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All Journal Transmisi: Jurnal Ilmiah Teknik Elektro Industrial Engineering Online Journal The Journal of Pure and Applied Chemistry Research JAIS (Journal of Applied Intelligent System) Sinkron : Jurnal dan Penelitian Teknik Informatika JST ( Jurnal Sains Terapan ) JTT (Jurnal Teknologi Terpadu) JURNAL MANAJEMEN MOTIVASI Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Jurnal Teknologi Sistem Informasi dan Aplikasi JSHP (Jurnal Sosial Humaniora dan Pendidikan) Jurnal Akuntansi Kompetif Infotekmesin Seminar Nasional Teknologi Informasi Komunikasi dan Administrasi [SEMINASTIKA] Abdimasku : Jurnal Pengabdian Masyarakat Publikasi Riset Orientasi Teknik Sipil (Proteksi) Journal of Soft Computing Exploration Jurnal Politica Dinamika Masalah Politik Dalam Negeri dan Hubungan Internasional Warta AKAB Jurnal Akuntansi, Manajemen, Bisnis dan Teknologi Industrial Research Workshop and National Seminar Nusantara Civil Engineering Journal Jurnal Ilmiah Sultan Agung JPM-AKA Journal Integration of Social Studies and Business Development Social Science Academic Jurnal Informatika Polinema (JIP) Jurnal Informatika: Jurnal Pengembangan IT Assoeltan: Indonesian Journal of Community Research and Engagement Beujroh : Jurnal Pemberdayaan dan Pengabdian pada Masyarakat KANGMAS: Karya Scientific Community Service is a journal Spektrum Industri Jurnal Pendidikan Ilmu Pengetahuan Alam Jurnal Pendidikan Ilmu Pengetahuan Alam
Candra Irawan
Politeknik Negeri Balikpapan
Religion Agriculture, Biological Sciences & Forestry Humanities Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Immunology & microbiology Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Nursing Physics Public Health Social Sciences Transportation Other

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Vehicle Detection Using Image Conversion Percentage to Binary Method Based on K-Means Irawan, Candra; Ningrum, Amanda Prawita; Nohan, Rejendra
(JAIS) Journal of Applied Intelligent System Vol. 9 No. 2 (2024): Journal of Applied Intelligent System
Publisher : LPPM Universitas Dian Nuswantoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62411/jais.v9i2.11178

Abstract

Vehicle detection is the artificial intelligence that can help us in transportation highway systems like counter vehicles passing through the road on Eid Mubarak day etc. The object in this case is divided into six classifications there are car, motorbike, van, truck, and three-wheel. On the dataset vehicle is mostly an image of a car that we get from Kaggle. To solve vehicle detection problems such as poor vehicle detection and reduced detection accuracy, we provide a new vehicle detection with a dataset at kaggle. The clustering process consists of steps in which input images are transformed into morphometrics. The next step is to classify the image data using the K-Means algorithm. The images grouped by this detection are vehicles. The first step is to determine the randomly drawn mean or center point of two image data values ​​in the database. If there is no data transfer, the group is considered stable and group creation is completed. Seven vehicle image data are used to test this application. And the result of our experiment on vehicle detection is about 85.7 % accurate
ANALISIS PENGARUH TEMPERATURE TERHADAP DENSITY CRUDE OIL DENGAN PENDEKATAN METODE THEIL PADA ANALISIS REGRESI LINIER NON-PARAMETRIK (Studi Kasus : Pusat Pengembangan Sumber Daya Manusia Minyak dan Gas Bumi (PPSDM MIGAS) Cepu) Irawan, Candra; Widharto, Yusuf
Industrial Engineering Online Journal Vol 12, No 1 (2023): WISUDA PERIODE JANUARI TAHUN 2023
Publisher : Program Studi Teknik Industri, Fakultas Teknik, Universitas Diponegoro

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

Abstract

AbstrakPusat Pengembangan Sumber Daya Manusia, Minyak, dan Gas Bumi (PPSDM MIGAS) adalah instansi pemerintah pusat dibawah Badan Pengembangan Sumber Daya Manusia Energi dan Sumber Daya Mineral, Kementerian Energi dan Sumber Daya Mineral yang mengolah crude oil milik PERTAMINA. Pengolahan crude oil dilakukan pada unit kilang dengan menerapkan uji density guna mengetahui kualitas dari crude oil tersebut. Pada proses pengukuran density crude oil juga dilakukan pengukuran temperature crude oil. Guna mengetahui pengaruh temperature tehadap density crude oil digunakan pendekatan analisis regresi linier non-parametrik metode Theil. Hasil penelitian menunjukkan bahwa temperature berpengaruh terhadap density crude oil dengan nilai korelasi Kendall-Tau sebesar - 0,810 yang mana hal ini menunjukkan korelasi yang sangat kuat serta hubungan dari kedua variable bersifat berlawanan arah. Koefisien Slope berada pada selang kepercayaan −2,298 < ????1 < 0,007, artinya density crude oil akan berkurang hingga 2,298 atau bertambah hingga 0,007 kg/m3 untuk setiap pertambahan 1°C temperature.Kata kunci: Analisis Regresi Linier, Methode Theil, Regresi Non Parametrik, Tau KendallAbstract[Analysis The Effect of Temperature to Density Crude Oil Using Theil Method Approach to Non-Parametric Linier Regression Analysis] The Center for Human Resources Development, Oil and Natural Gas (PPSDM MIGAS) is a central government agency under the Human Resources Development Agency for Energy and Mineral Resources, Ministry of Energy and Mineral Resources that processes PERTAMINA's crude oil. Crude oil processing is carried out at the refinery unit by applying a density test to determine the quality of the crude oil. In the process of measuring the density of crude oil, the temperature of crude oil is also measured. To determine the effect of temperature on density crude oil, Theil method approach to non-parametric linear regression analysis is used. The results showed that temperature affects the density of crude oil with a Kendall-Tau correlation value was -0.810, which shows a very strong correlation and the relationship between the two variables is opposite. The Slope coefficient is in the confidence interval of −2,298 < ????1 < 0,007, meaning that the density of crude oil will decrease to 2,298 or increase to 0,007 kg/m3 for every 1°C increase in temperature.Keywords: Linier Regression Analysis, Non-Parametric Regression, Tau Kendall, Theil Methods
Adaptive deep learning based on FaceNet convolutional neural network for facial expression recognition Al-Ghiffary, Maulana Malik Ibrahim; Cahyo, Nur Ryan Dwi; Rachmawanto, Eko Hari; Irawan, Candra; Hendriyanto, Novi
Journal of Soft Computing Exploration Vol. 5 No. 3 (2024): September 2024
Publisher : SHM Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52465/joscex.v5i3.450

Abstract

Facial recognition technology has become increasingly crucial in various applications, from personal identification, security, and human-care. Facial recognition has numerous practical applications, ranging from assessing mental health and well-being through facial expressions to evaluating customer satisfaction in service quality ratings. This study aims to develop a facial recognition model using a Convolutional Neural Network (CNN) with FaceNet architecture. The proposed method utilizes an advanced deep learning approach to generate high-quality facial embeddings, enhancing the model's ability to accurately identify and verify individuals. Our methodology includes training the CNN with FaceNet architecture, achieving an impressive average accuracy of 99.93%, with precision, recall, and F1-score all reaching 100%. The model demonstrated both high accuracy and efficiency, with an average training time of 13 minutes and 51 seconds. Future research should explore incorporating data augmentation, K-fold cross-validation, and additional transfer learning techniques to further enhance model performance and generalization. These advancements could lead to more resilient and flexible facial recognition systems capable of functioning effectively in diverse and challenging real-world conditions.
Predicting IT Incident Duration using Machine Learning: A Case Study in IT Service Management Caturkusuma, Resha Meiranadi; Alzami, Farrikh; Nurhindarto, Aris; Sulistiyono, MY Teguh; Irawan, Candra; Kusumawati, Yupie
Sinkron : jurnal dan penelitian teknik informatika Vol. 9 No. 1 (2025): Research Article, January 2025
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v9i1.14310

Abstract

In the digital era, ensuring customer satisfaction with IT services is crucial for business success. However, the complexity of IT infrastructure makes it difficult to manage services, requiring companies to focus on improving efficiency and reducing operational costs. One of the strategies used is Information Technology Service Management (ITSM), the main component of which is incident management, which aims to minimize service disruptions. While various studies on ITSM exist, research focused on Machine Learning models for predicting incident resolution times is relatively limited. This research aims to develop an incident resolution duration prediction model using a Random Forest Regressor-based regression approach. The dataset used is an event log from the ServiceNow system containing data on 24,918 incidents. The model was evaluated using the Mean Absolute Error (MAE), Root Mean Squared Error (RMSE), and R2 metrics, where the model achieved a MAE of 14.33 hours, RMSE of 69.8 hours, and R2 of 0.98. These results show that the model can provide accurate predictions and support better decision-making in IT incident handling. Time-related features, such as sys_update_month and closed_month, proved to be the most influential factors in predicting incident resolution duration.
Pelatihan Pemanfaatan Alat Sensor Hujan Berbasis Teknologi Industri 4.0 dalam Memantau Proses Pengeringan Produk di IKM Cipta Rasa Kuningan Utami, Andita; Irawan, Candra; Sukiman, Maman; Rosalina, Rosalina; Putri, Imalia Dwi; Suhartini, Suhartini; Nugraha, Dida Septiya; Bimo Seto, Kahfi Akmal Janitra
Jurnal Pengabdian Masyarakat AKA Vol 4, No 2 (2024): Desember 2024
Publisher : Politeknik AKA Bogor

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55075/jpm-aka.v4i2.253

Abstract

IKM memiliki peran strategis dalam perekonomian karena mampu menghasilkan produk yang beragam dan bersifat unik. Dukungan kepada IKM adalah upaya penting dalam memajukan perekonomian Indonesia. Cipta Rasa merupakan salah satu IKM di Kabupaten Kuningan yang  memproduksi berbagai macam makanan ringan seperti kecimpring dan opak. Dalam memproduksi produk, IKM Cipta Rasa masih menggunakan cara tradisional. Proses pengeringan yang dilakukan oleh IKM Cipta Rasa dengan memanfaatkan cahaya matahari sehingga efektivitas produksi sangat dipengaruhi oleh perubahan cuaca. Hal ini berdampak pada terhambatnya proses produksi pada musim hujan dan penurunan kualitas produk yang disebabkan oleh pengeringan yang tidak sempurna. Kegiatan Pengabdian Kepada Masyarakat (PkM) dilakukan dengan pelatihan pemanfaatan alat pendeteksi hujan berdasarkan sensor suhu, kelembaban, dan cahaya yang berfungsi untuk mendeteksi kemungkinan turunnya hujan. Adanya sensor berbasis teknologi industri 4.0 ini, memungkinkan pemilik IKM Cipta Rasa dapat memantau proses pengeringan produk sehingga dapat mengantisipasi turunnya hujan saat ada pemberitahuan pada aplikasi. Pelaksanaan kegiatan berjalan dengan lancar dan mendapat tanggapan baik dari pemilik IKM dan dari peserta pelatihan yang lain ditandai dengan semangat peserta kegiatan selama pelaksanaan kegiatan. Kegiatan pelatihan ini dapat membantu IKM dalam memaksimalkan proses pengeringan produk sehingga kualitas produk yang dihasilkan dapat dipertahankan.
A text security evaluation based on advanced encryption standard algorithm Bima, Aristides; Irawan, Candra; Laksana, Deddy Award Widya; Krismawan, Andi Danang; Isinkaye, Folasade Olubusola
Journal of Soft Computing Exploration Vol. 4 No. 4 (2023): December 2023
Publisher : SHM Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52465/joscex.v4i4.274

Abstract

This research approach analysis and examines a number of advanced encryption standard (AES) performance factors, including as encryption and decryption speed, processing resource, consumption, and resilience, to cryptanalysis attacks. The study’s findings demonstrate that AES is successful in providing high-level data security, particularly when used in the CBC (Cipher Block Chaining) operating mode. Performance is dependent on the length of the key that is utilized. Increasing the level of security through the use of longer keys may result in an increase in the amount of time needed for encryption. The experimental results show that the highest results from the data are as follows the length of the encryption time is 0.00005317 seconds, the length of the decryption time is 0.00000882 seconds, the results of BER and CER are 0, the results of entropy are 7.44237, and the results of avalanche influence are 54.86%.
Adsorption of Iron by Fly Ash Adsorbent of Coal Irawan, Candra; Atikah, Atikah; Rumhayati, Barlah
The Journal of Pure and Applied Chemistry Research Vol. 3 No. 3 (2014)
Publisher : Chemistry Department, The University of Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (518.667 KB) | DOI: 10.21776/ub.jpacr.%y.03.03.154

Abstract

This research has investigated adsorption of Fe with using fly ash adsorbent. Phases of adsorption of Fe isactivatedwithH2SO4afterthat thefly ashwere characterizedby usingXRF, FTIRandSEM. Determination ofoptimum conditionsonthe adsorptionof Fewithadsorbentmassvariations, variations incontact time, pHvariationandvariationconcentration andadsorptionisothermstudy. Resulth showthat theadsorptionof Fein optimum conditionoccurs inadsorbentmass of2.5g, for 60minutescontact timewithpH4at a concentration of20ppm. The results alsoable toadsorpup to94% Fe. The adsorption of Fe with using fly ashadsorbentwas more fitted to theLangmuirmodel than to Freundlich model <w:LsdException Locked="false" Priority=
Pendampingan Penyediaan Gambar Rencana Bangunan Bagi Masyarakat Sebagai Persyaratan Persetujuan Bangunan Gedung Ulfa, Anis Aulia; Irawan, Candra; Huda, Masrul
KANGMAS: Karya Ilmiah Pengabdian Masyarakat Vol 5 No 3 (2024): KANGMAS: Karya Ilmiah untuk Pengabdian Masyarakat
Publisher : Neolectura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37010/kangmas.v5i3.1774

Abstract

Kegiatan ini dilaksanakan untuk melakukan pendampingan kegiatan perencanaan perumahan warga graha indah, Kecamatan Balikpapan Utara, Kota Balikapapan. fasilitas layanan yang diberikan adalah pendampingan pembuatan gambar teknis dan pengajuan PBG. Dengan desain yang baik secara arsitektural, diharapkan mampu memenuhi persyaratan bangunan gedung. Pelaksanaan kegiatan ini dilakukan dalam beberapa tahapan, yaitu studi lapangan proses desain grafis dan visualisasi. Survei lapangan digunakan untuk mengumpulkan data situs, seperti mengukur luas situs dan menganalisis kondisi yang ada. Hasil pengukuran tersebut menjadi awal dari proses perencanaan dasar, yang kemudian berlanjut ke desain ruang pertemuan berupa visualisasi dan perhitungan struktur bangunan.. Hasil dari pelaksanaan kegiatan ini adalah : (1) telah diperbantukan dalam proses perencanaan desain bangunan, Kecamatan Balikpapan Utara, Kota Balikpapan; (2) penyusunan rencana anggaran biaya pelaksanaan pembangunan dan perhitungan struktur bangunan Lamin; (3) dari hasil perencanaan ini akan ditindaklanjuti sebagai Artikel koran daerah yaitu desain yang kontekstual dengan lingkungannya.
An Ensemble Learning Layer for Wayang Recognition using CNN-based ResNet-50 and LSTM Irawan, Candra; Rachmawanto, Eko Hari; Hadi, Heru Pramono
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol. 10, No. 1, February 2025
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/kinetik.v10i1.2053

Abstract

Wayang is commonly used to tell epic stories of Mahabharata and Ramayana, as well as local legends and myths. There are various types of wayang, such as wayang kulit (made of buffalo or goat leather), wayang golek (made of wood), and wayang klithik (combination of leather and wood). Although it indicates cultural richness, such diversity also makes it difficult for the general public to identify the character of wayang they are seeing because each type has unique characteristics and details. Recognizing   wayang characters is a challenging task due to their intricate designs and subtle variations. This research addresses this problem by leveraging machine learning technology, specifically CNN-based classification methods, to accurately identify wayang characters. This study proposed a novel method that integrates ResNet-50 transfer learning with LSTM, enhancing the model's ability to capture both spatial and sequential features of wayang images. The proposed model achieved an impressive accuracy of 97.92%, with precision, recall, and F1-scores all reaching 100%. Despite the extended training time of 188 minutes and 21 seconds, the results demonstrate the model's superior performance. This advancement can significantly aid in the preservation and educational dissemination of Indonesian cultural heritage. Future research can focus on optimizing the training process to reduce the time while maintaining or even improving the accuracy, potentially expanding the model's application scope and effectiveness.
Pelatihan Pembukuan Pengusaha UMKM Perdagangan Ban : Bookkeeping Training for UMKM Tire Trading Entrepreneurs Irawan, Candra
Assoeltan: Indonesian Journal of Community Research and Engagement Vol. 3 No. 1 (2025): Assoeltan: Indonesian Journal of Community Research and Engagement
Publisher : Edujavare Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70610/assoeltan.v3i1.765

Abstract

MSMEs in the tire trading sector play an important role in the local automotive industry, but often face obstacles in preparing accurate financial reports due to limited accounting knowledge. This causes difficulties in monitoring cash flow, measuring profitability, and accessing funding sources. Therefore, this community service aims to improve the understanding and skills of MSME actors in preparing simple financial reports through bookkeeping training. The method used is Participation Action Research (PAR) with a participatory approach involving lectures, interactive discussions, and direct assistance. This training includes material on the importance of financial reports, how to record daily transactions, and the preparation of balance sheets and profit and loss statements. The results of the community service show that participants experienced an increase in understanding in recording transactions systematically and structured, were able to separate personal and business finances, and prepare more accurate simple financial reports. However, there are still some weaknesses such as limited mentoring time and low understanding of accounting terms. In conclusion, this training is effective in improving the financial literacy of MSME tire trading actors, but more intensive mentoring and utilization of financial recording technology are needed to achieve more optimal results.
Co-Authors Abu Salam Ade Aisyah Arifna Putri Agus Winarno, Agus Agustina, Feri Akbar, Ilham Januar Al-Ghiffary, Maulana Malik Ibrahim Alfany, Fauzan Maulana Alhafish, Muhammad Radhi Alminda, Alfian Fadhilah ALQORNI, NISA Alzami, Farrikh Award Widya Laksana, Deddy Azhar, Kheiza Noor Aulia Aziz, Fuad Abdul Azzami, Salman Yuris Adila Barlah Rumhayati Basri Dahlan Bima, Aristides Bimo Seto, Kahfi Akmal Janitra Cahaya Jatmoko Cahyo, Nur Ryan Dwi Caturkusuma, Resha Meiranadi Christy Atika Sari Debi, Yoga Tegar Ardi Delicia Angow Diana Aqmala Edi Sugiarto Eko Hari Rachmawanto Eko Susanto Eni Sumanti Nasution Enriyani, Riri Fahmi Amiq Faradhina Azzahra Farida Farida Ferdy Kahandanie Ferdy Novri Fikri Budiman Firmansyah, Aksal Fitri, Rahma Hadi, Heru Pramono Hari Purnama, Hari Hasbi, Hanif Maulana Henny Pratiwi Adi Heru Lestiawan Hilmansyah Huda, Masrul Ifan Rizqa Ika Novita Dewi Inzaghi, Reza Bayu Ahmad Irpan Kusyadi Isinkaye, Folasade Olubusola Ismail Ismail Kango, Riklan Krismawan, Andi Danang Kusumawati, Yupie Laksana, Deddy Award Widya Lalang Erawan Lili Romli, Lili Lisandi, Anisa Mahfud Marendra, Fajar Mariatul Kiptiah Menhard, Menhard Monica, Lala Munawaroh Munawaroh Muslih Muslih MY. Teguh Sulistyono Nawang Retno Ningrum, Amanda Prawita Nohan, Rejendra Novi Hendriyanto, Novi Nugraha, Dida Septiya Nuraini Nuraini Nurhindarto, Aris Oryzanti, Parwa Piliang, Arfah Pramudya, Muhammad Kemal Caesar Aqidah Putri, Imalia Dwi Rachmat Mudiyono, Rachmat Rahmatia, Lintannisa Rajali, Muhammad Ramadhan Rakhmat Sani Randy Pradityo Rasmon Ratna Purwaningsih Rosalina Rosalina Rosalina RR. Ella Evrita Hestiandari Saputra, Randika Septian, Wira Aditia Sidhiq, Restu Fajar Simatupang, Lisnawaty Sinaga, Daurat Solichul Huda, Solichul Sri Hartini Sri Utami Kholilla Mora Siregar Suharnawi Suharnawi Suhartini Suhartini Sukiman, Maman Sulistiana, Oktavera Sulistiyono, MY Teguh suprayogi Sutarni, Yayan Dwi Syukri, Muhammad Yazidus Tomy Andrianto Tumanggor, Mutawaqil Bilah Ulfa, Anis Aulia Umah Nur, Raisul Utami, Andita Wibowo, Isro' Rizky Widharto, Yusuf Widya Rahmawati WIRDAYANI WAHAB, WIRDAYANI Yudi Prana Hikmat Yulita, Rahma Zaenal Arifin Zubir, Zubir