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All Journal Jurnal Teknik Industri Syntax Jurnal Informatika Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Jurnal Sistem dan Manajemen Industri Matrik : Jurnal Manajemen dan Teknik Industri Produksi Community Development Journal: Jurnal Pengabdian Masyarakat JTTT
Adhi Nugraha
Universitas Muhammadiyah Malang
Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Energy Engineering Health Professions Industrial & Manufacturing Engineering Public Health Transportation

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Pengukuran Kinerja Menggunakan Metode Balanced Scorecard dan Analytical Network Process Pada Perusahaan Manufaktur Lampu Adhi Nugraha; Muhammad Abdillah Arif; Ahmad Mubin
Matrik : Jurnal Manajemen dan Teknik Industri Produksi Vol 20 No 2 (2020)
Publisher : Prodi Teknik Industri Universitas Muhammadiyah Gresik

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30587/matrik.v20i2.1039

Abstract

Pengukuran kinerja yang selama ini digunakan oleh PT XYZ, sebuah perusahaan manufaktur lampu, hanya fokus pada aspek keuangan saja, sehingga aspek – aspek lain diantaranya aspek pelanggan, aspek proses bisnis internal, dan aspek pembelajaran & pertumbuhan masih belum terukur. Perusahaan perlu merancang suatu metode pengukuran kinerja untuk dapat mengetahui tingkat kinerja perusahaan saat ini, yang juga bisa digunakan sebagai acuan perbaikan dan peningkatan kinerja yang harus dilakukan perusahaan. Permasalahan yang dialami perusahaan terdapat pada aspek keuangan, pelanggan, proses bisnis internal, serta pembelajaran dan pertumbuhan. Dalam penyelesaian masalah kinerja, peneliti menggunakan model Balanced Scorecard untuk perancangan serta Analytical Network Process untuk pembobotan indikator kinerja. Adapun untuk pengukuran kinerja perusahaan menggunakan Objective Matrix dengan evaluasi menggunakan Traffic Light System. Dengan menggunakan beberapa metode tersebut, didapatkan beberapa Key Performance Indicator (KPI) yang dianggap kurang. KPI yang dianggap kurang diberikan usulan perbaikan yang dapat dilakukan perusahaan.
Decision Support System for Community Housing Subsidy Recipients Adhi Nugraha; Alvian Widianto; M. Irfan; M. Nasar; Merinda Lestandy
Jurnal Teknik Industri Vol. 21 No. 1 (2020): February
Publisher : Department Industrial Engineering, University of Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (494.914 KB) | DOI: 10.22219/JTIUMM.Vol21.No1.104-114

Abstract

Human needs consist of primary, secondary, and tertiary needs. In primary needs, the house is one of the most critical primary needs in supporting one’s life. However, not all residents in Indonesia can meet these needs. Therefore, the government provides subsidized housing ownership programs for people with low income. This study aims to propose a decision support system in determining the proper housing subsidy recipients. The method used in weighting is Analytic Hierarchy Process (AHP). Previous research was still limited to the selection of subsidized housing for developers and potential buyers. This method is projected to provide results in the form of a priority sequence of alternative solutions based on test results. The results were considered capable of providing a better solution for selecting prospective recipients of the housing subsidy program.
PEMBUATAN SISTEM INFORMASI ALUMNI PADA TK ABA 16 MALANG MENGGUNAKAN BOOTSTRAP Merinda Lestandy; Achmad Nurdim Fikri; Adhi Nugraha
Community Development Journal : Jurnal Pengabdian Masyarakat Vol. 2 No. 1 (2021): Volume 2 Nomor 1 Tahun 2021
Publisher : Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/cdj.v2i1.1485

Abstract

Salah satu upaya meningkatkan mutu sekolah yaitu dengan memanfaatkan teknologi informasi. Saat ini TK ABA 16 Malang belum memiliki sistem untuk menyimpan data siswa, alumni dan guru. Hal tersebut membuat TK ABA 16 Malang kesulitan ketika mencari data terkait siswa, alumni dan guru. Dari permasalahan mitra tersebut, dibuat Sistem Informasi Alumni TK ABA 16 Malang dengan menggunakan Bootstrap. Peserta yang menjadi mitra sasaran sebanyak 7 guru. Pengabdian ini dilakukan dengan 3 tahap yaitu, perancangan sistem dan model UML, implementasi sistem dan pelatihan sistem informasi. Hasil yang dicapai dalam kegiatan pengabdian masyarakat ini adalah pembuatan sistem informasi data alumni TK ABA 16 Malang dapat mengatasi masalah mitra sehingga lebih mudah dalam penyimpanan dan pencarian data siswa/alumni dan guru di dalam sistem.
Penerapan Synthetic Minority Oversampling Technique (SMOTE) untuk Imbalance Class pada Data Text Menggunakan kNN Sultan Maula Chamzah; Merinda Lestandy; Nur Kasan; Adhi Nugraha
SYNTAX Jurnal Informatika Vol 11 No 02 (2022): Oktober 2022
Publisher : Universitas Singaperbangsa Karawang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35706/syji.v11i02.6940

Abstract

Tokopedia is one of the online marketplace providers in Indonesia that facilitates internet users to buy and sell online. Tokopedia gets an average of 147.79 million website and application visitors per month. Although it has many users, of course in an application it has advantages and disadvantages. This was conveyed by users through reviews or reviews contained in the Google Play Store. In the review, it can be seen that more users who gave 5-star rating reviews than users gave 1 star rating. The Synthetic Minority Oversampling Technique or SMOTE is a popular method applied in order to deal with class imbalances. This study aims to determine the performance of the K-Nearest Neighbor algorithm in dealing with imbalance class using Synthetic Minority Oversampling Technique (SMOTE). This study uses 5000 data consisting of 3975 negative data and 1025 positive data. Of the 5000 data divided into two parts, 70% training data and 30% test data. The SMOTE-kNN method shows a better accuracy result, which is 90% compared to using only kNN with an accuracy value of 82%.
Telecommunication service quality analysis using integration of SIPA and modified Kano Hanny Kanavika Rizky Munawar; Annisa Kesy Garside; Adhi Nugraha; Amelia Khoidir
Jurnal Sistem dan Manajemen Industri Vol. 7 No. 1 (2023): June
Publisher : Universitas Serang Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30656/jsmi.v7i1.5530

Abstract

This article investigates the integrated approach of the Simultaneous Impor­tance-Performance Analysis (SIPA) model and the modified Kano model to evaluate and prioritize service attributes for telecommunication companies in Indonesia. The study is based on the demographic profiles and usage patterns of 74 respondents. The results demonstrate that the SIPA and Kano models can provide valuable insights for identifying priority areas and effective strategies for improving service quality. Specifically, the SIPA model helps to compare competitor performance and identify important service attributes. In contrast, the modified Kano model facilitates a dynamic cycle of service attribute evaluation to inform managerial strate­gies. This article contributes by highlighting the potential of the proposed ap­proach to offer valuable insights to telecommunication companies seeking to enhance their service offerings and remain competitive in a con­stantly evolving market.
Usulan Perbaikan Kualitas Pelayanan Cafe Dengan Integrasi Kansei Engineering Dan Model Kano ( Study Kasus : Senyawa Cafe ) Berdyanti Stevanny; Teguh Baroto; Adhi Nugraha
English Vol 1 No 2 (2023): Volume 1 - Nomor 2 - Oktober 2023
Publisher : Fakultas Teknik dan Teknologi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47970/jttt.v1i2.487

Abstract

Eksistensi cafe dunia bisnis saat ini sangat tinggi, khususnya pada generasi muda yang mendominasi menjadi konsumen cafe. Namun tidak hanya kalangan generasi muda, eksistensi cafe juga dapat mendominasi segala umur. Dalam peningkatan pelayanan untuk loyalitas konsumen, maka penelitian ini bertujuan untuk mengetahui solusi dalam meningkatkan kualitas terhadap pelayanan yang diberikan oleh Senyawa cafe. Untuk meningkatkan kualitas pelayanan dengan mendiskripsikan keinginan konsumen maka digunakan metode Kansei Engineering dan Model kano. Kedua metode tersebut mampu mengidentifikasikan keinginan serta harapan konsumen secara penuh yang kemudian dapat dijadikan respon dalam memperbaiki kualitas pelayanan Senyawa cafe. Pengelompokkan atribut pada model kano untuk 14 atribut pelayanan didapatkan atribut pada kategori must-be be. Atribut yang termasuk kategori one-dimensional memiliki 15 atribut. Atribut yang termasuk kategori attractive memiliki 1 atribut layana. Pada metode kansei engineering untuk menilai produk atau jasa melalui perasaan dan emosi yang terdiri dari 9 atribut kansei word diantaranya lengkap, nyaman, strategis, professional, raman, murah, bersih, estetik dan menarik
Analyzing Reddit Data: Hybrid Model for Depression Sentiment using FastText Embedding Merinda Lestandy; Amrul Faruq; Adhi Nugraha; Abdurrahim
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 8 No 2 (2024): April 2024
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v8i2.5641

Abstract

Depression, a prevalent mental condition worldwide, exerts a substantial influence on various aspects of human cognition, emotions, and behavior. The alarming increase in deaths attributable to depression in recent years demonstrates the imperative need to address this problem through prevention and treatment interventions. In the era of thriving social media platforms, which have a significant impact on society and psychological aspects, these platforms have become a means for people to express their emotions and experiences openly. Reddit stands out among these platforms as a significant place. The main aim of this study is to examine the feasibility of forecasting individuals' mental states by classifying Reddit articles on depression and non-depression. This work aims to employ deep learning algorithms and word embeddings to analyze the textual and semantic settings of narratives to detect symptoms of depression. The study effectively employed a BiLSTM-BiGRU model that applied FastText word embeddings. The BiLSTM-BiGRU model analyzes information bidirectionally, detecting correlations in sequential data. It is suitable for tasks dependent on input order or for addressing data uncertainties. The Reddit dataset, which contains text concerning depression, achieved an accuracy score of 97.03% and an F1 score of 97.02%.
Co-Authors Abdurrahim Achmad Nurdim Fikri Ahmad Mubin Alvian Widianto Amelia Khoidir Amrul Faruq Annisa Kesy Garside Berdyanti Stevanny Hanny Kanavika Rizky Munawar M. Irfan M. Nasar Merinda Lestandy Muhammad Abdillah Arif Nur Kasan, Nur Sultan Maula Chamzah Teguh Baroto