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Darmawijoyo, Darmawijoyo

Universitas Sriwijaya

Author-ID : 250154

Computer Science & IT Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering Languange, Linguistic, Communication & Media Library & Information Science Mathematics Social Sciences Other

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Pendampingan Guru Matematika Sekolah Menengah dalam Pembuktian Matematika Hartono, Yusuf; Darmawijoyo, Darmawijoyo; Somakim, Somakim; Puspita, Fitri Maya; Sari, Novita; Simarmata, Ruth Helen; Kurniadi, Elika
MATAPPA: Jurnal Pengabdian Kepada Masyarakat Volume 4 Nomor 1 Tahun 2021
Publisher : STKIP Andi Matappa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31100/matappa.v4i1.943

Tujuan kegiatan pengabdian ini adalah untuk mendampingi guru dalam melakukan pembuktian matematika. Metode pelaksanaan kegiatan yaitu presentasi dan pendampingan yang terdiri dari tiga tahapan yaitu persiapan, pelaksanaan, dan penyusunan laporan. Pelaksanaan kegiatan dilakukan sebanyak tiga kali pertemuan tatap maya meliputi pemberian materi dari narasumber dan presentasi tugas oleh peserta. Data yang diperoleh dari kegiatan ini adalah berupa persepsi guru terhadap bukti matematika, pendapat peserta terhadap kegiatan, dan dokumentasi tugas peserta yang dianalisis secara deskriptif kuantitatif. Hasil yang diperoleh yaitu persepsi guru tentang bukti matematika meningkat, pendapat peserta terhadap kegiatan ini sangat baik, dan meningkatnya kemampuan guru dalam pembuktian matematika.

Intrusion detection with deep learning on internet of things heterogeneous network Sharipuddin Sharipuddin; Benni Purnama; Kurniabudi Kurniabudi; Eko Arip Winanto; Deris Stiawan; Darmawijoyo Hanapi; Mohd. Yazid Idris; Rahmat Budiarto
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 10, No 3: September 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v10.i3.pp735-742

The difficulty of the intrusion detection system in heterogeneous networks is significantly affected by devices, protocols, and services, thus the network becomes complex and difficult to identify. Deep learning is one algorithm that can classify data with high accuracy. In this research, we proposed deep learning to intrusion detection system identification methods in heterogeneous networks to increase detection accuracy. In this paper, we provide an overview of the proposed algorithm, with an initial experiment of denial of services (DoS) attacks and results. The results of the evaluation showed that deep learning can improve detection accuracy in the heterogeneous internet of things (IoT).

Network anomaly detection research: a survey Kurniabudi Kurniabudi; Benni Purnama; Sharipuddin Sharipuddin; Darmawijoyo Darmawijoyo; Deris Stiawan; Samsuryadi Samsuryadi; Ahmad Heryanto; Rahmat Budiarto
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 7, No 1: March 2019
Publisher : IAES Indonesian Section

Data analysis to identifying attacks/anomalies is a crucial task in anomaly detection and network anomaly detection itself is an important issue in network security. Researchers have developed methods and algorithms for the improvement of the anomaly detection system. At the same time, survey papers on anomaly detection researches are available. Nevertheless, this paper attempts to analyze futher and to provide alternative taxonomy on anomaly detection researches focusing on methods, types of anomalies, data repositories, outlier identity and the most used data type. In addition, this paper summarizes information on application network categories of the existing studies.

Important Features of CICIDS-2017 Dataset For Anomaly Detection in High Dimension and Imbalanced Class Dataset Kurniabudi Kurniabudi; Deris Stiawan; Darmawijoyo Darmawijoyo; Mohd Yazid Bin Idris; Bedine Kerim; Rahmat Budiarto
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 9, No 2: June 2021
Publisher : IAES Indonesian Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52549/ijeei.v9i2.3028

The growth in internet traffic volume presents a new issue in anomaly detection, one of which is the high data dimension. The feature selection technique has been proven to be able to solve the problem of high data dimension by producing relevant features. On the other hand, high-class imbalance is a problem in feature selection. In this study, two feature selection approaches are proposed that are able to produce the most ideal features in the high-class imbalanced dataset. CICIDS-2017 is a reliable dataset that has a problem in high-class imbalance, therefore it is used in this study. Furthermore, this study performs experiments in Information Gain feature selection technique on the imbalance class datasaet. For validation, the Random Forest classification algorithm is used, because of its ability to handle multi-class data. The experimental results show that the proposed approaches have a very surprising performance, and surpass the state-of-the-art methods.

Enhanced Deep Learning Intrusion Detection in IoT Heterogeneous Network with Feature Extraction Sharipuddin Sharipuddin; Eko Arip Winanto; Benni Purnama; Kurniabudi Kurniabudi; Deris Stiawan; Darmawijoyo Hanapi; Mohd Yazid bin Idris; Bedine Kerim; Rahmat Budiarto
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 9, No 3: September 2021
Publisher : IAES Indonesian Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52549/.v9i3.3134

Heterogeneous network is one of the challenges that must be overcome in Internet of Thing Intrusion Detection System (IoT IDS). The difficulty of the IDS significantly is caused by various devices, protocols, and services, that make the network becomes complex and difficult to monitor. Deep learning is one algorithm for classifying data with high accuracy. This research work incorporated Deep Learning into IDS for IoT heterogeneous networks. There are two concerns on IDS with deep learning in heterogeneous IoT networks, i.e.: limited resources and excessive training time. Thus, this paper uses Principle Component Analysis (PCA) as features extraction method to deal with data dimensions so that resource usage and training time will be significantly reduced. The results of the evaluation show that PCA was successful reducing resource usage with less training time of the proposed IDS with deep learning in heterogeneous networks environment. Experiment results show the proposed IDS achieve overall accuracy above 99%.

Time Efficiency on Computational Performance of PCA, FA and TSVD on Ransomware Detection Benni Purnama; Deris Stiawan; Darmawijoyo Hanapi; Mohd. Yazid Idris; Sharipuddin Sharipuddin; Nurul Afifah; Rahmat Budiarto
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 10, No 1: March 2022
Publisher : IAES Indonesian Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52549/ijeei.v10i1.3481

Ransomware is able to attack and take over access of the targeted user'scomputer. Then the hackers demand a ransom to restore the user's accessrights. Ransomware detection process especially in big data has problems interm of computational processing time or detection speed. Thus, it requires adimensionality reduction method for computational process efficiency. Thisresearch work investigates the efficiency of three dimensionality reductionmethods, i.e.: Principal Component Analysis (PCA), Factor Analysis (FA) andTruncated Singular Value Decomposition (TSVD). Experimental results onCICAndMal2017 dataset show that PCA is the fastest and most significantmethod in the computational process with average detection time of 34.33s.Furthermore, result of accuracy, precision and recall also show that the PCAis superior compared to FA and TSVD.

PENERAPAN PEMBELAJARAN PEMODELAN MATEMATIKA MENGGUNAKAN PENDEKATAN KONSTRUKTIVISME TERHADAP KEMAMPUAN PEMECAHAN MASALAH UNTUK SISWA KELAS VIII SMP Febi Renico Selvia; Darmawijoyo; Muhammad Yusuf
Aksioma Vol. 3 No. 1 (2014)
Publisher : Universitas Tadulako

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22487/aksioma.v3i1.15

Abstrak: Penelitian ini merupakan penelitian deskriptif yang bertujuan untuk mengetahui bagaimana aktivitas belajar siswa selama pembelajaran pemodelan matematika menggunakan pendekatan konstruktivisme dan untuk mengetahui bagaimana kemampuan pemecahan masalah siswa setelah mengikuti pembelajaran pemodelan matematika menggunakan pendekatan konstruktivisme di kelas VIII SMP. Subjek penelitian ini adalah siswa kelas VIII.1 SMP Negeri 5 Palembang tahun pelajaran 2013/2014 yang berjumlah 36 orang siswa. Teknik pengumpulan data yang digunakan adalah observasi, tes, video rekaman, dan wawancara. Dari hasil analisis data dapat disimpulkan bahwa penerapan pemodelan matematika menggunakan pendekatan konstruktivisme berkategori baik dengan rata-rata sebesar 71,30 dan rata-rata kemampuan pemecahan masalah matematika siswa yang diperoleh sebesar 74,54 juga berkategori baik. Kata-kata kunci: pemodelan matematika, konstruktivisme

Pembelajaran Pecahan dengan Menggunakan Manik Susun Kiki Rizkiah Pertiwi; Zulkardi Zulkardi; Darmawijoyo Darmawijoyo
JRPM (Jurnal Review Pembelajaran Matematika) Vol. 2 No. 2 (2017)
Publisher : Department of Mathematics Education, Faculty of Tarbiyah and Teacher Training, UIN Sunan Ampel Surabaya

This study aimed to design a learning path which can help students to understand fractions based on Pendidikan Matematika Realistik Indonesia (PMRI) approach. The subject is 30 students of 4th grade of PP Qodratullah Langkan. Method of this research is design research, Hypothetical Learning Trajectory (HLT) developed from learning activity series using context stacked beads. The implementation of this research in 3 stages: preparing the design experiment, conducting the learning (the design experiment), and retrospective analysis in order to contribute to Local Instruction Theory support to students in studying fractions. The designed Hypothetical Learning Trajectory (HLT) is then compared to Actual Learning Trajectory (ALT) students during the learning to analyze whether students learn or not from what has been designed in the learning sequence. A retrospective analysis of the implementation of learning suggests that the use of the stacking bead context can help students understand fractions.

Kemajuan Belajar Siswa pada Penjumlahan Bilangan Desimal Menggunakan Pengukuran Berat Leni Maimuna; Darmawijoyo Darmawijoyo; Ely Susanti
JRPM (Jurnal Review Pembelajaran Matematika) Vol. 3 No. 1 (2018)
Publisher : Department of Mathematics Education, Faculty of Tarbiyah and Teacher Training, UIN Sunan Ampel Surabaya

This study was aimed at describing the student’ learning progress on decimals addition by a set of learning activitis based on Indonesian Realistic Mathematics Education. This research method is design research which contain three stages, namely: preliminary design, design experiment and retrospective analysis. Hypothetical Learning Trajectory (HLT) has been designed to play an important role as learning design and research instrument. HLT was tested to 30 fourth grade students. The data were collected through interview, observation, and field notes. The findings of the research showed that this instructional design could stimulate students in the introduction of one digit decimal through the result of weight measurement, the use of the model that the students make themselves (model of) to describe the measurement results at the second level, and marking the result of the measurement to the number line and continued by describing the process of decimals addition from the measurement activity to the number line in the more formal level. Furthermore at the formal level, students are able to solve the problem of the decimals addition using the correct procedure that is the place value rule.

DESAIN PEMBELAJARAN MATERI FUNGSI LINIER MENGGUNAKAN PEMODELAN MATEMATIKA Dyah Rahmawati; Darmawijoyo Darmawijoyo; Hapizah Hapizah
AKSIOMA: Jurnal Program Studi Pendidikan Matematika Vol 7, No 1 (2018)
Publisher : UNIVERSITAS MUHAMMADIYAH METRO

This research is aimed to create a learning trajectory of linear functions concept using mathematical modeling. The applied learning approach is the Model Eliciting Activities (MEAs). Design research was chosen as the research method consisting of three main phases; preliminary design, teaching experiments, and retrospective analysis. This research was conducted in class X in a public senior high school in Palembang. The result showed the design activity can encourage students to look at the form of modeling (charts/schemes/equation) that students make themself. Through steps on mathematical modeling takes students into the definition of the power to a linear functions, so the students had the idea in providing recommendations to solve real problems in life.

Co-Authors Abdul Harris ADI SAPUTRO Ahmad Fali Oklilas Ahmad Heryanto Aisyah Turidho Albertus Edward Mintaria Amarta, Nadiati Andi Harpeni Dewantara Andi Harpeni Dewantara, Andi Harpeni Anggria Septiani Mulbasari Anggria Septiani Mulbasari, Anggria Septiani ANISAH Anisah Anisah Apriana Sari Ruslan Ardiansyah, Hijir Azka, Dea Alvionita Azma, Tiara Rodiana B Santoso Bambang Riyanto Bambang Riyanto Bedine Kerim Bedine Kerim Billy Suandito C Hiltrimartin Cecil Hiltrimartin Charmila, Ninik Deris Stiawan Desi Permata Sari Devi Emilya Dhany Fachrudin, Achmad Dian Novita Dina Octaria Dinal Ulya Sukiman Dwi Budi Santoso Dwi Febianti Dyah Rahmawati EDWAR Eka Fitri Puspa Sari, Eka Fitri Puspa Eko Arip Winanto Ely Susanti Evy Yosita Silva Febi Renico Selvia Firsta, Risa Rahmatia Fitri Maya Puspita Frans van Galen Frans van Galen Hadi Purnawan Satria Hapizah Hardiyanti Indriani Harris, Abdul Hartatiana Hartatiana Hazlita Hazlita, Hazlita Hendra Pratama Idris, Mohd. Yazid Idris, Mohd. Yazid Indah Nur Hijriyah Indaryanti Indaryanti Irkham Ulil Albab Jaap den Hertog Jonny Simanullang Julaiha, Ellah Kairuddin . Kamaliyah Kamaliyah Khairun Nisak Kiki Rizkiah Pertiwi Kiki Rizkiah Pertiwi, Kiki Rizkiah Kurniabudi, Kurniabudi Kurniadi, Elika Leni Maimuna Leonardo Jonathan Shinariko Lestaria N, Yunika Lestariningsih Lestariningsih Lestariningsih Lestariningsih Lintang Fitra Utami Maimuna, Leni Maria Mareta Simalango marlina, eli Maya Saftari Meryansumayeka Meryansumayeka Mintaria, Albertus Edward Mira Nurhayati Mohd Yazid bin Idris Mohd Yazid Bin Idris Mohd. Yazid Idris Mohd. Yazid Idris Mohd. Yazid Idris Muhammad Ridho Muhammad Win Afgani Muhammad Yusuf Muhammad Yusuf Mulyono, Budi N Herawati Nety Wahyu Saputri Nila Kesumawati Nila Kesumawati Novita Sari Novita Sari Novitasari, Ranny Nurrosyadah, Naqiyyah Nyimas Aisyah Nyimas Aisyah Permata, Endah Dwi Pratiwi, Weni Dwi Primanita, Anggina Puji Astuti Purnama, Benni Purwoko Purwoko Purwoko Purwoko Purwoko R Wulandari Rahma Siska Utari Rahmat Budiarto Rahmat Budiarto Ratu Ilma Ratu Ilma Ratu Ilma Indra Putri Renny Sendra Wahyuni Retni Paradesa Ridwan, Ruslan Risnina Wafiqoh Riya Apriyani Rosanti, Aprida Ruslan Ridwan Saleha, Atikarani Noer Saliza Safta Assiti Saliza Safta Assiti Samsuryadi Samsuryadi Saparudin Saparudin Saputri, Nety Wahyu Sari, Arika Sari, Septi Puspita Scristia, Scristia Selvi Marcellia Selvia, Febi Renico Selvia, Febi Renico Septi Triyani Septi Triyani Shahibul Ahyan Sharipuddin, Sharipuddin Shintia Revina Simalango, Maria Mareta Simanullang, Jonny Simarmata, Ruth Helen Siregar, Jelita Herdia Siti Lestari Siti Rohayah Siti Rohayah, Siti Somakim, Somakim Sri Desy Siswanti Sujinal Arifin Sukmaningtyas, Novika Susanti, Elsa Syamsuryadi Syamsuryadi Syutaridho Tri Wahyudi Utami, Marta Risa Putri Vebrian, Rajab Wijaya, Aldi Putra Winda Wulandari Wulandari, Trisna Yajid Latif Yukans, Septy Sari Yundari, Yundari Yusliriadi Yusliriadi Yusliriadi, Yusliriadi Yusuf Hartono Zetra Hainul Putra Zulkardi Zulkardi Zulkardi Zulkardi Zulkardi Zulkardi Zulkardi Zulkardi Zulkardi Zulkardi Zulkardi Zulkardi Zulkardi

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