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All Journal Jurnal Transformatika Jurnal Informatika dan Teknik Elektro Terapan Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer) Jurnal Riset dan Aplikasi Mahasiswa Informatika (JRAMI) RISTEC : Research in Information Systems and Technology
Sunandar, Muhamad Agus
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Computer Science & IT Decision Sciences, Operations Research & Management

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IMPLEMENTASI ALGORITMA LINEAR REGRESSION UNTUK PREDIKSI HARGA SAHAM PT. ANEKA TAMBANG TBK Hermanto, Teguh Iman; Nugroho, Imam Ma ruf; Sunandar, Muhamad Agus; Totohendarto, Mochamad Hafid
Jurnal Transformatika Vol. 19 No. 2 (2022): January 2022
Publisher : Jurusan Teknologi Informasi Universitas Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26623/transformatika.v19i2.4396

Abstract

Stock investments that provide high returns, but the higher the benefits offered, the higher the risk that will be faced in investing, especially if it is not supported by knowledge of analyzing stocks. This study utilizes the Data Mining prediction technique with the Linear Regression algorithm on the shares of PT. Aneka Tambang Tbk or ANTM. The dataset that will be used is downloaded through the Yahoo Finance website in the period January 2016 - March 2021. In this study the analytical method used is SEMMA (Sample, Explore, Modify, Model, Assess). With RapidMiner Studio 9.9 tools. The result of testing the RMSE (Root Mean Squared Error) value is 17.135, MSE (Mean Squared Error) is 293.599 and the MAPE (Mean Absolute Percentage Error) value is 1.87%. Based on the MAPE, the accuracy of the Linear Regression algorithm in predicting the stock price of PT. Aneka Tambang Tbk provides high-accuracy predictions.
DESIGN AND DEVELOPMENT OF THE MOSQPRAY APPLICATION USING EXTREME PROGRAMMING METHOD Prayoga, Satrio Mukti; Defriani, Meriska; Sunandar, Muhamad Agus
RISTEC : Research in Information Systems and Technology Vol. 6 No. 1 (2025): RISTEC: Research in Information Systems and Technology
Publisher : RISTEC : Research in Information Systems and Technology

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Abstract

This study aims to design and develop an Android application called MosqPray to help Muslims access prayer schedules automatically based on location and search for nearby mosques using the Google Maps API. The app includes prayer time reminders and favorite mosque saving features. The development method used is Extreme Programming (XP), which emphasizes short iterations and active user involvement. Observations of three similar apps revealed limited native mosque search features and issues with interface and ads. Testing shows MosqPray runs stably on Android 8.0 and above and provides accurate information. The app is expected to support timely prayer, especially in unfamiliar locations.
Diagnosa Penyakit Jantung Berdasarkan Kondisi Tubuh Dengan Metode Artificial Neural Network Febrianti, Nisa; Hermanto, Teguh Iman; Sunandar, Muhamad Agus
JURNAL FASILKOM Vol. 15 No. 2 (2025): Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer)
Publisher : Unversitas Muhammadiyah Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/jf.v15i2.9348

Abstract

Penyakit jantung merupakan salah satu penyebab utama kematian yang dapat memengaruhi individu pada usia produktif maupun lanjut usia. Oleh karena itu, strategi deteksi dini sangat dibutuhkan untuk mengurangi risiko komplikasi serta menekan biaya perawatan medis. Penelitian ini mengembangkan model klasifikasi berbasis Artificial Neural Network (ANN) guna meningkatkan akurasi dalam mendiagnosis penyakit jantung. Data penelitian bersumber dari Heart Disease Dataset Kaggle dengan jumlah 1.025 rekam medis pasien yang memuat 14 parameter klinis, di antaranya jenis nyeri dada, kadar kolesterol, detak jantung maksimum, hingga kadar gula darah puasa. Pendekatan CRISP-DM digunakan untuk mengarahkan tahapan penelitian mulai dari pemahaman data, pemilihan fitur, pelatihan model, evaluasi performa, hingga penerapan pada aplikasi mobile. ANN yang dibangun memiliki dua lapisan tersembunyi, menggunakan algoritma optimisasi Adam, dan dilatih selama 50 epoch. Evaluasi menghasilkan akurasi 79,61%, precision 73,53%, recall 94,34%, serta F1-score 82,64%. Model ini berhasil diimplementasikan pada platform Android sehingga memudahkan prediksi kondisi jantung secara efisien. Penelitian ini diharapkan mendukung kemajuan teknologi kesehatan digital dan dapat ditingkatkan dengan dataset yang lebih luas serta arsitektur model yang lebih kompleks.
Implementasi Metode ANN untuk Klasifikasi Diagnosis Tiroid Berbasis Aplikasi Mobile Rengganis, Mega Dwi; Hermanto, Teguh Iman; Sunandar, Muhamad Agus
Jurnal Riset dan Aplikasi Mahasiswa Informatika (JRAMI) Vol 6, No 04 (2025): Jurnal Riset dan Aplikasi Mahasiswa Informatika (JRAMI)
Publisher : Universitas Indraprasta PGRI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30998/jrami.v6i04.14502

Abstract

Kelenjar tiroid memegang peranan penting dalam pengaturan metabolisme melalui produksi hormon yang memengaruhi pertumbuhan, pembentukan protein, serta distribusi oksigen dalam tubuh. Gangguan pada organ ini, seperti gondok dan nodul, merupakan masalah endokrin yang umum terjadi di seluruh dunia. Sayangnya, banyak kasus tidak terdeteksi dini akibat gejala yang tidak khas dan kerap diabaikan. Dengan demikian, dibutuhkan metode deteksi dini yang memiliki tingkat keandalan tinggi. Penelitian ini mengaplikasikan metode Artificial Neural Network (ANN) sebagai pendekatan klasifikasi berbasis machine learning untuk identifikasi gangguan pada kelenjar tiroid. Model ANN yang dibangun kemudian diintegrasikan ke dalam aplikasi Android dengan antarmuka yang ramah pengguna. Evaluasi performa menunjukkan akurasi 97%, precision 99%, recall 97%, dan f1-score 98%, mencerminkan kapabilitas model dalam mengenali pola data yang kompleks secara konsisten. Integrasi sistem ke dalam platform mobile terlaksana dengan lancar, menghasilkan alat pendukung diagnosis awal yang efektif dan mudah dijangkau.
ANALYSIS QUALITY OF SERVICE OF INTERNET NETWORK FIBER TO THE HOME SERVICE PT. XYZ USING WIRESHARK Rachman, Daffa Aditya; Muhyidin, Yusuf; Sunandar, Muhamad Agus
Jurnal Informatika dan Teknik Elektro Terapan Vol. 11 No. 3s1 (2023)
Publisher : Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jitet.v11i3s1.3436

Abstract

The development of information technology continues to grow every year and successfully creates new technology, namely the internet. The internet is a public computer system that is globally connected and uses TCP/IIP as a packet-switching communication protocol. Telecommunication companies have access to internet networks, namely Fiber to the home (FTTH). FTTH provides services so that customers can utilize optical telecommunications. So that it will have a larger bandwidth to access the telephone, internet, and cable TV at the same time. In the service that has been done by xyz company, there have been many users who use this service, but there are several factors in the service regarding the slow and poor internet network at certain hours, and it does not answer how the solution to overcoming FTTH services from xyz company in the field of physical network This research was conducted using the Quality of Service (QoS) method to overcome these problems by using four parameters of QoS: throughput, packet loss, delay, and jitter. QoS is the collection of a network to provide data traffic services that pass through it. The results found that the quality of service on 5 SSIDs/xxyz company customers with a speed of 20 MbpsThe results are "Very Satisfactory". The values of Throughput, packet loss, Delay, and Jitter on the SSID can produce a very good index, and the average gets a very good index value.
Co-Authors Defriani, Meriska Febrianti, Nisa Hermanto, Teguh Iman Muhyidin, Yusuf Nugroho, Imam Ma ruf Prayoga, Satrio Mukti Rachman, Daffa Aditya Rengganis, Mega Dwi Totohendarto, Mochamad Hafid