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All Journal INTEGER: Journal of Information Technology SMARTICS Journal J I M P - Jurnal Informatika Merdeka Pasuruan Jurnal Teknologi Terpadu SPIRIT
Muhammad Misdram
Jurusan Informatika Fakultas Teknologi Informasi Universitas Merdeka Pasuruan
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Engineering

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OPTIMASI KOMPOSISI MAKANAN UNTUK PENDERITA ANEMIA MENGGUNAKAN METODE VARIABLE NEIGHBORHOOD SEARCH Muhammad Misdram; Adi Cahyono
SPIRIT Vol 13, No 1 (2021): Jurnal SPIRIT
Publisher : STMIK YADIKA BANGIL

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53567/spirit.v13i1.201

Abstract

Abstract: Lack of blood or anemia is a condition when the body lacks healthy red blood cells or when red blood cells do not function properly. Anemia is defined as a low concentration of hemoglobin (Hb) in the blood (WHO, 2015). Anemia is one of the problems with anemia that commonly occurs when the number of erythrocytes is less than normal or due to low hemoglobin concentrations in the blood (Depkes, 2008). One of the efforts to live a healthy life in patients with anemia is to pay attention to the consumption of healthy foods as needed. The composition of food by paying attention to the level of iron content in food can be done using the Variable Neighborhood Search (VNS) method. The data used in this study are 100 food data and data on nutritional needs according to age and gender. VNS has several stages, namely after generating the initial solution then doing the shaking stage, local search. The test results show that the average fitness results are seen from the criteria values. The number of local searches that are too many does not guarantee a solution with the best fitness, but a large number of local searches can provide wider search opportunities. The results of the study were in the form of optimizing the composition of food that had been selected by the patient by approaching the nutritional needs of the anemic patient.Keywords: Anemia, Food Composition, Variable Neighborhood Search
KLASIFIKASI DATA SET VIRUS CORONA MENGGUNAKAN METODE NAÏVE BAYES CLASSIFIER Muhammad Misdram; Fahmi Syarifuddin; Anang Aris Widodo
SPIRIT Vol 12, No 2 (2020): SPIRIT
Publisher : STMIK YADIKA BANGIL

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53567/spirit.v12i2.184

Abstract

Abstract: At the beginning of 2020 the world of health was shocked by the discovery of a new virus that was known to have originated from this virus in Wuhan, China. Almost the whole world has experienced this virus pandemic. Then on February 11, 2020, the World Health Organization named the new virus Severa acute respiratory syndrome coronavirus-2 (SARS-CoV-2) and the name of the disease as Coronavirus Disease 2019 (COVID-19) (WHO, 2020). At first, the transmission of this virus could not be determined whether it was between animal-human or human-human. Meanwhile, the number of cases continues to increase over time. At that time, there were 15 medics infected by one of the patients. It was finally confirmed that the transmission of pneumonia can be transmitted from human to human. Until now, the handling of Covid-19 patients is still continuing. This is because the number of patients continues to grow every day. For this reason, an application is needed that can monitor the cure rate for Covid-19 patients. This system is built using the Naïve Bayes Classification (NBC) method. The NBC method is a method used for classification and can predict future opportunities based on past experiences. The test results show that using the Nive Bayes Method has a fairly good accuracy, namely 84%. Keywords : Covid-19, classification, Naïve Bayes Classifier
Pencarian Perangkat Alat Produksi Telekomunikasi Berbasis Webgis Menggunakan Metode Dijkstra Danang Tisma Amijaya; Anang Aris Widodo; Muhammad Misdram
J I M P - Jurnal Informatika Merdeka Pasuruan Vol 5, No 3 (2020): DESEMBER
Publisher : Fakultas Teknologi Informasi Universitas Merdeka Pasuruan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37438/jimp.v5i3.318

Abstract

Optical Distribution Cabinet (ODC)  adalah   salah      satu   alat   produksi yang  dimiliki PT.Telkom untuk mendistribusikan internet kesetiap daerah demi pelanggan supaya dapat menikmati jaringan internet.  Hampir disetiap kota bahkan setiap pelosok pedalaman ada perangkat milik PT. Telekomunikasi Indonesia. Pada penelitian ini penulis mengimplementasikan metode Dijkstra yang digunakan untuk mencari rute terpendek. Algoritma yang cukup popular yang  ditemukan  oleh  Edsger  Wybe  Dijkstra.  Dijkstra  akan  berperan  dalam  menentukan  rute terpendek  menuju  ke perangkat yang lokasinya sudah di dapatkan dari PT.Telkom Pasuruan. Djikstra merupakan salah satu varian bentuk algoritma popular dalam pemecahan persoalan terkait masalah optimasi pencarian lintasan terpendek sebuah lintasan yang mempunyai panjang minimum dari verteks a ke j dalam graph berbobot, bobot tersebut adalah bilangan positif jadi tidak dapat dilalui oleh node negatif. Namun jika terjadi demikian, maka penyelesaian yang diberikan adalah infiniti (Tak Hingga). Pada algoritma Dijkstra, node digunakan karena algoritma Dijkstra menggunakan graph berarah untuk penentuan rute listasan terpendek. Dari hasil penelitian yang telah di lakukan   penulis dapat mengambil kesimpulan menerapkan metode dijkstra dilakukan pada titik (A) yaitu lokasi awal dengan tujuan titik (J). kemudian didapakan beberapa pilihan rute yang yang berjumlah 4 rute dengan satuan Kilometer. untuk rute pertama mendapatkan hasil (0,67),   kedua (0,7),   ketiga (0,9), keempat  (0,69).  rute  yang diambil  berdasarkan  rute  yang  memiliki  nilai  paling  kecil  yaitu  rute  pertama  (0,67). Kemudian dapat disimpulkan bahwa rute pertama adalah rute terpendekk untuk menuju ke tujuan (J).Kata kunci : Dijkstra, Edsger Wybe Dijkstra, ODC,  rute terpendek
Implementasi Sistem Pakar Untuk Mendiagnosa Penyakit Pada Perokok Aktif Dan Perokok Pasif Dengan Menggunakan Metode Anfis Laila Safira; Muhammad Misdram; Dian Ahkam Sani
INTEGER: Journal of Information Technology Vol 6, No 1: Mei 2021
Publisher : Fakultas Teknologi Informasi Institut Teknologi Adhi Tama Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31284/j.integer.2021.v6i1.1202

Abstract

Abstract. Cigarettes or cigars are cylinders of paper measuring between 70 and 120 mm long and about 10 mm in diameter containing chopped dried tobacco leaves. A person who inhales cigarette smoke is called a smoker. Smokers are divided into active smokers and passive smokers. An active smoker is someone who regularly consumes the smallest amount of cigarettes even though it's only 1 cigarette a day, and a passive smoker is someone who inhales cigarette smoke from an active smoker. Exposure to secondhand smoke can cause serious illness and death. The dangers of smoking on the health of the body have been researched and proven by many people. Lack of self-care, and lack of knowledge about the dangers of smoking make some people no longer think about their health in the future. Many rule out the bad effects caused by cigarette smoke. This is because these effects are not immediately visible when you first smoke. Many smokers are reluctant to get checked out for various reasons. Therefore, researchers made the implementation of an expert system to diagnose diseases in active smokers and passive smokers using the Anfis method. Anfis is an amalgamation of the system's fuzzy interface mechanism described in a neural network architecture. From the results of the implementation trial, the accuracy of the learning rate was 70% - 90% by including the same symptoms.Keywords: Expert System, Cigarettes, Anfis
Kombinasi Metode F-AHP dan F-TOPSIS dengan Rasio Keuangan untuk Menentukan Peringkat Bank Perkreditan Rakyat di Kota Malang Abdul Aziz; Muhammad Misdram
SMARTICS Journal Vol 4 No 2: SMARTICS Journal (Oktober 2018)
Publisher : Universitas PGRI Kanjuruhan Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (414.371 KB) | DOI: 10.21067/smartics.v4i2.2771

Abstract

Penentuan Peringkat Bank Perkreditan Rakyat dipandang penting untuk mempermudah masyarakat dalam memilih. Penentuan peringkat Bank Perkreditan Rakyat biasanya dilakukan sesuai dengan ketentuan Bank Indonesia peraturan Bank Indonesia (BI) No. 30/12/KEP/DIR Tanggal 30 April 1997 tentang Tata Cara Penilaian Kesehatan BPR. Banyak studi yang telah dilakukan untuk menentukan metode penentuan peringkat dengan pendekatan metode Fuzzy MCDM, BSC, F-AHP, F-TOPSIS, VIKOR, DANP pada bidang perbankan. Pada penelitian ini diusulkan sebuah model pendekatan evaluasi penilaian kinerja dengan kombinasi metode F-AHP dan F-TOPSIS dengan rasio keuangan sebagai kriteria penilaian (Capital, Assets, Equity dan Liquidity) untuk menentukan peringkat BPR di Kota Malang. Data yang digunakan adalah data laporan keuangan perbankan selama tiga tahun (2014-2016). Hasil penelitian menunjukkan bahwa kombinasi metode F-AHP dan F-TOPSIS dengan rasio keuangan dapat digunakan sebagai metode alternatif untuk menyusun peringkat Bank Perkreditan Rakyat di Kota Malang.
Deteksi Penyakit Kulit dengan Metode Convolutional Neural Network Menggunakan Arsitektur VGG19 Ainunnisa Indah Rizqya; Nanda Martyan Anggadimas; Muhammad Misdram
Jurnal Teknologi Terpadu Vol 11 No 2 (2025): Desember, 2025
Publisher : LPPM STT Terpadu Nurul Fikri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54914/jtt.v11i2.1900

Abstract

Early detection of skin diseases remains a major challenge, particularly in regions with limited access to dermatological services. This issue is further exacerbated by the shortage of medical specialists and the widespread presence of inaccurate health information online. This study aims to develop an automated image-based classification system capable of identifying five types of skin diseases: Eczema, Melanocytic Nevus, Melanoma, Benign Keratosis, and Basal Cell Carcinoma. The proposed method utilizes a Convolutional Neural Network (CNN) with the VGG19 architecture, enhanced through transfer learning and partial fine-tuning at the block4_conv1 layer. A dataset of 10,000 JPG images was used, with preprocessing steps including normalization, data augmentation, edge detection, and class balancing. Model performance was evaluated using accuracy, precision, recall, F1-score, and confusion matrix. Experimental results show that the model achieved an accuracy of up to 84% in the best scenario, with balanced performance across other metrics, indicating strong multiclass classification capabilities. These findings demonstrate the effectiveness of VGG19 in detecting skin diseases from images. The results also suggest the potential development of mobile-based early detection systems to support communities in underserved areas.
Co-Authors Abdul Aziz Adi Cahyono Ainunnisa Indah Rizqya Anang Aris Widodo Danang Tisma Amijaya Dian Ahkam Sani Fahmi Syarifuddin Laila Safira Nanda Martyan Anggadimas