Article Per Year (5 Year)
p-Index From 2020 - 2025
9.278
P-Index
This Author published in this journals
All Journal Sinkron : Jurnal dan Penelitian Teknik Informatika Jurnal Teknik Informatika UNIKA Santo Thomas Jurnal Mantik Informatika Jurnal Tekinkom (Teknik Informasi dan Komputer) Journal of Computer Networks, Architecture and High Performance Computing International Journal of Business, Technology, and Organizational Behavior (IJBTOB) Majalah Ilmiah UPI YPTK Jurnal Teknik Informatika Unika Santo Thomas (JTIUST) Journal of Computer Science and Information Systems (JCoInS) IKA BINA EN PABOLO : PENGABDIAN KEPADA MASYARAKAT Journal of Student Development Information System (JoSDIS) Jurnal Pendidikan Indonesia (Japendi)
Syaiful Zuhri Harahap
Universitas Labuhanbatu
Aerospace Engineering Humanities Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Public Health Social Sciences Other

Published : 74 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 74 Documents
Search

 4   5   6   7   8 
Meningkatkan Indeks Penjualan Thriftting Sepatu di Pasar Gelugur Rantau Prapat dengan Strategi Penerapan PrestaShop Nasution, Fahri Emil Afandi; Harahap, Syaiful Zuhri; Nasution, Marnis
Journal of Computer Science and Information System(JCoInS) Vol 5, No 4: JCoInS | 2024
Publisher : Universitas Labuhanbatu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36987/jcoins.v5i4.6812

Abstract

To increase the sales index of Budi Shoes Thrift in the Glugur Rantauprapat market, this research will start developing e-commerce using CMS Prestashop. Data will be collected through observation and interviews with the owner of Budi Shoes Thrift.to understand customer preferences and buying and selling activities. Even though Prestashop allows easy online transactions, most users prefer to buy directly in store or use dropship services. The level of consumer trust in well-known local brand goods is the main component that influences this. Although Prestashop has tremendous potential to increase market and operational efficiency, effective promotion and outreach strategies are required to achieve success. The right strategy, which combines technology and increases customer trust, can drive Prestashop implementation, increase sales and strengthen market share.
Optimalisasi dan Strategi Penjualan Baju Thrifting Melalui Implementasi E-commerce CMS PrestaShop di Jalan Sigambal Rantauprapat Ardiansyah, Sandi; Harahap, Syaiful Zuhri; Munthe, Ibnu Rasyid
Journal of Computer Science and Information System(JCoInS) Vol 5, No 4: JCoInS | 2024
Publisher : Universitas Labuhanbatu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36987/jcoins.v5i4.6813

Abstract

Abstract This study aims to explore effective digital marketing strategies for enhancing thrift clothing sales in the era of information technology. With the rapid development of technology and increasing market competition, businesses that previously relied solely on social media platforms like Instagram now need to adapt by utilizing more professional e-commerce platforms. This research compares specific thrift platforms with websites using CMS Prestashop in attracting consumer attention. The methods employed include observation, interviews, and literature reviews, aiming to understand the interaction patterns between sellers and buyers, as well as the operational dynamics within thrift businesses. The findings are expected to provide valuable insights for entrepreneurs in formulating more effective digital marketing strategies, thereby increasing competitiveness and sustainability in an increasingly competitive market.
Implementasi Prestashop Pengembangan Website Hingga Pemasaran Dan Logistik Pada Toko SS Galery Rantauprapat Juwita, Juwita; Harahap, Syaiful Zuhri; Bangun, Budianto
Journal of Computer Science and Information System(JCoInS) Vol 5, No 4: JCoInS | 2024
Publisher : Universitas Labuhanbatu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36987/jcoins.v5i4.6816

Abstract

This article discusses the implementation of PrestaShop in website development, marketing and logistics at the SS Galery Rantauprapat store. PrestaShop is an e-commerce platform designed to make it easier to create and manage online stores with features that support sales, including product management, payment systems, and sales analysis. In the context of SS Gallery, the implementation of PrestaShop aims to increase operational efficiency and expand market reach. The implementation process begins with designing a website that is responsive and user-friendly, allowing customers to access product information easily. The e-marketing features in PrestaShop are also used to increase product promotions, attract more customers and increase their loyalty. In addition, an integrated logistics system helps in managing goods delivery efficiently, reducing customer waiting time. The results of this research show that using PrestaShop not only increases sales productivity but also simplifies the marketing process and logistics management. In this way, SS Galery Rantauprapat can compete better in an increasingly competitive digital market. This research provides insight for other business actors about the importance of information technology in supporting business growth in the digital era.
Perancangan Sistem Informasi Pendistribusian Beras Miskin Pada Kantor Kelurahan Sirandorung Berbasis Web Zuraidah, Zuraidah; Nasution, Marnis; Harahap, Syaiful Zuhri
Journal of Student Development Information System (JoSDIS) Vol 2, No 2: JoSDIS | Juli 2022
Publisher : Universitas Labuhanbatu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36987/josdis.v2i2.3276

Abstract

The development of today's increasingly advanced technology such as the use of computers has become popular in the community, the use of computers is very important because the computer is a tool in carrying out data processing activities, so that a job can be completed properly. How the distribution of rice for the poor can work properly using this application. The purpose of the study is to assist the process of distributing rice for the poor at the Sirandorung Village Office. The system analysis stage is a very important stage because errors at this stage will result in errors in the next stage. In analyzing the system, several methods are used, among others. Based on the results of research and discussion that the results of the analysis of the implementation of the distribution of rice for poor households (Raskin) in Sirandorung Village, Rantau Utara District, Labuhanbatu Regency, the implementation is still not precise and has not been implemented properly. This is based on the analysis above and based on the results of questionnaires and interviews with researchers from the Sirandorung sub-district office. All people in the Sirandorung sub-district should be collected and provided with detailed information about the Raskin program so that there is no misunderstanding or receiving inaccurate information about Raskin.
Prediksi Tweet Netizen Menggunakan Random Forest, Decision Tree, Naïve Bayes, dan Ensemble Algorithm Harahap, Vivi Nadenia; Irmayani, Deci; Harahap, Syaiful Zuhri
Jurnal Teknik Informatika UNIKA Santo Thomas Vol 6 No. 1 : Tahun 2021
Publisher : LPPM UNIKA Santo Thomas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54367/jtiust.v6i1.1274

Abstract

Gubernur DKI Jakarta saat ini, meski sudah terpilih sejak tahun 2017 selalu menarik untuk dibicarakan atau bahkan dikomentari. Komentar yang muncul berasal dari media secara langsung atau melalui media sosial. Twitter menjadi salah satu media sosial yang sering digunakan sebagai media untuk mengomentari gubernur terpilih bahkan bisa menjadi trending topic di media sosial Twitter. Netizen yang berkomentar pun beragam, ada yang selalu menge-Tweet kritik, ada yang berkomentar Positif, dan ada pula yang hanya me-retweet. Dalam penelitian ini, prediksi apakah Netizen aktif akan cenderung selalu menimbulkan komentar Positif atau Negatif akan dilakukan dalam penelitian ini. Model algoritma yang digunakan adalah Decision Tree, Naïve Bayes, Random Forest, dan juga Ensemble. Data Twitter yang diolah harus melalui preprocessing terlebih dahulu sebelum dilanjutkan menggunakan Rapidminer. Dalam uji coba menggunakan Rapidminer dilakukan dalam empat kali uji coba dengan membagi menjadi dua bagian yaitu data testing dan data latih. Perbandingan yang dilakukan adalah 10% data pengujian: 90% data pelatihan, kemudian 20% data pengujian: 80% data pelatihan, kemudian 30% data pengujian: 70% data pelatihan, dan yang terakhir adalah 35% data pengujian: 65% data pelatihan. Rata-rata Akurasi untuk algoritma Decision Tree adalah 93,15%, sedangkan untuk algoritma Naïve Bayes Akurasinya adalah 91,55%, kemudian untuk algoritma Random Forest adalah 93,41, dan yang terakhir adalah algoritma Ensemble dengan Akurasi sebesar 93,42%. sini. 65% data pelatihan. Rata-rata Akurasi untuk algoritma Decision Tree adalah 93,15%, sedangkan untuk algoritma Naïve Bayes Akurasinya adalah 91,55%, kemudian untuk algoritma Random Forest adalah 93,41, dan yang terakhir adalah algoritma Ensemble dengan Akurasi sebesar 93,42%. sini. 65% data pelatihan. Rata-rata Akurasi untuk algoritma Decision Tree adalah 93,15%, sedangkan untuk algoritma Naïve Bayes Akurasinya adalah 91,55%, kemudian untuk algoritma Random Forest adalah 93,41, dan yang terakhir adalah algoritma Ensemble dengan Akurasi sebesar 93,42%. sini.
Prediksi Tweet Netizen Menggunakan Random Forest, Decision Tree, Naïve Bayes, dan Ensemble Algorithm Harahap, Vivi Nadenia; Irmayani, Deci; Harahap, Syaiful Zuhri
Jurnal Teknik Informatika UNIKA Santo Thomas Vol 6 No. 1 : Tahun 2021
Publisher : LPPM UNIKA Santo Thomas

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (340.337 KB) | DOI: 10.54367/jtiust.v6i1.1274

Abstract

Gubernur DKI Jakarta saat ini, meski sudah terpilih sejak tahun 2017 selalu menarik untuk dibicarakan atau bahkan dikomentari. Komentar yang muncul berasal dari media secara langsung atau melalui media sosial. Twitter menjadi salah satu media sosial yang sering digunakan sebagai media untuk mengomentari gubernur terpilih bahkan bisa menjadi trending topic di media sosial Twitter. Netizen yang berkomentar pun beragam, ada yang selalu menge-Tweet kritik, ada yang berkomentar Positif, dan ada pula yang hanya me-retweet. Dalam penelitian ini, prediksi apakah Netizen aktif akan cenderung selalu menimbulkan komentar Positif atau Negatif akan dilakukan dalam penelitian ini. Model algoritma yang digunakan adalah Decision Tree, Naïve Bayes, Random Forest, dan juga Ensemble. Data Twitter yang diolah harus melalui preprocessing terlebih dahulu sebelum dilanjutkan menggunakan Rapidminer. Dalam uji coba menggunakan Rapidminer dilakukan dalam empat kali uji coba dengan membagi menjadi dua bagian yaitu data testing dan data latih. Perbandingan yang dilakukan adalah 10% data pengujian: 90% data pelatihan, kemudian 20% data pengujian: 80% data pelatihan, kemudian 30% data pengujian: 70% data pelatihan, dan yang terakhir adalah 35% data pengujian: 65% data pelatihan. Rata-rata Akurasi untuk algoritma Decision Tree adalah 93,15%, sedangkan untuk algoritma Naïve Bayes Akurasinya adalah 91,55%, kemudian untuk algoritma Random Forest adalah 93,41, dan yang terakhir adalah algoritma Ensemble dengan Akurasi sebesar 93,42%. sini. 65% data pelatihan. Rata-rata Akurasi untuk algoritma Decision Tree adalah 93,15%, sedangkan untuk algoritma Naïve Bayes Akurasinya adalah 91,55%, kemudian untuk algoritma Random Forest adalah 93,41, dan yang terakhir adalah algoritma Ensemble dengan Akurasi sebesar 93,42%. sini. 65% data pelatihan. Rata-rata Akurasi untuk algoritma Decision Tree adalah 93,15%, sedangkan untuk algoritma Naïve Bayes Akurasinya adalah 91,55%, kemudian untuk algoritma Random Forest adalah 93,41, dan yang terakhir adalah algoritma Ensemble dengan Akurasi sebesar 93,42%. sini.
Comparative Analysis of Incoming Goods Patterns Using FP-Growth and Apriori Algorithms: A Case Study in Retail Ritonga, Akbar Pramuja; Harahap, Syaiful Zuhri; Masrizal, Masrizal
Journal of Computer Networks, Architecture and High Performance Computing Vol. 7 No. 3 (2025): Articles Research July 2025
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v7i3.6776

Abstract

This study aims to analyze consumer purchasing patterns in minimarkets using the Apriori and Fp Growth association algorithms based on transaction data, where the data consists of 10 goods receipt transactions with 7 variable items such as Ultra Milk UHT 250ml, Indomie Goreng Spesial, Beras Ramos 5kg, Teh Cup Sariwangi 25's, Minyak Goreng Bimoli 1L, Soap Bar Lifebuoy 75g, and Mie Lemonilo Goreng 70g. The analysis process is carried out through the preprocessing stage, transformation to binary format, and application of the algorithm with minimum support parameters of 20% and confidence of 50%. The results show that Ultra Milk UHT 250ml has the highest support (0.5) followed by Indomie Goreng Spesial (0.4), while the combination of UHT Milk with Indomie has a support of 0.2; in terms of confidence, a number of rules even reach a perfect value of 1.0, for example the relationship between Teh Cup Sariwangi and Ultra Milk which always appear together. Quantitatively, Apriori produces 25 association rules with a processing time of approximately 2.1 seconds, while Fp Growth produces the same number of rules but is more efficient with a processing time of 1.3 seconds and lower memory usage, so it can be concluded that although both are equal in terms of rule quality, Fp Growth is superior in computational efficiency. This finding has important practical implications for minimarket management, especially to support shelf arrangement strategies, more targeted stock planning, and the preparation of bundling promotions based on product combinations with high confidence, while also showing a scientific contribution in the form of comparing the performance of two association algorithms on incoming goods data that is relatively rarely used in previous studies.
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.
Co-Authors Ah, Rahma Muti Aini, Putri Aisyah Hayati Ali Akbar Ritonga Amin, Mhd. Andini, Novira Dwi Andriani, Nur Putri ANTIKA, DEWI Aprilianto, Muhammad Ardiansyah, Rizaldi Bangun, Budianto Cahya, Susilo Tiadi Christoval, Peter Dalimunthe, Annisa Putri Faradilah, Rahma Fatma, Nurul Febriyanti, Ade Eka Hanif, Khairil Hansyah, Praida Harahap, Vivi Nadenia Hasibuan, Mila Nirmala Sari Hasibuan, Muhammad Adlin Hasibuan, Taufik Molid Hidayat Hermika, Eva Ibnu Rasyid Munthe Irmayani, Deci Irmayanti Irmayanti Irmayanti, Irmayanti Irmayati, Irmayati Iwan Purnama Iwan Purnama JP, Gafar Ilyaz Juledi, Angga Putra Juwita Juwita, Juwita Laila Sari Lestari, Putri Anggraini Lianah Lianah, Lianah Listia, Bella Ayu Lubis, Nadira Jannah Adeni M, Nelvi Nurrizqi Marnis Nasution Masrizal Megawati Pasaribu Meidy Putra Panusunan Siregar Melisa Melisa Melyani, Sri Mira Handayani Siregar Mth, Sri Rezky Aprilawati Br Muhammad Halmi Dar Munthe, Ibnu Rasyid Mushtafa Haris Munandar Muti’ah, Rahma Naibaho, Restu Fauzy Nasution, Fahri Emil Afandi Nasution, Fitri Aini Nasution, Intan Baiduri Nasution, Khodijah Nasution, Marnis Novita, Rini Pane, Dinda Nurinayah Panjaitan, Nia Putri Pasaribu, Nova Tresia Patriya, Angga Prayoga Pransiska, Apprillia Yudha Priyanti Priyanti Purba, Mhd. Rafly Putra, Fasdiansyah Putri Lestari, Putri Rafika, Mulya Rahma Muti’ah Ramadan, Ahmad Ramadhani Ramadhani Rambe, Aida Zahrah Hasanati Br Rambe, Nurhayati Rambey, Khiarul Akhyar Ritonga, Akbar Pramuja Ritonga, Ali Akbar Ritonga, Irmayanti SANDI ARDIANSYAH Sari, Kurnia Tika Sigit Prasetyo Nugroho Sihotang, Diko Pradana Sirait, Roby Gusmawan Siregar, Ade Elvi Rizki Siregar, Siti Kholijah Siregar, Siti Wahdina Sitepu, Melda Betaria Sitompul, Muhammad Sofyan Surbakti, M. Aufa Nayaka Fathan Suryadi, Sudi Suryadi, Sudi Syavitri, Tiara Wardani, Syafira Eka Wijaya, Alief Achmad Yeni Syahfutri S Yenni Syahfutri Sipahutar ZURAIDAH ZURAIDAH