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Jurnal Informasi dan Teknologi
Published by Universitas Putra Indonesia YPTK Padang
ISSN : 27149730     EISSN : 27149730     DOI : https://doi.org/10.37034/jidt
Core Subject : Science,
Computer Science & IT
Jurnal Informasi & Teknologi media kajian ilmiah hasil penelitian, pemikiran dan kajian analisis-kritis mengenai penelitian Rekayasa Sistem, Teknik Informatika/Teknologi Informasi, Manajemen Informatika dan Sistem Informasi. Sebagai bagian dari semangat menyebarluaskan ilmu pengetahuan hasil dari penelitian dan pemikiran untuk pengabdian pada Masyarakat luas dan sebagai sumber referensi akademisi di bidang Teknologi dan Informasi.
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 378 Documents
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Application of Unified Theory of Acceptance, Use of Technology Model and Delone & Mclean Success Model to Analyze Use Behavior in Mobile Commerce Applications Pramudito, Dendy K; Nuryana, Arief; Assery, Syeh; Purnomo, Hery; Ady Bakri, Asri
Jurnal Informasi dan Teknologi 2023, Vol. 5, No. 3
Publisher : SEULANGA SYSTEM PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60083/jidt.v5i3.382

Abstract

In order to assist businesses, create more efficient solutions and get the greatest benefits from these applications, this research was undertaken with the primary goal of identifying the elements that influence the behavior of utilizing food service applications and enhancing their use. Three variables from the Delone & Mclean IS Success Model and the measurement model, UTAUT, are used in this study's quantitative methodology. Users of food service applications on the island of Java make up the study's population. A total of 150 people responded to the samples. Purposive sampling was used to collect samples. Data analysis using SmartPLS version 4 and the PLS-SEM methodology. Five of the seven factors examined in the study of interest and usage behavior were found to be valid. This means that the use of food service applications can improve performance, assisted by supporting facilities and systems of good quality, so that it can affect the level of user acceptance of the food service application. This research can provide startups with an understanding of the factors that influence their application usage behavior, with the aim of increasing the acceptance and use of food service applications.
The Implementation of End User Computing Satisfaction and Delone & Mclean Model to Analyze User Satisfaction of M.TIX Application Pramudito, Dendy K; Arijanti, Susi; Yanto RUkmana, Arief; Oetomo, Dedy Setyo; Kraugusteeliana, Kraugusteeliana
Jurnal Informasi dan Teknologi 2023, Vol. 5, No. 3
Publisher : SEULANGA SYSTEM PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60083/jidt.v5i3.383

Abstract

This study aims to identify the elements that affect user satisfaction and the degree of user satisfaction with the online ticket application. This study makes use of the End User Computing Satisfaction (EUCS) model's development model, which includes three DeLone and McLean variables system quality, information quality, and service quality along with five EUCS model variables: content, accuracy, format, timeliness, and ease of use. The population of this study is made up of frequent users of Android-based online ticketing applications. Respondents were selected from as many as 175 respondents to be the research sample using the purposive sampling technique. Data analysis was carried out using the PLS-SEM approach with SmartPLS tools. The results showed that users were satisfied using the online ticket application, and out of eight hypotheses, two were rejected and 6 were accepted. So that the factors that influence user satisfaction in online ticket applications are accuracy, ease of use, timeliness, system quality, information quality, and service quality.
Pemodelan Topik Menggunakan n-Gram dan Non-negative Matrix Factorization Afidh, Razief Perucha Fauzie; Syahrial
Jurnal Informasi dan Teknologi 2023, Vol. 5, No. 1
Publisher : SEULANGA SYSTEM PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60083/jidt.v5i1.385

Abstract

Pemodelan topik merupakan teknik pembelajaran mesin yang digunakan untuk melihat topik dalam sekumpulan dokumen teks. Pada penelitian ini pemodelan topik yang digunakan adalah Non-Negative Matrix Factorization (NMF) dengan n-gram. Preprocessing seperti penghilangan tanda baca, angka dan stopword diimplementasikan pada penelitian ini. Proses ini dilakukan dengan terlebih dahulu mengubah kata yang terdapat dalam artikel menjadi kata berhuruf kecil. Penelitian ini juga mengeksplorasi keefektifan penerapan unigram, bigram, dan trigram pada pemodelan topik. Pada penelitian ini juga menggunakan coherence value untuk menentukan jumlah topik terbaik yang dapat dibentuk. Data yang digunakan pada penelitian ini berjumlah 53.920 artikel berita yang bersumber dari portal berita RMOL.id dan BeritaSatu.com untuk periode Juli sampai Desember 2022. Visualisasi t-SNE digunakan untuk melihat distribusi pembentukan topik. Berdasarkan hasil penelitian yang dilakukan diperoleh bahwa jumlah topik yang dapat dibentuk dari RMOL.id untuk unigram adalah 15 topik dengan nilai coherence value 0.812748, bigram adalah 10 topik dengan nilai coherence value 0.835738 dan trigram adalah 7 topik dengan nilai coherence value 0.830572. Sedangkan pada BeritaSatu.com diperoleh 10 topik untuk unigram dengan nilai coherence value 0.799718, bigram 15 topik dengan nilai coherence value 0.788762 dan trigram 15 topik dengan nilai coherence value 0.801935.
Implementation of Gradient Boosted Tree, Support Vector Machinery and Random Forest Algorithm to Detecting Financial Fraud in Credit Card Transactions Salomo Leuwol, Ferdinand; Ady Bakri, Asri; N. Bailusy, Muhsin; Setia Putra, Hari; Sukanti, Ni Ketut
Jurnal Informasi dan Teknologi 2023, Vol. 5, No. 3
Publisher : SEULANGA SYSTEM PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60083/jidt.v5i3.386

Abstract

According to Google Trends data, machine learning-based credit card identification has grown over the last five years, at the very least, across all nations. In order to detect credit card fraud in this study, the authors will use machine learning methods such random forests, support vector machines, and gradient-boosted trees. The authors used the Synthetic Minority Oversampling Technique (SMOTE) and Random Under Sampling (RUS) sampling methods in each algorithm to compare because there was a class imbalance in this investigation. The research findings demonstrate that the author's algorithm and sample technique were successfully used, as shown by the AUC values obtained for each being > 0.7. The top score in RUS was 0.7835 using the Random Forest algorithm, whereas the greatest score in SMOTE was 0.73 with the Gradient Boosted Trees approach. The Random Forest algorithm and the Random Under Sampling (RUS) technique are developed as a result of this research, and they are useful for identifying fraudulent credit card transactions.
Implementasi Extrem Programming Pada Pengembangan Repositori Digital Dokumen Pendukung Akreditasi Berbasis Web Sulistyowati; Erfan, Muhammad; Suparno
Jurnal Informasi dan Teknologi 2023, Vol. 5, No. 3
Publisher : SEULANGA SYSTEM PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60083/jidt.v5i3.387

Abstract

This research was conducted with the aim of producing an application that could facilitate the management of accreditation document data for both institutions and study programs in the form of a digital repository within STMIK Palangkaraya. With this application, it is hoped that the preparation of Laporan Evaluasi Diri (LED), Laporan Kinerja Perguruan Tinggi (LKPT) and Laporan Kinerja Program Studi (LKPS) can be written and read in a comprehensive manner with a direct link to the documents referred to in the report. In addition, this application is expected to speed up the process of searching for accreditation supporting documents when an assessment is carried out by an assessor. The type of research used is Research & Development (R&D) in collaboration with the Extreme Programming (XP) system development method. The stages of the research followed the development cycle of the web-based XP method. The final result of this research is the Digital Repository Dokumen Akreditasi (DIREKSI) application which can provide document links and display documents directly web-based. This application can be accessed online via the URL https://direksi.stmikplk.ac.id.
Diagnosa Penyakit Kulit Pada Hewan Kucing Menggunakan Metode Forward Chaining Muflihah, Yusrida; Pramana, Gito
Jurnal Informasi dan Teknologi 2023, Vol. 5, No. 3
Publisher : SEULANGA SYSTEM PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60083/jidt.v5i3.388

Abstract

Diagnosa penyakit kulit pada hewan kucing memegang peran penting dalam perawatan dan penanganan yang sesuai. Penelitian ini ditujukan guna membuat aplikasi diagnosa penyakit kulit pada kucing berbasis android dengan metode Forward Chaining. Metode ini menggunakan fakta-fakta untuk mendapatkan kesimpulan. Tahap perumusan masalah mengidentifikasi masalah yang dibahas, dan teknik pengumpulan data melibatkan wawancara dengan Dokter Wawa n’ Ca Petshop Klinik serta kajian pustaka. Data dianalisis menggunakan teknik wawancara kualitatif, termasuk persiapan, reduksi, dan penyajian data. Hasilnya adalah aplikasi diagnosa penyakit kulit pada kucing berbasis android yang membantu pemilik mengenali gejala dan memberikan saran pertolongan pertama. Metode Forward Chaining digunakan untuk mencocokkan fakta dengan kondisi dan aturan untuk memberikan diagnosis yang akurat. Hasil uji usability aplikasi memperoleh skor 82 yang menyatakan aplikasi layak digunakan. Penelitian ini berpotensi memberikan kontribusi dalam ilmu informatika dan solusi praktis dalam penanganan penyakit kulit pada kucing
The Evaluation of PDDIKTI User Acceptance Using The Unified Theory of Acceptance and Use of Technology Approach Ady Bakri , Asri; Rino Vanchapo, Antonius; Assery, Syeh; M. Usulu, Elvira; Juli, La
Jurnal Informasi dan Teknologi 2023, Vol. 5, No. 3
Publisher : SEULANGA SYSTEM PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60083/jidt.v5i3.389

Abstract

The scope of this research is about a database application system called Feeder PDDIKTI, where the application can be used as a complete data storage medium by all universities in Indonesia, both university data, lecturer data, study program data, and student data. However, in its application there are still some weaknesses that are felt by users while using the system.The purpose of study is to determine how well-liked the program is by users and to find out what factors affect user acceptance of the application using the modified Unified Theory of Acceptance and Use of Technology (UTAUT) model, whose data testing is assisted by using IBM SPSS. Thus, of the seven hypotheses put forth by the researcher, five are accepted, including Performance Expectancy, Social Influence, and Perceived Credibility, which are all shown to have a significant positive impact on behavioral intention in user acceptance. Facilitating Conditions and Behavioral Intention also have a significant positive impact on use behavior in user acceptance, while Effort Expectancy and Anxiety are shown to have no significant influence.
Analysis of E-Commerce User Acceptance of Technology-Based Loan Application Features Using The UTAUT Model K. Pramudito, Dendy; Rudin; Br Ginting, Riah Ukur; Sekianti, Atik; Sepria Baresi, Irfan
Jurnal Informasi dan Teknologi 2023, Vol. 5, No. 3
Publisher : SEULANGA SYSTEM PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60083/jidt.v5i3.390

Abstract

The purpose of this study was to obtain and determine the variables that influence the interest of pay later loan users in DKI Jakarta using the modified UTAUT 2 model by adding one perceived security variable. This study used a quantitative method by distributing questionnaires online to 163 pay later users. Using the PLS-SEM analysis approach with SmartPLS 3.3, of the 11 hypotheses tested, five had a significant effect, and six had no significant effect. The relationship path that has the greatest influence is behavioral intention and use behavior, while the path that has the least influence is social influence on use behavior. The results of this study provide recommendations on performance extension by increasing the performance of the pay later feature. Effort expectancy by making it easy to activate the pay later and providing limit adjustments. Social influence creates attractive ads and expands paid information. Hedonic motivation by improving the appearance of a more attractive user interface and increasing the use of the system with user experience. Price value by providing low interest and appropriate limits. Habit by following the recommendations of all variables as a reference for future improvement steps. Facilitating conditions pay later cooperates with other merchants as a payment option to expand the network. Perceived security by implementing fingerprint locks and enhancing user information security and privacy. Behavioral intention follows all recommendations on the factors that influence intention. and use behavior following the recommendations on the factors that influence the intensity level of the user's use of the pay later.
Analisis Algoritma ID3 Pada Kunjungan Akseptor KB di Kota Banjarmasin Yunita, Laurensia; Anisa, Fadhiyah Noor; Saputri, Rina
Jurnal Informasi dan Teknologi 2023, Vol. 5, No. 3
Publisher : SEULANGA SYSTEM PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60083/jidt.v5i3.392

Abstract

Adanya penurunan akseptor KB mulai dari bulan Februari hingga Maret akan memiliki dampak terhadap terjadinya kehamilan yang tidak diinginkan dan mengalami risiko dikehamilannya. Jika Akseptor yang sebelumnya aktif melakukan kunjungan ulang namun saat kunjungan berikutnya tidak melakukan kunjungan ulang maka proteksi terhadap kehamilan menjadi tidak ada sehingga kemungkinan kehamilan bisa terjadi. Dilihat dari beberapa alat kontrasepsi misalnya pil KB memiliki resiko kehamikan sebesar 20%, suntik KB sebesar 10% , IUD sebesar 15%. Jumlah tersebut jika terjadi penambahan kehamilan berkisar antara 370.000 sampai 500.000 kehamilan. Kunjungan ini bertujuan untuk mendapatkan pelayanan kontrasepsi oleh tenaga kesehatan dalam upaya menjarangkan kehamilan, menunda atau pun mengakhiri kesuburan. Namun selama wabah covid -19 dimana masyarakat diharuskan untuk tetap di rumah dan mengurangi berkegiatan diluar menyebabkan akseptor KB menunda untuk melakukan kunjungan ulang ke tenaga kesehatan karena khawatir tertular covid -19. Tujuan penelitian untuk mengetahui determinan kunjungan akseptor KB di Kota Banjarmasin pada masa pandemi covid-19. Dalam penelitian ini menggunakan pendekatan kuantitatif dengan sasaran wanita usia subur sebanyak 133 orang dan dianalisis menggunakan Algoritma ID3. Hasil penelitian menggunakan analisis algoritma ID3 terlihat faktor kunjungan akseptor KB didapatkan bahwa variabel pengetahuan merupakan variabel yang paling berpengaruh terhadap kunjungan akseptor KB. Sedangkan untuk variabel umur, pendidikan, dan dukungan suami menjadi variabel penyerta. Kesimpulan dari penelitian ini jika pengetahuan baik maka variabel yang menjadi penyerta utama adalah pendidikan. Pendidikan SMA dan PT akan secara langsung melakukan kunjungan ber KB, namun pendidikan SD akan melihat dukungan suami dan jumlah anak jika jumlah anak lebih dari 3 maka akseptor akan melakukan kunjungan berKB untuk mengatur kehamilan selanjutnya.
Implementasi Algoritma Decision Tree dan Random Forest dalam Prediksi Perdarahan Pascasalin Sinambela, Dewi Pusparani; Naparin, Husni; Zulfadhilah, Muhammad; Hidayah, Nurul
Jurnal Informasi dan Teknologi 2023, Vol. 5, No. 3
Publisher : SEULANGA SYSTEM PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60083/jidt.v5i3.393

Abstract

Perdarahan Postpartum (PPP) merupakan salah satu kegawatdaruatan pada persalinan yang dapat menyebabkan kematian di negara maju dan negara berkembang. Salah satu pencegahan terjadiya PPP dengan melakukan prediksi pada ibu bersalin dengan mempertimbangkan faktor faktor risiko menggunakan pendekatan model Machine Learning (ML). Algoritma Random Forest (RF) dan Decision Tree (DT) merupakan algoritma yang digunakan dalam prediksi kejadian PPP. Tujuan dari penelitian ini adalah mengembangkan kinerja dari Algoritma RF dan Algoritma RF untuk mengklasifikasi kejadian PPP. Hasil analisis Berdasarkan hasil analisis univariat yang ditunjukkan pada tabel 1 didapatkan ibu yang memiliki paritas > 4 sebanyak 102 orang (20,4%), jarak kehamilan ibu yang ≤ 2 tahun sebanyak 310 orang (62%), ibu pasca bersalin yang mengalami anemia sebanyak 124 orang (24,8%), ibu yang melahirkan bayi makrosomia sebanyak 60 orang (12 %), ibu yang mengalami komplikasi persalinan sebanyak 229 orang (45,8 %),ibu yang mengalami kehamilan ganda sebanyak 16 orang (3,2%), umur ibu yang berisiko sebanyak 132 orang (26,4%). Perbandingan tingkat akurasi algoritma RF mencapai 0,830 dibandingkan dengan algoritma DT sebesar 0.820, AUC RF 0.74. Hal ini menunjukan bahwa Algoritma RF mempunya perfomance metric lebih naik dibandingkan dengan algoritma DT. Algoritma Random Forest dapat dianggap sebagai salah satu algoritma representatif ML, yang dikenal karena kemudahannya dan efektivitasnya

Page 18 of 38 | Total Record : 378

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