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All Journal Indonesian Journal of Electrical Engineering and Informatics (IJEEI) CESS (Journal of Computer Engineering, System and Science) JURNAL MEDIA INFORMATIKA BUDIDARMA Seminar Nasional Teknologi Informasi Komunikasi dan Industri INTEK: Informatika dan Teknologi Informasi Jurnal Sistem informasi dan informatika (SIMIKA) Jurnal Tekinkom (Teknik Informasi dan Komputer) Journal of Computer System and Informatics (JoSYC) Jurnal Sistem Komputer dan Informatika (JSON) JUKI : Jurnal Komputer dan Informatika KLIK: Kajian Ilmiah Informatika dan Komputer SATIN - Sains dan Teknologi Informasi
Lola Oktavia
Universitas Islam Negeri Sultan Syarif Kasim Riau
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Mathematics Other

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Optimalisasi Pelayanan Kesehatan Melalui Integrasi Data Rekam Medis Rumah Sakit dan Puskesmas Suwanto Sanjaya; Lola Oktavia
Seminar Nasional Teknologi Informasi Komunikasi dan Industri 2015: SNTIKI 7
Publisher : UIN Sultan Syarif Kasim Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (466.439 KB)

Abstract

Each patient was treated at the hospital will be recorded in medical records at the hospital orclinic. Medical records of a patient in a hospital or health center is certainly not complete because patientstreated in different health centers and hospitals.Medical record separately in each health center and thehospital complicates the search and analyze medical history. Surely this can reduce the level of healthcare to patients. In this research, created a system that can integrate medical records each health centerand the hospital. Medical record data were taken from the Ibnu Sina hospital, Eria Bunda hospital, StabitaClinic, Nurul Shadri Clinic and Assyafni Clinic . Every business processes in hospitals and clinics traced tocreate a web service that will be parsing the medical records of each application to hospitals and clinics.With the implementation of the web service, medical record will be integrated with each other, thussimplifying the processing, and search history data medical records of patients. A complete medical recordhelps doctor to analyze disease and treatment process. This helps hospitals to improve health services forpatientsKeywords: Data Integration, Hospital, Medical Records, Patient, Web Service
Sistem Pemilihan Produk Skincare Untuk Pria Menggunakan Metode Simple Additive Weighting (SAW) Novendri Wahyudy; Elin Haerani; Fitra Kurnia; Lola Oktavia
INTEK : Jurnal Informatika dan Teknologi Informasi Vol. 5 No. 2 (2022)
Publisher : Universitas Muhammadiyah Purworejo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37729/intek.v5i2.2416

Abstract

Skincare identik dengan kesehatan wajah pada wanita, padahal pria juga membutuhkan perawatan kulit. Pria terutama kalangan remaja bisa memiliki masalah kulit seperti jerawat, kulit kusam, kulit terbakar terkena sinar UV, kulit berminyak. Permasalahan yang timbul yaitu sulitnya pria mendapatkan rekomendasi skincare yang tepat dan belum ada informasi yang membantu dalam memilih skincare. Kriteria yang masuk pada penelitian yaitu keluhan, jenis kulit, harga, merek, usia, kemasan dan kualitas. Penelitian pemilihan produk skincare pria dapat memberi manfaat bagi pria untuk mempermudah dalam memilih skincare yang tepat berdasarkan jenis kulit wajah masing - masing. Proses sistem menggunakan metode Simple Additive Weighting (SAW) dan implementasi menggunakan bahasa pemrograman Hypertext Prepocessor (PHP). Hasil penelitian ini dapat mempermudah pria untuk memilih produk skincare pria berdasarkan pengujian. Pengujian berdasarkan hasil analisa fungsional keseluruhan sistem dari pengujian Black Box mendapatkan hasil “Valid” dan pengujian menggunakan User Acceptance Testing (UAT) mendapatkan hasil skor 4,32 dari 4,21 – 5,00 “Sangat Setuju”.
KLASIFIKASI STATUS GIZI BAYI POSYANDU KECAMATAN BANGUN PURBA MENGGUNAKAN ALGORITMA SUPPORT VECTOR MACHINE (SVM) Emir Ramon; Alwis Nazir; Novriyanto Novriyanto; Yusra Yusra; Lola Oktavia
Jurnal Sistem Informasi dan Informatika (Simika) Vol 5 No 2 (2022): Jurnal Sistem Informasi dan Informatika (Simika)
Publisher : Program Studi Sistem Informasi, Universitas Banten Jaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47080/simika.v5i2.2185

Abstract

This research was conducted to apply the Support Vector Machine algorithm in the process of classifying the nutritional status of infants under five. The nutritional status of early childhood can determine what kind of human resources as successors of a nation in the future. Good nutritional status plays an important role in determining the success or failure of efforts to increase human resources, so that data on the nutritional status of toddlers such as at the Posyandu, Bangun Purba District can be classified using Data Mining techniques using the Support Vector Machine algorithm. The results of this study using 80% of the data as training data and 20% of the data as training data are f1 score 0.865, accuracy 0.876, precision score 0.871, and recall score 0.876. The results showed that from a total of 347 data on the nutritional status of infants, there were 284 infants with good nutrition, 15 infants with poor nutrition, 23 infants with less nutrition, 8 infants with excess nutrition, 6 infants with obesity, and 11 infants at risk of overnutrition. Based on these results, there were 304 baby nutrition data that were classified correctly from a total of 347 baby data that were used as testing data. From this research, it can be concluded that the Support Vector Machine algorithm can classify infant nutrition data at the Posyandu, Bangun Purba District, well.
Implementasi Metode Moora Pada Sistem Pendukung Keputusan Penilaian Kinerja Karyawan Heri Susanto; Fitra Kurnia; Yusra Yusra; Lola Oktavia
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 6, No 4 (2022): Oktober 2022
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v6i4.4750

Abstract

Employee performance appraisal is needed by an agency or company with the aim of evaluating performance and improving the quality of competent human resources and high loyalty for each employee at work, then an agency or company can give awards to each of its employees such as contract extensions, salary increases , get special promotions, appointments, and allowances, which can motivate every employee. This study aims to facilitate a planner in a company PT. SUPRACO INDONESIA in providing performance appraisals of each employee uses a decision support system using the Multi Objective Optimization On The Basic Of Ratio Analysis (MOORA) method. This employee performance appraisal decision support system uses a sample of 3 employees from 11 employees using the MOORA method of calculation. the final results of the calculations carried out are: for the first rank in alternative 2 with a value of 5.7805, while the second rank in alternative 1 with a value of 5.7736, and third place in alternative 3 with a value of 5.7671. In the tests carried out using Blackbox Testing, for all the features on the system running 100% with very good information and testing using the UAT (User Acceptance Test) method, it showed that the results of system user acceptance were 92%.
KLASIFIKASI PENYAKIT PARU-PARU DENGAN MENGGUNAKAN METODE NAÏVE BAYES CLASSIFIER Muhammad Yusril Haffandi; Elin Haerani; Fadhilah Syafria; Lola Oktavia
Jurnal Tekinkom (Teknik Informasi dan Komputer) Vol 5 No 2 (2022)
Publisher : Politeknik Bisnis Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37600/tekinkom.v5i2.649

Abstract

The lungs are one of the organs of the human body that are very important in the process of respiration. There are several types of lung diseases, including Asthma, Bronchitis, Dyspnea, Pneumonia, COPD, and Tuberculosis. There are difficulties in the classification process, because the symptoms shown by sufferers have similarities between diseases. The purpose of this research is to classify lung disease using the Naive Bayes Classifier method. The choice of this method is because it only requires a small amount of training data to determine the estimated parameters needed in the classification process. This research was conducted at the Regional General Hospital Major General HA Thalib City of Sungai Full from August 3 2022 to September 3 2022. The data taken was in the form of medical records of lung disease patients from July to August as many as 134 patient data containing 19 symptoms disease and 6 disease diagnoses. From the test results using the Rapidminer application and data separation in the form of 34 testing data and 100 training data with a data comparison of 7:3, an accuracy value of 97.06 was obtained.
Penerapan Data Mining untuk Menentukan Penyebab Kematian di Indonesia Menggunakan Metode Clustering K-Means Lili Rahmawati; Alwis Nazir; Fadhilah Syafria; Elvia Budianita; Lola Oktavia; Ihda Syurfi
Jurnal Sistem Komputer dan Informatika (JSON) Vol 4, No 3 (2023): Maret 2023
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/json.v4i3.5912

Abstract

Death in medical science is studied in a scientific discipline called tanatology. death is not only experienced by elderly people, but also can be experienced by young people, teenagers, or even babies. Death can be caused by various factors, namely, due to illness, old age, accidents, and so on. Based on information provided by the World Health Organization (WHO), there are five highest causes of death including ischemic heart disease, Alzheimer's, stroke, respiratory disorders, neonatal conditions. In this study, k-means is used to group causes of death in Indonesia based on the number of deaths that occur to determine the cases of death that have the most impact on the high mortality rate in Indonesia. Knowing what these death cases are will provide early preparation in anticipating the causes of death in Indonesia. The purpose of this study was to classify mortality rates based on the number of causes of death which were included in the low, medium, and high clusters by applying the K-Means method. In this study the authors used the K-Means clustering algorithm to classify death rates in data on causes of death in Indonesia from 2017-2021. The results of this study formed 3 clusters which were evaluated using the Davies Bouldin Index (DBI) in Rapidminer with a value of 0.259. Clustering results from a total of 21 cases obtained high, medium and low clusters. This cluster grouping was obtained according to the number of deaths per case, namely the first cluster (C0) was low with 17 cases, the second cluster (C1) was moderate with 3 cases and the third cluster (C2) was high with 1 case.
Klasifikasi Sentimen Masyarakat di Twitter terhadap Kenaikan Harga BBM dengan Metode K-NN Tiara Dwi Arista; Yusra Yusra; Muhammad Fikry; Lola Oktavia
JUKI : Jurnal Komputer dan Informatika Vol. 5 No. 1 (2023): JUKI : Jurnal Komputer dan Informatika, Edisi Mei 2023
Publisher : Yayasan Kita Menulis

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

Abstract

Kenaikan harga Bahan Bakar Minyak (BBM) di Indonesia merupakan isu besar yang menjadi topik utama hingga saat ini. Kenaikan harga BBM di Indonesia telah belangsung sejak awal September 2022. Kebijakan pemerintah menaikkan harga BBM kemudian menimbulkan banyak opini dari kalangan masyarakat. Opini masyarakat terkait kebijakan pemerintah adanya sentimen positif dan negatif yang dapat dilihat melalui media sosial, seperti Twitter. Tujuan dari penelitian ini adalah untuk mengklasifikasikan sentimen masyarakat terhadap kenaikan harga BBM di Twitter. Jumlah data yang digunakan adalah 3000 tweet yang dikumpulkan berdasarkan kata kunci yaitu “Kenaikan BBM” dan “BBM naik”. Menerapkan metode K-Nearest Neighbor (K-NN), Feature Weighting (TF-IDF), dan Feature Selection (Threshold) akan dilakukan implementasi dengan menggunakan tools yaitu Google Collab . Berdasarkan hasil pengujian metode K-NN menggunakan matriks konfusi pada 10 nilai K yang berbeda (3,5,7,9,11,13,15,17,19,21) dengan mekanisme perbandingan yang digunakan 70:30, 80:20, dan 90:10 diperoleh akurasi paling tinggi sebesar 83,3% pada K=13 dan K=15 untuk perbandingan data training dan testing 90:10.
Sistem Pakar Diagnosa Gangguan Stress Pasca Trauma Menggunakan Metode Certainty Factor Marliana Safitri; Fitri Insani; Novi Yanti; Lola Oktavia
Jurnal Sistem Komputer dan Informatika (JSON) Vol 4, No 4 (2023): Juni 2023
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/json.v4i4.6309

Abstract

Mental health disorder or commonly called Mental Health Disorder is a disturbing psychological behavior and is followed by traumatic events such as shock shell, war fatigue, accidents, victims of sexual violence, and the covid pandemic. Cases of post traumatic stress disorder data from Indonesian Psychiatric Association amounted to 80% of 182 examiners experiencing symptoms of post-traumatic stress due to exposure to covid, 46% experienced severe symptoms, 33% moderate, 2% mild and others did not show symptom. This study aims to diagnose post traumatic stress disorder using the assurance factor method with 35 symptom data and 3 levels of post traumatic stress disorder as a knowledge base. The certainty factor is a circulation management method and a decision-making strategy using the confidence factor in the system. Based on the research results of the expert system for diagnosing post traumatic stress disorder, the test results obtained an accuracy of 80%. The results of the accuracy of this expert system indicate that the expert system can potentially be used to diagnose post traumatic stress disorder.
Analisa Website Donasi Rumah Tahfizh Menggunakan Metode PIECES Raja Sultan Firsky; Fadhilah Syafria; Muhammad Affandes; Reski Mai Candra; Lola Oktavia
KLIK: Kajian Ilmiah Informatika dan Komputer Vol. 3 No. 6 (2023): Juni 2023
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/klik.v3i6.810

Abstract

One of the many media utilized on the internet is websites. Inadequate website performance, an abundance of irrelevant material, an unappealing website design, confusing navigation menus, and several other issues that influence website quality are issues that are frequently observed on websites. A non-profit organization called Rumah Tahfizh Donation operates a website with the domain donasirumahtahfizh.com that serves as a source of information for both website visitors and donors. The lack of website visitors is a problem Rumah Tahfizh Donation has to face. The more people who visit the website are needed so that more and more people know about the Rumah Tahfizh Donation, the more people want to donate through the Rumah Tahfizh Donation. You can use the PIECES Framework as a guide when creating the website in order to raise its quality. The PIECES Framework is a framework that has categories for dividing up issues and coming up with solutions. According to order, the classification is broken down into six groups: performance, information, economics, control, efficiency, and service. Further testing using the GTMetrix tool is required because the PIECES test has a flaw, notably the inability to acquire a load time score. Additionally, GTMetrix offers a grade that includes a score. The grade and score you receive go up the quicker the website loads
Klasifikasi Sentimen Masyarakat di Twitter terhadap Kenaikan Harga Bahan Bakar Minyak dengan Metode Modified K-Nearest Neighbor Sofiah; Yusra; Muhammad Fikry; Lola Oktavia
SATIN - Sains dan Teknologi Informasi Vol 9 No 1 (2023): SATIN - Sains dan Teknologi Informasi
Publisher : STMIK Amik Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (963.796 KB) | DOI: 10.33372/stn.v9i1.988

Abstract

Kenaikan harga Bahan Bakar Minyak menjadi salah satu tranding topic di kalangan masyarakat Indonesia, baik di dunia nyata maupun dunia maya khususnya di media sosial Twitter. Perkembangan teknologi informasi yang sangat pesat memudahkan masyarakat dalam menyebarkan informasi di sosial media. Naiknya harga BBM memunculkan opini masyarakat yang mengandung sentimen positif dan negatif. Penelitian ini dilakukan untuk mengetahui sentimen publik terkait kebijakan pemerintah yang menaikkan harga BBM serta menerapkan metode Modified K-Nearest Neighbor dalam pengklasifikasian sentimen pengguna Twitter terhadap kenaikan harga BBM. Modified K-Nearest Neighbor merupakan salah satu metode klasifikasi berdasarkan kemunculan kelas terbanyak pada data latih. Data yang digunakan adalah tweet dalam bahasa Indonesia berdasarkan kata kunci “kenaikan BBM” dengan jumlah dataset sebanyak 3.000 tweet. Pembobotan kata dengan menggunakan TF-IDF untuk melakukan klasifikasi sentimen ke dalam dua kelas positif dan negatif. Hasil dari penelitian ini adalah klasifikasi sentimen terhadap kenaikan harga BBM. Akurasi tertinggi didapat 83.33% pada data opini menggunakan perbandingan 90:10 dan K=3.
Co-Authors Abdillah, Rahmad Alwis Nazir Alwis Nazir Alwis Nazir Eka Suryani Indra Septiawati Elin Haerani Elin Haerani Elin Haerani Elin Haerani Elin Haerani Elin Haerani Elvia Budianita Emir Ramon Fadhilah Syafria Febby Kurniawan Fitra Kurnia Fitra Kurnia Fitri Insani Heri Susanto Ihda Syurfi Irma Sanela Iwan Iskandar Jasril Jasril Lili Rahmawati Marliana Safitri Muhammad Affandes Muhammad Fikry Muhammad Yusril Haffandi Nining Nur Habibah Novendri Wahyudy Novi Yanti Novriyanto Novriyanto Nurainun Nurainun Okfalisa Okfalisa Pizaini Pizaini Raja Sultan Firsky Reski Mai Candra Rizuan Rizuan Said Nanda Saputra Saktioto Saktioto Sofiah Sola Huddin Suwanto Sanjaya Tiara Dwi Arista Tiara Ramayanti Yusra Yusra Yusra Yusra, Yusra