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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Bulletin of Electrical Engineering and Informatics Jurnal Informatika Jurnal Informatika Proceeding International Conference on Information Technology and Business JUITA : Jurnal Informatika International conference on Information Technology and Business (ICITB) Annual Research Seminar JPSriwijaya Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Journal of Information Technology and Computer Science Inform : Jurnal Ilmiah Bidang Teknologi Informasi dan Komunikasi INTECOMS: Journal of Information Technology and Computer Science Jurnal ULTIMATICS Informatik : Jurnal Ilmu Komputer KOMIK (Konferensi Nasional Teknologi Informasi dan Komputer) SEINASI-KESI Jurnal Riset Informatika CSRID (Computer Science Research and Its Development Journal) Jurnal Informatika Global CCIT (Creative Communication and Innovative Technology) Journal Journal of Information Systems and Informatics Mulia International Journal in Science and Technical Indonesian Journal of Electrical Engineering and Computer Science Jurnal Generic Proceeding of International Conference Health, Science And Technology (ICOHETECH) Jurnal Pengabdian Kolaborasi dan Inovasi IPTEKS
Ermatita -
Universitas Sriwijaya
Agriculture, Biological Sciences & Forestry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Library & Information Science Medicine & Pharmacology Neuroscience Public Health Social Sciences

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SISTEM INFORMASI PERPUSTAKAAN SMP SANTO LOUIS PALEMBANG -, Ermatita
Jurnal Informatika Vol 16, No 1 (2016): Jurnal Informatika
Publisher : IIB Darmajaya

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Abstract

The development of information technology has been absolutely used by various institutions and organizations. Library on SMP St. Louis is a unit that serves the students, and have a lot of activity such as borrowing books, serve the creation of a membership card, manage the available data books and every transaction that occurs in the library. For it will be built the library information system at SMP St. Louis. This system was developed by FAST method. The results of this study are Informs library system that manages the data in the library. Given this system will simplify the management of the library. Additionally this system will provide services to students to more easily get information about books in a library. With the existence of the library information system then reports all activity in the Library, as well as information about the existence of the book easy to navigate.  Keywords: FAST, Information System, library 
ASSOCIATION RULE METHOD FOR INFORMATION SYSTEM EPIDEMIC DENGUE MAPPING BASED ASSOCIATION OF RISK FACTORS IN PALEMBANG Ermatita, Ermatita; Destriatania, Suci
Prosiding International conference on Information Technology and Business (ICITB) 2015: INTERNATIONAL CONFERENCE ON INFORMATION TECHNOLOGY AND BUSINESS (ICITB) 1
Publisher : Prosiding International conference on Information Technology and Business (ICITB)

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Abstract

Endemic diseases dangerous such as dengue fever must be handling seriously  for the risk minimize by the disease. Dengue Hemorrhagic Fever (DHF) is  disease  has not been found vaccine or cure is powerful. It is  necessary  treatment to prevent the occurrence of dengue fever, especially when it came to the incidence of dengue fever endemic in certain areas by doing Epidemiologist dengue fever. Epidemiology is identification of risk factors for DHF to find level of area  risk. Risk factors of hemorrhagic fever endemic must be identified  to prevent the occurrence of dengue fever. Identifying risk factors and  risk factors association  can  potential increase  the occurrence of dengue fever. This study developed  mapping information system Dengue epidemic through Association rule method of data mining. The information generated in the map of epidemic DHF level based association of potential risk factors that cause hemorrhagic fever endemic. Analysis with the Association Rule to determine level of  DHF epidemic area based data reporting system. KEY WORDS: information system mapping, data mining, Association Rule, endemic, Dengue Hemorrhagic Fever (DHF).
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
PERAMALAN POTENSI KEBAKARAN HUTAN DENGAN METODE DATA MINING Ermatita, Ermatita; Sukemi, Sukemi; Pratomo, Yudha
SEINASI-KESI Vol 1, No 1 (2018): Seinasi-Kesi 2018
Publisher : Fakultas Ilmu Komputer UPN Veteran Jakarta

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Abstract

Kebakaran hutan merupakan kejadian yang selalu berualang setiap tahun, terutama di Sumatera Selatan. Penanggulangan kebakaran hutan ini, terutama di lahan gambut, perlu dianalisis agar dapat diprediksi pola penyebaran kebakaran lahan gambut. Hal ini perlu dilakukan karena pemadaman kebakaran lahan gambut sulit dilakukan.Penelitian ini memproses data faktor-faktor yang memberikan potensi kebakaran hutan menerapkan data mining. Metode yang digunakan dalam penelitian ini . Hasil dari penelitian ini menunjukkan bahwa faktor-faktor penyebab dari kebakaran hutan yang diproses mempunyai potensi yang sama dalam menyebabkan kebakaran hutan.
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

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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

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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.
Penentuan Prioritas Pengembangan Industri Kecil dan Menengah di kota Palembang Metode Weighted Product (WP) (studi kasus : Dinas Perindustrian, Perdagangan dan Koperasi Kota Palembang Ermatita, Ermatita; Zalika, Indah; Putra, Pacu
SEINASI-KESI Vol 2, No 1 (2019): Seinasi-Kesi 2019
Publisher : Fakultas Ilmu Komputer UPN Veteran Jakarta

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Abstract

Dinas Perindustrian, Perdagangan dan Koperasi (Disperindag) Kota Palembang merupakan salah satu unsur pemerintahan yang bertanggung jawab di bidang pengembangan Industri Kecil Menengah(IKM) Kota Palembang. Dalam pengembang IKM sendiri terkadang sulit menentukan IKM yang layak disebut prioritas karena banyaknya kriteria yang sama untuk penilaian pada IKM Kota Palembang serta belum adanya sistem yang memiliki pemodelan data untuk mendukung keputusan tersebut. Untuk meminimalkan kendala tersebut maka diperlukan suatu sistem pendukung keputusan yang dapat membantu para pengambil keputusan(decision maker) menganilisa IKM yang layak mendapat prioritas. Salah satu metode yang dapat digunakan yaitu weighted product (WP), metode weighted product dapat digunakan untuk proses keputusan multi-dimensi, yang disebut dengan analisis berdimensi. Dalam pengembangan sistem ini  menggunakan metode waterfall, waterfall dipilih karena stakeholder mendefinisikan terlebih dahulu nilai bobot yang diperlukan dalam proses perhitungan metode WP.  Dari hasil implementasi sistem, disimpulkan bahwa dengan penggunaan sistem ini dapat membantu proses pengambilan keputusan untuk proses penentuan prioritas pengembangan IKM di Kota Palembang
Penerapan Knowledge Management System Berbasis Web Menggunakan Model Inukshuk dan Algoritma Levenshtein Octaria, Orissa; Ermatita, Ermatita; Sukemi, Sukemi
CSRID (Computer Science Research and Its Development Journal) Vol 11, No 2 (2019): CSRID JUNI 2019
Publisher : Universitas Potensi Utama

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (264.369 KB) | DOI: 10.22303/csrid.11.2.2019.63-73

Abstract

Manajemen pengetahuan atau knowledge management (KM) merupakan hal yang penting untuk  menyimpan atau mengatur pengetahuan yang sejatinya sudah ada. Sulitnya mendapatkan pengetahuan yang sebenarnya sudah lama diketahui menjadi kendala tersendiri bagi penerus baru untuk melanjutkan suatu jabatan tertentu, dalam hal ini wadah yang diteliti adalah bebrapa perguruan tinggi swata kota Palembang. Dosen baru dapat mengetahui bagaimana sistem pengajaran dalam perguruan tinggi tersebut, dan banyak pengetahuan lain yang harus dipahami oleh dosen baru tersebut. Oleh karena itu maka akan di bangun KMS menggunakan Model Inukshuk untuk menjadi sarana untuk mengatur pengetahuan yang yang sudah ada, adapun algoritma pencarian yang digunakan adalah Algoritma Levenshtein. Hasil yang ada nantinya berupa KMS yang penting bagi perguruan tinggi swasta tersebut untuk meyimpan serta mengelola sebuah pengetahuan. KMS yang dibangun akan berbasis web guna memudahkan pengguna yang sekarang ini sudah banyak menggunakan jaringan internet.
Model Promosi Pemilihan Jabatan Manajer Menggunakan Metode Weighted Product (WP) ( Studi Kasus: Bank Indonesia Provinsi Sumatera Selatan) Ermatita, Ermatita; Safithri, Selviana Rizki; Bardadi, Ali; Adrezo, Muhammad
SEINASI-KESI Vol 3, No 1 (2020): SEINASI-KESI 2020
Publisher : Fakultas Ilmu Komputer UPN Veteran Jakarta

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Abstract

Promosi jabatan memiliki peranan penting sebagai salah satu pergerakan pertumbuhan perusahaan. Bank indonesia provinsi sumatera selatan merupakan salah satu tempat mempunyai fungsi penting di dalam melayani masyarakat terutama masyarakat yang berada di provinsi sumatera selatan. Dalam pemilihan jabatan manajer terkadang sulit untuk menentukan siapa yangg layak dijadikan manajer karena banyaknya kriteria yang sama untuk penilaian jabatan manajer serta belum adanya sisstem yang memiliki permodelan data untuk mendukung suatu sistem pendukung keputusan. Untuk meminimalkan kendala tersebut maka diperlukan suatu sistem pendukung keputusan yang dapat membantu para pengambil keputusan (decision maker) menganalisa promosi jabatan manajer yang layakmendapatkan prioritasnya. Salah satu metode yang digunakan yaitu metode weighted product (WP) dimana metode weighted product adalah metode pengambilan keputusan multi kriteria
Co-Authors Abdiansah, Abdiansah Adi Sutrisman Ahmad Fali Oklilas Aidil Putrasyah Al Farissi Aldin, Moehammad Ali Bardadi Ali Bardardi Ali Ibrahim Ali Ibrahim Allsela Meiriza, Allsela Andini Dwi Lestari Apriansyah Putra Barlian Khasoggi Barlian Khasoggi Cindo, Mona Dafid Dedik Budianta Deris Stiawan Dian Palupi Rini Dian Palupi Rini Dien Novita Dwi Asa Verano Dwi Meylitasari Br. Tarigan Dwi Rosa Indah Endah Patimah Endy Suherman Erwin, Erwin Eva Darnila Eva Darnila Fajriana Fajriana, Fajriana Fathoni - Fauza Adelma Syafrizal Fuadi, Wahyu Huda Ubaya Huda Ubaya Husnawati Husnawati Ika Oktavianti ina aisyah handayani Indra Maulana Irmanda, Helena Nurramdhani Iwan Pahendra Iwan Pahendra Anto Saputra Jaidan Jauhari Johannes Petrus Joko Purnomo Ken Dhita Tania Kurniawan, Rizky Fariz Andry Lovinta Happy Atrinawati M Fariz Januarsyah M. Fariz Januarsyah M. Miftakul Amin Mauliza Mauliza, Mauliza Megah Mulya Mgs Afriyan Firdaus Mira Afrina Mochamad Aryo Aji Kurniawan Mohammed Y. Alzahrani Mona Cindo Monterico Adrian Muhammad Adrezo Muhammad Sadli Muhammad Sadli, Muhammad Mutammimul Ula Mutia Fadhila Putri Noor Falih Nurul Chamidah Nurul Mufliha Eka Putri Nurul Mufliha Eka Putri Octaria, Orissa Pacu Putra Pahendra, Iwan Parwito Parwito Rachma nia Rahman, Puti Ayu Andhini Rahmat Izwan Heroza Rahmat Izwan Heroza Reza Alfarezy Reza Firsandaya Malik Richki Hardi Rizka Dhini Kurnia Rizka Dhini Kurnia Royan Dwi Saputra Ruth Mariana Bunga Wadu Safithri, Selviana Rizki Samsuryadi Samsuryadi Shinta Puspasari Suci Destriatania Suci Destriatania Sukemi Sukemi Susan Dwi Saputri Susan Dwi Saputri Terttiaavini, Terttiaavini Verlly Puspita Wahyu Fuadi Yadi Utama Yudha Pratomo Yudha Pratomo Yudha Pratomo Yundari, Yundari Zalika, Indah