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INDONESIA
Jurnal Informasi dan Teknologi
Published by Universitas Putra Indonesia YPTK Padang
ISSN : 27149730     EISSN : 27149730     DOI : https://doi.org/10.37034/jidt
Core Subject : Science,
Computer Science & IT
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.
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 378 Documents
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Akurasi Pemberian Insentif Menggunakan Algoritma K-Medoids Terhadap Tingkat Kedisiplinan Pegawai Wendi Robiansyah; Gunadi Widi Nurcahyo
Jurnal Informasi dan Teknologi 2021, Vol. 3, No. 3
Publisher : SEULANGA SYSTEM PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/jidt.v3i3.125

Abstract

Assessment of a discipline is a performance evaluation stage that is important for the continuity of company activities. Monitoring and assessment of an employee's discipline must be carried out continuously in order to improve the quality of human resources. This research was conducted to make the accuracy of providing incentives based on the level of employee discipline. The data processed in this study is a recapitulation of the attendance of AMIK and STIKOM Tunas Bangsa Pematangsiantar employees as many as 25 employees as a sample. For grouping the employee data using the K-Medoids Algorithm. K-Medoids groups a set of n objects into a number of k clusters using the partition clustering method. Furthermore, the employee data is processed using Rapid Miner software. Research using this method obtained results in the form of grouping employees into 3 groups that have good discipline levels of 12 employees, sufficient discipline levels of 8 employees, and less disciplinary levels of 5 employees. Based on the grouping results that have been produced, it can be a consideration for the leadership to determine the amount of incentives for employees.
Pemilihan Kualitas Gambir dengan Multi-Objective Optimization on The Basis of Ratio Analysis (MOORA) Muhammad Iqbal; Sumijan
Jurnal Informasi dan Teknologi 2021, Vol. 3, No. 3
Publisher : SEULANGA SYSTEM PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/jidt.v3i3.126

Abstract

Gambier (gambir plantae) is an half of perdu plantation which in separated in several regions of Indonesia. It is especially live in Sumatra, Java, Maluku, and Burneo. In West Sumatra province, gambir is used to component for menyirih (betle) and also the farmer of gambir asproduction as. It is reserving from hot water. Extraction come from the leaves and twigs of gambir in depositor forms, then printed and then turned into dried forms. The gambir farmers usually sell their productions to the collectors with a certaibty prices. Gambir has many qualities based from it processing, catechin contains, colors, ash contains, water contains, and also its density. Some its barries often occurs from the gambir processing being into product, which a minusly quality suffers, that cause gambir price in decrease or not to expensive conditions in the market by using support decision by Multi-Objective Optimization by Ratio Analysis (MOORA) methode is a multi objektives system from which can be optimated some atributes whom contradicting each other in simultaneously, either lost profit (cost) or getting profit (benefit), the system using these methode used to choose some gambir qualified form for determine its price. These data of sample taken form Pesisir Selatan gambir, which the research result farmed that gambier ranked can be as support as some decisions to make the best gambir as price decision as. Form theseresearch could be conclude that the best gambir have an higher catechin contains, low water contains, a slightly ash contains, with a yellowish skin, and have as highest as density. Based on the data of sample of research, the best gambier in qualified in getting from Siam and pian with the grade in 0.163 with the good one criteria condition. From gambier standardization, all of gambier which have upper grade standars, qualified into good gambier quality, gambier with high quality or good can give an expensive price that encourages some gambir farmers in motivation to process gambir product being increase gambier quality that can be improve the price selling gambir as well as the purchase of gambier products.
Prioritas Pengadaan Buku Berdasarkan Data Kerusakan dan Kehilangan Menggunakan Metode Simple Additive Weighting Syahid Hakam Abdul Halim; Yuhandri Yunus; Sumijan
Jurnal Informasi dan Teknologi 2021, Vol. 3, No. 3
Publisher : SEULANGA SYSTEM PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/jidt.v3i3.128

Abstract

Supplying book which is estimated each year can fulfill the availability and requirement of books. With supplying book that has been done, it can increase the students reading interest in teaching and learning process. The frequency of using book in learning cause the book will be damaged or lost. The aim of this research is to find out the priority of supplying book based on damaged and lost data so that it can be used as a reference to determine the main priority in supplying book. If this priority can be determined, it will give the effect towards madrasah as well for librarian. The effect for madrasah is to give information about priority supplying book at school’s library. For librarian, the effect could be concluded as consideration in making decision to supplying the book at school’s library. To analyze the research, the researcher used 40 broken and lost data. Which is the broken data was obtained from the librarian of MAN 2 Kota Padang Panjang. In this research, the researcher used the Simple Additive Weighting with PHP programming and MySql database. The main concept of Simple Additive Weighting method is to find out the total rating performance for each alternative. The experiment of broken and lost data is done based on the alternative book which is normalized by attribute criteria (benefit or cost). The broken and lost data criteria was consisted of 4 criteria, they are 1 book’s stock criteria, 2. Book’s sheets criteria, 3. Book’s cover criteria, and 4. Book’s code criteria. The result ranking towards Simple Additive Weighting method based on 40 experiment data was found that 3 alternative books was obtained as priority in supplying book, they are Akidah Akhlak XI, Al Quran Hadist XI, and Ushul Fikih XI, which the Akidah Akhlak XI is the main priority.
Klasterisasi Penempatan Siswa yang Optimal untuk Meningkatkan Nilai Rata-Rata Kelas Menggunakan K-Means Yusma Elda; Sarjon Defit; Yuhandri Yunus; Raemon Syaljumairi
Jurnal Informasi dan Teknologi 2021, Vol. 3, No. 3
Publisher : SEULANGA SYSTEM PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/jidt.v3i3.130

Abstract

The implementation of learning by teachers can measure the quality of schools and students. Schools with diverse student backgrounds need to take strategic steps in managing learning to get optimal learning outcomes. Good learning designs and techniques can motivate students' interest in learning. The teacher's role is very important in managing learning to create an effective teaching and learning process. Data Mining or also known as Knowledge Discovery in Database (KDD) is the process of extracting knowledge from large data to find new patterns to get new knowledge and information. Data Mining technology is used to explore existing knowledge in the database. One of the methods used in data mining is clustering with the K-Means algorithm. This study aims to conduct student clustering to obtain a balanced class composition in order to improve the quality and student learning outcomes as seen in the increasing in the class average score. The data processed in this study came from the main school data as many as 90 students of the XI class of Computer Network Engineering Skills Competency at SMKN Negeri 2 Padang Panjang in the 2020/2021 school year. The variables used in data processing are student scores, parents' income and the distance from where students live to school. The student clustering calculation using K-Means succeeded in grouping 90 students into 3 clusters where cluster 1 totaled 47 students, cluster 2 totaled 10 students and cluster 3 totaled 33 students. Each member of the cluster will be divided evenly into 3 groups studying to get a balanced class composition. This research can be used as a basis for decision making by schools in clustering student placements to improve learning outcomes. By the increasing in the grade point average, the school average score will also increased.
Optimalisasi Pelayanan Perpustakaan terhadap Minat Baca Menggunakan Metode K-Means Clustering Dwiki Aulia Fakhri; Sarjon Defit; Sumijan
Jurnal Informasi dan Teknologi 2021, Vol. 3, No. 3
Publisher : SEULANGA SYSTEM PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/jidt.v3i3.137

Abstract

Knowledge Discovery in Database (KDD) is a structured analysis process aimed at getting new and correct information, finding patterns from complex data, and being useful. Data mining is at the core of the KDD process. Clustering is a data mining method that is suitable for optimizing library services because it can cluster books effectively and efficiently, with the K-Means algorithm data can be clustered and information from each centroid value of each cluster. Library services can optimize the placement of books so that students can quickly find books according to their reading interest more effectively and can be attracted to other books because they are in one grouping. Meanwhile, the library can prioritize the procurement of the next book. Optimization of library services in the cluster using the K-Means method. Clustering interest in reading has the criteria for the number of books available, borrowed books, and the length of time the books are borrowed. The book data is clustered into 3, namely very interested, in demand, and less desirable. After doing the calculation process from 40 samples of book types, it resulted in 6 iterations, and the final results were 3 clustering, namely cluster 1 of 4 books that were of great interest, cluster 2 of 20 books that were of interest, and cluster 3 of 16 books that were less desirable. This research can be used as a recommendation reference for optimizing library services both for the layout and procurement of books by prioritizing the types of books that are of great interest.
Simulasi Monte Carlo dalam Memprediksi Penerimaan Peserta Pelatihan Dasar CPNS Faisal Roza; Sarjon Defit; Gunadi Widi Nurcahyo
Jurnal Informasi dan Teknologi 2021, Vol. 3, No. 3
Publisher : SEULANGA SYSTEM PUBLISHER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/jidt.v3i3.140

Abstract

The implementation of basic training recruit (latsar) of civil servant (CPNS) at Pusat Pengembangan Sumber Daya Manusia (PPSDM) Ministry of Internal Affairs regional Bukittinggi. The leader takes decision in doing the implementation of latsar CPNS recruit in PPSDM scope regional Bukittinggi. Latsar CPNS is one of requirements to be civil servant. Therefore, it is necessary to collect data by doing observation, interview questionings with related party in the implementation of latsar CPNS recruit from 2018 to 2020. It can be predicted for the next recruit. After doing library references by reading some books and journals, the basic training recruit of CPNS sources from PPSDM regional Bukittinggi, and Monte Carlo simulation. By using Monte Carlo simulation in predicting data, it can get closer value of actual value. Based on distribution of sampling data, the method is by choosing random numbers from probability distribution to do simulation. The Monte Carlo result’s examination has got 173 participants for year 2019, 158 participants for year 2020, and 157 participants for year 2021 clearly. Although the rate of the accurate just reaches 81%, but it has been able to be recommended to help PPSDM regional Bukittinggi, Ministry of Internal Affairs in taking decision and planning for basic training recruit of CPNS for the next.
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 : SEULANGA SYSTEM PUBLISHER

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 : SEULANGA SYSTEM PUBLISHER

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 : SEULANGA SYSTEM PUBLISHER

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 : SEULANGA SYSTEM PUBLISHER

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.

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