Article Per Year (5 Year)
p-Index From 2021 - 2026
2.679
P-Index
This Author published in this journals
All Journal Sinkron : Jurnal dan Penelitian Teknik Informatika Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) ILKOM Jurnal Ilmiah Jurnal Matematika UNAND REMIK : Riset dan E-Jurnal Manajemen Informatika Komputer Jurnal Inovasi Teknik Informatika Journal of Computer Networks, Architecture and High Performance Computing Journal of Applied Data Sciences Journal of Computer Scine and Information Technology Jurnal Abdimas ADPI Sains dan Teknologi Jurnal Ipteks Terapan : research of applied science and education pendidikan, science, teknologi, dan ekonomi Jurnal Komtekinfo
Teri Ade Putra
Universitas Putra Indonesia YPTK Padang
Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Astronomy Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Health Professions Immunology & microbiology Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Materials Science & Nanotechnology Mathematics Medicine & Pharmacology Neuroscience Nursing Physics Public Health Veterinary Other

Published : 20 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 20 Documents
Search

 1   2 
Optimization Analysis Model Determining PNMP Mandiri Loan Status Based on Pearson Correlation Teri Ade Putra; Pradani Ayu Widya Purnama; Riandana Afira; Yesri Elva
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 6 No 6 (2022): Desember 2022
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v6i6.4469

Abstract

PNPM Mandiri is an organization engaged in financing small and medium enterprises in the community. The problem that always occurs is an error in determining the loan status resulting in bad credit. This study aims to present a classification analysis model for determining loan status at PNPM Mandiri. The classification analysis model was built using the Perceptron algorithm artificial neural network. The analysis model will later be optimized using the Person Correlation (PC) method to measure the accuracy of the variables used. The research dataset is based on historical data from the last 2 years as many as 67 data samples. The analysis variables consist of Business Type (X1), Loan Amount (X2), Collateral (X3), Income (X4), and Expenses (X5). The results of the analysis show that the model built can provide optimal classification results. These results can be seen based on the results of variable measurements using the PC method indicating that variable X2 has no significant relationship. With the results of these measurements, the performance of the artificial neural network presents maximum results in determining loan status. Overall, the results of this study can provide an effective analytical model as well as an alternative solution for determining loan status.
COUNTING GAME APPLICATION FOR KINDERGARTEN CHILDREN Teri Ade Putra; Raja Ayu Mahessya; Yesri Elva; Pradani Ayu Widya Purnama
Jurnal Ipteks Terapan (Research Of Applied Science And Education ) Vol. 15 No. 4 (2021): Jurnal Ipteks Terapan ( Research of Applied Science and Education )
Publisher : Lembaga Layanan Pendidikan Tinggi Wilayah X

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (762.094 KB) | DOI: 10.22216/jit.v%vi%i.793

Abstract

Problems The development of Information Technology plays an important role in human life. With the development of Information Technology, humans can easily get information and humans can easily carry out daily activities with the help of existing technology. Technology brings people to see the outside world further, open their minds to think, and build creativity to create new things, one of the technologies that is currently developing very rapidly is smartphone-based technology, especially Android. Many android applications are very helpful at this time such as health applications, transportation and there are also educational games. Educational games can make it easier to learn, sometimes when learning someone will be faced with conditions where it is difficult to understand the lesson, so with the educational game it is hoped that it can help users understand the lessons in the game, besides that educational games are a very fun learning tool for students. , because students will be happier and easier to understand by playing while learning
Selection of Quality Textile Materials as a Support for Supply Chain Management with the Weighted Product Method Alvi Martunasia; Teri Ade Putra; Raja Ayu Mahessya
Journal of Computer Scine and Information Technology Volume 9 Issue 2 (2023): JCSITech
Publisher : Universitas Putra Indonesia YPTK Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35134/jcsitech.v9i2.72

Abstract

Decision making is a matter that is very influential in the process of dealing with the selected alternative. At this time in making decisions is no longer just by human reason. Human limitations in thinking to solve a problem can now be assisted by computerization. The use of computers has developed from just processing data or presenting information, to being able to provide choices as a support for decision makers. The development of information technology has enabled decision makers to be made more quickly and accurately. The research aims to apply the weighted product method in reducing errors in the selection of quality textile materials. This research aims to facilitate the selection of quality textile materials. This research aims to be a good solution for khatialo shops in selecting quality textile materials. The weighted product (WP) method is one of the methods used to complete a decision-making system by considering the criteria and weights . Then proceed with the ranking process which will select the best alternative from a number of alternatives, in this case the alternative in question is the selection of quality textile materials based on the specified criteria. The results obtained with the highest rating value were achieved by the 4th alternative called Semi Sutra with the code TK04 alternative
Klasifikasi Penjualan Produk Menggunakan Algoritma Naive Bayes pada Konter HP Bayu Cell Purnama, Pradani Ayu Widya; Putra, Teri Ade
REMIK: Riset dan E-Jurnal Manajemen Informatika Komputer Vol. 8 No. 1 (2024): Call for Paper: Volume 8 Nomor 1 Januari 2024
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/remik.v8i1.13207

Abstract

Data Mining merupakan proses iteratif dan interaktif untuk menemukan pola atau model baru yang dapat digeneralisasi untuk masa yang akan datang, bermanfaat dan dapat dimengerti dalam suatu database yang sangat besar (massive database). Pada Konter HP Bayu Cell mempunyai masalah dalam menentukan produk yang laris atau tidak laris terjual pada konter tersebut. Dengan demikian untuk adanya suatu sistem yang dapat menunjang Konter HP Bayu Cell dalam mengambil keputusan secara cepat dan tepat agar tidak terjadinya penumpukan produk. Untuk itu pada penelitian ini penulis menggunakan Algoritma Data Mining Metode Algoritma Naïve Bayes, Pada metode Naive Bayes untuk ukuran peluang suatu peristiwa yang terjadi berdasarkan peristiwa lain yang telah (dengan asumsi, praduga, pernyataan, atau terbukti) terjadi. Pada data training yang dilakukan dengan produk handphone REDMI NOTE 9 menggunakan algoritma Naive Bayes dimana menghasilkan klasifikasi masuk ke kategori “Laris” dengan nilai 0,005211. Oleh karena itu pada konter HP Bayu sudah dapat menghasilkan hasil yang diharapkan dan dapat membantu dalam mengetahui mana saja produk handphone yang termasuk kategori laris dan tidak laris.
Penerapan Metode Simple Multi-Attribute Rating Technique (SMART) Untuk Menetukan Penerimaan Karyawan Pada PT.Suka Fajar Purnama, Pradani Widya Pradani; Putra, Teri Ade; Afira, Riandana
REMIK: Riset dan E-Jurnal Manajemen Informatika Komputer Vol. 8 No. 3 (2024): Volume 8 Nomor 3 Agustus 2024
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/remik.v8i3.13946

Abstract

Salah satu bagian penting dalam sebuah perusahaan adalah sumber daya manusia atau karyawan. Karyawan merupakan satu investasi bagi perusahaan untuk tumbuh kembang sesuai dengan visi misi dan tujuan dari perusahaan. Proses penerimaan karyawan memerlukan cara yang profesional dan akurat agar menghasilkan karyawan yang dapat mendukung mutu dan kesuksesan perusahaan. Data yang digunakan pada penelitian ini adalah data karyawan pada PT.Suka Fajar. Dimana pada penelitian menggunakan 6 buah kriteria yang sering menjadi pertimbangan diantarnya Pendidikan, Pengalaman Kerja, Status, Umur , Tes, Wawancara yang akan diolah menggunakan metode SMART. Dimana bobot pada tiap kriteria memiliki nilai interval 0-100 untuk tiap kriteria tergantung prioritas yang didahulukan. Hasil dari perhitungan dengan metode SMART diperolehlah dari 10 karyawan makan sebanyak 6 karyawan dinyatakan LOLOS dan 4 karyawan dinyatakan GAGAL.
Optimalisasi Customer Relationship Management dalam Memberikan Rekomendasi Pembelian Laptop pada Toko Kaito Komputer & CCTV Boy cenly dwi Sandes Pasella; Abulwafa Muhammad; Teri Ade Putra
Jurnal KomtekInfo Vol. 10 No. 4 (2023): Komtekinfo
Publisher : Universitas Putra Indonesia YPTK Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35134/komtekinfo.v10i4.464

Abstract

Laptop merupakan bentuk dari perkembangan teknologi yang banyak digunakan dalam berbagai bidang seperti pekerjaan, pendidikan, dan hiburan. Namun, banyak pengguna terkadang menghadapi kendala dalam memilih laptop yang sesuai dengan kebutuhan mereka, walaupun memiliki buget yang cukup memilih laptop yang cocok dan sesuai bukanlah hal yang mudah, hal tersebut dapat membuat penggunaan laptop yang tidak optimal terhadap kebutuhan penggunanya. Untuk itu, pada penelitian ini akan mengatasi masalah tersebut dengan mengembangkan sistem pendukung keputusan. Sistem pendukung keputusan digunakan sebagai upaya dalam merekomendasi laptop kepada pembeli. Adapun metode yang digunakan dalam sistem pendukung keputusan ini adalah SMART (Simple Multi Attribute Rating Technique). Penelitian ini bertujuan untuk memberikan rekomendasi pembelian laptop yang berlandaskan pada atribut user, penggunaan, buget, ukuran layar, sehingga dapat mempermudah pengambilan keputusan pembelian bagi konsumen. Implementasi metode SMART di Toko Kaito Komputer & CCTV diharapkan dapat meningkatkan tingkat kepuasan konsumen melalui penyediaan rekomendasi yang lebih terpersonalisasi. Dengan demikian, penelitian ini tidak hanya memberikan kontribusi pada pemahaman konsumen terhadap kebutuhan teknologi, tetapi juga berpotensi memperkuat hubungan antara konsumen dan penyedia layanan.
Enhancing Accuracy by Using Boosting and Stacking Techniques on the Random Forest Algorithm on Data from Social Media X Putra, Teri Ade; Ariandi, Vicky; Defit, Sarjon
ILKOM Jurnal Ilmiah Vol 16, No 2 (2024)
Publisher : Prodi Teknik Informatika FIK Universitas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/ilkom.v16i2.2058.184-189

Abstract

Online loans (commonly referred to as Pinjol) have become a widespread phenomenon in Indonesia, both in legal and illegal forms. It is undeniable that this is in line with the rapid development and innovation of technology. Pinjol cannot be separated from public comments, both positive and negative, on social media X. The study examined the communication patterns of Indonesian people using a sentiment analysis approach. The research utilized the Random Forest algorithm to perform sentient analysis. This algorithm combined the output of several decision trees to achieve a more accurate result. In addition to using a random forest algorithm, this study also made improvements by using stacking and boosting. The results of this study indicated that the highest accuracy of 86% was obtained by the SMOTE+RF+Adaboost (Boosting) model. In contrast, the lowest accuracy  of 60% was obtained in the RF+Adaboost model with a stacking technique.
A SISTEM PENDETEKSI SUHU RUANGAN: SISTEM PENDETEKSI SUHU RUANGAN DENGAN MENGUNAKAN ARDUINO Afira, Riandana; Purnama, Ayu Widya; Putra, Teri Ade; Wisky, Irzal Arief
Sinkron : jurnal dan penelitian teknik informatika Vol. 6 No. 2 (2022): Articles Research Volume 6 Issue 2, April 2022
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v7i2.11351

Abstract

In this era, all agencies, be it companies, offices, and industries, take advantage of technological developments with computerized systems. This progress gives an important role in human life. Currently, computers are not only used to process data, they can even be used to control an electronics-based system, such as in the field of controlling external equipment, controlling robots, electronic equipment, and so on. Along with the development of these technologies, the authors try to develop a type of electronic component, namely the LM35DZ Temperature Sensor and Arduino. This research was conducted to create a system that can measure temperature in a room using Arduino and the LM35DZ temperature sensor as the main components. This LM35DZ temperature sensor functions to convert the temperature scale into an electrical quantity in the form of a voltage with a high level of precision but is very simple. Arduino functions as a central place for processing all data and instructions, so that it can facilitate the development of a microcontroller application, starting from writing source programs, complications, uploading complication results and testing serial terminals. The use of Arduino in this tool is combined with ATMEGA 328 and the source program used is the C programming language.
Penerapan Metode Apriori untuk Pembelian di Minimarket Purnama, Pradani Ayu Widya; Putra, Teri Ade; Afira, Riandana; Wijaya, Romi
REMIK: Riset dan E-Jurnal Manajemen Informatika Komputer Vol. 9 No. 1 (2025): Volume 9 Nomor 1 Januari 2025
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/remik.v9i1.14249

Abstract

Agar selalu dapat bertahan dalam persaingan bisnis ataupun minimarket, para pelaku bisnis minimarket harus terus mengembangkan bisnis mereka. Meningkatkan kualitas produk, penambahan jenis produk, pengurangan biaya operasional dan dilakukan analisis data adalah beberapa hal yang dapat ditingkatkan oleh pihak minimarket. Algoritma apriori adalah salah satu algortima terbaik dalam data mining, dengan menggunakan algoritma apriori dan metode market basket analisis ini, peneliti dapat memahami pola pembelian konsumen dengan menganalisis produk-produk yang dibeli. Penelitian ini menghasilkan sebanyak 4 aturan (aturan 1 : Jika pelanggan membeli Produk Susu, mereka cenderung membeli Produk Roti, aturan 2 : Jika pelanggan membeli Produk Roti, mereka cenderung membeli Produk Susu, aturan 3 : Jika pelanggan membeli Produk Roti dan Produk Chiki, mereka cenderung membeli Produk Susu, aturan 4 : Jika pelanggan membeli Produk Susu dan Produk Permen, mereka cenderung membeli Produk Roti). 4 aturan yang didapat tersebut dapat dijadikan sebagai salah satu referensi bagi pihak minimarket dalam mendukung keputusan untuk melakukan tindakan yang bisa meminimalisir terjadinya penumpukan barang.
Enhancing the Performance of Machine Learning Algorithm for Intent Sentiment Analysis on Village Fund Topic Anam, M. Khairul; Putra, Pandu Pratama; Malik, Rio Andika; Karfindo, Karfindo; Putra, Teri Ade; Elva, Yesri; Mahessya, Raja Ayu; Firdaus, Muhammad Bambang; Ikhsan, Ikhsan; Gunawan, Chichi Rizka
Journal of Applied Data Sciences Vol 6, No 2: MAY 2025
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v6i2.637

Abstract

This study explores the implementation of Intent Sentiment Analysis on Twitter data related to the Village Fund program, leveraging Multinomial Naïve Bayes (MNB) and enhancing it with Synthetic Minority Over-sampling Technique (SMOTE) and XGBoost (XGB). The analysis categorizes tweets into six labels: Optimistic, Pessimistic, Advice, Satire, Appreciation, and No Intent. Initially, the MNB model achieved an accuracy of 67% on a 90:10 data split. By applying SMOTE, accuracy improved by 12%, reaching 89%. However, adding Chi-Square feature selection did not increase accuracy further. Incorporating XGB into the MNB+SMOTE model led to a 6% improvement, achieving a final accuracy of 95%. Comprehensive model evaluation revealed that the MNB+SMOTE+XGB model achieved 96% accuracy, 96% precision, 96% recall, and a 96% F1-score, with an AUC of 99%, categorizing it as excellent. These findings demonstrate that the combination of SMOTE for addressing class imbalance and XGBoost for boosting performance significantly enhances the MNB model's classification capabilities. The novelty lies in the integration of these techniques to improve intent sentiment classification for public opinion analysis on the Village Fund program. The results indicate that the majority of tweets labeled as "No Intent" reflect a lack of specific sentiment or actionable intent, providing valuable insights into public perception of the program.
Co-Authors Abulwafa Muhammad Afira, Riandana Alvi Martunasia Anam, M Khairul Ariandi, Vicky Aulia Fitrul Hadi Ayu, Purnama Boy cenly dwi Sandes Pasella Dinul Akhiyar elva, yesri Elva, Yesri Firdaus, Muhammad Bambang Gunawan, Chichi Rizka Ikhsan Ikhsan Irzal Arief Wisky Iskandar, Riki Jafnihirda, Lika Karfindo, Karfindo Lika Jafnihirda Mahessya, Raja Ayu Muhammad Hafizh Pandu Pratama Putra, Pandu Pratama Pradani Ayu Widya Purnama Pradani Ayu Widya Purnama Purnama, Ayu Widya Purnama, Pradani Ayu Widya Purnama, Pradani Widya Pradani Putra, Ondra Eka Rahman, Sepsa Nur Rahmat , Muhammad Arif Raja Ayu Mahessya Raja Ayu Mahessya Raja Ayu Mahessya Reza Suriadinata Riandana Afira Riki Iskandar Rio Andika Malik Sarjon Defit Sepsa Nur Rahman Wijaya, Romi Yesri Elva