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All Journal Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) INTEGER: Journal of Information Technology Jurnal Masyarakat Merdeka (JMM) Jurnal Teknik Informatika (JUTIF) COREAI: Jurnal Kecerdasan Buatan, Komputasi dan Teknologi Informasi
Misdram, Muhammad
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Mechanical Engineering Transportation Other

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Implementasi Sistem Pakar Untuk Mendiagnosa Penyakit Pada Perokok Aktif Dan Perokok Pasif Dengan Menggunakan Metode Anfis Safira, Laila; Misdram, Muhammad; Sani, Dian Ahkam
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
Prediksi Persediaan Bahan Baku Makanan pada Rumah Makan Menggunakan Metode Apriori (Studi Kasus Rumah Makan Soto Ayam Kampung Pasar Ranggeh) Yusuf, Angga Lazarudin; Misdram, Muhammad; Alamsyah, Muslim
COREAI: Jurnal Kecerdasan Buatan, Komputasi dan Teknologi Informasi Vol 5, No 1 (2024): Transformasi Digital: Tren dan Tantangan dalam Era Revolusi Industri 4.0
Publisher : Universitas Nurul Jadid

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33650/coreai.v5i1.6604

Abstract

Soto Ayam merupakan makanan lezat berkuah khas Nusantara, Soto Ayam adalah salah satu makanan favorit banyak orang. Soto Ayam bisa dikonsumsi kapan saja, baik pagi, siang, maupun malam, menggunakan nasi, lontong, atau ketupat. Berdasarkan seringnya terjadi kekurangan bahan baku makanan, maka dibuatlah prediksi persediaan bahan baku makanan mempergunakan metode Association Rule Mining (ARM) dengan memakai algoritma apriori. Hasil penelitian menunjukan bahwa dengan nilai minimum support 25% dan minimum confidence 50% menghasilkan kombinasi bahan baku beras dan ayam yang memiliki nilai support dan nilai confidence tertinggi dengan angka support 45,45% dan confidence 100%, sehingga bahan baku beras dan ayam yang harus di prioritaskan ketika memesan ulang bahan baku makanan.
STOCK PRICE PREDICTION USING THE LONG SHORT-TERM MEMORY METHOD Sahroni, Muhammad; Firman Arif, Mochammad; Misdram, Muhammad
Jurnal Teknik Informatika (Jutif) Vol. 5 No. 6 (2024): JUTIF Volume 5, Number 6, Desember 2024
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2024.5.6.2615

Abstract

Stocks are a highly risky investment instrument if not handled correctly. Therefore, accurately predicting stock prices is crucial to supporting better investment decisions. Today, more young people in the current generation know the importance of investing in stocks. Hence, understanding prediction methods early on is essential to reduce potential losses for prospective investors. With accurate prediction methods, the results will be more reliable. The data used consists of daily stock prices of Bank Syariah Indonesia from May 2019 to May 2024, totaling 1,215 data points. The research method employs LSTM (Long Short-Term Memory), which includes data collection, preprocessing, LSTM model formation, and model evaluation. The LSTM model is implemented using the Python programming language, and model evaluation is conducted using the Mean Absolute Percentage Error (MAPE) and Root Mean Squared Error (RMSE) metrics. The results show that the LSTM model can provide accurate predictions with a MAPE error value of only 1.72% and an RMSE of 53.49. This research indicates that the LSTM method is effective in predicting stock prices with an accuracy level of 98.28% and can be one of the bases when starting stock investment.
PENDAMPINGAN GURU-GURU UNTUK PENGEMBANGAN MEDIA IT DALAM MENG-ENTRI DATA SEBAGAI UPAYA UNTUK MEMPEROLEH SERTIFIKASI GURU DI LINGKUNGAN YAYASAN AMANAH PUTRA MANDIRI DI KECAMATAN GEMPOL KABUPATEN PASURUAN Misdram, Muhammad
JMM - Jurnal Masyarakat Merdeka Vol 1, No 1 (2018): NOVEMBER
Publisher : Universitas Merdeka Pasuruan

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (477.244 KB) | DOI: 10.51213/jmm.v1i1.8

Abstract

Pengabdian pada masyarakat berupa pendampingan dalam pengembangan media IT ini bertujuan untuk memberikan pengetahuan dan kemampuan dalam pengembangan media IT yang berguna untuk mengentri data Guru yang merupakan syarat yang diwajibkan oleh Dinas Pendidikan supaya data semua guru bisa diakses untuk memperoleh sertifikasi bagi guru. Kemampuan media IT diharapkan dapat mempercepat dan mempermudah perolehan sertifikasi guru dalam jabatan. Khalayak sasaran dalam kegiatan PPM ini adalah guru-guru dilingkungan Yayasan Amanah Putra Mandiri kec. Gempol, Kab. Pasuruan. Pendampingan dalam pengembangan media IT dilakukan dengan metode Praktek Langsung, demonstrasi dan latihan yang disertai uji coba mengentri data. Metode praktek dilakukan supaya guru-guru dapat mengoperasikan komputer. Metode demonstrasi dipakai untuk menunjukkan suatu proses kerja yaitu tahap-tahap pengembangan media IT, sedangkan metode latihan untuk mempraktikkan bagaimana cara mengentri data yang benar sebagai persyaratan program sertifikasi guru. Sementara uji coba untuk memberi kesempatan para Guru berkonsultasi dalam mengatasi kendala dalam memasukkan data guru. Ketersediaan tenaga ahli yang memadai dalam pengembangan media IT di Jurusan Teknik Informtika FTI Unmer Pasuruan, antusiasme Guru, dukungan kepala sekolah di lingkungan Yayasan Amanah Putra Mandiri terhadap pelaksanaan kegiatan dan dana pendukung dari FTI Unmer Pasuruan merupakan pendukung terlaksananya kegiatan PPM ini. Adapun kendala yang dihadapi adalah para guru belum memiliki pengetahuan awal tentang pengoperasian komputer dan keterbatasan waktu untuk pelatihan. Manfaat yang dapat diperoleh peserta dari kegiatan PPM ini antara lain dapat mengentri data guru di Dapodik Dinas Pendidikan. Media IT yang dihasilkan diharapkan dapat dengan mudah untuk memantau informasi sertifikasi bagi guru.Kata Kunci : Mengentri, Antusiasme, Dapodik
Gaussian Based-SMOTE Method for Handling Imbalanced Small Datasets Misdram, Muhammad; Noersasongko, Edi; Purwanto, Purwanto; Muljono, Muljono; Pamuji, Fandi Yulian
Jurnal Ilmiah Teknik Elektro Komputer dan Informatika Vol. 9 No. 4 (2023): December
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jiteki.v9i4.26881

Abstract

The problem of dataset imbalance needs special handling, because it often creates obstacles to the classification process. A very important problem in classification is to overcome a decrease in classification performance. There have been many published researches on the topic of overcoming dataset imbalances, but the results are still unsatisfactory. This is proven by the results of the average accuracy increase which is still not significant. There are several common methods that can be used to deal with dataset imbalances. For example, oversampling, undersampling, Synthetic Minority Oversampling Technique (SMOTE), Borderline-SMOTE, Adasyn, Cluster-SMOTE methods. These methods in testing the results of the classification accuracy average are still relatively low. In this research the selected dataset is a medical dataset which is classified as a small dataset of less than 200 records. The proposed method is Gaussian Based-SMOTE which is expected to work in a normal distribution and can determine excess samples for minority classes. The Gaussian Based-SMOTE method is a contribution of this research and can produce better accuracy than the previous research. The way the Gaussian Based-SMOTE method works is to start by determining the random location of synthesis candidates, determining the Gaussian distribution. The results of these two methods are substituted to produce perfect synthetic values. Generated synthetic values are combined with SMOTE sampling of the majority data from the training data, produce balanced data. The result of the balanced data classification trial from the influence of the Gaussian Based SMOTE result in a significant increase in accuracy values of 3% on average.
Co-Authors Alamsyah, Muslim Edi Noersasongko Fandi Yulian Pamuji Firman Arif, Mochammad Muljono Muljono Purwanto Purwanto Safira, Laila Sahroni, Muhammad Sani, Dian Ahkam Yusuf, Angga Lazarudin