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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 149 Documents
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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.
Analisis Clustering Kepuasan Pelanggan Bengkel Mobil Auto Muara Baru Menggunakan Metode K-Means Herdiansyah, Roydido; Suryadi, Sudi; Irmayanti, Irmayanti
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.v6i3.7929

Abstract

This study aims to analyze customer satisfaction of Muara Baru Auto Repair Shop by using K-Means clustering method. Customer satisfaction is a crucial factor in maintaining loyalty and improving service quality in the automotive industry. The Data was collected through surveys involving customers who had used the workshop services, and then analyzed using the k-Means algorithm to identify patterns and clusters in satisfaction levels. The results of the analysis show that there are several clustering that reflect variations in customer satisfaction levels, providing important insights into service aspects that need to be improved as well as areas that have met customer expectations. These findings indicate that the K-Means method is effective in analyzing customer satisfaction and can be used as a basis for workshop management to formulate service improvement strategies to better meet customer expectations.
Pengembangan Program Kewirausahaan melalui Manajemen Pendidikan di SMK Amal Luhur Kota Medan Haqki, Bay
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.v6i3.7891

Abstract

This study aims to describe and analyze how educational management plays a role in the development of entrepreneurship programs at SMK Amal Luhur in Medan City. The background of this study is based on the importance of integrating entrepreneurial values in the education system, especially in Vocational High Schools (SMK) which are oriented towards producing graduates who are ready to work and are economically independent. This study uses a descriptive qualitative approach with data collection techniques in the form of observation, in-depth interviews, and documentation studies. The results show that the development of the entrepreneurship program is carried out through a managerial process that includes entrepreneurship curriculum planning, implementation of project-based learning, and continuous evaluation involving teachers, students, and industry partners. In addition, the support of school leadership and collaboration with the business world are key factors in the success of the program. This study concludes that effective educational management can create a learning ecosystem that is conducive to the growth of students' entrepreneurial spirit.
Analisis Sentimen Pelayanan Pembayaran Pajak Menggunakan Metode Algoritma Naïve Bayes Pada Kantor Badan Pendapatan Daerah Labuhanbatu Utara Dengan Menggunakan RapidMiner Purba, Mhd. Rafly; Harahap, Syaiful Zuhri; 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.v6i3.7959

Abstract

Improving the quality of Public Services is a major need in the era of digitalization, including in the local taxation sector related to the sentiment of services provided in tax payments. The purpose of this study was to analyze public sentiment towards tax payment services in the Office of the regional Revenue Agency (Bapenda) Labuhanbatu Utara by applying Naïve Bayes algorithm using Rapid Miner software. Data analysis through text preprocessing, feature selection, and sentiment classification into positive, negative, and neutral categories. The Data obtained consisted of 225 community comments from the SIMPATDA application and 612 tweets with the hashtag #pajakLabura from Twitter, which reflected people's opinions directly. The analysis process is carried out through the stages of text preprocessing, feature selection, to the classification of sentiments into positive, negative, and neutral categories. The results showed that the Naïve Bayes algorithm is able to classify public opinion with a high degree of accuracy and establish similarities/differences in the aspects of service that are most complained about or appreciated by the public. This study also contributes to the development of data-based evaluation system in the scope of public services.
Kepatuhan Pembayaran Pajak Kendaraan Bermotor Menggunakan Algoritma Decision Tree Dan Random Forest Di Samsat Balige Wijaya, Alief Achmad; Harahap, Syaiful Zuhri; Ah, Rahma Muti; Nasution, Marnis
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.v6i3.7934

Abstract

This study aims to analyze and predict the total category of Motor Vehicle Tax (PKB) payments based on payment attributes and vehicle types, which is important to improve the effectiveness of tax management and support more appropriate decision making in related agencies; within the theoretical framework, classification models such as Decision Tree and Random Forest are used to predict data categories by utilizing historical patterns in the dataset, because these algorithms are able to capture interactions between attributes and provide logical interpretations of the prediction results; the research methodology is carried out using secondary data of PKB payments for 2024 from Samsat Balige, which is divided into training data and test data for the classification process and its performance is evaluated using accuracy, precision, recall, and F1-Score metrics through the Performance operator in RapidMiner; the results of the study show that Random Forest produces a more balanced prediction distribution with 100% accuracy, while Decision Tree has 96% accuracy but tends to be biased towards the “Low” category, and analysis of important attributes such as Fines, Total Amount, and the number of Jeep and Truck type vehicles shows a significant influence on the PKB payment category; Thus, the research conclusion confirms that Random Forest is proven to be more effective and stable than Decision Tree in predicting the total PKB payment category, is able to capture complex patterns between attributes, and provides accurate predictions on relatively small datasets, making it the optimal choice for PKB data classification.

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