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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Majalah Forum Teknik UGM Seminar Nasional Aplikasi Teknologi Informasi (SNATI) Transmisi: Jurnal Ilmiah Teknik Elektro IPTEK Journal of Proceedings Series Proceedings of KNASTIK TELKOMNIKA (Telecommunication Computing Electronics and Control) Prosiding Seminar Nasional Sains Dan Teknologi Fakultas Teknik Jurnal Teknik Elektro Prosiding SNATIF Jurnal Teknologi Informasi dan Ilmu Komputer International Journal of Advances in Intelligent Informatics Seminar Nasional Informatika (SEMNASIF) ELINVO (Electronics, Informatics, and Vocational Education) Semesta Teknika Jurnal Ilmiah KOMPUTASI Journal of Electrical Technology UMY JOIV : International Journal on Informatics Visualization Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Paradigma Emerging Science Journal Communications in Science and Technology JUTEI (Jurnal Terapan Teknologi Informasi) Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI) IJITEE (International Journal of Information Technology and Electrical Engineering) Prosiding Seminar Nasional Program Pengabdian Masyarakat Jurnal Nasional Teknik Elektro dan Teknologi Informasi Journal FORTEI-JEERI Prosiding Seminar Nasional Teknik Elektro, Sistem Informasi, dan Teknik Informatika (SNESTIK) Jurnal INFOTEL
Indah Soesanti
Universitas Gadjah Mada
Agriculture, Biological Sciences & Forestry Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Library & Information Science Mechanical Engineering Medicine & Pharmacology Social Sciences

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EKSTRAKSI CIRI BERBASIS WAVELET DAN GLCM UNTUK DETEKSI DINI KANKER PAYUDARA PADA CITRA MAMMOGRAM Hanifah Rahmi Fajrin; Hanung Adi Nugroho; Indah Soesanti
Prosiding SNST Fakultas Teknik Vol 1, No 1 (2015): PROSIDING SEMINAR NASIONAL SAINS DAN TEKNOLOGI 6 2015
Publisher : Prosiding SNST Fakultas Teknik

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Abstract

Kanker payudara merupakan  pembunuh nomor dua di dunia setelah kanker mulut rahim pada wanita. Dengan adanya deteksi dini kanker payudara kesempatan untuk bertahan hidup bagi penderita dapat ditingkatkan. Pada penelitian ini dilakukan pengolahan citra yang dapat melakukan pendeteksian dini terhadap kanker payudara. Terlebih dahulu dilakukan pra pengolahan pada citra dengan median filter dan connected component labeling (CCL) yang bertujuan untuk meningkatkan kualitas dan menghilangkan derau pada mammogram. Dengan mengekstrak ciri energi dari wavelet dekomposisi “haar” level 3, entropi, dan juga 5 ciri GLCM : IDM, ASM, korelasi, entropi, kontras.  kemudian dilakukan klasifikasi berbasis statistik yaitu dengan  regresi logistik untuk mendeteksi apakah citra mammogram termasuk normal atau abnormal. Penelitian dilakukan pada 108 data, yaitu 78 data abnormal dan 30 data normal, untuk pengujian dilakukan dengan algoritma k-fold validation. Pada fold-11 didapatkan nilai akurasi 81,45%, sensitivitas 82% dan spesifisitas 77,78%. Kata Kunci : GLCM, regresi logistik., transformasi wavelet
KAJIAN PUSTAKA METODE SEGMENTASI CITRA PADA MRI TUMOR OTAK Diah Priyawati; Indah Soesanti; Indriana Hidayah
Prosiding SNST Fakultas Teknik Vol 1, No 1 (2015): PROSIDING SEMINAR NASIONAL SAINS DAN TEKNOLOGI 6 2015
Publisher : Prosiding SNST Fakultas Teknik

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Abstract

Magnetic Resonance Images (MRI) marupakan mesin terbaik dalam mendiagnosa tumor otak. Namun Interpretasi MRI membutuhkan waktu lama, dan sulitnya mendeteksi adanya edema. Edema adalah jaringan yang berada di dekat sel tumor aktif dan tumpang tindih dengan jaringan normal. Saat ini proses diagnosa citra MRI masih mengandalkan kemampuan pakar radiologi secara manual. Hal ini membutuhkan waktu lama, dan keputusan yang diambil dapat bersifat subjektif.  Sehingga dibutuhkan sistem yang mampu melakukan segmentasi citra MRI untuk membagi daerah-daerah citra menjadi beberapa bagian yang homogen. Pada makalah ini akan dijelaskan metode-metode segmentasi citra pada MRI tumor otak. Penjelasan akan dimulai dari pemahaman tumor otak, peralatan penghasil citra otak seperti MRI, dan metode-metode segmentasi yang pernah dilakukan peneliti sebelumnya. Metode pengklasteran dapat menjadi salah satu pendekatannya. Dan pengklasteran fuzzy merupakan metode yang unggul untuk segmentasi citra tumor otak. Kata kunci: MRI, segmentasi, tumor otak
Metode Ekstraksi Ciri untuk Membedakan Citra Wajah Asli dan Foto Berbasis Perceptron Afri Yudamson , Indah Soesanti, Warsun Najib
Semesta Teknika Vol 16, No 1 (2013): MEI 2013
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/st.v16i1.431

Abstract

Face is one of media for human identification. Previous studies aimed at identifying human face were for a two-dimensional images. Thus, fraud may occur when providing input in two-dimensional face images (photos). This study aims to distinguish the original three-dimensional face image with two-dimensional face image. Feature extraction based on facial geometry principles (Incomplete sentence, subject only, do not know what the authors mean). Face images (both the original and the photos) were captured at deviated angle, to the left and to the right. Each image is then sliced for each face components (eyes and nose) and sought the position of the center point of each component. Comparison between the value of the right eye-nose projection vector to the left-right eye vector and the value of the left-right eye vector become the characteristics of each image. The perceptron method was used for the classifiers. The result, the software can distinguish the original three-dimensional and two-dimensional face image with an error of 8.33% of the 24 tested images. Error occurred for some samples that show big round nose.
Kompresi Citra Medis Menggunakan Alihragam Kosinus Diskret Dan Sistem Logika Fuzzy Adaptif Indah Soesanti
Semesta Teknika Vol 11, No 1 (2008): MEI 2008
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/st.v11i1.772

Abstract

The required of bandwidth for communication of digital image data is increased. Limited channel capacity favors image compression techniques. These techniques attempt to minimize the number of bits needed to represent an image and to reconstruct it with little visible distortion. The image data compression techniques reduce memory of storage data and time needed to transmit data. One of the image data compression methods is using Discrete Cosine Transform and Adaptive Fuzzy Logic. The objective of this research is compressing medical image using Discrete Cosine Transform and Adaptive Fuzzy Logic System. Discrete Cosine Transform is applied to find the data will which be encoded and Adaptive Fuzzy Logic System is applied to classify sub image into certain class. The class classification of a sub image is according to their AC energy levels. The systems assign more bits to a sub image if the sub image contains much detail (large AC energy) and less bits if contains less detail (small AC energy). The result of the research shows that the accurate calculation of AC energy determines class classification of sub image and bitmaps used for image data compression must be matching with characteristic of image. Bitmaps used for image data compression determine compression ratio and reconstructed image quality. The medical image compression with ratio of 1:4.8028 result in a reconstruction image with SNR of 63.8197 dB, and visually shows that the image is similar to the original image without significant error.
Perancangan Perangkat Lunak untuk Ekstraksi Ciri dan Klasifikasi Pola Batik Indah Soesanti
Semesta Teknika Vol 17, No 2 (2014): NOVEMBER 2014
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/st.v17i2.424

Abstract

The popularity of batik patterns in Indonesia has varied. Industrial modern devices in imaging have supported batik pattern recognition and classification. The important of product pattern information could not naturally visible. The information about batik pattern can be achieved by using the appropriate software design of image processing for extracting the features. One of the potential procedures is the unsupervised classification method based on specific feature.  In this research, the specific feature extraction based on the eigenimage of batik pattern was done. In the final step, the nearest distance eigenimage between reference batik image and test batik image was used to identify the batik from the classical pattern field point of view. The results of batik image identification conformed 96.67% with the reference batik images.
A Neuro-Fuzzy Approach for Vehicle Fuel Consumption Prediction Indah Soesanti; Ramadoni Syahputra
Journal of Electrical Technology UMY Vol 2, No 3 (2018)
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jet.2339

Abstract

This paper presents a neuro-fuzzy approach for predicting vehicle fuel consumption. The prediction of fuel consumption of a vehicle has become a strategic issue. This is because it is not only related to the problem of the availability of fuel which is getting thinner but also the problem of the environmental impact caused. In this study, the acquisition of the car parameter data was inputted, namely the number of cylinders, displacement, horsepower, weight, acceleration, and model year. The output variable that will be predicted is fuel consumption in miles per gallon (MPG). 'Weight' and 'Year' are chosen as the two best input variables. Training results and predictions are expressed in the three-dimensional input-output surface graph of the best two-input ANFIS model for MPG prediction. The graph shows a nonlinear and monotonic surface, where MPG is predicted to increase with an increase in 'Weight' and a decrease in 'Year'. The results of the RMSE training were 2.767 and the RMSE examination was 2.996. Based on the results of the study showed that the greater the weight of motor vehicles, the greater the amount of fuel needed to travel the same distance.
A Study of Sugarcane Waste for Biomass Energy in the Supply of Electrical Energy Ramadoni Syahputra; Oki Iwan Pambudi; Faaris Mujaahid; Indah Soesanti
Journal of Electrical Technology UMY Vol 4, No 1 (2020): June
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jet umy.v4i1.9746

Abstract

This paper presents a study of sugarcane waste for biomass energy in the supply of electrical energy. Biomass is a renewable energy source derived from organic matter such as wood and sugarcane waste. As much as 30 per cent of sugar cane raw material for sugar production is in the form of sugar cane waste. This sugarcane waste is very potential to be developed as a biomass energy raw material. In this study, an analysis of the potential of sugarcane waste at the Madukismo Yogyakarta sugar mill was carried out. Observations made to record how much cane waste is produced by the sugar factory every day of the year. Furthermore, these data are analyzed using Homer Energy software to obtain the potential of electrical energy produced during a year. The analysis was also carried out on the amount of electricity demand in the sugar factory. This study is done to calculate how much the contribution of electrical energy from biomass as a provider of electricity supply. The results of the analysis showed that sugarcane waste as much as 1.035 tons/day on average was able to meet all the electrical energy requirements for the operation of the Madukismo sugar factory.
A Fuzzy Logic Controller Approach for Controlling Heat Exchanger Temperature Indah Soesanti; Ramadoni Syahputra
Journal of Electrical Technology UMY Vol 3, No 4 (2019): December
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jet.3462

Abstract

This paper presents a fuzzy logic controller approach for controlling heat exchanger temperature. Fuzzy logic controller is an artificial intelligence-based controller. The fuzzy logic controller has been widely used for control applications in the industrial world. One of the tools used in the industrial world that requires accurate control is the heat exchanger. A heat exchanger is a device used to process the mixing of liquids that have different temperatures. In this case, temperature control becomes very important. Fuzzy logic control is applied to the heat exchanger so that the mixed fluid has a constant temperature. Fuzzy logic control models in this study are combined with neural network techniques. The fuzzy logic controller model is simulated in Matlab software. The results showed that the fuzzy logic controller was able to stabilize the temperature of the heat exchanger well.
Analysis of Induction Motor Performance Using Motor Current Signature Analysis Technique Ramadoni Syahputra; Hedi Purwanto; Rama Okta Wiyagi; Muhamad Yusvin Mustar; Indah Soesanti
Journal of Electrical Technology UMY Vol 5, No 1 (2021): June
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jet.v5i1.11764

Abstract

This paper discusses the analysis of the performance of an induction motor using the motor current signature analysis (MCSA) technique. Induction motor is a type of electric machine that is widely used in industry. One of the industries that utilize induction motors is a steam power plant (SPP). The role of induction motors is very vital in SPP operations. Therefore, it is necessary to monitor the performance, stability, and efficiency to anticipate disturbances that can cause damage or decrease the life of the induction motor. MCSA is a reliable technique that can be used to analyze damage to an induction motor. In this technique, the induction motor current signal is detected using a current transducer. The signal is then passed on to the signal conditioning and then into the data acquisition device. The important signal data is analyzed in adequate computer equipment. The results of this analysis determine the condition of the induction motor, whether it is normal or damaged. In this research, a case study was carried out at the Rembang steam power plant, Central Java, Indonesia. The results of the analysis of several induction motors show that most of them are in normal conditions and are still feasible to operate.
ANALISIS SEGMENTASI PELANGGAN MENGGUNAKAN KOMBINASI RFM MODEL DAN TEKNIK CLUSTERING Beta Estri Adiana; Indah Soesanti; Adhistya Erna Permanasari
Jurnal Terapan Teknologi Informasi Vol 2 No 1 (2018): Jurnal Terapan Teknologi Informasi
Publisher : Fakultas Teknologi Informasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (873.652 KB) | DOI: 10.21460/jutei.2018.21.76

Abstract

Intisari – Persaingan yang ketat di bidang bisnis memotivasi sebuah usaha kecil dan menengah (UKM) untuk mengelola pelayanan terhadap konsumen tetap (pelanggan) secara maksimal. Meningkatkan kesetiaan pelanggan dengan mengelompokkan pelanggan menjadi beberapa kelompok dan menentukan strategi pemasaran yang tepat dan efektif untuk setiap kelompok. Segmentasi pelanggan dapat dilakukan melalui pendekatan data mining dengan metode clustering. Tujuan utamanya segmentasi pelanggan dan mengukur kesetiaan mereka terhadap sebuah produk UKM. Dengan menggunakan metode CRISP-DM yang terdiri dari enam fase, yakni pemahaman bisnis (business understanding), pemahaman data (data understanding), persiapan data (data preparation), pemodelan (modelling), evaluasi (evaluation), dan penerapan (deployment). Algoritma K-means digunakan untuk pembentukan klaster dan RapidMiner sebagai tool yang digunakan untuk mengevaluasi klaster-klaster yang terbentuk. Pembentukan klaster didasarkan pada analisa RFM ( Recency, Frequency, dan Monetary). Davies Bouldin Index (DBI) digunakan untuk menemukan jumlah cluster (k) yang optimal. Hasilnya kelompok pelanggan yang terbentuk ada tiga kelompok dengan kelompok pertama berjumlah 30 pelanggan masuk dalam kategori typical customer, kelompok kedua terdapat 8 pelanggan yang masuk dalam kategori superstar dan kelompok ketiga berjumlah 89 pelanggan pada kategori dormant customer.
Co-Authors Adha Imam Cahyadi Adhi Soesanto, Adhi Adhi Susanto Adhistya Erna Permanasari Afrisal, Hadha Agus Eko Minarno Agus Jamal Al-Fahsi, Resha Dwika Hefni Andrey Nino Kurniawan Andrey Nino Kurniawan Nino Kurniawan Andrey Nino Kurniawan, Andrey Nino Anna Nur Nazilah Chamim Aqil Aqthobirrobbany Aqthobirrobbany, Aqil Arief Rachma Wibowo Bambang Sutopo Bana Handaga Beta Estri Adiana Cepi Ramdani Chamim, Anna Nur Nazilah Danny Kurnianto Desyandri Desyandri Dewi Purnamasar Diah Priyawati Dian Nova Kusuma Hardani Domy Kristomo Dwi Rochmayanti Dwi Rochmayanti Dwi Rochmayanti Eka Firmansyah Elfrida Ratnawati Faaris Mujaahid Fathania Firwan Firdaus Fikri Zaini Baridwan Hanifah Rahmi Fajrin Hanung Adi Nugroho Hedi Purwanto Hendriyawan A., M. S. Henry Sulistyo Hidayatul Fitri Hotama, Christianus Frederick Husnul Rahmawati Sakinnah I Made Agus Wirahadi Putra Ikhwan Mustiadi Indriana Hidayah Isbadi Urifan Karisma Trinanda Putra, Karisma Trinanda Krisna Nuresa Qodri Litasari Litasari Litasari M.S. Hendriyawan Achmad Maesadji Tjokronagoro Maesadji Tjokronagoro Maesadji Tjokronegoro Medycha Emhandyksa Meirista Wulandari Muhammad Arzanul Manhar Muhammad Rausan Fikri Mustar, Muhamad Yusvin Noor Akhmad Setiawan Nurokhim Nurokhim Oki Iwan Pambudi Oktoeberza, Widhia KZ Oyas Wahyunggoro Paulus Tofan Rapiyanta Pipit Utami Ramadoni Syahputra Ratnasari Nur Rohmah Rina Susilowati Risanuri Hidayat Rudy Hartanto Sekar Sari Siti Helmyati Soesanto, Adhi Sulistyo, Henry Sunu Wibirama Syahfitra, Febrian Dhimas Thomas Sri Widodo Thomas Sri Widodo Thomas Sri Widodo Thomas Sri Widodo Tole Sutikno Warsun Najib Widyawan Widyawati Prima, Widyawati Wijaya, Nur Hudha Wijaya, Nur Hudha Wiyagi, Rama Okta Yudhi Agussationo Yundari, Yundari