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Journal : Journal of Artificial Intelligence and Engineering Applications (JAIEA)

Implementation of Mechine Learning Eligibility for Customer Credit Payments at Bank BTN Using the K – Nearst Neighbor Algorithm Ema Sari Suwandi; Relita Buaton; Rusmin Saragih
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 3 No. 1 (2023): October 2023
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59934/jaiea.v3i1.246

Abstract

Credit is the provision of money or bills that can be equated with that, based on a loan agreement or agreement between a bank and another party that requires the borrower to pay off the debt after a certain period of time with interest (Government of Indonesia, 1998). In its initial development, credit had a function in stimulating mutual assistance aimed at meeting needs, both in the field of business and meeting daily needs.In developing applications, it is necessary to predict applications at Bank BTN Medan accurately, accurate prediction results are very important in showing the right rating and decision-making in selecting customers. When customers experience arrears, the system used by Bank BTN Medan is still manual and has not applied predication in credit arrears to customers of Bank BTN Medan. Tests carried out in this test use a credit customer dataset from Bank BTN Medan. This study predicts the eligibility of customer credit payments at Bank BTN with the K – Nearst neighbor algorithm. The prediction of the level of smoothness of credit payments is made using K-Nearest Neighbor in order to be able to predict the smoothness of future credit payments.
Clustering Disease on Settlements Inhabitant In place seedy With Use Clustering Method Ruine Buana Br Sitepu; Achmad Fauzi; Rusmin Saragih
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 3 No. 1 (2023): October 2023
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59934/jaiea.v3i1.275

Abstract

Residents living in slum areas often face serious problems related to public health, where the prevalence of disease tends to be high and its spread is difficult to control. The impact of the formation of slums for the community is that safety is threatened, health deteriorates, and social conditions worsen, causing many diseases for people living in slums. Therefore, this study aims to identify patterns and clusters of diseases that exist in residential areas in slums Binjai city using clustering method. The K-Means Algorithm clustering method was chosen because it is able to group data based on similar characteristics, so that it can help identify diseases in a more focused and efficient manner, using the MATLAB application is also very appropriate in this problem so that it can produce output from data mining that can be used in decision making. future decisions. By utilizing the data mining process using the clustering method, clustering can be a problem of grouping diseases in slum settlements. Based on the results of trials with 20 sample data conducted with MATLAB obtained in cluster 1 DHF cases with high slums, Cluster 2 cases of vomiting with moderate slums and cluster 3 cases of diarrhea with moderate slums. The results of this study are expected to provide in-depth insight into disease patterns and clusters in residential areas in slums.
Expert System To Determine Psychological Disorders In Chronic Kidney Failure (CKD) Patients Undergoing Hemodialysis Therapy Using Certainty Factor Method SELVY SELVY ANGGRAINI; Rusmin Saragih; Husnul Khair
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 3 No. 1 (2023): October 2023
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59934/jaiea.v3i1.280

Abstract

Chronic Kidney Failure (CKD) is damage to the kidneys both in structure and/or function that lasts for 3 months or more. Hemodialysis is a prolonged therapy that can significantly impact the physical and psychological well-being of patients with chronic kidney disease. This therapy has a big effect on sufferers. The psychological impact that appears can affect the success of therapy so it is important to recognize these symptoms and provide appropriate treatment to overcome them. Based on research at Delia General Hospital, patients who will undergo Hemodialysis therapy must come to the hospital to receive comprehensive therapy by a doctor. Long patient queues when undergoing therapy can make patients tired and remember the patient's condition in order to get information and therapy. Handling of these problems can be overcome by building a system that can determine psychological disorders in patients. Expert systems are computer-based systems that use knowledge, facts and reasoning techniques in solving problems that usually can only be solved by an expert in a particular field. Certainty Factor (CF) is a method capable of defining the degree of certainty of a rule or fact in describing an expert's belief in the problem at hand. With an expert system, it can help identify and determine early on psychological disorders in patients. From the results of trials conducted by expert systems to determine psychological disorders in patients with kidney failure using the Certainty Factor method, the highest value is depression with a percentage of 94.59%.
Measuring the Maturity Level of Oil Palm Fruit For CPO Production Based on Color With Using the LVQ Method Abdullah Hamid; Rusmin Saragih; Siswan Syahputra
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 3 No. 1 (2023): October 2023
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59934/jaiea.v3i1.303

Abstract

Palm oil is a very important commodity besides oil and gas which also has a fairly good export value. The palm oil produced must be supported by the quality standards set by SNI. The level of maturity when harvesting oil palm fruit greatly influences the quality of Crude Palm Oil (CPO) production, which is crude palm oil that has a reddish color obtained from extraction or from the pressing process of oil palm fruit flesh. In fact, in the field of oil palm fruit harvest, there are still many oil palm fruit that are not ripe enough and can even be said to be still raw, entering the CPO production process. Determination of the maturity level of oil palm fruit is generally determined based on the amount of loose fruit and color, so handling the harvest of oil palm fruit is an important activity in improving the quality of CPO. It is necessary to build a system capable of managing and processing palm fruit images to measure the maturity level of the palm fruit to be produced. To obtain the right level of accuracy, this research uses the Learning Vector Quantization (LVQ) method. LVQ is a method for conducting supervised competitive layer learning. From the results of trials conducted, it is proven that the system can measure very ripe oil palm fruit with HSV values (0.052209; 0.896021; 0.791114).
Clustering Data On Underage Marriage Using The Clustering Method Sonadi Perangin Angin; Rusmin Saragih; Marto Sihombing
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 3 No. 1 (2023): October 2023
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59934/jaiea.v3i1.370

Abstract

In Law no. 1 of 1974, article 7 paragraph (1) states that marriage is only permitted if the man has reached the age of 19 and the woman has reached the age of 16. Nationally, early marriage to the age of under 16 is 26.95%. In fact, based on the findings of Bappenas in 2008, it was stated that 34.5% of the 2,049,000 marriages in 2008 until now were child marriages which were increasing rapidly (Rifiani, 2011: 126). The influence of foreign culture is also one of the causes of the large number of underage marriages, foreign cultures which are very famous for freedom of dating, are the views of today's youth to have relations outside of legal marriage. Not only culture, information technology in the 4.0 era has greatly influenced the occurrence of underage marriages, adult video sites that are easily accessible via the internet. For this reason, the K-means clustering method is used as the right solution for the problem of underage marriage data by grouping the data based on age, gender, and occupation to get definite data, so that data grouping using the applicationmatlab andrapid miner can produce output from data mining that can be used in making decisions in the future Keywords: Underage marriage, clustering, matlab
Implementation of the Smart Method in Selection of Contraceptive Devices in Couples of Childbearing Age Case Study: Datar City Health Center Rahmawati; Rusmin Saragih; Mili Alfhi Syari
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 3 No. 1 (2023): October 2023
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59934/jaiea.v3i1.384

Abstract

In a marriage, the presence of a child is something that is desired. The Indonesian government, in particular, the National Population and Family Planning Agency (BKKBN) advises husband and wife couples to have a maximum of 2 children. One way to plan the number and timing of pregnancies is to use contraception. This research implements the SMART (Specific, Measurable, Achievable, Relevant, and Time-bound) Method in the selection of contraceptives for couples of reproductive age at the Kota Datar Health Center. The results obtained from the research conducted show that the SMART method used in this system has been proven to be effective in helping select contraceptives for couples of childbearing age in the Datar City Community Health Center case study, because it can select alternatives and carry out rankings in determining the right contraceptive for couples of childbearing age. according to needs based on predetermined criteria, where the injection alternative (A04) with a final score of 83 is a suitable contraceptive for couples of childbearing age according to their needs.
Design of an Automatic Trash Can Wheel Robot with Bluetooth Navigation Control Through Smartphone Application Irfan Yusuf; Yani Maulita; Saragih, Rusmin
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 4 No. 1 (2024): October 2024
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59934/jaiea.v4i1.631

Abstract

Environmental cleanliness is an important aspect that must be maintained, especially in this modern era. The use of appropriate technology can help increase awareness of cleanliness, one of which is by developing automatic trash cans. This research designs and builds a mobile robot in the form of an automatic trash can that can be controlled via an Arduino Uno microcontroller using Bluetooth and controlled via a smartphone application. This research designs a mobile robot in the form of an automatic trash can that can be controlled via an Arduino Uno microcontroller with Bluetooth and a smartphone application. The system receives navigation commands from the app and uses ultrasonic sensors to detect objects in front of the trash can. The microcontroller processes the command and sensor data to drive the DC motor and servo motor. The servo motor opens and closes the trash can lid automatically when an object is detected at a certain distance. The test results show that this robot can move according to instructions from a smartphone and successfully open and close the trash can lid automatically when detecting objects.
Analysis of Village Residents Receiving Social Assistance Using Linear Regression Method Rafli Fitriawan; Saragih, Rusmin; Ambarita, Indah
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 4 No. 1 (2024): October 2024
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59934/jaiea.v4i1.677

Abstract

This study aims to analyze the recipients of social assistance in Banyumas Village using the simple linear regression method. The research examines how household income affects the amount of social assistance received. Data was collected from the Banyumas Village Office, including information on income and the amount of social assistance received by residents. The results show a negative relationship between household income and the amount of assistance received, where higher income leads to smaller assistance. The model also demonstrates good accuracy with an average prediction error (MAPE) of 9.38%. Additionally, an R² value of 0.999972 indicates that the model can explain almost all variations in the data. This study provides valuable insights into the effectiveness of the social assistance program in Banyumas Village and to help improve the program in the future.
Co-Authors , Eka Putra Abdul Azan Abdul Azan Abdullah Hamid Abdullah Husein Achmad Fauzi ACHMAD FAUZI Alfina Damayanti Ambarita, Indah Andini Andini Andre Adrian Andrean Samuel Siahaan Aprilianda, Dinda Arianta Bangun Arnes Sembiring Asih, Munjiat Setiani Barany Fachri Boyke Gunawan Manurung Buaton, Relita Chairul Rizal Charles Jhony Mantho Sianturi, Charles Jhony Mantho Cindy Primadona Siahaan Damayanti, Fera Dandi Satria R Deni Apriadi Dewantara, Nowell Dimas Prayogi Dinda Firdawati Simamora Divi Handoko Eka Pandu Cynthia Eka, Muhammad Ema Sari Suwandi Fany Juliawati Fatimah Fatmaira, Zira Fauzi, Achmad frans ikorasaki Fuzy Yustika Manik Fuzy Yustika Manik, Fuzy Yustika Gea, Fide Evianti Ginting, Darmawan Gultom, Imeldawaty Handoko, Divi Herdiansyah Harahap Herdiansyah Harahap Hesty Vitara I Gusti Prahmana Ikhsan Arif Indra Prasetia, Indra Irfan Yusuf Ismi Asmita Jesayas Sembiring Khair, Husnul Lestari, Yuyun Dwi Lili Musarofah Lili Musarofah Loo, Petrus Magdalena Simanjuntak Magdalena Simanjuntak Magdalena Simanjuntak Mardiah Marto Sihombing Marto Sihombing Meisaroh Mhd Ferdiansyah Putra Mili Alfhi Syari Muhammad Danil Syahputra Muhammad Danil Syahputra Muhammad Eka Muhammad Eka Muhammad Noor Hasan Siregar Muhammad Reza Habibi Muhammad Zen, Muhammad Munadi Munadi Nasril Hidayat Nico Kurniawan Purba Nikous Soter Sihombing Novriyenni Novriyenni Novriyenni Novriyenni, Novriyenni Nurhayati Nurhayati Nurhayati Nurhayati Nurhayati Nurhayati Nurhayati Nurhayati Nurlaila Nurlaila Nurlaila Nurlaila Nuryahati - Pakpahan, emma martina Pakpahan, Victor Maruli Pardede, Akim Manaor Hara Pasaribu, Tioria Rafli Fitriawan Rahayu Utami Rahmadani Rahmadani Rahmawati Rahmawati, Rahmawati Raihan, Muhammad Ramadani, Suci Ramli Ramli Ramos Parulian Ambarita Ratih Puspadini Rianty Zabitha Siregar Ricky Ramadhan Harahap Rizki Kurniawan Ruine Buana Br Sitepu Ryan Hidayat Saripurna, Darjat SELVY SELVY ANGGRAINI Sihombing, Anton Sihombing, Marto Simanjuntak, Magdalena Sinaga, Ayu Puspita Sari Sirait, Win Gomgom Parsaulian Siswan Syahputra SITORUS, ERBIN Sonadi Perangin Angin Suci Pratiwi, Kiki Supiyandi Supiyandi Syahputra, Siswan Syari, Milli Alfhi Tantia Azzahra Tata Mustika Dewi tata, tatamustikadewi Theodora MV Nainggolan Ulandari, Seri Wati, Sri Kesuma Yani Maulita Yekolya Anatesya Yessi Fitri Annisah Lubis Yulia Ningsih Yusuf Afani Yuyun Dwi Lestari