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Multica Science and Technology
Published by Universitas Mulia
ISSN : -     EISSN : 27762386     DOI : https://doi.org/10.47002/mst.v1i1
Core Subject : Science,
Computer Science & IT Energy Library & Information Science Physics
Focus and Scope The journal covers all aspects of science and technology, that is: Science: Bioscience & Biotechnology; Chemistry; Food Technology; Applied Biosciences and Bioengineering; Environmental; Health Science; Mathematics; Statistics; Applied Physics; Biology; Pharmaceutical Science; etc. Technology: Artificial Intelligence; Computer Science; Computer Network; Data Mining; Web; Language Programming; E-Learning & Multimedia; Information System; Internet & Mobile Computing; Database; Data Warehouse; Big Data; Machine Learning; Operating System; Algorithm; Computer Architecture; Computer Security; Embedded system; Cloud Computing; Internet of Thing; Robotics; Computer Hardware; Geographical Information System; Virtual Reality; Augmented Reality; Multimedia; Computer Vision; Computer Graphics; Pattern & Speech Recognition; Image processing; ICT interaction with society; ICT application in social science; ICT as a social research tool; ICT in education
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 57 Documents
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COMPARISON OF MEAN CENTERING REGRESSION AND SPLINE TRUNCATED NONPARAMETRIC REGRESSION ON FACTORS AFFECTING THE NUMBER OF CRIMES IN INDONESIA Felicia Joy Rotua Tamba; Liana Oklas Ranly; Andrea Tri Rian Dani; Meirinda Fauziyah; Narita Yuri Adrianingsih; Mislan Mislan
Multica Science and Technology (ACCREDITED-SINTA 5) Vol. 5 No. 1 (2025): Multica Science and Technology
Publisher : Universitas Mulia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47002/fpp74f96

Abstract

Crime remains one of the major challenges facing Indonesia, with the national crime rate showing an upward trend in 2022. This increase is driven by various social, economic, and demographic factors. To investigate these influences, this study applies the nonparametric truncated spline regression method to identify the determinants of crime rates across provinces in Indonesia. The response variable is the number of recorded crimes, while the predictor variables include the percentage of people living in poverty, mean years of schooling, average monthly per capita expenditure on food and non-food items, number of beneficiary households, budget for food social assistance, liberty aspects from the Indonesia Democracy Index, and the percentage of people with mental disorders. The analysis reveals that the linear truncated spline regression model with three knot points provides the best fit, achieving a coefficient of determination (R²) of 87.31%. These findings highlight the model’s capability to capture complex, nonlinear relationships between socio-economic indicators, democratic freedoms, mental health, and crime incidence in Indonesia.
MAPPING CRIME-PRONE AREAS USING PRINCIPAL COMPONENT ANALYSIS (PCA) – CENTROID LINKAGE Yossy Candra; Andrea Tri Rian Dani
Multica Science and Technology (ACCREDITED-SINTA 5) Vol. 5 No. 1 (2025): Multica Science and Technology
Publisher : Universitas Mulia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47002/57qngy96

Abstract

Cluster analysis is a method employed to categorize data or objects according to their degree of resemblance. Centroid linkage is an algorithm that can be utilized in the grouping process. Centroid Linkage employs a hierarchical methodology that categorizes things into tiers according to their degree of similarity. Nevertheless, multicollinearity issues frequently arise in cluster analysis scenarios. Optimization of the centroid linkage technique through principal component analysis (PCA) diminishes research variables and generates a new principal component to address the issue of multicollinearity. To assess the validity of the clusters, the Silhouette Coefficient (SC) was utilized. The case study included characteristics deemed pertinent to crime issues in 34 provinces in Indonesia in 2021. The analysis yielded six principal components (PCs) with eigenvalues of one or above. The results from the Centroid Linkage algorithm indicated that the optimal number of clusters is 2, with a silhouette coefficient (SC) value of 0.61, signifying a well-structured and effective clustering arrangement. The attributes and delineation of each established cluster can yield insights for identifying crime-prone regions.
MATHEMATICAL REASONING ABILITIES OF STUDENTS IN TERMS OF FIELD DEPENDENCE (FD) COGNITIVE STYLE IN PROBLEM-SOLVING Zaini, Zaini
Multica Science and Technology (ACCREDITED-SINTA 5) Vol. 1 No. 1 (2021): Multica Science and Technology
Publisher : Universitas Mulia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47002/mst.v1i1.198

Abstract

Every individual has different abilities in translating problems because it is influenced by basic knowledge, experience, and cognitive. The cognitive types of FD were identical slower than others. This study describes the mathematical reasoning of students with cognitive type of FD in problem solving. The research data needed is the GEFT test, problem-solving tests, and interviews involving twostudents in level IV . All data were analyzed inductively. The results showed that students with the cognitive type of FD needed a long time to create connection to the problem thinking and they needed direction as a stimulus to stimulate their thinking. Lecturers can use realistic examples in the environment around them to make connections in their thinking.
APPLICATION OF INTELLIGENT SYSTEM WITH BACKPROPAGATION MODEL IN CLOUD IMAGE CLASSIFICATION Mulyadi Mulyadi; Ichwan, Muhammad; Rizka, Muhammad; Ula, Mutammimul
Multica Science and Technology (ACCREDITED-SINTA 5) Vol. 2 No. 1 (2022): Multica Science and Technology
Publisher : Universitas Mulia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47002/mst.v2i1.323

Abstract

The clouds have different patterns on each type and each type has different properties. The introduction of the type, shape, and nature of the cloud is indispensable in the weather forecasts so that the clouds can be classified. There are several methods used in the image classification process that is the method of the artificial neural network Backpropagation. The method of Backpropagation is one of the methods used for the classification process, in this research Backpropagation used on the training and testing process for the introduction of cloud imagery aimed at determining the type of cloud, before the second These stages are carried out imagery through the preprocessing process. From the training conducted using the Backpropagation method shows that this method generates the best weight value and saves that value into the database to do the testing process using a neural network Backpropagation. In addition, Backpropagation also has the ability to reduce errors by continuously correcting the weight until reaching the maximum target. Data used for training data as many as 92 cloud type image with each type of 10 imagery. In this study obtained a system success rate of 60.6%.
IMPLEMENTATION OF MACHINE LEARNING USING THE K-NEAREST NEIGHBOR CLASSIFICATION MODEL IN DIAGNOSING MALNUTRITION IN CHILDREN Mutammimul Ula; Ananda Faridhatul Ulva; Ilham Saputra; Mauliza Mauliza; Ivan Maulana
Multica Science and Technology (ACCREDITED-SINTA 5) Vol. 2 No. 1 (2022): Multica Science and Technology
Publisher : Universitas Mulia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47002/mst.v2i1.326

Abstract

The problem faced today is the lack of nutrition for children which causes stunting. One way to prevent stunting problems is to provide input to the community in Aceh for the importance of providing adequate nutrition for children. This study classifies toddlers who are identified as stunting with the K-NN model technology which is modeled in machine learning, the results are grouped. The purpose of this study was to determine the detection of malnutrition in toddlers and to classify data on malnutrition in toddlers using the k-means clustering method and the system that was built could be used as a reference to monitor the growth and development of children. Then in classifying malnutrition in children based on the results of the nutritional status criteria in toddlers, it can be known based on the index of Body Weight for Age (W/U), Height for Age (TB/U), and Weight for Height (W/TB). by entering data values ??from weight, height and gender of toddlers. The purpose of this study was to determine the detection of malnutrition under five at the Cut Meutia Hospital Kab. North Aceh. The process in the initial data analysis of Mr. ID, baby's name, gender, age, weight (kg), height (cm), the data to be classified for training data are 40 children in each region / village. In the assessment of nutritional status, it is classified as Malnutrition less than 3 SD or 70%, Malnutrition - 3 SD to < - 2 SD or 80%, Good Nutrition -2 SD to +2 SD, Over Nutrition >+2 SD. The results of the final score obtained are euclidean distance with a value of 1.3 with a ranking of malnutrition, age 1.6 months, weight (weight) 0.852, TB (height) 4.556 with euclidean distance with a value of 1.3 with a low ranking. For the second test data, age is 2.8 months, BB (weight) 0.222, TB (height) 4.556 with Euclidean distance with a value of 1.3 with a good rating of 0.778. The results of this study can be classified in children to children for each region in each region, village and sub-district of each Puskesmas in North Aceh Regency
THE EFFECT OF FIELD WORK PRACTICES ON WORK INTEREST OF CLASS XII STUDENTS OF ACCESS NETWORK ENGINEERING SKILLS COMPETENCE AT SMK NEGERI 5 TELKOM BANDA ACEH Husnizar Husnizar; Fathiah, Fathiah; Agus Fachruzi
Multica Science and Technology (ACCREDITED-SINTA 5) Vol. 2 No. 1 (2022): Multica Science and Technology
Publisher : Universitas Mulia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47002/mst.v2i1.327

Abstract

Education is a foundation for improving the quality of human resources. Quality education will be able to produce superior human resources from every aspect of life. One of the educations that is responsible for creating quality human resources is Vocational High School (SMK) education. Vocational learning load includes Face-to-face (TM) School Practice (PS) activities and Practical Activities in DU/DI. Field work practices can train and support the skills that students have learned while at school, so that they can be developed in the world of work. But apart from that, there are some SMKs that pay less attention to the implementation of the field work practice. The discrepancy between the material studied at school and what is faced by students in DU/DI. This study aims to determine how much influence field work practices have on the work interest of class XII students of Access Network Engineering Skills Competence at SMK Negeri 5 Telkom Banda Aceh. This study uses a quantitative approach with the method used is Ex Post Facto. The subjects of this study were 48 students of the Access Network Engineering Department. The instrument used is a questionnaire. The results of this study indicate that there is a positive influence between field work practices and work interest of class XII students of Access Network Engineering expertise competence at SMKN 5 Telkom Banda Aceh by 39.8%, while 60.2% is influenced by other factors. This study uses a quantitative approach with the method used is Ex Post Facto. The subjects of this study were 48 students of the Access Network Engineering Department. The instrument used is a questionnaire. The results of this study indicate that there is a positive influence between field work practices and work interest of class XII students of Access Network Engineering expertise competence at SMKN 5 Telkom Banda Aceh by 39.8%, while 60.2% is influenced by other factors. This study uses a quantitative approach with the method used is Ex Post Facto. The subjects of this study were 48 students of the Access Network Engineering Department. The instrument used is a questionnaire. The results of this study indicate that there is a positive influence between field work practices and work interest of class XII students of Access Network Engineering expertise competence at SMKN 5 Telkom Banda Aceh by 39.8%, while 60.2% is influenced by other factors.
LAMP MODIFICATION FROM HPLN TO LED TECHNOLOGY FOR SAVING ELECTRICAL ENERGY IN STREET LIGHTING Rosdiana Rosdiana; Arya Wiyangga Pradana; Muhammad Muhammad; Mutammimul Ula
Multica Science and Technology (ACCREDITED-SINTA 5) Vol. 3 No. 1 (2023): Multica Science and Technology
Publisher : Universitas Mulia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47002/mst.v3i1.423

Abstract

Energy Efficiency is a business that is carried out with the aim of reducing the amount of energy needed, in using an equipment or even an energy-related system. In its development in the field of lighting, LED (Light Emitting Diode) lamps are now starting to be used as lighting lamps for homes, industries and factories. In Indonesia, the use of LED lamps in lighting is still rarely used, because the price of LED lamps is quite expensive when compared to ordinary lamps. With the saving of electric power through the use of LED lights, the problem of operational costs will be easy to overcome. Indeed, the price of this LED lamp is a little expensive, but with the research on the comparison of the use of this LED lamp with HPL-N type lamps, the industry will consider using this LED lamp with a generally accepted application method to reduce energy expenditure. The previous conditions for Jalan Dolok Merawan used HPLN 250 Watt lamps with a handlebar angle of 24,920 ornaments, the resulting light intensity was 2189 Candela, the intensity of the resulting lighting was 97.94 Lux and has now been changed to make it more optimal to use 120 Watt LED type lights, the height of the pole used is 4 meterss with an ornament handlebar angle of 24.920, light intensity of 1242 Candella, lighting intensity of 55.33 lux. The results of this illumination intensity are in accordance with the standard determined by BSN SNI regarding Collector road class 3-7 Lux. The results achieved after the process of modifying HPL-N lamps to LEDs are that they can reduce the use of electrical energy in the lighting system and achieve efficiency for electric power consumption so that they can provide added value to the company in reducing the company's operational costs.
THE UTILIZATION OF COMPLEX PROPORTIONAL ASSESSMENT (COPRAS) IN DETERMINING THE SELECTION OF THE BEST SPEAKER Muhammad Rafli Nur Alam; Richki Hardi; Sumardi Sumardi
Multica Science and Technology (ACCREDITED-SINTA 5) Vol. 2 No. 1 (2022): Multica Science and Technology
Publisher : Universitas Mulia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47002/mst.v2i1.629

Abstract

Decision-making in choosing the appropriate sound system involves numerous considerations to achieve acceptable outcomes or quality. There are many critical factors influencing the selection of speaker models, such as the required program features, brand, design, power, and price. In this study, we introduce the Complex Proportional Assessment (COPRAS) method as a solution for making effective and high-quality decisions when selecting the best alternatives based on predefined criteria. The COPRAS method is employed to analyze various different alternatives and estimate their utility values. The case study presented in this research involves identifying the best alternatives according to the criteria within the context of sound systems. The COPRAS method aids in evaluating alternatives by taking into account the relative weights of each relevant attribute. Consequently, the use of the COPRAS method in selecting the best sound system has proven to be effective and beneficial. This method assists in addressing complexity, enhancing objectivity, and yielding more informative and accurate decisions.
DESIGN AND DESIGN OF A REAL-TIME KWH ELECTRICITY MONITORING SYSTEM BASED ON INTERNET OF THINGS IN SOLAR POWER PLANT Hadiyanto Hadiyanto; Syahruddin Syahruddin; Ali Abrar
Multica Science and Technology (ACCREDITED-SINTA 5) Vol. 3 No. 2 (2023): Multica Science and Technology
Publisher : Universitas Mulia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47002/mst.v3i2.763

Abstract

Monitoring electrical energy in the residential sector is necessary because the current use of electrical energy is less effective and is used very excessively and consumes more electrical power. So far, electrical power usage can only be seen through a kWh meter and only shows the cumulative amount of electrical energy used. However, the design limitations of analog panels only display aggregate consumption data, not real-time consumption data and allow direct monitoring in the field as well as manual recording, so more power is required and the process takes a long time. This research aims to design a real-time measurement system that is capable of monitoring electrical energy parameters for buildings in the residential sector for solar cell-based plants, so that consumers can monitor electricity consumption in real time via the internet. The research methodology is an experiment carried out using the monitoring system design method. Through a research scheme, collaboration with industry is proposed for 1 year with the first stage being hardware design, second being software programming. Hardware and software are connected so that the information presented can be accessed directly at that time. This device is designed to replace manual and conventional electrical energy measurement systems. The research results that will be obtained are a design for a real-time electrical power consumption monitoring system in the housing sector. The output is information on electrical energy consumption through off-line and on-line application media which is displayed on a desktop application on a computer, where the data delivery system is via communication
Determining the Quality of Earthquake Resistant House Buildings Using Simple Additive Weighting (Saw) and Technique For Order Of Preference By Similarity To Ideal Solution (Topsis) Burhanuddin Burhanuddin; Bakhtiar; Emi Maulani; Edi Yusuf
Multica Science and Technology (ACCREDITED-SINTA 5) Vol. 4 No. 1 (2024): Multica Science and Technology
Publisher : Universitas Mulia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47002/mst.v4i1.850

Abstract

This research aims to evaluate the quality of house buildings using the Simple Additive Weighting (SAW) model and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). This research uses six main criteria to assess building quality: Material strength, structural design, foundation, construction technology, construction quality, construction costs. With these six variables in determining the evaluation of house building materials. Determining the final ranking of these alternatives is based on their proximity to the ideal solution. Type A House, Type B House, Type C House, Type D House, Type E House and the weight value for each house C1 = 0.2; C2 = 0.1 ; C3 = 0.15 ; C = 0.20 ; C = 0.15; C = 0.2%. The ranking results for Type A Houses were 0.871, Type B Houses 0.874, Type C Houses 0.813, Type D Houses 0.976 and Type E Houses 0.959. The largest value is in Type D House 0.976 so the alternative Type D House 0.976 is the alternative chosen as the best alternative. Meanwhile, the ranking results for the topsis model for Type A Houses are 0.5423, Type B Houses are 0.5302, Type C Houses are 0.2709, Type D Houses are 0.8515 and Type E Houses are 0.959. The largest value is for Type D House 0.976 so that the Type E House alternative 0.8227 is the alternative chosen as the best alternative for Type E house. The research results show that the combination of the SAW and TOPSIS methods is effective in providing a comprehensive and objective evaluation of the quality of earthquake resistant house buildings. . The results of this research can be applied practically in the construction industry to improve the quality of earthquake-resistant house buildings, helping make more accurate and objective decisions.

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