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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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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.
APPLICATION OF NAIVE BAYES METHOD TO DIAGNOSE FMD DISEASE IN GOATS Sawitri, Sawitri; Simanjuntak, Magdalena; Pardede, Akim Manaor Hara
Journal of Mathematics and Technology (MATECH) Vol. 3 No. 2 (2024): Journal MATECH (November 2024)
Publisher : Yayasan Bina Internusa Mabarindo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63893/matech.v3i2.171

Abstract

Hoof and mouth disease (FMD) is an infectious disease that affects cloven-hoofed farm animals such as cows, buffaloes, goats, sheep and pigs. The emergence of FMD is caused by a virus called foot and mouth diseases virus (FMVD). The Virus slowly eats away at the hooves and mouths of livestock, making the animals unable to eat and walk. Examination of disease in goats periodically is currently less attention so as to make goats susceptible to disease. This makes it difficult for farmers in the initial handling and do not know what to do in the absence of an expert. The process of disease diagnosis in goats can not be done by just anyone because between the types of diseases with symptoms have uncertainty. Based on these problems, the authors create an expert system that is able to diagnose diseases in goats as is commonly done by an expert using Naive Bayes method that will help livestock groups in diagnosing diseases in goats. The input is in the form of symptoms that occur in the field and the output is the result of diagnosis and treatment advice. From the test results obtained because the conclusion value (P / PMK type Oise (O)) is greater than the value (P|PMK type Asia 1) then the decision is “PMK type Oise (O)” with a value of 0.02.
THE USE OF BAYES METHOD TO DIAGNOSE GESTATIONAL DIABETES IN PREGNANT WOMEN (CASE STUDY: DR. EDWARD JOB,. SP.OG) Maulidina, Nadia; Simanjuntak, Magdalena; Maulita, Yani
Journal of Mathematics and Technology (MATECH) Vol. 3 No. 2 (2024): Journal MATECH (November 2024)
Publisher : Yayasan Bina Internusa Mabarindo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63893/matech.v3i2.175

Abstract

 Gestational Diabetes is the cause of diabetes that occurs during pregnancy, generally, this pregnancy occurs in the second trimester, between Weeks 24 to 28. Gestational Diabetes is one of the causes of death of pregnant women due to lack of information or knowledge about the factors that cause gestational diabetes that occurs in mothers during pregnancy, causing health risks, and affect the decision of time, cost and others in carrying out direct medical consultations. Therefore, it is highly recommended that an expert system for treating gestational diabetes in pregnant women be able to find out early about what is happening and be able to overcome the causes and reduce mortality. With the existence of this system is expected to be an alternative for patients who experience complications of time, cost and others in consulting directly about the treatment of gestational diabetes in pregnant women, before coming directly to meet with a doctor/expert. From the process using the Bayes method above, it is explained that the diagnosis of gestational diabetes in pregnant women is diagnosed with gestational diabetes Diabetes Mellitus (P01) with a percentage of 90.73%.
EXPERT SYSTEM OF PREECLAMPSIA DIAGNOSIS USING CERTAINTY FACTOR METHOD Tarigan, Kiki Dea Ananda; Simanjuntak, Magdalena; Maulita, Yani
Journal of Mathematics and Technology (MATECH) Vol. 3 No. 2 (2024): Journal MATECH (November 2024)
Publisher : Yayasan Bina Internusa Mabarindo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63893/matech.v3i2.176

Abstract

Preeclampsia is an increase in blood pressure and excess protein in the urine that occurs after more than 20 weeks of pregnancy. If not treated immediately, preeclampsia can cause complications that are dangerous for the mother and fetus. One factor that can increase the risk of preeclampsia is the age of pregnant women who are under 20 years or more than 40 years. This condition needs to be treated immediately to prevent complications or develop into preeclampsia that can threaten the lives of pregnant women and fetuses. The causes of preeclampsia are still not exactly known. However, this condition is thought to occur due to abnormalities in the development and function of the placenta, which is an organ that functions to deliver blood and nutrients to the fetus. The use of internet technology makes it easier for humans to access information without limited space and time and facilitates the design of expert systems to diagnose preeclampsia in mothers, and is expected to reduce or even eliminate existing problems, Therefore, an application is needed that can help to diagnose preeclampsia by using the certainty factor method which is easier and becomes an alternative in providing more knowledge about the results of preeclampsia diagnosis in pregnant women and can provide advice and consultation media about preeclampsia disease in patients and can reduce the cost of consulting an expert. Based on the calculation of CF, the highest value is the type of preeclampsia with a value of 0.9939 or 99.39%. From the results obtained, the system identifies that the patient has a type of preeclampsia.
ANALISIS CLUSTER STUNTING DENGAN METODE K-MEANS DI KOTA BINJAI Buaton, Relita; Maulidya, Adek; Simanjuntak, Magdalena; Sinaga, Ayu Puspita Sari
Journal of Information System, Informatics and Computing Vol 9 No 1 (2025): JISICOM (June 2025)
Publisher : Sekolah Tinggi Manajemen Informatika dan Komputer Jayakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52362/jisicom.v9i1.1927

Abstract

Puskesmas berperan penting dalam meningkatkan kesehatan masyarakat. Analisis data kesehatan yang tepat dapat membantu dalam mengidentifikasi kelompok populasi yang membutuhkan perhatian khusus. Sumber daya manusia yang unggul dan berkualitas didasari dengan sumber daya manusia yang sehat dengan indikator tercukupinya asupan gizi sesuai dengan perkembangan usianya. Namun masalah kelaparan dan kekurangan gizi masih dihadapi oleh dunia hingga saat ini. Menurut laporan Unicef, jumlah penduduk yang menderita kekurangan gizi di dunia mencapai 767,9 juta orang pada tahun 2021. Organisasi Kesehatan Dunia (WHO) mengatakan, kekurangan gizi menjadi salah satu ancaman berbahaya bagi kesehatan penduduk dunia. Stunting juga berdampak di Indonesia, prevalensi balita yang mengalami stunting di Indonesia sebanyak 21,6% pada tahun 2022. Penelitian ini bertujuan untuk mengklasifikasikan data kesehatan dari Puskesmas di Binjai menggunakan algoritma K-Means untuk memahami karakteristik setiap kluster.Dilakukan studi lapangan dengan mengolah data hasil penimbangan anak, data diolah dengan menggunakan metode cluster sehingga diperoleh cluster stunting untuk wilayah Kota Binjai yakni kluster 1: mencerminkan kondisi kesehatan yang baik, dengan nilai rata-rata yang rendah pada indikator risiko gizi dan gizi buruk, kluster 2: menunjukkan kondisi yang sangat buruk, dengan nilai yang tinggi pada hampir semua indikator, mencerminkan masalah kesehatan yang serius di populasi tersebut dan kluster 3: menunjukkan kondisi moderat, dengan nilai yang berada di antara kluster 1 dan kluster 2. Hasil analisis menunjukkan bahwa terdapat tiga kluster yang berbeda, masing-masing dengan karakteristik kesehatan yang unik. Pengujian kluster dilakukan dengan menggunakan metode cluster analysis untuk memastikan validitas hasil. Temuan ini diharapkan dapat memberikan rekomendasi bagi pihak dians kesehatan dalam merancang program intervensi kesehatan yang lebih tepat sasaran dengan hasil pengujian Silhouette Score: 0.65, menunjukkan bahwa kluster yang terbentuk cukup baik. Davies-Bouldin Index: 0.3, menunjukkan pemisahan kluster yang baik. Inertia: 1500 menandakan bahwa data terdistribusi dengan baik di sekitar centroid.
OPTIMASI PENJADWALAN MATA KULIAH DENGAN MENGGUNAKAN PSO Simanjuntak, Magdalena; Sitompul, Melda Pita Uli; Juliana Naftali Sitompul; Kahfi Lanang; Rahimah Faizah
Jurnal Mahajana Informasi Vol 10 No 1 (2025): JURNAL MAHAJANA INFORMASI
Publisher : Universitas Sari Mutiara Indonesia Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51544/jurnalmi.v10i1.6062

Abstract

Penjadwalan mata kuliah merupakan masalah kompleks yang sering dihadapi oleh institusi pendidikan tinggi. Ketidakefisienan dalam penjadwalan dapat mengakibatkan konflik jadwal, pemanfaatan ruang yang tidak optimal, serta ketidakpuasan dosen dan mahasiswa. Oleh karena itu, diperlukan metode optimasi yang efektif untuk menghasilkan jadwal yang optimal dan efisien. Penelitian ini bertujuan untuk mengembangkan dan mengimplementasikan algoritma Particle Swarm Optimization (PSO) untuk mengoptimalkan penjadwalan mata kuliah. PSO dipilih karena kemampuannya dalam menangani masalah optimasi dengan ruang solusi yang besar dan kompleks. Algoritma ini diharapkan dapat menghasilkan jadwal yang meminimalkan konflik, mengoptimalkan penggunaan ruang kelas, serta memperhitungkan preferensi dosen dan mahasiswa. Penelitian ini menggunakan algoritma PSO untuk mencari solusi optimal dalam penjadwalan mata kuliah. Langkah-langkah dalam optimasi penjadwalan meliputi: Membentuk populasi partikel yang mewakili solusi potensial, Menetapkan jumlah partikel, kecepatan awal, koefisien kecepatan (c1, c2), dan faktor inersia, Mengembangkan fungsi tujuan yang mengevaluasi kualitas setiap solusi berdasarkan kriteria minimisasi konflik, optimalisasi penggunaan ruang, dan preferensi dosen serta mahasiswa, Memperbarui posisi dan kecepatan partikel berdasarkan rumus PSO, Mengevaluasi solusi baru, memperbarui pbest dan gbest berdasarkan hasil evaluasi, Menentukan kriteria konvergensi untuk mengakhiri iterasi algoritma. Dengan hasil penelitian ini, diharapkan dapat memberikan solusi yang praktis dan efektif bagi institusi pendidikan tinggi dalam mengelola penjadwalan mata kuliah, sehingga meningkatkan kualitas proses belajar mengajar.
Implementasi Algoritma Merkle Hellman untuk Keamanan Database Simanjuntak, Magdalena; Pasaribu, Tioria; Rahmadilla, Semiati
MEANS (Media Informasi Analisa dan Sistem) Volume 4 Nomor 1
Publisher : LPPM UNIKA Santo Thomas Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (339.35 KB) | DOI: 10.54367/means.v4i1.327

Abstract

The development of information technology today has a huge impact, namely the issue of security and confidentiality of data. One solution that can be used to guarantee the confidentiality and security of information is cryptography. By using cryptography, a data can be secured through the decryption and encryption process. Security issues and database confidentiality are the most important aspects of an information system. One mechanism to improve database security is to use asymmetric algorithms such as the Merkle Hellmen algorithm. Merkle Hellman is one of the crypto systems that uses the key type of asymmetry. In the Merkle Hellman system, the keys used are 2 different keys, namely the public key and the secret key. Encryption generates ciphertext and decryption produces a plaintext for securing databases that want to be kept confidential. The advantages of this Merkle Hellman algorithm is that there is no need for confidentiality in the key distribution process. From the results of experiments that have been done with this application, the encrypted database becomes a form of message that cannot be understood (ciphertext), but after the decryption process is done, the database is successfully returned to its original form (plaintext) that can be understood
Decision Support System for Choosing the Best Nurse Using the Multi Factor Evaluation Process (MFEP) Method at Djoelham Hospital, Binjai City Ningsih, Yulia; Simanjuntak, Magdalena; Saragih, Rusmin
Pascal: Journal of Computer Science and Informatics Vol. 2 No. 01 (2024): Pascal: Journal of Computer Science and Informatics
Publisher : Devitara Innovations

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Health workers are any person who is devoted to health and has knowledge and/or skills through education in the health field which for certain types requires the authority to carry out health efforts. A strategy is needed to increase the interest of health workers working in hospitals. The selection of exemplary health workers in hospitals is expected to be a motivation to increase the interest of health workers working in hospitals so that they can be a driver for the creation of health workers who have a nationalist, ethical and professional attitude, have a high spirit of service, are disciplined, creative, knowledgeable, skilled, virtuous and can uphold professional ethics. The purpose of this study is to evaluate the performance of nurses and reward the best nurses at Djoelham Hospital Binjai City. The use of the Multi Factor Evaluation Process (MFEP) method is relevant because it can help in integrating and evaluating various factors and criteria holistically. MFEP is a method that allows to evaluate various factors that affect decisions, as well as provide weight or value relative to each of these factors. The criteria used in this study are discipline, cooperation, loyalty, education, understanding of drug prescriptions, understanding of technology. The conclusion of this study is that the construction of this support system can help Djoelham Hospital in determining the best nurse and the use of the MFEP method in the decision support system to determine the best nurse increases accuracy in determining the best suitable nurse. This method is able to process various criteria that have been set, so that the results of decisions are more objective and fair compared to manual assessments.
Application of Decision Support System to Determine the Optimization of the Learning Plan Preparation Process in Schools Using the SAW Method Puspita Sari, Melani; Simanjuntak, Magdalena; Khadapi, Muammar
Pascal: Journal of Computer Science and Informatics Vol. 2 No. 01 (2024): Pascal: Journal of Computer Science and Informatics
Publisher : Devitara Innovations

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

The preparation of an effective learning plan is one of the important factors in improving the quality of education. In the context of the 2024 Independent Curriculum, the flexibility and independence of schools in designing learning plans will be greater, but this also requires the right strategy in determining priorities and the resources needed. This research aims to develop a Decision Support System (DSS) that can help optimize the process of preparing lesson plans in schools using the Simple Additive Weighting (SAW) method. The SAW method was chosen because of its ability to assess and compare various alternatives based on predetermined criteria, such as Relevance to the World of Work, Project-Based Learning, Special Competency Development, Technology Utilization, Soft Skills Development, Plan Flexibility, Inclusive Learning, Collaboration with Industry, Critical Thinking Skills, Time Management. The results of this study show that the DSS implemented is able to provide more effective and efficient recommendations in preparing learning plans that are in accordance with the principles of the 2024 Independent Curriculum. Thus, it is hoped that this system can be a tool for educators in developing more structured and targeted learning plans.
Diagnosis of Parasitic Diseases in Animals Cat Using Bayes Theorem Method Khairunisa, Salsabila; Maulita, Yani; 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.v3i1.265

Abstract

Cats are one of the most popular pets in the world, including Indonesian people who like to keep cats as pets, and even become a hobby for cat lovers. Diseases that often attack cats are caused by parasites, namely worms and fleas. Parasites that attack cats are grouped into two, namely ectoparasites and endoparasites. expert system which is a computer program , which is able to store knowledge and rules like an expert . With the help of an expert system, someone who is lay or not an expert in a particular field will be able to answer questions, solve problems, and make decisions that are usually made by an expert . The Bayes Theorem method can be applied to diagnose parasitic diseases in cats based on input symptoms chosen by the users, the system can perform analysis based on predetermined rules or knowledge base. Based on the probability value of each symptom and disease that has been made, the system can diagnose parasitic diseases in cats with different accuracy results, the highest value or percentage which is the result of the diagnosis of the parasitic disease. From the results of trials conducted by the expert system for diagnosing parasitic diseases in cats using the Bayes Theorem method, the highest value was obtained, namely the type of parasitic disease Flea Disease (P03) with a percentage of 38.66%.
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