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All Journal Natural Science: Journal of Science and Technology MEKTRIK INSIST (International Series on Interdisciplinary Research) ScientiCO : Computer Science and Informatics Journal
Andi Hendra
Tadulako University
Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering Mathematics Mechanical Engineering Other

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RANCANG BANGUN SISTEM PERPUSTAKAAN UNIVERSITAS TADULAKO MENGGUNAKAN RADIO FREQUENCY IDENTIFICATION DAN SENSOR PASSIVE INFRARED Sani, Asrul; Nugraha, Deny Wiria; Hendra, Andi
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Publisher : MEKTRIK

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Abstract

Radio frequency identification (RFID) is a tool for identifying objects using radio waves. RFID reader consists of a reader and a tag as the object is read. This technology is efficiently used in the manual library UNTAD as library card for its use without having direct contact (Contacless). Results of identification RFID reader in the form of a unique series of numbers. RFID reader is connected directly to a PC via a USB cable (Universal Serial Bus), so that the identification appear on the LCD monitor screen. The identification result is managed by the application that is made from Visual Basic 6 with GUI (grapichal User Interface) that simple connected in Acess 2007 database so that the library data is stored properly. Microcontroller ATMega8535 serves as a voice recorder module controller ISD 1820 remind visitors to fill out the list of visitors of the PIR sensor detection results when there are visitors who come in and as recipients visitor data contained in the application is then displayed on the LCD 2x16. From the combination of these technologies can overcome UNTAD library system is still manual because it produces a rapid and accurate data.
RANCANG BANGUN SISTEM KLASIFIKASI STATUS GIZI BALITA MENGGUNAKAN METODE K-NEAREST NEIGHBOR (KNN) Amalia, Rizki; Musdalifah, Selvy; Hendra, Andi; Sudarsana, I Wayan
Natural Science: Journal of Science and Technology Vol 2, No 2 (2013): Volume 2 Number 2 (August 2013)
Publisher : Univ. Tadulako

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Children under five age is a group that susceptible to health problems such as lack of energy and protein nutrition, so this age group should get special attentions. One of the problems that should get an attention is problems nutritional status of children. Nutritional status of children is one of the indicators the level of social welfare. The classification of children?s nutritional status was conducted by nutritionist, but the problem is the scattering of nutritionist in Palu is very limited, especially in areas which far away from the city center. This case of study will be taken from Pantoloan Boya village. The limited of nutritionist was being the problems in detecting the indication of malnutrition. Through this research will be made an implementation based of computer system that has a same understanding as a nutritionist who is able to determine the nutritional status of children. One method that can be used in solving the classification of the nutritional status of children is K-Nearest Neighbor (KNN) method. K-Nearest Neighbor (KNN) is one method that use the learning algorithm where the result from the new testing sample is classified based on the majority of KNN?s category. In this research, the system classified the children according to their nutritional status based on data that obtained from the place of research. These results using k = 1 as the number of nearest neighbors which labels the majority of the k nearest neighbors are used to predict the unknown nutritional status of new data. This is because for k = 1 has better accuracy results than other values ??of k is equal to 81.67%.
MODEL MATEMATIKA UNTUK SISTEM EVAKUASI TSUNAMI KOTA PALU (SET-KP) BERBASIS JALUR TERPENDEK DAN WAKTU EVAKUASI MINIMUM Sudarsana, I Wayan; Mendi, Sulistiawati; Abdullah, Abdullah; Hendra, Andi; Sahari, Agusman
Natural Science: Journal of Science and Technology Vol 2, No 3 (2013): Volume 2 Number 3 (December 2013)
Publisher : Univ. Tadulako

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Abstract

Kota Palu memiliki tingkat resiko tinggi terhadap ancaman gempa bumi dan tsunami karena terletak dalam Sabuk Gempa Pasifik dan bentangan sesar Palu Koro. Kriteria InaTews waktu yang tersedia untuk evakuasi setelah peringatan dini tsunami berbunyi adalah 15 menit. Evakuasi penduduk dari pesisir pantai kota Palu ke tempat aman merupakan tindakan yang harus dan segera dilakukan sebagai langkah penyelamatan bila terjadi tsunami. Informasi tentang tempat, jalur terpendek, dan waktu tempuh minimum untuk evakuasi memainkan peranan yang sangat penting dalam keselamatan penduduk yang akan dievakuasi. Pada penelitian ini telah dihasilkan sebuah perangkat lunak Sistem Evakuasi Tsunami untuk kota Palu (SET-KP) berbasis jalur terpendek dan waktu evakuasi minimum. Penentuan jalur terpendek dalam SET-KP menggunakan algoritma Dijkstra dan menghitung waktu evakuasi minimumnya menggunakan model matematika . Skenario evakuasi penduduk di semua cluster pesisir kota Palu menggunakan perangkat lunak SET-KP diperoleh bahwa cluster dengan jumlah penduduk cukup banyak waktu evakuasinya melebihi ketentuan InaTews. Sementara itu, cluster dengan jumlah penduduk sedikit ketentuan InaTews dapat dipenuhi, seperti cluster C70, C76 dan C79. Oleh karena itu, shelter (titik evakuasi) yang telah didefinitifkan sebelumnya dalam dokumen BPBD perlu direposisi untuk memenuhi ketentuan InaTews.
Rancang Bangun Sistem Presensi Menggunakan Sidik Jari (Studi Kasus Pada Lembaga Pemasyarakatan Klas II-A Palu) Amriana, Amriana; Hendra, Andi; Bakhtiar, Arfiah
ScientiCO : Computer Science and Informatics Journal Vol 1, No 1 (2018): Scientico : April
Publisher : Fakultas Teknik, Universitas Tadulako

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Abstract

Dermatoglyphic has been widely applied to recognize a person's identity, because people basically have something unique or characteristic possessed only by themselves. This raises the idea of making it a unique identity. This is useful for employees presence applications, especially at Lembaga Pemasyarakatan Klas IIA Palu which is still doing manual presence. This system provides the division of labor time and wereable to detect the fingerprints of employees using a fingerprint scanner. The system was made in several stages of the input fingerprint image, binarization fingerprint image, fingerprint image quality improvement, and matching fingerprint image. Improvements to the quality of the fingerprint image consists of the surgical process of mathematical morphology opening and erosion. The detection process of the fingerprint image used euclidean distance measurement points minutiae. The test results indicate that the presence system accuracy using euclidean distance measurement could detect the fingerprint image by 89% from 20 fingerprint data with 5 times testing for each data.
Support Vector Machine (SVM) For Toddler’s Nutritional Classification in Palu City Andi Hendra; Gazali Gazali
INSIST Vol 1, No 1 (2016)
Publisher : Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (177.549 KB) | DOI: 10.23960/ins.v1i1.19

Abstract

Abstract—Toddlers are groups who are vulnerable about the health nutrition problems. Nutritional status of children is one of the indicators that can describes the level of social welfare in the city. Nutritionists are the people that can determined the nutritional status. The problem that arises is the limited number of the nutrition experts in each area, this problem causes the children’s malnutrition in the Palu city is detected in very slow condition. The aims of this study is to help the health professionals in the health centers or the hospitals to determine the children’s nutritional status computerized, so the malnutrition problem in the Palu city can be detected earlier. Besides that, to help the government in policy making about nutrition of the toddlers in Palu city. This study uses a Support Vector Machine (SVM) which implemented in computer-based software application to analyze nutrition of the toddlers.Keywords—Nutrition, Software, Support Vector Machine (SVM), Toddlers, Palu city.
Co-Authors Agusman Sahari Amriana Amriana Asrul Sani Bakhtiar, Arfiah Deny Wiria Nugraha Gazali Lembah I Wayan Sudarsana Muhammad Rivai Rizki Amalia Selvy Musdalifah Sulistiawati Mendi