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All Journal JISICOM (Journal of Information System, Infomatics and Computing) Jurnal Informatika Kaputama (JIK) Jurnal Sistem Informasi Kaputama (JSIK) JURNAL MAHAJANA INFORMASI JTIK (Jurnal Teknik Informatika Kaputama) MEANS (Media Informasi Analisa dan Sistem) Journal of Artificial Intelligence and Engineering Applications (JAIEA) International Journal of Informatics, Economics, Management and Science Journal of Engineering, Technology and Computing (JETCom) Journal of Mathematics and Technology (MATECH) Jurnal Pengabdian Pada Masyarakat METHABDI Jurnal Ilmu Komputer dan Sistem Informasi Jurnal ABDIMAS MUTIARA Pascal: Journal of Computer Science and Informatics JURNAL TEKNOLOGI, KESEHATAN DAN ILMU SOSIAL
Simanjuntak, Magdalena
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Regional Data Mining Implementation Of Contraceptive Equipment Users In The City Of Binjai By Type Using Clustering method Edelwais, Nurul; Simanjuntak, Magdalena; Sihombing, Marto
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.v3i1.284

Abstract

The government of the Binjai City BKKBN Office is one of the institutions responsible for controlling population growth and family planning in Indonesia which has a long-term impact that will occur if the family planning program is not implemented properly, there will be a population explosion and will cause various problems, including declining degree of health, social welfare, economic and cultural issues. Therefore, it is important to understand about contraception which will be useful in assisting the community in regulating birth rates and improving the quality of life, how contraceptives are used in Binjai City and how the levels of their use vary by region. This study aims to identify areas that use contraceptives in Binjai City based on the type of contraceptive used and to provide useful information for the government and health organizations in making policies and programs that benefit the community. Based on the results of the research conducted using a sample of 20 data, the results obtained from the data group are 12 data with the area group of contraceptive users in Binjai City based on their type with Age (X) being 18-25 years, and for the Kelurahan group (Y) is Binjai , and the type of contraception (Z ) injection for family planning.
Classification Of Diseases In Patients Based On Factors Environment Using The K-Means Algorithm At Puskesmas Subdistrict Selesai Ramadhani, Sisca; Sihombing, Marto; Simanjuntak, Magdalena
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.v3i1.309

Abstract

Diseases caused by the environment are disease phenomena caused by the relationship between humans and environmental factors. Diseases that occur due to the environment that must be known by the public are such as ISPA, dermatitis, diarrhea, pulmonary TB, and so on. In the area of the Kecamatan Selesai, there are still many environmental conditions Not yet such as damaged roads and smoke from factories that cause air pollution, so with condition environment like This can affect public health. Puskesmas Selesai is Public health center Which located in region Kecamatan Selesai. The data of patients seeking treatment at this puskesmas are only used archives and to view the patient's medical history. The public should know about symptoms of the disease in order to get appropriate services. In data mining techniques for clustering patient disease data can be used as new information useful for puskesmas or related as material counseling to society. The purpose of this study is to analyze the results of the application of data mining using K-Means Clustering in grouping patient diseases based on the environment with age, village and disease diagnoses variables.
Decision Support System for Determining Effective Learning Strategies for Students Using the SMART Method Athaya, Fara; Simanjuntak, Magdalena; Sitompul, Melda Pita Uli
Pascal: Journal of Computer Science and Informatics Vol. 2 No. 02 (2025): Pascal: Journal of Computer Science and Informatics
Publisher : Devitara Innovations

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Abstract

Effective learning strategies are essential factors in improving students’ academic achievement. However, at SMP Negeri 2 Binjai, several challenges remain, including the low effectiveness of applied learning methods, the lack of adaptation to individual learning styles, and the limited use of academic data in supporting learning decisions. These issues were further exacerbated by the post-pandemic shift toward hybrid learning models, which has not been fully optimized. To address this problem, this study designed a Decision Support System (DSS) using the SMART (Simple Multi-Attribute Rating Technique) method to recommend suitable learning strategies for students. The system was developed through stages of requirement analysis, logical design of the SMART calculation, and the implementation of integrated multi-criteria processing. The results show that the system can provide objective and accurate learning strategy recommendations. From 32 students analyzed, 11 students (34.37%) were recommended to adopt E-learning, 7 students (21.87%) to use Blended Learning, and 14 students (43.75%) to apply Traditional Learning. The highest score of 1.00 was achieved by two students in the E-learning category, while the lowest score of 0.125 was recorded in the Traditional category. These findings confirm that the application of the SMART method in DSS is effective in helping teachers and students determine more adaptive and personalized learning strategies, thereby supporting the improvement of learning quality in schools.
A Decision Support System for the Selection and Distribution of Superior Durian Seedlings to the Community Using the Decision Tree Method Danisuwara, Ardiya Kansya; Manurung, Hotler; Simanjuntak, Magdalena
Pascal: Journal of Computer Science and Informatics Vol. 2 No. 02 (2025): Pascal: Journal of Computer Science and Informatics
Publisher : Devitara Innovations

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Abstract

The durian fruit is an agricultural commodity with high economic value and strong demand both domestically and internationally. However, the success rate of durian cultivation in Indonesia remains relatively low, at approximately 30.3%. This is partly due to the limited experience of farmers in managing durian plantations and the absence of an objective system for selecting eligible recipients of superior seedlings. Inaccurate selection of seedling recipients can lead to low productivity, suboptimal fruit quality, and an imbalance between market supply and demand. To address these issues, this study proposes the development of a Decision Support System (DSS) for the selection of superior durian seedling recipients using the Decision Tree algorithm. The study identifies several factors influencing eligibility, including age, land area, land ownership, farming experience, socioeconomic status, number of plants, water availability, membership in farmer groups, regional location, and education level. Data from 300 respondents were collected and processed through several preprocessing stages, including categorical data encoding, numerical data binning, normalization, and the division of training and testing datasets. The Decision Tree model was developed using the Scikit-learn library in the Python programming language, with the Gini index as the splitting criterion. The experimental results indicate that the model achieved an accuracy of 85%, a precision of 90%, and a recall of 95% for the "Eligible" class, demonstrating the system’s effectiveness in accurately identifying qualified recipients. The system was implemented as a GUI-based desktop application using Tkinter, equipped with features for data input, eligibility prediction, recipient data management, and statistical visualization. The implementation of this system is expected to enhance objectivity, efficiency, and accountability in the distribution of superior durian seedlings, thereby contributing to increased productivity among durian farmers and promoting better market equilibrium.
DATA MINING PENGOLAHAN SEMUA PENGADUAN MENGGUNAKAN ALGORITMA K-MEANS (STUDI KASUS POLRES KOTA BINJAI) Yunika , Vica; Simanjuntak, Magdalena; Sembiring, Arnes
Jurnal Informatika Kaputama (JIK) Vol 6 No 2 (2022): Volume 6, Nomor 2, Juli 2022
Publisher : STMIK KAPUTAMA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59697/jik.v6i2.1112

Abstract

Hukum mengatur hubungan antara orang dengan orang lain dan membatasi kepekaan serta mengadakan larangan atau keharusan agar tercapai ketertiban hukum di dalam masyarakat.Tak jarang setiap orang berani melakukan tindakan yang melanggar aturan hukum demi mendapatkan sesuatu yang diinginkan,bahkan dapat menyebabkan kerugian, kehihangan suatu hak atas tindak kejahatan yang dilakukan. Masyarakat dapat melakukan pengaduan atas suatu tindakan yang terjadi pada dirinya yaitu dengan cara datang kekantor Kepolisian. Polres Kota Binjai memiliki data-data setiap pelaporan terhadap pengaduan masyakat yang terus bertambah setiap masyarakat yang melakukan pengaduan yang biasa disimpan dalam sebuah file dalam komputer. Data tersebut dapat diolah menjadi data yang berguna yang dapat digunakan untuk memperoleh sebuah informasi yang baru dengan cara membuat sebuah sistem yang akan membantu untuk menemukan informasi baru dari data tersebut. Algoritma K-Means adalah algoritma clustering yang populer dan banyak digunakan dalam dunia industri. Clustering menganalisis objek data yang digunakan untuk menghasilkan grup, grup tersebut didapatkan berdasarkan prinsip memaksimalkan kesamaan dalam kelas dan meminimalkan kesamaan antar kelas. Clustering adalah membagi data ke dalam grup-grup yang mempunyai obyek dengan karakteristiknya sama.
JARINGAN SARAF TIRUAN UNTUK MEMPREDIKSI JUMLAH PENGANGGURAN DI KOTA BINJAI DENGAN MENGGUNAKAN METODE BACKPROPAGATION Roynaldi, Muhammad; Simanjuntak, Magdalena; Khair, Husnul
JTIK (Jurnal Teknik Informatika Kaputama) Vol. 5 No. 1 (2021): Volume 5, Nomor 1, Januari 2021
Publisher : STMIK KAPUTAMA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59697/jtik.v5i1.580

Abstract

Unemployment is a very complex problem because it affects and is influenced by several factors that interact with each other following a pattern that is not always easy to understand. The strategic problem in Binjai City is not much different from that in the Central Government of North Sumatra, namely the high unemployment rate, given the large number of workforce that appears every year, as well as several factors such as age levels and inflation in Binjai City, making it difficult for many people to find work. or what is called unemployment. The lack of maximum efforts by the government and the private sector in creating employment opportunities is one of the triggers for the increasing number of unemployed in Indonesia, especially coupled with the low level of public education and inadequate human resources, which makes people unable to find work. One of the methods used in predicting a data is Artificial Neural Network using the backpropagation method. With a maximum epoch between 0 - 10000 with a learning rate of 0.2 and a target error ranging from 0.01 to 0.1 to get convergent results. The results of the prediction of the number of unemployed can be predicted by some experiencing an average predicted increase and some experiencing a decrease.
PENERAPAN ALGORITMA RIVEST SHAMIR ADLEMAN (RSA) UNTUK MENGAMANKAN DATABASE PROGRAM KELUARGA HARAPAN (PKH) Putra, Andika Cahya; Simanjuntak, Magdalena; Nurhayati, Nurhayati
JTIK (Jurnal Teknik Informatika Kaputama) Vol. 5 No. 1 (2021): Volume 5, Nomor 1, Januari 2021
Publisher : STMIK KAPUTAMA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59697/jtik.v5i1.588

Abstract

To maintain security, encryption techniques are used so that the confidentiality of the data is guaranteed. One of the encryption algorithms that is often used is the RSA (Rivest Shamir Adleman) algorithm. On this occasion the author is interested in studying the sql server database security application. In this study, the RSA (Rivest Shamir Adleman) algorithm is used to protect the PKH (Family Hope Program) database. The system will generate public keys and private keys. To secure the PKH database is encrypted with a public key. All data will be encrypted, while the private key will decrypt or restore the original state with the RSA algorithm. The application of the RSA cryptographic algorithm is a good solution for the sql server database security system that will be used to secure the PKH database. To ensure the confidentiality of PKH data stored in the database, by using the RSA algorithm into the system, the data is stored in the database so that the contents of the data cannot be understood by other parties.
JARINGAN SARAF TIRUAN MEMPREDIKSI PENJUALAN MAKANAN DAN MINUMAN DENGAN MENGGUNAKAN METODE BACKPROPAGATION (STUDI KASUS : PONDOK JATI RESTO BINJAI) Satria R, Dandi; Simanjuntak, Magdalena; Saragih, Rusmin
JTIK (Jurnal Teknik Informatika Kaputama) Vol. 5 No. 1 (2021): Volume 5, Nomor 1, Januari 2021
Publisher : STMIK KAPUTAMA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59697/jtik.v5i1.590

Abstract

Pondok Jati Resto (PJR) is a cafe that provides a variety of foods and beverages that are sold to attract customers or potential customers. The number of food and beverages that have been sold, of course, PJR has data on sales of food and beverages. So far, sales data have only been seen from sales reports. It is of course very unfortunate that other data, for example, such as ordered food and beverage menus, can be used as an evaluation material for food and beverage needs that are often in demand. Food and drink is one of the most needed needs by humans. There are many types of food and drink that are made to fulfill the desire to try a food and drink. Apart from being at home, food and beverages can also be obtained at shops, stalls, restaurants, cafes and so on. The increasing number of population levels and the increasing popularity of the food and beverage business, of course, there are more and more food and beverage sellers circulating in several areas, one of which is Cafe Pondok Jati Resto. The application of artificial neural networks to predict the amount of food and beverages using Matlab software using the Backpropagation method can be applied in predicting the number of food and beverage sales. Based on the analysis process that has been carried out under the artificial neural network system using the Backpropagation method, it can identify data on the number of food and beverage sales, with test results or predictions of the average number of foods per year 20, 5 drinks and 19 snacks.
Application of the Certainty Factor Method for Diagnosing Mental Illness Disease Mirah, Alta; Maulita, Yani; Simanjuntak, Magdalena
International Journal of Informatics, Economics, Management and Science Vol 2 No 2 (2023): IJIEMS (August 2023)
Publisher : Sekolah Tinggi Manajemen Informatika dan Komputer Jayakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52362/ijiems.v2i2.1208

Abstract

Mental illness is a disease that is widespread among Indonesian people. Mental illness, also known as mental health disorder, is a term that refers to various conditions that can affect a person's thoughts, moods, feelings or behavior. However, there are still many Indonesian people who do not recognize and indicate the existence of mental illness because many people do not pay attention to their mental health or those around them. the small number of psychiatrists available in each area and the costs required are also not small, causing ordinary people to be reluctant to carry out examinations with psychiatrists, this of course leads to delays in treatment which can even be fatal. To prevent the increase in sufferers of mental illness, a system is needed that can store the knowledge of experts or psychologists who understand how to handle mental illness. An expert expert system is an artificial intelligence program that combines a knowledge base with an inference system to emulate an expert. The certainty factor method is a method used to solve cases of uncertainty, where the size is based on a fact or rule that can be used in expert systems. With the existence of an expert system for diagnosing mental illness, the general public can recognize early symptoms of mental illness, so treatment can be done earlier. From the results of the trials conducted, the results of the mental illness expert system were obtained with the highest score, namely depression with a confidence value of 90.02%.
Pengenalan Tanda Tangan Dengan Menggunakan Metode Jaringan Syaraf Tiruan Backpropagation Hasibuan, Layla Mutiara; Fauzi, Achmad; Simanjuntak, Magdalena
JURNAL TEKNOLOGI KESEHATAN DAN ILMU SOSIAL (TEKESNOS) Vol. 4 No. 2 (2022): JURNAL TEKNOLOGI KESEHATAN DAN ILMU SOSIAL (TEKESNOS)
Publisher : Universitas Sari Mutiara Indonesia

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Abstract

Tanda tangan (signature) adalah sebuah tanda (sign) atau symbol yang merupakan versi miniatur dari pemiliknya. Tanda tangan juga merupakan fitur biometrik yang dapat digunakan untuk memverifikasi identitas seseorang. Tanda tangan yang digunakan sebagai identifikasi diri sendiri serta keberadaan tanda tangan dalam sebuah dokumen menyatakan bahwa pihak yang menandatangani, mengetahui dan menyetujui atau sebagai pengesahan seluruh isi dari dokumen serta menjadi bukti yang sah. Pengenalan tanda tangan dilakukan dengan menggunakan jaringan syaraf tiruan dengan algoritma backpropagation. Dalam algoritma backpropagation tanda tangan dilatih untuk mengenali tanda tangan seseorang dengan beberapa data seperti data target, data latih dan data uji. Kemudian jaringan tersebut dilakukan pengujian jaringan. Hasil aplikasi digunakan untuk mengenali pengenalan tanda tangan dengan menggunakan metode backpropagation yang didapatkan dengan akurasi yang berbeda mengikuti sesuai dengan data asli yang didapat dari ekstraksi ciri. Dimana akurasi terendah didapat 30% dan akurasi tertinggi didapat 100%.
Co-Authors Achmad Fauzi Adek Maulidya Agus Sapitri, Liana Ambarita, Indah Ana, Putri Annatasia, Kristina Apriandi Alfa Reza Saragih Ariska, Dedek Arliana, Lina Athaya, Fara Buaton, Relita Danisuwara, Ardiya Kansya Defita Br. Manurung, Sella Edelwais, Nurul Fauzan Akbar, Ahmad Fauzi Ahmad Muda Fauzi, Achmad Ginting, Budi Serasi Ginting, Darmawan Hasibuan, Layla Mutiara Imran Lubis Kadim, Lina Arliana Nur Kahfi Lanang Khadapi, Muammar Khair, Husnul Khairunisa, Salsabila MANURUNG, HOTLER Maulidina, Nadia Melda Pita Uli Sitompul Mirah, Alta Muammar Khadafi Nopita, Siska Novriyenni Novriyenni, Novriyenni Nurhayati Nurhayati Pardede, Akim Manaor Hara Pasaribu, Tioria Pramana, I Gusti Puspita Sari, Melani Putra, Andika Cahya Rahayu, Nur Aprilia Rahimah Faizah Rahmadilla, Semiati Ramadhani, Sisca Ratih Puspadini Roynaldi, Muhammad Rusmin Saragih, Rusmin Sari, Indah Kelana Satria R, Dandi Sawitri Sawitri Selfira, Selfira Sembiring, Arnes Sihombing, Anton Sihombing, Marto Sinaga, Ayu Puspita Sari Syahputra, Siswan Tarigan, Kiki Dea Ananda Yani Maulita Yulia Ningsih Yunika , Vica