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All Journal POSITIF Jurnal Pengabdian Multidisiplin Indonesia Jurnal Sistem Komputer Asia Jurnal ilmiah teknologi informasi Asia
Tria Aprilianto, Tria
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Arts Computer Science & IT Economics, Econometrics & Finance Education Electrical & Electronics Engineering Social Sciences

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Journal : POSITIF

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Analisa Pola Kelulusan Mahasiswa Pada Sekolah Tinggi Manajemen Informatika & Komputer ASIA Malang Dengan Menggunakan Algoritma Iterative Dichotomiser 3 (ID3) Yosepta, Dwi Anggih; Aprilianto, Tria
POSITIF : Jurnal Sistem dan Teknologi Informasi Vol 3 No 1 (2017): POSITIF - Jurnal Sistem dan Teknologi Informasi
Publisher : P3M Politeknik Negeri Banjarmasin

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31961/positif.v3i1.398

Abstract

Sekolah Tinggi Manajemen Informatika & Komputer ASIA Malang merupakan salah satu sekolah tinggi yang berada dalam lingkup pembinaan Kopertis Wilayah VII Jawa Timur yang dituntut untuk dapat menghasilkan lulusan dengan mutu yang baik. Tetapi kenyataannya tingkat kelulusan pada setiap angkatan masih terbilang cukup rendah bahkan tidak sedikit mahasiswa yang harus di dropout. Berdasarkan data mahasiswa lulus angkatan 2008-2011, rata-rata kelulusan mahasiswa sebesar 47%. Penelitian ini bertujuan untuk menganalisa pola kelulusan mahasiswa berdasarkan data induk mahasiswa serta riwayat perkuliahannya. Algoritma ID3 atau Iterative Dichotomiser 3 merupakan algoritma yang dapat digunakan untuk menganalisa pola kelulusan mahasiswa. Analisa dilakukan dengan cara menghitung entropy dan information gain pada setiap atribut yang selanjutnya membentuk pohon keputusan. Hasil penelitian ini diperoleh pola kelulusan mahasiswa yang kemudian dapat di generate menjadi pohon keputusan. Atribut yang mempengaruhi kelulusan mahasiswa adalah Indeks Prestasi Semester. Dari 1089 data yang digunakan untuk penelitian dihasilkan 27 pola/rule dan tingkat akurasi yang dihasilkan oleh perangkat lunak cukup baik yaitu 99,39% dengan pengujian yang dilakukan terhadap 163 dataset yang diambil secara acak. Sedangkan pengujian dengan data baru dihasilkan akurasi sebesar 100% dengan menguji 69 data.
EKSTRAKSI FITUR UNTUK MENGIDENTIFIKASI MARGA TANAMAN MENGGUNAKAN ALGORITMA BACKPROPAGATION Jatmika, Sunu; Aprilianto, Tria; Idris, Muhammad
POSITIF : Jurnal Sistem dan Teknologi Informasi Vol 6 No 1 (2020): Positif : Jurnal Sistem dan Teknologi Informasi
Publisher : P3M Politeknik Negeri Banjarmasin

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31961/positif.v6i1.907

Abstract

Feature extraction is the beginning to be able to classify and interpret images by linking the characteristics of the leaves into a group of clans according to their type. The algorithm used is backpropagation based on shape and color. The formulation of the problem taken is how the use of the backpropagation algorithm can improve the quality of the community in identifying leaf images. The purpose of this study is to make it easier for the general public to recognize plants, especially the family Azadirachta, Swietenia, and Khaya. This study uses data collection techniques in the form of observation, interviews, and documentation. Data analysis is done by entering content into the system. Data will be input into the learning machine obtained from feature extraction and processed with the backpropagation method. System design uses backpropagation algorithm to classify plants through leaf features. This system uses Android Studio and SQLite databases. The results of this study are that of 9 test data there are 8 recognizable data and 1 incorrectly recognized data. The data shows the accuracy of the backpropagation algorithm in facilitating the general public to recognize plants, especially the family Azadirachta, Swietenia, and Khaya is 88.9%. In addition, the results of the questionnaire show that the backpropagation algorithm has 66% application benefits, 76% ease of interaction, and 80% application display. The overall average of the benefits of each aspect is 74.2%.
SISTEM SMART GATE DENGAN MENGGUNAKAN WASTAFEL DAN SENSOR SUHU TOUCHLESS SENSOR BERBASIS FUZYY LOGIC CONTROL Jatmika, Sunu; Aprilianto, Tria; Burhanudin, Dimas
POSITIF : Jurnal Sistem dan Teknologi Informasi Vol 8 No 1 (2022): Positif : Jurnal Sistem dan Teknologi Informasi
Publisher : P3M Politeknik Negeri Banjarmasin

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31961/positif.v8i1.1262

Abstract

Health protocol standards are the main standards during the Covid-19 period. Because there is still a lack of public awareness in carrying out the protocol, one of which is that many people do not wash their hands before doing activities or even check body temperature sensors. In offices, whether private or government, tourist attractions, education and other health protocols still use employees, especially to check body temperature and lack of discipline in terms of checking users, so that people stay tipped, it is necessary the development of standard automation technology that must be carried out when the public will enter the office area or students before entering the school area through the gate. In order for the gate to be open, it must go through two standard health protocols, namely hand washing and checking body temperature. If one is not done and the value is not in accordance with the Covid task force standards, the gate will still be closed, for the hand washing process and temperature sensors use This touchless sensor is to reduce the level of risk of direct contact so that it will reduce the level of spread of the covid-19 virus. The results of this study from 50 respondents who tested the smart gate the success rate reached 90% percent success with 2 input parameters, namely through hand washing and body temperature sensors where the data was processed using fuzzy logic control. The method used for testing is using the functional tools/sensors used. While 10% is not successful because of the external light intensity factor when reading the sensor.
PEMANFAATAN METODE TOPIC MODELLING HIERARCHICAL DIRICHLET PROCESS DALAM MENGEVALUASI KUALITAS KONTEN WEBSITE BERDASARKAN ULASAN PENGGUNA Jatmika, Sunu; Mukti, Fransiska Sisilia; Aprilianto, Tria; Al Zahwa, Naviza Yulia
POSITIF : Jurnal Sistem dan Teknologi Informasi Vol 10 No 1 (2024): Positif : Jurnal Sistem dan Teknologi Informasi
Publisher : P3M Politeknik Negeri Banjarmasin

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31961/positif.v10i1.2199

Abstract

The evaluation of website content is important to ensure that the presented content aligns with users' needs and preferences. This can be accomplished by analyzing user reviews regarding the website's content. This research leverages the Hierarchical Dirichlet Process (HDP) method to automatically identify primary topics from 32 users' reviews, resulting in three main recurring topics: 'good', 'bug', and 'update'. Using the OSEMN framework, the final evaluation indicates that the 'good' topic exhibits the highest cosine similarity value compared to other topics. This signifies that the positive aspects highlighted in users' reviews regarding the website's content dominate and possess significant similarities among the reviews. These findings offer crucial insights into comprehending user evaluations of website content, serving as a basis for more effective and targeted content improvements moving forward.
Co-Authors Al Zahwa, Naviza Yulia Burhanudin, Dimas Fransiska Sisilia Mukti Muhammad Idris Niam Yusuf Awallu, Niam Yusuf Nur Lailatul Aqromi Samsul Arifin Satriyo Cahya Rachmanda Sunu Jatmika, Sunu Yosepta, Dwi Anggih Yosepta, Dwi Anggih Yuliana Melita Pranoto