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Hak Akses Menggunakan Metode Vlan Pada perpustakaan Universitas Gunung Jati Thomas Agam; Martanto; Yudhistira Arie Wijaya
KOPERTIP : Jurnal Ilmiah Manajemen Informatika dan Komputer Vol. 4 No. 3 (2020): KOPERTIP: Jurnal Ilmiah Manajemen Informatika dan Komputer
Publisher : Puslitbang Kopertip Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32485/kopertip.v4i3.150

Abstract

Perpustakaan Universitas Gunung Jati Swadaya sebagai sarana untuk memberikan pelayanan yang berkaitan dengan referensi atau bahan kajian. Terdapat fasilitas internet di perpustakaan Universitas Gunung Jati Swadaya. Pengguna internet di perpustakaan Universitas Swadaya Gunung Jati bermacam-macam, antara lain mahasiswa, staf, dosen. Masing-masing memiliki hak akses yang berbeda. Izin tiap pengguna diatur agar koneksi bisa lebih stabil karena jaringan sudah dibagi menjadi bagian-bagian kecil agar jaringan tidak terlalu sibuk. Selain itu, setiap pengguna mendapatkan kecepatan bandwidth yang berbeda tergantung pada grup mana dia berada. Salah satu cara untuk berbagi jaringan secara virtual adalah dengan menggunakan Virtual Local Area Network (VLAN). Virtual Local Area Network tidak mengubah jaringan fisik tetapi hanya mengubah jaringan virtual. Tujuan dari penelitian ini adalah untuk mengatur pembagian hak akses setiap pengguna sesuai dengan porsinya. Penelitian ini menggunakan metode implementasi Prepare Plan Design Operate Optimize (PPDIO). Tahap pertama, peneliti menyiapkan analisis kebutuhan setiap pengguna sesuai dengan hak aksesnya. Tahap kedua, peneliti melakukan perancangan topologi jaringan polos. Pada tahap ketiga, peneliti melakukan simulasi desain jaringan yang telah dibuat menggunakan proxy. Pada tahap keempat, peneliti melakukan implementasi sesuai dengan konfigurasi yang telah dilakukan. Pada tahap kelima, peneliti melakukan monitoring operasi menggunakan winbox. Tahap keenam yang peneliti lakukan adalah melakukan optimasi pengelolaan jaringan. Hasil penelitian ini menunjukkan bahwa hasil T One Sample Test menunjukkan bahwa nilai T hitung adalah 77,905 > 1,297 nilai T tabel. Dengan demikian, terdapat perbedaan yang signifikan antara peningkatan dan tidak peningkatan pengelolaan hak akses menggunakan metode VLAN. Dengan demikian dapat disimpulkan bahwa pengelolaan hak akses menggunakan metode VLAN dapat meningkatkan keamanan pada perpustakaan Universitas Swadaya Gunung Jati Cirebon.
Pemodelan Proses Bisnis Sistem Akademik Menggunakan Business Process Modeling Notation Denni Pratama; Yudhistira Arie Wijaya; Dian Ade Kurnia
Jurnal ICT: Information Communication & Technology Vol. 22 No. 2 (2022): JICT-IKMI, December 2022
Publisher : LPPM STMIK IKMI Cirebon

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

Abstract

Based on observations and interviews, paper spending at XYZ High School reaches 65% of the total monthly office stationery budget, and this has been happening since 2008. Using paper as a document carries the risk of loss and damage and is problematic when stored. Search and find again. In addition, the raw paper material is trees, which currently coincide with environmental issues. Therefore, a circular economy needs to be applied to organizations to reduce the use of single-use items. The paperless movement can be implemented to reduce the use of paper, which a digital-based system has replaced. Implementing an integrated academic system through digital media is expected to reduce paper usage and dependence at XYZ High School and make the educational system's business processes more effective and efficient. Business Process Modeling Notation (BPMN) is used to design and model the academic system business processes at XYZ College. Through this BPMN, the business processes of the XYZ High School educational system can be clearly described, including the study plan system, lecture and exam scheduling system, lecturer assignment system, and study result assessment system. With the analysis and modeling of business processes and identification of system requirements in the XYZ High School academic system, it is hoped that it can be a proposal for improvement of existing business processes and also as the basis for developing the educational system at XYZ College and developing it into a good and reliable application product
KLASIFIKASI MOTIF BATIK JAWA MENGGUNAKAN ALGORITMA K-NEAREST NEIGHBORS (KNN) MUHAMAD DENI AKBAR; Martanto Martanto; Yudhistira Arie Wijaya
JURSIMA (Jurnal Sistem Informasi dan Manajemen) Vol 10 No 2 (2022): Jursima Vol. 10 No. 2, Agustus Tahun 2022
Publisher : INSTITUT TEKNOLOGI DAN BISNIS INDOBARU NASIONAL

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47024/js.v10i2.412

Abstract

Batik is one of Indonesia's beautiful and well-known heritages throughout the world, batik as a traditional heritage of the archipelago comes with a variety of motifs. Each region has different motifs and different philosophies. The number of Indonesian batik motifs spread from Aceh to Papua, so not everyone can distinguish batik motifs. This study aims to distinguish between Javanese batik motifs and non-Javanese batik motifs. The batik motifs taken by researchers as samples from the Java region were the Mega Mendung batik motif, Lasem batik motif, Sekar Jagad batik motif, Kawung batik motifs and motifs, and for non-Javanese researchers took samples of Cendrawasih batik motifs, Dayak batik motifs, and batik motifs. nutmeg, and Balinese batik motifs. The research method uses the K-Nearest Neighbors (KNN) algorithm which has stages of collecting image on batik motifs, knowing Javanese and non-Javanese batik motifs, pre-processing, feature extraction, image classification, and evaluation of motifs. Color feature extraction is carried out using gray level co-occurrence matrix (GLCM) methods. Based on the test results show that with the application of GLCM and KNN with an image size ratio of 200x200 with a ratio of k=5 the percentage of split image 80% test and 20% training is able to produce an accuracy of 65%.
Analisis Sistem Website Sekolah Adiwiyata Menggunakan Website Quality (WEBQUAL) Muhamad Nur Fauzan; Odi Nurdiawa; Yudhistira Arie Wijaya
Jurnal Janitra Informatika dan Sistem Informasi Vol. 3 No. 1 (2023): April - Jurnal Janitra Informatika dan Sistem Informasi
Publisher : Indonesian Scientific Journal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25008/janitra.v3i1.167

Abstract

Pertumbuhan teknologi dalam pencarian data salah satunya adalah website, sebagai media yang disediakan lewat koneksi internet, dimana pengguna bisa mengakses seluruh tipe data dimanapun serta kapanpun sepanjang terkoneksi dengan jaringan internet. Web telah menjadi bagian dari organisasi nirlaba termasuk pula lembaga pemerintahan. Sistem data web Sekolah Adiwiyata Kota Cirebon dapat diakses secara publik baik oleh pihak internal sekolah maupun masyarakat luas. Permasalahan yang dibahas yaitu Bagaimana membuat dan merancang web sekolah dengan Metode Webqual 4.0” dan belum adanya system yang dapat menghasilkan informasi yang baik dan efisien sehingga perlu dibuatkan website sekolah menggunakan metode WebQual-4.0. Tujuan penelitan ini untuk menguji sejauhmana pengaruh kulaitas khasiat (Usabilitiy), Mutu Data (Information Quality), Mutu Interaksi Pelayanan (Service Interaction Quality) serta kepuasan pengguna dari totalitas (Overall Impression). Metode yang digunakan dengan pendekatan mulai pengumpulan informasi kuesioner yang dibagikan kepada responden sebanyak 200 responden juga menggunakan metode WebQual, dilanjutakan dengan Uji Regresi Linear Simpel, uji F serta uji T, apabila kuesioner tersebut belum valid dan reliabel, dilakukan kembali pengujian. namun apabila informasi sudah valid serta reliable hingga informasi tersebut layak untuk duterapkan. Hasil penelitian ini menghasilkan nilai akurasi baik usability, information quality, mutu interaksi, service interaction quality mempengaruhi terhadap kepuasan pengguna, sebesar 78,4%.
Sistem Informasi Pelayanan Surat Keterangan Desa Jalatrang Berbasis Web Fianita Rusadi; Yudhistira Arie Wijaya
Manajemen Kreatif Jurnal Vol 1 No 2 (2023): Mei : Manajemen Kreatif Jurnal
Publisher : Sekolah Tinggi Ilmu Ekonomi Trianandra

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1948.149 KB) | DOI: 10.55606/makreju.v1i2.1315

Abstract

This study aims to determine the information system service certificate for Jalatrang Village, Ciamis Regency using data collection techniques through field research, namely observation and in-depth interviews with 8 informants who were selectedqualitatively descriptively. The results show that the service information system for village certificates in ciamis district provides positive things to the village. This research was contuted by a library study, namely the collection of data and information through books and other reading sources that are relevant to the problem to be studied. Field research is data obtained by observation. The purpose of this final project is a web-Based Village Certificate Service Information System in Jalatrang Village” aims to design a database that accommodates all information about Jalatrang Village so that this information can be provided and presented more effective in terms of time and energy utilization.
KLASIFIKASI MOTIF BATIK JAWA MENGGUNAKAN ALGORITMA K-NEAREST NEIGHBORS (KNN) MUHAMAD DENI AKBAR; Martanto Martanto; Yudhistira Arie Wijaya
JURSIMA (Jurnal Sistem Informasi dan Manajemen) Vol 10 No 2 (2022): Jursima Vol. 10 No. 2, Agustus Tahun 2022
Publisher : INSTITUT TEKNOLOGI DAN BISNIS INDOBARU NASIONAL

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47024/js.v10i2.412

Abstract

Batik is one of Indonesia's beautiful and well-known heritages throughout the world, batik as a traditional heritage of the archipelago comes with a variety of motifs. Each region has different motifs and different philosophies. The number of Indonesian batik motifs spread from Aceh to Papua, so not everyone can distinguish batik motifs. This study aims to distinguish between Javanese batik motifs and non-Javanese batik motifs. The batik motifs taken by researchers as samples from the Java region were the Mega Mendung batik motif, Lasem batik motif, Sekar Jagad batik motif, Kawung batik motifs and motifs, and for non-Javanese researchers took samples of Cendrawasih batik motifs, Dayak batik motifs, and batik motifs. nutmeg, and Balinese batik motifs. The research method uses the K-Nearest Neighbors (KNN) algorithm which has stages of collecting image on batik motifs, knowing Javanese and non-Javanese batik motifs, pre-processing, feature extraction, image classification, and evaluation of motifs. Color feature extraction is carried out using gray level co-occurrence matrix (GLCM) methods. Based on the test results show that with the application of GLCM and KNN with an image size ratio of 200x200 with a ratio of k=5 the percentage of split image 80% test and 20% training is able to produce an accuracy of 65%.
Pengelompokkan Dataset Bus Menggunakan Algoritma K-Means Anjar Permadi; Yudhistira Arie Wijaya
INFORMATICS FOR EDUCATORS AND PROFESSIONAL : Journal of Informatics Vol 7 No 2 (2023): INFORMATICS FOR EDUCATORS AND PROFESSIONAL : JOURNAL OF INFORMATICS (Juni 2023)
Publisher : Lembaga Penelitian dan Pengabdian Masyarakat Universitas Bina Insani

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51211/itbi.v8i1.2259

Abstract

Data mining is the process of finding information by identifying patterns from datasets. The process of finding this information can be done by grouping data into several groups from a dataset which in data mining is called the clustering method. Clustering is the process of partitioning a dataset into several subsets or groups based on the similarity of the characteristics of each data in the existing groups. The clustering method used in this research is K-Means which belongs to the Partition Clustering algorithm group. This method has also been widely used in solving problems related to sales clustering, forest fires, agriculture, transportation, and so on. In this study, the k-means algorithm was used to classify the Bus BB dataset based on data collected during 2022. In the process of converting raw datasets into useful information, the Knowledge Discovery in Database (KDD) process was used. In the early stages, data cleaning will be carried out, then data selection, data transformation, and data mining will be carried out using the Rapidminer software. Modeling results were evaluated using the Davies Bouldin Index (DBI) instrument. Based on the research that has been done, it can be seen that the K-Means algorithm can be used to group BB bus datasets. Which later can be used by companies as an illustration, this research can also be used as input for companies/service providers. Abstrak Bahasa Inggris maksimum 250 kata dalam satu alinea menggunakan huruf Arial 10, spasi 1. Abstrak berisi pendahuluan singkat, tujuan, metode dan hasil secara ringkas dan jelas. Penulisan singkatan yang tidak umum tidak diperkenankan kecuali didefinisikan sebelumnya.
Pengelompokkan Tingkat Pemahaman Kurikulum Berbasis KKNI Menggunakan Metode X-Means Clustering Saeful Anwar; Nisa Dieanwati Nuris; Yudhistira Arie Wijaya
Jurnal Informatika: Jurnal Pengembangan IT Vol 4, No 2-2 (2019): Special Issue on Seminar Nasional - Inovasi Dalam Teknologi Informasi & Teknol
Publisher : Politeknik Harapan Bersama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30591/jpit.v4i2-2.1869

Abstract

In Law Number 12 of 2012 concerning Higher Education in Article 35 Paragraph 2 explains that the development of PT curriculum refers to the National Higher Education Standards for every study program that develops noble, intellectual intelligence and skills. KKNI or the Indonesian National Qualification Framework brings together, equates, and combines the field of education with the field of training and work experience and conceptually the Indonesian National Qualification Framework (KKNI) is composed of six (6) main parameters consisting of science, knowledge, know-how, skills, affection, competency. From the results of clustering analysis or grouping using the x-means algorithm it is found that the parameters of science (A), knowledge (B), skill (D), and competency (F) respondents are more likely to answer understanding and are very understanding. In the know-how parameter (C) the tendency of respondents to answer is well understood, whereas for the affection parameter (E) respondents tend to answer between understanding and quite understand but is in contrast between cluster 0 and cluster 1.
Analisa Clustering untuk Mengelompokan Data Penayangan Film Bioskop Menggunakan Algoritma K-Means Moh Nurdayat Dayat; Nana Suarna; Yudhistira Arie Wijaya
INTERNAL (Information System Journal) Vol. 6 No. 1 (2023)
Publisher : Masoem University

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Abstract

The purpose of this study is one of the analyzes to obtain film screening data, the approach used in this study is the K-means algorithm using the parameter measure type Numerical Measure with Numerical Measure Euclidean Distance to get the best Davies Bouldin Index (DBI), with the intention of getting helps grouping datasets of film screenings at the Ramayana Cirebon XXI Cinema. Results from the evaluation of the Davies Bouldin Index (DBI) obtained is (K-2) with a Davies Bouldin Index (DBI) value of 0.864, because the value obtained is the smaller the Davies Bouldin Index (DBI) value, it shows the optimum performance of the resulting cluster.
Analisis Data Stok Alat Kesehatan menggunakan Metode Regresi Linier Berdasarkan Nilai RMSE Trian Nurmansyah; Rudi Kurniawan; Yudhistira Arie Wijaya
Jurnal Informatika dan Rekayasa Perangkat Lunak Vol 6, No 1 (2024): Maret
Publisher : Universitas Wahid Hasyim

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36499/jinrpl.v6i1.10275

Abstract

Inventory of healthcare equipment, whether in hospital or clinic settings, represents a significant investment requiring substantial cost allocation. However, estimating these equipment needs often relies solely on the overall available stock, as monthly or yearly requirements tend to fluctuate. Consequently, this approach leads to an inability to meet all necessary equipment needs, resulting frequently in surplus inventory. Therefore, anticipating this issue requires predicting healthcare equipment stock at Klinik Pembina Sehat. This study aims to forecast equipment stock using the linear regression algorithm method. The selection of this algorithm is due to its suitability in handling the linear relationship between dependent and independent variables. Research findings demonstrate the developed model's ability to predict healthcare equipment stock with a reasonably high level of accuracy, with a Root Mean Square Error (RMSE) value of 93.359. This value signifies a relatively low prediction error, indicating the model's precision in estimating stock requirements. Thus, this research holds the potential to enhance operational efficiency in managing healthcare equipment stock within the clinic and serves as a foundation for further studies to improve stock planning processes in similar healthcare institutions.
Co-Authors Abrar Bayan, Athaullah Ade Irma Purnama Sari Adi Hermawan Adiyanto, Alfian Adjie Setyadj, Mochammad Agni, Vega Putra Dwi Ahmad Faqih AKBAR, MUHAMAD DENI Alfirda Sofyan, Zahra Aliya Anisa Rahma Alya Fadia Amelia, Astri An-naziz Safaat, Wafik Andi Ardiansyah Andriyani, Wini Andriyanti, Rina Anggara, Doni Anjar Permadi Aprianto, Wili Arif Firmansyah, Aditiya ASEP SAEFUDDIN Asmana, Asmana Azhar, Alwan Dadang Sudrajat Danar Dana, Raditya Darma Irawan, Bobi Darussalam, Luthvi Nurfauzi Denni Pratama Dermawan, Hibrizi Dzaky Dian Ade Kurnia Dian Ade Kurnia Edi Tohidi Edi Wahyudin Falih, Alfi Rizqi Falih FANDI ACHMAD Fauzan, Muhamad Nur Fianita Rusadi Fianita Rusadi Firmansyach, Wildan Attariq Hadi Wicaksana, Arya Hamonangan, Ryan Hayati, Umi Hegarmanah Muhabatin Herman Hermawan, Adi Hidayat, Hilpad Hidayat, Zaids Syarif Ibnu Ubaedila Ikhwan Fahruddin, Yusuf Inawati, Windi Irfan Ali Irfan Ali, Irfan Irma Agustina Irma Purnamasari, Ade Jaelani Sidik Jayawarsa, A.A. Ketut Jurnal Konsera Khoeri, Yajid Komala, Wulan Kurniawan , Rudi Kusmiyaty, Agesty Laela Laela Leli Oktaviani Lukmanul Hakim Manzis, Zian Martanto Martanto . Martanto Martanto Maryam, Beby Masjunedi, Masjunedi Maulana, Tedy Mifta Almaripat Mita Amelia Moh Nurdayat Dayat Muhamad Basysyar , Fadhil MUHAMAD DENI AKBAR Muhamad Nur Fauzan Muhammad Aditya Rabbani Adit Nabila, Aynun Nana Suarna Nashir, Mukhtar Nining Rahaningsih Nisa Dieanwati Nuris Nisa Dienwati Nuris Novita Safitri Nur Amalia, Yustika Nurazijah, Wulan Nurdiawa, Odi Nurholipah, Titin Nurrahman, Rizki Odi Nurdiawa Odi Nurdiawan Pebriyanto, Ramdhan Pratama, Denni Prihartono, Willy Rinaldi Dikananda, Arif Rini Astuti Rini Astuti Rini Astuti Riri Narasati Rizal Rizal Rubangiya Rubangiya Rudi Kurniawan Rudi Kurniawan Rudi Kurniawan Saeful Anwar Saeful Anwar, Saeful Satria Turangga Septian Nugraha, Titan Septiani Gumilar, Tia Shifa Dwi Oktaviani Suarna, Nana Sulaeman, Muhammad Suteja Syach Putra, Yanuar Tati Suprapti Taufik Hidayat Tegar Lazuardi, Muhammad Thomas Agam Tiana Dewi Tohidi, Edi Tri Anelia Trian Nurmansyah Triswanto, Triswanto Tuti Hartati Tuti Hartati Tuti Hartati Wahyudi Wahyudi Wangi Nur Qibti, Intan Wartumi Wartumi Willy Prihartono Winayah, Winayah Windy Astuti Yudis Firmansyah yulani, Yulani - Yulia, Yuli