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All Journal JURNAL MEDIA INFORMATIKA BUDIDARMA Building of Informatics, Technology and Science Journal of Computer System and Informatics (JoSYC) Jurnal Sistem Komputer dan Informatika (JSON) KLIK: Kajian Ilmiah Informatika dan Komputer
Lola Oktavia
Universitas Islam Negeri Sultan Syarif Kasim Riau, Pekanbaru
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Industrial & Manufacturing Engineering

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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%.
S Sistem Pakar Diagnosa Gangguan Kejiwaan Menggunakan Metode Inferensi Forward Chaining dan Certainty Factor Muhammad Fauzan; Fitri Wulandari; Elin Haerani; Lola Oktavia
Building of Informatics, Technology and Science (BITS) Vol 4 No 4 (2023): Maret 2023
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v4i4.3232

Abstract

The era of artificial intelligence AI technology is now an advantage because the system does all the work according to the human brain. Expert Systemis abranch ofartificial intelligencethat adapts the mind and reasoning of an expert to solve a problem and make a decision so that it draws conclusions based on the facts. From cases of psychiatric disorders, this expert system is highly recommended to make it easier to find out what type of disorder you are suffering from to assist the public and experts in diagnosing diseases quickly and accurately. For this reason, researcherscreated an expert system for diagnosingpsychiatric disordersusing the forwardchaining inferencemethod and certainty factor. Based on the results of the implementation and analysis thathave been carried out in this study, it produces a software system, namely an expert system that has an easy-to-understand display, and can assist experts in diagnosing psychiatric disorders
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.
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
Pemodelan Klasifikasi Untuk Menentukan Penyakit Diabetes dengan Faktor Penyebab Menggunakan Decision Tree C4.5 Pada Wanita Nining Nur Habibah; Alwis Nazir; Iwan Iskandar; Fadhilah Syafria; Lola Oktavia; Ihda Syurfi
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.v4i4.6202

Abstract

Diabetes is closely related to the pancreas, where the pancreas produces the natural hormone insulin, but its function is problematic which causes an increase in blood sugar levels in the body. Rising blood pressure can affect organ function in damaging the function of organs in a person's body such as the kidneys, heart and brain. Where makes a person have a history of diabetes. Diabetes that attacks adults can be prevented through exercise and a regular and healthy diet. According to the International Diabetes Federation (IDF) organization, it is estimated that at least 19.5 million Indonesian people between the ages of 20 and 79 will suffer from diabetes in 2021. China is in first place with diabetes with 140.9 million people. India is next in line with the number of people with diabetes of 74.2 million people. Therefore, early diagnosis is very important because it aims to reduce diabetes and diabetes complications in the future. It is necessary to collect data on patients with diabetes who are expected to be able to do prevention. Therefore applying classification techniques with data mining with the C4.5 algorithm. Where the classification can achieve better accuracy. Algorithm C4.5 is generally used in determining the nodes of a decision tree. Based on the test results, the accuracy is 76.67 percent, the precision is 72 percent, and the recall is 41.67 percent.
Penerapan Algoritma K-Medoids Pada Clustering Penerima Bantuan Pangan Non Tunai (BPNT) Tiara Ramayanti; Elin Haerani; Jasril Jasril; Lola Oktavia
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 7, No 3 (2023): Juli 2023
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v7i3.6475

Abstract

Bantuan Pangan Non Tunai (BPNT) is assistance distributed by the government to underprivileged communities to ease the financial burden that is increasingly burdening their lives. In a number of cases, it was found that the number of people who received BPNT was not properly targeted, so it was necessary to analyze the pattern of the characteristics of BPNT recipients so that the assistance was right on target. There are many criteria that must be considered to determine the people who are entitled to receive BPNT, so an appropriate algorithm is needed to determine the right cluster when analyzing characteristic patterns. This study applies the K-Medoids algorithm to classify BPNT data obtained from Firza Syahputra's research in 2020–2021, with a total of 732 attributes, so that the government can consider the factors that characterize beneficiaries. Perform tests using the Silhouette coefficient, which is useful for maximizing clustering results. The clustering result is three clusters, and the silhouette coefficient is 0.4439221599010089. The results of the analysis show that clustering performed using the K-Medoids algorithm can assume that clusters are grouped according to grouping: cluster 0 is eligible to receive BPNT, cluster 1 is considered, and cluster 2 is not eligible to receive BPNT.
Penerapan Fuzzy C-Means Pada Klasterisasi Penerima Bantuan Pangan Non Tunai Sola Huddin; Elin Haerani; Jasril Jasril; Lola Oktavia
KLIK: Kajian Ilmiah Informatika dan Komputer Vol. 4 No. 1 (2023): Agustus 2023
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/klik.v4i1.988

Abstract

One of the social assistance programs routinely provided by the government to Beneficiary Families (KPM) to overcome poverty problems in Indonesia at this time is Non-Cash Food Assistance (BPNT). The Pekanbaru City Social Service itself in distributing BPNT still experiences obstacles, such as the provision of assistance that is less targeted due to the absence of a system that is able to determine the recipient of aid appropriately. This research applies the Fuzzy C-Means Clustering method to analyze KPM data using MATLAB tools. This algorithm allows overlap between data groups and classifies KPM based on their characteristic patterns. This algorithm takes into account the membership level of each data in each group, thus providing more flexible results and not categorizing data rigidly. The results of the application of the FCM Clustering method in this study form two clusters, where the first cluster contains 331 data while in the second cluster there are 351 data. Testing the results of FCM clustering conducted using the Silhouette Coefficient method produces an average coefficient value of 0.426653079. Based on the value of the test results that have been carried out, the FCM algorithm is considered capable of forming clusters on BPNT data
Pengukuran Tingkat Layanan Helpdesk Menggunakan COBIT 5 Febby Kurniawan; Novriyanto; Elin Haerani; Lola Oktavia
KLIK: Kajian Ilmiah Informatika dan Komputer Vol. 4 No. 3 (2023): Desember 2023
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/klik.v4i3.1474

Abstract

The Riau Provincial Information and Statistics Communication Service is a government agency tasked with formulating policies, conducting evaluations and reporting in the field of information and communication technology in various sectors of society. The Riau Provincial Information and Statistics Communication Agency has one of the services, namely a helpdesk to assist in handling problems related to the use of information technology. The helpdesk is one of the most important parts in the Riau Provincial Information and Statistics Communication Service because it is a liaison for each Regional Apparatus Organization (OPD), but the helpdesk at the Riau Provincial Information and Statistics Communication Service (Diskominfotik) does not yet have a benchmark that can be used to evaluate the performance of the helpdesk system. The purpose of this study is to determine the level or level of helpdesk services in optimizing information technology using the COBIT 5 framework and focusing on DSS03 Domain. This research was conducted by interviewing 8 respondents who were involved in the helpdesk and had 27 questions on the DSS03 domain. This research obtained the results of measuring the level of helpdesk service capability in Diskominfotik Riau Province  is at level 4, namely Predictable  Process where diskominfotik has run IT processes in accordance with established SOPs but needs to make continuous improvements in order to reach the target level to be achieved, which is at level 5 Optimizing Process
Penerapan Algoritma Naïve Bayes Classifier Dalam Klasifikasi Status Gizi Balita dengan Pengujian K-Fold Cross Validation Nurainun Nurainun; Elin Haerani; Fadhilah Syafria; Lola Oktavia
Journal of Computer System and Informatics (JoSYC) Vol 4 No 3 (2023): May 2023
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v4i3.3414

Abstract

Nutritional status is a condition related to nutrition that can be measured and is the result of a balance between nutritional needs in the body and nutritional intake from food. In Indonesia, there are still many nutritional problems such as malnutrition and other nutritional problems. This research will use the Naïve Bayes Classifier algorithm with K-Fold Cross Validation testing. The data used is data on the nutritional status of toddlers in August 2022 at the Rambah Samo I Health Center. Attributes in this study include Gender, Birth Weight, Birth Height, Age at Measurement, Weight, Height, ZS BB/U, BB/U, ZS TB/U, and TB/U. Determination of the nutritional status of toddlers in this study was based on the BB/TB index which consisted of 6 classes, namely severely wasted, wasted, normal, possible risk of overweight, overweight, and obese. From the research conducted, it was found that the Naïve Bayes Classifier algorithm with K-Fold Cross Validation can correctly classify the nutritional status of toddlers. From data processing using 10-Fold Cross Validation on the Naïve Bayes Classifier algorithm, it is known that the highest accuracy value is 82.94% in the 5th iteration, while the lowest accuracy value is 65.88% in 6th iteration. With an average overall accuracy value of 75.47%. Meanwhile, the average precision value obtained is 81.36% and the average recall value is 75.47%.
Co-Authors Alwis Nazir Eka Suryani Indra Septiawati Elin Haerani Elvia Budianita Fadhilah Syafria Febby Kurniawan Fitra Kurnia Fitri Insani Fitri Wulandari Heri Susanto Ihda Syurfi Iwan Iskandar Jasril Jasril Lili Rahmawati Marliana Safitri Muhammad Affandes Muhammad Fauzan Nining Nur Habibah Novi Yanti Novriyanto Novriyanto Nurainun Nurainun Raja Sultan Firsky Reski Mai Candra Sola Huddin Tiara Ramayanti Yusra Yusra