Garuda - Garba Rujukan Digital

p-Index From 2019 - 2024

4.997

P-Index

This Author published in this journals

All Journal Nuansa Informatika Sistemasi: Jurnal Sistem Informasi Technologia: Jurnal Ilmiah Tematik : Jurnal Teknologi Informasi Komunikasi International Journal of Global Operations Research International Journal of Quantitative Research and Modeling Majalah Bisnis & IPTEK Formosa Journal of Applied Sciences (FJAS) International Journal of Ethno-Sciences and Education Research SisInfo : Jurnal Sistem Informasi dan Informatika Nuansa Informatika Jurnal Bhakti Karya dan Inovatif INTERNAL (Information System Journal) In Search (Informatic, Science, Entrepreneur, Applied Art, Research, Humanism)

Budiman

Fakultas Teknik Dan Informatika, Universitas Informatika Dan Bisnis Indonesia

Author-ID : 3318497

Religion Arts Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Languange, Linguistic, Communication & Media Mathematics Physics Social Sciences Transportation Other

Published : 38 Documents Claim Missing Document

Claim Missing Document

Articles

1 2 3 4

Analisis Penerimaan Google Classroom Menggunakan Pendekatan Technology Acceptance Model (TAM) Dan End-User Computing Satisfaction (EUCS) Zatin Niqotaini; Budiman Budiman
Sistemasi: Jurnal Sistem Informasi Vol 10, No 3 (2021): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

AbstrakPandemi virus corona (COVID-19) memberikan dampak besar terhadap berbagai aktivitas manusia di seluruh dunia khususnya negara Indonesia, salah satunya aktivitas pendidikan dan kegiatan pembelajaran di kampus. Kebijakan dari pemerintah tentang WFH (work from home) menjadikan proses kegiatan pembelajaran secara tatap muka di kampus dihentikan sementara sejak bulan Maret 2020 hingga waktu yang belum dapat ditentukan. Universitas Informatika dan Bisnis Indonesia sebagai salah satu institusi pendidikan swasta di Jawa Barat, dituntut untuk mengikuti perubahan metode pembelajaran yaitu pembelajaran jarak jauh (online) yang sebelumnya menggunakan tatap muka secara langsung. Salah satu platform yang banyak digunakan adalah google classroom. Google classroom merupakan aplikasi yang memungkinkan terbentuknya kelas di dunia maya, sebagai salah satu platform yang banyak digunakan tentunya perlu diperlukan evaluasi kepuasaan pengguna terutama mahasiswa agar terdapat perbaikan kedepannya. Penelitian ini dikaji dengan menggunakan model Technology Acceptance Model (TAM) dengan mempertimbangkan faktor Persepsi Kegunaan (Perceived Usefulness), Persepsi Kemudahan Penggunaan (Perceived Ease Of Use) dan Sikap Terhadap Perilaku (Attitude Toward Using). End-User Computing Satisfaction (EUCS) dengan mempertimbangkan Isi (Content), Akurasi (Accuracy), Tampilan (Format), Kemudahan (Ease) dan Ketepatan Waktu (Timeliness). Subyek penelitian yang digunakan adalah mahasiswa di lingkungan Universitas Informatika dan Bisnis Indonesia (Unibi). Hipotesis yang menghasilkan hubungan antar konstruk di dalam TAM dan EUCS diukur dengan Structural Equation Model (SEM) dan software AMOS 26. Hasil penelitian ini menunjukkan bahwa model TAM dan EUCS dapat menjelaskan faktor – faktor yang mempengaruhi penerimaan google classroom pada Unibi dimana Perceived Usefullness (PU) dipengaruhi oleh Perceived Ease of Use (PEOU) 52,2%. Attitude Toward Using (AT) dipengaruhi oleh Perceived Usefullness (PU) 34,4%, Content (CT) 25,4%, Accuracy (AC) 11,9%, dan Format (FT) 18,4%.Kata kunci : e-learning, google classroom, technology acceptance model (TAM), end user computing satisfaction (EUCS) AbstractCoronavirus pandemic (COVID-19) has a big impact on various human activities around the world, especially indonesia, one of which is educational activities and learning activities on campus. The government's policy on WFH (work from home) has temporarily suspended the process of face-to-face learning on campus from March 2020 until an indefinite period of time. University Informatics and Business Indonesia as one of the private educational institutions in West Java, is required to follow the changes in learning methods, namely distance learning (online) that previously used face-to-face. One of the widely used platforms is google classroom. Google classroom is an application that allows the formation of classes in cyberspace, as one of the widely used platforms of course need to evaluate user satisfaction, especially students in order for there to be improvements in the future. This study was reviewed using Technology Acceptance Model (TAM) model taking into account Perceived Usefulness, Perceived Ease Of Use and Attitude Toward Using. End-User Computing Satisfaction (EUCS) taking into account Content, Accuracy, Display (Format), Ease and Timeliness. The subjects of the study used were students in University Informatics and Business Indonesia environment. Hypotheses that produce relationships between constructs within TAM and EUCS are measured by structural equation models (SEM) and AMOS 26 software. The results of this study showed that tam and EUCS models can explain the factors that influence the acceptance of google classroom in Unibi where Perceived Usefullness (PU) is influenced by Perceived Ease of Use (PEOU) 52.2%. Attitude Toward Using (AT) was influenced by Perceived Usefullness (PU) 34.4%, Content (CT) 25.4%, Accuracy (AC) 11.9%, and Format (FT) 18.4%..Keywords: e-learning, google classroom, technology acceptance model (TAM), end user computing satisfaction (EUCS).

Comparative Analysis of Data Mining Classification Algorithm Performance for Searching Prospective Student Interests Budiman Budiman; Zatin Niqotaini
Sistemasi: Jurnal Sistem Informasi Vol 11, No 2 (2022): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Admission of new students is an activity that’s always carried out by every university in the new academic year. The decline in the number of registrants every year is an obstacle for AMIK HASS in new student admissions, efforts are needed to process the existing data on new student admissions. Data mining applications use classification algorithms that aim to make predictions. The algorithms used are Nave Bayes (NB), Decision Tree J48 (J48), K-Nearest Neighbor (K-NN), Random Forest (RF), and Support Vector Machine (SVM). Algorithm testing to analyze the performance of each algorithm uses WEKA. The data set used in this study is the search for potential and interest of prospective new students as many as 5,934 records. The tests carried out on the five algorithms use the test percentage split mode, which is 70% for training data and 30% for test data. The highest accuracy rate on J48 is 90.34% followed by RF at 89.04%, SVM at 88.43%, K-NN at 87.53%, NB at 87.25%. J48 is the best algorithm for testing data sets with the lowest prediction error rate of 0.26. The J48 classification algorithm has explicit rules for the classification and handling of heterogeneous data by having 255 rules.

Data Mining Implementation Using Naïve Bayes Algorithm and Decision Tree J48 In Determining Concentration Selection Budiman Budiman; Reni Nursyanti; R Yadi Rakhman Alamsyah; Imannudin Akbar
International Journal of Quantitative Research and Modeling Vol 1, No 3 (2020)
Publisher : Research Collaboration Community (RCC)

Computerization of society has substantially improved the ability to generate and collect data from a variety of sources. A large amount of data has flooded almost every aspect of people's lives. AMIK HASS Bandung has an Informatic Management Study Program consisting of three areas of concentration that can be selected by students in the fourth semester including Computerized Accounting, Computer Administration, and Multimedia. The determination of concentration selection should be precise based on past data, so the academic section must have a pattern or rule to predict concentration selection. In this work, the data mining techniques were using Naive Bayes and Decision Tree J48 using WEKA tools. The data set used in this study was 111 with a split test percentage mode of 75% used as training data as the model formation and 25% as test data to be tested against both models that had been established. The highest accuracy result obtained on Naive Bayes which is obtaining a 71.4% score consisting of 20 instances that were properly clarified from 28 training data. While Decision Tree J48 has a lower accuracy of 64.3% consisting of 18 instances that are properly clarified from 28 training data. In Decision Tree J48 there are 4 patterns or rules formed to determine concentration selection so that the academic section can assist students in determining concentration selection.

ANALISIS PENERIMAAN GOOGLE CLASSROOM MENGGUNAKAN PENDEKATAN TECHNOLOGY ACCEPTANCE MODEL (TAM) DAN END-USER COMPUTING SATISFACTION (EUCS) (STUDI KASUS UNIVERSITAS INFORMATIKA DAN BISNIS INDONESIA) Zatin Niqotaini; Budiman Budiman
Technologia : Jurnal Ilmiah Vol 12, No 4 (2021): Technologia (Oktober)
Publisher : Universitas Islam Kalimantan Muhammad Arsyad Al Banjari

ABSTRAKPandemi virus corona (COVID-19) memberikan dampak besar terhadap berbagai aktivitas manusia di seluruh dunia khususnya negara Indonesia, salah satunya aktivitas pendidikan dan kegiatan pembelajaran di kampus. Kebijakan dari pemerintah tentang WFH (work from home) menjadikan proses kegiatan pembelajaran secara tatap muka di kampus dihentikan sementara sejak bulan Maret 2020 hingga waktu yang belum dapat ditentukan. Universitas Informatika dan Bisnis Indonesia sebagai salah satu institusi pendidikan swasta di Jawa Barat, dituntut untuk mengikuti perubahan metode pembelajaran yaitu pembelajaran jarak jauh (online) yang sebelumnya menggunakan tatap muka secara langsung. Salah satu platform yang banyak digunakan adalah google classroom. Google classroom merupakan aplikasi yang memungkinkan terbentuknya kelas di dunia maya, sebagai salah satu platform yang banyak digunakan tentunya perlu diperlukan evaluasi kepuasaan pengguna terutama mahasiswa agar terdapat perbaikan kedepannya. Penelitian ini dikaji dengan menggunakan model Technology Acceptance Model (TAM) dengan mempertimbangkan faktor Persepsi Kegunaan (Perceived Usefulness), Persepsi Kemudahan Penggunaan (Perceived Ease Of Use) dan Sikap Terhadap Perilaku (Attitude Toward Using). End-User Computing Satisfaction (EUCS) dengan mempertimbangkan Isi (Content), Akurasi (Accuracy), Tampilan (Format), Kemudahan (Ease) dan Ketepatan Waktu (Timeliness). Subyek penelitian yang digunakan adalah mahasiswa di lingkungan Unibi. Hipotesis yang menghasilkan hubungan antar konstruk di dalam TAM dan EUCS diukur dengan Structural Equation Model (SEM) dan software AMOS 26. Hasil penelitian ini menunjukkan bahwa model TAM dan EUCS dapat menjelaskan faktor – faktor yang mempengaruhi penerimaan google classroom pada Unibi dimana Perceived Usefullness (PU) dipengaruhi oleh Perceived Ease of Use (PEOU) 52,2%. Attitude Toward Using (AT) dipengaruhi oleh Perceived Usefullness (PU) 34,4%, Content (CT) 25,4%, Accuracy (AC) 11,9%, dan Format (FT) 18,4%.Kata kunci : E-learning, Google Classroom, Technology Acceptance Model (TAM), End User Computing Satisfaction (EUCS).

PENGARUH PEMANFAATAN SISTEM AKADEMIK ONLINE TERHADAP KEPUASAN MAHASISWA MENGGUNAKAN TECHNOLOGY ACCEPTANCE MODEL (TAM) Budiman Budiman
Majalah Bisnis & IPTEK Vol 9 No 2 (2016): Bisnis dan Iptek
Publisher : Pusat Penelitian Dan Pengabdian Masyarakat (P3M) STIE Pasundan Bandung

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

This study aimed to analyze the effect of Academic Information Systems Online (SIA Online) for student satisfaction in the D3 Program Information Management AMIK HASS Bandung by using models Technology Acceptance Model. The use of TAM model based on the fact that so far TAM is a concept that is considered good in explaining user behavior toward new information technology systems. The populations in this study were students D3 AMIK HASS Information Management Bandung. The sample made with proportional sampling is proportional sampling method based on sub-populations. Sampling using proportional sampling technique for the study population was spread covers college campus 1 and 2. Data were analyzed by SEM (Structural Equation Modeling) with AMOS software (Analysis of Moment Structure). Results of this study proved the hypothesis received only 8 of the total 10 hypotheses proposed. Only the following relationships are shown to have a positive effect: a) Self Efficacy (SE) with Perceived Usefulness (PU), b) Self Efficacy (SE) with Perceived Ease of Use (PEOU, c) Self Efficacy (SE) with Perceived Enjoyment ( PE), d) Perceived Enjoyment (PE) with Behavioral Intention to Use (BITU), e) Perceived Usefulness (PU) with Attitude Toward Using (ATU). f) Perceived Usefulness (PU) with Behavioral Intention to Use (BITU), g) Perceived Ease of Use (PEOU) with Attitude Toward Using (ATU), h) Behavioral Intention to Use (BITU) with Actual Use (AU). It is proved that the use of SIA Online can not be fully explained by the Technology Acceptance Model. Keywords: self efficacy, perceived enjoyment, perceived usefulness, perceived ease of use, attitude, behavioral intention to use, actual use.

Perbandingan Algoritma Klasifikasi Data Mining untuk Penelusuran Minat Calon Mahasiswa Baru Budiman Budiman
NUANSA INFORMATIKA Vol 15, No 2 (2021)
Publisher : FKOM UNIKU

During the AMIK HASS pandemic, it was difficult to determine new student candidates. So that to attract public interest, the Marketing Department has implemented several strategies to attract prospective students to become new students. The data mining technique used in predicting is a classification that includes Naïve Bayes, J48 Decision Tree, and K-Nearest Neighbor. This study aims to perform a comparative analysis of data mining classification algorithms using WEKA tools. The method used in this study, using CRISP-DM. The dataset used by the three classifications is 5,934 records with split mode, the percentage of testing is 70% as much as 4154 as training data and 30% as much as 1780 data as test data. Based on the test results on the three classification models, the highest accuracy value is obtained in the J48 Decision Tree classification, which has a value of 90.3%. While the K-Nearest Neighbor classification has a lower accuracy of 87.52% and the Naïve Bayes classification has an accuracy of 87.24%. The comparison of the AUROC J48 Decision Tree test results has the highest value of 0.9654 while the Naïve Bayes results are 0.9461 and the K-Nearest Neighbor results are 0.9343. The three classifications with ABK scores above 0.90 are included in the excellent classification category

Optimalisasi K-Means Berbasis Particle Swarm Optimization untuk Hasil Produksi Tanaman Sayuran di Indonesia Budiman Budiman
NUANSA INFORMATIKA Vol 17, No 1 (2023)
Publisher : FKOM UNIKU

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25134/fkom uniku.v17i1.6646

Sektor pertanian memegang peranan penting dalam memenuhi kebutuhan pokok masyarakat, dengan demikian akan mendongkrak laju perekonomian, sosial, dan perdagangan. BPS pada September 2020 mencatat jumlah penduduk sebesar 270,20 juta jiwa Bertambahnya jumlah penduduk pada setiap tahun, berbanding lurus dengan permintaan kebutuhan pokok yang semakin meningkat. Sedangkan produksi sektor pertanian tidak setiap tahun meningkat. Penelitian ini bertujuan untuk mengelompokan daerah-daerah yang memiliki tingkat hasil produksi tanaman sayuran yang tinggi atau tingkat hasil produksi tanaman sayuran yang masih rendah. Penerapan K-Means clustering memungkinkan untuk mengoptimasi K-Means clustering dengan PSO sehingga dihasilkan informasi yang lebih bermutu. Hasil pemodelan K-Means clustering berbasis PSO untuk hasil produksi tanaman sayuran di Indonesia cluster 0 (sedang) sebanyak 8,82%, cluster 1 (rendah) sebanyak 88,2%, dan cluster 2 (tinggi) sebanyak 2,94%. Provinsi Jawa Barat berada dalam cluster 2, sehingga Provinsi Jawa Barat mendominasi dalam produksi tanaman sayuran di Indonesia. Hasil pengujian berdasarkan rata-rata silhouette coefficient, K-Means berbasis PSO lebih baik daripada K-Means murni meskipun nilai tersebut tidak berbeda signifikan yaitu dengan rata-rata nilai silhouette coefficient sebesar 0,714114. Rata-rata waktu komputasi waktu komputasi K-Means murni lebih cepat dengan rata-rata 0,748 detik dibandingan K-Means berbasis PSO. Waktu yang dibutuhkan lebih lama karena K-Means berbasis PSO memperbaiki kelompok data dari hasil bentukan K-Means clustering.

Rancang Bangun Single Page Application Berbasis Framework Laravel Dan Elm (Studi Kasus E-Job XYZ) Trisna Gelar Abdillah; Budiman Budiman
SisInfo Vol 1 No 1 (2019): SisInfo
Publisher : Universitas Informatika dan Bisnis Indonesia

E-Job merupakan aplikasi lowongan kerja online yang memberikan layanan informasi lowongan pekerjaan kepada para pencari kerja. Aplikasi ini bertujuan untuk membantu pencari kerja berdasarkan kualifikasi yang diberikan oleh pembuka lowongan kerja atau perusahaan. Artikel ini memaparkan rancang bangun single page application berbasis framework laravel dan elm (studi kasus e-job xyz). Single App Application adalah pengembangan web yang hanya menggunakan satu halaman saja. Artinya, meskipun pengguna beralih ke menu lain, pada URL tidak menunjukkan perubahan halaman. Hal ini dapat diimplemntasikan dengan sebuah sistem backend berbasis RestFulAPI dan sistem frontend yang besifat reaktif. Pada penelitan ini penulis menggunakan Laravel, sebuah Web Framework berbasis PHP yang memudahkan pengembang aplikasi untuk membangun sebuah arsitektur web berbasis RESTFul API, dilengkapi dengan fitur keamanan akses data menggunakan autorisasi berbasis Oauth2 sebagai sistem backend sedangankan Bahasa pemrograman ELM atau arsitektur ELM digunakan untuk membangun sistem frontend pada SPA E-job.

Implementasi Aplikasi Absensi Dosen Berbasis Dekstop Application Studi Kasus: Perguruan Tinggi X Budiman Budiman
SisInfo Vol 1 No 2 (2019): SisInfo
Publisher : Universitas Informatika dan Bisnis Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (408.988 KB)

Perkembangan teknologi infomasi saat ini semakin pesat, ketergantungan terhadap teknologi informasisemakin meningkat. Pemanfaatan teknologi informasi dapat dimanfaatkan oleh semua bidang, salahsatunya bidang pendidikan. Dalam melaksanakan kegiatan perkuliahan perlu adanya pencatatan aktivitasperkuliahan salah satunya adalah absensi dosen. Absensi Dosen merupakan pencatatan aktivitas dosendalam melaksanakan tridharma bidang pendidikan. Pada Perguruan Tinggi X, pencatatan absensi dosenbelum menggunakan sistem komputerisasi. Sehingga pelaporan rekapitulasi absensi dosen membutuhkanwaktu yang lama dan sering terjadi kesalahan yang berdampak pada kesalahan honorarium dosen. Denganmenggunakan model pengembangan perangkat lunak Rapid Aplication Development maka implementasiaplikasi absensi dosen dapat membantu pencatatan absensi dosen, memberikan informasi mengenairekapitulasi absensi dosen secara periodik dan dapat digunakan dalam melakukan monitoring serta evaluasikehadiran mengajar.

Perancangan Aplikasi Sistem Tindak Lanjut Pelanggan Pada Pt. Xyz Budiman Budiman
SisInfo Vol 2 No 01 (2020): SisInfo
Publisher : Universitas Informatika dan Bisnis Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (408.988 KB)

Pemanfaatan teknologi informasi semakin berkembang, perusahaan atau organisasi sudah bertransformasi menggunakan teknologi informasi dalam menunjang setiap pelayanan yang diberikan kepada pelanggan. PT. XYZ merupakan perusahaan yang bergerak di bidang penyedia produk dan jasa. Semakin tinggi penggunaan produk dan jasa maka semakin rentan sebuah perusahaan mengalami masalah dalam memberikan layanan kepada pelanggan. Jika terjadi masalah keluhan dari pelanggan, perusahaan dapat menindaklanjuti melalui bagian atau unit terkait. Tindak Lanjut Pelanggan merupakan layanan prima yang diberikan perusahaan atas keluhan pelanggan. Untuk merancang kebutuhan sistem dalam aplikasi disajikan dalam bentuk diagram Unified Modelling Language. Sehingga perancangan aplikasi sistem tindak lanjut pelanggan dapat mengelola data keluhan pelanggan serta dapat dilanjutkan pada tahap pengembangan sistem sehingga pada saat implementasi perusahaan dapat meningkatkan layanan dan kinerja dalam melayani pelanggan.

Co-Authors Aggi Panigoro Sarifiyono Ahmad Fauzi Ramadhan Ahmad Rizqy Hamdy Amos Duan Nugroho Ari Rizki Fauzi Cahya Miftahul Falah Catherin Rumambo Mogot Pandin Chairul Habibi Chairul Habibi Darsiti . Della Puspita Sari Dirham Triyadi Elia Setiana Fikri Rizqillah Hasani Gelar, Trisna Hasan Nuraripin Imannudin Akbar Imannudin Akbar Irtsa Yasyfa Ismi Nur Muhamad Jilan Hafizh Ferdiansyah Efendi Putra Karlina, Nichi Hana M. Rizki Ramadhan Niqotaini, Zatin Nur Alamsyah Nursyanti, Reni R. Yadi Rakhman A R. Yadi Rakhman Alamsyah Reni Nursyanti Reynaldy Gimnastiar Sophian Ramadhan Suci Fitriani Setiawan Tiara Sartina Jayanti Titan Parama Titan Parama Yoga Titan Parama Yoga Tutik Ultsa Rahmatika Valencia Claudia Jennifer Kaunang Vani Maharani Nasution Venia Restreva Danestiara Venia Restreya Danestiara Wulandari Wulandari Zein Suna Arfigan Said

Title

Found 38 Documents
Search

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Title Search

Found 38 Documents Search

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Title

Found 38 Documents
Search