Article Per Year (5 Year)
p-Index From 2021 - 2026
11.219
P-Index
This Author published in this journals
All Journal EDUNOMIC : JURNAL ILMIAH PENDIDIKAN EKONOMI FAKULTAS KEGURUAN DAN ILMU PENDIDIKAN Jurnal Informatika dan Teknik Elektro Terapan Infotech Journal InfoTekJar : Jurnal Nasional Informatika dan Teknologi Jaringan Jurnal Teknik Komputer AMIK BSI Bina Insani ICT Journal Informatics for Educators and Professional : Journal of Informatics IndoMath: Indonesia Mathematics Education JITK (Jurnal Ilmu Pengetahuan dan Komputer) KOPERTIP: Jurnal Ilmiah Manajemen Informatika dan Komputer JURNAL TEKNOLOGI DAN OPEN SOURCE JURIKOM (Jurnal Riset Komputer) Jurnal ICT : Information Communication & Technology Building of Informatics, Technology and Science Infotekmesin JATI (Jurnal Mahasiswa Teknik Informatika) Respati Media Informatika Journal of Computer System and Informatics (JoSYC) Jurnal Sains Teknologi Transportasi Maritim Jurnal Sistem Komputer dan Informatika (JSON) Madani : Indonesian Journal of Civil Society MEANS (Media Informasi Analisa dan Sistem) Jurnal Teknologi Informasi dan Komunikasi Innovation in Research of Informatics (INNOVATICS) Jurnal Teknik Informatika (JUTIF) Jurnal Digit : Digital of Information Technology Mosharafa: Jurnal Pendidikan Matematika JUSTIN (Jurnal Sistem dan Teknologi Informasi) Jupiter Journal of Computer & Information Technology Journal of Artificial Intelligence and Engineering Applications (JAIEA) Jurnal Informatika dan Teknologi Informasi BULLET : Jurnal Multidisiplin Ilmu AMMA : Jurnal Pengabdian Masyarakat Jurnal Sistem Informasi dan Manajemen Jurnal Accounting Information System (AIMS) INTERNAL (Information System Journal) Smatika Jurnal : STIKI Informatika Jurnal
Odi Nurdiawan
STMIK IKMI Cirebon
Humanities Automotive Engineering Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Nursing Social Sciences Transportation Other

Published : 101 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 101 Documents
Search

 6   7   8   9   10 
PENINGKATAN MODEL ASOSIASI TOKO IKHSAN MENGGUNAKAN ALGORITMA FP-GROWTH Hanafi, Muhammad Salman; Nurdiawan, Odi; Basysyar, Fadhil Muhammad
Jurnal Informatika dan Teknik Elektro Terapan Vol 13, No 1 (2025)
Publisher : Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jitet.v13i1.5833

Abstract

FP-Growth, Data Mining, Purchase Patterns, Marketing Strategies, Retail Store.
KLASIFIKASI PENERIMA BANTUAN SOSIAL DENGAN ALGORITMA RANDOM FOREST UNTUK PENANGANAN COVID 19 Rosid, Abdur; Nurdiawan, Odi; Dwilestari, Gifthera
JURSIMA Vol 10 No 2 (2022): Jursima Vol. 10 No. 2, Agustus Tahun 2022
Publisher : INSTITUT TEKNOLOGI DAN BISNIS INDOBARU NASIONAL

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47024/js.v10i2.398

Abstract

The Covid 19 outbreak has an impact on the community so that there are family heads who cannot work in general. The policy pursued by the central government is to provide assistance to workers who have salaries below 5 million and other programs. The obstacles faced to the community are not exactly recipients of assistance in accordance with the criteria set by the government. The criteria set by the government are workers who have salaries below 5 million. The purpose of the study can model the recipients of social assistance that is on target, so that the assistance can be useful in the time of the Covid 19 pandemic. This method of approaching research uses knowladge data discovery with the first stage of data obtained by social services in 2020 the second stage of data classification based on the riteri that has been established. The third stage of preprocessing is used to clean up noise data, stage four of the random forest model by using rapid miner tool version 9.9. Stage six discussion of the results of the model produced from random forest. The results expected in the study get a good model so that it becomes a recommendation in determining the recipients of sosial assistance
IMPLEMENTASI ALGORITMA FP-GROWTH UNTUK MENUNJANG KEPUTUSAN PERSEDIAN BARANG DI CV INDOTECH JAYA SENTOSA KOTA CIREBON Nurrohmat, Iman; Nurdiawan, Odi; Bahtiar, Agus
JURSIMA Vol 10 No 2 (2022): Jursima Vol. 10 No. 2, Agustus Tahun 2022
Publisher : INSTITUT TEKNOLOGI DAN BISNIS INDOBARU NASIONAL

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47024/js.v10i2.421

Abstract

Indotech Jaya Sentosa is a company engaged in trading in the form of computers and network infrastructure. Currently experiencing problems in managing inventory for its customers. These obstacles include the frequent occurrence of overcapacity in storage warehouses that exceeds the number of requests, even more so in the era of the Covid-19 pandemic. This study aims to provide a solution to the problems at CV Jaya Sentosa, namely by applying a technique or algorithm to support decisions in managing its merchandise inventory. The approach taken is to use a data mining approach involving the FP-Growth algorithm method. FP-Growth Algorithm is a method to find the pattern of relationship between one or more items in a dataset. While the steps taken to the data mining approach include business understanding, data understanding, data preparation, data modeling, data evaluation and deployment. The final result of this research is expected to be able to apply association rules where these rules can be used as a reference in predicting what kind of inventory should be held to facilitate inventory management.
PENERAPAN MACHINE LEARNING UNTUK MENENTUKAN KELAYAKAN KREDIT MENGGUNAKAN METODE SUPPORT VEKTOR MACHINE Syafi'i, Syafi'i; Nurdiawan, Odi; Dwilestari, Gifthera
JURSIMA Vol 10 No 2 (2022): Jursima Vol. 10 No. 2, Agustus Tahun 2022
Publisher : INSTITUT TEKNOLOGI DAN BISNIS INDOBARU NASIONAL

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47024/js.v10i2.422

Abstract

Credit is one of the services provided by banks, credit risk that occurs in the provision of credit loans, in the case that the customer is unable to pay the loan received is always considered by the bank, and supervises the customer to reduce risk. The main risk for banks and financial institutions is to differentiate creditors who have the potential for bad loans, this crisis is a concern for financial institutions about credit risk. SUPPORT VEKTOR MACHINE algorithm is an algorithm used to form a decision tree. The decision tree is a very powerful and well-known classification and prediction method. The richer the information or knowledge contained by the training data, the accuracy of the decision tree will increase. The SUPPORT VEKTOR MACHINE algorithm classification method can determine the credit worthiness of the national civil capital capitals as evidenced by the performance table data consisting of the AUC results, Acuracy results. The results of the application of machine learning using the vector machine support algorithm against cooperative data in KPRI "RUKUN" SMKN 1 Lemahabang to determine creditworthiness based on the results of the Performance Vector from the Support Vector Machine algorithm resulted in smooth prediction, smooth true 130, prediction of jammed, true jam 72, current prediction true jam 41, prediction of jammed true jam 332. The accuracy rate of the performance vector of the support vector algorithm is 80.34%. .
RANCANG BANGUN SISTEM INFORMASI PENDATAAN INVENTARIS BERBASIS WEB PADA SERVER PT JASA MARGA (PERSERO) TBK. CABANG PALIKANCI abdullah, nur syarief; Dikananda, Arif Rinaldi; Anwar, Saeful; Nurdiawan, Odi
JURSIMA Vol 10 No 3 (2022): Jursima Vol.10 No.3
Publisher : INSTITUT TEKNOLOGI DAN BISNIS INDOBARU NASIONAL

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47024/js.v10i3.464

Abstract

PT Jasa Marga (Persero) Tbk. The Palikanci branch is a toll gate support company, but computer Inventory Data Collection which includes servers and is still considered manual data collection so that it consumes a lot of paper and is very vulnerable to being lost and takes a lot of time to collect lost or torn data. To emphasize and learn in understanding the problems as described, the formulation of the problem that researchers can explain is to design a computerized information system for data collection of Jasa Marga's server inventory, create a database for data collection of server inventory items for managers to carry out their work. The purpose of the research is to find out, develop and create an ongoing asset collection application system into the PHP and HTML programming language using the MySQL database. So that researchers can draw conclusions in processing inventory data collection server by implementing applications that have been designed and built in a systematic and structured manner, so that the level of damage in the process of carrying out data collection for seafarers can be resolved.
ANALISA PEMBELIAN SEPEDA MENGGUNAKAN ALGORITMA APRIORI PADA TOKO SEPEDA BRADEN BIKE Rizki, Dicky Miftakhul; Nurdiawan, Odi; Anwar, Saeful
JURSIMA Vol 10 No 3 (2022): Jursima Vol.10 No.3
Publisher : INSTITUT TEKNOLOGI DAN BISNIS INDOBARU NASIONAL

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47024/js.v10i3.465

Abstract

The store is a place for trading activities that provide all daily necessities with a special type of goods. Braden Bike Shop is a store that sells a variety of bicycle products and accessories, but the data collection of sales transactions for goods that have been sold is usually written on sheets of paper and collected paper that has been sold and rewrites items that have been sold manually to new paper to record sales reports every month with the current system, The purpose of this study is to find the rules of the combination of items by looking at the relationships of two or more variables, The method used is the A priori Algorithm Method in data mining techniques, namely the association rule or association rule used using a minimum support of 10% and a minimum of confidence of 50%, The results obtained are 12 rules 2 itemsets and 2 rules 3 itemssets following sales for 1 year using a priori algorithms, namely categories Aviator_GN, Exotic_GN, Interbike_GN, Fastron_GN, Polygon_GN, Seat Covers, Anti-Slip_AS Grips and Bell_AS. Results obtained based on manual calculations and using Rapid Miner software have results above the minimum support of 10%and confidence of 50%.
RANCANG BANGUN SISTEM INFORMASI PERSEDIAAN BARANG BERBASIS WEB PADA PT PARAGON FURNITAMA INDUSTRY Dikananda, Arif Rinaldi; Yunus, Shofian; Anwar, Saeful; Nurdiawan, Odi
JURSIMA Vol 10 No 3 (2022): Jursima Vol.10 No.3
Publisher : INSTITUT TEKNOLOGI DAN BISNIS INDOBARU NASIONAL

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47024/js.v10i3.474

Abstract

PT. Paragon Furnitama Industry is one of the companies engaged in the production of fabric and leather sofas, back seats, and chair cushions, at this time the inventory process is still done manually because it still uses records in books and Microsoft Excel, the process sometimes finds several problems including data redundancy, discrepancies in stock of goods with records, and providing long reports because data validation is needed first. So that the information received by the parties concerned is very difficult to obtain quickly. To emphasize and study the problems as described, the problem formulation that researchers can explain is to design an inventory information system so that the company's performance is getting better. The Design and Build of this Goods Inventory Information System is built based on a website. The design of the information system uses the Software Development Life Cycle (SDLC) with the waterfall method so that this design system is expected to improve performance and performance, especially those related to processing inventory data to making inventory reports at PT. Paragon Furnitama Industry.
Irvan Himawan PREDIKSI HARGA SAHAM DENGAN ALGORITMA REGRESI LINIER DENGAN RAPIDMINER Himawan, Irvan; Nurdiawan, Odi; Dwilestari, Gifthera
JURSIMA Vol 10 No 3 (2022): Jursima Vol.10 No.3
Publisher : INSTITUT TEKNOLOGI DAN BISNIS INDOBARU NASIONAL

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47024/js.v10i3.475

Abstract

Stock investment in the capital market is very important for every company in the world. Stock prices in the capital market move very randomly, the highs and lows of stock prices are influenced by many factors. Therefore, it is necessary to predict the stock price so that it can help investors to see investment prospects in the future. In this study, the prediction of the stock price of BRI Bank with the BBRI stock code will be carried out, using an algorithm, namely Linear Regression on rapid miners. This Linear Regression Algorithm is the best algorithm to use because it is the most complex compared to other algorithms. Based on signaling theory, which are information signals needed by investors, the value of forecasting results that have been obtained can be used to consider investors' decisions that the stock has high or low risk in the future. Based on the theory of risk, this forecasting analysis helps investors to minimize losses. Stock prediction is one of the technical analysis. Stock buying and selling transactions without technicalities are gambling behavior and contain gharar or ambiguity. The impact of not using this technical analysis clearly resulted in transactions containing maisir and gharar which were clearly prohibited. The historical stock data used in the test was obtained from the finance.yahoo.com web page with the category PT. Bank Rakyat Indonesia Tbk, or with the issuer code BBRI shares. What will be used is annual data for the last 5 years in the form of time series accompanied by open, high, low and volume variables as independent variables and close as dependent variables. The algorithm used is multiple linear regression.
Model Sentimen Analisis Berdasarkan Ulasan Aplikasi Webtoon pada Google Play Store Ditingkatkan dengan Algoritma Random Forest Deasiva, Imanda; Nurdiawan, Odi; Basysyar, Muhammad Fadhil
Media Informatika Vol 24 No 1 (2025)
Publisher : P3M STMIK LIKMI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37595/mediainfo.v24i1.319

Abstract

Penelitian ini bertujuan untuk meningkatkan model analisis sentimen berdasarkan ulasan aplikasi Webtoon di Google Play Store dengan algoritma Random Forest. Data ulasan dikumpulkan melalui metode web scraping, mencakup teks ulasan, skor, dan tanggal. Proses praproses teks dilakukan, termasuk penghapusan stopwords, tokenisasi, stemming, dan normalisasi untuk menghasilkan data bersih dan terstruktur. Teknik TF-IDF digunakan untuk ekstraksi fitur, mengubah teks menjadi representasi numerik yang relevan bagi algoritma pembelajaran mesin.Random Forest dipilih karena kemampuannya menangani data kompleks dan mengurangi overfitting melalui pendekatan ensemble. Algoritma ini membangun beberapa pohon keputusan yang bekerja secara kolektif untuk memprediksi sentimen ulasan. Model dilatih dan diuji pada data yang telah dibagi, menghasilkan akurasi sebesar 67,5%. Evaluasi lebih lanjut menunjukkan bahwa Random Forest memberikan performa yang baik pada metrik precision, recall, dan F1-score, terutama dalam menangani keragaman bahasa informal pada ulasan pengguna.Hasil penelitian menunjukkan bahwa Random Forest mampu meningkatkan akurasi analisis sentimen dibandingkan model baseline seperti Naïve Bayes dan SVM. Penelitian ini memberikan kontribusi signifikan dalam memahami persepsi pengguna aplikasi Webtoon, membantu pengembang untuk meningkatkan layanan berdasarkan analisis sentimen yang lebih akurat. Selain itu, penelitian ini mendemonstrasikan potensi penerapan Random Forest dalam analisis data teks di platform digital dengan volume data besar.
ANALISIS FAKOR-FAKTOR YANG MEMPENGARUHI EFISIENSI BAHAN BAKAR KENDARAAN MENGGUNAKAN TEKNIK DATA MINING Musliyadi, Mar'i; Nurdiawan, Odi; Dwilestari, Gifthera
JATI (Jurnal Mahasiswa Teknik Informatika) Vol. 9 No. 2 (2025): JATI Vol. 9 No. 2
Publisher : Institut Teknologi Nasional Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36040/jati.v9i2.13048

Abstract

Efisiensi bahan bakar kendaraan menjadi isu penting dalam upaya global untuk mengurangi konsumsi energi dan emisi karbon, yang berkontribusi terhadap perubahan iklim dan polusi udara. Meningkatnya jumlah kendaraan bermotor dan meningkatnya permintaan terhadap bahan bakar fosil menambah urgensi untuk meningkatkan efisiensi bahan bakar guna mengurangi dampak lingkungan. Penelitian ini bertujuan untuk menganalisis faktor-faktor yang memengaruhi efisiensi bahan bakar kendaraan dengan menggunakan teknik data mining. Dataset yang digunakan mencakup variabel seperti jenis kendaraan, ukuran mesin, berat kendaraan, kecepatan rata-rata, serta kondisi jalan dan cuaca. Penelitian ini mengadopsi algoritma Naïve Bayes untuk mengidentifikasi faktor-faktor yang berpengaruh terhadap efisiensi bahan bakar, dengan teknik cross-validation yang memastikan akurasi hasil model. Hasil penelitian menunjukkan bahwa faktor utama yang memengaruhi efisiensi bahan bakar adalah jenis kendaraan, ukuran mesin, dan kecepatan rata-rata, dengan kecepatan optimal pada rentang 50-70 km/jam untuk efisiensi bahan bakar maksimal. Selain itu, kondisi jalan dan suhu lingkungan juga memiliki pengaruh signifikan, meskipun efeknya bervariasi tergantung pada jenis kendaraan. Model prediktif yang dihasilkan memiliki tingkat akurasi sebesar 99,64%, menunjukkan kemampuan yang sangat baik dalam memprediksi konsumsi bahan bakar berdasarkan variabel input yang diberikan. Penelitian ini mengindikasikan bahwa efisiensi bahan bakar dapat ditingkatkan melalui desain kendaraan yang lebih optimal, seperti pengurangan berat kendaraan dan peningkatan efisiensi mesin. Tantangan yang dihadapi dalam penelitian ini mencakup variabilitas faktor eksternal, seperti data cuaca yang tidak konsisten, dan solusi yang diusulkan melibatkan metode pengumpulan data yang lebih komprehensif untuk memperoleh hasil yang lebih akurat. Hasil penelitian ini dapat digunakan sebagai dasar untuk pengembangan strategi penghematan energi, desain kendaraan yang lebih efisien, serta sebagai referensi bagi penelitian lanjutan untuk mengurangi konsumsi bahan bakar dan emisi karbon.
Co-Authors Abdul Rauf Chaerudin Abdul Robi Padri abdullah, nur syarief Ade Irma Purnamasari Ade Irma Purnamasari Ade Irma Purnamasari Ade Kurnia, Dian Ade Rizki Rinaldi Adisty Tri Putra Agis Maulana Robani Agung Nugraha Agus Surip Ahmad Faqih Ahmad Faqih Ahmad Faqih Ahmad Faqih Ahmad Zam Zami Aini, NoviFirda Ainnur Rahman, Rizal Amar, Mohammad Rosihin Amarda, Juan Amri, Hajijin Ananda Rafly Andi Setiawan Andi Setiawan Anwar Musaddad Aria Pratama Arif Fitriyanto, Goffar Arif Rinaldi Dikananda Asyraful Hijrah, Ahmad baihaqqi, Farisky Bambang Irawan Basysyar, Fadhil Muhammad Basysyar, Muhammad Fadhil Cep Lukman Rohmat Cep Lukman Rohmat Cep Lukman Rohmat Dadang Sudrajat Deasiva, Imanda Dewanty Rafu, Maria Dias Bayu Saputra Dikananda, Arif Rinaldi Dilla Eka Lusiana Diniarti, Indah Dita Rizki Amalia Dodi Solihudin Dwi Teguh Afandi Edi Tohidi Edi Wahyudin Eko Wiyandi ETI KURNIAWATI Ezar Qotrunnada Fadhil M. Basysyar Fadrin Helmi FANDI ACHMAD Fathurrohman, Fathurrohman Faturrohman, Faturrohman Fauzi Fauzi Febriansyah, Feggy Fidya Arie Pratama Fidya Arie Pratama Firmansyah Firmansyah Fitriyani, Nur Sifa Gifthera Dwilestari Haidar Fakhri Hanafi, Muhammad Salman Hayati, Umi Heliyanti Susana Herdiana, Ruli Herdiana, Rully Heriyawan, Ikhsan Himawan, Irvan Hira Wahyuni Azizah Ibnu Ubaedila Irfan Ali Irfan Ali Irfan Ali, Irfan Irma Purnamasari, Ade Irvandi Irvandi IRVANDI, IRVANDI Jaelani Sidik Jamalul'ain, Abdul Jayawarsa, A.A. Ketut Julia Eka Yanti Juliadi, Diky Karlina, Lita Kaslani Khamim Surya Hadi Kusuma Al Atros Khoirul Insan, Moh Khoirul Kurnia, Dian Ade Kurniawan Fajar Abdulloh Laturrizqi, Washi Lukmanul Hakim M. Basyisyar, Fadhil M. Iqbal Fadhilah, Aji Mamluah, Karimatul Mariyani, Dinda Martanto . Mauludin, Muhammad Rifqi Medina Aprilia Putri Melia Melia Melia Melia Melisa Hikari Mia Fijriani Muchamad Sobri Sungkar, Muchamad Sobri Muhalim, Alvy Mulyana Mulyana Mulyawan Mulyawan Musliyadi, Mar'i Nana Suarna Nana Suarna Nana Suarna Nanda Permatasari Nining Rahaningsih Nining Rahaninsih Noval Salim Nur Atikah Nurcholis, Rifki Nurdiawan, Rudi Nurhadiansyah Nurhadiansyah Nurhadiansyah, Nurhadiansyah Nurhakim, Bani Nurrohmat, Iman Pratama, Denni Pratama, Fidya Arie Pratama, Irfan Pratiwi, Fitriyani Prihartono, Willy Purnamasari, Ade Irma Putra, Aris Pratama Putri, Haidah R, Nining Riansah, Adam Rinaldi Dikananda, Arif Rinaldi Dikanda, Arif Riyan Suryatana Riyan, Ade Bani Rizki Rinaldi, Ade Rizki, Dicky Miftakhul Rohmat, Cep Lukman Rokhmatan Khaerullah, Rizal Rudi Hartono Rudi Kurniawan Rudi Kurniawan Ruli Herdiana Ruli Herdiana Rully Pramudita Saeful Anwar Saeful Anwar Saeful Anwar, Saeful Saepul Hadi Salsa Billa Agistina Seputra, Nenda Alfadil Suarna, Nana Subandi, Husein Suripno Susana, Heliyanti Syafi'i, Syafi'i Tati Suprapti Taufik Hidayat Tengku Riza Zarzani N Tio Prasetiya Tio Prasetya TOMAS TOMAS Topan Hadi Tuti Hartati Tuti Hartati Wiyandi, Eko Yudhistira Arie Wijaya Yunus, Shofian Zeya Sebastian, Muhammad