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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 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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Information System Analysis of Priority Data Mining Members Cards Using the K-Means Algoritma in Ramayana Panbil : Analisis Data Mining Penentuan Prioritas Penggunaan Member Card Menggunakan Algoritma K-Means Pada Ramayana Panbil Holman Tua, Arnol; Elisa, Erlin
International Journal of Technology Vocational Education and Training Vol. 1 No. 1 (2020): IJTVET Vol.1 No.1 (2020)
Publisher : Perkumpulan Doktor Indonesia Maju (PDIM)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46643/ijtvet.v1i1.16

Abstract

Data mining is a technology that has been developing for quite a long time. To run a company business, data mining is needed using existing databases. This research uses data mining using clustering methods to get new knowledge that is useful for the company. Members card user transaction data is very useful for company management to increase sales, for example in determining the determination criteria of priority member card users. The algorithm used is K-Means Clustering, which is the process of grouping a number of data or objects into clusters. Testing is done with the Rapid Miner Studio 9.6 application. produce clusters of priority grouping of data using member cards
Data Mining Analysis Using Bayes Method to Measure Damage Rate of Motor Engines: Analisa Data Mining Menggunakan Metode Bayes Untuk Mengukur Tingkat Kerusakan Mesin Motor Febry irianti Simanjuntak, Sheryl; Elisa, Erlin
International Journal of Technology Vocational Education and Training Vol. 1 No. 1 (2020): IJTVET Vol.1 No.1 (2020)
Publisher : Perkumpulan Doktor Indonesia Maju (PDIM)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46643/ijtvet.v1i1.33

Abstract

Workshop is a business that is engaged in the automotive business such as a medium-sized business down the workshop providing complete motorcycle spare parts, not only that the workshop in general also serves motorcycle service and accepts light and heavy service for all types of motorcycle brands. Hendri Motor is one of the workshops in Piayu which already has many customers who receive motorcycle service every month in Batam City. The level of motor damage that can be categorized as motor damage is mild damage, moderate damage, or severe damage because most users prefer to change oil once a month, in fact there are also those who have passed the specified time period to replace oil, for example it can be up to 2 months to 5 the month does not replace new oil. Analysis is needed to see the pattern of consumer data so that it can produce motor service probabilities that will later be useful for categorizing in light or heavy service. From so much consumer data, Data Mining is performed using the Naïve Bayes. The results of this mining activity are expected to provide a decision to see the prediction patterns of motor service consumer behavior
Analisa dan Penerapan Algoritma C4.5 Dalam Data Mining Untuk Mengidentifikasi Faktor-Faktor Penyebab Kecelakaan Kerja Kontruksi PT.Arupadhatu Adisesanti elisa, erlin
JOIN (Jurnal Online Informatika) Vol 2 No 1 (2017)
Publisher : Department of Informatics, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/join.v2i1.71

Abstract

Kecelakaan merupakan suatu kejadian yang tidak terencana begitupun pada sebuah proyek konstruksi dimana kecelakaan sering terjadi hal ini disebabkan oleh berbagai faktor. Kita lihat pada  Industri jasa konstruksi yang merupakan salah satu sektor industri yang memiliki risiko kecelakaan kerja yang cukup tinggi. Banyaknya kecelakaan kerja yang terjadi tidak terlepas dari faktor Human Error, tentunya berdampak pada kinerja dan pekerjaan yang dilaksanakan, Metode yang digunakan dalam analisis ini adalah Algoritma C4.5 yang merupakan salah satu algoritma modern untuk melakukan Data Mining, Algoritma C4.5 disebut juga dengan pohon keputusan (decision tree) yaitu merupakan salah satu metode klasifikasi yang menggunakan representasi struktur pohon, dan pada setiap node merepresentasikan atribut,cabangnya merepresentasikan nilai dari atribut, dan daun merepresentasikan kelas, Konsep dari pohon keputusan ini adalah dengan mengumpulkan data selanjutnya dibuatkan decision tree yang kemudian akan dihasilkan rule-rule solusi permasalahan. dari hasil penelitian faktor-faktor yang menjadi penyebab terjadinya kecelakaan kerja kontrusksi yang sering terjadi adalah Lingkungan Tempat Kerja, Rambu-Rambu Keselamatan dan Pekerja dan Cara kerja.
Digital Marketing Dalam Kewirausahaan Pada Masa Pandemi Covid 19 Simanjuntak, Pastima; Handoko, Koko; Elisa, Erlin; Eko Suharyanto, Cosmas
Jurdimas (Jurnal Pengabdian Kepada Masyarakat) Royal Vol. 6 No. 4 (2023): Oktober 2023
Publisher : STMIK Royal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33330/jurdimas.v6i4.2092

Abstract

Abstract: Because of the presence of the 4.0 Industrial Revolution, digital technology and the internet have become the backbone of technology, one of which is social media. Different types of popular social media, such as Twitter, Facebook, and instagram, serve different functions and serve different purposes. The Marketplace is a social media platform that has many advantages when used properly. Traders can sell their goods online on the marketplace by providing clear photos and descriptions. Furthermore, the payment method is made on the marketplace, on average, after the goods arrive, they pay or many call it COD (cash on delivery). Everything has changed, however, as a result of the Covid 19 pandemic. The government's health protocol restrictions have resulted in a decrease in income. The purpose of this service is to provide guidance to the Hang Nadim Batam School. The method used is by conducting a survey, then training and finally an evaluation. The results of this service showed that 80% of students could understand digital marketing technology          Keywords: digital marketing; entrepreneurship; social media; pandemic covid  Abstrak: Dengan hadirnya Revolusi Industri 4.0, teknologi digital dan internet menjadi tulang punggung teknologi, salah satunya media sosial. Berbagai jenis media sosial populer, seperti Twitter, Facebook, dan instagram, memiliki fungsi dan tujuan yang berbeda. Marketplace adalah platform media sosial yang memiliki banyak keuntungan jika digunakan dengan benar. Pedagang dapat menjual barangnya secara online di marketplace dengan memberikan foto dan deskripsi yang jelas. Selain itu metode pembayaran yang dilakukan di marketplace rata-rata setelah barang sampai mereka membayar atau banyak yang menyebutnya COD (cash on delivery). Namun, semuanya berubah akibat pandemi Covid-19. Pembatasan protokol kesehatan yang dilakukan pemerintah berdampak pada penurunan pendapatan. Tujuan pengabdian ini adalah untuk memberikan pembinaan pada Sekolah Hang Nadim Batam. Metode yang dilakukan dengan melakukan survey selanjutnya pelatihan dan terakhir evaluasi. Hasil dari pengbadian ini didapat bahwa siswa-siswa 80% bisa mengerti dengan teknologi digital marketing. Kata kunci: digital marketing; kewirausahaan; media sosial; pandemi covid
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).
Algoritma FP-Growth untuk Menganalisa Frekuensi Pembelian Gas Elpiji 3 Kg Elisa, Erlin; Azwanti, Nurul
INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi Vol 3 No 1 (2019): Vol. 3 No. 1 Februari 2019
Publisher : Universitas Nusantara PGRI Kediri

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (362.081 KB) | DOI: 10.29407/intensif.v3i1.12652

Abstract

The use of gas in Indonesia is a more profitable alternative, one of which is the oil conversion program, LPG (liquefied petroleum gas). UD.Maju Bersama, which is a distribution agent for 3 Kg LPG gas for household needs, so far because of the many requests, of course LPG agents like this need to forecast the frequency of purchases to find out if the sales have been sold as optimally as possible and stocks can be provided well and supplies adequate for consumer demand. this problem can be solved by applying one of the Datamining techniques which is using the FP-Growth Algorithm method to find out the Frequency of Purchase of 3 Kg LPG Gas. Frequent Pattern Growth (FP-Growth) can be used to determine the set of data that most often appears (frequent itemset) in a data set. The results of data processing purchases at the Elpiji UD base. Forward Together the most sold or purchased values ​​at week 1 and 2 on each month with the highest value support 66.67% confidence 100.00%. the results can help base owners to make decisions on gas supply so that they can be used to increase the amount of supply from distributors to agents and increase profits with support and confidence.
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 Budi Santoso Butar Butar, Masro Shausi 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 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 Wilianti, Livia Yvonne Wangdra Zetli, Sri Zetly, Sri