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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) TEKNIK Techno.Com: Jurnal Teknologi Informasi TELKOMNIKA (Telecommunication Computing Electronics and Control) Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika Padjadjaran Journal of Dentistry JETT (Jurnal Elektro dan Telekomunikasi Terapan) International Journal of Artificial Intelligence Research Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan JPEK (Jurnal Pendidikan Ekonomi dan Kewirausahaan) To Maega: Jurnal Pengabdian Masyarakat Journal of Electronics, Electromedical Engineering, and Medical Informatics JMECS (Journal of Measurements, Electronics, Communications, and Systems) Indonesian Journal of Electrical Engineering and Computer Science Community Development Journal: Jurnal Pengabdian Masyarakat ASEAN Marketing Journal Media Ilmiah Akuntansi eProceedings of Engineering Community Service Seminar and Community Engagement (COSECANT) Journal of Computer Engineering: Progress, Application and Technology Al-Mubtadi : Jurnal Pendidikan Guru Madrasah Ibtidaiyah
Hilman Fauzi, Hilman
Universitas Telkom
Religion Agriculture, Biological Sciences & Forestry Humanities Biochemistry, Genetics & Molecular Biology Computer Science & IT Control & Systems Engineering Dentistry 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 Materials Science & Nanotechnology Medicine & Pharmacology Nursing Public Health Social Sciences Other

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Perancangan Aplikasi Grafologi Berbasis Smartphone Android Untuk Identifikasi Kecenderungan Optimisme & Pesimisme Individu (the Design Of Graphology Applications Based Smartphone Android To Identify Individual Optimism And Pessimism Tendencies) Oktiandi Nugroho Wasktio; Hilman Fauzi
eProceedings of Engineering Vol 8, No 5 (2021): Oktober 2021
Publisher : eProceedings of Engineering

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Abstract

Grafologi merupakan salah satu cabang ilmu psikologi yang sering digunakan ahli grafolog untuk menganalisis kepribadian seseorang melalui tulisan tangan sehingga dapat mengetahui kencenderungan emosional atau kepribadian seseorang. Kepribadian merupakan hal dasar yang melekat pada tiap individu yang tidak bisa dinilai dari penampilannya. Pada penelitian ini penulis akan merancang aplikasi berbasis android untuk mengidentifikasi kecenderungan emosional atau kepribadian seseorang melalui tulisan tangan. Pengujian ini dilakukan untuk mengetahui beberapa kepribadian trait, seperti emosi optimis & pesimis, karakter interaksi sosial yang cenderung menjaga jarak & tidak menjaga jarak, dan self-confident & inferiority. Hasil pengujian sistem aplikasi pada Tugas Akhir ini mampu mengidentifikasi kecenderungan emosional individu. Sistem aplikasi yang dirancang mampu mengidentifikasi tiga kepribadia trait dengan cukup baik. Dari 35 sampel data citra tulisan tangan terdapat 29 sampel data citra yang berhasil mencapai kesamaan dengan tiga kepribadian trait yang diuji dan mendapat hasil akurasi sebesar 82.85%. Kata Kunci: Grafologi, Android, Kepribadian Trait, Garis Dasar Tulisan, Jarak Spasi Antar Kata, Ketinggian Baris dalam Menentukan Ketinggian Huruf “i”.
Analisa Jenis Kelamin Berdasarkan Citra Wajah Menggunakan Metode Gray Level Co-occurrence Matrix (glcm) Dan Klasifikasi Naive Bayes Andi Zahra Bunga Zana; Jangkung Raharjo; Hilman Fauzi TSP
eProceedings of Engineering Vol 8, No 5 (2021): Oktober 2021
Publisher : eProceedings of Engineering

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Pada penelitian tugas akhir ini dilakukan perancangan sistem untuk dapat mengklasifikasikan jenis kelamin berdasarkan citra wajah pada manusia. Dengan melakukan ekstraksi ciri menggunakan metode Gray Level Co-Occurrence Matrix (GLCM) dan proses klasifikasi menggunakan metode Naive Bayes yang bertujuan untuk dapat membedakan jenis kelamin laki-laki dan wanita pada manusia. Citra wajah tersebut dikelompokkan berdasarkan kelas laki-laki dan wanita. Tujuan dari penelitian tugas akhir ini untuk mengetahui jenis kelamin pada manusia dan manfaat dari perancangan sistem ini salah satunya dapat digunakan dalam bidang kesehatan untuk mendeteksi perbedaan jenis kelamin laki-laki atau wanita dan sebagai salah satu teknologi awal untuk aplikasi kesehatan cerdas lanjutan dalam pengukuran Body Mass Index (BMI). H
Ekstraksi Detak Jantung Berbasis Pengolahan Citra Wajah Dengan Algoritma Bss (blind Separation Signal) (heart Rate Extraction Based On Processing Of Facial Images Using Bss (blind Separation Signal) Algorithm) Utari Nur Ramadhani Yora; Hilman Fauzi; Syamsul Rizal
eProceedings of Engineering Vol 8, No 5 (2021): Oktober 2021
Publisher : eProceedings of Engineering

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Detak Jantung merupakan suara debaran jantung yang dihasilkan akibat aliran darah melewati jantung. Jantung merupakan organ vital sehingga metode untuk mendeteksinya beraneka ragam, mulai dari metode konvensional hingga modern. Semakin berkembangnya teknologi membuat sistem pendeteksi detak jantung kini semakin maju. Pada penelitian Tugas Akhir ini, akan dilakukan pengembangan lebih lanjut mengenai ekstraksi detak jantung manusia menggunakan citra wajah. Metode yang digunakan adalah Blind Separation Signal (BSS) dengan metode deteksi wajah yang digunakan adalah You Only Look Once (YOLO) generasi ketiga atau YOLOv3 dengan mengamati ROI dari variasi warna kulit wajah seseorang yang disebabkan oleh sirkulasi darah. Hasil akhirnya berupa detak jantung manusia berbasis aplikasi python yang memudahkan kita untuk mengukur detak jantung. Akurasi yang didapatkan untuk model deteksi objek YOLOv3 adalah sebesar 95%. Pengujian terbaik dilakukan pada posisi wajah lurus dengan jarak 40 cm dan dilakukan pada malam hari menggunakan pencahayaan lampu LED 14.5watt dan didapatkan akurasi tertinggi adalah 97,7%. Kata Kunci: Jantung, Detak Jantung, Pengolahan Citra Digital Wajah, Blind Separation Signal (BSS), You Only Look Once (YOLO), Region of Interest (ROI).
Klasifikasi Citra Kanker Serviks Menggunakan Deep Residual Network Revydo Bima Anshori; Hilman Fauzi; Thomhert Suprapto Siadari
eProceedings of Engineering Vol 9, No 6 (2022): Desember 2022
Publisher : eProceedings of Engineering

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Abstract

Abstrak—Penyakit kanker serviks menempati posisi ke dua dengan angka kematian tinggi kaum wanita setiap tahunnya menurut WHO. Penyebab penyakit ini karena adanya Human Papilloma Virus (HPV) yang menyerang langsung ke serviks, selain itu juga pola hidup yang kurang sehat dapat mempengaruhi terserangnya penyakit ini. Deteksi dini kanker serviks dapat dilakukan dengan menggunakan pemeriksaan Inspeksi Visual Asam Asetat (IVA). Hasil dari pemeriksaan IVA dapat dilihat kasat mata tetapi ahli medis memiliki perbedaan diagnosis dikarenakan penglihatan sendiri.Untuk membantu ahli medis mendapatkan diagnosis yang sesuai maka pemeriksaan dapat dilakukan dengan pendekatan teknologi. Teknologi yang akan digunakan adalah citra digital. Pengambilan gambar hasil pemeriksaan IVA format .jpg. Penelitian ini dilakukan klasifikasi citra kanker serviks dari hasil pemeriksaan IVA yang telah dilakukan oleh Rumah Sakit Hasan Sadikin Bandung. Untuk pengolahan citra pemeriksaan IVA akan menggunakan citra hasil CLAHE dan citra hasil Canny Edge Detection. Untuk pengklasifikasian akan menggunakan deep learning dengan arsitektur ResNet-50 dan ResNet-101 serta melakukan pengujian terhadap hyperparameter yaitu optimizer, learning rate, batch size, dan input size. Pada penelitian ini hasil terbaik mengunakan citra hasil Canny Edge Detection dengan hyperparameter menggunakan optimizer SGD, learning rate 0.1, batch size 32, dan input size 224×224. Dari hyperparameter tersebut hasil akursi yang dicapai sebesai 98,26 %. Kata kunci— Canny Edge Detection, CLAHE, Kanker Serviks, Pengolahan Citra Digital, Pemeriksaan IVA, ResNet.
PELATIHAN PENGENALAN TEKNOLOGI VIRTUAL REALITY UNTUK GURU SLB-B Yulinda Eliskar; Rustam Rustam; Hilman Fauzi TSP
Prosiding COSECANT : Community Service and Engagement Seminar Vol 2, No 2 (2022)
Publisher : Universitas telkom

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (208.66 KB) | DOI: 10.25124/cosecant.v2i2.18609

Abstract

Pentingnya media pembelajaran dalam menunjang keberhasilan proses belajar mengajar seringkali terabaikan. Berbagai alasan yang menjadi penyebab diantaranya adalah sulitnya mendapatkan media pembelajaran atau tidak dipahaminya teknologi yang akan digunakan. Di sisi lain, banyak alternatif yang dapat digunakan oleh para pendidik untuk menyampaikan materi pembelajaran. Salah satunya adalah dengan memanfaatkan teknologi virtual reality. Teknologi ini dapat digunakan untuk anak-anak berkebutuhan khusus terutama bagi tipe B (tuna rungu). Siswa akan merasa melihat seperti di dunia nyata. Pelaksanaan pengabdian pasyaraka ini dalam bentuk metode penyuluhan, pelatihan, praktek, pendampingan dan evaluasi. Melalui kegiatan pengabdian masyarakat ini, diharapkan dapat memudahkan guru-guru SLB dalam menyampaikan ilmunya. Pelatihan ini diberikan kepada guru-guru SLB-B (tuna rungu) yang berjumlah 16 orang. Tujuannya adalah agar para guru bisa menggunakan alat berupa virtual reality box (VR Box) sebagai media teknologi virtual reality. Mereka mempraktekkan langsung dan juga melakukan simulasi bagaimana teknologi ini bisa diterapkan dengan membuat tampilan model tiga dimensi.Kata Kunci: Virtual reality; VR Box, tuna rungu
Classification of Normal and Abnormal Heart Sounds Using Empirical Mode Decomposition and First Order Statistic Hilman Fauzi; Achmad Rizal; Mazaya 'Aqila; Alvin Oktarianto; Ziani Said
Journal of Electronics, Electromedical Engineering, and Medical Informatics Vol 5 No 2 (2023): April
Publisher : Department of Electromedical Engineering, POLTEKKES KEMENKES SURABAYA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35882/jeeemi.v5i2.287

Abstract

Analysis of heart sound signals for automatic segmentation and classification has revealed in recent decades that it has the potential to detect pathology accurately in clinical applications. Various audio signal processing techniques have been used to reduce the subjectivity of heart sound analysis. This study aims to classify normal and abnormal heart sound signals. The feature extraction process was optimized by EMD and calculated using five first-order statistical parameters: mean, variance, kurtosis, skewness, and entropy. The classification system is optimized with a mutual information algorithm to select traits that can significantly improve system performance. In addition, the selection of the optimal system configuration also includes the k-fold cross-validation and kNN methods with k values ​​and the proper distance type. Based on the test results, the highest accuracy of 98.2% was obtained when the value of k = 1 and the type of cosine distance on kNN with a five-fold cross-validation system evaluation model.
Study of Neuromarketing in Consumer Behavior due to Product Logos Color Changes Effect Denta Rahmadani; Hilman Fauzi; Reza Armanda Lubis; Maya Ariyanti
CEPAT Journal of Computer Engineering: Progress, Application and Technology Vol 1 No 02 (2022): August 2022
Publisher : Universitas Telkom

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25124/cepat.v1i02.5245

Abstract

Consumer behavior can be detected by conducting surveys, but this method lacks the depth of analysis to measure consumer behavior. By utilizing technological and scientific advances through the study of neuroscience, especially in neuromarketing, it is hoped to improve the ability to analyze consumer behavior. Neuromarketing has been widely used to measure consumer behavior through several stimuli, including logo colors. Neuromarketing to the human brain's response is done using electroencephalography (EEG) signal analysis. Data collection was carried out on six students aged 19-24 years. Subjects were given a stimulus of five original logo colors and five logo colors recolored with the number of questions in three sessions. Pre-processing uses a butterwort horde four bandpass filter with a theta-band frequency band in the frequency range of 4-8 Hz. Data on color changes using questionnaires and EEG signal data is processed on spatial and spectral domains to view active areas of short-term memory. The result obtained is the effect of the change in logo color on consumer memory and the active location of short-term memory on the logo's color. Using spatial selection, the number of channels was reduced from 16 to 4 channels or by 75%. The selected channels are in the memory and visual areas.
Strategi Pengembangan Bisnis Kopi Sipirok Berdasarkan Perspektif Ekonomi Islam (Studi Kasus Usaha Batu Kopi Sipirok Desa Situmba Kabupaten Tapanuli Selatan) Fauzi, Hilman; Marliyah, Marliyah; Dharma, Budi
JPEK: Jurnal Pendidikan Ekonomi dan Kewirausahaan Vol 8 No 2 (2024): JPEK (Jurnal Pendidikan Ekonomi dan Kewirausahaan)
Publisher : Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/jpek.v8i2.27652

Abstract

This research focuses on the SWOT analysis of the Sipirok coffee stone business in Situmba Village, Sipirok District, South Tapanuli Regency. This research uses a descriptive research methodology using a qualitative approach. Primary data from coffee business owners was used for research. This research aims to analyze the conditions of the Sipirok coffee stone business in Situmba Village, The results of the research show that the score obtained on the IFAS matrix is ​​3.87, while the score from the EFAS matrix is ​​4.07. This value shows that the Sipirok coffee stone business is in quadrant II, which means that the score shows that the Sipirok coffee stone business is in the village. Situmba, Sipirok District, South Tapanuli Regency, in the SWOT Analysis which was compiled from internal and external factors, resulted in the ST strategy, namely utilizing existing strengths to overcome existing threats. And finally utilizing agricultural extension workers to care for coffee plants in Situmba Village.
Age Identification System with Panoramic Image Processing Digital Molar Dental Radiograph with Adaptive Region Growing Approach Method Fauzi, Hilman; Tsani, Fajri; Oscandar, Fahmi; Adzra, Faaiq Ammaria
JMECS (Journal of Measurements, Electronics, Communications, and Systems) Vol. 10 No. 2 (2023): JMECS
Publisher : Universitas Telkom

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25124/jmecs.v10i2.6365

Abstract

Forensics plays a crucial role in legal enforcement, particularly in cases where objects or human victims undergoing forensic identification have suffered significant damage. Teeth offer a robust solution in the identification process due to their resilience to various circumstances. Forensic odontology focuses on dental identification for judicial purposes. One crucial parameter in forensic odontology is age estimation. Generally, an individual's dental development is directly related to age, which can be observed through the dental pulp. The dental pulp tends to narrow or widen with increasing age. In this study, an image processing system using the Adaptive Region Growing Approach (ARGA) method was developed for dental pulp molar radiograph images. Subsequently, the dental pulp images were classified using the Support Vector Machine (SVM) method. The research process encompassed data collection, image processing, feature extraction, and molar dental pulp size classification. The results demonstrated an accuracy of over 80% in the system, using specific parameters such as an adjustment threshold of OTSU 1.15, a clip limit histogram Equalization of 0.1, a polynomial kernel type, and one against one coding type for data classification into four classes. This study concludes that the Adaptive Region Growing Approach (ARGA) method and Support Vector Machine (SVM) classification can be effectively implemented in age estimation using panoramic radiograph images. This has the potential for significant applications in forensic odontology, supporting victim identification in legal enforcement.
Spatial and Spectral EEG Signal Analysis with Case Study of Slogans on Consumer’s Behaviour Tresna, Hilman Fauzi; Pratiwi, Daulika; Ariyanti, Maya; Fauzi, Adryan
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol. 8, No. 3, August 2023
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/kinetik.v8i3.1747

Abstract

Neuromarketing utilizes neuroscientific techniques to investigate consumer behavior, providing valuable insights beyond traditional research methods such as questionnaires and interviews which may not provide a complete understanding of consumer decision-making processes. Electroencephalography (EEG) has emerged as a promising tool for analyzing consumer responses to marketing stimuli. Nevertheless, the neural processing of slogans and their impact on short-term memory recall using EEG signals remains understudied. This research aims to bridge this gap by examining the neural activity associated with the recall of slogans using EEG analysis. By employing a spatial selection and spectral processing method, which involves Butterworth BPF filtering and L2-norm normalization to identify optimal channel combinations, active brain areas involved in slogan processing can be identified. Results reveal prominent activation in the frontal and occipital regions, particularly the F4 channel, indicating active recall and visual processing in individuals who correctly respond to slogans. These findings underscore the significance of slogans as visual marketing stimuli and offer insights for effective branding strategies. Leveraging EEG signals and understanding short-term memory processes enables marketers to optimize the impact of slogans on consumer engagement and brand recognition.
Co-Authors Achmad Rizal Achmad Rizal Adzra, Faaiq Ammaria Alvin Oktarianto Anak Agung Gede Mahendra Kusuma Andi Zahra Bunga Zana Andria Puja Pratama Ayudina, Nasya Azhar, Tauhid Nur Aznida Firzah Abdul Aziz Bagas Farhan Hadyantoro Bambang Hidayat Bambang Hidayat . Barri, Hablul Bayu Angga Medica Firmanda Bima Ansori, Revydo BIRU, BANYU Boby Irfanudin Anwar Budi Harsono, Ali Cynthia Erika Dayan Aldina Dendi Gusnadi Denta Rahmadani Dewa Nyoman Indra Dharma, Budi Dwi Sukma Bestry Fahmi Oscandar Fahmi Oscandar, Fahmi Fahreza, Ghazy Ahmad Faidil Hadi Fathurrachman, Dhia Firdaus Fauzi, Adryan Favian Dewanta Fina Maharani Fitra Ayu Larasati Galih Surya Gede Hari Yogiswara Gelar Budiman Hadyningtyas, Ivy Anindhita HARSONO, ALI BUDI Hasibuan, DR David H.M. Haya, Allika Fadia Heris, Faradisya Hutagalung, Yessica Maria I Wayan Agus Sugiarsa Irfan Darmawan Iwan Iwut Tritoasmoro Jangkung Raharjo Januar, Rifat Kinantan, Muhammad Rafi Komura, Tadayasu Kyoso, Masaki Lubis, Reza Armanda M. Abdullah Azzam Marliyah, Marliyah Marpaung, bintangsahala0203 Marpaung, Dhea Romantika Marpaung, DR Annaria Magdalena Mas Sarwoko Suraatmadja Masaki Kyoso Maya Ariyanti Mazaya 'Aqila Misbakhul Munir Mochamad Dandi Mohd Ibrahim Shapiai Mohd. Ibrahim Shapiai Muhammad , Ardisatria Surya Muhammad Hablul Barri Muhammad Ilham Muhammad Zuhairi Mumtaz, Yasmin Nasya Ayudina Darsono Naufal Reza Alfiandy Nugraha, M.Fajar Zulvan Nur Ibrahim Octavian Putera Kesuma Sugeng Oktafiani, Venia Oktiandi Nugroho Wasktio Pratiwi, Daulika Putra Fajar Alam Raditiana Patmasari Rahmadani, Denta Rahmah, Qisthi Nur Rahman, Fadlur Rahmat Widadi Raihan Nur Fadhlillah Ramanta Limantara Sidam Ramdhan Nugraha Rasta, John Ratri Dwi Atmaja Revydo Bima Anshori Reza Armanda Lubis Rio Fa, Farrel Rita Magdalena Rizqullah, Rafif Rustam Rustam Rustam Saepulloh, Saepulloh Said, Ziani Salim, La Ode Agus Salsabila, Afap Saputri, Ikra Yuni SENJAYA, ARIO Shapiai, Mohd. Ibrahim Siadari, Thomhert Siadari, Thomhert S. Sofia Sa'adiah SOFIA SAIDAH Sophya Hadini Marpaung Sugondo Hadiyoso Suhardjo Suhardjo Syamsul Rizal Syatta, Hurin Tadayasu Komura Tauhid Nur Azhar Thomhert Suprapto Siadari Tsani, Fajri Twinarya Bagus Wibawa Uswah Khairuddin Utari Nur Ramadhani Yora Vany Octaviany Wan Siti Nur Shafiqa Wan Musa Yanti, Suci Dwi Yasi Oktodiranto Yasman, Fudhla Ramadhana Yulinda Eliskar Yunita, Kurnia Sri Ziani Said