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Contact Name
Verdi Yasin
Contact Email
editor.matech@gmail.com
Phone
+6281210617515
Journal Mail Official
info@binainternusa.org
Editorial Address
Jalan Raya Kebagusan Utara No. 063 RT.22, RW.04, Kecamatan Ampelgading, Pemalang, 52364 Jawa Tengah, Indonesia
Location
Kab. pemalang,
Jawa tengah
INDONESIA
Journal of Mathematics and Technology (MATECH)
ISSN : -     EISSN : 28293940     DOI : -
Journal of Mathematics and Technology (MATECH) Merupakan Media Publikasi Ilmiah untuk Para Akademisi dan Peneliti, yang berasal dari hasil Pemikiran dan Penelitian sesuai Cakupan dan Fokus yang ada dalam Manajemen Informasi Jurnal ini. Pengelola/Penyunting mengingatkan kepada semua calon penulis bahwa kami hanya menerima pengiriman kertas/Naskah Jurnal yang berasal dari Penelitian asli (Original) dari penulis, tidak berasal dari Plagiasi hasil penelitian dari peneliti orang lain. Scope : Matematika dan Logika, Matematika Terapan ,Teknik, Teknik Komputer & Teknik Elektro, Teknologi Informasi dan Komunikasi, Informatika, Ilmu komputer & Sistem Informasi, Kecerdasan Buatan dan Sains Data, Teknologi Pendidikan & Pendidikan Matematika. Focus : Ilmu Matematika, Logika Matematika, Logika Fuzzy, Statistik, Riset Operasional, Matematika Ekonomi, Matematika Pendidikan, Matematika Pendidikan, Matematika Komputasi, Matematika Murni, Matematika Terapan, Riset Operasional, Teknik, Teknik Terapan, Teknologi Terbarukan, Robotika , Internet of Things (IoT), Teknik Komputer, Sistem Komputer, Informatika, Teknik Perangkat Lunak, Teknologi Informasi, Ilmu Komputer, Sistem Informasi, Teknologi Terapan, Teknologi Multimedia, Teknologi Komunikasi & Internet. Kecerdasan Buatan, Jaringan Saraf Tiruan, Data Mining, Sistem cerdas, Data Warehouse, Big Data, Sains Data. Teknologi Pendidikan, Mesin Pembelajaran dan Pendidikan Matematika
Articles 19 Documents
Search results for , issue "Vol. 2 No. 2 (2023): Journal MATECH (November 2023)" : 19 Documents clear
DATA MINING GROUPING THE FEASIBILITY OF APPLYING FOR CREDIT TO CUSTOMERS USING THE K-MEANS ALGORITHM METHOD ON CV. MOTORBIKE CHOICE Natalia Sianturi, Ruth; Sihombing, Marto; Sihombing, Anton
Journal of Mathematics and Technology (MATECH) Vol. 2 No. 2 (2023): Journal MATECH (November 2023)
Publisher : Yayasan Bina Internusa Mabarindo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63893/matech.v2i2.145

Abstract

In the midst of the current era of technological development, many changes have occurred in the field of transportation. Transportation is an important aspect of human life because transportation contributes to daily human life and activities. With the existence of transportation, people can easily reach somewhere far or near. Motorcycles are a means of transportation that is quite popular in the community. CV. Choice of Motors is an individual company engaged in the provision of new or used motorcycle loans. Motorcycle credit is a loan facility that aims to finance the purchase of a motorbike where the source of credit payment comes from income. Customers who apply for credit both individually and as an institution with a maximum financing of up to a certain amount along with the BPKB guarantee for the motorbike purchased. In setting credit policies, companies must first formulate credit standards and credit terms, the data needed as credit requirements include: KTP, income, employment, family cards, and other administrative requirements. Then a field survey will be carried out and then the results of the survey are analysis, after which the results of the analysis are returned to the company. Based on the results of the study, there were 4 groups of 20 data, namely group 1 with 5 data, group 2 with 8 data, and group 3 with 7 data.
CLASSIFICATION OF HOUSEHOLD VIOLENCE (KDRT) CASES BASED ON CAUSING FACTORS USING CLUSTERING METHOD Aprilianda, Dinda; Saragih, Rusmin; Saripurna, Darjat
Journal of Mathematics and Technology (MATECH) Vol. 2 No. 2 (2023): Journal MATECH (November 2023)
Publisher : Yayasan Bina Internusa Mabarindo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63893/matech.v2i2.146

Abstract

Domestic violence is a violation of human rights and a crime against human dignity and is a form of discrimination. Therefore, no matter how small the violence committed can be reported as a criminal act that can be processed by law. The Office of Women's Empowerment, Child Protection, Population Control and Family Planning has the task of solving problems that often occur in cases of domestic violence (KDRT) against someone, especially women, which results in physical, sexual, psychological, and/or misery or suffering. household neglect including threats to commit acts, coercion, or unlawful deprivation of liberty within the household sphere. therefore it is necessary to have an application that can process this data based on age, type of violence and causal factors to be used as information specifically about cases of domestic violence so that it is easier for the community to understand later. This was created to overcome the problem of extracting important information from a data set of domestic violence cases based on the causative factors at the agency using the k-means clustering method which will be built later. From the results of research conducted using a sample of 20 data, it can be concluded that the most common data are in cluster 2 with data on cases of domestic violence (KDRT) based on many causal factors with a total of 7 data and located in the age group (X ) is aged 17-25 years, and for the type of violence group (Y) that is carried out is Abuse and the causal factors (Z) which mostly occur due to External Factors / Divorce.
APPLICATION OF THE CLUSTERING METHOD FOR GROUPING DATA BASED ON FAMILY SOCIO-ECONOMIC STATUS Hidayati, Erika
Journal of Mathematics and Technology (MATECH) Vol. 2 No. 2 (2023): Journal MATECH (November 2023)
Publisher : Yayasan Bina Internusa Mabarindo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63893/matech.v2i2.148

Abstract

Socio-economic is a position that is regulated socially and places a person in a certain position in society. Socio-economic conditions of the community can be seen through the aspects of education, employment and income. The socio-economic condition of the community can be said to be good if their daily needs have been met, be it the need for clothing, food or shelter, conversely if one of these needs is not fulfilled then it can be said that the socio-economic condition is bad. Writing this proposal uses the clustering method which is one of the data mining techniques for grouping basic family data using the k-means algorithm clustering method. By applying 20 alternative data samples of student data and providing a total of 3 clusters, and utilizing 3 main criteria as research in this proposal, the resulting number of cluster 1 is 11 data, cluster 2 is 7 data. And cluster 3 as much as 3 data. This Family Basic Data grouping system is designed with the MATLAB application programming language and utilizes the GUI as its interface.
GROUPING COMMUNITY BUSINESS DATA BASED ON THE TYPE OF BUSINESS USING THE CLUSTERING METHOD AT THE TANJUNG MERAHE VILLAGE OFFICE Lestari, Dian
Journal of Mathematics and Technology (MATECH) Vol. 2 No. 2 (2023): Journal MATECH (November 2023)
Publisher : Yayasan Bina Internusa Mabarindo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63893/matech.v2i2.149

Abstract

Grouping is an alternative that can be used to explore information so that it becomes new knowledge for everyone who wants to get it. and in this case the information to be explored is about community businesses in Tanjung Merahe Village, Finish District. This excavation was made to obtain information about the types of businesses that exist in Tanjung Merahe Village based on the age of the business in order to make it easier for the government to find out the type of business and its business income which can be further developed so that it becomes a superior product in Tanjung Merahe Village and can facilitate the Village Government in making decisions if there is assistance from the central government based on the type of business owned by the community. Writing this proposal uses the clustering method which is one of the data mining techniques for grouping community business data using the k-means algorithm clustering method. By applying 20 alternative data samples of student data and providing a total of 3 clusters, and utilizing 3 main criteria as research in this proposal, the resulting number of cluster 1 is 6 data, cluster 2 is 8 data. And cluster 3 as much as 6 data. This community business data grouping system is designed with the MATLAB application programming language and utilizes the GUI as its interface.
DATA MINING GROUPING LOCATIONS OF DRUG USERS BASED ON THEIR ADDICTION LEVEL Oni, Riyen
Journal of Mathematics and Technology (MATECH) Vol. 2 No. 2 (2023): Journal MATECH (November 2023)
Publisher : Yayasan Bina Internusa Mabarindo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63893/matech.v2i2.151

Abstract

The problem that has now been declared a national disaster is the inappropriate and excessive use of drugs. Where this problem is a negative deviation that can be detrimental to the user, society, the State, and all aspects of life. The unfortunate thing is that these drug users are actually people who know the dangers of using these drugs, but for the sake of their lifestyle they are willing to bear all the consequences of using these drugs. By applying 20 alternative data samples of student data and providing a total of 3 clusters, and utilizing 3 main criteria as research in this proposal, the resulting number of cluster 1 is 8 data, cluster 2 is 10 data. And cluster 3 as much as 2 data. This Drug User Data grouping system is designed with the MATLAB application programming language and utilizes the GUI as its interface.
SISTEM PENDUKUNG KEPUTUSAN PENANGANAN PENYAKIT DENGUE HEMORRHAGIC FEVER (DBD) DENGAN MOTEDE SAW Sijabat, Maruba; Hara Pardede, Akim Manaor; Prahmana, I Gusti
Journal of Mathematics and Technology (MATECH) Vol. 2 No. 2 (2023): Journal MATECH (November 2023)
Publisher : Yayasan Bina Internusa Mabarindo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63893/matech.v2i2.152

Abstract

Dengue hemorrhagic Fever/Dengue Hemorrhagic Fever is an acute febrile disease that can cause death and is caused by four serotypes of viruses of the genus Flavivirus, RNA viruses of the Flaviviridae family. Dengue is transmitted to humans mainly by the Aedes aegypti mosquito and the Aedes albopictus mosquito, and is also transmitted by Aedes polynesiensis and several other mosquito species that actively suck blood during the day. After the infective blood is inhaled by the mosquito, the virus enters the mosquito's salivary glands and multiplies to become infective within 8-10 days, which is called the extrinsic incubation period. Dengue cases (dengue hemorrhagic fever) continue to increase every year, according to the World Health Organization (WHO) as much as 3.21% in 2020 of the total world population. In Indonesia, cases reached 16,320, in June 2021, which is still a high number. The number of cases in April was 6,417 cases, this prevalence increased when compared to cases in May 2021 which were 9,903 cases. Due to DHF (Dengue hemorrhagic fever) which increased causing the death rate in May of 98 cases, an increase in June was recorded 147 cases. Therefore, it is necessary to take decisions that can be used to support and assist management in making semi-structured and unstructured decisions. To determine the treatment mitgasi action on dengue hemorrhagic fever quickly and reduce the high risk of contracting dengue fever. Problems in dengue hemorrhagic fever can be solved by using the saw method to determine the handling action quickly. From the tests conducted obtained values ranging from the lowest value to the lowest in the case of dengue hemorrhagic fever (DHF), so based on the acquisition of the highest value of 0.7525 (75.25%) in Alternative 1.
PENGELOMPOKKAN MENGGUNAKAN METODE CLUSTERING UNTUK PEMBERIAN OBAT PADA PASIEN BPJS Ariska, Dedek; Simanjuntak, Magdalena; Lubis, Imran
Journal of Mathematics and Technology (MATECH) Vol. 2 No. 2 (2023): Journal MATECH (November 2023)
Publisher : Yayasan Bina Internusa Mabarindo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63893/matech.v2i2.153

Abstract

BPJS Kesehatan merupakan badan hukum yang menyelenggarakan program jaminan Kesehatan yang dibentuk untuk menyelenggarakan jaminan sosial dinamakan Badan Penyelenggara Jaminan Sosial (BPJS). Pada saat ini Pemberian resep obat di rumah sakit juga dilakukan oleh dokter sesuai dengan standar yang sudah ditetapkan oleh rumah sakit berdasarkan penyakit yang diderita oleh pasien yang menggunakan jasa dari jaminan pelayanan kesehatan. Karena banyaknya pasien yang menggunakan jasa BPJS menyebabkan menumpuknya data-data pemberian obat pada pasien, sehingga menyulitkan pihak instansi dalam mengolah data pemberian obat pada pasien, masalah ini sering terjadi karena data yang tersimpan masih tercatat secara terpisah antara laporan pemberian obat dan laporan data pasien BPJS sehingga sangat sulit dalam mengetahui jumlah pemberian obat yang ada saat ini. Untuk itu diperlukan suatu sistem tambahan yang akan digunakan dalam pengelompokkan pemberian obat pada pasien BPJS menggunakan variabel - variabel yang sudah ditentukan dengan menggunakan metode clustering, agar nantinya dapat mempermudah admin dalam mengolah data dan informasi yang ada. Dari 20 data yang digunakan sebagai sampel didapatlah hasil yang dibagi menjadi 3 yaitu grup 1 terdapat 12 data dan 2 grup terdapat 3 data dan grup 3 terdapat 5 data. Dengan penjelasan dengan titik Centroid pada grup 1 yaitu (3.50) (16.58) (13.17) dapat diketahui bahwasannya pada cluster 1 kelompok pemberian obat pada grup usia (X) adalah 36-45 Tahun, dan untuk kelompok jenis penyakit (Y) yang dialami oleh pasien adalah Hipertensi dengan penanganan pemberian Resep obat (Z) yaitu Clonidin 0,15 tab.
IDENTIFICATION OF BANANA FRUIT USING BACKPROPAGATION METHOD Widodo, Dian; Fauzi, Achmad; Sembiring, Arnes
Journal of Mathematics and Technology (MATECH) Vol. 2 No. 2 (2023): Journal MATECH (November 2023)
Publisher : Yayasan Bina Internusa Mabarindo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63893/matech.v2i2.155

Abstract

Identifikasi jenis buah pisang dan penilaian tingkat kematangannya merupakan proses yang penting dalam industri pertanian dan distribusi. Dalam upaya untuk mengotomatisasi proses ini, penulis menyarankan pendekatan pemaparan buah pisang dan tingkat kematangannya menggunakan jaringan saraf tiruan Backpropagation . Melalui proses pengolahan citra digital, citra atau gambar dari buah pisang akan dilakukan ekstraksi ciri-ciri seperti RGB ( red green blue ), metrik dan eksentrisitas(ciri bentuk). Hasil proses training data citra sebanyak 55 data citra yang diinputkan, diperoleh proses training data jenis pisang dengan 11 iterasi dari inputan maksimum epoch 10000, target error atau performance 0.00642 dengan nilai rata-rata sebesar 80%. Selanjutnya diperoleh proses data pelatihan tingkat kematangan pisang dengan 4 iterasi dari input maksimum epoch 10000, target error atau performance 0.00606 dengan nilai akurasi sebesar 90%. Dari proses uji citra yang telah dilakukan bahwa sistem dapat mengidentifikasi jenis buah pisang beserta tingkat kematangannya berdasarkan inputan ekstraksi fitur dari citra buah pisang. Penelitian ini juga bertujuan untuk menguji dan mengetahui tingkat akurasi penerapan metode Backpropagationdalam mengidentifikasi jenis buah pisang dan tingkat kematangannya.
THE USE OF DEMPSTER SHAFER'S METHOD FOR DIAGNOSING ACUTE RENAL FAILURE IN CHILDREN Nopita, Siska; Simanjuntak, Magdalena; Lubis, Imran
Journal of Mathematics and Technology (MATECH) Vol. 2 No. 2 (2023): Journal MATECH (November 2023)
Publisher : Yayasan Bina Internusa Mabarindo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63893/matech.v2i2.156

Abstract

Acute kidney failure (acute kidney injury) is a condition in which the kidneys stop functioning suddenly. Acute kidney failure is known to attack children in the age range of 6 months-18 years, as of October 18, 2022, a total of 118 cases have been reported, most of which are dominated by ages 1-5 years. This condition can occur due to impaired blood flow to the kidneys, disorders in the kidneys, or blockages in the urinary tract, with initial symptoms in the form of gastrointestinal infections and symptoms of ARI, the typical symptom is the amount of urine that decreases even can not tub at all. In such conditions, it is already an advanced phase and must be immediately taken to health facilities such as hospitals. Acute renal failure in children is a significant health problem. Its prevalence has increased in recent years and can have serious repercussions on children's health. Acute kidney failure can lead to impaired kidney function, an increased risk of complications such as edema, electrolyte disturbances and impaired body fluid balance. The process of diagnosing acute kidney failure in children can be challenging because the symptoms and signs are often nonspecific. The Diagnosis is made based on clinical evaluation, laboratory tests such as urine and blood analysis, and imaging exams if necessary. Because the knowledge and information of the community / patient is still lacking, causing delays in handling the early symptoms of acute kidney failure in children. Therefore, it is necessary to have a system in addressing the problem of acute kidney failure in children by knowing the early symptoms of the disease and other information. The system that will be built will be able to detect acute renal failure disease with symptoms suffered by patients using the dempster shafer method at the output of the system. The purpose of this study is to design an expert system application using the Dempster Shaper method in diagnosing kidney failure in children.
EXPERT SYSTEM OF DISEASES OF THE FEMALE CHILDBEARING PERIOD USING BAYES THEOREM METHOD Ananda Sari, Dea; Novriyenni, Novriyenni; Ramadani, Suci
Journal of Mathematics and Technology (MATECH) Vol. 2 No. 2 (2023): Journal MATECH (November 2023)
Publisher : Yayasan Bina Internusa Mabarindo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63893/matech.v2i2.157

Abstract

A woman's fertile period is a menstrual cycle in women that occurs once a month. The average fertile period lasts between days 8-19 after the first menstrual period ends. During this fertile period, women will release mature egg cells from the ovaries to the uterus or the so-called ovulation period. There are several menstrual cycles in women, namely the follicular fake menstrual cycle (pre-ovulation) and the luteal phase. If the menstrual period in women is smooth, it is said that it is impossible to have a disease, but in fact there are still diseases in women who have experienced a menstrual period who must get a doctor's treatment as soon as possible.Edward clinic is one of the gynecology clinics that currently serves a variety of health care in pregnant women and complaints in certain areas of women, as well as problems with female fertility. With the development of increasingly sophisticated technology, Edward clinic must be able to follow the development of existing systems in order to make it easier for users to find more complete information by processing patient data and other information. Therefore, the authors want to design an application to assist users in providing services to patients in obtaining more efficient information about the problem of women's fertile period disease, by designing and building a system that will be used in the process to diagnose women's fertile period disease based on symptoms felt by patients using Bayes ' Theorem method, in order to facilitate and shorten the time patients in consultation or further examination. From the results of the study obtained the certainty value of the combination of bayes ' theorem that patients are likely to experience egg follicle disease in women's fertile period with a percentage of 69.50%.

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