Article Per Year (5 Year)
p-Index From 2020 - 2025
7.469
P-Index
This Author published in this journals
All Journal Jurnal Teknologi dan Manajemen Informatika InfoTekJar : Jurnal Nasional Informatika dan Teknologi Jaringan JURNAL ILMIAH INFORMATIKA Computer Based Information System Journal Jurnal Informasi dan Komputer Building of Informatics, Technology and Science JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) JPMB: Jurnal Pemberdayaan Masyarakat Berkarakter Ar-Rasyid: Jurnal Pendidikan Agama Islam Kontribusi: Jurnal Penelitian dan Pengabdian Kepada Masyarakat Jurnal Puan Indonesia Jurnal Desain dan Analisis Teknologi Jurnal Pengabdian Ibnu Sina Jurnal Pengabdian Barelang Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen) Computer & Science Industrial Engineering Journal Prosiding Seminar Nasional Ilmu Sosial dan Teknologi (SNISTEK)
Harman, Rika
Universitas Putera Batam
Religion Agriculture, Biological Sciences & Forestry Humanities Biochemistry, Genetics & Molecular Biology Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Public Health Social Sciences Other

Published : 65 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 14 Documents
Search
Journal : Computer Based Information System Journal

 1   2 
PENERAPAN ALGORITMA C4.5 UNTUK MEMPREDIKSI PENJUALAN BARANG PADA PT PRIMA NIAGA INDOMAS Alyshen, Alyshen; Harman, Rika
Computer Based Information System Journal Vol. 12 No. 1 (2024): CBIS Journal
Publisher : Universitas Putera Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33884/cbis.v12i1.8328

Abstract

Facing the dynamics of a competitive and rapidly changing business environment, PT Prima Niaga Indomas, a snack food distribution company, encounters challenges in optimizing its product sales. Accurate sales forecasting is crucial to maintaining inventory efficiency, avoiding overstock, and meeting customer demand. This research aims to implement the C4.5 algorithm to predict the sales of snack food products at PT Prima Niaga Indomas. The location of PT Prima Niaga Indomas is at Puri Industrial Park 2000 Block D No. 5, Batam Centre, Batam City, Riau Islands. By leveraging historical sales data, product information, marketing factors, and external variables, this study seeks to develop a predictive model to assist the company in forecasting snack food product sales more accurately. The data generated from this research is expected to make a significant contribution to improving the operational efficiency of PT Prima Niaga Indomas. Data analysis is conducted by applying the C4.5 algorithm using WEKA software version 3.8.5, with manual calculations for comparison using Microsoft Excel. The research findings indicate the accuracy of data in the rules of delivery, durability, price, size, and quality. The researchers utilized two decision variables, namely, whether a product is sold or not. This study provides valuable insights into optimal inventory management, identification of sales trends, and faster responsiveness to market changes. The implication is that PT Prima Niaga Indomas can leverage this predictive model to enhance operational efficiency and productivity. Keywords: Algorithm C4.5, Data Mining, Sales Prediction
SISTEM PENDUKUNG KEPUTUSAN KENAIKAN GAJI KARYAWAN MENGGUNAKAN METODE TOPSIS BERBASIS WEB Syaputra, Wendy; Harman, Rika
Computer Based Information System Journal Vol. 12 No. 2 (2024): CBIS Journal
Publisher : Universitas Putera Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33884/cbis.v12i2.9050

Abstract

This research, titled “Decision Support System for Employee Salary Increase Using the TOPSIS Method Based on Web” addresse the issues of non-transparency and subjectivity in determining employee salary increases at Bintang Moro. Fair and objective salary adjustmentsare crucial for retaining and motivating employees, as well as ensuring the company’s sustainability and growth. Decicion support system (DSS) designed in this study uses the TOPSIS method, implemented as a web based application. TOPSIS method was selected for its ability to rank alternatives based ontheir proximity to an ideal solution, ensuring objective decision making.the research involved collecting data on employee performance and salary increases over thepast three months at Bintang Moro. This data was processed using the TOPSIS method and intergrated into a web-based system developed with PHP and Mysql. Finding indicate that the TOPSIS-based DSS provides more objective and transparent recommendations for salary increases. Web-based system also facilitates management in monitoring and evaluating employee performancemore efficiently. The system implementation leads to more equtable salary decisions, fostering a positive work environment. The research contributes to the field by offering a practical solution for decision support in employee salary management. It can serve as a refrence for developing similar system in other organizarional contexrs
ANALISIS ALGORITMA C4.5 UNTUK MENENTUKAN FAKTOR PEMBELIAN SEPEDA BEKAS PADA TOKO SEPEDA BATAM Harman, Rika; Amrizal, Amrizal
Computer Based Information System Journal Vol. 9 No. 2 (2021): CBIS Journal
Publisher : Universitas Putera Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33884/cbis.v9i2.4473

Abstract

The large number of bicycle enthusiasts has made the demand for bicycles increasing, not only new bikes but also used bikes. With the sale, of course, there are also purchases of used bikes, which before buying, of course, you must know the buying factor for used bikes to be sold. However, as long as this business is running, there has never been an in-depth analysis of factors affecting the purchase of used bikes for sale or making a reference or standard regarding the factors that affect the purchase of used bikes for sale. Thus, many customers who have bought used bicycles have complained about used bikes that have been purchased after using them for some time. With this problem, the researcher wants to provide a solution to the problems faced by motorcycle shops so far, namely by analyzing the data on used bikes that will be sold using one of the methods in the datamining technique, namely the C4.5 algorithm. The following are the results of the research: a). If the bicycle wheels are bent, the bicycle will not be purchased; b). If the bicycle rims are not bent or normal and the bicycle komstir is rocking then the bicycle will not be purchased; and c). If the bicycle wheels are not bent or normal and the bike is not rocking or steady, the bicycle will be purchased.
Penerapan Algoritma Apriori Dan K-Means Untuk Analisis Pola Pembelian Pada Toko A8 Electronic & Furniture Piayu Ambarita, Tri Mey Wendelina; Harman, Rika
Computer Based Information System Journal Vol. 13 No. 1 (2025): Jurnal CBIS
Publisher : Universitas Putera Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33884/cbis.v13i1.9555

Abstract

A8 Electronic & Furniture Piayu Store faces challenges in identifying frequently purchased product combinations and arranging products for customer convenience. This research aims to analyze consumer purchasing patterns and group consumers based on their habits using the Apriori algorithm and K-Means. The Apriori algorithm identifies frequent itemsets, such as a 55% likelihood of purchasing an AC after buying a fan and a tendency to purchase a mic with a speaker. K-Means clustering, with an optimal configuration of 4 clusters (Davis-Bouldin score: 0.754), categorizes 54 items in cluster 0, 18 in cluster 1, 20 in cluster 2, and 28 in cluster 3. These insights are recommended for optimizing stock management, tailoring promotions, and improving customer service. The study demonstrates the potential of transaction data analysis to support strategic decision-making and business growth.
Co-Authors Alfannisa Annurullah Fajrin Algifanri Maulana, Algifanri Alyshen, Alyshen Ambarita, Tri Mey Wendelina Amrizal Amrizal Amrizal Amrizal Amrizal Andarwati, Alifia Putri Andini, Mayada Dwi Arnomo , Sasa Ani Arnomo, Sasa Ani Ayu Wulandari Azwanti, Nurul Calvin Darmansah Darmansah, D Darmansah, Darmansah Devina Desliana Siagian Elisa, Erlin Ellvan Reisyer, Kevin Ellvan Reisyer Evan Rosiska Fredy, Julian Handoko, Koko Harina, Harina Hendra Hendra Hendra Purnama Ika Purnama Sari kok seng, vincent kiu Lase, Hellina Ofnani Narti Eka Putria Nofriadi Nofriadi Nopriadi Nopriadi Novri Adhiatma Ong, Ricky Panjaitan, Tulus Bobi Saen Evansen Pardede, Grace Theresia Rahmat Fauzi Reisyer, Kevin Ellvan Rosiska, Evan Sarah Astiti S.Kom., M.MT Sepentia, Nirpan Sigalingging, Iska Heriyati Simanjutak, Pastima Syahril Effendi Syaputra, Wendy Telutci, Telutci Tri Driano, Welly Tukino, Tukino tukino, tukino Vilona Fitri Alfionita ZAHARA, MUTHIA Zai, Onesimo Zetli, Sri