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All Journal PROSIDING SEMINAR NASIONAL CENDEKIAWAN Abdimas Universal Jurnal Teknologi Informasi : Jurnal Keilmuan dan Aplikasi Bidang Teknik Informatika Intelmatics
Syandra Sari
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Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Law, Crime, Criminology & Criminal Justice Library & Information Science Social Sciences

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Pemberdayaan UMKM Komunitas OK OCE Menggunakan Media Digital Rully Mardjono; Laser Narindro; Adrian Sjamsul Qamar; Syandra Sari; Arfa Maulana; Ida Jubaidah
Abdimas Universal Vol. 4 No. 1 (2022): April
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat Universitas Balikpapan (LPPM UNIBA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36277/abdimasuniversal.v4i1.190

Abstract

For support development oaf real sector economy, the efforts which needed to foster Micro, Small And Medium Enterprises (MSMEs) in running their business units, we should to provide knowledge and skills to MSME actors for running and develope their business units. Based on that things, OK OCE team which collaboration with Informatics Engineering Major, Trisakti University carried out skills training in the form of using the okeoce.net website application through the Community Service Program, the aim that MSME actors can have the skills to create a portfolio of business units and collect data through a website application for mentoring and coaching efforts. The method used in this acivity are seminar and workshop for using of okeoce.net website with implementation method by online. From the results of the training assessment through online questionnaires, 90.26% considered that they are understand and very satisfied with the materials and methods provided during training. With the MSME data in the website, it can be used as basis data  for decision making for policy makers to analyze and mapping for MSME data based on their types and needs to determine strategic policies for development of curriculum and training materials for MSME development strategies.
APLIKASI PENCATATAN TRANSAKSI KOMUNITAS BAGINDA (BANK SAMPAH GUNUNG INDAH) Indah Pradhipta; Syandra Sari; Anung B Ariwibowo
PROSIDING SEMINAR NASIONAL CENDEKIAWAN Prosiding Seminar Nasional Cendekiawan 2017 Buku III
Publisher : Lembaga Penelitian Universitas Trisakti

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25105/semnas.v0i0.2517

Abstract

Komunitas Bank Sampah adalah sebuah gerakan masyarakat yang bertujuanmendaur ulang sampah pada rumah-rumah masyarakat dengan sistem pencatatantransaksi untuk setiap anggotanya. Aplikasi Bank Sampah merupakan aplikasi yangbertujuan untuk membantu Komunitas Bank Sampah Gunung Indah (BAGINDA) RW 011Kp. Gunung Utara, Cirendeu dalam melakukan proses bisnis dan transaksi padakomunitas bank sampah, seperti penyetoran sampah, pengeluaran dana, dan pemasukandana. Pada aplikasi ini ada dua pengguna yang dapat memakainya yaitu Admin danNasabah. Pembuatan aplikasi menggunakan bahasa pemrograman JAVA, PHP dan basisdata MySQL. Evaluasi terhadap aplikasi berupa kuesioner menunjukkan dari 32pengguna nasabah 75% memberikan tanggapan yang baik untuk aplikasi ini.
PENGEMBANGAN APLIKASI PEMBELAJARAN BERBASIS ANDROID STUDI KASUS: BELAJAR MEMBACA UNTUK ANAK BALITA Abby Hilman Abby Hilman; Ahmad Zuhdi; Syandra Sari
PROSIDING SEMINAR NASIONAL CENDEKIAWAN PROSIDING SEMINAR NASIONAL CENDEKIAWAN 2019 BUKU I
Publisher : Lembaga Penelitian Universitas Trisakti

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25105/semnas.v0i0.5684

Abstract

Penelitian bertujuan untuk mengetahui perkembangan anak balita yang didampingi oleh orang tua dalam belajar membaca bahasa Indonesia yang menggunakan sistem pembelajaran berbantuan komputer dengan istilah Computer Aided Instruction (CAI) untuk mempermudah proses penyampaian. Penelitian ini menggunakan acuan dari buku “PRAKTIS MEMBACA” yang digunakan untuk mengetahui pola suku kata dan juga huruf vokal dan konsonan. Aplikasi yang dikembangkan dalam penelitian ini mengikuti sistematika dalam seri buku “Praktis Membaca”, dengan memperkenalkan kepada anak balita huruf-huruf vokal, dilanjutkan dengan kombinasi huruf konsonan dan vokal mulai dari pola yang sederhana (KV) hingga pola yang semakin sulit (V-KV, KV-KV, KVK-KV) dan seterusnya. Pola suku kata tersebut akan ditampilkan secara acak di aplikasi android agar pola yang dihasilkan lebih beragam dan juga ada tingkatan dalam belajar. Aplikasi ini dibuat agar kata-kata yang dipelajari anak balita lebih dinamis, berbeda jika anak balita hanya membaca dari buku cetak.
PERBANDINGAN KINERJA KLASIFIKASI SENTIMEN ULASAN PRODUK PEMBELIAN BERAS DI MARKETPLACE SHOPEE Dedy Sugiarto; Syandra Sari; Anung Barlianto Ariwibowo; Fitria Nabilah Putri; Dimmas Mulya; Tasya Aulia; Arviandri Naufal Zaki
Jurnal Teknologi Informasi: Jurnal Keilmuan dan Aplikasi Bidang Teknik Informatika Vol. 17 No. 1 (2023): Jurnal Teknologi Informasi : Jurnal Keilmuan dan Aplikasi Bidang Teknik Inform
Publisher : Universitas Palangka Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

This study aims to compare the performance of product purchase sentiment classification in market place shopee using four classification algorithms, namely support vector machine (SVM), naïve bayes (NB), logistic regression (LR),  k-nearest neighbor (KNN) and associated with the feature extraction model used, namely term frequency - inverse document. frequency (TF-IDF) and bag of word (BOW).   Data collection was carried out by extracting rice product review data through the Shopee website using a web scraping technique which was then saved in the form of a file with CSV format. The number of product reviews obtained is 3531 reviews and after pre-processing through the elimination of duplicate reviews, there are 464 reviews with details 16.17% having a negative label (rating 1 or 2), 15.52% having a neutral label (rating 3), and 68.32% have a positive label (rating 4 or 5). The composition of the rankings shows that the data is not balanced. The experimental results show that the combination of LR with TF-IDF shows the best performance with an accuracy of 80%.
An ANALYSIS OF OIL SENTIMENT SENTIMENTS ON TWITTER USING SUPPORT VECTOR MACHINE: ANALISIS SENTIMEN SUBSIDI BAHAN BAKAR MINYAK (BBM) DI TWITTER MENGGUNAKAN SUPPORT VECTOR MACHINE Ibnu Bilal Marta Prawira; Binti Solihah; Syandra Sari
Intelmatics Vol. 3 No. 1 (2023): Januari-Juni
Publisher : Penerbitan Universitas Trisakti

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25105/itm.v3i1.16187

Abstract

Twitter is one of the social media platforms used by people in Indonesia. Twitter is often used by its users to express opinions regarding a product, institution or event. From the keyword fuel, fuel subsidy is a keyword that is currently a trending topic because changes in fuel subsidies affect the prices of other staples, to find out the value of sentiment in public opinion, sentiment analysis is one of the methods used is the support vector machine and lexicon based. Lexicon is a labeling method by matching the words contained in the document with the words contained in the dictionary. After labeling, the data is tested using the classification method, the classification stage is carried out after going through the preprocessing phase, where the tweet classification results tend to be positive or negative, using the Support Vector Machine method and validated by K-Fold Cross Validation.This research produced 50,001 data which were divided into 21,561 positive sentiments, 9206 neutral sentiments and 19234 negative sentiments. From these results it can be concluded that the data shows public support for rising fuel prices or changing fuel subsidy prices.
Co-Authors Abby Hilman Abby Hilman Adrian Sjamsul Qamar Ahmad Zuhdi Anung B Ariwibowo Arfa Maulana Arviandri Naufal Zaki Binti Solihah Dedy Sugiarto Dimmas Mulya Fitria Nabilah Putri Ibnu Bilal Marta Prawira Ida Jubaidah Indah Pradhipta Narindro, Laser Rully Mardjono Tasya Aulia