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All Journal Jurnal Buana Informatika Jurnal Informatika dan Teknik Elektro Terapan INTEGER: Journal of Information Technology JURNAL MEDIA INFORMATIKA BUDIDARMA Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Jusikom: Jurnal Sistem Informasi Ilmu Komputer ILKOMNIKA: Journal of Computer Science and Applied Informatics Journal Cerita: Creative Education of Research in Information Technology and Artificial Informatics Jifosi Letters in Information Technology Education (LITE) Nusantara Science and Technology Proceedings Jurnal Teknik Informatika (JUTIF) Jurnal Pengabdian Masyarakat Indonesia International Journal Of Computer, Network Security and Information System (IJCONSIST) Ranah Research : Journal of Multidisciplinary Research and Development Jurnal Riset Multidisiplin dan Inovasi Teknologi Merkurius: Jurnal Riset Sistem Informasi dan Teknik Informatika Neptunus: Jurnal Ilmu Komputer dan Teknologi Informasi
Eka Prakarsa Mandyartha
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Agriculture, Biological Sciences & Forestry Humanities Chemical Engineering, Chemistry & Bioengineering 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 Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Medicine & Pharmacology Public Health Social Sciences Transportation Other

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IMPLEMENTATION OF SUPPORT VECTOR MACHINE AND HARMONY SEARCH FOR CATARACT SEVERITY CLASSIFICATION IN FUNDUS IMAGES Hermadiputri, Firdausa Yasmin; Mandyartha, Eka Prakarsa; Rizki, Agung Mustika
Jurnal Sistem Informasi dan Ilmu Komputer Vol. 8 No. 1 (2024): JUSIKOM: JURNAL SISTEM INFROMASI ILMU KOMPUTER
Publisher : Fakultas Teknologi dan Ilmu Komputer Universitas Prima Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34012/jurnalsisteminformasidanilmukomputer.v8i1.5394

Abstract

Cataract is a condition that causes clouding of the lens of the eye and is a leading cause of blindness, including in Indonesia. Cataract diagnosis is often inconsistent between ophthalmologists due to personal experience. This research proposes a Support Vector Machine (SVM) based classification system and Harmony Search metaheuristic algorithm to optimize the weight vector 'w' on the SVM hyperplane as a supporting tool for cataract diagnosis. The research data comes from Kaggle which includes normal eye fundus images and cataracts with mild-moderate and severe levels. The research stages include image conversion from RGB to Grayscale, image enhancement with Histogram Equalization and GLCE, and feature extraction using GLCM and Haar Wavelet Transform, and unbalanced data is balanced by the SMOTEENN method. The results showed that Harmony Search successfully improved SVM accuracy compared to Conventional SVM using Gradient Descent. Accuracy increased by 18% from 0.53 to 0.71 on unbalanced data, and by 13% from 0.67 to 0.80 on balanced data. In addition, Harmony Search can improve computational time efficiency due to its ability to explore space globally.
SIMAPA System Testing Using Alpha and Beta Tests Puspaningrum , Eva Yulia; Yudha K., Dhian Satria; Utami, Hapsari Wiji; Via, Yisti Vita; Mandyartha, Eka Prakarsa; Maulana, Hendra
Nusantara Science and Technology Proceedings 8th International Seminar of Research Month 2023
Publisher : Future Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11594/nstp.2024.4133

Abstract

The SIMAPA system is a system for monitoring children's activities and development which is implemented at KB-TK Agripina Surabaya. The SIMAPA system has been designed using system development, namely SDLC (System Development Life Cycle). The system can be declared valid and by what is expected if testing has been carried out. An application can be tested using collaborative alpha and beta testing using the black box method. Alpha testing is carried out to see whether all systems can run well and is carried out by the system manufacturer. Meanwhile, in beta testing, the party who will assess the system is the user or people who are not involved in creating the system. This testing is carried out by distributing questionnaires to several users to assess the application that has been built. The questionnaire contains questions about the system being built so that it can be concluded whether the application is by the objectives. The results of the Beta test with 6 questions about the system obtained good results with an average score of 92%. so that the system built is by what is expected.
SEGMENTASI SEL PAP SMEAR SERVIKS BERTUMPUK MENGGUNAKAN LOCAL ADAPTIVE THRESHOLDING DAN WATERSHED Lutfia, Qonita; Mandyartha, Eka Prakarsa; Rizki, Agung Mustika
Jurnal Informatika dan Teknik Elektro Terapan Vol 12, No 3 (2024)
Publisher : Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jitet.v12i3.4811

Abstract

Kanker serviks merupakan ancaman kesehatan global serius, dengan WHO melaporkan sekitar 604.000 kasus baru dan 342.000 kematian pada tahun 2020. Penelitian ini mengeksplorasi kombinasi metode local adaptive threshold dan segmentasi watershed untuk meningkatkan akurasi deteksi dini kanker serviks dengan lebih akurat mengidentifikasi sel-sel yang saling tumpang tindih pada Pap Smear. Metode Local Adaptive Threshold menyesuaikan nilai ambang berdasarkan karakteristik lokal gambar, dan segmentasi watershed diaplikasikan untuk memisahkan sel-sel yang saling tumpang tindih. Kombinasi ini menunjukkan hasil yang menjanjikan dalam meningkatkan efisiensi dan akurasi skrining kanker serviks, mendukung strategi WHO untuk eliminasi kanker serviks. Namun, adopsinya menghadapi tantangan di negara berkembang karena keterbatasan sumber daya dan kesenjangan digital. Tes menggunakan K-Fold Cross Validation (5 dan 7) menunjukkan akurasi 90.93% untuk k=5, dengan rata-rata precision 97.97%, recall 49.22%, dan F1-Score 65.50%. Pada k=7, hasil sedikit meningkat dengan precision 97.99%, recall 49.24%, dan F1-Score 65.53%. Rata-rata PSNR adalah 43.4341 dB dan MSE 3.45061, menegaskan efektivitas metode.Kata Kunci: Local Adaptive Thresholding, Watershed, Cervical Cancer, Pap Smear
KLASIFIKASI PENYAKIT DAUN PADI MENGGUNAKAN SUPPORT VECTOR MACHINE BERDASARKAN FITUR MENDALAM (DEEP FEATURE) Margarita, Devina; Maulana, Hendra; Mandyartha, Eka Prakarsa
JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Vol 9, No 4 (2024)
Publisher : STKIP PGRI Tulungagung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29100/jipi.v9i4.5634

Abstract

Tanaman padi memiliki peran yang sangat penting dalam menyediakan pangan bagi populasi global. Namun, serangan hama dan bakteri dapat menghambat produksi padi dengan mengganggu proses fotosintesis dan fase generatifnya, yang berakhir pada penurunan kualitas dan kuantitas panen. Untuk mengatasi tantangan ini, penelitian ini mengusulkan pemanfaatan teknologi pemrosesan citra dan pembelajaran mesin. Metode yang digunakan mencakup Convolutional Neural Network (CNN) dengan arsitektur VGG-19 untuk mengekstraksi fitur citra, serta Support Vector Machine (SVM) dengan pendekatan pelatihan menggunakan Sequential Minimal Optimization (SMO) untuk klasifikasi. Penelitian ini terdiri dari lima tahap utama: preprocessing , pembagian data, ekstraksi fitur CNN, pelatihan SVM, dan evaluasi hasil. Berbagai skenario dengan kernel SVM yang berbeda dievaluasi, di mana hasilnya menunjukkan bahwa kernel RBF dan linear mampu mencapai akurasi tertinggi, yaitu 93,94%. Penelitian ini menunjukkan bahwa penggunaan CNN dan SVM dalam mengatasi hambatan klasifikasi citra penyakit daun pada tanaman padi, dapat memberikan hasil yang signifikan.
How HEXAD Types Influence Systemic and Finer-Grained Experiences in Gameful Educational Media: An Exploratory Study Sugiarto; Atmaja, Pratama Wirya; Mandyartha, Eka Prakarsa
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.v10i1.1985

Abstract

Education in the 21st century demands technology support, in which gameful media, such as educational games, can provide. Providing this support also requires the media to accommodate the different needs of the players, which can be identified by classifying the players’ type using HEXAD typology. However, the effect of HEXAD type classification on players’ experience in gameful media is still vague. This study aims to adress this vagueness by exploring the implementation of HEXAD in a more systemic and fine-grained manner using a playtest of an educational role-playing game. We measured the playtesters’ gameplay and learning experiences (n = 60) through a questionnaire developed based on HEXAD scale, GUESS, and EGameFlow. We also measured the correlation between the playtesters’ HEXAD types and their gameplay and learning experiences. Our analysis of the correlations uncovers exciting findings, including that the “achiever” type strongly appreciates playability features and that playability is among the essential gameplay factors for HEXAD types. We also propose design principles that can guide future research and development of the media.
KLASIFIKASI PENYAKIT KULIT BERBASIS SUPPORT VECTOR MACHINE DENGAN EKSTRAKSI FITUR ABCD RULE Wibisono, Al Danny Rian; Mandyartha, Eka Prakarsa; Al Haromainy, Muhammad Muharrom
JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Vol 10, No 1 (2025)
Publisher : STKIP PGRI Tulungagung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29100/jipi.v10i1.6039

Abstract

Penyakit kulit merupakan masalah kesehatan yang signifikan, gejala dari penyakit ini berupa gatal, nyeri, mati rasa, dan kemerahan. Penyakit ini dapat disebabkan oleh beberapa faktor seperti virus, jamur, dan mikroorganisme. Menurut data Dinas Kesehatan Surabaya tahun 2019, prevalensi penyakit kulit dan jaringan subkutan mencapai 4,53%, menjadikannya penyakit terbanyak keenam yang dialami masyarakat. Oleh sebab itu, pada penelitian ini diusulkan sebuah penelitian mengenai klasifikasi penyakit kulit menggunakan Support Vector Machine melalui analisis fitur ABCD Rule. Pada penelitian ini akan dilakukan labeling pada 5 kelas penyakit kulit yang akan digunakan sebagai data latih dan data uji melalui 7 tahapan utama yakni Pengumpulan Dataset Citra Penyakit Kulit, Pre-processing Inpaint Talea, Pre-processing Gaussian Blur dan Normalisasi Mask, Segmentasi Thresholding Otsu Bitwise, Restorasi Kontur, Ekstraksi Fitur ABCD Rule, dan klasifikasi menggunakan Support Vector Machine (SVM). Sebanyak 4 skenario pengujian dilakukan untuk menemukan model terbaik, dimana skenario pengujian melibatkan pengaturan pembagian data yang berbeda, kernel berbeda, dan parameter yang berbeda pada model Support Vector Machine (SVM). Melalui skenario tersebut didapatkan hasil terbaik, yaitu Akurasi sebesar 86,42%, Spesifisitas sebesar 96,60%, dan Sensitivitas sebesar 86,42%. Hal ini menunjukkan bahwa metode yang diusulkan memiliki kinerja yang cukup baik dalam mengklasifikasikan jenis penyakit kulit. Penelitian ini tidak hanya berpotensi dalam meningkatkan diagnosis penyakit kulit secara efisien, tetapi juga mendorong pengembangan sistem deteksi berbasis teknologi untuk mendukung layanan kesehatan kulit yang lebih terjangkau dan andal.
Penerapan Model Hybrid Convolutional Neural Network dan Long Short-Term Memory untuk Pengenalan Real-Time Sistem Isyarat Bahasa Indonesia (SIBI) Hidayat, Syahrul; Via, Yisti Vita; Mandyartha, Eka Prakarsa
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 8, No 3 (2024): Juli 2024
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v8i3.7837

Abstract

The Indonesian Sign Language System (SIBI) is an essential means of communication for the deaf and speech-impaired community in Indonesia. However, the limited public understanding of SIBI often hinders effective communication. This study develops a real-time SIBI sign recognition model to facilitate effective communication for the deaf and speech-impaired in Indonesia. The proposed method integrates a hybrid CNN-LSTM model to process the spatial and temporal information from the data. The study evaluates the model's performance on 25 types of SIBI signs. The dataset used consists of image sequences captured in real-time. Training is conducted with various parameters, including batch size, learning rate, and epochs. Model evaluation is carried out using accuracy, precision, recall, and f1-score metrics. The training and validation results show an increase in accuracy with the number of epochs: 87% at 10 epochs, 93% at 25 epochs, and 100% at 50 epochs. In real-time detection tests, the model with the image sequence dataset accurately detected SIBI signs in environments and with objects consistent with the dataset. The real-time detection program generates SIBI sign predictions in text form and sentences. The output of this research is efficient and accurate SIBI sign recognition technology. This research is expected to facilitate more effective communication for the deaf and speech-impaired community in Indonesia.
Sistem Pakar untuk Mendeteksi Awal Gangguan Kecemasan pada Remaja (Anxiety Disorder) Menggunakan Metode Forward Chaining Eriyansyah Yusuf Suwandana; Eka Prakarsa Mandyartha; Firza Prima Aditiawan
Merkurius : Jurnal Riset Sistem Informasi dan Teknik Informatika Vol. 3 No. 2 (2025): Merkurius : Jurnal Riset Sistem Informasi dan Teknik Informatika
Publisher : Asosiasi Riset Teknik Elektro dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/merkurius.v3i2.705

Abstract

Health is important for every human being. Health, education and income of each individual are three important factors that greatly influence the quality of human resources. Anxiety disorders are a significant mental health problem and can affect an individual's quality of life. Early detection of anxiety disorders is important to provide appropriate intervention and prevent the development of more serious conditions. This research aims to develop an expert system that is able to detect anxiety disorders based on symptoms reported by penggunas. This system uses a forward chaining method and a knowledge base compiled from medical literature and consultations with mental health experts. Several stages of system creation include collecting data on symptoms of anxiety disorders, preparing a knowledge base, implementing a forward chaining inference algorithm, and kuatating the system using test data and expert consultation. The expert system developed in this research is able to provide accurate initial information regarding the symptoms of anxiety disorders in adolescents based on the symptoms input by the pengguna. By utilizing a knowledge base and appropriate diagnostic rules, the system can identify key symptoms that indicate the presence of an anxiety disorder.
Optimalisasi Website Sebagai Media Branding Dan Digital Marketing Batik Lamongan Pada Produsen Titik Batik di Desa Surabayan Kabupaten Lamongan Puspaningrum, Eva Yulia; Mandyartha, Eka Prakarsa; Akbar, Fawwaz Ali
Jurnal Pengabdian Masyarakat Indonesia Vol 5 No 1 (2025): JPMI - February 2025
Publisher : CV Infinite Corporation

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jpmi.3376

Abstract

Dengan berkembangnya teknologi, para pelaku UMKM perlu mengembangkan usahanya agar tidak ketinggalan dalam memanfaatkan media digital dalam mempromosikan dan memasarkan produknya. Produsen Titik Batik merupakan salah satu UMKM di Desa Surabayan Kecamatan Sukodadi Kabupaten Lamongan yang berperan dalam melestarikan Batik Lamongan. Selama ini, Titik Batik memasarkan produknya secara tradisional melalui pameran, penjualan langsung, dan promosi dari mulut ke mulut. Cara ini hanya efektif dalam menjangkau pelanggan lokal di Kabupaten Lamongan saja. Banyak masyarakat yang belum mengenal seperti apa motif batik lamongan. Untuk meningkatkan jangkauan pasar dan menjangkau pelanggan di luar Lamongan, Titik Batik membutuhkan strategi pemasaran yang lebih luas. Meningkatnya penggunaan internet dan teknologi memberikan peluang yang sangat besar bagi UMKM seperti Titik Batik untuk menggunakan platform online sebagai media promosi dan pemasaran. Oleh karena itu, tujuan dari kegiatan pengabdian masyarakat ini adalah membantu Titik Batik dalam melakukan promosi secara digital dengan menerapkan website sebagai media agar produk lebih diketahui oleh konsumen lebih luas dan meningkatkan penjualan. Metode dari kegiatan ini yaitu membuat sebuah website sebagai media branding dan marketing digital dan kemudian memberikan pelatihan sebagai transfer knowledge dalam penggunaan website. Hasil dari kegiatan ini adalah sebuat website Titik Batik yang dapat digunakan sebagai media branding dan marketing yang berisi mengenai identitas dari Titik Batik, Produk serta Portofolio dari Konsumen Batik Lamongan. Hasil lainnya yaitu Batik Lamongan semakin dikenal karena informasi tentang Batik Lamongan dapat di akses oleh masyarakat dimanapun dan kapanpun. Hal ini berdampak pada keberlanjutan UMKM Produsen Titik Batik adalam memasarkan Batik Lamongan kepada masyaraka serta adanya peningkatan penjualan menjadi lebih luas.
The Trade-off between Energy-Accuracy in the IoT-based Activity Monitoring System Sri Indrawanti, Annisaa; Mandyartha, Eka Prakarsa
IJCONSIST JOURNALS Vol 6 No 2 (2025): March
Publisher : International Journal of Computer, Network Security and Information System

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33005/ijconsist.v6i2.131

Abstract

Activity monitoring system is used in many fields such patient’s activity monitoring system for self-quarantine in their home. The IoT- based activity monitoring system uses the limited resources (e.g., bandwidth, battery and memory) for monitoring the user’s activity. The limited resources (such as battery) provide the limited lifetime battery in activity monitoring system. By resource efficiency, it will extend the battery lifetime. Resource efficiency is achieved by adaptively reporting user activity depending on the level of the user’s activity emergency. But, when the user’s activity reporting data is based on the emergency level, then it reduces the data detail and its activity recognition accuracy. So, we develop energy-savings techniques for user’s activity reporting and analyze the effect of energy-savings techniques to the accuracy of activity recognition using different methods. The results show the energy-savings techniques can save battery life up to 8%, bandwidth up to 146,5 bytes/sec and memory up to 2,8% compared to non-energy saving technique. But the energy-saving techniques give less accuracy in the four different activity recognition methods up to 11% in average.
Co-Authors Achmad Junaidi Agung Mustika Rizki, Agung Mustika Agung Subekti, Mohamad Rafli Agustin, Risda Rosdiana Akbar, Fawwaz Ali Anggraini Puspita Sari Ani Dijah Rahajoe Basuki Rahmat Chastine Fatichah Eliza, Nidya Eriyansyah Yusuf Suwandana Eva Yulia Puspaningrum Fathuddin, Muhammad Abdul Hafizh Fedianto, Muhammad Helmi Satria Firza Prima Aditiawan Gusti Eka Yuliastuti Hermadiputri, Firdausa Yasmin indrawanti, annisaa sri Intan Yuniar Purbasari Isnaini, Frisda Dita Kamila, Shaffa Cahya kristanti, beni tiyas Lutfia, Qonita Margarita, Devina Maulana, Hendra Maulana, Raihan Thobie Nabil Muchammad Kurniawan Muhammad Muharrom Al Haromainy Nurlaili, Afina Lina Pratama Wirya Atmaja Ramadhan, Ike Reyhan Jarsi Yoga Rizal Setya Perdana Sadrai, Maharani Putri Serlynda Dwi Rosalina Sri Indrawanti, Annisaa Sri Wibawani, Sri Subairi Subairi Sugiarto Syahrul Hidayat Taufikurrahman Taufikurrahman Utami, Hapsari Wiji Wibisono, Al Danny Rian Yisti Vita Via Yudha K., Dhian Satria