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All Journal ComEngApp : Computer Engineering and Applications Journal IJCCS (Indonesian Journal of Computing and Cybernetics Systems) JURNAL SISTEM INFORMASI BISNIS JAKPI Bulletin of Electrical Engineering and Informatics Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) Jurnal Teknologi Informasi dan Ilmu Komputer JUITA : Jurnal Informatika Jurnal Teknologi dan Sistem Komputer Jurnal ELTIKOM : Jurnal Teknik Elektro, Teknologi Informasi dan Komputer Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Jurnal Sains dan Informatika JKIE (Journal Knowledge Industrial Engineering) Jurnal Ilmiah Ecobuss Juriti Prima (Jurnal Ilmiah Teknik Industri Prima) Journal of Electronics, Electromedical Engineering, and Medical Informatics Jurnal Sistem Teknik Industri Jurnal Mnemonic Jurnal Teknik Industri Terintegrasi (JUTIN) Jurnal Teknik Informatika (JUTIF) Blend Sains Jurnal Teknik Scientific Journal of Informatics Indonesian Journal of Electronics, Electromedical Engineering, and Medical Informatics
Irwan Budiman
Fakultas MIPA, Universitas Lambung Mangkurat Banjarbaru, Kalimantan Selatan
Aerospace Engineering Agriculture, Biological Sciences & Forestry Automotive Engineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Electrical & Electronics Engineering Energy Engineering Health Professions Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mathematics Mechanical Engineering Public Health Social Sciences

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K-Modes Clustering untuk Mengetahui Jenis Masakan Daerah yang Populer pada Website Resep Online (Studi Kasus: Masakan Banjar di cookpad.com) Indriani, Fatma; Budiman, Irwan
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 4 No 4: Desember 2017
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1144.909 KB) | DOI: 10.25126/jtiik.201744548

Abstract

AbstrakPada makalah ini dipaparkan clustering pada data resep masakan daerah Banjar untuk mengetahui jenis makanan yang paling banyak di-post secara online oleh pengguna website recipe sharing. Pertama-tama data resep sebanyak 355 dikumpulkan dari suatu website resep, untuk selanjutnya dilakukan ekstraksi data bahan dan pembersihan. Metode clustering yang dipilih adalah k-modes karena cocok digunakan pada data kategorikal. Berdasar metode Elbow, jumlah cluster yang ideal adalah k=4 dan k=8. Jumlah cluster k=4 menghasilkan kelompok yang lebih umum, sedangkan k=8 menghasilkan kelompok yang lebih spesifik. Adapun kelompok yang berhasil diidentifikasi untuk k=4 adalah sayur asam, soto banjar, masakan gurih lain-lain, kue dan bubur manis. Sedangkan kelompok dengan jumlah cluster k=8 adalah sayur asam, soto banjar, kue basah, masakan gurih lain-lain, masak habang, bubur manis, kuah ketupat, dan masakan gurih asam. Evaluasi nilai purity menunjukkan nilai masing-masing 0,825 untuk k=4 dan 0,831 untuk k=8.Kata kunci: data mining, clustering, k-modes, resep masakan, bahanAbstractIn this paper, we cluster user-submitted recipes of Banjar regional cuisine to find out which type of cuisine are popular according to its ingredients. 355 recipes are collected from a recipe sharing website, then the ingredients extracted and cleaned. The clustering method chosen is k-modes because it is suitable for categorical data. Based on the Elbow method, the ideal number of clusters is k = 4 and k = 8. The number of clusters k = 4 produces more general cuisines group, whereas k = 8 produces more specific groups. The groups identified for k = 4 are (1) “sayur asam” (sour soup), (2)“soto banjar” (Banjar chicken soup), (3) savory dishes, and (4) sweet dishes. While the group with the number of clusters k = 8 consists of (1)“sayur asam” (sour soup)  (2) “soto banjar”, (3) Banjar sweet puddings, (4) various savory dishes, (5) “masak habang” (Banjar sweet chili dishes), (6) sweet porridge, (7) “kuah ketupat” (spicy coconut soup) and (8) various savory sour dishes. The purity of clusters are shown to be 0.825 for k=4 and 0.831 for k=8.Keywords: clustering, k-modes, data mining, recipe, ingredient
Kombinasi Seleksi Fitur Berbasis Filter dan Wrapper Menggunakan Naive Bayes pada Klasifikasi Penyakit Jantung Azizah, Siti Roziana; Herteno, Rudy; Farmadi, Andi; Kartini, Dwi; Budiman, Irwan
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 10 No 6: Desember 2023
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jtiik.2023107467

Abstract

Penyakit jantung menjadi salah satu penyebab utama kematian bersama dengan penyakit lainnya. Dalam bidang teknologi, data mining dapat digunakan untuk mendiagnosa suatu penyakit yang bersumber dari data rekam medis pasien. Pada klasifikasi dataset medis, Naive Bayes merupakan salah satu metode terbaik yang digunakan. Tujuan dari penelitian ini adalah untuk mengetahui perbandingan hasil akurasi dari Naive Bayes menggunakan beberapa seleksi fitur yaitu Forward Selection, Backward Elimination, kombinasi union hasil seleksi fitur Forwad Selection dan Backward Elimination, Information Gain, Gain Ratio, dan kombinasi union hasil seleksi fitur Information Gain dengan Gain Ratio. Data yang digunakan dalam penelitian ini adalah data penyakit jantung yang didapatkan dari UCI Machine Learning Repository. Dari implementasi pemodelan yang akan dilakukan menghasilkan nilai akurasi tertinggi sebesar 91.80% pada algoritma Naive Bayes dengan kombinasi union hasil seleksi fitur Information Gain dan Gain Ratio menggunakan perbandingan data latih dan data uji 80:20. Sedangkan akurasi Naive Bayes dengan kombinasi union hasil seleksi fitur Forward Selection dan Backward Elimination hanya memiliki nilai akurasi sebesar 83.61%   Abstract Heart disease is one of the leading causes of death along with other diseases. In the field of technology, data mining can be used to diagnose a disease sourced from patient medical record data. In the classification of medical datasets, Naive Bayes is one of the best methods used. The purpose of this study is to determine the comparison of the accuracy results of Naive Bayes using several feature selections, namely Forward Selection, Backward Elimination, a combination of union of Forwad Selection and Backward Elimination feature selection results, Information Gain, Gain Ratio, and a combination of union of Information Gain feature selection results with Gain Ratio. The data used in this research is heart disease data obtained from the UCI Machine Learning Repository. From the implementation of modeling that will be carried out, the highest accuracy value is 91.80% in the Naive Bayes algorithm with a combination of union of Information Gain and Gain Ratio feature selection results using a ratio of training data and test data of 80:20. While the accuracy of Naive Bayes with a combination of union selection results of Forward Selection and Backward Elimination features only has an accuracy value of 83.61%.  
Perencanaan Ulang Rencana Strategis untuk Pemasaran Produk di Masa Pandemi Covid-19: Indonesia Hartono, James Luis; Budiman, Irwan; Sembiring, Anita Christine
JURITI (Jurnal Ilmiah Teknik Industri )Prima Vol 3 No 1 (2019): Juriti Prima (Jurnal Ilmiah Teknik Industri Prima)
Publisher : Fakultas Teknologi dan Ilmu Komputer, Universitas Prima Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

UKM Prime Store bergerak sebagai toko retail yang menjual berbagai oli dengan mengambil oli dari distributor oli yang sah, dengan mendistribusikannya ke berbagai bengkel sepeda motor dan ke para agen sebanyak mungkin agar dapat sampai kepada konsumen. Rencana strategi perlu digunakan dikarenakan penurunan permintaan pasar sebesar 20% di tahun 2019, dimana pada tahun 2018 dapat terjual 2000 dus setiap bulannya, namun di tahun 2019 hanya terjual 1600 dus setiap bulannya, di tahun 2020 terjadi kenaikan 10% di awal tahun menjadi 1700-1800 di bulan Januari - Juni 2020, lalu menurun lagi sampai dengan akhir tahun 2020. Adapun tujuan dari penelitian adalah untuk meningkatkan volume penjualan dengan memanfaatkan kemajuan teknologi, meningkatkan penjualan melalui brosur, iklan dan promosi. Metode yang digunakan adalah Metode SWOT, QSPM, Metode 4P dan KPI. Dari hasil strategi yang didapatkan 6 strategis yang dapat digunakan dari pengolahan data QSPM, diharapkan UKM dapat meningkatkan penjualan dengan memanfaatkan kemajuan teknologi, dan meningkatkan penjualan melalui brosur, iklan dan promosi yang di buat UKM. Penelitian ini diharapkan dapat membantu perusahaan maupun UKM yang terkena dampak pandemi untuk dapat bangkit dan meningkatkan penjualan produk mereka kembali.
Gender Classification Based on Electrocardiogram Signals Using Long Short Term Memory and Bidirectional Long Short Term Memory Halim, Kevin Yudhaprawira; Nugrahadi, Dodon Turianto; Faisal, Mohammad Reza; Herteno, Rudy; Budiman, Irwan
Jurnal Ilmiah Teknik Elektro Komputer dan Informatika Vol. 9 No. 3 (2023): September
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jiteki.v9i3.26354

Abstract

Gender classification by computer is essential for applications in many domains, such as human-computer interaction or biometric system applications. Generally, gender classification by computer can be done by using a face photo, fingerprint, or voice. However, researchers have demonstrated the potential of the electrocardiogram (ECG) as a biometric recognition and gender classification. In facilitating the process of gender classification based on ECG signals, a method is needed, namely Long Short-Term Memory (LSTM) and Bidirectional Long Short-Term Memory (Bi-LSTM). Researchers use these two methods because of the ability of these two methods to deal with sequential problems such as ECG signals. The inputs used in both methods generally use one-dimensional data with a generally large number of signal features. The dataset used in this study has a total of 10,000 features. This research was conducted on changing the input shape to determine its effect on classification performance in the LSTM and Bi-LSTM methods. Each method will be tested with input with 11 different shapes. The best accuracy results obtained are 79.03% with an input shape size of 100×100 in the LSTM method. Moreover, the best accuracy in the Bi-LSTM method with input shapes of 250×40 is 74.19%. The main contribution of this study is to share the impact of various input shape sizes to enhance the performance of gender classification based on ECG signals using LSTM and Bi-LSTM methods. Additionally, this study contributes for selecting an appropriate method between LSTM and Bi-LSTM on ECG signals for gender classification. 
The Effectiveness of Data Imputations on Myocardial Infarction Complication Classification Using Machine Learning Approach with Hyperparameter Tuning Mazdadi, Muhammad Itqan; Saragih, Triando Hamonangan; Budiman, Irwan; Farmadi, Andi; Tajali, Ahmad
Jurnal Ilmiah Teknik Elektro Komputer dan Informatika Vol. 10 No. 3 (2024): September
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jiteki.v10i3.29479

Abstract

Complications from Myocardial Infarction (MI) represent a critical medical emergency caused by the blockage of blood flow to the heart muscle, primarily due to a blood clot in a coronary artery narrowed by atherosclerotic plaque. Diagnosing MI involves physical examination, electrocardiogram (ECG) evaluation, blood sample analysis for specific heart enzyme levels, and imaging techniques such as coronary angiography. Proactively predicting acute myocardial complications can mitigate adverse outcomes, and this study focuses on early prediction using classification methods. Machine learning algorithms such as Support Vector Machine (SVM), Random Forest, and XGBoost were employed to classify patient medical records accurately. Techniques like K-Nearest Neighbors (KNN) imputation, Iterative imputation, and Miss Forest were used to handle incomplete datasets, preserving vital information. Hyperparameter optimization, crucial for model performance, was performed using Bayesian Optimization, which minimizes the objective function by modeling past evaluations. The contribution to this study is to see how much influence data imputation has on classification using machine learning methods on missing data and to see how much influence the optimization method has when performing hyperparameter tuning. Results demonstrated that the Iterative Imputation method yielded excellent performance with SVM and XGBoost algorithms. SVM achieved 100% accuracy, precision, sensitivity, F1 score, and AUC. XGBoost reached 99.4% accuracy, 100% precision, 79.6% sensitivity, an F1 score of 88.7%, and an AUC of 0.898. KNN Imputation with SVM showed results similar to Iterative Imputation with SVM, while Random Forest exhibited poor classification outcomes due to data imbalance, causing overfitting.
Improvement Of Production Quality With Improved Scheduling Of PT Jaya Baru Mandiri With Hodgson Algorithm Method Wati, Vera; David; Budiman, Irwan
Journal Knowledge Industrial Engineering (JKIE) Vol 8 No 1 (2021): JKIE (Journal Knowledge Industrial Engineering)
Publisher : Department of Industrial Engineering - Universitas Yudharta Pasuruan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35891/jkie.v8i1.2499

Abstract

Jaya Baru Mandiri company is a manufacturing company engaged in the manufacture of machinery spare parts. One of the spare parts products that are often made is mainshaft, for the purposes of palm oil mills. In the process of making mainshaft, there is still often a delay (lateness). So that in this study, it was done to improve the scheduling of the production process in order to deliver the product to consumers in a timely manner. To clarify the production process, the method that will be used in this study is hodgson algorithm method, shortest processing time (SPT). Hodgson's algorithmic method serves to minimize the number of tardy jobs in the scheduling of production machines. The purpose of hodgson's algorithm scheduling is to improve the efficiency of scheduling the ideal production process as well as minimize unnecessary waste of time with the improvements recommended in this study. It is expected that the production process of PT. Jaya Baru Mandiri can improve its production process effectively and efficiently.
Developing Standard Operating Procedure for Production in North Sumatra Construction Companies Arumbasari, Atita; Rhamadani, Poetri; Christine Sembiring, Anita; Budiman, Irwan
Journal Knowledge Industrial Engineering (JKIE) Vol 8 No 2 (2021): JKIE (Journal Knowledge Industrial Engineering)
Publisher : Department of Industrial Engineering - Universitas Yudharta Pasuruan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35891/jkie.v8i2.2524

Abstract

In the industrial era 4.0, the competition between corporate companies is getting tighter. This is a reference for the company's productivity in operating a product or service, one of which is PT.X. It can be seen from the running performance process, PT. X has constraints on the production performance process. Therefore, PT.X seeks to increase productivity in the production process. So that in this study, a proposal design was carried out on a standard operating procedure (SOP) using the Business Process Model (BPM) method. The result of the proposed design with BPM is to minimize the production time by 2 hours 40 minutes so that the production process can run more effectively and efficiently. With that, the best solution in handling this case research provides suggestions on the work process that is running with efficient improvements.
Reducing Fire Response Time in Medan City by Determining Hydrant Points Using ArcGis Software and Optimizing Routes Using the Djisktra Algorithm Stepvani, Putri; Saragi , Yosefin; Budiman, Irwan
Journal Knowledge Industrial Engineering (JKIE) Vol 8 No 2 (2021): JKIE (Journal Knowledge Industrial Engineering)
Publisher : Department of Industrial Engineering - Universitas Yudharta Pasuruan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35891/jkie.v8i2.2534

Abstract

The development of an area will increase the risk of fire. Fire will not only cause physical, material loss, it can also cause casualties. In a span of 3 years, 46 major fire cases were recorded, not including unregistered fire cases. To be able to reduce the losses incurred, the fire fighters must be able to meet the fire response time of 15 minutes. To be able to meet this response time, a water source that can be used to douse the fire is needed as well as the fastest route to get to the destination point in the shortest possible time. The method used for laying the hydrant is the distribution method using Arc Gis software. The results obtained are that it takes 26 hydrant locations that are scattered in several central business areas and densely populated in the 3 sub-districts.
Replanning Strategis Plan for Marketing Product with SWOT Analysis, QSPM, Marketing Mix 4P and KPI Methods During the COVID-19 Pandemic: English Hartono, James Luis; Budiman, Irwan; Sembiring, Anita Christine
Journal Knowledge Industrial Engineering (JKIE) Vol 8 No 2 (2021): JKIE (Journal Knowledge Industrial Engineering)
Publisher : Department of Industrial Engineering - Universitas Yudharta Pasuruan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35891/jkie.v8i2.2535

Abstract

UKM Prime Store operates as a retail store that sells various oils by taking oil from authorized oil distributors, distributing it to various motorbike repair shops and to as many agents as possible so that it reaches consumers. The strategic plan needs to be used due to the decline in market demand by 20% in 2019, where in 2018 2000 boxes were sold per month, but in 2019 only 1600 boxes were sold per month, in 2020 there was an increase of 10% at the beginning of the year to 1700- 1800 in January - June 2020, then decreased again until the end of 2020. The purpose of this research is to increase sales volume by utilizing technological advances, increasing sales through brochures and promotions. The methods used are the SWOT method, QSPM and the 4P method. From the strategic results obtained 6 strategies that can be used from QSPM data processing, it is hoped that UKM can increase sales by taking advantage of technological advances, and increase sales through brochures and promotions made by UKM. This research is expected to help companies and UKM affected by the pandemic to get up and increase the sales of their products again.
Analysis of Pandemic Bussnines Strategy Development at PT Milala Wisata Tour and Travel Panjaitan, Andreas; Stefen Sembiring, Andes; Christine Sembiring , Anita; Budiman, Irwan
Journal Knowledge Industrial Engineering (JKIE) Vol 8 No 2 (2021): JKIE (Journal Knowledge Industrial Engineering)
Publisher : Department of Industrial Engineering - Universitas Yudharta Pasuruan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35891/jkie.v8i2.2536

Abstract

The research is the qualitative and quantitative results using SWOT, STP, Marketing mix 7P, and cashflow for 3 years method analysis. This research aims to develop the business of PT Milala Wisata Tour & Travel during Covid-19 pandemic by using a typical culinary side business so that the main business can survive. SWOT analysis is a way to systematically identify various factors in order to formulate company strategy. The data collection technique carried out by the researcher is by direct observation conducted at the company and conducting interviews with the owner of PT. Milala Wisata Tour & Travel. Also by adding from reading books and also other sources related to the research title. The 7P Marketing mix includes price, product, process, people, physical evidance, promotion, place. To find out the strengths, weaknesses, and feasibility of typical culinary side businesses, an analysis is first carried out to find out how the target market is The data obtained from the collection and then analyzed using the Internal Rate of Return & Cashflow for 3 years to see the feasibility level of typical culinary side businesses are suitable and able to support the main business of the The results of research from Cashflow for 3 years show that a typical culinary side business deserves to be realized as a support for main business during the Covid-19 pandemic. Typical culinary side businesses have strengths and are in line with the travel business so they can take advantage of existing opportunities.
Co-Authors Adi Mu'Ammar, Rifqi Ahdyani, Annisa Salsabila Ahmad Tajali Al Ghifari, Muhammad Akmal Al Habesyah, Noor Zalekha Andi Farmadi Andreas Panjaitan, Andreas Anita Christine Sembiring Anshory, Muhammad Naufal Antoh, Soterio AROTAMA, ARDIAN HIRAMAN Arumbasari, Atita Azizah, Azkiya Nur Azizah, Siti Roziana Chandra Wijaya david Deni Sutaji Dodon Turianto Nugrahadi Dwi Kartini, Dwi Engmir Faisal, M. Reza Fathmah, Siti Fatma Indriani Friska Abadi Halim, Kevin Yudhaprawira Halimah Halimah Hartono, James Luis Herteno, Rudy Jumadi Mabe Parenreng Kacaribu, Loista Sevnin Kamaluddin Kamaluddin Kartika, Tengku Heny Lilies Handayani Mahmud Mahmud Manik, Cindy Vivi Anggreni Martalisa, Asri Muhammad Alkaff Muhammad Itqan Mazdadi Muhammad Reza Faisal, Muhammad Reza Muliadi Muliadi MULIADI -, MULIADI Nantheni, Sobha Noor Hidayah Nurdiansyah Nurdiansyah Prastya, Septyan Eka Radityo Adi Nugroho Rhamadani, Poetri Rizky, Muhammad Hevny Rozaq, Hasri Akbar Awal Rudy Herteno Said, Muhammad Al Ichsan Nur Rizqi Santonius, celvin Saputro, Setyo Wahyu Saragi , Yosefin Saragih, Triando Hamonangan Sembiring, Anita Stefen Sembiring, Andes Stepvani, Putri Syahputra, Muhammad Reza Tajali, Ahmad Tampubolon, Jusra Tarigan, Uni Pratama Tuti Sarma Sinaga Wahyu Caesarendra Wahyu Saputro, Setyo Wardana, Muhammad Difha Wati, Vera Winda Agustina YILDIZ, Oktay Yunida, Rahmi