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Richki Hardi
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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 7 Documents
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Search results for , issue "Vol. 5 No. 1 (2025): Multica Science and Technology" : 7 Documents clear
IMPLEMENTATION OF NEURAL NETWORK IN PREDICTING STOCK PRICE OF PT BANK RAKYAT INDONESIA (PERSERO) TBK Nurmayanti, Wiwit Pura; Ni Luh Desvita Pratiwi; Nariza Wanti Wulan Sari; Desi Yuniarti; Erlyne Nadhilah Widyaningrum; Thesya Atarezcha Pangruruk
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/dwkza342

Abstract

Forecasting involves estimating future outcomes by examining patterns in both historical and present data. A commonly used data type in forecasting is time series data, characterized by observations collected at consistent time intervals. One forecasting technique that has gained significant attention is the Neural Network, particularly through the Backpropagation method utilized in this study. In the context of the stock market, price fluctuations are influenced by a variety of factors, including shareholder rights, company performance, and the balance between supply and demand. Typically, a rise in stock prices leads to decreased demand, while a decline tends to stimulate it. Predicting stock prices, such as those of Bank Rakyat Indonesia (BRI), can support investors in making well-informed decisions. This research seeks to identify the optimal number of neurons in the hidden layer for forecasting BRI stock prices by minimizing error metrics such as MAPE, MSE, and MAE. The analysis revealed that forecasting the stock price of PT Bank Rakyat Indonesia (Persero) Tbk. using a neural network with one hidden neuron resulted in a MAPE of 1.22248 and an MAE of 61.30548.
TRAFFIC ACCIDENT VICTIM CLASSIFICATION IN BONTANG USING NW-KNN AND BACKWARD ELIMINATION Mangalik, Gerald; Nariza Wanti Wulan Sari; Surya Prangga; Wiwit Pura Nurmayanti; Ika Purnamasari
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/yfbspb33

Abstract

Traffic accidents have been a serious problem caused by various factors such as road conditions, driver behavior, and weather. To understand the pattern of victim severity, a classification approach capable of handling imbalanced data and irrelevant features was needed. This study aimed to classify the status of accident victims using the Neighbor Weighted K-Nearest Neighbor (NW-KNN) method, equipped with backward elimination for feature selection. Backward elimination was employed to reduce insignificant features and improve accuracy.The case study for this research involved the status of accident victims in Bontang City, with a sample size of 93 cases. There were nine features in this study: accident victim status, accident time, road density, road function, road surface condition, speed limit at the location, road slope, and road status.The research results showed that the best parameter combination for classification using the NW-KNN method with backward elimination was K = 7 and E = 3. The "type of accident" feature was eliminated, leaving 8 features. Classification results using the NW-KNN method with backward elimination yielded an accuracy of 88.89%, demonstrating an improvement in classification performance for identifying the status of traffic accident victims. Thus, this method proved to be an effective approach for traffic accident analysis in Bontang City.
USER EXPERIENCE (UX) AND USER INTERFACE (UI) DESIGN FOR E-GOVERNMENT SERVICES IN EAST KALIMANTAN: ENHANCING PUBLIC SERVICE ADOPTION THROUGH USER-CENTERED DESIGN Mundzir Mundzir
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/wr3h6h10

Abstract

This study investigates how user-centered User Experience (UX) and User Interface (UI) design influence the adoption of e-government services in East Kalimantan, Indonesia. Despite efforts to digitize public services, citizen engagement with these platforms remains low, often due to usability issues. Employing a qualitative descriptive approach grounded in the User-Centered Design (UCD) framework, data were collected through semi-structured interviews, direct user observations, and policy document analysis. Thematic analysis using NVivo revealed key pain points such as inconsistent interface design, cognitive overload, poor error recovery, and low user trust. Quantitative insights from observational data highlighted that task abandonment often occurred at CAPTCHA verification and form submission stages. The findings emphasize the importance of integrating UX/UI design principles, including heuristic evaluation and participatory design, into the development of digital public services. This study contributes to the discourse on e-government by demonstrating that citizen-centered design is crucial not only for improving service usability but also for fostering public trust and long-term adoption. Future work should focus on the development of standardized UX frameworks for regional governments to ensure inclusive, accessible, and responsive digital services.
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.
PROTECTION SYSTEM INI SOLAR PANEL AGAINST INDUCTION MOTOR LOAD Hadiyanto Hadiyanto; Ali Abrar; Rudiansyah Rudiansyah
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

Abstract

Solar Power Plants (PLTS) have become one of the solutions to meet the need for clean and sustainable energy. However, like other electrical systems, PLTS is also susceptible to disturbances and problems that can interfere with its performance and reliability. This study aims to design and build a voltage and current protection system at the PLTS inverter output to protect the 1-phase induction motor from damage due to unstable voltage and current. The protection system used is Over/Under Voltage Protector, and MCB for overvoltage and undervoltage protection and load current limitation, in order to protect electrical equipment connected to the PLTS system. The test results show that the protection system implemented on the Inverter Output can protect against overvoltage above 250 V, undervoltage below 185 V, and overcurrent.where if this happens then the electricity supply to the load will be automatically cut off
DESIGN AND DEVELOPMENT OF A PV INVERTER SYSTEM WITH A REAL POWER CONCEPT FOR INDUCTION MOTOR LOADS Hadiyanto Hadiyanto; Ali Abrar; Syahruddin Syahruddin; Muhammad Rifaldy Zhaqi
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/mst.v5i1.997

Abstract

The type of inverter used greatly affects the efficiency of the PLTS in distributing electrical power to the load to be used. The use of an inappropriate inverter type will cause electrical equipment to quickly become damaged [4]. This study was conducted to help determine the type of inverter that is more appropriate for use in a PLTS system with inductive and resistive loads, so that the quality of the electrical power produced is maximized. This study compared the 1000 Watt Pure Sine Wave Inverter and the 1000 Watt Modified Sine Wave Inverter by measuring the waveform, voltage output value, current output value, power output value, voltage Total Harmonic Distortion (THD) value and current Total Harmonic Distortion value. The final results of the study showed that the Pure Sine Wave Inverter was superior in producing output power, had lower voltage and current distortion values and could produce output waves with a pure sine shape

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