Article Per Year (5 Year)
p-Index From 2021 - 2026
2.765
P-Index
This Author published in this journals
All Journal International Journal of Informatics and Communication Technology (IJ-ICT) Tekno : Jurnal Teknologi Elektro dan Kejuruan Annual Research Seminar JURNAL MEDIA INFORMATIKA BUDIDARMA KOMIK (Konferensi Nasional Teknologi Informasi dan Komputer) Jurnal Tekno Kompak Jurnal Mantik Mulia International Journal in Science and Technical International Journal of Engineering, Science and Information Technology Jurnal Rekayasa Elektro Sriwijaya Indonesian Journal of Electrical Engineering and Renewable Energy (IJEERE) Jurnal Indonesia Sosial Teknologi Jurnal Pendidikan Indonesia (Japendi) Electrician : Jurnal Rekayasa dan Teknologi Elektro Jurnal Ecotipe (Electronic, Control, Telecommunication, Information, and Power Engineering)
Iwan Pahendra
Teknik Elektro, Universitas Sriwijaya, Palembang, Indonesia
Astronomy Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Social Sciences Transportation

Published : 25 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 25 Documents
Search

 1   2   3 
IMPLEMENTASI SISTEM PAKAR PADA PASIEN PENDERITA TUBERKULOSIS POTENTIAL DROP OUT DI RUMAH SAKIT CUT MEUTIA ACEH UTARA Darnila, Eva; Ula, Mutammimul; Mauliza, Mauliza; Ermatita, Ermatita; Pahendra, Iwan
KOMIK (Konferensi Nasional Teknologi Informasi dan Komputer) Vol 2, No 1 (2018): Peranan Teknologi dan Informasi Terhadap Peningkatan Sumber Daya Manusia di Era
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (23.348 KB) | DOI: 10.30865/komik.v2i1.968

Abstract

The existence of a technology that identifies and controls patients with potential drop out TB disease which is increasingly rapid will be a top priority, especially for the health team in following up the success of treatment. In this study, an expert system was used to diagnose patients with potential Drop Out tuberculosis by using a Case Based Reasoning model to see patients with potential Droup Out. For variable names used are pulmonary smear patients (+), new patients, pulmonary smear (-) / ro (+), new patients, extra pulmonary, relapsed patients, re-treatment, default patients, re-treatment patients, failed patients and others -other. The last detection process is taken from the highest value obtained in the diagnosis of all the symptoms that have been witnessed. Based on the results of the application of the Expert System on Potential Drop Out Tuberculosis Patients at Cut Meutia Hospital in North Aceh based on the case code 31 with a detection system for the AFB (+) Lung Patient with its detection symptoms, the patient coughs with phlegm for 2-3 weeks or more. the results of sputum examination, patients who have been treated with TB drugs less than 1 month and TB patients on sputum examination, patients who have been treated with TB drugs less than 1 month, TB patients stop the treatment and TB patients return to the facility health service facilities with the highest case value of 0.6111 of all detection systems that have been tested.Keywords: Expert system,  CBS, TB
ANALISIS MODEL NAIVE BAYES UNTUK IDENTIFIKASI PENGGOLONGAN DAYA LISTRIK DI KOTA LHOKSUMAWE Sadli, Muhammad; Fajriana, Fajriana; Fuadi, Wahyu; Ermatita, Ermatita; Pahendra, Iwan
KOMIK (Konferensi Nasional Teknologi Informasi dan Komputer) Vol 2, No 1 (2018): Peranan Teknologi dan Informasi Terhadap Peningkatan Sumber Daya Manusia di Era
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (23.348 KB) | DOI: 10.30865/komik.v2i1.971

Abstract

Electricity subsidy is provided for all 450 VA power household customers and 900 VA power household customers who are poor and disadvantaged. However, there are many facts that household customers with 450 VA power are capable and 900 VA power household customers consist of capable households, boarding houses or luxury rented. Households are able to use more electricity than poor households. This paper describe to the identification of household customers' electrical power in the Lhokseumawe city to facilitate PLN in classifying customer power by using the Naive Bayes method. Naive bayes value variables used in this study are: monthly income, highest diploma, last job, house area, subscription fee and government registered household. The classification of household customer power is grouped into three categories, namely low (450 VA down), medium (900 VA) and high (above 1300 VA).. Based on household customer data that is used as training data, the Naive Bayes method is able to classify the customer data tested. So the Naive Bayes method successfully predicts the magnitude of the probability of household electrical power with an accuracy percentage of 80%.Keywords: Electricity, Naive Bayes,  CBS, low birth weight, subsidy
Expert System Technology in Implementation of K-Means Clustering Algorithm in Patients with Tuberculosis at Cut Meutia Hospitals North Aceh Eva Darnila; Mutammimul Ula; Mauliza; Iwan Pahendra; Ermatita; Hardi, Richki
Mulia International Journal in Science and Technical Vol 2 No 1 (2019): August
Publisher : Universitas Mulia

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

Abstract

Technology in detecting potential drop out tuberculosis (TB) in Cut Meutia hospital and Health Office plays a great role and has been very important. This is seen from the increasing number of patients who could not be cured succesfully and who do not care about TB which will have fatal consequences on their health. In addition, the main cause of the increase in the number of potential drop out TB patients is because of the lack of awareness of the community, especially the middle economic level family of the danger of TB disease as seen from the irregular treatment that they have and the continued smoking habit. In this study, an expert system was used to diagnose patients with potential Drop Out tuberculosis who were then diagnosed into the cluster of each TB patient using the K-Means algorithm. The system implementation in the expert system is that the initial symptoms include the question of whether the patient has cough with phlegm for 2-3 weeks or more (yes), has the patient been treated with TB drugs less than 1 month (no), experienced no appetite and nausea. From the results of these symptoms, there are diagnoses of New Patients, Pulmonary BTA (-) / Ro (+), with sub-acute level having moderate severity and duration, the severity can reduce the health status of the patient, the patient is eventually expected to recover and totally recovered the disease does not develop into a chronic disease. The results of this expert system would be entered into the K-Means clustering. The test results of the k-means clustering algorithm with K = 3 (C1, C2, C3). with initial centroid values of m1: C1, 5, 5, 5, 5, 5, 5 and m_2: C2, 3, 3, 3, 3, 3, with patient p1 with the value of each cluster (C1) = 6.928, ( C2) = 2.828, C3 = (4). For the closest cluster value is C2, then the BCV (Between Cluster Variation) calculation value is 19,596, and the WCV (Within cluster Variation) value is 144. Then the ratio value is 0.136. The result of the iteration -3 can be stopped because it does not experience the movement of the clusters and the clusters have been optimal. The results of this system can classify patients for each village and sub-district area so that the Hospital officials and the Health Office can directly monitor potential drop out TB patients and can facilitate the Head of Office/region in handling clustered TB patients using K-Means. Furthermore, in the coming years, it can be used as a tool in taking preventive measures.
Implementation of Clustering K-Means Algorithm classification of the need of Electricity power for each region at PT Lhokseumawe Muhammad Sadli; Wahyu Fuadi; Fajriana; Ermatita; Iwan Pahendra; Mutammimul Ula; Hardi, Richki
Mulia International Journal in Science and Technical Vol 2 No 1 (2019): August
Publisher : Universitas Mulia

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

Abstract

PLN (State Electricity Company) is in charge of providing stock of needs for the grouping of electrical power and classification for each region in Lhokseumawe City. The area that were grouped based on the amount of power consists of the four subdistricts, namely Banda Sakti, Blang Mangat, Muara Dua and Muara Satu, each of which is sourced from the village. The importance of clusters is to separate each data between data in the villages that will be input into sub-district data. Furthermore, the K-Means Clustering Classification was used in determining the grouping of electrical power needs in each region in the Lhokseumawe City where this system classify the electricity stock needs in each region categorized into a cluster. In this study, Clustering Classification of K-Means variables include job (V1), overall income (V2), house area (V3), number of rooms (V4), number of electronic equipment (V5) and total of power usage (V6). Results of grouping of C1 system = Subsidy R-1/450 VA, C2 = Subsidy R-1/900 VA, C3 = Non Subsidy R-1/900, C4 = Non Subsidy R-1/1300, C5 = Non Subsidy R- 1/2200 VA. The purpose of this study is to be able to predict the classification of each electric power requirement for each region based on the input data per district. This has an impact on the community and PLN's stock of electricity needs in order to remain stable. It is found out from the Clustering K-Means Classification that there is a new cluster for Banda Sakti. The last step in determining Clustering K- Means stopped at the the iteration 3 until the cluster is optimal. The results of this study are in the form of grouping of PLN Customers from each region displayed in the system in the form of classification of electrical power in each subdistrictdistrict. Furthermore, the grouping can be recommended to predict the power needs of each sub-district and belong to the cluster provided by the PLN.
Memprediksi Penyakit Kanker Payudara dan Liver menggunakan Algoritma Backpropagation Miftahul Falah; Dian Palupi Rini; Iwan Pahendra
Annual Research Seminar (ARS) Vol 5, No 1 (2019): ARS 2019
Publisher : Annual Research Seminar (ARS)

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

Abstract

Pada sebuah penelitian sangat penting untuk dilakukannya analisis sebuah prediksi atau peramalan, sehingga penelitian yang dilakukan akan lebih terarah dan tepat. Seperti halnya dalam memprediksi penyakit, mengingat pentingnya mengetahui kondisi kesehatan agar tidak berdampak kedepannya. Sehingga, diperlukan prediksi atau peramalan dengan tujuan memperkecil suatu masalah yang akan terjadi dikemudian hari. Dari beberapa jurnal yang telah di baca sebagai referensi, penulis memilih melakukan penelitian untuk memprediksi dua penyakit dengan memilih salah satu metode didalam ANN yaitu Algoritma Backpropagion (BP) dengan tujuan dilakukannya penelitian untuk mengetahui tingkat akurasi Algoritma Backpropagation (BP). Hasil penelitian menunjukkan bahwa prediksi penyakit kanker payudara dengan dataset sebanyak 569 data dan memiliki 31 atribut menghasilkan nilai akurasi sebesar 97.70 % sedangkan prediksi penyakit liver sebanyak 583 data dan memiliki 11 atribut menghasilkan nilai akurasi sebesar 70.84% dari sumber pengambilan dataset yaitu KAGGLE dengan waktu komputasi yang sama selama 3 sekon.
Kombinasi Algoritma Backpropagation Neural Network dengan Gravitational Search Algorithm Dalam Meningkatkan Akurasi Miftahul Falah; Dian Palupi Rini; Iwan Pahendra
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 5, No 1 (2021): Januari 2021
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v5i1.2597

Abstract

Predicting disease is usually done based on the experience and knowledge of the doctor. Diagnosis of such a disease is traditionally less effective. The development of medical diagnosis based on machine learning in terms of disease prediction provides a more accurate diagnosis than the traditional way. In terms of predicting disease can use artificial neural networks. The artificial neural network consists of various algorithms, one of which is the Backpropagation Algorithm. In this paper it is proposed that disease prediction systems use the Backpropagation algorithm. Backpropagation algorithms are often used in disease prediction, but the Backpropagation algorithm has a slight drawback that tends to take a long time in obtaining optimum accuracy values. Therefore, a combination of algorithms can overcome the shortcomings of the Backpropagation algorithm by using the success of the Gravitational Search Algorithm (GSA) algorithm, which can overcome the slow convergence and local minimum problems contained in the Backpropagation algorithm. So the authors propose to combine the Backpropagation algorithm using the Gravitational Search Algorithm (GSA) in hopes of improving accuracy results better than using only the Backpropagation algorithm. The results resulted in a higher level of accuracy with the same number of iterations than using Backpropagation only. Can be seen in the first trial of breast cancer data with parameters namely hidden layer 5, learning rate of 2 and iteration as much as 5000 resulting in accuracy of 99.3 % with error 0.7% on Backpropagation Algorithm, while in combination BP & GSA got accuracy of 99.68 % with error of 0.32%.
Rancang Bangun Geographic Information System (GIS) Sebagai Pengembangan Sistem Monitoring Area Perkebunan Berbasis IoT Nadia Thereza; Iwan Pahendra Anto Saputra; Zaenal Husin
Jurnal Tekno Kompak Vol 15, No 1 (2021): Februari
Publisher : Universitas Teknokrat Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33365/jtk.v15i1.908

Abstract

Operasional sektor perkebunan di Indonesia sebagian besar masih mengandalkan sistem konvensional yang menggunakan tenaga manusia untuk melakukan kontrol ke lapangan. Dengan kondisi tersebut, masih sulit jika ingin melakukan peningkatan kinerja operasional menjadi lebih efisien, efektif, dan produktif. Ditambah lagi, kondisi pandemi yang tengah dihadapi saat ini secara tidak langsung sangat berdampak dan berpotensi menurunkan angka produktivitas. Sistem operasional ataupun pengelolaan lahan perkebunan harus mengalami perubahan. Pemanfaatan teknologi dan inovasi sangat dibutuhkan untuk membantu mempertahankan ataupun meningkatkan kualitas dan kuantitas hasil produksi. Oleh sebab itu, dibutuhkan suatu rancangan sistem informasi berbasis website, yang bekerja menyampaikan informasi kondisi geografis suatu area secara real-time sebagai solusi dari permasalahan pemantauan kondisi geografis. Sistem informasi tersebut bekerja menggunakan informasi berupa data spasial (bereferensi geografis) yang dikenal dengan Sistem Informasi Geografis atau Geographic Information System (GIS).Tujuan penelitian ini adalah untuk  membangun GIS berbasis web guna memberikan informasi dan menggambarkan kondisi (normal, rawan, kritis) pada suatu area/lahan secara real-time. Metode penelitian ini terdiri dari lima tahapan, yaitu persiapan penelitian (studi literatur), pengkajian objek (observasi, analisis kebutuhan sistem), perancangan dan pembangunan GIS dan integrasi dengan IoT, analisis dan pengujian penerapan GIS, serta penarikan kesimpulan. Sistem informasi geografis yang dibuat adalah dengan menampilkan peta (maps) area yang dipantau. Perangkat lunak yang digunakan untuk menampilkan maps adalah Google Maps Platform yang mana pada platform tersebut terdapat interface yang disebut API (Application Programming Interface). Google Maps API digunakan untuk menghubungkan sistem informasi geografis yang berbasis website dengan google maps. GIS memberikan informasi dan menggambarkan kondisi geografis suatu area secara real-time, kondisi area yang normal ditandai dengan warna hijau, kondisi antara (rawan kritis) ditandai dengan warna kuning serta kondisi area yang kritis ditandai dengan warna merah. Dengan adanya sistem informasi geografis, maka membantu para pekerja lapangan dalam memantau kondisi geografis suatu area secara real-time tanpa harus berada langsung di lokasi. Berdasarkan hasil penilaian pengguna, sebagian besar menyatakan “sangat setuju” bahwa GIS ini bermanfaat, bersifat user-friendly, mudah diakses kapanpun dan di manapun, serta memiliki kecepatan akses yang baik. Selain itu, sebagian besar juga menyatakan “setuju” bahwa GIS mampu menampilkan informasi yang akurat dan dapat membantu pekerjaan.
CO2 (Carbon Dioxide) Metric Monitoring Tool Based on Internet of Things (IoT) Iwan Pahendra; Eva Damila; Ermatita
Jurnal Mantik Vol. 4 No. 3 (2020): November: Manajemen, Teknologi Informatika dan Komunikasi (Mantik)
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/mantik.Vol4.2020.1059.pp2013-2016

Abstract

Monitoring of CO2 (Carbon Dioxide) metric on campus is very necessary to do. A lot of vehicles passing by on campus will make pollution bigger day by day. Development of green campus has to be done at this time. Based on UI Green Metric 2018, 719 campuses have participated to develop a green campus and issues of sustainability. One of requirement is implementation of smart system to solve pollution problems. To develop CO2 metric monitoring tool based on IoT needs hardware and software. The hardware consists of CO2 sensor type MG-811, communication module SIM 800, ADC module ADS1115 and microcontroller ESP32. Software is done using PHP and database. Parameters to be measured is CO2 level. Furthermore, information about CO2 level can be displayed and accessed in real-time via computers. The sensors read the value every in 5 seconds. The results is in average value, CO2 level is 25.50 ppm (parts per million). There is below threshold value for CO2 level according to government regulation. It is a normal condition and no pollution because campus is still in lockdown.
Perancangan Dua Link MPLS Menggunakan Protokol Routing Open Shortest Path First dan Enhanced Interior Gateway Routing Protocol pada Jaringan Wide Area Network Jaka Naufal Semendawai; Desi Windi Sari; Nadia Thereza; Iwan Pahendra Anto Saputra; Puspa Kurniasari; Abdul Haris Dalimunthe; Melia Sari
Jurnal Rekayasa Elektro Sriwijaya Vol. 3 No. 2 (2022): Jurnal Rekayasa Elektro Sriwijaya
Publisher : Jurusan Teknik Elektro Fakultas Teknik Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36706/jres.v3i2.52

Abstract

Di era ini, penggunaan internet merupakan sebuah komponen penting dalam menunjang kehidupan manusia. Hal ini disebabkan karena kegiatan yang dilakukan oleh setiap manusia, rata-rata sudah berbasis online. Hal ini juga terjadi pada aktivitas pengiriman data, khususnya pada pengiriman data yang dilakukan secara berkala. Namun, seringkali pada saat pengiriman data terdapat sebuah error yang dapat menghambat proses pengiriman data. Error tersebut dapat berupa request timed out atau destination host unreachable. Untuk mengatasi hal tersebut, diperlukan sebuah topologi jaringan komputer yang mampu melakukan aktivitas pengiriman data secara maksimal, baik dari segi keamanan, maupun kecepatan transmisi data yang stabil. Pada penelitian ini, penulis menggunakan router Cisco yang dikonfigurasikan dengan menggunakan kombinasi protokol EIGRP dan OSPF. Selain itu, penulis juga menggunakan dua buah link MPLS yang dapat memberikan kecepatan transfer data yang cepat. Protokol EIGRP sendiri dapat memperluas jangkauan dari router dan protokol OSPF dapat memberikan kemampuan untuk menentukan rute terbaik dari router pengirim ke penerima. Perancangan ini dilakukan pada jaringan dengan jenis Wide Area Network. Pengujian yang dilakukan pada penelitian ini adalah dengan cara menggunakan perintah ping pada aplikasi command prompt untuk menguji apakah router pengirim sudah terhubung ke router penerima. Selain itu, penulis juga menggunakan perintah traceroute untuk melihat rute yang diambil oleh router pengirim pada saat mengirimkan data ke penerima. Penulis juga menggunakan aplikasi Wireshark untuk mengambil data seperti delay, jitter, dan throughput. Untuk data packet loss dan round-trip time diambil dari aplikasi Command Prompt. Hasil yang didapatkan dari perancangan ini diharapkan dapat memberikan sebuah jalan atau terobosan baru bagi user dalam kegiatan pengiriman data yang dilakukan secara berkala dan berbasis online dengan menggunakan jaringan yang prima.
IMPLEMENTASI SISTEM PAKAR PADA PASIEN PENDERITA TUBERKULOSIS POTENTIAL DROP OUT DI RUMAH SAKIT CUT MEUTIA ACEH UTARA Eva Darnila; Mutammimul Ula; Mauliza Mauliza; Ermatita Ermatita; Iwan Pahendra
KOMIK (Konferensi Nasional Teknologi Informasi dan Komputer) Vol 2, No 1 (2018): Peranan Teknologi dan Informasi Terhadap Peningkatan Sumber Daya Manusia di Era
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/komik.v2i1.968

Abstract

The existence of a technology that identifies and controls patients with potential drop out TB disease which is increasingly rapid will be a top priority, especially for the health team in following up the success of treatment. In this study, an expert system was used to diagnose patients with potential Drop Out tuberculosis by using a Case Based Reasoning model to see patients with potential Droup Out. For variable names used are pulmonary smear patients (+), new patients, pulmonary smear (-) / ro (+), new patients, extra pulmonary, relapsed patients, re-treatment, default patients, re-treatment patients, failed patients and others -other. The last detection process is taken from the highest value obtained in the diagnosis of all the symptoms that have been witnessed. Based on the results of the application of the Expert System on Potential Drop Out Tuberculosis Patients at Cut Meutia Hospital in North Aceh based on the case code 31 with a detection system for the AFB (+) Lung Patient with its detection symptoms, the patient coughs with phlegm for 2-3 weeks or more. the results of sputum examination, patients who have been treated with TB drugs less than 1 month and TB patients on sputum examination, patients who have been treated with TB drugs less than 1 month, TB patients stop the treatment and TB patients return to the facility health service facilities with the highest case value of 0.6111 of all detection systems that have been tested.Keywords: Expert system,  CBS, TB
Co-Authors Abdul Haris Dalimunthe Abdul Haris Dalimunthe Abdul Haris Dalimunthe Ahmad Firman Aprimivi Manda Dalimunthe, Abdul Haris Deris Stiawan Deris Stiawan Desi Windi Sari Desi Windisari Dian Palupi Rini Dian Palupi Rini Ermatita Ermatita - Ermatita Ermatita Ermatita Ermatita Eva Damila Eva Darnila Eva Darnila eva darnila, eva darnila Fajriana, Fajriana Fajriana, Fajriana Fuadi, Wahyu Jaka Naufal Semendawai Jaka Naufal Semendawai Jaka Naufal Semendawai Khairunisa Khalid Mawardi Kurniasari, Puspa Maryana Maryana Mauliza Mauliza Mauliza Mauliza, Mauliza Melia Sari Melia Sari, Melia Miftahul Falah Miftahul Falah Mohamed Shenify Muhammad Fakhri Muhammad Sadli Muhammad Sadli Muhammad Sadli, Muhammad Mutammimul Ula Nadia Thereza Nadia Thereza Nadia Thereza Nadia Thereza Prasetio, Robi Puspa Kurniasari Puspa Kurniasari Rahmat Budiarto Richki Hardi Sari, Melia Semendawai, Jaka Naufal Sinambela Marzuki Wahyu Fuadi Wahyu Fuadi Zaenal Husin