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INDONESIA
JURNAL ILMIAH INFOKOM
Published by Politeknik Piksi Ganesha Indonesia
ISSN : 2339188X     EISSN : 27224147     DOI : https:/doi.org/10.56689
Core Subject : Science, Engineering,
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering
Computer Science, Artificial Intelligency, Cyber Ethnic, E-Commerce, E-Government, E-Learning, Cloud Computing, Information Technology, Information System, Software Engineering, Architecture Enterprise, Database, Data Mining, Data Security, Network Engineering, Network Security.
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 138 Documents
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PERANCANGAN APLIKASI SKRINING GUNA EFEKTIVITAS PENGISIAN KUISONER SKRINING DI PUSKESMAS PABUARAN SUBANG Yuyun Yunengsih; Isty Youandinie; Rini Suwartika Kusumadiarti
INFOKOM (Informatika & Komputer) Vol 13 No 2 (2025): JURNAL INFOKOM DESEMBER 2025
Publisher : POLITEKNIK PIKSI GANESHA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56689/infokom.v13i2.2144

Abstract

This study aims to develop a screening questionnaire application to improve the effectiveness, efficiency, and accuracy of the questionnaire filling process at Pabuaran Subang Public Health Center. The development method used is the Rational Unified Process (RUP) consisting of the inception, elaboration, construction, and transition phases. The main problem is that the process is still manual, requiring a long time, prone to input errors, and difficult for data processing. The results show that the developed application accelerates filling, minimizes recording errors, and facilitates health workers in accessing and analyzing screening data. This application is expected to be further developed into an integrated system with real-time data analysis to enhance the quality of public health services
DESAIN SISTEM INFORMASI KELENGKAPAN FORMULIR INFORMED CONSENT RAWAT INAP DENGAN METODE AGILE Ririn Nur Fajrin; Yuyun Yunengsih; Rini Suwartika Kusumadiarti
INFOKOM (Informatika & Komputer) Vol 13 No 2 (2025): JURNAL INFOKOM DESEMBER 2025
Publisher : POLITEKNIK PIKSI GANESHA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56689/infokom.v13i2.2172

Abstract

Completeness of informed consent forms is a prerequisite for clinical quality and legal protection in inpatient services. However, in many hospitals, informed consent analysis is still combined with general summaries of medical record incompleteness, so analysis of each informed consent component is not carried out specifically. This leads to a lack of focused monitoring, potentially reducing the quality of medical records. This study designed and evaluated an information system to analyze the completeness of informed consent in an integrated, accurate, and actionable manner. The system development method followed the Agile (Scrum) framework. Agile is an iterative and flexible software development approach that emphasizes team collaboration and rapid response to change. The main stages of the Agile method include: (1) Plan; (2) Design; (3) Develop; (4) Test; (5) Deploy; (6) Review. It is concluded that the digitalization of informed consent completeness analysis based on Agile provides a flexible and adaptive solution for improving medical record quality and patient safety. Further work is recommended in the form of integration with electronic medical records, the addition of quality indicator dashboards, and controlled trials to assess the impact on process efficiency and compliance.
AUTOMATISASI PENDAFTARAN RAWAT JALAN UNTUK MENINGKATKAN EFEKTIVITAS LAYANAN KESEHATAN DI KLINIK GIGI DRG. MIRANTI P DARMAWATI Ivo Ayu Yuliani; Yuyun Yunengsih; Falaah Abdussalaam
INFOKOM (Informatika & Komputer) Vol 13 No 2 (2025): JURNAL INFOKOM DESEMBER 2025
Publisher : POLITEKNIK PIKSI GANESHA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56689/infokom.v13i2.2189

Abstract

The patient registration process at Klinik Gigi drg. Miranti P. Darmawati is still carried out manually, often causing long queues, data entry errors, and service delays. This study aims to develop an automated outpatient registration system to improve service effectiveness. The research applies the Waterfall method, starting from needs analysis, system design, implementation, and testing. Data were collected through observations of the registration process and interviews with clinic staff. The results show that the automation system can speed up the registration process, reduce data entry errors, and increase satisfaction for both patients and staff. It is recommended that the system be further developed with integration to electronic medical records and a schedule reminder feature to achieve more optimal healthcare services.
APLIKASI PENJUALAN ANEKA OLAHAN IKAN BERBASIS WEB MENGGUNAKAN METODE MARKETPLACE Iyan Sunandar; Sri Nuryani; Fachmi Ramdani
INFOKOM (Informatika & Komputer) Vol 13 No 2 (2025): JURNAL INFOKOM DESEMBER 2025
Publisher : POLITEKNIK PIKSI GANESHA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56689/infokom.v13i2.2259

Abstract

Marketing activities are a form of assessment of the success of marketing activities carried out comprehensively by a company or organization. Thus, marketing activities can be viewed as a concept to measure the extent to which results are achieved by the company's products. This study aims to uncover the forms and processes of marketing activities at the Various Fish Processing Gallery in Ambulu Village, Losari District. This study used a qualitative approach through literature studies, interviews, and field studies to observe the processed fish products produced by the gallery. The results showed that marketing activities were carried out by prioritizing the authentic taste of the product and the quality of its packaging. Marketing also utilized a web-based sales application with a marketplace method. The processed fish products from this gallery have a distinctive taste that is a main selling point. However, promotional activities are still limited to the Ciayumajakuning area. Nevertheless, the use of a web-based application with a marketplace method is expected to increase sales results compared to before. In terms of pricing, the Various Fish Processing Gallery in Ambulu Village applies competitive prices and is able to compete in the market
EXPLAINABLE MACHINE LEARNING UNTUK PREDIKSI HARGA MOBIL BEKAS DAN ANALISIS FAKTOR PENENTU HARGA Dwi Robiul R; M. Al-Adib; Romi Antoni; Diyo Mollana F; Rahmad S; Fauzan Hamdi R; Adil Setiawan
INFOKOM (Informatika & Komputer) Vol 13 No 1 (2025): JURNAL INFOKOM JUNI 2025
Publisher : POLITEKNIK PIKSI GANESHA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56689/infokom.v13i1.2322

Abstract

This research aims to predict used car prices and analyze the price determinants using an Explainable Machine Learning (XAI) approach. Used car price prediction presents a significant challenge in the automotive market, where pricing is influenced by various complex variables. The methodology involves comparing the performance of two machine learning models: linear regression (LR) and random forest (RF), trained on a dataset comprising 2,059 used car data points and 19 engineered features. The best-performing model is then interpreted using the SHAP (SHapley Additive exPlanations) method to identify the contribution of each feature. The evaluation results demonstrate that the Random Forest (RF) model exhibits superior performance compared to the Linear Regression model. The Random Forest model achieved a coefficient of determination (R2) of 0.819 and a Mean Absolute Error (MAE) of 294,591.0 . This performance is significantly better than the linear regression model, which yielded an R2 of 0.771 and an MAE of 716,221.3. The SHAP interpretive analysis identified the most significant price determinants. In sequential order, the five most dominant factors influencing price prediction are max power, car age, vehicle length (length_num), vehicle width (width_num), and kilometer (mileage). This finding provides transparent and justifiable insights into the key variables underlying price fluctuations in the used car market.
PREDIKSI JUMLAH WISATAWAN MANCANEGARA KE INDONESIA MENGGUNAKAN ALGORITMA LINEAR REGRESSION DAN RANDOM FOREST REGRESSION Adil Setiawan; Susiana Khosasih; Marulak Lasron Siahaan; Khoiri Sutan Hasibuan; Bualazatulo Laia; Satriyo Wibowo
INFOKOM (Informatika & Komputer) Vol 13 No 1 (2025): JURNAL INFOKOM JUNI 2025
Publisher : POLITEKNIK PIKSI GANESHA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56689/infokom.v13i1.2326

Abstract

Tourism is one of Indonesia’s leading sectors, contributing significantly to the national economy. Forecasting the number of international tourist arrivals is a strategic necessity to support policy planning and the sustainable development of the tourism industry. This study aims to compare the performance of two regression algorithms, Linear Regression and Random Forest Regression, in forecasting international tourist arrivals to Indonesia. The dataset covers the period 2020–2025, obtained from the Central Bureau of Statistics (BPS) with variables that underwent preprocessing such as normalization and handling of missing values. The methodology includes an 80:20 train-test split, tabular regression, and parameter tuning for Random Forest Regression to enhance model performance. Linear Regression was selected as a baseline model, while Random Forest Regression was chosen for its capability to model nonlinear patterns. Model evaluation was conducted using Mean Absolute Error (MAE), Root Mean Squared Error (RMSE), and R² Score. The results show that Linear Regression produced an RMSE of 59,967.668, MAE of 14,837.645, and R² Score of 0.007, indicating low accuracy. In contrast, Random Forest Regression achieved substantially better results with an RMSE of 9,696.530, MAE of 1,193.143, and R² Score of 0.974. These findings confirm that Random Forest Regression provides higher accuracy than Linear Regression, particularly in addressing seasonal patterns and uncertainties caused by global factors. In conclusion, Random Forest Regression can be considered a more reliable forecasting method for predicting international tourist arrivals. The forecasting results can serve as a basis for decision-making in destination capacity planning, foreign exchange revenue estimation, and risk mitigation against global disruptions (pandemics, geopolitical issues, crises), thereby supporting adaptive and sustainable strategies for national tourism development.
OPTIMASI PIPELINE KLASIFIKASI PENYAKIT PADI MENGGUNAKAN STRATEGI AUGMENTASI CITRA INTENSIF DAN TRANSFER LEARNING EFFICIENTNET-B0 Dwi Robiul R; Diyo Mollana F; Nanda S; Johan; Rahmad S; Satriyo W; Rika Rosnelly
INFOKOM (Informatika & Komputer) Vol 13 No 2 (2025): JURNAL INFOKOM DESEMBER 2025
Publisher : POLITEKNIK PIKSI GANESHA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56689/infokom.v13i2.2355

Abstract

Rice plant diseases represent a significant challenge to global food productivity. This study aims to optimize a rice disease classification pipeline using the EfficientNet-B0 architecture combined with intensive image augmentation strategies and transfer learning. The dataset comprises 10,407 rice leaf images categorized into 10 classes, including healthy conditions and nine types of diseases. Augmentation strategies such as random rotation, color jittering, and random resized cropping were implemented to enhance model robustness against diverse field conditions. Evaluation results demonstrate that the model achieved outstanding performance, with a Top-1 Accuracy of 96.25% and a Top-5 Accuracy of 99.90%. Grad-CAM++ analysis validated that the model accurately focuses feature extraction on pathological leaf areas. t-SNE visualization revealed clear feature cluster separation between classes, further supported by ROC curve AUC values reaching 1.00 for the majority of categories. This research confirms that the proposed pipeline is highly reliable for early rice disease detection and holds significant potential for mobile device implementation to assist farmers.
IMPLEMENTASI SISTEM ABSENSI BERBASIS GPS PADA PERANGKAT MOBILE UNTUK MONITORING KEHADIRAN SISWA DI SMK TARUNA ABDI BANGSA Atika Sari; Rini Suwartika Kusumadiarti; Candra Mecca Sufyana
INFOKOM (Informatika & Komputer) Vol 13 No 1 (2025): JURNAL INFOKOM JUNI 2025
Publisher : POLITEKNIK PIKSI GANESHA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56689/infokom.v13i1.2709

Abstract

Student attendance management is a crucial aspect of the educational process, closely related to student discipline, learning engagement, and performance evaluation. However, conventional manual attendance systems widely used in schools still suffer from several weaknesses, including vulnerability to data manipulation, delayed recapitulation, and a lack of transparency. With advancements in information and communication technology, leveraging GPS (Global Positioning System) technology on mobile devices presents a novel alternative for a more modern, efficient, and accurate attendance system. This research aims to design, develop, and implement a GPS-based attendance system on mobile devices that enables automatic recording of student attendance based on their geographical location. The methodology employed is Research and Development (R&D), utilizing a prototype model that encompasses stages of needs analysis, system design, development, testing, and evaluation. The implementation results indicate that the GPS-based attendance system can reduce proxy attendance practices, enhance administrative efficiency, and provide real-time attendance data that can be monitored by both school authorities and parents.

Page 14 of 14 | Total Record : 138

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