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All Journal PROCESSOR Jurnal Ilmiah Sistem Informasi, Teknologi Informasi dan Sistem Komputer Jurnal Ilmiah Media Sisfo Jurnal Manajemen Teknologi dan Sistem Informasi Jurnal Pengabdian Masyarakat Unama Prosiding Seminar Nasional Ilmu Teknik
Yulia Arvita
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Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering

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Perancangan E-Office Administrasi Pada Kantor Kelurahan Muara Bulian Yulia Arvita; Agus Siswanto; Ibnu Sani Wijaya; Irawan Irawan; Agus Setiawan Sholeh
Jurnal Processor Vol 16 No 2 (2021): Processor
Publisher : LPPM STIKOM Dinamika Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33998/processor.2021.16.2.1093

Abstract

Management of administrative data at the Muara Bulian Village Office which is still conventional where data collection and reporting are still using bookkeeping, so that there is often difficulty in making letters, reports and searches, the absence of digital data back-up makes the administration process less efficient. So an efficient and effective information system is needed to support ticket sales bookkeeping. In addition, researchers also design computerized administrative applications. The benefit of this study is that it can improve the quality of service to the population. The results of this study are an administrative application as a tool for processing administrative data, letters and report generation. This application is expected to help employees of the Muara Bulian Village Office in providing the best service to the population. Keywords: E-Office, administration, Village Office
Analisa dan Perancangan Sistem Pendukung Keputusan Penentuan Pemberian Kredit Pada Bank XYZ Yulia Arvita
Jurnal Ilmiah Media Sisfo Vol 11 No 1 (2017): JURNAL ILMIAH MEDIA SISFO
Publisher : LPPM STIKOM Dinamika Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (598.521 KB)

Abstract

Kredit merupakan salah satu bentuk jasa yang ada dalam perbankan yaitu menyalurkan dana kepada masyarakat dengan menggunakan jaminan. Dalam pemberian suatu kredit atau pinjaman pada Bank XYZ terdapat 5 faktor dasar yang menjadi acuan dalam analisa pemberian kredit yang dikenal dengan 5C (Charater, Capacity, Capital, Collateral, Condition of economic). Faktor - faktor tersebut yang akan menjadi kriteria sistem pendukung keputusan. Dalam menganalisis kredit ini, membutuhkan waktu yang lama dan prosedur yang panjang. Maka dirancanglah sebuah sistem pendukung keputusan agar dapat memudahkan pihak bank khususnya bagian kredit dalam menganalisa proses kredit dan memberikan prioritas sehingga dapat memberikan keuntungan apabila kredit tersebut disetujui. Sistem pendukung keputusan ini menggunakan metode AHP yang memberikan informasi yang presisi agar dapat menghasilkan keputusan yang tepat untuk pemberian kredit usaha dan sistem ini akan difokuskan untuk menyelesaikan masalah ketidaktepatan informasi yang dibutuhkan untuk merumuskan keputusan pemberian kredit modal.
Analisa dan Perancangan Sistem Pendukung Keputusan Penentuan Pemberian Kredit Pada Bank XYZ Yulia Arvita
Jurnal Ilmiah Media Sisfo Vol 11 No 1 (2017): JURNAL ILMIAH MEDIA SISFO
Publisher : LPPM Universitas Dinamika Bangsa

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

Abstract

Kredit merupakan salah satu bentuk jasa yang ada dalam perbankan yaitu menyalurkan dana kepada masyarakat dengan menggunakan jaminan. Dalam pemberian suatu kredit atau pinjaman pada Bank XYZ terdapat 5 faktor dasar yang menjadi acuan dalam analisa pemberian kredit yang dikenal dengan 5C (Charater, Capacity, Capital, Collateral, Condition of economic). Faktor - faktor tersebut yang akan menjadi kriteria sistem pendukung keputusan. Dalam menganalisis kredit ini, membutuhkan waktu yang lama dan prosedur yang panjang. Maka dirancanglah sebuah sistem pendukung keputusan agar dapat memudahkan pihak bank khususnya bagian kredit dalam menganalisa proses kredit dan memberikan prioritas sehingga dapat memberikan keuntungan apabila kredit tersebut disetujui. Sistem pendukung keputusan ini menggunakan metode AHP yang memberikan informasi yang presisi agar dapat menghasilkan keputusan yang tepat untuk pemberian kredit usaha dan sistem ini akan difokuskan untuk menyelesaikan masalah ketidaktepatan informasi yang dibutuhkan untuk merumuskan keputusan pemberian kredit modal.
PELATIHAN PENGGUNAAN GOOGLE WRKSPACE DENGAN MENGGUNAKAN SMARTPHONE UNTUK SISWA SMP NEGERI 25 KOTA JAMBI Nurhayati; Yulia Arvita; Manja Purnasari; Yessi Hartiwi
Jurnal Pengabdian Masyarakat UNAMA Vol 2 No 1 (2023): JPMU Volume 2 Nomor 1 April 2023
Publisher : LPPM Universitas Dinamika Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33998/jpmu.2023.2.1.737

Abstract

Pada saat pandemi saat ini siswa di tuntut untuk bisa melaksanakan pembelajaran daring melalui media teknologi di rumah. Teknologi yang bisa di gunakan siswa dalam proses belajaran salah satu satu nya mayoritas siswa miliki adalah smartphone. Google workspace adalah salah satu aplikasi di smartphone yang bisa didownload dengan gratis.dan ini juga merupakan salah satu fasilitas yang digunakan dalam proses pembelajaran. Google workspace ini banyak jenis nya salah satu nya adalah google doc yang digunakan dalam proses pembelajaran. Tujuan di adakanya PKM ini adalah untuk memberikan sosialisasi dan pelatihan mengenai google doc yang merupakan salah satu solusi untuk mengerjakan tugas dari rumah selama proses pembelajaran daring lewat sarana smartphone. sehingga di harapkan siswa – siswa di SMP Negeri 25 Kota Jambi pada saat pandemi tetap dapat mengikuti pelajaran dan dapat membuat tugas sekolah dengan menggunakan smartphone.
Klasifikasi Metode Pembayaran Transaksi Menggunakan Algoritma Naïve Bayes dan Support Vector Machine: Studi Kasus 17 Coffee & Eatery Nur Aufa, Lia; Nurhadi Nurhadi; Yulia Arvita
Prosiding Seminar Nasional Ilmu Teknik Vol. 2 No. 2 (2025): Desember: Prosiding Seminar Nasional Ilmu Teknik
Publisher : Asosiasi Riset Ilmu Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/prosemnasproit.v2i2.88

Abstract

This study aims to classify customer payment methods at 17 Coffee & Eatery using machine learning algorithms, namely Naïve Bayes and Support Vector Machine (SVM). The increasing use of digital and non-cash payments has generated large volumes of transaction data that are rarely analyzed optimally, even though such data contain valuable information for business decision making. This research used secondary transaction data collected from January to March 2025, consisting of 10,147 transaction records. The dataset included several attributes such as order time, payment time, transaction type, total sales, number of items, and payment method. Data preprocessing was performed through data cleaning, feature engineering, normalization, and label encoding before being divided into training and testing sets with an 80:20 ratio. The Naïve Bayes and SVM models were then trained and evaluated using accuracy, precision, recall, F1-score, and ROC–AUC metrics. The results show that both algorithms were able to classify payment methods effectively, but SVM achieved higher accuracy and more stable performance than Naïve Bayes. These findings indicate that SVM is more suitable for handling complex and heterogeneous transaction patterns. The implementation of machine learning for transaction classification can support more efficient financial management and data-driven decision making for small and medium enterprises in the culinary sector.
Comparative Analysis of BiLSTM, CRF, and BiLSTM-CRF Models On Clinical Named Entity Recognition Tasks Using the NCBI Disease Corpus Dataset Agus Siswanto; Yulia Arvita; Muhammad Wardani; Febri
Jurnal Manajemen Teknologi Dan Sistem Informasi (JMS) Vol 6 No 2 (2026): JMS Vol 6 No 2 September 2026
Publisher : LPPM Universitas Dinamika Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33998/jms.2026.6.2.2928

Abstract

Biomedical Named Entity Recognition (NER) plays an important role in Clinical Natural Language Processing by enabling the automatic extraction of disease-related entities from medical text. This study compares the performance and stability of three sequence labeling approaches: Conditional Random Field (CRF), Bidirectional Long Short-Term Memory (BiLSTM), and BiLSTM-CRF. Experiments were conducted using the NCBI Disease Corpus, comprising 5,392 training instances, 918 validation instances, and 937 test instances, with a class imbalance ratio of 11.06:1. Each model employed 200-dimensional GloVe word embeddings, which achieved 78.2% vocabulary coverage. To assess the consistency of model performance, experiments were repeated across five different random seed configurations. The results demonstrate that BiLSTM-CRF achieved the highest F1-score of 78.86% (±0.34%), outperforming CRF at 78.49% and BiLSTM at 76.73% (±0.86%). Compared with BiLSTM, the hybrid model improved the F1-score by 2.13 percentage points, while its improvement over CRF reached 0.38 percentage points. BiLSTM-CRF also exhibited the most stable performance, as reflected by its lower standard deviation. Learning curve analysis further showed that BiLSTM-CRF consistently surpassed the other approaches after utilizing 40% of the training data. These findings suggest that combining BiLSTM's contextual representation capability with CRF-based sequence dependency modeling provides a more effective and stable approach for disease entity recognition in biomedical text..
Development of the DPD APERSI Jambi Membership System Based on Organizational Activity Monitoring Dwi Ayu Gusriyanti; Lazuardi Yudha Pradana; Yulia Arvita; Rofi'i, Imam
Jurnal Manajemen Teknologi Dan Sistem Informasi (JMS) Vol 6 No 2 (2026): JMS Vol 6 No 2 September 2026
Publisher : LPPM Universitas Dinamika Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33998/jms.2026.6.2.2945

Abstract

At the Jambi Provincial Chapter of APERSI, the processes for data collection and membership management are still handled using conventional methods—specifically, Microsoft Excel—without integration with other data systems. This leads to difficulties in monitoring member activity and managing the mandatory dues payable by developers, as well as frequent miscommunication regarding the presentation of organizational information. The objective of this research is to design a membership information system that facilitates more structured member data management and activity monitoring. The study results in an APERSI membership information system capable of streamlining member data collection, activity monitoring, annual dues management, and organizational administration through improved system integration. The system is expected to enhance the organization's performance in executing its programs and support more transparent and accurate membership management.
Co-Authors Agus Setiawan Sholeh Agus Siswanto Dwi Ayu Gusriyanti Febri Ibnu Sani Wijaya Irawan Irawan Lazuardi Yudha Pradana Manja Purnasari Muhammad Wardani Nur Aufa, Lia Nurhadi Nurhadi Nurhayati Nurhayati Rofi'i, Imam Yessi Hartiwi