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All Journal TELKOMNIKA (Telecommunication Computing Electronics and Control) JOIV : International Journal on Informatics Visualization INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi J-Dinamika: Jurnal Pengabdian Kepada Masyarakat DIKEMAS (Jurnal Pengabdian Kepada Masyarakat) Jurnal Bakti Masyarakat Indonesia TEPIAN International Conference on Industrial Revolution for Polytechnic Education Archive: Jurnal Pengabdian Kepada Masyarakat Seminar Nasional Ilmu Terapan Jurnal Informatika: Jurnal Pengembangan IT Cahaya Pengabdian

Kusuma, Dedy Hidayat

Politeknik Negeri Banyuwangi

Author-ID : 744499

Religion Agriculture, Biological Sciences & Forestry Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Mathematics Public Health Social Sciences Other

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Adaptive Neural Fuzzy Inference System and Automatic Clustering For Earthquake Prediction in Indonesia Mohammad Nur Shodiq,Dedy Hidayat Kusuma,Mirza Ghulam Rifqi,Ali Ridho Barakbah,Tri Harsono
International Conference on Industrial Revolution for Polytechnic Education Vol. 2 No. 2 (2020): International Conference on Industrial Revolution for Polytechnic Education
Publisher : PolinemaPress

Show Abstract | Download Original | Original Source | Check in Google Scholar

Earthquake is a type of natural disaster. The Indonesian archipelago is located in the world's three mega plates, they are Australian plate, Eurasian plate, and Pacific plate. Therefore, it is possible for applied of earthquake risk of mitigation. One of them is to provide information about earthquake occurrences. This information is used for spatiotemporal analysis of earthquakes. This paper presented Spatial Analysis of Magnitude Distribution for Earthquake Prediction using adaptive neural fuzzy inference system (ANFIS) based on automatic clustering in Indonesia. This system has 3 main sections: (1) Data preprocessing, (2) Automatic Clustering, (3) Adaptive Neural Fuzzy Inference System. For experimental study, earthquake data is obtained Indonesian Agency for Meteorological, Climatological, and Geophysics (BMKG) and the United States Geological Survey’s (USGS), the year 2010-2017 in the location of Indonesia. Automatic clustering process produces The optimal number of cluster, that is 7 clusters. Each cluster will be analyzed based on earthquake distribution. its calculate the b value of earthquake to get the seven seismicity indicators. Then, implementation for ANFIS uses 100 training epochs, Number of MFs is 2, MFs type input is gaussmf. The ANFIS result showed that the system can predict the non-occurrence of aftershocks with the average performance of 70%

Neural Network for Earthquake Prediction Based on Automatic Clustering in Indonesia Mohammad Nur Shodiq; Dedy Hidayat Kusuma; Mirza Ghulam Rifqi; Ali Ridho Barakbah; Tri Harsono
JOIV : International Journal on Informatics Visualization Vol 2, No 1 (2018)
Publisher : Society of Visual Informatics

A model of artiï¬cial neural networks (ANNs) is presented in this paper to predict aftershock during the next five days after an earthquake occurrence in selected cluster of Indonesia with magnitude equal or larger than given threshold. The data were obtained from Indonesian Agency for Meteorological, Climatological and Geophysics (BMKG) and United States Geological Surveyâ€™s (USGS). Six clusters was an optimal number of cluster base-on cluster analysis implementing Valley Tracing and Hill Climbing algorithm, while Hierarchical K-means was applied for datasets clustering. A quality evaluation was then conducted to measure the proposed model performance for two different thresholds. The experimental result shows that the model gave better performance for predicting an aftershock occurrence that equal or larger than 6 Richterâ€™s scale magnitude.

Detection Object on Sea Surface to Avoid Collision with Post-Processed in Background Subtraction Image Alif Akbar Fitrawan; Mohammad Nur Shodiq; Dedy Hidayat Kusuma
JOIV : International Journal on Informatics Visualization Vol 3, No 2 (2019)
Publisher : Society of Visual Informatics

Data on shipping accident investigations from the National Transportation Safety Committee (NTSC) throughout 2010-2016 of fifty-four accident cases at sea, seventeen of which were accidents caused by collisions on ships in Indonesian waters, act to avoid a collision by detecting an object on the sea surface. Detection object is challenging because so many varieties object on the sea surface. Illumination variations with different seasons, periods, illumination intensity and direction affect the detection of objects directly. A rough sea is seen as a dynamic background of moving objects with size order and shape. All these factors make it difficult to object detection. Therefore, it is possible to conclude that background subtraction on sea surface problem remains open and a definitive robust solution is still missing. In this paper, we have applied a selection of background subtraction algorithms with post-processed to the problem. Experimental results with our dataset verify the high efficiency of our proposed method

Adaptive Neural Fuzzy Inference System and Automatic Clustering for Earthquake Prediction in Indonesia Mohammad Nur Shodiq; Dedy Hidayat Kusuma; Mirza Ghulam Rifqi; Ali Ridho Barakbah; Tri Harsono
JOIV : International Journal on Informatics Visualization Vol 3, No 1 (2019)
Publisher : Politeknik Negeri Padang

Earthquake is a type of natural disaster. The Indonesian archipelago located in the world's three mega plates; they are Australian plate, Eurasian plate, and Pacific plate. Therefore, it is possible for applied of earthquake risk of mitigation. One of them is to provide information about earthquake occurrences. This information used for spatiotemporal analysis of earthquakes. This paper presented Spatial Analysis of Magnitude Distribution for Earthquake Prediction using adaptive neural fuzzy inference system (ANFIS) based on automatic clustering in Indonesia. This system has three main sections: (1) Data preprocessing, (2) Automatic Clustering, (3) Adaptive Neural Fuzzy Inference System. For experimental study, earthquake data obtained Indonesian Agency for Meteorological, Climatological, and Geophysics (BMKG) and the United States Geological Survey’s (USGS), the year 2010-2017 in the location of Indonesia. Automatic clustering process produces The optimal number of cluster, that is 7 clusters. Each cluster will be analyzed based on earthquake distribution. Its calculate the b value of earthquake to get the seven seismicity indicators. Then, implementation for ANFIS uses 100 training epochs, Number of membership function (MFs) is 2, MFs type input is gaussian membership function (gaussmf). The ANFIS result showed that the system can predict the non-occurrence of aftershocks with the average performance of 70%.

Improvement security in e-business systems using hybrid algorithm L. Sumaryanti; Dedy Hidayat Kusuma; Rosmala Widijastuti; Muhammad Najibulloh Muzaki
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 19, No 5: October 2021
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v19i5.20403

E-business security becomes an important issue in the development of technology, to ensure the safety and comfort of transactions in the exchange of information is privacy. This study aims to improve security in e-business systems using a hybrid algorithm that combines two types of keys, namely symmetric and asymmetric keys. Encryption and decryption of messages or information carried by a symmetric key using the simple symmetric key algorithm and asymmetric keys using the Rivest Shamir Adleman (RSA) algorithm. The proposed hybrid algorithm requires a high running time in the decryption process compared to the application of a single algorithm. The level of security is stronger because it implements the process of message encryption techniques with two types of keys simultaneously.

Face Shield Pelindung Covid-19 Bagi Tenaga Medis Puskesmas Rawat Inap Di Kabupaten Banyuwangi Mohammad Shodiq; Dedy Kusuma; Muhammad Al Haris; Nuraini Lusi
DIKEMAS (Jurnal Pengabdian Kepada Masyarakat) Vol 5 No 2 (2021)
Publisher : Politeknik Negeri Madiun

Show Abstract | Download Original | Original Source | Check in Google Scholar

Angka kasus positif kasus Covid 19 di Kabupaten Banyuwangi semakin hari semakin meningkat. Dari sisi fasilitas kesehatan, saat ini telah ditunjuk rumah sakit rujukan penanganan Covid-19 yakni RSUD Genteng dan RSUD Blambangan. Di samping itu juga terdapat 45 puskesmas yang menjadi fasilitas pratama yang berhadapan langsung dengan masyarakat yang berobat. Dari seluruh puskesmas tersebut terdapat 16 puskesmas yang melayani rawat inap dan beroperasi selama 24 jam. Secara umum permasalahan yang dihadapi mitra adalah ketersediaan alat pelindung diri (APD) yang terbatas baik itu masker, pelindung wajah, dan baju hazmat. Keberadaan alat pelindung tersebut sangatlah penting dalam mencegah penularan Covid-19 dari pasien yang berobat kepada para tenaga medis terutama pada puskesmas yang menyediakan layanan rawat inap dan beroperasi 24 jam dan 7 hari dalam seminggu. Untuk pengadaan baju hazmat dan masker. Pemerintah Kabupaten Banyuwangi telah menggandeng UMKM untuk memproduksi dan memasok kebutuhan. Namun untuk pelindung wajah (face shield) karena jumlah yang tersedia terbatas maka puskesmas secara mandiri membuatnya dengan menggunakan plastik mika sampul. Hal ini tentunya sangat jauh dari standar APD face shield yang ditetapkan. Adapun luaran dari kegiatan ini adalah proses pembuatan alat faceshield berjumlah 200 unit untuk menambah APD guna memerangi Covid-19 di Banyuwangi.

Sistem Rekomendasi Destinasi Pariwisata Menggunakan Metode Hibrid Case Based Reasoning dan Location Based Service Sebagai Pemandu Wisatawan di Banyuwangi Dedy Hidaya Kusuma; Moh. Nur Shodiq
INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi Vol 1 No 1 (2017): Vol. 1 No. 1 Februari 2017
Publisher : Universitas Nusantara PGRI Kediri

As one of the fastest growing tourist destinations, the number of tourist arrivals in Banyuwangi Regency shows a significant growth where in the range of 2010 - 2015 there is an increase of domestic tourists by 161% and abroad by 210%. The increase in tourist numbers is not a trouble-free process, especially with regard to visitor preferences that change over time. Tourist information and a variety of tourist interests often make tourists confused in determining the choice of any destination to visit. While Banyuwangi tourism information that is available in printed form or that can be accessed online still requires tourists to sort and choose their own in accordance with the interests and preferences so that tourists need any suggestions or recommendations. In the field of tourism, this recommendation may include objects to be visited, existing tourist events, travel schedules, travel routes, availability of infrastructure and so forth. The recommendation system proposed in this research uses a combination of (hybrid) case-based reasoning and location-based methods. The system is built in the form of android based mobile applications. Input from users to the system of travelers preferences include tourist types, tariff categories, modes of transportation, and tourism activities. These preferences together with user location based on GPS coordinates are further compared to the tourist object attributes stored on the system using the nearest neighbor similarity method. The output of the system in the form of recommendation of tourism object that has the highest similarity to the user preference. The results of this study are expected to assist tourists in choosing tourism objects in Banyuwangi according to their preferences or demand criteria.

Sistem Presentasi Cerdas Menggunakan Pengenalan Gerakan Tangan Berdasarkan Klasifikasi Dari Sinyal Electromyography (EMG) Menggunakan Myo Armband Dedy Hidayat Kusuma; Mohammad Nur Shodiq
INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi Vol 2 No 1 (2018): Vol. 2 No. 1 Februari 2018
Publisher : Universitas Nusantara PGRI Kediri

Technological developments to support the current learning system are so fast that there is an interactive innovation technology for educational trends. One of the technologies implemented is an interactive presentation application in a multimedia class or smart presentation system. This technology makes it possible to control the presentation in a natural way with their hand movements. This introduction can replace conventional mouse roles and functions to facilitate teacher performance in applying interactive technology in the classroom. To build this intelligent presentation system, it is divided into several parts: 1) Recognition sensor arm movement using Myo armband; 2) Hand gesture of hand movements made several steps include: a) data retrieval based on realtime and wireless; b) feature extraction; c) classification using artificial neural network; and 3) Smart presentation, is a presentation system that can understand human behavior and provide interactive presentations.The expected benefits of the results of this study are, with the construction of intelligent presentation systems using hand-gesturing recognition based on the classification of electromyography signals, 1) Make presentations more efficient, engaging and easier to understand, and also make the discussion more interactive and improve communication; 2) Assists the presenter of material in exposing the material by using a presentation control system based on hand gestures.

Si-Bidan: Sistem Informasi Kesehatan Ibu dan Anak Dedy Hidayat Kusuma; Mohammad Nur Shodiq; Dianni Yusuf; Lailatus Saadah
INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi Vol 3 No 1 (2019): Vol. 3 No. 1 Februari 2019
Publisher : Universitas Nusantara PGRI Kediri

Midwives are one of the health workers who provide child and maternal health (CMH) services and family planning. At present, most of the recording of midwife services is still managed conventionally by manual book keeping. It is less effective and efficient which causes the workload to increase, the information retrieval process is quite long and the risk of missing important data is likely to occur frequently. On the other hand, maternal patients are required to visit the midwife directly if they want to know the information on the progress of the pregnancy and their child. Based on these facts, a CMH information system was built that was accessible to midwives and parents. The information system developed consists of two integrated applications, namely web-based applications for midwives and mobile applications for parents. The web application facilitates midwives to record transactions, make reports, and deliver information to patients. While the mobile application makes it easier for parents to monitor the development of maternal and child health and other information provided by midwives. The system was developed using the water-fall software development model. The test results using the black-box test method indicate that the CMH system has been able to meet the user's functional requirements.

Parallel Class Ranking Model Using Analytic Hierarchy Process With Multi Criteria Dedy Hidayat Kusuma; Moh Nur Shodiq; Indah Kurnia Fitriani
INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi Vol 4 No 1 (2020): February 2020
Publisher : Universitas Nusantara PGRI Kediri

Madrasah Aliyah Negeri (MAN) Banyuwangi using a worksheet which can lead to error occurrences and slow decision making. A system for decision support that can improve the ranking process and quality were developed in this paper. The proposed system implemented the codeigniter framework, MySQL database, and PHP programming language. The system provided three user roles which are teacher, student, and administrator role. These four parameters are used as ranking system input, including academic values, non-academic values, violation scores, and student attendance. The ranking process was conducted by applying the analytic hierarchy process (AHP) method. The developed decision support system was tested using two ways: the black box testing method and providing questionnaires. Black box testing result shows that the system has functionally worked, while user’s questionnaire gives 92,29% well accepted by users. The results show that the decision support system can help manage values and determine the parallel ranking list.

Co-Authors Ali Ridho Barakbah Alif Akbar Fitrawan Annisa Rani Maulida Carenza Al Kharraz Devit Suwardiyanto Dianni Yusuf Eka Mistiko Rini Endi Sailul Haq Herman Yuliandoko, Herman I Putu Sudhyana Mecha Indah Kurnia Fitriani Lailatus Saadah Lilik Sumaryanti Lukman Hakim Lutfi Hakim Mirza Ghulam Rifqi Mirza Ghulam Rifqi Mistiko Rini, Eka Moh Nur Shodiq Moh. Nur Shodiq Moh. Nur Shodiq, Moh. Nur Mohammad Nur Shodiq Mohammad Nur Shodiq Mohammad Nur Shodiq Mohammad Nur Shodiq Mohammad Nur Shodiq, Mohammad Nur Mohammad Shodiq Muhamad Fuad Al Haris Muhammad Al Haris Muhammad Fuad Alharis Muhammad Najibulloh Muzaki Nuraini Lusi Pamuji, Dian Ridlo Rosmala Widijastuti Sepyan Purnama Kristanto Tovia Oktalita Sari Tri Harsono

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