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All Journal Sintaks: Jurnal Bahasa dan Sastra Indonesia Software Development Digital Business Intelligence and Computer Engineering ITIJ
Halim, Christina
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Humanities Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering Languange, Linguistic, Communication & Media Other

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Detection of Abnormal Human Sperm Morphology Using Support Vector Machine (SVM) Classification Mas Diyasa, I Gede Susrama; Prasetya, Dwi Arman; Cahyani Kuswardhani, Hajjar Ayu; Halim, Christina
Information Technology International Journal Vol. 2 No. 2 (2024): Information Technology International Journal
Publisher : Magister Teknologi Informasi UPN "Veteran" Jawa Timur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33005/itij.v2i2.36

Abstract

Abnormal sperm morphology is a key indicator of male infertility, making its accurate detection crucial for reproductive health assessments. This study explores the application of Support Vector Machine (SVM) classification to automatically detect abnormalities in human sperm morphology. A dataset of microscopic sperm images was collected and labelled based on normal and abnormal morphological features, including head shape, midpiece defects, and tail irregularities. Feature extraction techniques were employed to quantify key morphological characteristics, which were then used to train the SVM model. The proposed SVM-based approach demonstrated high accuracy in classifying normal versus abnormal sperm morphology, significantly reducing the time and error associated with manual analysis. This method provides an efficient, automated solution for andrology laboratories and fertility clinics, enhancing diagnostic consistency and reliability. By incorporating machine learning techniques, this system holds promise for improving the precision of sperm morphology analysis, ultimately contributing to better fertility treatments and outcomes
Analisis Penggunaan Bahasa Indonesia pada Kemasan Produk Makanan dan Minuman Ringan Iqbal, Naufaldy; Fitriani, Sella Olivia; Halim, Christina; Ababil, Zulfaz Refie; Nurhayati, Eni
Sintaks: Jurnal Bahasa & Sastra Indonesia Vol. 3 No. 2 (2023)
Publisher : Medan Resource Center

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57251/sin.v3i2.979

Abstract

Indonesian is a language that is a unit in the State of Indonesia which is a tool to be able to communicate between people. The purpose of this study is to analyze how errors - both in terms of spelling and from the structure of phrases - are used on food and soft drink product packaging. This study used a descriptive method, namely research conducted by observing something (object of research) and then explaining what was observed. The results of this study indicate that there are still errors in the use of some food and soft drink products. These errors include spelling and inaccuracies in phrase structure. The result of this research is the discovery of several food and soft drink products that still have deviations such as losing phonemes, adding phonemes, and changing phonemes. Deviations at the phonological level on the packaging of food and soft drink products are the main attraction and give a unique impression to consumers.
Analisis Video Keluhan Pelanggan Menggunakan Automatic Speech Recognition dan Analisis Polaritas Sentimen Fahrudin, Tresna Maulana; Aryananda, Rangga Laksana; Gunawan, Ellexia Leonie; Belardo, Valentino; Marcelia, Firsta; Halim, Christina
Software Development, Digital Business Intelligence, and Computer Engineering Vol. 1 No. 1 (2022): SESSION (SEPTEMBER)
Publisher : Politeknik Negeri Banyuwangi Jl. Raya Jember km. 13 Labanasem, Kabat, Banyuwangi, Jawa Timur (68461) Telp. (0333) 636780

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57203/session.v1i1.2022.14-21

Abstract

Tingkat kepuasan pelayanan pelanggan dapat ditinjau berdasarkan keluhan-keluhan pelanggan. Begitu besarnya potensi transaksi penjualan produk dengan pelanggan melalui e-commerce juga meningkatkan peluang terjadinya komplain atau keluhan pelanggan terkait kecacatan produk, keterlambatan produk, kualitas produk, dan lainnya. Keluhan pelanggan biasa disampaikan melalui ulasan-ulasan di media sosial berbentuk teks. Namun, data keluhan pelanggan saat ini semakin bervariasi dalam bentuk video. Oleh karena itu, penelitian ini mencoba untuk menganalisis video keluhan pelanggan menggunakan automatic speech recognition dan analisis polaritas sentimen. Hasil eksperimen menunjukkan bahwa telah ditemukan beberapa keluhan pelanggan pada video yang dianimasikan bertempat di restoran dan mini market. Nilai compound pada video keluhan pelanggan di restoran pada potongan video ke-7 sebesar -0.4747, potongan video ke-10 sebesar -0.8664, dan potongan video ke-11 sebesar -0.6801, sedangkan nilai compound pada video keluhan pelanggan di mini market pada potongan video ke-1 sebesar -0.1027, potongan video ke-2 sebesar -0.2023, dan potongan video ke-5 sebesar -0.5563. Nilai compound tersebut merepresentasikan keluhan pelanggan yang mengarah ke sentimen negatif.
Co-Authors Ababil, Zulfaz Refie Aryananda, Rangga Laksana Belardo, Valentino Cahyani Kuswardhani, Hajjar Ayu Dwi Arman Prasetya Eni Nurhayati, Eni Fahrudin, Tresna Maulana Fitriani, Sella Olivia Gunawan, Ellexia Leonie Iqbal, Naufaldy Marcelia, Firsta Mas Diyasa, I Gede Susrama