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Pelatihan Keterampilan Dasar Komputer Dan Teknologi Informasi Bagi Siswa Sekolah Dasar Di SD Negeri 2 Tibubeneng Nengah Widya Utami; Ni Luh Putu Ning Septyarini Putri Astawa
Jurnal Pelayanan dan Pengabdian Masyarakat (Pamas) Vol 4, No 1 (2020): Jurnal Pelayanan dan Pengabdian Masyarakat (Pamas)
Publisher : Lembaga Penelitian dan Pengabdian Masyarakat (LPPM Universitas Respati Indonesia)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52643/pamas.v4i1.781

Hasil analisis situasi menunjukkan minimnya kondisi pendidikan yang berkaitan dengan Teknologi Informasi dan Komunikasi (TIK) khususnya bagi siswa-siswi di sekolah dasar. Tujuan kegiatan ini adalah untuk memberikan pengetahuan dan keterampilan dasar komputer serta teknologi informasi kepada siswa di sekolah dasar. Pelatihan ini diharapkan memberikan bekal kepada siswa tentang keterampilan dasar komputer dan teknologi informasi khususnya internet bagi pengembangan ilmu pengetahuan, serta sebagai bentuk pengembangan nilai-nilai karakter dalam bidang pendidikan berupa rasa keingintahuan, kreatif, inovatif, dan komunikatif. Subjek kegiatan pengabdian kepada masyarakat adalah siswa-siswi di SD Negeri 2 Tibubeneng, Kabupaten Badung yang berjumlah 104 orang. Kegiatan pelatihan ditunjang dengan metode ceramah, tanya jawab, demonstrasi, dan praktek langsung penggunaan aplikasi komputer. Hasil kegiatan menunjukkan bahwa pelatihan ini dapat memberikan pengetahuan, pemahaman, dan keterampilan bagi siswa-siswi dalam menggunakan aplikasi dasar seperti Paint dan Microsoft Word, serta memahami penggunaan internet sehat dalam pencarian informasi. Kata kunci: pelatihan, keterampilan, komputer, tibubeneng.

Perancangan Sistem Point of Sales (POS) Terintegrasi pada UD. Akor Nature Bag Putu Ari Widiastuti; Nengah Widya Utami; Ni Made Estiyanti
Jutisi : Jurnal Ilmiah Teknik Informatika dan Sistem Informasi Vol 10, No 2: Agustus 2021
Publisher : STMIK Banjarbaru

The UD. Akor Nature Bag Management does not yet have a good financial reporting system because it only relies on notes from sales. The management also cannot know the development of the company's branches in real time, because sales transactions are sent by the branch to the center once a week or once a month. This article presents the design of an integrated Point of Sales system, which is tailored to the needs of the UD Akor Nature Bag. The research method used is a system development method with a prototyping approach, starting from planning and ending with the proposed system design. Point of Sales system design includes context diagram design, data flow diagram design, system database design, and user interface design. The design of the user interface is made in the form of a static web and uses a template from Stisla.Keywords: System Design, Point of Sales System, Prototyping ABSTRAK. Manajemen UD Akor Nature Bag belum memiliki sistem pelaporan keuangan yang baik karena hanya mengandalkan nota-nota dari penjualan. Pihak manajemen juga tidak dapat mengetahui perkembangan cabang perusahaan secara realtime, karena transaksi penjualan dikirim oleh cabang ke pusat setiap satu minggu atau satu bulan sekali. Artikel ini menyajikan rancangan sistem Point of Sales terintegrasi, yang disesuaikan dengan kebutuhan pada UD Akor Nature Bag. Metode penelitian yang digunakan adalah metode pengembangan sistem dengan pendekatan prototyping, dimulai dari perencanaan dan berakhir pada perancangan sistem usulan. Perancangan sistem Point of Sales memuat rancangan diagram konteks, rancangan data flow diagram, rancangan database sistem, serta rancangan user interface. Rancangan user interface dibuat dalam bentuk web statis dan menggunakan template dari Stisla.Kata kunci: Perancangan Sistem, Sistem Point of Sales, Prototyping

Model Aplikasi Sistem Pendukung Keputusan Pemberian Kredit Berbasis Web pada Koperasi Simpan Pinjam I Wayan Arya Wiguna; I Gede Putu Krisna Juliharta; Nengah Widya Utami
Jutisi : Jurnal Ilmiah Teknik Informatika dan Sistem Informasi Vol 11, No 1: April 2022
Publisher : STMIK Banjarbaru

Abstrak. Sistem permohonan peminjaman kredit yang sedang berjalan pada Koperasi Serba Usaha Tri Gunartha Werdhi Banjar Ubud Kelod masih dikelola secara manual, dimana pemohon datang langsung ke kantor perusahaan sehingga pemrosesan permohonan menjadi tidak efisien. Proses pengambilan keputusan pemberian pinjaman juga belum dilakukan secara terkomputerisasi sehingga hasil keputusan dikhawatirkan menjadi tidak konisten. Paper ini menyajikan model aplikasi Sistem Pendukung Keputusan berbasis Web dengan menggunakan metode SAW (Simple Additive Weighting) untuk mendukung kinerja manajemen koperasi dalam menilai kelayakan pemberian pinjaman kredit secara konsisten kepada anggota. Pengembangan sistem mengikuti tahapan-tahapan dalam metode Waterfall. Desain sistem menggunakan tools desain terstruktur, sedangkan implementasi desain menggunakan aplikas Visual Studio Code untuk membuat Web berbasis PHP dan database MySql. Hasil uji BlackBox menunjukkan fitur-fitur fungsional aplikasi telah valid memenuhi kebutuhan pengguna, berupa fitur pendataan anggota, transaksi pengajuan pinjaman, proses simulasi pemberian kredit berbasis SAW, transaksi setoran/pembayaran anggota, daftar Anggota, serta riwayat setoran/pembayaran anggota. Sistem juga dapat menyajikan keputusan pemberian pinjaman kredit secara konsisten.Kata Kunci: Pengajuan pinjaman kredit; Jasa simpan pinjam; Keputusan; Simple Additive Weighting Abstract. The credit loan application system that is currently running at the Tri Gunartha Werdhi Banjar Ubud Kelod Multipurpose Cooperative is still managed manually, where the applicant comes directly to the company office so that the application processing becomes inefficient. The decision-making process for granting loans has also not been carried out computerized so that the results of the decisions are feared to be inconsistent. This paper presents a Web-based Decision Support System application model using the SAW (Simple Additive Weighting) method to support cooperative management performance in assessing the feasibility of providing credit loans consistently to members. System development follows the stages in the Waterfall method. The system design uses structured design tools, while the design implementation uses Visual Studio Code applications to create PHP-based Web and MySQL databases. The results of the BlackBox test show that the functional features of the application have been valid to meet user needs, in the form of member data collection features, loan application transactions, SAW-based credit granting simulation processes, member deposit/payment transactions, member lists, and member deposit/payment history. The system can also provide credit lending decisions consistently.Keywords: Credit loan application; savings and loan services; decisions; Simple Additive Weighting

Perancangan Sistem Pengendalian Internal dan Penerapannya pada Sistem Pembelian dan Sistem Penjualan di UD. Kartini Singaraja Luh Eka Sri Utami; Ni Made Estiyanti; Nengah Widya Utami
Jutisi : Jurnal Ilmiah Teknik Informatika dan Sistem Informasi JUTISI Vol. 9, No. 3, Desember 2020
Publisher : STMIK Banjarbaru

ABSTRAK. Manajemen usaha dagang “UD. Kartini” Singaraja belum memiliki sistem pengendalian Intern pada sistem penjualan dan pembelian yang sedang berjalan, pengelolaan sistem masih dilakukan secara manual, sehingga pemilik usaha tidak dapat mengetahui secara pasti persediaan barang yang masih tersedia dan yang sudah terjual karna volume dan jenis barang yang begitu banyak. Pihak manajemen perusahaan juga belum memiliki sistem pelaporan keuangan yang baik karena hanya mengandalkan nota-nota dari pembelian barang dari pihak supplier. Artikel ini menyajikan rancangan sistem pengendalian intern pada sistem pembelian dan penjualan, yang disesuaikan dengan kebutuhan manajemen UD. Kartini Singaraja. Metode penelitian yang digunakan adalah penelitian pengembangan, dengan mengadopsi beberapa tahapan awal pada model pengembangan sistem SDLC (System Development Life Cycle), yaitu analisis kebutuhan sistem dan berakhir pada perancangan sistem usulan yang baru. Rancangan sistem penjualan dan sistem pembelian memuat diagram konteks, data flow diagram, rancangan database sistem, serta rancangan user interface. Rancangan sistem pengendalian intern pada sistem pembelian dan sistem penjualan yang dibuat, dapat menjadi pedoman dalam pengembangan aplikasi sistem pengendalian intern pada sistem penjualan dan sistem pembelian sesuai dengan kebutuhan pengelolaan manajemen UD. Kartini Singaraja. Kata Kunci: Perancangan Sistem, Pengendalian Intern, Sistem Pembelian dan Penjualan, Sistem Development Life Cycle ABSTRACT. "UD. Kartini" Singaraja trade business management does not have an internal control system in the ongoing sales and purchase system, the management of the system is still done manually, so that business owners cannot know for certain the inventory of goods that are still available and that have been sold because of the volume and so many types of goods. The company management also does not have a good financial reporting system because it only relies on receipts from the purchase of goods from the supplier. This article presents the design of internal control systems in the purchasing and sales system, which is tailored to the management needs of UD. Kartini Singaraja. The research method used is development research, by adopting some initial stages in the SDLC (System Development Life Cycle) system development model, which is an analysis of system requirements and ending in the design of a new proposed system. The sales system design and the purchasing system contain context diagrams, data flow diagrams, system database designs, and user interface designs. The design of the internal control system on the purchasing system and the sales system that was made, can be a guideline in developing the application of the internal control system on the sales system and the purchasing system in accordance with the needs of the UD. Kartini Singaraja’s management. Keywords: System Design, Internal Control, Purchasing and Sales Systems, System Development Life Cycle

CLASSIFICATION OF BLOOD DONOR DATA USING C4.5 AND K-NEAREST NEIGHBOR METHODS (CASE STUDY: UTD PMI BALI PROVINCE) Ni Ketut Melly Astuti; Nengah Widya Utami; I Gede Putu Krisna Juliharta
Jurnal Pilar Nusa Mandiri Vol 18 No 1 (2022): Publishing Period for March 2022
Publisher : LPPM Universitas Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/pilar.v18i1.2790

Classification of blood donor data at UTD PMI Bali Province by applying the C4.5 and K-Nearest Neighbor algorithms. The number of blood donor data donors is 34,948, of which 90% of the data, namely 31,454 is used as training data. Meanwhile, 10% of the data, which is 3,494 data, is used as the implementation of data testing using the Orange application. C4.5 obtained an accuracy score of 92.9%, F1 of 92.2%, Precision of 93.1%, Recall of 92.9%, specificity of 68.2%. While K-nearest neighbor obtained an accuracy score of 91%, F1 of 90.1%, Precision of 90.8%, Recall of 91%, specificity of 63%. With the AUC (Area Under Curve) value for the C4.5 algorithm is 0.875 and the K-nearest neighbor is 0.813 Good Classification. The results of the evaluation using the confusion matrix C4.5 obtained an accuracy score of 92.6%, F1 of 95.7%, Precision of 99.4%, Recall of 92.4%, specificity of 96%. While k-nearest neighbor obtained an accuracy score of 90.9%, F1 of 94.6%, Precision of 98.4%, Recall of 91.2%, specificity of 88.4%. Based on the evaluation of the confusion matrix and the ROC Analysis Graph, the C4.5 algorithm obtained higher results than the K-Nearest Neighbor algorithm. Based on the data on the characteristics of blood donors at UTD PMI Bali Province, it shows that the gender is male, Badung area, Age 20 to < 30, the occupation of private employees dominates in blood donation.

Sistem Informasi Geografis Peternakan Ayam Pada Kabupaten Jembrana Berbasis Website Ni Made Mila Fatmasari; I Putu Agus Swastika; Nengah Widya Utami
KARMAPATI (Kumpulan Artikel Mahasiswa Pendidikan Teknik Informatika) Vol. 10 No. 2 (2021)
Publisher : Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/karmapati.v10i2.37051

This thesis proposal discusses the difficulties of chicken buyers to get information on chicken farms in Jembrana Bali, and the limited information obtained, currently complete information on farm layout in Jembrana Regency, only exists at the Jembrana District Animal Husbandry Service, then chicken breeders are also it is still difficult to provide information about their layout due to the limited means of adequate information in each village. So a chicken farm geographic information system was created with the aim of helping chicken buyers, livestock raisers and the Chicken Farming Service to get information on chicken breeding in Jembrana Regency more easily.Keywords— livestock, chicken, GIS, Website, Jembrana

Klasifikasi Penentuan Kelayakan Pemberian Kredit Menggunakan Metode Naive Bayes Classifier (Kasus: Koperasi Simpan Pinjam Artha Segara) Ni Komang Ayu Suarpurningsih; Nengah Widya Utami; Ni Made Estiyanti
J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 6, No 1 (2022): EDISI MARET
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/j-sakti.v6i1.454

Artha Segara Savings and Loans Cooperative is a company that provides savings and loan services to customers. In providing savings and loan services, it is not uncommon for customers to experience delays in paying bills or what is called bad credit. Bad credit is where the customer cannot do or is unable to pay the bill in part or all of the obligations as agreed. The cooperative must analyze the causes of the occurrence of bad loans using credit data that have been previously owned. Credit data owned by the Artha Segara Savings and Loans Cooperative can be analyzed using Data Mining. Where the data are classified using the Naïve Bayes Classifier method in calculating the probability level for each value of the target attribute in each customer credit case. The Naïve Bayes Classifier method can be used in several Data Mining tools or applications, one of which is the Orange Data Mining tool. The output of the Orange Data Mining system is the result of classification of customer credit data that is eligible or not eligible to reapply for credit. Researchers tested customer credit datasets from 2018 to 2020 as many as 1,200 data by dividing the dataset into 2 types of data, namely training data (training data) and test data (testing data). Comparison of training data and testing data is 70%:30%. Testing of training data as much as 840 data and testing data of 360 data produces 99.8% accuracy rate

EVALUASI USABILITY PADA E-LEARNING UNIVERSITAS PENDIDIKAN GANESHA DENGAN METODE USABILITY TESTING Nengah Widya Utami; I Ketut Resika Arthana; I Gede Mahendra Darmawiguna
Jurnal Nasional Pendidikan Teknik Informatika : JANAPATI Vol. 9 No. 1 (2020)
Publisher : Prodi Pendidikan Teknik Informatika Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/janapati.v9i1.23663

Penelitian ini bertujuan untuk untuk mengevaluasi E-Learning Universitas Pendidikan Ganesha pada aspek usability menggunakan metode usability testing yaitu teknik Performance Measurement dan teknik Retrospective Think Aloud (RTA), serta dapat memberikan rekomendasi perbaikan atas sistem tersebut berdasarkan hasil evaluasi usability yang dilakukan. Ada tiga aspek usability yang dikaji yaitu efektivitas (effectiveness), efisensi (efficiency), dan kenyamanan atau kepuasan pengguna (satisfaction) menggunakan E-Learning Undiksha. Populasi dalam penelitan ini yaitu dosen dan mahasiswa di Fakultas Teknik dan Kejuruan (FTK) dengan melibatkan 32 responden yaitu 16 responden dosen dan 16 responden mahasiswa. Teknik pengumpulan data dilakukan dengan tiga teknik yaitu teknik wawancara, Performance Measurement, dan RTA. Analisis data yang dilakukan yaitu menggunakan uji statistik Mann Whitney U Test dan perhitungan Software Usability System (SUS). Hasil penelitian menunjukkan bahwa (1) E-Learning Undiksha masih belum efektif dilihat dari adanya kesalahan (error) pengguna dosen dan mahasiswa saat pengerjaan tugas, (2) E-Learning Undiksha sudah efisien dilihat dari tidak adanya perbedaan yang signifikan waktu pengerjaan tugas kelompok mahir dan kelompok pemula oleh responden dosen dan mahasiswa, (3) Pengguna baik dosen maupun mahasiswa merasa kurang puas menggunakan E-Learning Undiksha dilihat dari skor kuisioner SUS sebesar 60.94 dan 61.09. Dengan demikian berdasarkan hasil analisis data tersebut disimpulkan bahwa E-Learning Undiksha belum memiliki usability yang baik karena tidak memenuhi kriteria sebuah produk dengan usability yang baik. Hal ini dapat dilihat pada penilaian tingkat efektivitas, efesiensi, dan kepuasan pengguna, halaman E-Learning Undiksha ini tidak mampu memenuhi kriteria yang baik untuk ketiga aspek tersebut. Berdasarkan hal tersebut, rekomendasi perbaikan dalam penelitian ini difokuskan untuk mengubah tata letak (layout) halaman dan menu navigasi pada hasil data penyebab kesalahan (error) pengguna, dan menyederhanakan menu serta konsistensi penggunaan Bahasa dan istilah sesuai saran dari pengguna. Perbaikan dilakukan dengan membuat wireframe halaman utama E-Learning Undiksha, halaman utama pengguna, halaman mengelola matakuliah, halaman mengubah konten matakuliah, halaman menambah aktivitas, halaman membuat kuis, halaman mendaftar matakuliah, dan halaman forum diskusi.

Klasifikasi Penentuan Kelayakan Pemberian Kredit Menggunakan Metode Naive Bayes Classifier (Kasus: Koperasi Simpan Pinjam Artha Segara) Ni Komang Ayu Suarpurningsih; Nengah Widya Utami; Ni Made Estiyanti
J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 6, No 1 (2022): EDISI MARET
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/j-sakti.v6i1.454

Artha Segara Savings and Loans Cooperative is a company that provides savings and loan services to customers. In providing savings and loan services, it is not uncommon for customers to experience delays in paying bills or what is called bad credit. Bad credit is where the customer cannot do or is unable to pay the bill in part or all of the obligations as agreed. The cooperative must analyze the causes of the occurrence of bad loans using credit data that have been previously owned. Credit data owned by the Artha Segara Savings and Loans Cooperative can be analyzed using Data Mining. Where the data are classified using the Naïve Bayes Classifier method in calculating the probability level for each value of the target attribute in each customer credit case. The Naïve Bayes Classifier method can be used in several Data Mining tools or applications, one of which is the Orange Data Mining tool. The output of the Orange Data Mining system is the result of classification of customer credit data that is eligible or not eligible to reapply for credit. Researchers tested customer credit datasets from 2018 to 2020 as many as 1,200 data by dividing the dataset into 2 types of data, namely training data (training data) and test data (testing data). Comparison of training data and testing data is 70%:30%. Testing of training data as much as 840 data and testing data of 360 data produces 99.8% accuracy rate

Klasifikasi Penentuan Penerima Bantuan Sosial Tunai (BST) Menggunakan Algoritma C4.5 Di Desa Keramas, Gianyar, Bali Ni Wayan Oktha Pratiwi; Nengah Widya Utami; I Gede Juliana Eka Putra
Jurnal Informatika Teknologi dan Sains Vol 4 No 3 (2022): EDISI 13
Publisher : Program Studi Informatika Universitas Teknologi Sumbawa

The current Covid-19 pandemic has led to an increase in the poverty rate in Indonesia. To overcome the decline in income, the Ministry of Social Affairs provides Cash Social Assistance (BST) to 9 million KPM in Indonesia. One of the villages that received cash social assistance is Keramas Village. The problem is that the BST recipient is not precise. The purpose of this study is to classify the eligibility of BST recipients using the C4.5 algorithm and the C4.5 algorithm is expected to be able to provide recommendations for decision making in receiving other assistance. The results of this study are to predict whether the community is eligible or not eligible to receive BST. Researchers tested using 5 attributes, including having received other assistance, employment, education, having a poor card, and number of dependents. The test uses 2,074 data which is divided into 2 types of data, namely 80% training data and 20% testing data. This test produces an accuracy of 97.83% and compares with the K-Nearest Neighbor algorithm which produces an accuracy of 92.29% and Naïve Bayes of 91.81%.

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