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Pelatihan Penggunaan Copywriting bagi Komunitas Kubependa Rawalumbu Bekasi Nugroho, Fifto; Asruddin
Jurnal Pengabdian Masyarakat Gemilang (JPMG) Vol. 2 No. 3: Juli 2022
Publisher : HIMPUNAN DOSEN GEMILANG INDONESIA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58369/jpmg.v2i3.67

Abstract

Rumah singgah disabilitas mandiri (KUBEPENDA) produce a variety of household processed products such as masks, processed snacks that have been packaged properly. Currently, this community has started online marketing through the marketplace. Therefore, promotion is needed so that this KUBEPENDA business can be widely known. By conducting training on the use of copywritng on products, online or offline stores. The method used is offline counseling in the form of providing customized materials and training on the use of the Canva application to design product packaging. After the presentation of the material, as well as conducting training and evaluation, it can be seen that this counseling is going well. From the results of the evaluation carried out by freeing participants to copy the products they produced themselves, it can be seen that the success of the training reached 66% of the total participants, the rest produced enough copies
Implementing Preference Selection Index for Optimal Employee Ranking in Organizational Decision-Making Wijanarko, Rony; Nugroho, Fifto; Islam, Khoirul
Journal of Computer Networks, Architecture and High Performance Computing Vol. 6 No. 3 (2024): Articles Research Volume 6 Issue 3, July 2024
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v6i3.4387

Abstract

The rapid development of information technology has affected various aspects of life, including in the world of work. This research aims to apply the Preference Selection Index (PSI) method in determining the best employees at Bina Karya Utama Company. The assessment is based on four main criteria: Attendance, Tardiness, Overtime, and Length of Service. Data is obtained through observation and interviews, then processed using the PSI method which involves the normalization process and the calculation of preference values. The results showed that employees with alternative code A8 obtained the highest score, followed by A5 and A9. The PSI method proved to be effective in helping companies make objective and fair decisions, as well as motivating employees to improve their performance. This research concludes that a PSI-based decision support system can improve transparency and fairness in employee evaluation at Bina Karya Utama Company.
Optimizing Decision-Making for Aid Allocation in Underdeveloped Regions Using the MOORA Method Wijaya, Vera; Nugroho, Fifto; Kraugusteeliana, Kraugusteeliana
Journal of Computer Networks, Architecture and High Performance Computing Vol. 6 No. 3 (2024): Articles Research Volume 6 Issue 3, July 2024
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v6i3.4389

Abstract

The allocation of assistance for the Family Hope Program is a process that requires precision to ensure that assistance is given to those most in need. This research develops a Decision Support System (DSS)  using the Multi-Objective Optimization on the Basis of Ratio Analysis (MOORA) method for optimizing the selection of beneficiaries in disadvantaged villages which includes criteria used including education, toddlers, pregnant women, disabilities, elderly, income, employment, number of dependents, and house size. Each criterion is normalized and given a weight according to its level of importance. The results show that alternative A2 has the highest optimization value with Yi of 0.254, followed by A8 (0.208) and A5 (0.204). In contrast, alternatives A3 (0.029) and A10 (0.035) have the lowest optimization value. Matrix normalization and criteria weights show the significant influence of the criteria of education, pregnant women, elderly, income, number of dependents, and house size in the selection process. The implementation of DSS with the MOORA method is proven to increase efficiency and accuracy in the selection process of Family Hope Program beneficiaries, reduce subjective errors, and ensure assistance is channeled to those who really need it. Therefore, the MOORA method is recommended as an effective tool to optimize social assistance allocation, increase transparency, and reduce bias in decision-making.
PERANCANGAN ALAT PENGUKURAN SUHU DAN KADAR OKSIGEN DALAM TUBUH BERBASIS MIKROKONTROLER Nugroho, Fifto; Ulan Bani, Alexius; Esperito Epifanius Velazques, Emmanuel
JURSIMA Vol 10 No 2 (2022): Jursima Vol. 10 No. 2, Agustus Tahun 2022
Publisher : INSTITUT TEKNOLOGI DAN BISNIS INDOBARU NASIONAL

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47024/js.v10i2.429

Abstract

The development of modern technology makes it possible to make a more advanced tool. The health sector as one of the important components of life also does not escape the support of technology. One of the implementations is the design and manufacture of a system for measuring temperature and oxygen levels in the body. Measurements are made using the fingers to detect oxygen levels and the hands to detect the temperature without injuring the body. This measuring instrument uses the MAX30100 sensor, MLX90614, Arduino Uno, 16x2 LCD with I2C and Buzzer. This tool is able to measure temperature and oxygen levels with a buzzer as a sound indicator if conditions are not appropriate / abnormal
Application of Tsukamoto Fuzzy Logic in Expert System Application for Diagnosing Web-Based Skin Diseases KN, Nurwijayanti; Rasna, Rasna; Ismail, Rima Ruktiari; Sugiharto, Agus; Nugroho, Fifto
International Journal of Engineering, Science and Information Technology Vol 5, No 2 (2025)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v5i2.827

Abstract

Skin health is essential for everyone. In addition to supporting someone who can reduce self-confidence, skin diseases can also interfere with a person's concentration in activities. An expert system is a system designed to be able to imitate the expertise of an expert in answering questions and solving a problem. The expert system will solve a problem obtained from a dialogue with the user. With the help of an expert system, someone who is not an expert can answer questions, solve problems, and make decisions that an expert usually makes. This needs to be anticipated and handled seriously, especially for types of skin diseases, some of which can be fatal, and some can even be classified as cancer. Experts are needed to diagnose each disease in this case, but consultation with experts requires costly funds. For this reason, this system is designed to help people diagnose skin diseases online, making it easier for sufferers to diagnose the diseases they suffer from by themselves. The method used is the fuzzy Tsukamoto method. Analysis of the introduction of the disease is carried out by identifying various symptoms of the disease. The types of diseases diagnosed include tinea versicolor [P001], scabies [P002], ringworm [P003], dandruff [P004], vitiligo [P005], pityriasis alba [P006], hives [P007], erythema multiforme [P008], acne [P009], keloids [P010], melanoma [P011], eczema [P012], boils [P013], measles [P014], psoriasis [P015], impetigo [P016], and herpes [P017]. Skin disease sufferers can diagnose their disease without consulting with a specialist directly. This system can be used as a substitute for a specialist in producing a diagnosis in the form of the name of the disease suffered by the system user (user). This system provides a solution for users regarding more economical disease diagnosis.
Electre Method Decision Support System for Concrete Type Selection in Building Structures Prasiwiningrum, Elyandri; Rasna, Rasna; Heka Ardana, Putu Doddy; Nugroho, Fifto; Aini, Qurrotul
International Journal of Engineering, Science and Information Technology Vol 5, No 2 (2025)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v5i2.843

Abstract

Choosing the correct type of concrete in building construction is a crucial step that significantly affects the structure's quality, durability, and safety. Concrete, as the most widely used building material, has various types with different characteristics, such as compressive strength, tensile strength, modulus of elasticity, and durability. During this time, people who make concrete often ignore the strength of the concrete itself. They do not care what will happen if the manufacture of concrete is not by the recommended concrete construction. Concrete is the primary material for constructing a building such as a building. The quality of concrete is determined by its constituent materials, which include hydraulic cement, coarse aggregate, fine aggregate, water, and other additives. The concrete mix determines the strength of the concrete. If the building is built with unsuitable concrete, it will be quickly destroyed during natural disasters such as earthquakes. Based on this, the concrete type selection must be precise and accurate. Decision Support Systems are used in this research to provide additional input to decision-makers. Decision support systems can deliver maximum results by using algorithms or methods. The Electre method is one of the multicriteria decision-making methods based on ranking by pairwise comparisons of existing alternatives based on appropriate criteria. Overall, this research is expected to significantly improve the quality of decision-making in selecting concrete types, resulting in a safer, more durable, and more efficient building structure. The results obtained after inputting criteria values and alternative values are concrete types such as reinforced concrete, precast concrete, and lightweight concrete.
Using Artificial Neural Networks and the Kohonen Method, an Image Pattern Recognition System for Khat Art Types Rasna, Rasna; Lubis, Adyanata; Suryadi, Dikky; Bani, Alexius Ulan; Nugroho, Fifto
International Journal of Engineering, Science and Information Technology Vol 5, No 2 (2025)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v5i2.851

Abstract

Arabic letter writing is known as khat art. Khat is classified into many categories and can be identified into three types: Khat Naskhi, Khat Qufi, and Khat Farisi, per the rules established in the art of Khat. Arabic letters, the subjects of khat art, evolved following the region where it first appeared. As a result, the Qufi style, for instance, marked the start of the evolution of Khat in the tenth century. Previously somewhat rigid, Khat became more fluid and beautiful, although it remained angular. Subsequently, the art of Sulus, Naskhi, Raiham, Riqa, and Tauqi evolved and exhibited the form of Khat, cursive (italic)—artificial neural network-based khat art type recognition by selecting the Kohonen
Application Dictionary of Scientific Plants and Animals Android-Based Algorithm Using Jaro Winkler Distance Rasna, Rasna; Rosiana Dewi, Ni Wayan Emmy; Bani, Alexius Ulan; Lamsir, Seno; Nugroho, Fifto
International Journal of Engineering, Science and Information Technology Vol 5, No 2 (2025)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v5i2.839

Abstract

The dictionary is a kind of reference book composed of abjad and contains terms of terms and their meanings. Dictionaries are needed in education to figure out the word or term you want to know its meaning. In education, it is found in many terms, for example, in the biological sciences. In biology, there is the term a scientific term that must be known to every student, especially those who pursue the field of biology. The scientific term, or scientific name, is the Latin name of plants and animals and is one of the critical discussions in the biology field contained in the course curriculum of elementary school, junior high school, and senior high school lectures. The field of biology is the subject of the taxonomy of plants and animals, and each student is required to know the Latin of every plant and animal. This is because plants and animals in the world of biology are known to scientists with scientific language. In this research, the author applies the scientific language dictionary of plants and animals using an algorithm based on the android Jaro Winkler distance. Jaro Winkler's distance algorithm searches for the desired plants and animals. In this study, the plant names and scientific names are taken from existing books and journals. Each name consists of 1000 names of plants and animals, with each of the 500 names of plants and 500 animal names along with scientific language and the images, respectively. The system will generate output from the scientific names of plants and animals and be equipped with pictures and explanations. The results from this study use an algorithm called Jaro Winkler Distance to search for the names of the desired plants and animals by matching each character entered with the characters in the database.
Investigating the Impact of ReLU and Sigmoid Activation Functions on Animal Classification Using CNN Models M Mesran; Sitti Rachmawati Yahya; Fifto Nugroho; Agus Perdana Windarto
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 8 No 1 (2024): February 2024
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v8i1.5367

Abstract

VGG16 is a convolutional neural network model used for image recognition. It is unique in that it only has 16 weighted layers, rather than relying on a large number of hyperparameters. It is considered one of the best vision model architectures. However, several things need to be improved to increase the accuracy of image recognition. In this context, this work proposes and investigates two ensemble CNNs using transfer learning and compares them with state-of-the-art CNN architectures. This study compares the performance of (rectified linear unit) ReLU and sigmoid activation functions on CNN models for animal classification. To choose which model to use, we tested two state-of-the-art CNN architectures: the default VGG16 with the proposed method VGG16. A dataset consisting of 2,000 images of five different animals was used. The results show that ReLU achieves a higher classification accuracy than sigmoid. The model with ReLU in fully connected and convolutional layers achieved the highest precision of 97.56% in the test dataset. The research aims to find better activation functions and identify factors that influence model performance. The dataset consists of animal images collected from Kaggle, including cats, cows, elephants, horses, and sheep. It is divided into training sets and test sets (ratio 80:20). The CNN model has two convolution layers and two fully connected layers. ReLU and sigmoid activation functions with different learning rates are used. Evaluation metrics include accuracy, precision, recall, F1 score, and test cost. ReLU outperforms sigmoid in accuracy, precision, recall, and F1 score. This study emphasizes the importance of choosing the right activation function for better classification accuracy. ReLU is identified as effective in solving the vanish-gradient problem. These findings can guide future research to improve CNN models in animal classification.
Implementing Preference Selection Index for Optimal Employee Ranking in Organizational Decision-Making Wijanarko, Rony; Nugroho, Fifto; Islam, Khoirul
Journal of Computer Networks, Architecture and High Performance Computing Vol. 6 No. 3 (2024): Articles Research Volume 6 Issue 3, July 2024
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v6i3.4387

Abstract

The rapid development of information technology has affected various aspects of life, including in the world of work. This research aims to apply the Preference Selection Index (PSI) method in determining the best employees at Bina Karya Utama Company. The assessment is based on four main criteria: Attendance, Tardiness, Overtime, and Length of Service. Data is obtained through observation and interviews, then processed using the PSI method which involves the normalization process and the calculation of preference values. The results showed that employees with alternative code A8 obtained the highest score, followed by A5 and A9. The PSI method proved to be effective in helping companies make objective and fair decisions, as well as motivating employees to improve their performance. This research concludes that a PSI-based decision support system can improve transparency and fairness in employee evaluation at Bina Karya Utama Company.