Articles
The Multi Attribute Utility Theory (Death) Method In The Decision Of The Distributor Distributor Selection (Metode Multi Attribute Utility Theory (Maut) Dalam Keputusan Pemilihan Distributor Barang)
Ritna Wahyuni;
Sarjon Defit;
Gunadi Widi Nurcahyo
Jurnal KomtekInfo Vol. 7 No. 2 (2020): Komtekinfo
Publisher : Universitas Putra Indonesia YPTK Padang
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DOI: 10.35134/komtekinfo.v7i2.69
Distributors are intermediaries who distribute products from factories to retailers. While the distributor of goods is the distributor of goods from factories to shops that need these goods. Incorrect selection of distributors can interfere with the sales process at the store. To improve the quality and quality of a store, it requires the best distributor of goods. This study aims to determine the best distributor of goods. The method used is the Multi Attribute Utility Theory (MAUT) of distributor data at the Padang Luar Sundanese Convenience Store. The data processed in this study consisted of a number of distributor data selected by the Multipurpose Store. From some of the distributor data, the Decision Support System is very necessary in the selection of distributors who aim for the selection of appropriate alternative decisions. The selection of distributors uses 15 samples of distributor data and 5 criteria data that are used as the basis for selecting distributors, namely quality of goods, affordable prices, strategic locations, service responses, and giving bonuses. The results of testing on this method obtained an accuracy rate of 86.67% of the right distributors and in accordance with the realization of the UI data. So this research is very suitable in choosing the best distributor. From the test results, it has got the 5 best distributors by assigning a weight of 11.50 to the best distributor, so the criteria set by the All-Round Shop can be used as a reference in the selection of distributors of goods.
Optimalisasi Pendapatan Integrasi Sawit dengan Sapi Menggunakan Metode Monte Carlo
Hermanto;
Sarjon Defit;
Yuhandri
Jurnal KomtekInfo Vol. 8 No. 4 (2021): Komtekinfo
Publisher : Universitas Putra Indonesia YPTK Padang
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DOI: 10.35134/komtekinfo.v8i4.183
Hidup manusia sangat dipengaruhi oleh perkembangan lmu pengetahuan dan teknologi inforrmasi dalam penunjang kehidupan, salah satu nya dalam sektor pertanian. Teknologi informasi dalam sektor pertanian yang tepat waktu dan relevan memberikan informasi yang tepat guna kepada rumah tangga usaha pertanian untuk pengambilan keputusan dalam berusaha tani, sehingga efektif dalam meningkatkan produktivitas,dan pendapatan. Di Kabupaten Sijunjung petani yang merapkan sistem integrasi kelapa sawit dengan sapi hanya beberapa petani yang menerapkan hal itu, di karenakan keterbatasan informasi dan menyebabkan pendapatan dari petani yang menerapkan metode ini tidak menentu. Maka dari itu teknologi di harapkan dapat membantu mengatasi permasalahan tersebut. Metode yang di gunakan dalam penelitian ini adalah metode Monte Carlo dengan mengunakan data pendapatan petani kelapa sawit yang mengunakan metode integrasi kelapa sawit dengan sapi yang berada di kabupaten sijunjung tepatnya di kecamatan Kamang Baru, data di peroleh dengan cara wawancara secara langsung kepada petani di mana mempunyai lahan 1,5 hektar kebun kelapa sawit dengan 8 ekor sapi, dan di peroleh lah data pendapatan petani dari tahun 2018, 2019 dan 2020 dimulai dari bulan januari sampai bulan desember. Variabel yang digunakan dalam penelitian ini adalah jumlah pendapatan petani perbulannya. Data jumlah pendapatan petani tersebut akan di olah menggunakan metode Monte Carlo dibantu dengan Microsoft Excel untuk pencarian manualnya. Data jumlah pendapatan petani tahun 2018 digunakan sebagai data uji coba untuk memprediksi jumlah pendapatan petani pada tahun 2019, data tahun 2019 di gunakan untuk memprediksi jumlah pendapatan petani tahun 2020, dan data tahun 2020 untuk memprediksi pendapatan tahun 2021
Algoritma K-Means Untuk Klasterisasi Tugas Akhir Mahasiswa Berdasarkan Keahlian
Weri Sirait;
Sarjon Defit;
Gunadi Widi Nurcahyo
Jurnal Sistim Informasi dan Teknologi 2019, Vol. 1, No. 3
Publisher : Rektorat Universitas Putra Indonesia YPTK Padang
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DOI: 10.37034/jsisfotek.v1i3.5
School of Information and Computer Management (STMIK) Indonesia Padang is a private university under the auspices of the Higher Education Service Institution (LLDIKTI) Region X, producing graduates who are competent in the field of system analysts and database administrators. Requirements to meet undergraduate graduates (S1) final year students need to complete a final project or thesis. Final year students at STMIK Indonesia Padang often experience confusion in taking the final assignment topic. This is due to the fact that the final year students have not been able to direct their potential in determining the final assignment topic. In this case, researchers conducted the process of grouping final level students using the Data Mining K-means Clustering technique. The process of grouping final-level students is done by utilizing the data of course values from the field mapping system analysts and database administrators. In this grouping two clusters will be produced, namely students taking the final assignment of system analysts and database administrator. So by using this K-means Clustering method, students have direction in taking the final assignment topic. The results obtained from 40 data samples used were students who took the topic of the final project system analysts as many as 20 students and students who took the final assignment of database administrators were 20 students.
Implementasi Algoritma K-Means untuk Klasterisasi Peserta Olimpiade Sains Nasional Tingkat SMA
Miftahul Hasanah;
Sarjon Defit;
Gunadi Widi Nurcahyo
Jurnal Sistim Informasi dan Teknologi 2019, Vol. 1, No. 3
Publisher : Rektorat Universitas Putra Indonesia YPTK Padang
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DOI: 10.37034/jsisfotek.v1i3.6
The abundance of students causes student data in the system to also be abundant. Schools often find it difficult to manage large amounts of data manually, especially in selecting National Science Olympiad participants and decisions made are less effective. So this research was conducted with the aim of helping the school in selecting OSN participants appropriately and effectively. The method used is Clustering with K-Means algorithm on the report card grades of students majoring in Natural Sciences at SMA Negeri 5 Sijunjung. The results in this study get 3 clusters of students on the selection of OSN participants, namely students who are Very Competent, Competent and Less Competent. This research can be used as a benchmark used by schools in making decisions on the selection of OSN participants.
Penentuan Tingkat Kerusakan Peralatan Labor Komputer Menggunakan Data Mining Rough Set
Riyan Ikhbal Salam;
Sarjon Defit
Jurnal Sistim Informasi dan Teknologi 2019, Vol. 1, No. 4
Publisher : Rektorat Universitas Putra Indonesia YPTK Padang
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DOI: 10.37034/jsisfotek.v1i4.7
Equitments of computer laboratory have a function as an important tools in supporting pratical lecturing. These facilities should always be on a condition like ready are proper to use both computers and others. To avoid equipment detriment, it is necessary to do early identification in which prevent the worse condition of equitments. The method use in this study is rough set method wich consists several stages such as Decision System, Equivalence Class, Discernibility Matrix, Discernibility Matrix Modulo D, Reduction, and Generate Rules. From this study, it was found that 14 rules in making decisions for equipments treatment of computer laboratory such as use, repair and replace. Thus, this mrthod is very capable in determining the detriment level of laboratory equipment.
Penerapan Artificial Intelligent Rough Set dalam Pengawasan Kinerja Notaris
Adek Putri;
Sarjon Defit;
S Sumijan
Jurnal Sistim Informasi dan Teknologi 2019, Vol. 1, No. 4
Publisher : Rektorat Universitas Putra Indonesia YPTK Padang
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DOI: 10.37034/jsisfotek.v1i4.8
The Regional Supervisory Council (MPD) has the authority to conduct periodic checks on notaries. In carrying out supervision there is no clear legal or regulatory basis on how the notary performance assessment is categorized as very good, good or bad so there is no common perception from MPD members. The purpose of this study is to help MPD find the assessment category in monitoring the performance of the notary public in West Sumatra. To get the assessment category, the Rough Set method can be used to analyze the performance of a notary public. The data used in this study is the data notary examination at the Regional Office of the Ministry of Law and Human Rights in West Sumatra. This study produced 18 rules to get a decision whether the results of the notary performance check are very good, good or not good. So this research is very appropriate to be applied to get the results of the examination of notary performance.
Data Mining Menggunakan Rough Set dalam Menganalisa Modal Upah Produksi pada Industri Seragam Sekolah
Rahman Arief Putra;
Sarjon Defit
Jurnal Sistim Informasi dan Teknologi 2019, Vol. 1, No. 4
Publisher : Rektorat Universitas Putra Indonesia YPTK Padang
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DOI: 10.37034/jsisfotek.v1i4.12
In a fund industry is a very important factor, mismanagement or unavailability of funds can have a negative impact on the industry, the successful shop still uses internal capital that is capital from the sale of the store itself, the sales results are not always sufficient to pay the production wage money cause late payments which adversely affect the performance of workers and the industry itself, production wage data on successful stores can be utilized by using the rough set method to find solutions to predict future production wages, The results found 57 rules of 8 reducts from 11 Equivalence Classes that provide new information that is the cause factor of not achieving capital production wages, the main factor is income followed by sewing wages, cut wages.
Sistem Pakar dalam Mengidentifikasi Penyakit Kandungan Menggunakan Metode Forward Chaining Berbasis Android
Adi Gunawan;
Sarjon Defit;
S Sumijan
Jurnal Sistim Informasi dan Teknologi 2020, Vol. 2, No. 1
Publisher : Rektorat Universitas Putra Indonesia YPTK Padang
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DOI: 10.37034/jsisfotek.v2i1.16
Maternal Mortality Rate (MMR) in Indonesia is very high, so that maternal health problems are a national problem. This problem needs to get top priority. The health of pregnant women is crucial for the growth of the fetus they contain. Pregnancy can cause a decrease in maternal resistance. This decrease will trigger the arrival of various diseases. For that we need a system that can identify uterine diseases quickly and accurately. This study aims to identify uterine diseases in pregnant women based on symptoms experienced. This identification is the initial information that is useful to support the decision to take preventative action. Data processed in this study were 20 patients. This data is sourced from the Sungai Melati City Clinic which goes to an obstetrician, Dr. Yandi Zulkarnaen, SpOG. The method used in processing data is Android-based Forward Chaining. The results of this study include the name of the disease, description of the disease, and treatment solutions. After testing and calculating the level of system accuracy, a good degree of accuracy is obtained from the system calculation results with an expert decision of 90% of the 20 test data. Based on the level of accuracy, the expert system is very precise in identifying uterine diseases quickly.
Klasterisasi Tingkat Kehadiran Dosen Menggunakan Algoritma K-Means Clustering
Ismail Virgo;
Sarjon Defit;
Y Yuhandri
Jurnal Sistim Informasi dan Teknologi 2020, Vol. 2, No. 1
Publisher : Rektorat Universitas Putra Indonesia YPTK Padang
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DOI: 10.37034/jsisfotek.v2i1.17
Non-Civil Servant Lecturers of Batusangkar State Islamic Institute (IAIN) are still manual in recording the presence of non-civil servant lecturers. This study aims to use an application to record the number of meetings conducted during the teaching and learning process by non civil servant lecturers who are able to study courses. The meeting data will be an assessment of the performance of non civil servant lecturers. Higher education quality assurance institutions can classify non-civil servant lecturer meeting data using Knowledge Discovery in Database (KDD). The next stage is to do data mining with the K-Means Clustering Algorithm. The results of this study grouping lecturers into 3 groups: 72 subjects taught by non-civil servant lecturers in the group rarely meet (4,7650%), 69 courses that are taught by non-civil servant lecturers in the group are in meetings (4,5665%), and 1370 subjects taught by lecturers non civil servants in the diligent group meeting (90.6684%). Based on the results of the study it was concluded that the academic year 2017/2018 odd semester and even non-civil servant lecturers supporting certain subjects diligently entered at each meeting with attendance rates of 12-16 times meetings per semester
Analisis Tingkat Kejahatan pada Anak Dibawah Umur Menggunakan Metode FP-Growth
Angga Putra Juledi;
Sarjon Defit;
Y Yuhandri
Jurnal Sistim Informasi dan Teknologi 2020, Vol. 2, No. 1
Publisher : Rektorat Universitas Putra Indonesia YPTK Padang
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DOI: 10.37034/jsisfotek.v2i1.18
Crimes in minors are a series of negligence by parents who endanger or pose a dangerous threat to the child. The purpose of this study is to implement Data Mining, Association rule, and the FP-Growth Algorithm in cases of juvenile crime so that it can extract knowledge and important and interesting information from the database. The data source used is raw data that has not been processed and is a crime data on minors which are summarized in the form of reports from the West Sumatra Regional Police. The results of this study are in the form of software by analyzing data collected using the FP-Growth Algorithm and using the concept of FP-Tree development in searching for Frequent Itemset, for testing the results carried out with applications that have been designed namely the Php programming language. The results of testing are obtained from associations of crime cases that often occur in minors. So it can be seen that data mining using the FP-Growth Algorithm can be used to analyze cases of crime in minors as a material consideration for the police in order to know the ins and outs of crime in children so that it can assist the investigation process.