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All Journal Jurnal Khatulistiwa Informatika Pendas : Jurnah Ilmiah Pendidikan Dasar Jurnal Informatika Global KOMMAS: Jurnal Pengabdian Kepada Masyarakat Jurnal Pengabdian Mandiri OKTAL : Jurnal Ilmu Komputer dan Sains Jurnal Ilmu Komputer
Achmad Hindasyah
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Humanities Astronomy Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Engineering Languange, Linguistic, Communication & Media Social Sciences Other

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ANALISIS PENDETEKSI KESALAHAN INSTALL BARCODE PADA INNER BOX MENGGUNAKAN SEVEN TOOLS METHOD APPROACH SEBELUM DAN SESUDAH PERBAIKAN (STUDI KASUS PT. DUTA NICHIRINDO PRATAMA) Ade Suma Edi; Makhsun Makhsun; Achmad Hindasyah
Jurnal Khatulistiwa Informatika Vol 9, No 1 (2021): Periode Juni 2021
Publisher : Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/jki.v9i1.9190

Abstract

PT. Duta Nichirindo Pratama merupakan perusahaan yang bergerak dalam  bidang Autoparts Manufacture. Penelitian tugas akhir ini melakukan analisis problem kesalahan penempelan barcode pada inner box menggunakan metode seven tools approach. Analisis pada penelitian ini adalah membandingkan proses pengecekan barcode sebelum perbaikan yaitu pengecekan secara manual atau visual check dan setelah perbaikan yaitu merancang serta membuat mesin pendeteksi barcode secara otomatis dengan sistem berbasis Visual Basic.Net dan Arduino. Perancangan sistem ini menggunakan diagram UML (Unified Modeling Language), perancangan basis data dan perancangan menu antarmuka. Mesin yang dibuat kemudian akan diuji dengan menggunakan pendeteksi black box test. Hasil analisis pengukuran data NG Ratio sebelum perbaikan dan sesudah perbaikan menunjukan penurunan kesalahan sebesar 100%. Data sortir kesalahan deteksi penempelan barcode sebelum perbaikan untuk pengiriman periode bulan Januari sampai dengan Desember 2019 sebesar 2272 Pcs (51,79%). Data kesalahan deteksi penempelan barcode setelah perbaikan untuk pengiriman periode bulan Januari sampai dengan Juni 2020 sebesar 0 Pcs.
Penerapan DSpace Sebagai Institutional Repository Software Sekolah Tinggi Ilmu Komunikasi Profesi Indonesia Firman Pratama; Sewaka Sewaka; Achmad Hindasyah; Devi Damayanti
KOMMAS: Jurnal Pengabdian Kepada Masyarakat Vol 3, No 2 (2022): KOMMAS: JURNAL PENGABDIAN KEPADA MASYARAKAT
Publisher : KOMMAS: Jurnal Pengabdian Kepada Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (603.236 KB)

Abstract

 Berdasarkan data PDDikti Bulan Maret 2021 yang di sandingkan dengan data OpenDoar Bulan Maret 2021 penerapan institusional repository di Indonesia pada institusi pendidikan tinggi baru sekitar 3% dari Perguruan Tinggi yang ada di Indonesia. Saat ini kebutuhan digitalisasi dokumen akademik menjadi hal yang penting bagi penyelenggara Pendidikan. Sekolah Tinggi Ilmu Komunikasi Profesi Indonesia sebagai penyelenggara Pendidikan memerlukan perangkat lunak open source dalam membantu melakukan manajemen arsip dokumen digital yang ada. DSpace dipilih sebagai Institutional Repository Software Sekolah Tinggi Ilmu Komunikasi Profesi Indonesia dikarenakan sudah banyak digunakan oleh institusi serta mudah relatif mudah digunakan. Penerapan DSpace diharapkan dapat membantu mitra memiliki sistem untuk melakukan digitalisasi karya ilmiah serta dokumen lainnya yang dapat berguna bagi masyarakat umum bagi perkembangan ilmu pengetahuan.
PENERAPAN METODE WAIGHTED PRODUCT UNTUK MENENTUKAN TEMPAT STRATEGIS UNTUK BISNIS KULINER BERBASIS WEB (STUDI KASUS : KECAMATAN LEGOK) Muhammad Saipudin Latif; Achmad Hindasyah
OKTAL : Jurnal Ilmu Komputer dan Sains Vol 3 No 05 (2024): OKTAL : Jurnal Ilmu Komputer Dan Sains
Publisher : CV. Multi Kreasi Media

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Abstract

Business is buying and selling activities with the aim of making a profit. Currently doing business has become an alternative to earn additional income besides the main job. Many things influence people to do business, one of which is a strategic location for doing business, both for beginners and those who want to expand their business. The problem faced by business people in determining a strategic location is not carefully considering the right location for doing business so that not a few survive because the location chosen is not strategic. Therefore we need a Decision Support system that can help business people to determine a strategic location to do business effectively. The method used in this study is the Waighted Product method. This method was chosen because it is able to select the best alternative from several alternatives considered, in this case the intended alternative is a strategic location based on predetermined criteria. Determining a strategic location is determined by determining the weight value for each criterion, then a ranking process is carried out which will determine the optimal alternative, namely a strategic location for doing business.
INNOVATIVE WORKSHOP OF MASTERY REMOTE DESKTOP AND TEAMVIEWER FOR STUDENTS OF DHARMA VOCATIONAL SCHOOL KARAWACI OF COMPUTER NETWORK DEPARTMENT Taswanda Taryo; Achmad Hindasyah; Agung Budi Susanto; Farkhan Mubarok; Nining Suharwati; Dahlan Supriatna; Suharyadi; Gregorius Eduard D. P.; Entis Sutisna; Mukhlishoh Syaukati Robbi; Ajeng Permata Suri
JURNAL PENGABDIAN MANDIRI Vol. 4 No. 1: Januari 2025 (In Press)
Publisher : Bajang Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53625/jpm.v4i1.9581

Abstract

Information and communication technology (ICT) has become the backbone of various industrial sectors. There are many applications that can be offered to solve computer repair problems remotely and Remote Desktop and TeamViewer applications are two of them. Dharma Siswa Karawaci Vocational School is committed to preparing graduates who are ready to work and highly competitive in the industrial world. The PKM of Postgraduate Program in Informatics Engineering, Pamulang University-UNPAM conducted an innovative workshop on Remote Desktop and TeamViewer on October 19, 2024. A survey showed they are satisified to participate in the workshop. Student participants can improve the skills of the Vocational School students in mastering Remote Desktop and TeamViewer technology for solving problems and managing networks remotely. The workshop will provide practical experience that suits the current needs of the IT industry, through direct training and simulations. Considering that the workshop only takes a few hours, the student participants of the workshop can continue their training not only at the school or at home, but also can communicate with the Team of S2 TI UNPAM. If necessary, the follow-up workshops can be carried out either offline or online.
Analisis Komparasi Metode Sistem Pendukung Keputusan pada Gaya Belajar “VARK” Riani, Ambar; Taswanda Taryo; Achmad Hindasyah
Jurnal Ilmiah Informatika Global Vol. 14 No. 3
Publisher : UNIVERSITAS INDO GLOBAL MANDIRI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36982/jiig.v14i3.3402

Abstract

Learning style is an important factor in the success of the learning process from learning resources to individuals or groups. Understanding learning styles can be a strategy in the learning process. One of the learning styles is "VARK" which is the preference of individuals or learning groups consisting of visual, aural, read/write, and kinesthetic. Various methods are developed to find out the learning style of an individual or group of learners. In this research, a decision support system (SK) will be developed that provides learning style recommendations for individuals or study groups whether the tendency is visual, aural, read/write, or kinesthetic. The method used is a combination of simple additive weighting (SAW) and weighted product (WP).  The SPK development stages consist of data collection through distributing surveys to 55 student respondents at the 1926 Education Foundation where the dominant characteristic of the respondent's learning style is visual, namely 56%, analyzing SAW and WP methods, developing SPK with a web-based system, testing the system using the black box testing method.
Analisis Pengembangan Dalam Penerapan Recommender System Menggunakan Metode Algoritma Apriori Dan K-Means Clustering Pada Aplikasi E- Commerce. (Studi Kasus Di Big Sport Tangerang) Sukanda, Ahmad; Achmad Hindasyah; Taswanda Taryo
Jurnal Ilmu Komputer Vol 2 No 2 (2024): Jurnal Ilmu Komputer (Edisi Desember 2024)
Publisher : Universitas Pamulang

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Abstract

The sales and marketing system in Big Sport is still carried out conventionally, causing the problem of sales transactions which causes a decrease in turnover. The solution to this problem is an e-commerce application for Big Sport and implementing a strategy recommendation system. By implementing the a priori algorithm method used to find out product recommendations on Big Sport to look for products that frequently appear (frequent itemset) with a minimum support calculation of 3 and a minimum Confidence of 50% from sales transaction data in June 2023 from 18 product data to determine the Association Rule for a combination of itemsets that gets an average lift ratio test value of 1.67 with a maximum Confidence value of 100% which forms 22 Association Rule results to provide good and accurate product recommendations for e-commerce applications based on sales transaction history data . The K-Means Clustering method was implemented using tolls rapidminer using transaction data for 6 months from 18 products. From the rapidminer run, the results from cluster 0 contain 8 items, cluster 1 has 7 items, and cluster 2 has 3 items with an average value. within a centroid distance of 2381.332, where cluster 0 has a value of 1975.234, cluster 1 has a value of 2995.918 and cluster 2 has a value of 2030.222. It can be concluded that items in cluster 0 are products with low sales levels, items in cluster 2 with medium sales levels, and items in cluster 1 with high sales levels. And the Davies Bouldin Index value is 0.462 which shows the fact that the centroid distance assessment results are almost close to 0 which can be concluded to have satisfactory results because the lower the DBI value, the better the cluster value so that it can be used as a reference in product procurement.
Uji Performansi Algoritma K.Means Dalam Mencari Cluster Terbaik Pada Data Sales, Stock Produk Food Beverage (Studi Kasus: PT.Airmas International) Haris Fadhillah; Achmad Hindasyah; Joni Prasetyo
Jurnal Ilmu Komputer Vol 2 No 2 (2024): Jurnal Ilmu Komputer (Edisi Desember 2024)
Publisher : Universitas Pamulang

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Abstract

This research was conducted with the aim of knowing the products that are most in demand by customers, also knowing the products that sell less and knowing the accuracy of testing the performance of sales, stock data. The qualitative method used focuses on interpretation and understanding of interviews or observations to collect sales data, stock of 23 food beverage product items. The results of manual calculation of the k-means algorithm with sales data, stock is to find out the number of products that are in demand by customers with categories: very salable = 3 product items, salable = 5 product items, less salable = 15 product items, then sales data, stock is tested with RapidMiner and Python applications for clustering / grouping what products are in demand by customers the results are the same as the categories: very salable = 3 product items, salable = 5 product items, less salable = 15 product items and looking for the best number of clusters is 3.
Analisis Resiko Stunting Di Kota Tangerang Menggunakan Metode Regresi Linier dan Support Vector Machine Muhamad Farid Hasan Khadafi; Achmad Hindasyah; Tukiyat
Jurnal Ilmu Komputer Vol 3 No 1 (2025): Jurnal Ilmu Komputer (Edisi Juli 2025)
Publisher : Universitas Pamulang

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Abstract

Stunting remains a significant public health issue in Indonesia, particularly in Tangerang City, affecting the physical and cognitive development of children. This problem requires serious attention due to its long-term impacts on children's quality of life and their potential in the future.This study aims to analyze the risk factors contributing to the occurrence of stunting in Tangerang City using Linear Regression and Support Vector Machine (SVM) methods. The research question focuses on identifying and predicting the main risk factors influencing the prevalence of stunting. The research method employs Linear Regression Algorithm and Support Vector Machine Algorithm. The study population consists of children under five years old registered at community health centers in Tangerang City. Data samples were collected from 5,376 children, with 80% (4,300 children) used for training and 20% (1,076 children) for model testing. Several socio-economic and health variables were considered as potential risk factors, including household income, maternal education level, access to clean water and sanitation, dietary diversity, and the presence of antenatal care. Data analysis revealed performance differences between the two models used. The SVM model achieved a significantly higher accuracy of 89% with a standard error of 0.4, demonstrating strong predictive capability. In contrast, the Linear Regression model yielded a lower accuracy of 74% with a standard error of 1.5. This difference highlights the potential advantages of SVM in capturing complex and non-linear relationships within the dataset. These findings can inform targeted interventions and policy recommendations to address the causes of stunting in Tangerang City. Further research could explore a broader range of risk factors.
ANALISIS SENTIMEN PADA PENGGUNA APLIKASI DANA MENGGUNAKAN METODE LSTM DAN BERT UNTUK MENINGKATKAN PENGGUNA APLIKASI DANA Winarni; Achmad Hindasyah; Tumpal Sahala Sirait
Pendas : Jurnal Ilmiah Pendidikan Dasar Vol. 10 No. 04 (2025): Volume 10 No. 04 Desember 2025 Terbit
Publisher : Program Studi Pendidikan Guru Sekolah Dasar FKIP Universitas Pasundan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23969/jp.v10i04.37457

Abstract

Sentiment analysis is an important computational technique used to identify opinions and perceptions expressed by users through textual reviews on digital platforms. This research aims to conduct sentiment analysis on user reviews of the DANA digital wallet application collected from the Google Play Store. The dataset was systematically obtained through a web scraping process, resulting in thousands of review entries as the primary data source. The text data underwent several preprocessing stages, including case folding, cleansing, slang normalization, stopword removal, and tokenization, to produce clean and structured text suitable for modeling. The sentiment classification model employed in this study is the LSTM-BERT architecture, in which IndoBERT is utilized to generate contextual word representations based on the Transformer mechanism, while LSTM is used to capture sequential patterns within the textual data. The model was trained using training data and evaluated using validation and testing datasets. Model performance was assessed using accuracy, precision, recall, F1-score metrics, and confusion matrix visualization. The experimental results indicate that the proposed model achieved an accuracy of 0.70, a weighted average F1-score of 0.67, and a macro average F1-score of 0.58. The model performed well in identifying positive and negative sentiment classes, while performance on the neutralclass remained relatively low due to dataset imbalance issues. These findings demonstrate that the LSTM-BERT model is effective for sentiment classification in Indonesian-language review data from fintech applications, although further improvements are required, particularly in addressing class imbalance to enhance overall model performance.
Co-Authors Ade Suma Edi AGUNG BUDI SUSANTO Ajeng Permata Suri Dahlan Supriatna Devi Damayanti Entis Sutisna Farkhan Mubarok Firman Pratama Gregorius Eduard D. P. Haris Fadhillah Joni Prasetyo Makhsun Makhsun Muhamad Farid Hasan Khadafi Muhammad Saipudin Latif Mukhlishoh Syaukati Robbi Nining Suharwati R. Suharyadi Riani, Ambar Sewaka Sewaka Sukanda, Ahmad Taswanda Taryo Tukiyat Tumpal Sahala Sirait Winarni