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All Journal International Journal of Electrical and Computer Engineering Seminar Nasional Aplikasi Teknologi Informasi (SNATI) Jurnal Teknologi Informasi dan Ilmu Komputer International Journal of Advances in Intelligent Informatics Journal of Information Systems Engineering and Business Intelligence Indonesia Symposium on Computing Indonesian Journal on Computing (Indo-JC) JOIV : International Journal on Informatics Visualization Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) JURNAL MEDIA INFORMATIKA BUDIDARMA Jurnal Sisfokom (Sistem Informasi dan Komputer) KOMIK (Konferensi Nasional Teknologi Informasi dan Komputer) JURIKOM (Jurnal Riset Komputer) YUME : Journal of Management TEKNOLOGIA TEKTRIKA - Jurnal Penelitian dan Pengembangan Telekomunikasi, Kendali, Komputer, Elektrik, dan Elektronika Building of Informatics, Technology and Science JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Journal of Data Science and Its Applications Jurnal Sistem Komputer dan Informatika (JSON) Journal of Applied Data Sciences Mosharafa: Jurnal Pendidikan Matematika Indonesian Journal of Social Science Research Open Science and Technology eProceedings of Engineering Innovative: Journal Of Social Science Research AMMA : Jurnal Pengabdian Masyarakat Jurnal INFOTEL
Adiwijaya
Universitas Telkom
Agriculture, Biological Sciences & Forestry Humanities Automotive Engineering 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 Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Mathematics Mechanical Engineering Nursing Public Health Social Sciences Other

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Skema Penyembunyian Teks Terkompresi Adaptive Huffman pada Citra Digital Menggunakan Kuantisasi Berbasis Graf Melanida Tagari; Adiwijaya Adiwijaya; Gia Septiana
Indonesia Symposium on Computing Indonesia Symposium on Computing 2015
Publisher : Indonesia Symposium on Computing

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Abstract

Jaringan komputer dan internet semakin banyak digunakan untuk aktivitas pengiriman data. Namun, tidak ada jaminan bahwa jaringan komputer dan internet yang digunakan sebagai media pengiriman data ini aman dari pihak ketiga yang tidak memiliki hak akses terhadap data tersebut. Berbagai teknik telah dikembangkan untuk melindungi data dari pengaksesan secara ilegal. Salah satu diantaranya yaitu dengan menyisipkan/menyembunyikan data tersebut ke dalam media cover. Pada penelitian ini, implementasi penyembunyian data memanfaatkan kuantisasi berbasis graf, yaitu menggunakan Vector Quantization (VQ) dan pewarnaan graf dengan menggunakan Genetic Algorithm. Untuk meningkatkan kapasitas penyisipan, data dikompres terlebih dahulu dengan menggunakan Adaptive Huffman sebelum penyisipan dilakukan. Hasil pengujian menunjukkan bahwa skema ini dapat menghasilkan kapasitas penyisipan sebanyak 9000 bit atau sekitar 1800 karakter, dengan nilai PSNR 27,5054 db.  
Skema Penyembunyian Teks Terkompresi Arithmetic Coding pada Citra Digital Menggunakan Kuantisasi Berbasis Graf Elza Oktaviana; Adiwijaya Adiwijaya; Gia Septiana
Indonesia Symposium on Computing Indonesia Symposium on Computing 2015
Publisher : Indonesia Symposium on Computing

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Abstract

Dewasa ini, komunikasi melalui aplikasi, jaringan dan internet membutuhkan keamanan dari serangan cyber, terutama komunikasi yang melibatkan transmisi data. Tidak sedikit algoritma telah dikembangkan untuk mengatasi penyadapan atau pengaksesan secara ilegal tersebut. Ilmu dan Seni menyembunyikan data ke media digital merupakan salah satu cara yang biasanya digunakan untuk penyamaran saat melakukan komunikasi yang melibatkan transmisi data. Teknik ini bekerja dengan cara menyisipkan data atau informasi yang bersifat pribadi pada suatu media sehingga data atau informasi yang disisipkan ke media tersebut tidak terlihat secara jelas. Penelitian ini mengajukan sebuah skema penyembunyian data berupa teks pada citra digital dengan menggunakan kuantisasi berbasis graf. Skema ini bekerja dengan cara menyisipkan teks pada suatu graf yang merupakan representasi dari hasil kuantisasi citra digital yang merupakan media penyisipannya. Untuk meningkatkan kapasitas penyisipan, skema ini memanfaatkan algoritma Arithmetic Coding untuk kompresi teks yang akan disisipi, dengan tetap memperhatikan kualitas dari citra hasil penyisipan. Hasil penelitian menunjukkan tingkat keberhasilkan skema ini berada pada saat berhasil menyisipkan sekitar 7255 bit data rahasia dengan PSRN citra tersisipi bernilai 28,5324db.      
Algoritma Pengenalan Ucapan Huruf Hijaiyah Bertanda Baca Menggunakan Mel Frequency Cepstral Coefficients dan Hidden Markov Model Andrian Fakhri; Adiwijaya .; Untari Novia Wisesty
Indonesia Symposium on Computing Indonesia Symposium on Computing (IndoSC) 2016
Publisher : Indonesia Symposium on Computing

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Abstract

Speech recognition merupakan sebuah metode yang dapat mengubah sinyal-sinyal suara ke dalam bentuk data digital agar dapat dipahami computer. Sistem pengenalan suara terdiri dua bagian utama yaitu proses ekstraksi ciri dan klasifikasi. Pada penelitian ini penulis menggunakan metode MelFrequency Ceptral Coefficient (MFCC) pada proses ekstraksi ciri bertujuan untuk mendapatkan informasi penting yang terkandung dalam sinyal suara, informasi tersebut akan merepresentasikan karakteristik khusus dari suatu huruf atau kata yang diucapkan. Untuk proses klasifikasi dan pembentukan model penulis menggunakan metode Hidden Markov Model (HMM), setiap data yang dimodelkan menggunakan metode ini akan menghasilkan model HMM, maka jumlah model akan sama dengan jumlah data yang di training. Sistem speech recognition juga dapat diterapkan pada sistem pengenalan ucapan huruf hijaiyah. Setelah penulis melakukan pengujian terhadap sistem dengan menggunakan 128 codebook dan 7 states untuk mengenali 168 huruf yang berbeda didapat tingkat akurasi tertinggi 41%. Dan saat pengujian untuk mengenali 28 huruf akurasi tertinggi yang mencapai 57%.
Learning Struktur Bayesian Networks menggunakan Novel Modified Binary Differential Evolution pada Klasifikasi Data Azmi Hafizha Rahman Zainal Arifin; Muhammad Syahrul Mubarok; Adiwijaya Adiwijaya
Indonesia Symposium on Computing Indonesia Symposium on Computing (IndoSC) 2016
Publisher : Indonesia Symposium on Computing

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Abstract

Bayesian Networks merupakan salah satu metode pemodelan probabilitas pada Probabilistic Graphical Models. Bayesian Networks terdiri dari nodes yang merepresentasikan variabel pada masalah yang dikaji dan edges yang merepresentasikan relasi dependensi antar node. Pada masalah yang sederhana, struktur Bayesian Networks biasanya ditentukan oleh ahli di bidang masalah tersebut atau berasal dari intuisi alami manusia. Perancangan struktur Bayesian Networks secara manual ini akan sulit dilakukan apabila kasus yang dikaji merupakan kasus yang kompleks yang memiliki sangat banyak node dan sangat banyak kemungkinan edges yang menghubungkannya. Pada penilitian ini, dilakukan pengujian dan analisa terhadap proses pencarian struktur Bayesian Networks menggunakan algoritma Novel Modified Binary Differential Evolution. Novel Modified Binary Differential Evolution merupakan algoritma optimasi permasalahan diskrit dengan representasi solusi berbentuk biner yang merupakan pengembangan dari algoritma Differential Evolution. Hasil pengujian terhadap data Alarm, Asia, Carpo, Insurance, dan Water masing-masing diperoleh skor BDeu sebesar -1973.77, -243.68, -2450.54, -2024.17, dan -1621.90.
Penerapan Question Answering System Pada Pembahasan Agama Islam Dengan Pendekatan Metode Pattern Based Rosyadi, Ramadhana; Al-Faraby, Said; Adiwijaya, Adiwijaya
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 2, No 4 (2018): Oktober 2018
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v2i4.949

Abstract

Islam has 25 prophets as guidelines for human life, documents containing information about the stories of the lives of the prophets during their lifetime. This study aims to build a more specific question and answer system by generating relevant answers not in the form of documents. Question Answering System is able to overcome problems in the Question and answer system, information retrieval systems where the answers issued are correct with responses to requests submitted, not in the form of documents that may contain answers. This study uses the Pattern Based method as extracting sentence pieces which are the answers to find answers that match the patterns that have been made. The selection of datasets causes a number of questions that can be submitted to be limited to information stored in the data itself. Besides that, questions are also limited in the form of Question words that are Factoid, namely Who, when, where, what and how. Accuracy results obtained using the Pattern Based method on Question Answering System are 39.36%.
Identifikasi Citra berdasarkan Gigitan Ular menggunakan Metode Active Contour Model dan Support Vector Machine Dewangga, Dhiya Ulhaq; Adiwijaya, Adiwijaya; Utama, Dody Qori
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 3, No 4 (2019): Oktober 2019
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v3i4.1409

Abstract

Tropical countries have a warm and humid climate are suitable habitat for the lives of reptile animals, especially snakes. Snakes are a type of reptile animal that is widely found in tropical countries, especially in Indonesia. The worst thing that happens when meeting a snake is the bite of snake. If the bite comes from a venomous snake it can cause a more serious problem than the bite from non-venomous snake is, which can cause paralysis, disability, and the worst is death. According to the WHO (World Health Organization) an estimated 5.4 million people are bitten by snakes each year with almost 2.7 million being bitten by venomous snakes and get affected symptoms. Around 81,000 to 138,000 people die every year. This research uses image processing technic to make the identification system of snake bites whether venomous or non-venomous. The method used in this system is Active Contour Model and Support Vector Machine. By using these methods, the highest accuracy is obtained in the best of SVM kernel, on RBF kernel and Polynomial kernel.
Deteksi Kanker Berdasarkan Klasifikasi Data Microarray Menggunakan Least Absolute Shrinkage and Selection Operator dan Functional Link Neural Network Putri, Dinda Rahma; Adiwijaya, Adiwijaya; Sibaroni, Yuliant
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 4, No 4 (2020): Oktober 2020
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v4i4.2349

Abstract

Cancer is a dangerous disease that arises from the conversion of normal cells into tumor cells that develop into malignant tumors. According to WHO, cancer is the second deadliest disease in the world. About 70% of cancer deaths occur in low and middle income countries such as Indonesia. Cancer can be detected by recognizing patterns of expression of human genes. DNA Microarray is a technology that can find patterns of gene expression in a variety of different conditions by means of microarray data classification. Microarray data has very large dimensions and needs to be reduced in order to obtain informative genes to detect cancer optimally. In this study, the authors use the Least Absolute Shrinkage and Selection Operator (LASSO) as a feature selection method to reduce data dimensions and Functional Link Neural Network (FLNN) as a classification method with Legendre Polynomial base functions. With a series of processes that have been carried out, obtained an average accuracy of 86.41% and an average f1-score of 81.83%
Perbandingan CART dan Random Forest untuk Deteksi Kanker berbasis Klasifikasi Data Microarray Riska Chairunisa; Adiwijaya; Widi Astuti
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 4 No 5 (2020): Oktober 2020
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (434.683 KB) | DOI: 10.29207/resti.v4i5.2083

Abstract

Cancer is one of the deadliest diseases in the world with a mortality rate of 57,3% in 2018 in Asia. Therefore, early diagnosis is needed to avoid an increase in mortality caused by cancer. As machine learning develops, cancer gene data can be processed using microarrays for early detection of cancer outbreaks. But the problem that microarray has is the number of attributes that are so numerous that it is necessary to do dimensional reduction. To overcome these problems, this study used dimensions reduction Discrete Wavelet Transform (DWT) with Classification and Regression Tree (CART) and Random Forest (RF) as classification method. The purpose of using these two classification methods is to find out which classification method produces the best performance when combined with the DWT dimension reduction. This research use five microarray data, namely Colon Tumors, Breast Cancer, Lung Cancer, Prostate Tumors and Ovarian Cancer from Kent-Ridge Biomedical Dataset. The best accuracy obtained in this study for breast cancer data were 76,92% with CART-DWT, Colon Tumors 90,1% with RF-DWT, lung cancer 100% with RF-DWT, prostate tumors 95,49% with RF-DWT, and ovarian cancer 100% with RF-DWT. From these results it can be concluded that RF-DWT is better than CART-DWT.
Implementation of Naïve Bayes and Gini Index for Spam Email Classification Fikri Rozan Imadudin; Danang Triantoro Murdiansyah; Adiwijaya
Indonesia Journal on Computing (Indo-JC) Vol. 6 No. 1 (2021): April, 2021
Publisher : School of Computing, Telkom University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34818/INDOJC.2021.6.1.452

Abstract

Email is a medium of information that is still frequently used by people today. At the moment email still has an endless problem that is spam email. Spam email is an email that can pollute, damage or disturb the recipient. In this study, we show the performance and accuracy of Multinomial Naïve Bayes (MNNB) and Complete Gini-Index Text (GIT) for use in spam email filtering. In this study, we used 6 cross-validations as testers for the built classification machines. We found that the average yield can exceed Multinomial Naïve Bayes without using feature selection which only uses 80000 features with a difference of 0.39%. Feature selection also increases speed during classification and can reduce features that are less relevant to the category to be classified.
Comparative analysis of ReliefF-SVM and CFS-SVM for microarray data classification Mochamad Agusta Naofal Hakim; Adiwijaya Adiwijaya; Widi Astuti
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 4: August 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i4.pp3393-3402

Abstract

Cancer is one of the main causes of death in the world where the World Health Organization (WHO) recognized cancer as among the top causes of death in 2018. Thus, detecting cancer symptoms is paramount in order to cure and subsequently reduce the casualties due to cancer disease. Many studies have been developed data mining approaches to detect symptoms of cancer through a classifying human gene data expression. One popular approach is using microarray data based on DNA. However, DNA microarray data has many dimensions that can have a detrimental effect on the accuracy of classification. Therefore, before performing classification, a feature selection technique must be used to eliminate features that do not have important information to support the classification process. The feature selection techniques used were ReliefF and correlation-based feature selection (CFS) and a classification technique used in this study is support vector machine (SVM). Several testing schemes were applied in this analysis to compare the performance of ReliefF and CFS with SVM. It showed that the ReliefF outperformed compared with CFS as microarray data classification approach.
Co-Authors A Rakha Ahmad Taufiq Abu Bakar, Muhammad Yuslan Ade Iriani Sapitri Ade Romadhony Ade Sumiahadi, Ade Adhitia Wiraguna Adhitia Wiraguna Aditya Arya Mahesa Adnan Imam Hidayat Adwin Rahmanto Afrian Hanafi Al Faraby, Said Al Mira Khonsa Izzaty Alfian Akbar Gozali Alvi Syah Amalya Citra Pradana Amir Andi Ahmad Irfa ANDI FUTRI HAFSAH MUNZIR Andina Kusumaningrum Andri Saputra Andrian Fakhri Andriyan B Suksmono Anggitha Yohana Clara Aniq Atiqi Aniq Atiqi Rohmawati Anisa Salama Annas Wahyu Ramadhan Annisa Adistania Annisa Aditsania Antika Putri Permata Wardani Aras Teguh Prakasa Ardiansyah, Yusfi Astrid Frillya Septiany Astrima Manik Aziz, Muhammad Maulidan Azmi Hafizha Rahman Zainal Arifin Bambang Riyanto T. Bayu Julianto Bayu Munajat Bayu Munajat Bayu Rahmat Setiaji Bernadus Seno Aji Bernadus Seno Aji Bintang Peryoga Bisma Pradana Brama Hendra Mahendra Chiara Janetra Cakravania Clarisa Hasya Yutika D. R. Suryandari Dana Sulistiyo Kusumo Danang Triantoro Danang Triantoro Murdiansyah Daniel Tanta Christopher Sirait Dany Dwi Prayoga Dany Dwi Prayoga Della Alfarydy Akbar Deni Saepudin Denny Alriza Pratama Desi Sitompul Dewangga, Dhiya Ulhaq Dian Chusnul Hidayati Didi Rosiyadi Didit Adytia Dinda Karlia Destiani Dody Qori Utama Dody Qory Utama Dwi Yanita Apriliyana Dwi Yanita Apriliyana Dwifebri, Mahendra Eko Darwiyanto Eliza Jasin Elza Oktaviana Elza Oktaviana Endro Ariyanto Ergon Rizky Perdana Purba F. A. Yulianto Fachri Pane, Syafrial Fahmi Salman Nurfikri Faris Alfa Mauludy Faris Alfa Mauludy Farudi Erwanda Farudi Erwanda Fathur Rohman Fathurrohman Elkusnandi Fhira Nhita Fikri Rozan Imadudin Firda A. Ma’ruf Firdausi Nuzula Zamzami Firly Juanita Surahman Fuad Ash Shiddiq Gde Agung Brahmana Suryanegara Gheartha, I Gusti Bagus Yogiswara Ghozy Ghulamul Afif Gia Septiana Gia Septiana Gia Septiana Gilang Rachman Perdana Gilang Rachman Perdana Gilang Titah Ramadhani Grace Tika Guntoro Guntoro Guntoro Guntoro Guntoro Guntoro Hadyan Arif Hafidudin . Hafizh Fauzan Hafizh Fauzan Hendro Prasetyo Henri Tantyoko Honakan Honakan I Kadek Haddy W. I Made Riartha Prawira I.G.N.P.Vasu Geramona Ilham Kurnia Syuriadi Ilham Yunirakhman Imadudin, Fikri Rozan Imam Prayoga Indriani Indriani Irene Yulietha Irma Irma Irma Palupi Irwinda Famesa Iyon Priyono Jendral Muhamad Yusuf Zia Ul Haq Jenepte Wisudawati Simanullang K, Kasnaeny Kamal Hasan Mahmud Kemas Muslim Lhaksmana Kemas Rahmat Saleh Raharja Kemas Rahmat Saleh Wiharja Kurnia C Widiastuti Kurniawan W. Handito Laila Putri Lalu Gias Irham Lisa Marianah Lisa Marianah Luke Manuel Daely Mahendra Dwifebri P Mahendra Dwifebri Purbolaksono Mahmud Dwi Sulistiyo Melanida Tagari Melanida Tagari Michael Sianturi Milah Sarmilah Moc. Arif Bijaksana Mochamad Agusta Naofal Hakim Mochammad Naufal Rizaldi Mohamad Irwan Afandi Mohamad Mubarok Mohamad Syahrul Mubarok Mohamad Syahrul Mubarok Mohammad Syahrul Mubarok Monica Triyani Muhammad Afianto Muhammad Enzi Muzakki Muhammad Fauzan Muhammad Feridiansyah Muhammad Ghufran Muhammad Irvan Tantowi Muhammad Kenzi Muhammad Mubarok Muhammad Mujaddid Muhammad Naufal Mukhbit Amrullah Muhammad Nurjaman Muhammad Shiddiq Azis Muhammad Shiddiq Azis Muhammad Surya Asriadie Muhammad Syahrul Mubarok Muhammad Yuslan Abu Bakar Nanda Prayuga Nida Mujahidah Azzahra Nida Mujahidah Azzahra Niken Dwi Wahyu Cahyani Novelty Octaviani Faomasi Daeli Novia Russelia Wassi Nuklianggraita, Tita Nurul Nur Ghaniaviyanto Ramadhan Oscar Ramadhan Pinem, Joshua Pratama Dwi Nugraha Preddy Desmon Purbalaksono, Mahendra Dwifebri Putri, Dinda Rahma Putri, Dita Julaika Raihana Salsabila Darma Wijaya Rendi Kustiawan Reynaldi Ananda Pane Riche Julianti Wibowo Riko Bintang Purnomoputra Riska Chairunisa Rizki Syafaat Amardita Rizky Pujianto Rizma Nurviarelda Roberd Saragih Rosyadi, Ramadhana Said Faraby Satria Mandala Sekar Kinasih Semeidi Husrin Sheila Annisa Shidqi Aqil Naufal Shuni’atul Ma’wa Sigit Bagus Setiawan St.Sukmawati S. Sugeng Hadi Wirasna Suriyanti Suriyanti Syafrial Fachri Pane, Syafrial Fachri Syahrizal Rizkiana Rusamsi Syam, Mukhlisah Syifa Khairunnisa Talitha Kayla Amory Tati LR Mengko Tesha Tasmalaila Hanif Timami Hertza Putrisanni Tita Nurul Nuklianggraita Triyani, Monica Try Moloharto Untari Novia Wisesty Untari Wisesty Untari. N. Wisesty Untary Novia Wisesty Vina Mutiara Purnama Warih Maharani Widi Astuti Widi Astuti Widi Astuti Winda Christina Widyaningtyas Wisnu Adhi Pradana Yana Meinitra Wati Yoga Widi Pamungkas Yuliant Sibaroni Zahra Putri Agusta Zakia Firdha Razak Zulfikar Fauzi