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All Journal Paradigma
Ridwansyah Ridwansyah
Universitas Nusa Mandiri
Computer Science & IT

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KLASIFIKASI ANAK BERKEBUTUHAN KHUSUS TUNAGRAHITA MENGGUNAKAN METODE ALGORITMA C4.5 I Made Dananjaya Priyatama; Ridwansyah Ridwansyah
Paradigma Vol. 24 No. 1 (2022): Periode Maret 2022
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (307.573 KB) | DOI: 10.31294/paradigma.v24i1.1087

Abstract

Children with mental retardation are children who have differences from other children that can be seen significantly with our naked eyes, because they are children with special needs both mentally, physically and can be seen from their psychology. Intellectuals of mentally retarded children are socially slower to do everything in achieving the goals they want optimally. Children with mental retardation usually have disorders such as speech disorders or physical and mental disabilities, as well as uncontrollable emotions. The problems that exist with teachers of children with special needs are because many teachers do not know the characteristics of mentally retarded children and how to handle them through IQ levels and several other factors. In solving problems for children with special needs, these children need to be classified due to their differences from one person to another in developmental delays and physical conditions they experience, so it is necessary to distinguish educational or teaching strategies that are designed and programmed for them. With the C4.5 algorithm method, which can classify children with special needs based on existing characteristics with data that is tested with a model that is used cross validation and evaluated with a confusion matrix. Based on the results of testing with this method, the accuracy obtained is very high so that it can be used by teaching staff from the accurate information.
Grouping Data in Predicting Infant Mortality Using K-Means and Decision Tree Ridwansyah Ridwansyah; Verry Riyanto; Abdul Hamid; Sri Rahayu; Jajang Jaya Purnama
Paradigma Vol. 24 No. 2 (2022): September 2022 Period
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (391.355 KB) | DOI: 10.31294/paradigma.v24i2.1399

Abstract

Death is something that we cannot avoid where, when and how death comes. The high infant mortality rate is the main thing and the Indonesian government must prioritize, one of the government's efforts to reduce infant mortality is by conducting a surveillance program, namely PWS KIA where the program is uniting the health of mothers and babies in the local area, basically there are several infant deaths that have causes from the time of pregnancy, accidents, disasters, diseases or because it is destiny from God, for that research is carried out in classifying infant mortality data. For grouping infant mortality data, a K-Means method is needed to analyze data by carrying out a data modeling process without supervision or also known as unsupervised learning. In showing the centroid in the early stages of the k-means algorithm, it is very influential on the results of the cluster carried out on the infant mortality dataset. taken from data.go.id with different centroid results. The results of the clustering model pattern that can be trusted by the government or the Health department to prevent infant mortality. From the clustering results, four labels are tested again using the decision tree algorithm.
Optimization of the YOLOv7 Object Detection Algorithm for Estimating the Amount of Apple Harvest Verry Riyanto; Imam Nawawi; Ridwansyah Ridwansyah; Ganda Wijaya; Toto Haryanto
Paradigma Vol. 25 No. 1 (2023): March 2023 Period
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/p.v25i1.1809

Abstract

The increasing population consumed in high production and food needs for survival. Apples are one of the crop harvest products in Indonesia whose needs are increasing, because they are not only needed for human vitamins but can be used as hand fruit or a form of gratitude to those who receive the fruit. In the process of harvesting apples in agricultural land, harvesting is often found which is not feasible in the hands of consumers because it takes too long for apples to not be harvested when the condition of the fruit is feasible in maturity. Therefore, the authors approach this problem by processing the image results obtained to form a detection model, whether the apples are said to be feasible to be harvested immediately and from the image results it can also be calculated the number of fruits captured by the image model , feature enhancements Estimates on objects from this image model are expected to provide more timely harvest predictions in order to provide longer aging of apples and good fruit quality after reaching consumers
The Method User Experience Questionnaire Analysis of Identitas Kependudukan Digital Application Galang Fachrul Farlian; Ridwansyah Ridwansyah
Paradigma Vol. 25 No. 2 (2023): September 2023 Period
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/p.v25i2.2353

Abstract

User Experience (UX) becomes important to explore and fulfill the needs for developing user-focused applications or products. The problems that exist to measure the level of user experience in the Digital Resident Identity (IKD) application and complaints submitted by users tend to lead to system and service quality problems in the IKD application. Then research purposes are assessed to evaluate the extent to which users can utilize and interact with the application. The method used by researchers is the User Experience Questionnaire (UEQ). UEQ is a widely used scoring methodology used to quantitatively measure user experience by administering a questionnaire to individuals that measures their subjective experiences and perceptions. Variables in UEQ, namely: efficiency, perspicuity, dependability, novelty, stimulation, and interestingness. The evaluation results of user experience in IKD applications using UEQ showed that there were 5 variables that received positive evaluation results, including attractiveness variables (mean 2.14), clarity variables (perspicuity) (mean 1.725), efficiency variables (efficiency) ( mean 1.725), accuracy variable (mean 1.525), and stimulation variable (mean 1.475). Whereas the novelty variable (mean 0.602) gets neutral evaluation results. From these results it can be used by IKD application developers to improve the user experience (user experience) of IKD applications on novelty variables by improving the appearance of applications that are more creative, inventive, and also cutting edge. The developer can pay attention to the recommendations that have been presented in this study. Parties who wish to conduct further research can use other evaluation methods such as Heuristic Evaluation.
Co-Authors Abdul Hamid Galang Fachrul Farlian Ganda Wijaya I Made Dananjaya Priyatama Imam Nawawi Jajang Jaya Purnama Sri Rahayu Toto Haryanto Verry Riyanto