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Syaiful Zuhri Harahap
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Program Studi Sistem Informasi, Fakultas Sains & Teknologi, Universitas Labuhanbatu Jalan Sisingamangaraja No.126 A KM 3.5 Aek Tapa, Bakaran Batu, Rantau Sel., Kabupaten Labuhanbatu, Sumatera Utara 21418
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Journal of Computer Science and Information Systems (JCoInS)
Published by Universitas Labuhanbatu
ISSN : -     EISSN : 27472221     DOI : 10.36987
Core Subject : Science,
Computer Science & IT
Journal of Computer Science and Information Systems (JCoInS) - Journal of the Information Systems Study Program seeks to facilitate critical study and in-depth analysis of information system problems, this journal is an expert computer science scientist, information system scientist. e-ISSN : 2747-2221
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 22 Documents
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Search results for , issue "Vol 6, No 3: JCoInS | 2025" : 22 Documents clear
Analisis Minat Konsumen Terhadap Produk Makanan Pada Mie Gacoan Menggunakan Algoritma Decision Tree (Studi Kasus Mie Gacoan Rantau Prapat) Harahap, Ismalya Wahyuni; Nasution, Fitri Aini; Yanris, Gomal Juni
Journal of Computer Science and Information System(JCoInS) Vol 6, No 3: JCoInS | 2025
Publisher : Universitas Labuhanbatu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36987/jcoins.v6i3.7973

Abstract

This study was conducted to analyze consumer interest in Mie Gacoan Rantau Prapat using a Decision Tree-based classification method. This analysis aims to determine the most influential factors in determining consumer interest in the food product. The theoretical basis used is the concept of data mining with classification techniques, where Decision Tree was chosen because of its ability to produce easy-to-understand models. In addition, theories regarding model evaluation such as accuracy, precision, and recall are also used to measure the performance of the built classification. This research methodology includes collecting data from 100 consumer entries which are then divided using the Split Data feature in RapidMiner with a ratio of 60:40, resulting in 40 training data and 60 testing data. The classification process is carried out using the Decision Tree algorithm, while evaluation is carried out with the performance operator to assess the model results. The classification results show that cleanliness is a major factor in determining consumer interest, where the number of consumers in the Interest category is more dominant than the No Interest category. The model evaluation yielded an accuracy of 73.33% with a precision of 73.47% in the Interested class and 72.73% in the Not Interested class, as well as a recall of 92.31% in the Interested class and 38.10% in the Not Interested class. In conclusion, the classification model developed is able to provide a picture of consumer interest patterns with a fairly good level of accuracy. These results can be a strategic reference for Mie Gacoan to improve service quality and cleanliness as the main factors determining consumer interest.
Implementasi K-Means Dalam Menentukan Tingkat Kepuasan Pelanggan Pada Bengkel Rizal Rantauprapat Rambey, Khiarul Akhyar; Suryadi, Sudi; Harahap, Syaiful Zuhri; Juledi, Angga Putra
Journal of Computer Science and Information System(JCoInS) Vol 6, No 3: JCoInS | 2025
Publisher : Universitas Labuhanbatu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36987/jcoins.v6i3.7937

Abstract

The growing automotive industry demands workshops to improve the quality of service for customer satisfaction. However, manual measurement of satisfaction is often inefficient and subjective. This study proposes the application of machine learning algorithms K-Means Clustering to analyze customer satisfaction data in Rizal workshop. This method is used to Group customers into several clusters based on similar satisfaction characteristics. The results of this grouping are expected to provide more objective and in-depth insights to identify patterns of satisfaction, thus enabling the workshop to formulate a more effective and targeted service quality improvement strategy.
Penerapan Data mining Klasifikasi Tingkat Kepuasan Mahasiswa Terhadap Pelayanan Akademik Menggunakan Metode Naïve Bayes Dan Support Vector Machine (Studi Kasus Program Studi Sistem Informasi Universitas Labuhanbatu) Antika, Dewi; Harahap, Syaiful Zuhri; Ah, Rahma Muti; Juledi, Angga Putra
Journal of Computer Science and Information System(JCoInS) Vol 6, No 3: JCoInS | 2025
Publisher : Universitas Labuhanbatu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36987/jcoins.v6i3.7917

Abstract

This study was conducted to classify public satisfaction levels using the Support Vector Machine (SVM) algorithm as the primary data analysis method. The objective of this study was to obtain an accurate and reliable prediction model for determining the Satisfaction and Dissatisfaction categories based on the available data. The theoretical basis used refers to the concept of machine learning, specifically SVM, which works by forming an optimal hyperplane to separate data classes. In addition, model evaluation theories such as the Confusion Matrix were used to objectively measure prediction performance. The research methodology included data collection, pre-processing, dividing the dataset into training and test data, and training the SVM model. Evaluation was conducted using accuracy, sensitivity, and specificity metrics to assess the model's ability to predict data accurately. The results and discussion indicate that the SVM successfully classified the majority of data correctly, with the Satisfaction class having a perfect prediction rate while the Dissatisfaction class still had a small error. Further analysis indicated the need for SVM parameter optimization to improve accuracy in the minority class. The conclusion of this study states that the SVM has good performance in classifying public satisfaction data, although it still requires refinement in recognizing certain class patterns. This finding opens up opportunities for developing more adaptive methods to improve predictive performance.
Pengembangan Sistem Informasi Akademik Berbasis Web Sebagai Sistem Pengolahan Nilai Siswa di SMK Muhammadiyah 03 Aek Kanopan Menggunakan Metode Research And Development Priyanti, Priyanti; Harahap, Syaiful Zuhri; Nasution, Fitri Aini; Suryadi, Sudi
Journal of Computer Science and Information System(JCoInS) Vol 6, No 3: JCoInS | 2025
Publisher : Universitas Labuhanbatu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36987/jcoins.v6i3.7878

Abstract

Web-based academic information system is an effective solution to manage the value of students at SMK Muhammadiyah 03 AEK Kanopan. This study aims to develop and evaluate the feasibility of the system using Research and Development methods. The developed system is designed to address challenges in the current value processing process, such as efficiency, accuracy, and data accessibility. In system development, the methodology used includes needs analysis, system design, implementation, and testing. Needs analysis is conducted to identify important features that must be present in the system, such as value input, final value calculation, report generation, and access for teachers, students, and administrative staff. After that, the system is designed with an intuitive interface and powerful functionality. The results of this study indicate that the web-based academic information system developed is very feasible to be used as a value processing system at SMK Muhammadiyah 03 AEK Kanopan. This feasibility is supported by evaluations from various stakeholders, including teachers and administrative staff, who assess this system can improve efficiency, reduce errors, and facilitate access to value information. Thus, this system is expected to be a reliable tool to support the teaching and learning process in the school.
Analisis Dampak Implementasi Sistem Informasi Manajemen Pada Efisiensi Proses Bisnis Kedai Kopi "Sahoeta Kopi" Wonosari Menggunakan Metode K Means Ardian, Aldi; Suryadi, Sudi; Nasution, Fitri Aini; Bangun, Budianto
Journal of Computer Science and Information System(JCoInS) Vol 6, No 3: JCoInS | 2025
Publisher : Universitas Labuhanbatu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36987/jcoins.v6i3.7974

Abstract

This study aims to perform clustering analysis on consumer data coffee shop “Sahoeta coffee” by using the method of K-Means clustering in RapidMiner Studio. The Data used include attributes of Consumer age, number of purchases per day, income per day, and capital per day. The clustering process divides the data into five different clusters, each with different characteristics in terms of purchases and revenue. The clustering results showed that Cluster 0 contained consumers with older age and more frequent shopping, while Cluster 1 contained younger consumers with lower purchases. Clusters 2, 3, and 4 show a pattern of consumers with higher incomes and capital, indicating that they have greater purchasing power. Visualization of clustering results provides a clear picture of consumer segments that can be used to design more specific marketing strategies.
Penerapan Metode Naïve Bayes Dalam Memprediksi Kepuasan Pelanggan Terhadap Pelayanan (Studi Kasus : Brastagi Supermarket Rantauprapat) Putra, Fasdiansyah; Harahap, Syaiful Zuhri; Irmayanti, Irmayanti; Bangun, Budianto
Journal of Computer Science and Information System(JCoInS) Vol 6, No 3: JCoInS | 2025
Publisher : Universitas Labuhanbatu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36987/jcoins.v6i3.7938

Abstract

Supermarkets are crowded shopping centers and have a high potential for violations against consumers, especially because most of the products sold are basic foodstuffs. This study aims to predict the level of customer satisfaction with service in Brastagi supermarket Rantauprapat by applying the Naïve Bayes method of Data Mining algorithm. The primary data collection process is done through the distribution of online questionnaires using Google Form to customers. To ensure the validity of the data, further verification was carried out through direct interviews with customers as well as supermarket managers. The results of this study are expected to provide in-depth analysis and new information for the management of Brastagi Supermarket Rantauprapat regarding customer satisfaction, which can be used as a basis for improving service quality in the future.
Perancangan Dan Implementasi E-Commerce Pada Jasa Titipan Luar Negeri (Cargo) Studi Kasus JNE Cabang Rantauprapat Rangkuti, M. Andri Gautama; Yanris, Gomal Juni; Sihombing, Volvo
Journal of Computer Science and Information System(JCoInS) Vol 6, No 3: JCoInS | 2025
Publisher : Universitas Labuhanbatu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36987/jcoins.v6i3.7927

Abstract

The development of information technology has driven transformation in various sectors, including international logistics services that demand speed, accuracy, and transparency of information. JNE Rantauprapat Branch, as a provider of international courier services, requires an integrated e-commerce system to address the challenges of services that were previously manual. This study uses the Waterfall method with structured stages of needs analysis, system design, implementation, testing, and maintenance. The technologies used include Laravel and MySQL, with testing conducted through black-box testing and user acceptance testing. The results show that the developed e-commerce system successfully integrates online ordering, shipping cost checking, real-time tracking, and international outlet tracking features effectively. This system is able to provide accurate information, reduce staff workload, and increase customer satisfaction. The research discussion confirms that this digital transformation not only simplifies operational processes but also strengthens the branch's competitiveness in the international logistics market. In addition, this system opens up opportunities for optimizing data management to support strategic decision-making. In conclusion, the implementation of e-commerce in international cargo services at JNE Rantauprapat Branch has been proven to improve efficiency and service quality. This implementation is also a long-term strategy to maintain competitiveness in the increasingly competitive digital era.
Analisis Sentimen Ulasan Produk Suncreen Wardah Pada Marketplace Shopee Menggunakan Metode Naïve Bayes Rambe, Nurhayati; Harahap, Syaiful Zuhri; Ritonga, Ali Akbar; Bangun, Budianto
Journal of Computer Science and Information System(JCoInS) Vol 6, No 3: JCoInS | 2025
Publisher : Universitas Labuhanbatu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36987/jcoins.v6i3.7992

Abstract

The development of the digital world and the popularity of online marketplaces such as Shopee have changed the way consumers interact and review products. Reviews of Wardah sunscreen products, which have an important role in skin health, are one of the most widely found. Understanding the sentiment of these reviews is crucial for manufacturers to improve product quality. Therefore, this study aims to analyze and classify consumer sentiment towards Wardah sunscreen products on Shopee. Using the Naïve Bayes classification method, the reviews will be categorized into positive, negative, and neutral sentiments to get an overall picture of the public perception of the product.
Pengembangan Sistem Informasi Berbasis Web Sebagai Sistem Pengelolaan Nilai Sekolah Menengah Siswa SMP Negeri 2 Satap Kualuh Hilir Dengan Menggunakan Metode End User Computing Satisfacation Siregar, Ade Elvi Rizki; Harahap, Syaiful Zuhri; Irmayanti, Irmayanti; Bangun, Budianto
Journal of Computer Science and Information System(JCoInS) Vol 6, No 3: JCoInS | 2025
Publisher : Universitas Labuhanbatu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36987/jcoins.v6i3.7879

Abstract

Research is a crucial element in the learning process to measure students ' understanding and evaluate the quality of Education. However, the process of managing student grades is often complicated, especially with dynamic curriculum changes in Indonesia, such as the transition from the 2013 curriculum to The Independent curriculum. Based on the problems in SMP Negeri 2 Satap Kualuh Hilir, this study aims to design and build a web-based student Value Management Information System. The development of this system is expected to be a solution to manage value more quickly, accurately, and efficiently. In addition, this system is designed to maximize the utilization of computer network facilities that are already available in schools, so as to assist teachers and schools in producing assessment reports that are in accordance with the applicable curriculum.
Penerapan Data Mining Untuk Memprediksi Prestasi Akademik Siswa SMKS IT Shah Hamidun Majid Menggunakan Algoritma Decision Tree Sahbana, Ahmad; Nasution, Fitri Aini; Ritonga, Ali Akbar; Suryadi, Sudi
Journal of Computer Science and Information System(JCoInS) Vol 6, No 3: JCoInS | 2025
Publisher : Universitas Labuhanbatu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36987/jcoins.v6i3.7939

Abstract

Education is the main foundation in the development of superior human resources, especially in the digital era that demands the use of Information Technology. One of the main challenges is how schools are able to effectively manage and analyze academic data. Data mining comes as a solution in extracting hidden information from educational data so that it can support strategic decision making. This study focuses on the application of Decision Tree algorithm in predicting student academic achievement in SMKs It Shah Hamidun Majid. The Decision Tree algorithm was chosen because it is easy to understand and is able to provide accurate classification based on various variables, such as attendance, grades, and student background. By utilizing academic data for the 2023/2024 school year, this study is expected to produce predictive models that help schools identify factors that affect student achievement, provide personalized coaching recommendations, and support data-based policies. The results of this study are expected to be a real contribution in the development of academic information systems that are adaptive, inclusive, and oriented to improving the quality of education at the private vocational school level.

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