutions from previous cases. The data processed were 22 symptoms and 8 types of disease for 22 cases. The accuracy results are very good by being able to identify all types of malnutrition. So that this research can be used as a recommendation in speed to identify malnutrition in toddlers quickly.

Sistem Pendukung Keputusan Menggunakan Metode Multi Attribute Utility Theory Untuk Pemilihan Layanan Digital Ira Nia Sanita; Sarjon Defit; Gunadi Widi Nurcahyo
Computer Science and Information Technology Vol 4 No 1 (2023): Jurnal Computer Science and Information Technology (CoSciTech)
Publisher : Universitas Muhammadiyah Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/coscitech.v4i1.4742

Dinas Komunikasi, Informatika dan Statistik (Kominfotik) Provinsi Sumatera Barat merupakan Dinas yang diberi kewenangan untuk membangun dan mengembangkan layanan digital untuk semua Perangkat Daerah di Pemerintah Provinsi Sumatera Barat. Seluruh Perangkat Daerah dapat mengajukan permintaan pembangunan layanan digital ke Dinas Kominfotik. Akan tetapi, tidak semua layanan digital yang diminta akan difasilitasi dan diakomodir oleh Dinas Kominfotik. Ada beberapa kriteria pemilihan dalam pembangunan Layanan Digital yaitu Layanan Digital yang sesuai dengan Arsitektur Sistem Pemerintahan Berbasis Elektronik (SPBE) Nasional, mendukung Program Unggulan Pemerintahan Provinsi Sumbar, Quick Win Layanan sesuai Peta Rencana SPBE, tujuan pembuatan layanan digital, serta Bahasa Pemograman yang digunakan dalam pembangunan Aplikasi. Penelitian ini menggunakan metoda Multi Attribute Utility Theory (MAUT). Metode MAUT digunakan untuk menentukan pemilihan layanan digital yang akan dibangun berdasarkan bobot dan kriteria yang sudah ditentukan. Kemudian dilakukan proses perankingan yang akan menentukan pilihan yang menjadi prioritas. Dan dari hasil pengujiannya didapatkan penerapan metode MAUT pada Sistem Pendukung Keputusan pemilihan layanan digital menghasilkan alternatif yang menjadi prioritas (rangking 1) adalah Layanan Penerimaan Peserta Didik Baru (PPDB) dengan nilai 0,933. Kata Kunci : Sistem Pendukung Keputusan, Layanan Digital, Multi Attribute Utility Theory (MAUT)

Sistem pendukung keputusan menggunakan metode analytical hierarchy process (ahp) dalam penentuan kualitas bibit cabai DWI JULISA UTARI; Gunadi Widi Nurcahyo; Yuhandri Yunus
Computer Science and Information Technology Vol 4 No 1 (2023): Jurnal Computer Science and Information Technology (CoSciTech)
Publisher : Universitas Muhammadiyah Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/coscitech.v4i1.4743

The system is a network of procedures made according to an integrated pattern to carry out the main activities of a company in which there is an information system which is interconnected with one another which ultimately produces information/data that is useful for the intended person according to its designation. Today's Decision Support Systems (DSS) have assisted an organization in helping make important decisions in various sectors. One of them is the agricultural sector. Chili is a horticultural crop that is widely grown by farmers and the community, one of these plants is used as an ingredient for cooking. The purpose of this research is to provide convenience in determining the quality of chili seeds to farmers and the community. The data processed in this study were 5 criteria and 6 alternatives. Data on the quality of chili seeds obtained from the TPHP Office of Sungai Penuh City. The data is processed first, calculated manually and followed by applying calculations from the Analytical Hierarchy Process method. The processing steps determine the weight of each criterion, assign a score (paired comparison), summarize all scores (total weight). During data processing, the level of accuracy is still calculated. The result of testing this method is that the calculation of chili seeds has an accuracy of 83% based on the quality level of the specified criteria. Specifically, the testing decision support system is able to identify the quality of chili seeds. The level of accuracy achieved by the analytical hierarchy process is quite accurate and can help farmers and the community.

Perbandingan algoritma c4.5 dan naive bayes dalam prediksi kelulusan mahasiswa Rovidatul; Yuhandri Yunus; Gunadi Widi Nurcahyo
Computer Science and Information Technology Vol 4 No 1 (2023): Jurnal Computer Science and Information Technology (CoSciTech)
Publisher : Universitas Muhammadiyah Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/coscitech.v4i1.4755

College management requires graduation predictions to determine early prevention measures for drop out cases. The length of a student's study period can be caused by various factors, so it is necessary to know which students have the potential to graduate not on time. Data mining techniques can be used to explore new knowledge so that it can produce predictions of student graduation. Some algorithms that can be used are C4.5 and Naive Bayes. The purpose of this study was to predict the graduation of students from the Faculty of Social and Political Sciences at Andalas University using the C4.5 and Naive Bayes algorithms. The attributes used are age at college, gender, grade point average 1-4. The data used are FISIP undergraduate students who graduated in 2022 as many as 378. The results show that the accuracy of the Naive Bayes algorithm is better than C4.5 with the highest accuracy of 81.58%.

Analisis Penggunaan Metode Port Knocking pada Sistem Keamanan Jaringan Komputer (Studi Kasus di Universitas Baiturrahmah) Roby Nurbahri; Yuhandri; Gunadi Widi Nurcahyo
Jurnal Sistim Informasi dan Teknologi 2023, Vol. 5, No. 1
Publisher : SEULANGA SYSTEM PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/jsisfotek.v5i1.211

Sistem keamanan jaringan digunakan untuk mencegah dan mengidentifikasi masuk pengguna yang tidak sah (penyusup) di jaringan komputer. Tujuannya adalah untuk mengantisipasi bahaya jaringan komputer, yang berupa ancaman fisik atau logik. Ancaman fisik adalah ancaman yang merusak komponen fisik atau perangkat keras komputer, sedangkan ancaman logik meliputi pencurian data atau peretasan akun. Pihak-pihak yang tidak dapat dipercaya dapat menyalahgunakan akses ke sistem keamanan yang tidak dieksploitasi secara maksimal dan menimbulkan risiko yang signifikan. Serangan terhadap keamanan jaringan dilakukan dengan terlebih dahulu mempelajari detail port yang terbuka, kemudian memanfaatkannya. Mayoritas cracker menggunakan sistem port terbuka untuk menyerang sistem jaringan. sebagai ilustrasi, Serangan Dos atau ddos yang menargetkan host atau komputer target dengan sejumlah besar paket yang datang dari beragam host.. Dalam hal ini cracker perlu mengetahui port yang terbuka dan target agar serangan ini berhasil. Serangan masuk lewat celah terbuka di jaringan komputer, salah satunya adalah port yang terbuka, sehingga memungkinkan pengguna internet yang tidak memiliki izin akses atau yang tidak berkepentingan dapat dengan mudah mengelola port-port yang terbukaIde di balik metode port-knocking adalah menyembunyikan layanan jarak jauh di balik Firewall dan hanya mengizinkan akses ke port tersebut ketika klien dapat diautentikasi ke firewall. Hal ini dapat bertindak sebagai pencegah serangan zero-day dan membantu mencegah pemindai menemukan service yang tersedia dan dapat diakses pada host. Dalam hal ini blocking port dapat melindungi firewall dari pemindai.

The Implementation of Artificial Neural Networks to measure the correlation of teacher's workload to the number of own learning media Erizke Aulya Pasel; Yuhandri Yuhandri; Gunadi Widi Nurcahyo Nurcahyo
Computer Science and Information Technology Vol 4 No 1 (2023): Jurnal Computer Science and Information Technology (CoSciTech)
Publisher : Universitas Muhammadiyah Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/coscitech.v4i1.4757

The use of learning media in the teaching and learning process is an effort to increase the effectiveness and quality of the learning process. However, the need for learning media is not compatible with the number of learning media made by the teacher himself. One of the factors that causes it is the teacher's workload which is quite a lot so that the teacher does not have enough time to make his own learning media. This study aims to measure the extent of the correlation between the teacher's workload and the amount of instructional media that the teacher himself made. Artificial Neural Network with Backpropagation method is a tool that can be used to solve complex problems, one of which is to measure the level of correlation. The ability of an Artificial Neural Network with the Backpropagation method to adapt to changes that occur in the input and output values makes the prediction accuracy quite high. The teacher's workload variables used are the number of face-to-face hours of even and odd semesters, additional assignments (deputy principal/head of laboratory), homeroom teacher, and extracurricular coaches. The target used is the number of learning media made by the teacher himself. The data used in this study were taken from the workload of teachers at SMAN 4 Payakumbuh in 2022. The architectural patterns used are 5-4-1, 5-5-1, 5-7-1, 5-10-1, and 5- 12-1. From the test results with the Matlab R2013a software, the best pattern was obtained, namely the 5-12-1 pattern with an MSE value of 0.1001, a MAPE of 2.11, and a data accuracy of 97.89%. From the results of the training and testing, it was concluded that the correlation between the teacher's workload and the amount of self-made learning media is very low or not closely related.

ALGORITMA C4.5 UNTUK PREDIKSI BIMBINGAN SISWA BERDASARKAN TIPOLOGI HIPPOCRATES-GALENUS Boy Sandy Dwi Nugraha.H; Sarjon Defit; Gunadi Widi Nurcahyo
Jurnal Teknoif Teknik Informatika Institut Teknologi Padang Vol 11 No 1 (2023): TEKNOIF APRIL 2023
Publisher : ITP Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21063/jtif.2023.V11.1.1-8

The type of personality possessed by a student belived affect their behavior, whether positively or negatively, and if left unattended, it will harm the student. Student guidance is necessary to provide appropriate guidance for the student. This study aims to predict student guidance based on personality by using student data at SMP 1 Negeri Tembilahan. The data collection process was obtained from the BK teacher at SMPN 1 Tembilahan for grade 8 and grade 7. Grade 8 will be used as training data and grade 7 will be used as testing data. 5 parameters were selected for the prediction process and 1 label as the target class. The method used is the C4.5 algorithm to build a decision tree and obtain prediction rules. The results of the study were obtained using Confusion Matrix testing with a prediction accuracy rate of 70%. The ultimate goal of the student guidance prediction process is to have a higher percentage of "Yes" (need guidance) than "No" (don't need guidance) in the prediction results. Therefore, it can be stated that the prediction process model with the C4.5 algorithm is suitable for determining good decision-making results in terms of prediction, and the researcher hopes that after obtaining these results, the BK teacher at SMPN 1 Tembilahan can provide guidance as soon as possible and provide necessary guidance to students who need it.

Classification of Multiple Emotions in Indonesian Text Using The K-Nearest Neighbor Method Ahmad Zamsuri; Sarjon Defit; Gunadi Widi Nurcahyo
Journal of Applied Engineering and Technological Science (JAETS) Vol. 4 No. 2 (2023): Journal of Applied Engineering and Technological Science (JAETS)
Publisher : Yayasan Riset dan Pengembangan Intelektual (YRPI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37385/jaets.v4i2.1964

Emotions are expressions manifested by individuals in response to what they see or experience. In this study, emotions were examined through individuals' tweets regarding the election issues in Indonesia in 2024. The collected tweets were then labeled based on emotions using the emotion wheel, which consisted of six categories: joy, love, surprise, anger, fear, and sadness. After the labeling process, the next step involved weighting using TF-IDF (Term Frequency-Inverse Document Frequency) and Bag-of-Words (BoW) techniques. Subsequently, the model was evaluated using the K-Nearest Neighbor (KNN) algorithm with three different data splitting ratios: 80:20, 70:30, and 60:40. From the six labels used in the modeling process, the accuracy was then calculated, and the labels were subsequently merged into positive and negative categories. Then the modeling was conducted using the same process with the six labels. The results of this study revealed that the utilization of TF-IDF outperformed BoW. The highest accuracy was achieved with the 80:20 data splitting ratio, attaining 58% accuracy for the six-label classification and 79% accuracy for the two-label classification

Algoritma K-Means Clustering Penggunaan Bandwidth Internet (Studi Kasus di Pemerintah Daerah Kabupaten Padang Pariaman) Rizki Mubarak; Sarjon Defit; Gunadi Widi Nurcahyo
Explore: Jurnal Sistem Informasi dan Telematika (Telekomunikasi, Multimedia dan Informatika) Vol 14, No 1 (2023): Juni
Publisher : Universitas Bandar Lampung (UBL)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36448/jsit.v14i1.3037

Untuk menunjang kegiatan di Pemerintahan dibutuhkan koneksi jaringan yang yang cepat dan tepat. Sehingga memerlukan jaringan bandwith yang lebar. Manajemen Bandwidth perlu dilakukan agar kecepatan jaringan tetap stabil. Penelitian ini bertujuan untuk melihat pola penggunaan bandwidth di Pemerintah Daerah Kabupaten Padang Pariaman menggunakan K-Means Clustering. Data diambil dari aplikasi Cacti sebuah software open-source, pemantauan jaringan berbasis web. Total datasets hasil ekstraksi yang digunakan adalah sebanyak 32 data OPD (Organisasi Perangkat Daerah) yang ada di Pemerintah Daerah Kabupaten Padang Pariaman tahun 2022.. Data-data yang tersedia selanjutnya diolah untuk mendapatkan target cluster dengan memanfaatkan konsep data mining menggunakan metode K-Mean Clustering. Pengelompokan data pengunaan bandwidth di Kabupaten Padang Pariaman menggunakan metode Clustering dengan algoritma K-Means dengan atribut Nama OPD, Inbound Average, Inbound Maksimum, Outbound Average, Outbound Maximum yang digunakan dalam proses perhitungan dan pembagian data ke dalam 3 cluster dengan kategori penggunaan bandwidth tinggi, rendah, dan sedang. Perhitungan dilakukan secara manual dan kemudian dilakukan pengujian dengan software RapidMiner. Hasil dari perhitungan manual diperoleh jumlah anggota cluster yang sama dengan perhitungan dengan software RapidMiner.

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

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