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Sistem Presentasi Cerdas Menggunakan Pengenalan Gerakan Tangan Berdasarkan Klasifikasi Dari Sinyal Electromyography (EMG) Menggunakan Myo Armband Kusuma, Dedy Hidayat; Shodiq, Mohammad Nur
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

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (389.981 KB) | DOI: 10.29407/intensif.v2i1.11939

Abstract

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

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1110.18 KB) | DOI: 10.30630/joiv.3.2.207

Abstract

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 Shodiq, Mohammad Nur; Kusuma, Dedy Hidayat; Rifqi, Mirza Ghulam; Barakbah, Ali Ridho; Harsono, Tri
JOIV : International Journal on Informatics Visualization Vol 3, No 1 (2019)
Publisher : Politeknik Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1452.798 KB) | DOI: 10.30630/joiv.3.1.204

Abstract

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%.
Si-Bidan: Sistem Informasi Kesehatan Ibu dan Anak Kusuma, Dedy Hidayat; Shodiq, Mohammad Nur; Yusuf, Dianni; Saadah, Lailatus
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

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (433.328 KB) | DOI: 10.29407/intensif.v3i1.12508

Abstract

  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.
Sistem Prediksi Kebutuhan Obat di Puskesmas Menggunakan Metode Least Square Suwardiyanto, Devit; Shodiq, Mohammad Nur; Kusuma, Dedy Hidayat; Sari, Tovia Oktalita
Jurnal Informatika: Jurnal Pengembangan IT Vol 4, No 1 (2019): JPIT, Januari 2019
Publisher : Politeknik Harapan Bersama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30591/jpit.v4i1.1085

Abstract

The Puskesmas is a health service center at the first level in the community. Medication is an important requirement in health agencies, including health centers. The Puskesmas must provide medicine for patients for a period of a month. As well, the puskesmas also has to plan drug requests for the period of the following month. The problem that often arises is about drug supplies. If the demand for drugs is too much, it will cause the drug to be removed for a long period of time, so that it will result in drug expiration. Likewise, if the demand for drugs is too little then it becomes less good, which results in less optimal service to the community. During this time, planning for drug demand for use in the next period, still using instinctive techniques by the head of the health center of the puskesmas. So, this will lead to excess or even reduced drug supply. In this study a system that is able to predict future drug needs was built. The results of this prediction can be used as a reference for drug requests to the health department. The method used to predict is the Least Square method, while the system to control the upper and lower limits uses the Minimum Maximum Stock Level (MMSL) method. The test system for prediction errors in this study uses Mean Absolute Percentage Error (MAPE). This systems was implemented using the PHP language and visualized on a web-based basis. The system test results showed an average prediction error rate of 12.70%. The existence of this system is expected to be able to assist the planning process of drug needs in the future at the puskesmas.