Garuda - Garba Rujukan Digital

Pemetaan Toko Komputer Berbasis Web di Kabupaten Garut Fitriani, Leni; Agustin, Yoga Handoko; Fauzi, Bayu Muhammad
Jurnal Algoritma Vol 20 No 2 (2023): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.20-2.1304

A computer shop is a place that sells equipment related to computers. As technology advances, people's needs for computer shop locations are also increasing. Computer shops themselves not only sell various computer needs such as hard disks, Random Access Memory, and accessories such as mice and keyboards, some computer shops also sell products in the form of services such as computer servicing, computer assembly, installing software, and buying and selling used computers. Currently, information about computer shops only consists of explanations about the shop and mapping of computer shop location points, there is no information based on completeness categories in the form of product services, computer accessories, computer buying and selling. This means that the public or potential consumers do not know much about the location and search for computer shops in the city of Garut. Because the level of public need for the availability of goods and services will be very necessary, an application system is needed that can help increase store sales and the needs of the public as consumers. The aim of this research is the design and development of web-based computer shop mapping in Garut Regency. The methodology used to design this application is Rational Unified Process (RUP) with several stages of inception, elaboration, construction, and using Unified Modeling Language (UML) modeling. The results of this research are a geographic information system mapping computer shops to help make it easier for users or potential consumers to choose a complete computer shop and recommended computer shop.

Sistem Informasi Geografis Perumahan Menggunakan Metode Rational Unified Process Septiana, Yosep; Agustin, Yoga Handoko; Jungjunan, Aditya Rahma
Jurnal Algoritma Vol 21 No 1 (2024): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.21-1.1463

Geographic Information Systems (GIS) have become an increasingly important tool in the dissemination of housing information in this modern era. People need this information to make it easier to find housing that suits their needs and financial capabilities. The Housing and Settlements Service (DISPERKIM) is a government agency that regulates housing in an area. In collecting data on housing locations built at DISPERKIM, Garut Regency, Microsoft Excel is used, but to see housing location points, they are still separated by using Google Maps. Apart from that, the existing information system does not yet have a maps feature that contains geospatial data or points of distribution of housing locations to make it easier for people to find housing information based on the areas on the maps. The aim of this research study is to create a geographic information system. housing at Disperkim to make it easier to collect data on the location of housing being built and provide information to the public. The method used in this research uses Rational Unified Process (RUP) with the structure of Inception, Elaboration, Construction and Transition, through information system design using Unified Modeling Language (UML) which consists of use case diagrams, activity diagrams, sequence diagrams and class diagrams . The impact of this research resulted in a housing geographic information system which is managed by Disperkim and housing agents as admins and can be accessed by the public as users. The sources used in this information system are housing data from Disperkim and the Sikumbang PUPR website. The hope is that with the presence of this information system, people can more easily and efficiently find information about available housing locations.

Pengembangan Sistem Pakar Diagnosa Kerusakan Motor Injeksi Matic Menggunakan Forward Chaining dan Expert System Development Nugraha, Insan Satia; Agustin, Yoga Handoko; Rahayu, Raden Erwin Gunadi
Jurnal Algoritma Vol 21 No 1 (2024): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.21-1.1493

Technological progress at this time is extremely rapid in the field of transportation, one of which is automatic injection motorbikes, for automatic injection motorbikes there are definitely obstacles or problems in reducing the performance of ordinary motorbikes. In this case, many automatic injection motorbikes go to the Ahass Fahya Jaya Motor workshop, in This problem should be done with simple checks, such as checking the spark plug, checking the battery and etc. In checking small things, the author has created a professional system application by providing the knowledge of experienced experts and has received a certificate from Ahass, anticipating that this application may be useful for readers or users of the application. In making this expert system application there are several features, one of which can be accessed by the admin with a certain code, later the user will enter the full name, email and motorbike series, the administrator can change the symptoms of damage, change the solution and also add application knowledge. Based on these problems, we obtained a knowledge base of 20 damage data and 23 symptoms obtained from visits to Ahass Fahri Jaya Motor. Selecting the forward chaining method can efficiently produce solutions by combining existing knowledge rules and known facts. Meanwhile, choosing the Expert System Development Life Cycle methodology for expert systems can be carried out in a more structured, efficient and effective manner. This methodology helps in producing high quality, accurate and reliable expert systems in supporting decision making in a particular domain. Based on user testing or at the usability testing stage, it has an accuracy value of 95% from the 26 automatic injection motor damage diagnosis test data carried out.

Pengembangan Aplikasi Diagnosa Penyakit Mata dengan Algoritma Teorema Bayes Agustin, Yoga Handoko; Asgara, Zidan; Baswardono, Wiyoga
Jurnal Algoritma Vol 21 No 1 (2024): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.21-1.1564

The eye is one of the senses that has great importance, because it functions in connection with the surrounding environment. If there are eye problems that are ignored, it will be an early sign of a potentially dangerous eye disorder. As the quality of life decreases and the level of stress received, complaints related to eye disease also increase. Human knowledge and skills are not eternal, they can be lost due to various reasons such as death, retirement, or job changes. When making conclusions, experts may be influenced by certain factors that have the potential to influence the final outcome of that conclusion. So that society can prevent and treat eye diseases, an expert system application is needed to assist eye polyclinic officers and the public in diagnosing eye diseases using the Bayes Theorem inference method. Bayes' theorem is a mathematical equation used to estimate the possibility of future events or their probabilities. This probability refers to the chance of an outcome occurring based on previous information. Its function is to update existing predictions or hypotheses. The results of this research are conclusions about the type of eye disease suffered based on the symptoms chosen by the patient and have been calculated using Bayes calculations. Based on testing 50 patient sample data, the percentage of conformity between the system and experts was 86% of the test data.

Sistem Informasi Geografis Perumahan Menggunakan Metode Rational Unified Process Septiana, Yosep; Agustin, Yoga Handoko; Jungjunan, Aditya Rahma
Jurnal Algoritma Vol 21 No 1 (2024): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.21-1.1463

Geographic Information Systems (GIS) have become an increasingly important tool in the dissemination of housing information in this modern era. People need this information to make it easier to find housing that suits their needs and financial capabilities. The Housing and Settlements Service (DISPERKIM) is a government agency that regulates housing in an area. In collecting data on housing locations built at DISPERKIM, Garut Regency, Microsoft Excel is used, but to see housing location points, they are still separated by using Google Maps. Apart from that, the existing information system does not yet have a maps feature that contains geospatial data or points of distribution of housing locations to make it easier for people to find housing information based on the areas on the maps. The aim of this research study is to create a geographic information system. housing at Disperkim to make it easier to collect data on the location of housing being built and provide information to the public. The method used in this research uses Rational Unified Process (RUP) with the structure of Inception, Elaboration, Construction and Transition, through information system design using Unified Modeling Language (UML) which consists of use case diagrams, activity diagrams, sequence diagrams and class diagrams . The impact of this research resulted in a housing geographic information system which is managed by Disperkim and housing agents as admins and can be accessed by the public as users. The sources used in this information system are housing data from Disperkim and the Sikumbang PUPR website. The hope is that with the presence of this information system, people can more easily and efficiently find information about available housing locations.

Pengembangan Sistem Pakar Diagnosa Kerusakan Motor Injeksi Matic Menggunakan Forward Chaining dan Expert System Development Nugraha, Insan Satia; Agustin, Yoga Handoko; Rahayu, Raden Erwin Gunadi
Jurnal Algoritma Vol 21 No 1 (2024): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.21-1.1493

Technological progress at this time is extremely rapid in the field of transportation, one of which is automatic injection motorbikes, for automatic injection motorbikes there are definitely obstacles or problems in reducing the performance of ordinary motorbikes. In this case, many automatic injection motorbikes go to the Ahass Fahya Jaya Motor workshop, in This problem should be done with simple checks, such as checking the spark plug, checking the battery and etc. In checking small things, the author has created a professional system application by providing the knowledge of experienced experts and has received a certificate from Ahass, anticipating that this application may be useful for readers or users of the application. In making this expert system application there are several features, one of which can be accessed by the admin with a certain code, later the user will enter the full name, email and motorbike series, the administrator can change the symptoms of damage, change the solution and also add application knowledge. Based on these problems, we obtained a knowledge base of 20 damage data and 23 symptoms obtained from visits to Ahass Fahri Jaya Motor. Selecting the forward chaining method can efficiently produce solutions by combining existing knowledge rules and known facts. Meanwhile, choosing the Expert System Development Life Cycle methodology for expert systems can be carried out in a more structured, efficient and effective manner. This methodology helps in producing high quality, accurate and reliable expert systems in supporting decision making in a particular domain. Based on user testing or at the usability testing stage, it has an accuracy value of 95% from the 26 automatic injection motor damage diagnosis test data carried out.

Pengembangan Aplikasi Diagnosa Penyakit Mata dengan Algoritma Teorema Bayes Agustin, Yoga Handoko; Asgara, Zidan; Baswardono, Wiyoga
Jurnal Algoritma Vol 21 No 1 (2024): Jurnal Algoritma
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/algoritma/v.21-1.1564

The eye is one of the senses that has great importance, because it functions in connection with the surrounding environment. If there are eye problems that are ignored, it will be an early sign of a potentially dangerous eye disorder. As the quality of life decreases and the level of stress received, complaints related to eye disease also increase. Human knowledge and skills are not eternal, they can be lost due to various reasons such as death, retirement, or job changes. When making conclusions, experts may be influenced by certain factors that have the potential to influence the final outcome of that conclusion. So that society can prevent and treat eye diseases, an expert system application is needed to assist eye polyclinic officers and the public in diagnosing eye diseases using the Bayes Theorem inference method. Bayes' theorem is a mathematical equation used to estimate the possibility of future events or their probabilities. This probability refers to the chance of an outcome occurring based on previous information. Its function is to update existing predictions or hypotheses. The results of this research are conclusions about the type of eye disease suffered based on the symptoms chosen by the patient and have been calculated using Bayes calculations. Based on testing 50 patient sample data, the percentage of conformity between the system and experts was 86% of the test data.

IMPLEMENTATION OF MULTIPLE LINEAR REGRESSION ALGORITHM IN PREDICTING RED CHILI PRICES IN GARUT REGENCY Yoga Handoko Agustin; Fitri Nuraeni; Rika Lestari
JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer) Vol. 10 No. 2 (2024): JITK Issue November 2024
Publisher : LPPM Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/jitk.v10i2.5882

Vegetables, including red chili peppers, play an important role in food and economic balance. Significant price fluctuations and inflation are often problems for farmers and traders. Garut Regency, as the center of red chili production in West Java, faces similar challenges. This research aims to implement a Multiple Linear Regression algorithm to predict the price of red chili peppers in the Garut Regency, highlighting the novelty of using a combination of One Hot Encoding, Feature Engineering, Standard Scaler, and Hyperparameter Tuning techniques. The method used is CRISP-DM with 6 stages: Business Understanding, Data Understanding, Data Preparation, Modeling, Evaluation, and Deployment. The data used is the price and production of red chili peppers per week in 2018-2023, with a total of 702 records. This research involved 8 trials with data transformation and normalization scenarios. The model evaluation used MSE, RMSE, MAPE, R-squared, and statistical hypothesis testing metrics. Results showed 5 significantly influential attributes: year, month, production, net harvested area, and productivity. The best model yielded MSE 202,134,650, RMSE 14,217, MAPE 29.16%, and R-squared 0.320. This approach is simpler yet effective and is able to provide fairly accurate predictions. This research is expected to contribute to providing predictive models that help farmers and traders anticipate price fluctuations, as well as provide insights for policymakers in price management.

Implementation of Naïve Bayes Algorithm to Predict Food Crop Production Results in Garut Regency Oktapiani, Vini; Agustin, Yoga Handoko
Jurnal Sistem Cerdas Vol. 7 No. 3 (2024)
Publisher : APIC

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37396/jsc.v7i3.455

The ups and downs of food crop production each year are caused by changes in the area of land planted each year. These changes are influenced by several factors, including crop rotation, government policies, changes in agricultural practices, environmental factors such as climate, and economic pressures. In an effort to improve the efficiency and productivity of food crop production in Garut Regency, the use of technology and data analysis methods is becoming increasingly important. This research aims to predict food crop production in Garut Regency with Naïve Bayes algorithm and evaluate influential factors. This modeling is analyzed using Feature Forward selection and SMOTE techniques to determine the most influential attributes and overcome class imbalance. The method used is Cross-Industry Standard Process For Data Mining (CRISP-DM). Where the use of SMOTE successfully handles unbalanced classes, and the application of Feature selection results in the 5 most influential factors, namely crop type, added planting, realized harvest area, realized production and production. The results showed that the Naive Bayes model with Cross validation and Xgboost resulted in an Accuracy value of 82.54%, Recall value of 81.67%, Precision value of 83.34%. And the AUC value is 0.904% with the Good Classification category.

Sentiment Analysis Using Grok AI as an Auto-Labeling Tool in The Text Processing Stage Agustin, Yoga Handoko; Kurniadi, Dede; Julianto, Indri Tri; B. Balilo Jr , Benedicto
Sinkron : jurnal dan penelitian teknik informatika Vol. 9 No. 2 (2025): Research Articles April 2025
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v9i2.14632

A critical aspect of Natural Language Processing (NLP) is text processing, where text labeling represents the most significant challenge due to its resource-intensive nature when conducted manually. At this stage, automatic labeling emerges as a more practical solution, particularly with the advent of Artificial Intelligence (AI), which offers tools to address this obstacle. Grok AI, equipped with a new feature operable on Platform X, provides a promising approach. This study aims to leverage the Grok AI feature on Platform X for automatic text labeling. The research methodology involves labeling text data obtained from a public dataset. To assess the quality of the labeling results, an evaluation method employing Naive Bayes classification modeling is applied. The findings reveal that Grok AI's performance closely approximates that of human labeling. The highest accuracy achieved by Grok AI is 51.71% using the k-Nearest Neighbors (k-NN) algorithm, approaching the human labeling accuracy of 60.52% with k-NN. Furthermore, Grok AI surpasses the performance of VADER labeling, which achieves an accuracy of only 49.49% with Naive Bayes. Consequently, the Grok AI feature on Platform X presents a viable alternative for the automatic labeling of text data.

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