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All Journal Teknika Jurnal Informatika Proceeding International Conference on Information Technology and Business Jurnal SIMADA (Sistem Informasi dan Manajemen Basis Data) Yumary: Jurnal Pengabdian kepada Masyarakat JUSTIN (Jurnal Sistem dan Teknologi Informasi) Jurnal Publika Pengabdian Masyarakat Jurnal INFOTEL
Nurlistiani, Rini
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Humanities Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Social Sciences Other

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PELATIHAN PENCACATAN KEUANGAN DAN PENERAPAN SOFTWARE POINT OF SALE (POS) PADA UMKM JAMUR MERANG KECAMATAN METRO SELATAN, KOTA METRO Wibaselppa, Anggawidia; Mutiara, Suci; Zulanda, Reisa Dyasvaro; Nurlistiani, Rini
Jurnal Publika Pengabdian Masyarakat Vol 6, No 2 (2024): Jurnal Publika Pengabdian Masyarakat
Publisher : Institut Informatika dan Bisnis Darmajaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30873/jppm.v6i2.4069

Abstract

Usaha Mikro, Kecil, dan Menengah (UMKM) sering menghadapi tantangan dalam pengelolaan keuangan, terutama dalam pencatatan laporan keuangan yang terstruktur. Hal ini dapat berdampak pada kurang optimalnya evaluasi kinerja usaha serta pengambilan keputusan bisnis. Pelatihan ini bertujuan untuk meningkatkan kemampuan pelaku UMKM Jamur Merang Mas Gagas di Kelurahan Sumbersari Bantul, Kecamatan Metro Selatan, Kota Metro, dalam melakukan pencatatan laporan keuangan sederhana berbasis Microsoft Excel dan menerapkan software Point of Sale (POS). Kegiatan pelatihan meliputi pengenalan konsep pencatatan keuangan sederhana, penggunaan fitur Microsoft Excel untuk membuat laporan keuangan, serta implementasi software POS dalam mendukung aktivitas penjualan dan manajemen inventaris. Pelatihan dilakukan dengan metode partisipatif, termasuk sesi teori, praktik langsung, dan diskusi interaktif. Hasil dari pelatihan ini menunjukkan peningkatan pemahaman dan keterampilan peserta dalam menyusun laporan keuangan yang terstruktur, serta efisiensi dalam proses pencatatan transaksi penjualan menggunakan software POS. Diharapkan, penerapan hasil pelatihan ini dapat membantu UMKM Jamur Merang meningkatkan transparansi keuangan, mempermudah pengambilan keputusan, dan mendukung pertumbuhan usaha secara berkelanjutan.
Pengembangan Keterampilan Associate Data Scientist melalui Pelatihan dengan RapidMiner Safitri, Egi; Nurlistiani, Rini; Kurniawan, Hendra
Yumary: Jurnal Pengabdian kepada Masyarakat Vol. 5 No. 4 (2025): Juni
Publisher : Penerbit Goodwood

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35912/yumary.v5i4.3664

Abstract

Purpose: This study aims to evaluate the effectiveness of an online Associate Data Scientist training program that utilizes RapidMiner as the primary platform for teaching data science and machine learning. The goal is to assess participants' improvements in data preprocessing, algorithm application, and model evaluation skills. Methodology/approach: The training program was conducted via Zoom and included interactive lectures, live demonstrations, hands-on exercises, and individual assignments. RapidMiner was used as the main tool throughout the sessions. Participants were evaluated through tasks assigned in each session and a final project that required them to analyze a dataset, apply relevant algorithms, and assess model performance. Results/findings: The results showed significant improvement in participants’ technical understanding and application skills. The average final project score was 87.0, indicating strong competence in data handling, algorithm selection, and model evaluation. Most participants completed the project successfully, demonstrating their readiness to apply data science concepts in real-world scenarios. Conclusions: The online training effectively bridged the gap between theory and practice, proving that remote learning can deliver quality outcomes in technical education. The combination of RapidMiner and a structured training format enabled participants to gain applicable skills in data science. However, improvements in instructional delivery and interaction are still needed to optimize learning experiences. Limitations: Challenges included internet connectivity issues and limited real-time interaction, which sometimes hindered learning flow and instructor support. Contribution: This study provides valuable insights into data science education, proving that online programs with practical tools like RapidMiner can successfully build core competencies in aspiring data professionals.
Optimization of Genetic Algorithm from Comparison of Machine Learning for Heart Disease Prediction Purwati, Neni; Nurlistiani, Rini
JUSTIN (Jurnal Sistem dan Teknologi Informasi) Vol 13, No 2 (2025)
Publisher : Jurusan Informatika Universitas Tanjungpura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26418/justin.v13i2.87898

Abstract

Ischemic Heart Disease (IHD) is the leading cause of death worldwide, accounting for 13% of global fatalities. The number of deaths caused by IHD rose from 2.7 million in 2000 to 9.1 million in 2021, an increase of 6.4 million. IHD can be diagnosed through medical examinations or various health tests, as well as by leveraging technological advancements in artificial intelligence to enable early disease detection. This early detection is crucial for preventing heart disease, as there is currently no cure for the condition. This study aims to compare machine learning algorithms based on decision tree methods (Decision Tree, Random Forest, and Gradient Boosted Tree) with optimization using genetic algorithms to predict heart disease. The dataset used includes information from 8,625 patients who have experienced heart attacks, featuring attributes such as Sex, General Health, Age Category, Height (in meters), Weight (in kilograms), BMI, and "Had Heart Attack" as the label attribute. The initial modeling phase involved splitting the data into 80% for training (6,900 samples) and 20% for testing (1,725 samples). The results showed that the Random Forest model achieved the highest accuracy at 95.26%, narrowly surpassing the Decision Tree model, which attained 95.22%, by 0.04%. Meanwhile, the Gradient Boosted Tree model demonstrated the lowest accuracy at 90.99%. Subsequently, the application of the Genetic Algorithm significantly improved the accuracy, precision, and recall metrics across all three models, although the recall value for the Gradient Boosted Tree model decreased by 5.17%.
Pengujian Black box Pada Sistem Informasi Layanan PPID Dengan Metode Equivalence Partitioning Kausar, Firdaus; Nurlistiani, Rini; Nurjoko, Nurjoko; Rahardi, Agus
TEKNIKA Vol. 19 No. 3 (2025): Teknika September 2025
Publisher : Politeknik Negeri Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5281/zenodo.15567123

Abstract

Penelitian ini bertujuan untuk menguji kualitas perangkat lunak pada Sistem Informasi Layanan PPID menggunakan metode pengujian black box dengan teknik Equivalence Partitioning. Metode ini digunakan untuk mengidentifikasi kesalahan input berdasarkan kelas-kelas ekivalensi guna mengurangi jumlah kasus uji tanpa mengurangi efektivitas pengujian. Pengujian dilakukan pada fitur-fitur utama sistem seperti pengajuan permohonan informasi, pengajuan keberatan, serta fitur login pengguna. Hasil pengujian menunjukkan bahwa semua fitur yang diuji berhasil melewati skenario uji yang telah ditentukan, menandakan bahwa sistem telah berjalan sesuai dengan yang diharapkan. Dengan demikian, sistem ini dapat dikatakan memiliki tingkat keandalan yang baik dalam hal fungsionalitas.
Application of Ensemble Machine Learning for Infectious Diseases with Vaccine Intervention: A Global COVID-19 Case Study Safitri, Egi; Fikri, Ruki Rizalnul; Nurlistiani, Rini
JURNAL INFOTEL Vol 16 No 4 (2024): November 2024
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/infotel.v16i4.1263

Abstract

The COVID-19 pandemic has posed significant challenges worldwide, especially in controlling the spread of the disease through vaccination and active case monitoring. This study aims to evaluate the effectiveness of various ensemble machine-learning models in predicting the number of daily vaccinations and the number of active cases of COVID-19 based on global data. The models used include Random Forest, Bagging, Gradient Boosting Machine (GBM), AdaBoost, and XGBoost. The evaluation results show that Random Forest provides the best performance in predicting both the number of daily vaccinations and active COVID-19 cases, with a MSE value of 4.7e+09, MAE of 16,971.1, and RMSE of 68,557.2 for daily vaccinations, as well as an R² Score of 0.989, indicating a high ability to explain data variability. The Bagging model also showed excellent results with MSE of 4.78e+09 and MAE of 17,039.8. In contrast, the AdaBoost model performed the worst in predicting both variables, with an MSE of 5.54e+10 and an MAE of 106,228.6. These findings suggest that Random Forest and Bagging are superior models for predicting the number of daily vaccinations and active COVID-19 cases. This study provides important insights into using machine learning to predict vaccination effectiveness and active case dynamics, aiding decision-making in global pandemic control efforts.
Implementasi Pemasaran Digitalisasi Jasa Fotografi Berbasis Web Linda, Deppi; Nurlistiani, Rini; Nursiyanto, Nursiyanto; Zulkarnaini, Zulkarnaini; Purnomo, Hendri
Jurnal Informatika Vol 24 No 2 (2024): Jurnal Informatika
Publisher : Institut Informatika Dan Bisnis Darmajaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30873/jurnalinformatika.v24i2.746

Abstract

As the digital era develops, the need for photography services is increasing. To meet their needs, many individuals and organizations seek photography services for various purposes, such as personal photo shoots, weddings, and other photography packages. When booking a photography studio, we often encounter obstacles such as the difficulty of finding a suitable studio, determining the price and package, and the slow booking process. By digitalization web-based photography service booking market, we have found a solution that allows customers to easily search for photography studios, view portfolios, and compare prices and packages offered. This allows the photography studio to expand its market reach, faster reservations, and improve the quality of its services. They used PHP programming language and Extreme Programming (XP) method to create a web-based information system to design a photo booking marketplace. The system aims to simplify the process of online photo booking in the region
SISTEM INFORMASI E-COMMERCE TOKO HIJAB BERBASIS WEB DENGAN METODE EXTREME PROGRAMMING Nurlistiani, Rini; Kurniawan, Hendra; Yuliawati, Dona; Maria, Okta
Jurnal SIMADA (Sistem Informasi dan Manajemen Basis Data) Vol. 7 No. 1 (2024): Jurnal SIMADA (Sistem Informasi dan Manajemen Basis Data)
Publisher : LP2M Institut Informatika Dan Bisnis Darmajaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30873/simada.v7i1.393

Abstract

Development of increasingly modern technological devices can provide advantages for entrepreneurs to market services and products with the aim of expanding market share with a wide reach. The scope of product sales in an area becomes ineffective in being able to compete to attract consumer interest. The role of information technology can be carried out using internet media so that consumers can access it online or can be called e-commerce. The object of this research was carried out at a hijab shop in the Natar area, South Lampung. The problems that exist include the sales process which is carried out directly, such as consumers coming to the shop to buy products, which has an impact on operational costs, energy and time, especially consumers who are in areas where they cannot see information on the availability of the product they want to buy. The system development method used is Extreme Programming. The results obtained are that the use of the website is running well, as evidenced by the results of system testing using blackbox testing of 91.66%, which means that this e-commerce information system is running successfully and can be used by consumers, especially in the South Lampung area and its surroundings.
Assessment of Usability and Acceptance of An Academic Information System Using SUS And TAM Adaptation Nurlistiani, Rini; Romadona, Romadona; Kurniawan, Hendra; Nursiyanto, Nursiyanto
Prosiding International conference on Information Technology and Business (ICITB) 2023: INTERNATIONAL CONFERENCE ON INFORMATION TECHNOLOGY AND BUSINESS (ICITB) 9
Publisher : Proceeding International Conference on Information Technology and Business

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

Abstract

Organizations, companies, and the world of education carry out all learning activities using e-learning. There is an important part that requires an academic system with structured data, namely the system at private universities in Indonesia, for example,Informatics and Business Institute Darmajaya. Darmajaya is one of the educational institutes that uses online learning media information technology called e-learning for students and lecturers. The newest information system used at IIB Darmajaya is the academic information system (AIS) which consists of Darmajaya students and lecturers. Result from the assessment showing of lecturers understand how to use AIS with value 56.92, and 65.93 from students of IIB Darmajaya. Keywords :SUS,TAM, Evaluation, Acceptance, Usability
Co-Authors - Nurjoko Agus Rahardi, Agus Deppi Linda Dona Yuliawati Fikri, Ruki Rizalnul Hendra Kurniawan Hendri Purnomo Kausar, Firdaus Maria, Okta Mutiara, Suci Neni Purwati Nursiyanto Romadona, Romadona Safitri, Egi Sugeng, Santoso Wibaselppa, Anggawidia Zulanda, Reisa Dyasvaro