Articles
<![CDATA[Rekayasa Aplikasi Pengarsipan Surat Permohonan Hak Milik Tanah Dengan menggunakan Metode Prototyping ]]>
<![CDATA[Egia Rosi Subhiyakto]]>;
<![CDATA[Yani Parti Astuti]]>;
<![CDATA[Danang Wahyu Utomo]]>
<![CDATA[ Infotekmesin Vol 13 No 1 (2022): Infotekmesin: Januari, 2022 ]]>
Publisher : <![CDATA[P3M Politeknik Negeri Cilacap ]]>
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DOI: 10.35970/infotekmesin.v13i1.891
<![CDATA[National Land Agency received requests for land rights every day. The letters can be submitted through two stages of acceptance and archiving. Still using conventional systems makes data retrieval requires relatively more time. This research aims to design and build an information system data archiving for incoming request at the National Land Agency. The software has been designed with login feature, data management land owners and land owner data search and print feature data. Analysis of system requirements using object-oriented method which uses the use-case diagram in order to illustrate the functionality of the system and some of the criteria of non-functional requirements are also outlined. The next step was the coding implementation and evaluation of the system built. The system development method used was the prototyping method. The selection of this method was intended, therefore the client can get a clear picture of the system being built. Evaluation was conducted in the developer and the user environment. The evaluation in the user environment was done by distributing questionnaires covering three parameters namely the usefulness of the application, ease of use and user satisfaction. The results showed that the information systems built have a useful value (85.7%) and are easy to use (100%), therefore it satisfied the users.]]>
<![CDATA[Pengembangan Sistem Modul Komisi Dinamis pada Modul Penjualan ERP - Odoo12 ]]>
<![CDATA[Danang Wahyu Utomo]]>;
<![CDATA[Defri Kurniawan]]>;
<![CDATA[Egia Rosi Subhiyakto]]>
<![CDATA[ Infotekmesin Vol 12 No 2 (2021): Infotekmesin: Juli 2021 ]]>
Publisher : <![CDATA[P3M Politeknik Negeri Cilacap ]]>
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DOI: 10.35970/infotekmesin.v12i2.729
<![CDATA[The improvement of the sales system not only focuses on the advantage result of the sales transaction but also can use another parameter to improve it. One of a parameter used is commission. Giving commissions to the salesperson can improve their work performance and have an impact on increasing sales targets. Based on the study literature, the problem faced by the company is the discrepancy of commission. It canbe affected by several factors such as the commission system are not integrated with the main system, improper formula, or there are many systems used in the company so it the staff are difficult to integrate the system. For example, the company using Odoo ERP to support sales transaction and use commission information system separately. The salesperson must integrate sales data into both of the systems. It can affect the time delay of decision commission. Based on the problem above, we propose a prototype commission system that integrates with Odoo12. The salesperson does not need to integrate data manually into the system because it automatically integrates into the system. This study uses a prototyping model as a software development method. The results show that the commission system can implement on the Odoo12 ERP to decide commission to the salesperson. 70% of respondent agree that system has able to use in order to setting up commission module on Odoo]]>
<![CDATA[Rekomendasi Produk E-commerce Berbasis Klasifikasi Ulasan Menggunakan Ensemble Random Forest dan Teknik Boosting ]]>
<![CDATA[Donny Saputro]]>;
<![CDATA[Danang Wahyu Utomo]]>
<![CDATA[ Infotekmesin Vol 15 No 2 (2024): Infotekmesin, Juli 2024 ]]>
Publisher : <![CDATA[P3M Politeknik Negeri Cilacap ]]>
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DOI: 10.35970/infotekmesin.v15i2.2315
<![CDATA[The increasing popularity of e-commerce poses a new challenge to provide customers with a more personalized and effective shopping experience. In situations like this, product recommendations are very important to increase consumer satisfaction and increase sales. Using Random Forest and Boosting ensemble techniques, this research introduces a method for e-commerce product recommendation based on user review analysis. The Aim is to test the Random Forest algorithm with several boosting techniques for ensemble learning. The results show that the Random Forest method combined with the Xgboost technique can provide product recommendations that are 87.25% more accurate and relevant than other boosting techniques. In precision analysis, Random Forest-XGBoost achieved a higher accuracy of 90% compared to other boosting techniques. Additionally, the combined use of Boosting and Random Forest techniques improves the model's performance in handling complexity and variation in e-commerce product reviews.]]>
<![CDATA[Klasifikasi Stunting Balita menggunakan Metode Ensemble Learning dan Random Forest ]]>
<![CDATA[Selma Marsya Finda]]>;
<![CDATA[Danang Wahyu Utomo]]>
<![CDATA[ Infotekmesin Vol 15 No 2 (2024): Infotekmesin, Juli 2024 ]]>
Publisher : <![CDATA[P3M Politeknik Negeri Cilacap ]]>
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DOI: 10.35970/infotekmesin.v15i2.2326
<![CDATA[Stunting is a long-term condition that describes nutritional deficiencies that affect children's growth and development from an early age, especially linear growth. Examination of the stunting status of toddlers in Indonesia, especially at the Karanganyar Community Health Center, still uses book calculations so errors are still found in the use of formulas which result in inaccuracies in the classification of stunting. Efforts to improve research results were carried out using the Random Forest algorithm which was enhanced with ensemble methods such as the Bagging and Boosting methods to classify stunting data. The aim of this research is to find out which technique will produce the best and most accurate accuracy. The Ensemble Boosting techniques used are XGBoost and Gradient Boosting. This research uses a dataset from the Karanganyar Health Center, Semarang City with a total of 2000 data records. The test results produced the highest accuracy algorithm, namely the Random Forest + Bagging algorithm which obtained accuracy results of 98.25%. Based on the analysis results obtained, the Bagging and Boosting methods can accurately predict stunting data.]]>
<![CDATA[Pembelajaran Ensemble untuk Klasifikasi Ulasan Pelanggan E-commerce Menggunakan Teknik Boosting ]]>
<![CDATA[Matius Rama Hadi Suryanto]]>;
<![CDATA[Danang Wahyu Utomo]]>
<![CDATA[ Infotekmesin Vol 15 No 2 (2024): Infotekmesin, Juli 2024 ]]>
Publisher : <![CDATA[P3M Politeknik Negeri Cilacap ]]>
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DOI: 10.35970/infotekmesin.v15i2.2314
<![CDATA[Technological developments have developed rapidly and impact changing behavior in daily activities. Now, selling and buying activities are carried out in e-commerce services. The increase in e-commerce users is the main factor in improving the quality of e-commerce services. One of the factors to improve the quality of e-commerce services is customer reviews. Customer reviews are useful for shop owners to find out whether the product offered has positive or negative reviews. The large number of customer reviews is the main factor in the difficulty of shop owners in classifying customer reviews. This study proposes classifying customer reviews using ensemble learning with boosting techniques such as XGBoost, AdaBoost, Gradient Boosting, and LightGBM. The use of an ensemble with a boosting technique aims to improve the algorithm’s performance. In a test scenario apply majority voting to produce the best performance from each algorithm. The result shows that the XGBoost algorithm produces higher accuracy than other techniques are 92.30%. On the analysis of matric evaluation of precision, recall, and F1-Score, XGBoost produces higher true positive values than other techniques such as AdaBoost, Gradient Boosting, and Light GBM]]>
<![CDATA[Prediksi Diabetes menggunakan Metode Ensemble Learning dengan Teknik Soft Voting ]]>
<![CDATA[Hilmi Hanif]]>;
<![CDATA[Danang Wahyu Utomo]]>
<![CDATA[ Infotekmesin Vol 16 No 1 (2025): Infotekmesin: Januari 2025 ]]>
Publisher : <![CDATA[P3M Politeknik Negeri Cilacap ]]>
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DOI: 10.35970/infotekmesin.v16i1.2534
<![CDATA[Diabetes is a chronic disease characterized by high blood glucose levels due to the body's inability to produce or use insulin effectively. This disease is one of the serious global health problems, and it has a significant impact; therefore, early detection is very important. Efforts to overcome this challenge can be made by applying machine learning, which provides a new and effective approach. This study aims to predict diabetes with a higher accuracy level through the Ensemble Learning Soft Voting method. In addition, the data balancing technique using SMOTE is applied to overcome the problem of imbalance in the data set. This study also compares various classification models using Machine Learning algorithms, namely LightGBM, XGBoost, and Random Forest. The test results show that the Random Forest model achieves the highest level of accuracy at 97.20%. In comparison, the Ensemble Learning Soft Voting method that combines the three algorithms has increased the accuracy to 97.74%. This Ensemble Learning approach has proven effective in significantly improving predictions and performing better than a single model.]]>
<![CDATA[Deteksi Dini Gangguan Kesehatan Mental dengan Model Bert dan Algoritma Xgboost ]]>
<![CDATA[Rahmadika Putri Tresyani]]>;
<![CDATA[Wahyu Utomo, Danang]]>;
<![CDATA[Maldini, Naufal]]>
<![CDATA[ Infotekmesin Vol 16 No 1 (2025): Infotekmesin: Januari 2025 ]]>
Publisher : <![CDATA[P3M Politeknik Negeri Cilacap ]]>
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DOI: 10.35970/infotekmesin.v16i1.2535
<![CDATA[Mental health disorders are severe conditions that affect a person's thoughts, feelings, behavior, and well-being. Data from the World Health Organization (WHO) shows that more than 264 million people worldwide experience depression, one of the most common forms of mental health disorders. However, limited access to psychological services, such as lack of professionals and high costs, are major challenges in providing adequate support. Therefore, innovative technology-based solutions are needed for efficient and affordable psychological support. Efforts to improve research results to develop a mental health chatbot model by combining BERT (Bidirectional Encoder Representations from Transformers) and XGBoost (Extreme Gradient Boosting) models. The BERT model is used to understand the context of the conversation, while the XGBoost algorithm is used for text classification. The dataset used comes from Kaggle, which consists of 312 question patterns with several patterns or classes, namely 79 classes. The results of the program implementation test produced a percentage of 93.05% and output in the form of a program in the execution of the model on Google Colab..]]>
<![CDATA[Pengembangan Sistem Modul Komisi Dinamis pada Modul Penjualan ERP - Odoo12 ]]>
<![CDATA[Wahyu Utomo, Danang]]>;
<![CDATA[Kurniawan, Defri]]>;
<![CDATA[Rosi Subhiyakto, Egia]]>
<![CDATA[ Infotekmesin Vol 12 No 2 (2021): Infotekmesin: Juli 2021 ]]>
Publisher : <![CDATA[P3M Politeknik Negeri Cilacap ]]>
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DOI: 10.35970/infotekmesin.v12i2.729
<![CDATA[The improvement of the sales system not only focuses on the advantage result of the sales transaction but also can use another parameter to improve it. One of a parameter used is commission. Giving commissions to the salesperson can improve their work performance and have an impact on increasing sales targets. Based on the study literature, the problem faced by the company is the discrepancy of commission. It canbe affected by several factors such as the commission system are not integrated with the main system, improper formula, or there are many systems used in the company so it the staff are difficult to integrate the system. For example, the company using Odoo ERP to support sales transaction and use commission information system separately. The salesperson must integrate sales data into both of the systems. It can affect the time delay of decision commission. Based on the problem above, we propose a prototype commission system that integrates with Odoo12. The salesperson does not need to integrate data manually into the system because it automatically integrates into the system. This study uses a prototyping model as a software development method. The results show that the commission system can implement on the Odoo12 ERP to decide commission to the salesperson. 70% of respondent agree that system has able to use in order to setting up commission module on Odoo]]>
<![CDATA[Rekayasa Aplikasi Pengarsipan Surat Permohonan Hak Milik Tanah Dengan menggunakan Metode Prototyping ]]>
<![CDATA[Rosi Subhiyakto, Egia]]>;
<![CDATA[Parti Astuti, Yani]]>;
<![CDATA[Wahyu Utomo, Danang]]>
<![CDATA[ Infotekmesin Vol 13 No 1 (2022): Infotekmesin: Januari, 2022 ]]>
Publisher : <![CDATA[P3M Politeknik Negeri Cilacap ]]>
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DOI: 10.35970/infotekmesin.v13i1.891
<![CDATA[National Land Agency received requests for land rights every day. The letters can be submitted through two stages of acceptance and archiving. Still using conventional systems makes data retrieval requires relatively more time. This research aims to design and build an information system data archiving for incoming request at the National Land Agency. The software has been designed with login feature, data management land owners and land owner data search and print feature data. Analysis of system requirements using object-oriented method which uses the use-case diagram in order to illustrate the functionality of the system and some of the criteria of non-functional requirements are also outlined. The next step was the coding implementation and evaluation of the system built. The system development method used was the prototyping method. The selection of this method was intended, therefore the client can get a clear picture of the system being built. Evaluation was conducted in the developer and the user environment. The evaluation in the user environment was done by distributing questionnaires covering three parameters namely the usefulness of the application, ease of use and user satisfaction. The results showed that the information systems built have a useful value (85.7%) and are easy to use (100%), therefore it satisfied the users.]]>
<![CDATA[Implementasi Principal Component Analysis (PCA) pada Pengenalan Wajah Resolusi Rendah ]]>
<![CDATA[Tanjung, Reza Phina]]>;
<![CDATA[Wahyu Utomo, Danang]]>
<![CDATA[ Infotekmesin Vol 15 No 1 (2024): Infotekmesin: Januari, 2024 ]]>
Publisher : <![CDATA[P3M Politeknik Negeri Cilacap ]]>
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DOI: 10.35970/infotekmesin.v15i1.2148
<![CDATA[Face recognition involves matching facial features by restricting the facial area. The problem found in the experiment was that the program recognized images outside the face area, especially for low-resolution images. The PCA algorithm and the proposed bounding box approach can identify the facial area and match it with training data. The experiment uses the Yaleface and Face94 datasets in various scenarios, including normal resolution and resolution reduction (75%, 50%, and 25% of the original size). On gif images, the proposed algorithm can produce similarities between the detected image and the input image in a resolution reduction of up to 50%. On jpg images, reducing resolution to 75% does not affect the performance of PCA. The proposed method can recognize faces with similarities in variations of pose and facial expression. The Euclidean value of the jpg image produces a better similarity value than the gif image.]]>
