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Optimization of Medical Device Inventory Planning with the Apriori Method at Malahayati Pharmacy Medan Rahmadsyah, Andi; Batubara, Rini Oktari
CSRID (Computer Science Research and Its Development Journal) Vol. 17 No. 1 (2025): Februari 2025
Publisher : LPPM Universitas Potensi Utama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22303/csrid-.17.1.2025.93-105

Malahayati Islamic Hospital (RSIM) is a General Hospital engaged in the field of medical or health services for the community, with the aim of assisting the government in serving the community in the field of health and improving the quality of public health, both physical, spiritual and social health. In this hospital there is a pharmacy that helps patients and other medical personnel to obtain medicines and medical devices needed in its management, often the availability of medical devices in the warehouse is very minimal and errors often occur in data collection. In planning the supply of medical devices, the pharmacy finds it difficult to find out information about which types of medical devices are most in demand so that in the future they will increase stock in the warehouse. This can make customers dissatisfied in receiving services, errors in data management that still uses manual methods and is not yet systematic. To overcome this, a system is needed that can be used to find out forecasting using the Apriori Method. In the design and manufacture of this system, the Visual Basic (VB) 2010 application and data storage using the SQL Server 2008 database are used. With this system, it can help the pharmacy to find out information on the supply of medical devices that will come to the Malahayati pharmacy.

Sistem Pakar Diagnosa Penyakit DBD Pasien Puskesmas Tanjung Sarang Elang Menggunakan Metode Certainty Factor Ainun, Annisa; Samsir, Samsir; Subagio, Selamat
CSRID (Computer Science Research and Its Development Journal) Vol. 17 No. 1 (2025): Februari 2025
Publisher : LPPM Universitas Potensi Utama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22303/csrid-.17.1.2025.118-126

Health is valuable for humans, because anyone can experience health problems. Children are very susceptible to germs and lack of sensitivity to symptoms of a disease is a fear for parents. Parents are lay people who do not understand health. If a child has a health problem, they prefer to trust it to experts or specialist doctors who already know more about health, regardless of whether the problem is still at a low or chronic level. With the convenience of having experts or specialist doctors, sometimes there are also disadvantages such as limited working hours (practice) and many patients so they have to wait in line. In the rainy season, almost no area in Indonesia is free from dengue fever attacks. Research shows that dengue fever has been found in all provinces of Indonesia. Two hundred cities reported an Extraordinary Event (KLB). The incidence rate increased from 0.005 per 100,000 people in 1968 and drastically jumped to 627 per 100,000 people. An Expert System is a computer system designed to imitate the problem-solving abilities of an expert in a particular field using the knowledge and analysis methods that have been defined by the expert. The results obtained in using this system are the information system for DHF patients at the Tanjung Sarang Elang Health Center can be completed easily without requiring a lot of energy and time, does not require many files if more than one DHF disease data is needed and the data produced is free from errors. Thus it is expected to be very helpful in diagnosing DHF patients at the Tanjung Sarang Elang Health Center. Macromedia Dreamweaver is an HTML editor for designing, writing code (php) and as a program for processing and building websites, web pages and other web applications.

Sistem Pakar Deteksi Penyakit Culvularia Dengan Metode Forward Chaining Panjaitan, Indra Syahputra; Subagio, Selamat; Samsir, Samsir
CSRID (Computer Science Research and Its Development Journal) Vol. 17 No. 1 (2025): Februari 2025
Publisher : LPPM Universitas Potensi Utama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22303/csrid-.17.1.2025.106-117

Oil palm diseases generally attack leaves during the seedling phase and can cause major losses if not handled properly. Symptoms that appear include yellow spots that then develop into necrosis, inhibiting seedling growth, and increasing the death rate of plants that during the entire life cycle of plants, from seeds, nurseries, planting, to storage of harvests, plants are never free from disturbances that can inhibit their growth and development. These disturbances can be in the form of pest attacks, infections of disease-causing pathogens, competition with weeds, or unfavorable environmental factors. A researcher from India estimated that crop yield losses were caused by weeds of around 33%, disease-causing pathogens of around 26%, pest attacks of around 7%, rats of around 6%, and damage during storage of around 7%. In other words, biological disturbances such as weeds, pathogens, and pests, as well as abiotic factors such as storage conditions, can cause significant decreases in yields if not managed properly. An expert system is a system that attempts to adopt human knowledge into a computer so that the computer can solve problems as is usually done by experts. While an expert system is a branch of artificial intelligence that uses the special knowledge possessed by an expert to solve certain problems. Forward Chaining is a method of data reasoning that starts from known facts and uses rules (IF-THEN) to reach a conclusion or solution. With this application, it is expected that the community can carry out early treatment and prevention of the disease independently, so as not to worsen the disease in the plant. The expert system is also equipped with a Microsoft Visual Studio solution, a complete application created by Microsoft. In Visual Studio, there are several programming languages that are often used, such as Visual Basic 2008. Visual Studio 2008 Express Edition is very popular as a Windows Application Development Tool.

Implementation of Social Media Analytics Using Buffer Tool to Measure Business Instagram Content Performance Yohana, Yohana; Kosasi, Sandy; Yuliani, I Dewa Ayu Eka
CSRID (Computer Science Research and Its Development Journal) Vol. 17 No. 2 (2025): Juni 2025
Publisher : LPPM Universitas Potensi Utama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22303/csrid-.17.2.2025.191-203

Instagram social media has been utilized by businesses as a platform for digital marketing activities. To assess the success of these marketing efforts, measuring content performance on Instagram is essential. This measurement involves analyzing data and insights regarding metrics such as reach, engagement, and impressions. These metrics are obtained through the process of Social Media Analytics (SMA) on the Instagram platform. However, many businesses experience a consistent decline in insights, resulting in decreased effectiveness of digital marketing. This study proposes a solution by implementing enhanced digital marketing on Instagram, followed by the measurement of Key Performance Indicators (KPIs). The measurement tool used is Buffer, which provides a comprehensive analysis dashboard concerning content performance, audience interaction patterns, and the impact of posting times on audience engagement in real-time. The KPI measurement during 3 months results indicate a significant increase, including a 66% rise in posts, a 69% increase in impressions, a 32% increase in reach, a 167% increase in likes, a 90% increase in comments, and a 105% increase in new followers for Casia store's Instagram channel. The accuracy of the data obtained from the Buffer analytic tool is verified through comparison with the impression metrics from Instagram Insight, which show identical figure, and Buffer has proven to be effective and accurate for measuring content performance and supports the implementation of SMA on the Instagram platform.

Segmentation and Classification of Vitamin C Content in Red Chili Pepper Images Using the Linear Discriminant Analysis (LDA) Method: Segmentation and Classification of Vitamin C Content in Red Chili Pepper Images Using the Linear Discriminant Analysis (LDA) Method Ramadhanu, Agung; Chan, Fajri Rinaldi; Yasmin, Nabilla; Negoro, Wahyu Saptha; Mardison, Mardison; Hendri, Halifia
CSRID (Computer Science Research and Its Development Journal) Vol. 17 No. 2 (2025): Juni 2025
Publisher : LPPM Universitas Potensi Utama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22303/csrid-.17.2.2025.149-162

The vitamin C content in red chili peppers plays a crucial role in meeting nutritional needs, particularly in free nutritious lunch programs. Red chili peppers are one of the essential sources of vitamin C in daily consumption. However, vitamin C content in chilies can degrade due to storage and drying processes. This study develops a segmentation and classification method for vitamin C content in red chili pepper images using Linear Discriminant Analysis (LDA) as a faster and more efficient alternative to conventional laboratory methods. The dataset consists of 100 red chili images categorized into fresh and dried chilies. The analysis process includes preprocessing, feature extraction of color and texture (RGB, HSV, GLCM), dimensionality reduction, and classification using LDA. Experimental results show that this method achieves 99% accuracy on training data and 97% on test data, demonstrating that digital image processing can serve as a non-destructive approach for food quality estimation. This approach has the potential to be applied in food quality monitoring within the food industry and public nutrition programs.

Expert System for Selecting College Majors Based on Interests and Talents Using the Certainty Factor (CF) Method Siregar, Aldi Sajali; Ritonga, Wahyu Azhar; Samsir, Samsir
CSRID (Computer Science Research and Its Development Journal) Vol. 17 No. 2 (2025): Juni 2025
Publisher : LPPM Universitas Potensi Utama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22303/csrid-.17.2.2025.163-175

Generally, new prospective students often experience confusion in choosing a major in Computer Science, Informatics Engineering Program at Universitas Al Washliyah Labuhanbatu that truly matches their academic abilities and interests. Often, the decision to choose a major is influenced by the environment, such as following close friends or advice from parents, without considering the students' true potential and talents. However, choosing an inappropriate major can negatively impact their academic future and career. Therefore, it is crucial for prospective students to recognize and understand their academic abilities as well as their special interests and talents. The expert system for major determination developed using the Certainty Factor method is expected to provide an effective solution by combining various indicators of interests, talents, and academic abilities of prospective students. This method utilizes established rules to calculate the certainty level (CF value) for each possible major based on the data and characteristics possessed by the student. By combining CF values from various facts, the system can provide recommendations for the major that best fits the student's greatest potential. This model does not rely solely on academic scores but also considers special interests such as social, creative, and artistic talents possessed by students, making the major selection decision more precise and directed. Thus, this Decision Support System can assist the Faculty of Computer Science, Informatics Engineering Program at Universitas Al Washliyah Labuhanbatu in selecting truly potential new students and providing appropriate recommendations, thereby minimizing the risk of wrong major choices and increasing the likelihood of academic and career success for prospective students.

Expert System for Stroke Diagnosis Using the Forward Chaining Method for Lecturers at UNIVA Labuhanbatu Samsir, Samsir; Syahputra, Andi; Subagio, S.
CSRID (Computer Science Research and Its Development Journal) Vol. 17 No. 2 (2025): Juni 2025
Publisher : LPPM Universitas Potensi Utama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22303/csrid-.17.2.2025.176-190

Stroke is a health problem that often occurs when the blood supply to the brain lacks oxygen and nutrients. As a result, in a matter of minutes, brain cells begin to die. This condition is classified as a serious disease and can be life-threatening, therefore requiring immediate medical attention. Stroke accounts for 10% of all deaths in the world and is the third leading cause of death after coronary heart disease (13%) and cancer (12%) in developed countries. The prevalence of stroke varies in different parts of the world. The prevalence of stroke in the United States is around 7 million (30%), while in China the prevalence of stroke ranges from 1.8% (rural) to 9.4% (urban). Worldwide, China is the country with the highest death rate from stroke (19.9% of all deaths in China), along with Africa and North America. The incidence of stroke worldwide is 15 million each year, one third of whom die and one third of whom experience permanent disability. The purpose of this study is to help and facilitate lecturers at Labuhanbatu University to diagnose stroke in determining treatment and how to overcome it effectively and efficiently. Lecturers at Univa Labuhanbatu can diagnose in advance what disorders they are experiencing before going to the doctor, so they can save time and money. This system is present as a means to help diagnose patients using the Forward Chaining method. With an expert system, laypeople will be able to solve quite complicated problems that can actually only be solved with the help of experts. For experts, expert systems will also help their activities as very experienced assistants. Microsoft Visual Studio .NET is a complete collection of development tools for building ASP.NET Web applications, XML Web Services, desktop applications, and mobile applications. In Visual Studio, these are the .NET programming languages such as Visual Basic, Visual C++, Visual C# (CSharp), and Visual J# (JSharp). All use the same integrated development environment or IDE so that it is possible to share tools and facilities

Expert System for Diagnosing Eye Disorders (Refractive Errors) Using the Certainty Factor (CF) Method at Tanjung Sarang Elang Community Health Center Subagio, Selamat; Harahap, Fauji; Samsir, Samsir
CSRID (Computer Science Research and Its Development Journal) Vol. 17 No. 2 (2025): Juni 2025
Publisher : LPPM Universitas Potensi Utama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22303/csrid-.17.2.2025.204-216

The medical and technology fields are rapidly advancing, leading many people to use computers to help diagnose, prevent, and treat human diseases. One major issue in the medical world is the imbalance between the number of patients and doctors. Additionally, most people lack medical training, so when experiencing symptoms of a disease, it is often difficult to immediately know the correct steps to take. Eye diseases vary in severity, ranging from mild to severe. One common eye disorder affecting many people is refractive error, which generally falls into two categories: hyperopia (farsightedness) and myopia (nearsightedness). Early detection of symptoms related to refractive errors requires accurate and prompt diagnosis. Therefore, with the rapid development of technology, it is essential to develop systems capable of early detection of eye diseases, especially refractive errors, by using technology that mimics human expert capabilities, such as expert systems. This expert system integrates expert knowledge within two main environments: the development environment and the consultation environment, helping the community diagnose diseases more easily and efficiently. For example, the use of the Certainty Factor method in expert systems enables the calculation of diagnostic certainty levels based on the combination of symptoms reported by patients and expert knowledge, achieving a confidence level of up to 96.7%. This demonstrates that expert system technology can be a valuable tool in addressing the imbalance between patients and doctors while improving access to faster and more accurate diagnoses. To build such systems, Microsoft Visual Studio .NET provides a complete set of tools for developing ASP.NET web applications, XML Web Services, desktop applications, and mobile applications. Within Visual Studio, .NET programming languages such as Visual Basic, Visual C++, Visual C# (CSharp), and Visual J# (JSharp) are used in a unified integrated development environment (IDE), enabling developers to efficiently share tools and resources to create reliable and user-friendly expert system applications. The system was developed and tested using symptom data from 40 patients collected at the Tanjung Sarang Elang Community Health Center. The testing showed a diagnostic accuracy of up to 96.7% in detecting symptoms of both hyperopia and myopia.

Analysis of User Satisfaction Level of Google Application Classroom Using the ECUS Method Putra, Edson Yahuda; Lahamendu, Irene Gloria; Ngangk, Stivia Yuliefri Lulij; Adam, Stenly Ibrahim; Tangka, George Morris William
CSRID (Computer Science Research and Its Development Journal) Vol. 17 No. 2 (2025): Juni 2025
Publisher : LPPM Universitas Potensi Utama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22303/csrid-.17.2.2025.217-228

Despite wide adoption during the COVID‑19 pandemic, Google Classroom’s long‑term acceptance in Indonesian higher education remains under‑examined. This study measures end‑user satisfaction using the five‑factor End‑User Computing Satisfaction (EUCS) framework. A cross‑sectional survey captured 247 valid responses from undergraduate students at Universitas Klabat who had used Google Classroom for at least one semester. Twenty Likert‑scaled items (4 per EUCS dimension) were adapted from Doll & Torkzadeh (1988) and checked for reliability (Cronbach’s α) and validity. Multiple‑linear regression assessed the partial effect of each EUCS factor on overall satisfaction, while descriptive statistics profiled satisfaction levels. Four dimensions—Content (β = 0.299, p < 0.001), Ease of Use (β = 0.268), Format (β = 0.182), and Timeliness (β = 0.222)—significantly predict satisfaction (Adj. R² = 0.682). Accuracy (β = 0.009, p = 0.841) is non‑significant, likely due to low internal consistency (α = 0.429). Overall, 69.6 % of respondents report being satisfied or very satisfied with Google Classroom. Content richness, intuitive interface, presentation quality, and timely feedback drive student satisfaction, whereas perceived accuracy warrants instrument refinement. Findings inform LMS developers and university decision‑makers on prioritised enhancement areas.

Komparasi Algoritma Data Mining Sebagai Prediksi Harapan Hidup Pasien Gagal Jantung: Komparasi Algoritma Data Mining Sebagai Prediksi Harapan Hidup Pasien Gagal Jantung Merdekawati, Agustiena
CSRID (Computer Science Research and Its Development Journal) Vol. 14 No. 3: October 2022
Publisher : LPPM Universitas Potensi Utama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22303/csrid-.14.3.2022.188-202

The heart is the most vital organ of the body. Heart failure is the leading cause of death with the largest number of cases. Therefore, it is necessary to estimate the biggest factor in life expectancy in patients with heart failure, so as to reduce mortality. In predicting the life expectancy of heart failure by using Knowledge Discovery in Database (KDD) it is possible to find predictive patterns of life expectancy for heart failure, so that it can reduce mortality. In this study using the C4.5 algorithm and the C4.5 algorithm with PSO (Particle Swarm Optimization) to obtain a predictive pattern of life expectancy for heart failure which then obtained the percentage of precision, recall and accuracy. This research is to produce a predictive pattern of life expectancy for heart failure with the criteria for the length of time the action has a top priority. By using the C4.5 algorithm, an accuracy of 73.33% is obtained, while using the C4.5 and PSO algorithms an accuracy of 99.00% is obtained, so it can be concluded based on the accuracy level that the C4.5 and PSO algorithm modeling has a higher accuracy than the C4.5 algorithm. . By using the C4.5 algorithm, the ROC graph accuracy is 0.897%, while using the C4.5 and PSO algorithms the ROC graph accuracy is 1.00%, so it can be concluded based on the ROC graph accuracy level that the C4.5 and PSO algorithm modeling has more accuracy. higher than the C4.5 algorithm.

Home Page

OAI Link

Editorial Team

Contact

Reviewer

Google Scholar

Contact Name
Elsa Aditya

Contact Email
redaksijurnalupu@gmail.com

Phone
+6285175205250

Journal Mail Official
redaksijurnalupu@gmail.com

Editorial Address
JL. KL. Yos Sudarso Km. 6,5 No. 3A, Tanjung Mulia, Medan, Sumatera Utara, 20241

Location
Kota medan,

Sumatera utara

INDONESIA

Abstract

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Home Page

OAI Link

Editorial Team

Contact

Reviewer

Google Scholar

Contact Name Elsa Aditya

Contact Email redaksijurnalupu@gmail.com

Phone +6285175205250

Journal Mail Official redaksijurnalupu@gmail.com

Editorial Address JL. KL. Yos Sudarso Km. 6,5 No. 3A, Tanjung Mulia, Medan, Sumatera Utara, 20241

Location Kota medan, Sumatera utara INDONESIA

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Contact Name
Elsa Aditya

Contact Email
redaksijurnalupu@gmail.com

Phone
+6285175205250

Journal Mail Official
redaksijurnalupu@gmail.com

Editorial Address
JL. KL. Yos Sudarso Km. 6,5 No. 3A, Tanjung Mulia, Medan, Sumatera Utara, 20241

Location
Kota medan,

Sumatera utara

INDONESIA