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All Journal Telematika : Jurnal Informatika dan Teknologi Informasi Seminar Nasional Informatika (SEMNASIF) Dharma: Jurnal Pengabdian Masyarakat Jurnal INFOTEL
Heriyanto Heriyanto
Prodi Teknik Informatika Universitas Pembangunan Nasional "Veteran" Yogyakarta
Computer Science & IT Electrical & Electronics Engineering Social Sciences

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ANALISA DETEKSI GAMBAR TERMODIFIKASI DENGAN DEVIASI RGB Heriyanto Heriyanto
Telematika Vol 9, No 2 (2013): Edisi Januari 2013
Publisher : Jurusan Teknik Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31315/telematika.v9i2.288

Abstract

Saving picture which one media represent become part of memory or history document. It ispossible that very important to personal. Storage media of picture sometimes become importantthat had been happened a modification about the original picture whitch a document become veryvaluable because change by other people and than It is very difficult to prove will the truth of dataand original picture and modification picture. Modification picture in general to repair or withspecific purpose become the picture makes wrong purpose. BRG picture ( Blue Red Green)representing base from colour in picture and It can be analyses about the picture change or colouraddition or the picture not change. Process checking of original picture is not also pixel but changeof colour a picture, can be known also with change of original primary colour of picture withadditional colour of picture, so that can be known by effect change of the colour with some analysiswhich can ascertain colour change or not. How big change of the colour can be calculating withuse of primary colour mean, change of blue colour mean, change of green colour mean, change ofmean red and also all of them can be combine.Keywords : History, Color, BRG (Blue, Red, Green), Modification, Document, Picture
Good Morning to Good Night Greeting Classification Using Mel Frequency Cepstral Coefficient (MFCC) Feature Extraction and Frame Feature Selection Heriyanto Heriyanto
Telematika Vol 18, No 1 (2021): Edisi Februari 2021
Publisher : Jurusan Teknik Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31315/telematika.v18i1.4495

Abstract

Purpose:Select the right features on the frame for good accuracyDesign/methodology/approach:Extraction of Mel Frequency Cepstral Coefficient (MFCC) Features and Selection of Dominant Weight Normalized (DWN) FeaturesFindings/result:The accuracy results show that the MFCC method with the 9th frame selection has a higher accuracy rate of 85% compared to other frames.Originality/value/state of the art:Selection of the appropriate features on the frame.
Identifikasi Ucapan Warna Menggunakan LPC (Linier Predictive Code ) Dan Kelompok Pemilihan Bobot Heriyanto Heriyanto; Oliver Samuel Simanjuntak
Telematika Vol 14, No 1 (2017): Edisi April 2017
Publisher : Jurusan Teknik Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31315/telematika.v14i01.1968

Abstract

Pelajaran mengenal warna dapat dilakukan dengan melihat gambar dan mengucapkan dengan suara. Pengenalan dengan deteksi suara untuk mengenal warna-warna bagi anak-anak sangat diperlukan baik dengan media suara maupun gambar. Pada anak-anak belajar mengenal warna dapat dilakukan dengan menggunakan pengenalan ucapakan warna. Pada saat belajar mengenal warna dengan ucapan  maka dilakukan deteksi suara atau ucapan warna menggunakan LPC. Salah satu metode untuk mengenal ucapakan dengan LPC (Linier Predictive Code) dapat meningkatkan akurasi 60%. Ekstraksi ciri selain menggunakan metode Linear Predictive Coding (LPC) berdasarkan Aibinu dkk. (2011) dengan LPC diantara 40%-60%. Penelitian ini menggunakan LPC yang menghasilkan kooefisien cepstral yang kemudian dilakukan seleksi fiture. Kombinasi seleksi fiture yang diambil diantaranya dengan 1. Mengelompokan nilai data 2. Melakukan pemilihan bobot. Hasil akurasi uji coba dilakukan dengan ucapan 1..10 warna dilakukan terhadap laki-laki dan perempuan sebanyak 10 orang mendapatkan nilai prosentase 95%
PENCARIAN DOKUMEN TEKS ARSIP SURAT DENGAN METODE INDEXING DAN QUERY Heriyanto Heriyanto
Seminar Nasional Informatika (SEMNASIF) Vol 1, No 1 (2015): Informatika Dalam Pengelolaan Sumber Daya Alam
Publisher : Jurusan Teknik Informatika

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Abstract

Pengarsipan surat menyurat di dalam aktifitas baik dalam arsip surat sendiri maupun dalam lingkungan kantor sangatlah penting. Pada saat-saat tertentu terkendala pada dimana suatu saat surat yang ingin dicari yang ada tulisan kata-kata tertentu atau kalimat ada pada surat-surat apa saja, kapan surat itu dibuat dan di file yang mana berkas tersebut pernah di simpan. Berkas surat yang sedikit belum menjadi masalah namun setelah data surat yang sudah dibuat bertumpuk-tumpuk bahkan sampai bertahun-tahun dengan jumlah yang banyak menjadi bingung. Permasalah tersebut maka dilakukan dengan proses penemuan kembali dengan indeks agar pada saat-saat tertentu data surat dapat ditemukan dengan baik. Metode indeks prinsipnya mengambil indeks yang ada pada buku. Buku yang tebal mempunyai indeks langsung dapat menemukan di dalam buku tersebut ada kata atau kalimat apa saya dapat ditemukan. Pada pengarsipan surat maka dapat dilakukan indeks yang sudah tersimpan dengan penyimpanan, dan dapat namun terlebih dahulu harus dioleh ketahapan awal pemecahan kata dalam suatu teks kalimat tersebut dilakukan indeks dan sekaligus tersimpan dalam database dengan tabel penyimpanan.
DETEKSI SUARA UCAPAN SALAM BAHASA ARAB MENGGUNAKAN MEL FREQUENCY CEPSTRAL COEFFICIENT (MFCC) DAN PEMILIHAN FITUR MIN MAX Heriyanto Heriyanto
Seminar Nasional Informatika (SEMNASIF) Vol 1, No 1 (2020): Peran Digital Society dalam Pemulihan Pasca Pandemi
Publisher : Jurusan Teknik Informatika

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Abstract

AbstractArabic greeting sounds are used in everyday life for Muslims in Indonesia. Salam recognition is used to check how correct the pronunciation of Arabic greetings is for Indonesians. The first stage was to collect the sample of greeting readings as much as 50 records of male and female records in wav recordings. One person takes the source of greeting reading as a reference for reference. Retrieval of test data as much as 50 samples of test data. The second stage is to perform feature extraction with MFCC from cepstral coefficient and frame results. The third stage is testing by checking the suitability of the greeting reading with the calculation of min max. The result of checking the suitability of reading on the selection of the right features carried out by MFCC has a result of 60.25%. Meanwhile, MFCC with a minimum yield of 71.75.0%. This shows that the use of the min max test can improve accuracy because there are more unique cepstral and max and min coefficients with a significant difference of 11.5%.Keywords : checking, feature extraction, reference, features, speechSuara ucapan salam bahasa Arab digunakan dalam kehidupan sehari-hari bagi umat beragama Islam di Indonesia. Pengenal ucapan salam dilakukan untuk mengecek seberapa benar dalam pelafalan ucapan salam berbahasa Arab bagi orang Indonesia. Tahap pertama dilakukan pengambilan sampel bacaan salam sebanyak 50 data rakaman putra dan putri dalam rekaman wav. Pengambilan sumber bacaan salam diambil satu orang sebagai acuan untuk referensi. Pengambilan data uji sebanyak 50 sampel data uji. Tahap kedua adalah melakukan ekstraksi ciri dengan MFCC hasil cepstral coeficient dan frame. Tahap ketiga adalah pengujian dengan pengecekan kesesuaian bacaan salam dengan perhitungan min max. Hasil pengujian pengecekan kesesuaian bacaan terhadap pemilihan fitur yang tepat dilakukan dengan MFCC mempunyai hasil sebesar 60,25%. Sedangkan MFCC dengan min max hasil sebesar 71.75,0%. Hal tersebut menunjukkan bahwa penggunaan pengujian min max dapat meningkatkan akurasi karena terdapat cepstral dan coefficients max dan min lebih unik dengan selisih 11.5% cukup signifikanKata Kunci : pengecekan, ekstraksi ciri, referensi, fitur, ucapan
PENCARIAN KEMIRIPAN JUDUL SKRIPSI DAN ABSTRAK DENGAN METODE EXACT MATCH (STUDI KASUS PROGRAM STUDI TEKNIK INFORMATIKA UPN “VETERAN” YOGYAKARTA) Heriyanto Heriyanto
Seminar Nasional Informatika (SEMNASIF) Vol 1, No 1 (2012): Computation And Instrumentation
Publisher : Jurusan Teknik Informatika

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Abstract

Beberapa mahasiswa dalam pencarian tema dan judul skripsi sering kali mengalami kesulitan dan kendala dengan beberapa kali harus mengganti dan merubah judul skripsi. Pengajuan judul terkadang diterima dan ditolak berdasarkan pertimbangan salah satunya adalah judul yang sudah ada, Adapun kendala utama adalah menghindari indikasi adanya kesamaan judul dan adanya indikasi plagiat. Adanya kesamaan judul skripsi antara mahasiswa satu dengan lain tanpa dilakuan pengecekan dapat terjadi redundancy judul yang tentunya dapat dihindari apabila ada kontrol dari dosen atau jurusan yang dapat melakukan pengecekan sebelum judul tersebut di setujui. Berangkat dari akar adanya kesamaan dan kemiripan judul dan abstrak dan menjadikan indikasi plagiat maka perlu dibuatkan suatu sistem perangkat lunak yang secara otomatis dapat memudahkan melakukan pengecekan secara akurat pada judul-judul skipsi maupun abstrak mahasiswa. Bertolak dari pentingnya adanya suatu perangkat lunak yang secara cepat dapat mengecek judul skripsi maupun abstrak maka penulis mengambil judul “Pencarian Kemiripan Judul Skripsi dan Abstrak dengan Metode Exact Match (Studi Kasus Program Studi Teknik Informatika UPN ”Veteran” Yogyakarta) ” dapat membandingkan sejauh mana nilai kemiripan dan beberapa judul yang sama dan serupa dapat tampil sebagai antisipasi plagiat yang semakin marak.
ANALISA INDEKS WAV UNTUK LAGU DANGDUT DAN POP Heriyanto Heriyanto
Seminar Nasional Informatika (SEMNASIF) Vol 1, No 1 (2011): Computatinal
Publisher : Jurusan Teknik Informatika

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Abstract

Media Audio merupkan media yang banyak digunakan dalam multimedia. Data WAV merupakan salah satu data lagu yang dapat diindeks untuk mencari perbedaan lagu dangdut dan lagu pop. Kedua jenis lagu tersebut banyak dipakai dan merupakan dua jenis lagu yang diidentifikasi berbeda. Bagaimana suatu indeks wav untuk mencari perbedaan kedua lagu tersebut dengan Average Energy. Data yang dioleh dengan Average Energy kemudian di kalkulasikan menjadi suatu data yang dapat dicari perbedaan pada sampling data yang diambil. Menghitung Average Energy dengan 100 sampling data
PENDAMPINGAN UMKM KWT SUKA MAJU UNTUK MENINGKATKAN PRODUKSI DAN PEREKONOMIAN MASYARAKAT DUSUN PALIHAN Heriyanto Heriyanto; Yuli Fauziah; Dyah Ayu Irawati
Dharma: Jurnal Pengabdian Masyarakat Vol 1, No 2 (2020): November
Publisher : Universitas Pembangunan Nasional "Veteran" Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (357.956 KB) | DOI: 10.31315/dlppm.v1i2.4043

Abstract

The SUKAMAJU Women's Farmer Group (KWT) is a group of women craftsmen of banana tree processing. During the Covid-19 pandemic, sales and marketing of processed banana food were very limited. Online marketing in times of the Covid-19 pandemic is urgently needed and requires support. Community service from UPN Veteran Yogyakarta, in this case, is programmed to help solve problems during the pandemic. Marketing through the internet and social media is very much needed, while the ability of mothers to master social media and the internet is very limited. The service team from UPN Veteran Yogyakarta is trying to help with solutions going into the field to help provide full assistance and also assistance for production equipment so that food processing craftsmen maintain production in KWT. The hope of the community service team is that there will be an increase in sales results by providing full assistance in both marketing media and increasing production equipment with an average increase of 8-9 pieces per day.
Implementation of Mel-Frequency Cepstral Coefficient as Feature Extraction using K-Nearest Neighbor for Emotion Detection Based on Voice Intonation Revanto Alif Nawasta; Nur Heri Cahyana; Heriyanto Heriyanto
Telematika Vol 20, No 1 (2023): Edisi Februari 2023
Publisher : Jurusan Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31315/telematika.v20i1.9518

Abstract

Purpose: To determine emotions based on voice intonation by implementing MFCC as a feature extraction method and KNN as an emotion detection method.Design/methodology/approach: In this study, the data used was downloaded from several video podcasts on YouTube. Some of the methods used in this study are pitch shifting for data augmentation, MFCC for feature extraction on audio data, basic statistics for taking the mean, median, min, max, standard deviation for each coefficient, Min max scaler for the normalization process and KNN for the method classification.Findings/result: Because testing is carried out separately for each gender, there are two classification models. In the male model, the highest accuracy was obtained at 88.8% and is included in the good fit model. In the female model, the highest accuracy was obtained at 92.5%, but the model was unable to correctly classify emotions in the new data. This condition is called overfitting. After testing, the cause of this condition was because the pitch shifting augmentation process of one tone in women was unable to solve the problem of the training data size being too small and not containing enough data samples to accurately represent all possible input data values.Originality/value/state of the art: The research data used in this study has never been used in previous studies because the research data is obtained by downloading from Youtube and then processed until the data is ready to be used for research.
Classification of Javanese Script Hanacara Voice Using Mel Frequency Cepstral Coefficient MFCC and Selection of Dominant Weight Features Heriyanto Heriyanto; Tenia Wahyuningrum; Gita Fadila Fitriana
JURNAL INFOTEL Vol 13 No 2 (2021): May 2021
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/infotel.v13i2.657

Abstract

This study investigates the sound of Hanacaraka in Javanese to select the best frame feature in checking the reading sound. Selection of the right frame feature is needed in speech recognition because certain frames have accuracy at their dominant weight, so it is necessary to match frames with the best accuracy. Common and widely used feature extraction models include the Mel Frequency Cepstral Coefficient (MFCC). The MFCC method has an accuracy of 50% to 60%. This research uses MFCC and the selection of Dominant Weight features for the Javanese language script sound Hanacaraka which produces a frame and cepstral coefficient as feature extraction. The use of the cepstral coefficient ranges from 0 to 23 or as many as 24 cepstral coefficients. In comparison, the captured frame consists of 0 to 10 frames or consists of eleven frames. A sound sampling of 300 recorded voice sampling was tested on 300 voice recordings of both male and female voice recordings. The frequency used is 44,100 kHz 16-bit stereo. The accuracy results show that the MFCC method with the ninth frame selection has a higher accuracy rate of 86% than other frames.
Co-Authors Agfianto Eko Putra Bambang Yuwono Bambang Yuwono Dessyanto Boedi Prasetyo Dyah Ayu Irawati Dyah Ayu Irawati, Dyah Ayu Frans Richard Kodong GITA FADILA FITRIANA Langit Da Silva Marbun, Andre Julio Nawasta, Revanto Alif Nur Heri Cahyana Nur Heri Cahyana Oliver Samuel Simanjuntak Revanto Alif Nawasta Simon Pulung Nugroho Sri Hartati Sri Hartati Tantra Nurhuda Tenia Wahyuningrum Yuli Fauziah