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Contact Name
Prof. Dr. H. Jufriadif Na`am, S.Kom, M.Kom
Contact Email
jufriadifnaam@upiyptk.ac.id
Phone
+6287895670026
Journal Mail Official
jidt@upiyptk.ac.id
Editorial Address
Kampus Universitas Putra Indonesia YPTK Padang Jl. Raya Lubuk Begalung Padang, Sumatera Barat - 25221
Location
Kota padang,
Sumatera barat
INDONESIA
Jurnal Informasi dan Teknologi
ISSN : 27149730     EISSN : 27149730     DOI : https://doi.org/10.37034/jidt
Core Subject : Science,
Jurnal Informasi & Teknologi media kajian ilmiah hasil penelitian, pemikiran dan kajian analisis-kritis mengenai penelitian Rekayasa Sistem, Teknik Informatika/Teknologi Informasi, Manajemen Informatika dan Sistem Informasi. Sebagai bagian dari semangat menyebarluaskan ilmu pengetahuan hasil dari penelitian dan pemikiran untuk pengabdian pada Masyarakat luas dan sebagai sumber referensi akademisi di bidang Teknologi dan Informasi.
Articles 14 Documents
Search results for , issue "2021, Vol. 3, No. 4" : 14 Documents clear
Sistem Pakar dalam Mengidentifikasi Penyakit pada Sapi Bali Menggunakan Metode Certainty Factor M Rasyid; S Sumijan
Jurnal Informasi dan Teknologi 2021, Vol. 3, No. 4
Publisher : Rektorat Universitas Putra Indonesia YPTK Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/jidt.v3i4.145

Abstract

Bali cattle are livestock that are very easy to maintain and the price is economical. Most of the people of Kampar Regency, Riau Province, keep cattle with the type of Bali cattle. The difficulty that is often experienced by Balinese cattle breeders is the disease that attacks Bali cattle. Lack of knowledge of breeders in diseases that attack Bali cattle resulted in the death of Bali cattle due to lack of handling and farmers suffered losses. The purpose of this study is to create an expert system that can assist veterinarians, animal health workers in identifying early diseases that attack Bali cattle and how to treat them early. To make it easier to identify diseases in Bali cattle, the method used in this study is the Certainty Factor (CF) method, where this method proves a fact in an incident based on evidence from experts. The data processed in this study were 6 types of diseases. The results of this study produce a value for the level of certainty of a disease that attacks Bali cattle and can assist veterinarians in identifying the types of diseases in Bali cattle.
Klasifikasi Penerima Bantuan Pangan Non Tunai Menggunakan Metode Decision Tree Nopi Purnomo; Sarjon Defit; Y Yuhandri
Jurnal Informasi dan Teknologi 2021, Vol. 3, No. 4
Publisher : Rektorat Universitas Putra Indonesia YPTK Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/jidt.v3i4.148

Abstract

Non-Cash Food Assistance is one of the government programs that has changed its name from the RASKIN or RASTRA program which is given to poor families every month by providing an electronic account to buy food at a seller that has been determined by the village government in collaboration with Bank Mandiri. The food assistance given to the beneficiary families is a form of government concern in accordance with the criteria determined by the Ministry of Social Affairs of the Republic Indonesia. The problem that often occurs in the Cipang Kiri Hulu Village Government was the difficulty in determining families who deserve to be given the non-cash food assistance in every year, so that it can cause messy and also protests from the people due to the large number of beneficiary families who are not on target. This study was conducted to classify families who receive the non-cash food assistance so that the results of this study can be used as a reference in making decisions whether appropriate or not to receive the non-cash food assistance in Cipang Kiri Hulu Village. The method that used was classification with the Decision Tree C4.5 Algorithm by using 14 attributes. The data used in this study was data from observations at the research location and interviews directly at the homes of families who received the non-cash food assistance in 2021 where there were 62 population data that have been presented in the csv file. The analysis of this study used the Rapid Miner Software version 9.5.001. The result of this research was to get 3 Rules. The rule was obtained from the final result of the decision tree's form.
Sistem Pakar Dalam Mengidentifikasi Kenaikan Pangkat Pegawai Negeri Sipil Menggunakan Metode Backward Chaining Yolla Rahmadi Helmi; Y Yuhandri; Gunadi Widi Nurcahyo
Jurnal Informasi dan Teknologi 2021, Vol. 3, No. 4
Publisher : Rektorat Universitas Putra Indonesia YPTK Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/jidt.v3i4.149

Abstract

Promotion can be interpreted as an element in enforcing the career of Civil Servants (PNS). The promotion to the rank of Civil Servants (PNS) is in the form of an award for work achievements that have been achieved and service to the country after fulfilling certain conditions. At this time there are still many Civil Servants (PNS) who do not understand employee governance such as this promotion and there are still many who do not know what are the completeness of promotions and do not know whether a Civil Servant (PNS) can be promoted. or not. This study aims to make Civil Servants (PNS) know whether it is proven or not to be able to be promoted based on certain conditions that must be met for promotion. The data processed in this study were directly directed by experts. The data is sourced from the staffing of the Regional Office of the Ministry of Religion of West Sumatra Province. The promotion data is processed and developed using an expert system built using PHP programming and MySQL database. In the Expert System in identifying the promotion of Civil Servants using the Backward Chaining method, the appropriate and suitable results are obtained between the expert data and the tracking results. 5 matches were obtained from the tracking results with 5 expert data whose percentage reached 100%, so whether or not a Civil Servant could be promoted to rank could be identified. It is hoped that the application that has been built in this research can be useful for Civil Servants (PNS) in identifying promotions, and to provide information about promotions.
Data Mining dalam Pengelompokan Penyakit Pasien dengan Metode K-Medoids Dwi Utari Iswavigra; Sarjon Defit; Gunadi Widi Nurcahyo
Jurnal Informasi dan Teknologi 2021, Vol. 3, No. 4
Publisher : Rektorat Universitas Putra Indonesia YPTK Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/jidt.v3i4.150

Abstract

Disease is a condition in which the mind and body experience a kind of disturbance, discomfort for those who experience it. Day by day, the number of patients at the Kuok Health Center is increasing with various types of different diseases. The increase number of patients requires the Kuok Health Center staff always update the patient's medical record data. The patient's medical record data is the form of a report containing the number of patients and their illnesses. Based on these data, the Puskesmas needs to find out information about the diseases that are most vulnerable and suffered by many patients. This study aims to classify patient disease data to find out the most common diseases suffered by patients at the Kuok Health Center, Kampar Regency. The grouping of patient disease data is carried out with the Data Mining Clustering and followed by the K-Medoids method. Next, cluster testing is carried out using the Silhouette Coefficient. The results of this study indicate that in cluster 1 the most common disease suffered by patients is non-insulin dependent diabetes mellitus (type II) with a total of 435 cases. In cluster 2, the most common disease suffered by patients was Essential Hypertension (Primary) with a total of 2785 cases. For cluster 3, the most common disease suffered by patients was Vulnus Laseratum, Punctum, with a total of 328 cases. From the cluster results obtained, the results of the Silhouette Coeficient test are 0.900033674.
Machine Learning Rekomendasi Produk dalam Penjualan Menggunakan Metode Item-Based Collaborative Filtering Daniel Theodorus; Sarjon Defit; Gunadi Widi Nurcahyo
Jurnal Informasi dan Teknologi 2021, Vol. 3, No. 4
Publisher : Rektorat Universitas Putra Indonesia YPTK Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/jidt.v3i4.151

Abstract

The shift towards Industry 4.0 has pushed many companies to adopt a digital system. With the sheer amount of data available today, companies start to face difficulties with providing product recommendation to their customers. As a result, data analysis has become increasingly important in the pursuit of providing the best service (user experience) to customers. The location appointed in this research is PT. Sentral Tukang Indonesia which is engaged in the sale of building materials and carpentry tools such as: paint, plywood, aluminum, ceramics, and hpl. Machine Learning has emerged as a possible solution in the field of data analysis. The recommendation system emerged as a solution in providing product recommendation based on interactions between customers in historical sales data. The purpose of this study is to assist companies in providing product recommendation to increase sales, to make it easier for customers to find the products they need, providing the best service (user experience) to customers. The data used is customer, item, and historical sales at PT. Sentral Tukang Indonesia over a time span of 1 period.data historical sales divide to dataset training 80% and dataset testing 20%. The Item-based Collaborative Filtering method used in this study uses Cosine Similarity algorithm to calculate the level of similarity between products. Score prediction uses Weighted Sum formula while computation of error rate uses the Root Mean Squared Error formula. The result of this study shows top 10 product recommendations per customer. The products displayed are products with the highest score from the individual customer. This research can be used as a reference by companies looking to provide product recommendations needed by their customers.
Identifikasi Tingkat Pemakaian Obat Menggunakan Metode Fuzzy C-Means Hidayati Rusnedy; Gunadi Widi Nurcahyo; S Sumijan
Jurnal Informasi dan Teknologi 2021, Vol. 3, No. 4
Publisher : Rektorat Universitas Putra Indonesia YPTK Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/jidt.v3i4.152

Abstract

Medicine is one of the irreplaceable components in health services that can help in treating sick people. Planning for drug needs is one of the important aspects in drug management, because it affects the procurement, distribution and use of drugs in health care units. Planning the right drug needs will make procurement effective and efficient so that it is in accordance with the needs of health services with guaranteed quality and can be obtained when needed. Puskesmas is one of the health services that is managed under the District and City Health Offices. However, in reality there are still obstacles in the process of drug procurement at the Puskesmas so that it has not yet achieved excellent service related to the availability of drug services. Clustering in Data Mining can be used to analyze the use of drugs, planning and controlling drugs at the Puskesmas. The method that will be used in this research is the Fuzzy C-Means algorithm, which is the most widely used and relatively successful unsupervised machine learning method among many fuzzy clustering algorithms. The purpose of this study was to categorize drug data which can be used as a reference in making decisions in planning and controlling medical supplies at the puskesmas. Based on 501 Pharmacy Monthly LPLPO data records in October 2020-February 2021, the results obtained in cluster one are 179 types of drugs which are included in the low level of use, cluster 2 there are 18 types of drugs that are included in the moderate level of use and cluster 3 as many as 4 types. drugs that are included in the high level of use.
Sistem Pakar Dalam Mengidentifikasi Penanda Minat Karakteristik Ekstrakurikuler Berbasis Case Based Reasoning Sisi Hendriani; Gunadi Widi Nurcahyo; Y Yuhandri
Jurnal Informasi dan Teknologi 2021, Vol. 3, No. 4
Publisher : Rektorat Universitas Putra Indonesia YPTK Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/jidt.v3i4.154

Abstract

Extracurricular is an additional activity at school whose purpose is to help develop students' talents, talent is defined as an innate ability which is a potential that needs to be developed and trained. Extracurricular selection is chosen by the students themselves without the intervention of teachers or parents so that students often only follow the majority of their friends' wishes. Knowing the extracurricular characteristics of students through the type of learning will make students' self-development more focused. This study uses the Case Based Reasoning method with similarity calculations which has 4 stages, namely retrieve (rediscover old similar cases), reuse (make old cases as solutions to new cases), revise (evaluate proposed solutions) and retain (store new cases). on a case basis) to determine the type of learning of students which will then be known to be suitable extracurricular activities due to the condition of the psychological development of children during the junior high school (SMP) level who tend to make the wrong choice or just participate in choosing something, especially in terms of selection. extracurricular at school. The learning styles are classified into six learning styles, namely Linguistic, Kinesthetic, Interpersonal, Musical, Naturalist and Logical Mathematics which are then adapted to the extracurricular fields at school. This study identifies the characteristics of student interest using student data at SMP Negeri 17 Padang, the results of similarity 66% for interpersonal learning style, 0% for kinesthetic learning style, 6% for musical learning style, 14% for natural learning style, 0% for logical mathematics learning style and 13% for linguistic learning style. The resulting expert system can help students quickly provide an appropriate extracurricular overview.
Sistem Keputusan dengan Metode Multi Attribute Utility Theory dalam Penilaian Kinerja Pegawai Fuad El Khair; Sarjon Defit; Y Yuhandri
Jurnal Informasi dan Teknologi 2021, Vol. 3, No. 4
Publisher : Rektorat Universitas Putra Indonesia YPTK Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/jidt.v3i4.155

Abstract

In an agency, it takes an employee who is able to carry out the work in accordance with the objectives in achieving a target becomes an assessment by the leaders. Not only attendance, but also leadership, commitment, cooperation, discipline, service orientation, integrity and ability to perform the task given also need to be used as an indicators . The purposes aim to motivate employees to be passionate in doing every activity and to have a positive influence on their work in facing challenges of globalization. Decision Support System is a need. It is called a Multi Attribute Utility Theory method is a quantitative comparison method that usually combines measurements of different risk costs and benefits. The data processed for employee performance assessment in this study as many as 20 samples sourced from the Population and Civil Registration Office of Pesisir Selatan Regency. This based on several specified criteria and weights. There are 6 data that are used in it. Such as service orientation, integrity, commitment, discipline, cooperation and employee performance goals. The result is able to support employee decisions using predetermined criteria. So that highest value is in the 6th alternative with a value of 1.8 and the lowest value on the 16th alternative with a value of 0. Later it will be a consideration for Population and Civil Registry Office of South Coast Regency to assess its employees in certain period. Employee performance assessment is proven to be able to help the South Coast Population and Civil Registration Office.
Sistem Penunjang Keputusan dalam Penentuan Calon Kepala Madrasah dengan Metode Weighted Product Ade Silvia; S Sumijan
Jurnal Informasi dan Teknologi 2021, Vol. 3, No. 4
Publisher : Rektorat Universitas Putra Indonesia YPTK Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/jidt.v3i4.156

Abstract

Madrasah is one of educational institutions integrated in the system of national education as outlined in UU Sisdiknas No. 2 Tahun 1989 and updated in the UU No. 2 Tahun 2003. The manager or the headmaster of madrasah plays the most significant role in the progress of madrasah, having a variety of functions such as managerial and supervisional ones with implication on its physical and non physical aspects. Therefore, it is very essential to choose a headmaster of certain madrasah out of the best possible candidate. In West Sumatera, election of headmaster through promotion and rotation lies upon the authortity of the provincial office of the Ministry of Religious Affairs, i.e. its Head of Office and selection committee. To this time, the basis for the election depends on simple observation, interviews and a kind of selection process for a number of teachers sent by the regency offices of the Ministry of Religious Affairs. This survey is conducted to rank all promoted candidates according to certain criteria outlined by the regulations by computerised information system. The method used in this survey is weighted product, one of the methods of the Decision Support System DSS. With this method in the system, all possible candidates will be ranked and the selection commitee will need less time and more accuration to pick the best ones. It is hoped that this product will be a contribution to be used by the provincial office of the Ministry of Religious Affairs in West Sumatra and can be adjusted to needs of the office.
Prediksi Potensi Relawan Pendonor Darah Menjadi Pendonor Darah Tetap dengan Penerapan Metode Klasifikasi Decision Tree Afifah Cahayani Adha; Y Yuhandri; Gunadi Widi Nurcahyo
Jurnal Informasi dan Teknologi 2021, Vol. 3, No. 4
Publisher : Rektorat Universitas Putra Indonesia YPTK Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/jidt.v3i4.158

Abstract

Blood donation is an important activity to obtain blood as a raw material into the blood supply chain. If there is not enough blood in the human body, then human survival will be threatened, for some conditions blood transfusions are required, such as accidents, childbirth or certain grades of dengue fever. UTD PMI Pekanbaru City is the organizing body for blood donation activities in the process of helping and serving the blood needs for public. Based on data from the Ministry of Health in 2019, Pekanbaru City lacked in blood stock 32.4 percent, which the ideal supply of blood bags in Pekanbaru City was 130,019 blood stock. This causes some hospitals difficult to find the supply of blood stock. The cause of lacking in blood bags' availability in Pekanbaru City was the number of volunteer donors fluctuates and the public's low interest in becoming volunteer blood donors. So it becomes a problem when the number of requests for blood increases, while the supply at the blood bank is running low. The method used in this research was the Decision Tree method. The algorithm used in this study was the C.45 Algorithm. To solve the problems that occur, data analysis of blood donor volunteers was carried out. Based on the results of the testing data analysis as many as 50 records, 6 rules were produced which can be concluded that age over 19 years with an entrepreneur job has the potential to become a permanent blood donor

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