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All Journal KLIK (Kumpulan jurnaL Ilmu Komputer) (e-Journal) InfoTekJar : Jurnal Nasional Informatika dan Teknologi Jaringan JOIN (Jurnal Online Informatika) Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi Jurnal Pengabdian Pada Masyarakat Rang Teknik Journal JURNAL ILMIAH INFORMATIKA Journal Information System Development Jurnal Teknik Informatika UNIKA Santo Thomas Computer Based Information System Journal Jurdimas (Jurnal Pengabdian Kepada Masyarakat) Royal Jurnal Informasi dan Komputer Building of Informatics, Technology and Science Jurnal Manajemen Informatika dan Sistem Informasi Jurnal Tekinkom (Teknik Informasi dan Komputer) JPMB: Jurnal Pemberdayaan Masyarakat Berkarakter Jurnal Teknik Informatika Unika Santo Thomas (JTIUST) Jurnal Puan Indonesia Jurnal Sains Informatika Terapan (JSIT) Jurnal PADI (Pengabdian mAsyarakat Dosen Indonesia) Jurnal Pengabdian Ibnu Sina Jurnal Pengabdian Barelang JPMTT (Jurnal Pengabdian Masyarakat Teknologi Terbarukan) International Journal of Technology Vocational Education and Training (IJTVET) Computer & Science Industrial Engineering Journal Prosiding Seminar Nasional Ilmu Sosial dan Teknologi (SNISTEK)
Elisa, Erlin
Universitas Putra Batam
Religion Agriculture, Biological Sciences & Forestry Humanities Biochemistry, Genetics & Molecular Biology Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering 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

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IMPLEMENTASI FRAMEWORK NODE.JS PADA SISTEM INFORMASI KESEHATAN IBU HAMIL DI KOTA BATAM Jeni, Jeni Chrisna Sitanggang; Elisa, Erlin
Computer Science and Industrial Engineering Vol 11 No 1 (2024): Comasie
Publisher : LPPM Universitas Putera Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33884/comasiejournal.v11i1.8972

Abstract

The world of technology is developing rapidly, which greatly influences humans to use the convenience provided by the use of technological facilities. In the context of health services, information systems function as the center of health development and are responsible for encouraging, providing, and delivering services. Pregnancy that lasts 9 months requires many examinations to determine the health of the fetus. However, consultations with doctors are sometimes lacking in conveying accurate and precise information due to the large number of patients. Not infrequently, predetermined schedules are often postponed or cancelled. Therefore the aim of this research is To design a Health Information System for Pregnant Women in Batam City using Unified Modeling Language (UML). With the Agile method and using JavaScript and Node.Js
ANALISIS KLASIFIKASI ALGORITMA C.45 DALAM MEMPREDIKSI TINGKAT PENJUALAN PERLENGKAPAN IBADAH Novrianto; Elisa, Erlin
Computer Science and Industrial Engineering Vol 11 No 1 (2024): Comasie
Publisher : LPPM Universitas Putera Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33884/comasiejournal.v11i1.8987

Abstract

This research was conducted at a shop that sells goods or equipment for Buddhist worship called the Sinar Mas Indah shop. The Sinar Mas Indah shop operates every day except major holidays such as Chinese New Year. So far, the Sinar Mas Indah store has never used sales transaction data for analysis for the benefit of future business progress, sales transaction data is only stored in archive form, if it is old and feels no longer needed, it will simply be thrown away. , if used to predict future sales then decisions to increase sales in the future can be easily achieved. This research utilized datamining techniques with the C4.5 algorithm by testing the results using Weka software, from the 5 variables tested, category, brand, quantity, quality and price with a total of 160 test data. After calculating the entropy and gain values, the highest gain value was obtained. making consideration of consumer purchasing factors, namely Price, Quality, Quantity and category, into the main factors in decision making and there are results for Correctly Classified Instances 109 Data with a percentage value of 68.125% then for Incorrectly Classified Instances 51 data with a percentage value of 31.875%.
PENERAPAN METODE PROFILE MATCHING UNTUK PENENTUAN SEPEDA MOTOR HONDA MATIC TERBAIK BERDASARKAN PREFERENSI KONSUMEN Budi Santoso; Erlin Elisa
Computer Science and Industrial Engineering Vol 12 No 1 (2025): Comasi Vol 12 No 1
Publisher : LPPM Universitas Putera Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33884/comasiejournal.v12i1.9549

Abstract

Motorbikes are currently a very popular means of transportation as vehicles for various daily activities. So far, consumers only buy through recommendations from local people when buying motorbikes. This causes many consumers to lack knowledge about the motorbike specifications that are most suitable for each consumer's needs. So we need an approach that can help consumers determine the motorbike that best suits their needs based on assessing aspects of consumers who have been using it for a long time. In this research, the calculation method used is profile matching. For this research, an assessment analysis was carried out on 6 types of Honda motorbikes based on aspects of design, comfort, performance, features, fuel efficiency, price balance and the need for user experience, aesthetic appearance and price match with complete features. For the results of the analysis using the profile matching method, the score with the highest ranking was the Honda Scoopy which received the highest score in all aspects and for various needs such as user experience, aesthetic appearance, and price match with complete features. The Honda PCX and Vario are ranked second and third and could also be the second choice because they have an insignificant difference in value with the Honda Scoopy. Furthermore, Honda PCX, Genio and Beat can also be choices if adjusted to individual needs.
METODE PROFILE MATCHING SEBAGAI PENUNJANG KEPUTUSAN PEMBERIAN KREDIT PADA CV BUANA MOTOR Hendry; Erlin Elisa
Computer Science and Industrial Engineering Vol 13 No 1 (2025): Comasie Vol 13 No 1
Publisher : LPPM Universitas Putera Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33884/comasiejournal.v13i1.10272

Abstract

The credit approval process at CV. Buana Motor has traditionally been carried out manually and subjectively, which can lead to inaccuracies in decision-making. To address this issue, a decision support system is needed to assist in assessing the eligibility of prospective debtors more objectively. This study aims to apply the profile matching method as a tool to determine credit eligibility based on several predefined criteria, including income, installment amount, installment duration, type of employment, home ownership status, and length of residence. The first three criteria are classified as core factors, while the remaining three are considered secondary factors. This study uses data from 340 customers as samples. The results show that 273 customers (approximately 80.29%) were classified as eligible for credit, while 67 customers (19.71%) were deemed ineligible. These findings indicate that the profile matching method can provide systematic and objective assessment results and effectively support the credit decision-making process at CV. Buana Motor.
KLASIFIKASI OPINI PENONTON FILM PADA PLATFORM STREAMING VIDEO DENGAN ALGORITMA NAIVE BAYES Alita Tiffana; Elisa, Erlin
Computer Science and Industrial Engineering Vol 13 No 2 (2025): Comasie Vol 13 No 2
Publisher : LPPM Universitas Putera Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33884/comasiejournal.v13i2.10328

Abstract

Video streaming platforms have become an essential component of contemporary society since they offer flexible access to entertainment. However, opinions about these programs are still divided, with some members of the public being more supportive than others. This study aims to categorize viewer attitudes toward video streaming services, specifically Netflix and Disney+, into three groups: good, negative, and neutral. The strategy used is the Naïve Bayes Algorithm, and web scraping techniques are used to collect user comment data from the Google Play Store. Preprocessing, data labeling, classification, and model evaluation using metrics like accuracy, precision, recall, and F1 score are all part of the analytical process.The results of the investigation showed that the Gaussian Naïve Bayes generated an accuracy of 43.52% for Disney+ and 41.99% for Netflix. This study shows that automated public opinion analysis is initially feasible, despite its current low degree of accuracy. Disney+ technically does better in classification, while Netflix gets more favorable reviews based on user assessments based on ratings. It is hoped that this research will provide the basis for more accurate opinion analysis instruments in the future.
PENERAPAN METODE PROFILE MATCHING DALAM PEMILIHAN PRODUK PELEMBAB SOMETHINC UNTUK KONDISI KULIT NORMAL TO OILY Wilianti, Livia; Elisa, Erlin
Computer Science and Industrial Engineering Vol 13 No 3 (2025): Comasie Vol 13 No 3
Publisher : LPPM Universitas Putera Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33884/comasiejournal.v13i3.10449

Abstract

This study addresses the core issue of consumers experiencing difficulties in selecting suitable moisturizer products for normal to oily skin, amidst the rapid growth of the skincare industry in Indonesia. The objective of this research is to calculate the gap between the ideal and actual profiles in order to identify the degree of compatibility based on predefined criteria, as well as to determine the relevant attributes involved in forming both profiles. The research employs the Profile Matching method as the primary approach to analyze the alignment between product alternatives and the ideal consumer profile. The research design includes the identification of research type, determination of population and sample, data collection procedures through online questionnaires, and data analysis methods. The findings indicate that the Profile Matching method is effective in identifying the most suitable moisturizer product from the Somethinc brand for normal to oily skin. The analysis produces a ranking of products based on the total scores calculated, assisting users in understanding product suitability, effectiveness, and usage behavior. A small or zero gap between the ideal and actual profiles signifies a high degree of compatibility, demonstrating that this method is capable of providing accurate product recommendations. The key aspects contributing to profile formation include product suitability (skin type, skin reaction, product match), usage behavior (frequency of use, awareness of skin type, intention to continue usage), and product effectiveness (variants tried, perceived improvements, and product knowledge).
PENERAPAN ALGORITMA K-MEANS UNTUK PENGELOMPOKAN PADA DATA SUPERMARKET MENGUNAKAN PEMOGRAMAN PYTHON WIBOWO, RIZKY PRASTYA; Elisa, Erlin
Computer Science and Industrial Engineering Vol 14 No 01 (2026): Comasie Vol 14 No 1
Publisher : LPPM Universitas Putera Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33884/comasiejournal.v14i01.11287

Abstract

The rapid growth of transactional data in the retail sector, particularly in supermarkets, has resulted in large and complex sales datasets that require effective analytical methods to identify meaningful sales patterns. This study applies data mining through clustering techniques by implementing the K-Means algorithm using Python to classify supermarket sales patterns and group transactions with similar characteristics. The research methodology includes data collection, preprocessing, normalization using StandardScaler, determination of the optimal number of clusters through the Elbow Method, clustering with the K-Means algorithm, and evaluation of clustering quality using the Silhouette Score, Davies–Bouldin Index, and Inertia (Within-Cluster Sum of Squares). The results indicate that from 1,000 sales transactions, three clusters were formed, consisting of 515 transactions in the low sales cluster, 314 in the medium sales cluster, and 171 in the high sales cluster. The clustering evaluation produced a Silhouette Score of 0.6055, a Davies–Bouldin Index of 0.502, and an Inertia value of 122.01, indicating that the resulting clusters are compact and well separated. These findings confirm that the K-Means algorithm is effective for grouping supermarket sales patterns and can support sales management and strategic planning.
Co-Authors Adisaputra, Winarta - Agustira, Felia alfannisa annurrallah fajrin Alfannisa Annurullah Fajrin Alfannisa Fajrin Algifanri Maulana, Algifanri Alita Tiffana Amrizal Amrizal Amrizal Andi Maslan Andrianto Andrianto Anggia Arista anto, ridy Arista, Anggia aryanto, Mhd isrok Azwanti, Nurul Boru Sitorus, Melani Krissa Delvi Br Purba, Neni Marlina Budi Santoso Butar Butar, Masro Shausi Darmansah Darmansah Darmansah, Darmansah Darmansyah , Darmansyah david Effendi, Bagus Cecep Eko Suharyanto, Cosmas Ellbert Hutabri, Ellbert Fajrin, Alfannisa fajrin, alfannisa annurrallah Febry irianti Simanjuntak, Sheryl Fernaldy, Kelvin Fransisco, Rico Fransisco Handoko, Koko Handoko, Koko Harman, Rika Hartati, Milasari Hendry . Hernandi, Gelen Betanio Holman Tua, Arnol Jeni, Jeni Chrisna Sitanggang Khe Ben KIKI VALENTINA SIANTURI Koko, Koko Handoko Larisma Nursinta Nainggolan Leonardo Lowensky, Elnas Mardiansyah, Yopy Maslan, Andi Muhammad Taufik Syastra NANDA HARRY MARDIKA Naomi, Cathrine Narti Eka Putria Nofriani Fajrah, Nofriani Nopriadi Nopriadi Novianti, Agnes Novri Adhiatma Novri Adhiatma Novri Adhiatma, Novri Novrianto NURJAYA NURJAYA, NURJAYA Nurma Dhona Handayani Rahmad Rahmat Fauzi Rahmat Fauzi Raymond Raymond Ronald Wangdra Satria, ROBBY Sijabat, Aditiya Riyanto Simanjuntak, Pastima Simanjutak , Pastima Simanjutak, Pastima Sinaga, Dewi Febryanti Sesilia Suharyanto, Cosmas Eko Suvianto Wangdra tan, Fitrini Tan, James Tanjung, Muhammad Iqbal Tipa, Handra Tri Utami, Yunita Tukino, Tukino tukino, tukino Uape, Frederikus Cyriaco Leu Le Vincent Z Viska, Indriani Yulia Wandela, Rido Sepka WIBOWO, RIZKY PRASTYA Wilianti, Livia Yvonne Wangdra Zetli, Sri Zetly, Sri