Claim Missing Document
Check
Articles

Found 29 Documents
Search

Simulasi Monte Carlo dalam Memprediksi Penerimaan Peserta Pelatihan Dasar CPNS Faisal Roza; Sarjon Defit; Gunadi Widi Nurcahyo
Jurnal Informasi dan Teknologi 2021, Vol. 3, No. 3
Publisher : Rektorat Universitas Putra Indonesia YPTK Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/jidt.v3i3.140

Abstract

The implementation of basic training recruit (latsar) of civil servant (CPNS) at Pusat Pengembangan Sumber Daya Manusia (PPSDM) Ministry of Internal Affairs regional Bukittinggi. The leader takes decision in doing the implementation of latsar CPNS recruit in PPSDM scope regional Bukittinggi. Latsar CPNS is one of requirements to be civil servant. Therefore, it is necessary to collect data by doing observation, interview questionings with related party in the implementation of latsar CPNS recruit from 2018 to 2020. It can be predicted for the next recruit. After doing library references by reading some books and journals, the basic training recruit of CPNS sources from PPSDM regional Bukittinggi, and Monte Carlo simulation. By using Monte Carlo simulation in predicting data, it can get closer value of actual value. Based on distribution of sampling data, the method is by choosing random numbers from probability distribution to do simulation. The Monte Carlo result’s examination has got 173 participants for year 2019, 158 participants for year 2020, and 157 participants for year 2021 clearly. Although the rate of the accurate just reaches 81%, but it has been able to be recommended to help PPSDM regional Bukittinggi, Ministry of Internal Affairs in taking decision and planning for basic training recruit of CPNS for the next.
Akurasi dalam Mengidentifikasi Citra Anggrek Menggunakan Backpropagation Artificial Neural Network Ardia Ovidius; Gunadi Widi Nurcahyo; Sumijan; Roni Salambue
Jurnal Informasi dan Teknologi 2021, Vol. 3, No. 3
Publisher : Rektorat Universitas Putra Indonesia YPTK Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/jidt.v3i3.115

Abstract

Orchids are ornamental flower plants in the Family Orchidaceae whose habitat is spread over almost all continents in the world, except Antarctica. There are so many orchid enthusiasts in Indonesia and this fact made orchids a promising commodity for ornamental plant cultivator. With a variety of orchid species that reach more than 25,000 species, the identification of orchid species becomes a little complicated for orchid lovers. The purpose of this study was to determine the accuracy level of orchid species identification through image recognition so that it can be used as a reference in determining the feasibility of this method. This study used 120 images of orchids in 6 species. The image of the orchid was obtained by shooting at several locations using the camera. The photo is then processed using image processing software by cropping and resizing to speed up computing time during network training. Furthermore, MatLab software is used to perform the feature extraction process in the form of color feature data and moment invariants. Data from feature extraction is used as input for training artificial neural networks using the Back Propagation method. Calculation of the level of accuracy done by testing the network using the test data that has been provided. The trial results show that 26 of 30 were successfully recognized so that the accuracy rate can be calculated, namely 86.7%. An accuracy rate of 86.7% can be considered feasible and can be used as a basis for consideration of using this tested method as the right method for identifying orchids through images.
Machine Learning Rekomendasi Produk dalam Penjualan Menggunakan Metode Item-Based Collaborative Filtering Daniel Theodorus; Sarjon Defit; Gunadi Widi Nurcahyo
Jurnal Informasi dan Teknologi 2021, Vol. 3, No. 4
Publisher : Rektorat Universitas Putra Indonesia YPTK Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/jidt.v3i4.151

Abstract

The shift towards Industry 4.0 has pushed many companies to adopt a digital system. With the sheer amount of data available today, companies start to face difficulties with providing product recommendation to their customers. As a result, data analysis has become increasingly important in the pursuit of providing the best service (user experience) to customers. The location appointed in this research is PT. Sentral Tukang Indonesia which is engaged in the sale of building materials and carpentry tools such as: paint, plywood, aluminum, ceramics, and hpl. Machine Learning has emerged as a possible solution in the field of data analysis. The recommendation system emerged as a solution in providing product recommendation based on interactions between customers in historical sales data. The purpose of this study is to assist companies in providing product recommendation to increase sales, to make it easier for customers to find the products they need, providing the best service (user experience) to customers. The data used is customer, item, and historical sales at PT. Sentral Tukang Indonesia over a time span of 1 period.data historical sales divide to dataset training 80% and dataset testing 20%. The Item-based Collaborative Filtering method used in this study uses Cosine Similarity algorithm to calculate the level of similarity between products. Score prediction uses Weighted Sum formula while computation of error rate uses the Root Mean Squared Error formula. The result of this study shows top 10 product recommendations per customer. The products displayed are products with the highest score from the individual customer. This research can be used as a reference by companies looking to provide product recommendations needed by their customers.
Prediksi Tingkat Prevalensi Stunting Kabupaten Lima Puluh Kota Menggunakan Metode Monte Carlo Mike Zaimy; Sarjon Defit; Gunadi Widi Nurcahyo
Jurnal Informasi dan Teknologi 2021, Vol. 3, No. 4
Publisher : Rektorat Universitas Putra Indonesia YPTK Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/jidt.v3i4.165

Abstract

Stunting is a condition of failure to thrive in children under five years old (infants under five years old) due to chronic malnutrition so that children are too short for their age. According to available data, the stunting prevalence rate in Lima Puluh Kota Regency in 2020 is quite high, at 8.28%. This has become the attention of the central government by establishing Lima Puluh Kota Regency as one of the Regencies/Cities Locations for the National Integrated Stunting Reduction Intervention Focus. The results of this study aim to assist the District Government of Lima Puluh Kota in planning the convergence of programs/interventions as an effort to accelerate stunting prevention and reduce the percentage of stunting under five in Lima Puluh Kota Regency. This research data uses the stunting prevalence rate from 2018 to 2020 which comes from data on the number of toddlers and the number of stunting toddlers from 22 health centers in Lima Puluh Kota Regency. Furthermore, the data was processed using the Monte Carlo method to predict the stunting prevalence rate in 2021. Based on the tests conducted using the Monte Carlo method, the highest stunting prediction rates were found at the Pakan Rabaa Public Health Center and the Suliki Public Health Center with a stunting prevalence rate of 11.70%. The level of accuracy obtained is 93.73%. The Monte Carlo method is suitable for predicting the prevalence of stunting in Lima Puluh Kota Regency, seen from the high level of accuracy from the results of data processing.
Sistem Pakar Dalam Menganalisa Penyakit Perut Dengan Menggunakan Metode Certainty Factor Annisa Amalia; Gunadi Widi Nurcahyo; Y Yuhandri
Jurnal Informasi dan Teknologi 2021, Vol. 3, No. 4
Publisher : Rektorat Universitas Putra Indonesia YPTK Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/jidt.v3i4.159

Abstract

Food technology that is increasingly advanced makes people tend to consume fast food, as well as foods that contain chemicals. This causes the tendency of an unhealthy lifestyle and becomes one of the factors that cause stomach disease. Stomach disease can be experienced at the age of children to adulthood. Unhealthy lifestyle means eating patterns that are initially consumptive on healthy foods and then turn into consumptive foods that are less healthy. Not only food, rarely exercise is also likely to cause pain in the stomach. Diagnosing stomach disease is still carried out by conducting face-to-face consultations with health workers, which can take a long time and cost a lot of money. Lack of information on stomach disease sufferers about the symptoms of stomach disease, causes patients not to know the type of stomach disease they are experiencing. This is the goal of research that will build an expert system software that is expected to be able to analyze stomach diseases and help the community, stomach sufferers and health workers in diagnosing types of stomach diseases. The method used in this study is Certainty Factor (CF) or the certainty value of a disease. Expert system software development is done by analyzing software requirements, system user needs. The dataset of this study is the symptoms and types of stomach diseases that occur at the Salido Health Center. The result of the system built is the result of the diagnosis of stomach disease with the percentage of certainty value from the calculation using Certainty Factor. The system will also provide information about the description, causes and prevention of the types of stomach diseases diagnosed. With the construction of an expert system of stomach diseases, it is hoped that this research can be a reference for users in diagnosing stomach diseases. The accuracy results obtained after testing the system is 80%.
Sistem Pakar Menggunakan Metode Certainty Factor untuk Mengidentifikasi Penyakit pada Hewan Peliharaan Fortia Magfira; Gunadi Widi Nurcahyo
Jurnal Informasi dan Teknologi 2020, Vol. 2, No. 3
Publisher : Rektorat Universitas Putra Indonesia YPTK Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/jidt.v2i3.68

Abstract

Large domesticated types of ruminants such as goats, buffalo and cows are animals that are commonly kept and used as food sources and as assistants to human work in rural areas. Knowledge about pets, especially animal health, is something owners really need to keep their pets healthy. The owner's lack of knowledge about diseases and early handling of diseases in pets and the difficulty of seeing a veterinarian in urgent situations prevent pets from getting proper first aid. This study aims to identify the types of diseases suffered by pets based on the symptoms experienced by pets precisely. The method used is themethod Certainty Factor to accommodate the uncertainty of an expert's thinking on 12 diseases and 47 disease symptoms in pets. The results of this study can identify diseases in pets and produce certainty values ​​for the types of diseases in the form of diseases suffered by pets. So that this research can be a reference in identifying diseases in pets and providing knowledge to owners about first aid and disease management in pets.
Sistem Pakar Metode Forward Chaining Untuk Psikoterapi Kejiwaan Terhadap Penyakit Kepribadian Genetik Wahyudi Wahid; Gunadi Widi Nurcahyo; Sumijan Sumijan
Jurnal Informasi dan Teknologi 2020, Vol. 2, No. 4
Publisher : Rektorat Universitas Putra Indonesia YPTK Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/jidt.v2i4.72

Abstract

The problem with personality disease is that the disorder experienced cannot be easily identified because it tends to be ignored. Most people who experience symptoms of the disorder are still reluctant to see a doctor or a psychiatrist. This is due to several limitations such as limited places for consultation or psychiatrists. With these limitations the role of the Expert System is very important in solving a problem, the problem is a personality disease. The purpose of building this Expert System is to help people who suffer from personality problems consult online without having to come directly to a psychiatrist. This expert system will later become a solution to these genetic personality problems. So that people are no longer difficult to see a doctor or psychiatrist. All data to be used are sourced from experts. Forward Chaining is used in this research as a method. The search technique that begins with the facts obtained, then adjusts the rule model that has been built is called Forward Chaining. Observations will result in a website-based Expert System product that users can access online. The accuracy of the system has been tested by related parties and results in a faster and more efficient information. The conclusion of this research is to help people to diagnose the symptoms of personality disorder that they experience unconsciously and the test results can clearly detect genetic personality disease.
Sistem Pakar pada Sistem Pembayaran Uang Kuliah Cicilan Menggunakan Metode Weighted Product (Studi Kasus Universitas Dharma Andalas) Rahmad Supriadi; Gunadi Widi Nurcahyo
Jurnal Informasi dan Teknologi 2021, Vol. 3, No. 1
Publisher : Rektorat Universitas Putra Indonesia YPTK Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/jidt.v3i1.89

Abstract

Dharma Andalas University is a change in form from the Dharma Andalas Higher School of Economics (STIE). Dharma Andalas University is one of the private universities in the city of Padang which is under the auspices of the Andalas Dharma Education Foundation (YPDA) which is directly fostered by the Andalas University alumni association. Dharma Andalas University is a private university so operational costs come from student tuition fees. Payment of tuition fees is an obligation of every student, considering that tuition fees are quite expensive, Dharma Andalas University provides relief for students to make tuition payments in installments. The purpose of this study is to assist the leadership in making a decision to pay installments using the Weighted Product method. In this study, the data processed is the data of students who apply for installment tuition payments at Dharma Andalas University. The data processing is to determine the criteria for each alternative by multiplying for attribute match reting, then rank with the attribute weight value which results in the vector value V, then the vector value V is ranked from the highest value to the lowest value where the highest value will be prioritized. Furthermore compared to the manual calculation method with a system that has been made, the results are the same with an accuracy rate of 97%, so that it can be recommended to the leadership to help make decisions about the payment of tuition installments.
Sistem Pakar dalam Mengidentifikasi Tingkat Keparahan Penyakit pada Tanaman Kelapa Sawit Menggunakan Framework Codeigniter Yunita Cahaya Khairani; Gunadi Widi Nurcahyo
Jurnal Informasi dan Teknologi 2021, Vol. 3, No. 1
Publisher : Rektorat Universitas Putra Indonesia YPTK Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/jidt.v3i1.113

Abstract

Palm oil is an industrial plant that produces oil (both cooking oil and fuel), soap and wax. One of the factors that can reduce the growth and productivity of oil palm is the presence of disease in the oil palm plant. In helping to identify and provide information about oil palm diseases, an Expert System was created to identify diseases in oil palm plants and their handling. The data that is processed in this research is knowledge about disease symptoms in oil palm plants which comes from an expert. The symptom data is processed using an expert system that has been designed and developed using the PHP Framework Codeigniter programming language and MySQL as the database. This system was successfully developed to identify the severity of the disease in oil palm plants and produce 100% accuracy. This system has been able to provide information to farmers about oil palm plant diseases and solutions to overcome them. This research is very suitable to be applied in identifying diseases in oil palm plants, so this research is suitable for use by oil palm farmers.
Akurasi Pemberian Insentif Menggunakan Algoritma K-Medoids Terhadap Tingkat Kedisiplinan Pegawai Wendi Robiansyah; Gunadi Widi Nurcahyo
Jurnal Informasi dan Teknologi 2021, Vol. 3, No. 3
Publisher : Rektorat Universitas Putra Indonesia YPTK Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/jidt.v3i3.125

Abstract

Assessment of a discipline is a performance evaluation stage that is important for the continuity of company activities. Monitoring and assessment of an employee's discipline must be carried out continuously in order to improve the quality of human resources. This research was conducted to make the accuracy of providing incentives based on the level of employee discipline. The data processed in this study is a recapitulation of the attendance of AMIK and STIKOM Tunas Bangsa Pematangsiantar employees as many as 25 employees as a sample. For grouping the employee data using the K-Medoids Algorithm. K-Medoids groups a set of n objects into a number of k clusters using the partition clustering method. Furthermore, the employee data is processed using Rapid Miner software. Research using this method obtained results in the form of grouping employees into 3 groups that have good discipline levels of 12 employees, sufficient discipline levels of 8 employees, and less disciplinary levels of 5 employees. Based on the grouping results that have been produced, it can be a consideration for the leadership to determine the amount of incentives for employees.