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All Journal International Journal of Evaluation and Research in Education (IJERE) Jurnal Kependidikan: Penelitian Inovasi Pembelajaran Jurnal Buana Informatika TELKOMNIKA (Telecommunication Computing Electronics and Control) Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Journal of Information Technology and Computer Science Cyberspace: Jurnal Pendidikan Teknologi Informasi INOVTEK Polbeng - Seri Informatika JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI JURNAL PENDIDIKAN TAMBUSAI JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Antivirus : Jurnal Ilmiah Teknik Informatika Jutisi: Jurnal Ilmiah Teknik Informatika dan Sistem Informasi Progresif: Jurnal Ilmiah Komputer JUKANTI (Jurnal Pendidikan Teknologi Informasi) Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) Jurnal Mnemonic INFORMASI (Jurnal Informatika dan Sistem Informasi) JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Abdimasku : Jurnal Pengabdian Masyarakat Aiti: Jurnal Teknologi Informasi Jurnal Teknologi Informasi dan Komunikasi Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Journal of Business and Audit Information System (JBASE) Jurnal Indonesia : Manajemen Informatika dan Komunikasi Decode: Jurnal Pendidikan Teknologi Informasi Jurnal Minfo Polgan (JMP) Prosiding Seminar Nasional Sisfotek (Sistem Informasi dan Teknologi Informasi) IT-Explore: Jurnal Penerapan Teknologi Informasi dan Komunikasi Eduvest - Journal of Universal Studies SmartComp Jurnal Pendidikan Teknologi Informasi (JUKANTI) Jurnal Indonesia : Manajemen Informatika dan Komunikasi Kesatria : Jurnal Penerapan Sistem Informasi (Komputer dan Manajemen)
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Analisa Tweet Mahasiswa untuk Deteksi Gejala Depresi dengan Penerapan Natural Language Processing Dhinora, Monica Yoshe; Mailoa, Evangs
Jurnal Indonesia : Manajemen Informatika dan Komunikasi Vol. 6 No. 2 (2025): Mei
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) STMIK Indonesia Banda Aceh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63447/jimik.v6i2.1405

Abstract

Mental health issues are increasingly gaining attention, with depression being a primary factor linked to high suicide rates caused by psychological disorders. College students are identified as a vulnerable group to depression and anxiety, which can be triggered by various factors. Meanwhile, individuals self-expression on social media, especially on platform X (Twitter), which offers freedom of expression, is considered reflective of one’s mental well-being. This study aims to explore the analysis of college students tweets using a Natural Language Processing (NLP) approach to detect depressive symptoms through linguistic patterns. Data was collected via crawling techniques using keywords such as “depression”, “stress”, and “burnout” resulting in 24,167 tweets from January to March 2025. After data cleaning, 8,308 tweets remained. Sentiment labeling using the Inset Lexicon shows that 68.1% (5,663 tweets) were labeled negative, reflecting college students tendency to use platform X as a medium to express negative emotions. The Random Forest model integrated with TF-IDF feature extraction achieved 87.51% accuracy, demonstrating its capability to address majority class bias (negative) and capture the morphological complexity of informal language. The implications of the research encourage the development of a digital monitoring system for the proactive detection of college college students depression symptoms. The lexicon’s limitations in incorporating informal vocabulary (slang) becomes a recommendation for further research to enhance analysis accuracy.
ANALISIS SENTIMEN ULASAN KONSUMEN MENGGUNAKAN ALGORITMA TF-ID UNTUK MENGETAHUI TINGKAT KEPUASAN PELANGGAN(STUDI KASUS : GUNTHEM PREMIUM COFFEE) Widyastuti, Fransisca Sonia; Mailoa, Evangs
JURNAL TEKNOLOGI INFORMASI DAN KOMUNIKASI Vol. 16 No. 2 (2025): September
Publisher : UNIVERSITAS STEKOM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/jtikp.v16i2.1010

Abstract

In today’s digital era, customer review shared across online platforms are regarded as key indicators for evaluating customer satisfaction and shaping the reputation of s business, including coffee shops. In this study, sentiment analysis was conducted on customer reviews of Gunthem Premium Coffee using the TF-IDF (Term Frequency – Inverse Documen Frequency) method. A total of 46 review entries were collected from Google Maps and GoFood and were manually labeled as either positive or negative. The analysis was carried out in several stages, including text pre-processing, manual labeling, and feature extraction using TF-IDF. Irrelevant word were removed, and important terms were identified based on their weight across the dataset. The result showed that most reviews expressed positive sentiments, with words such as “delicious”, “coffee”, “comfortable”, and “clean” found to have the highest TF-IDF weights. A wordcloud visualization was also created to support the analytical findings. Therefore, the TF-IDF method was proven effective in identifying customer opinions and can serve as a foundation for formulating strategies to enchance service quality and customer satisfaction in the coffee shop industry..
MARKET BASKET ANALYSIS MENGGUNAKAN ALGORITMA APRIORI UNTUK MENDUKUNG STRATEGI PROMOSI PRODUK Bintang Samasto, Revo; Mailoa, Evangs
JURNAL TEKNOLOGI INFORMASI DAN KOMUNIKASI Vol. 16 No. 2 (2025): September
Publisher : UNIVERSITAS STEKOM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/jtikp.v16i2.1011

Abstract

The intense business competition requires companies to deeply understand consumer behavior in order to design effective marketing strategies. This study was conducted to analyze customer purchasing patterns using the market basket analysis method with the Apriori algorithm. This was done because previously the company carried out promotional strategies conventionally without utilizing data analysis or understanding consumer purchasing patterns, resulting in less optimal promotional outcomes. The data used consists of 103 briquette sales transactions during the period from March 2024 to March 2025, which were then processed to find frequent itemsets and association rules. The analysis results show that the combination of Hexagonal With Hole (non-premium) briquettes and Rectangle (non-premium) briquettes is the most frequently purchased together, with a support value of 39.81%, a confidence value of 91.11%, and a lift value of 1.42. These findings provide strategic insights that companies can use to design promotions through bundling and cross-selling.
PENGELOMPOKAN GAYA BELAJAR SISWA UNTUK MENDUKUNG EFEKTIFITAS PEMBELAJARAN DENGAN K-MEANS Krisna Setiawan; Mailoa, Evangs
JURNAL TEKNOLOGI INFORMASI DAN KOMUNIKASI Vol. 16 No. 2 (2025): September
Publisher : UNIVERSITAS STEKOM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/jtikp.v16i2.1013

Abstract

Many schools use learning styles that are not aligned with students' preferences, which can hinder the effectiveness of learning. This study aims to cluster students based on their learning style preferences to support more effective teaching. Data were collected from 27 students using a questionnaire covering four learning styles: Visual, Auditory, Reading/Writing, and Kinesthetic. The K-Means algorithm was used to cluster the data, resulting in three optimal clusters with the highest Silhouette Score of 0.340. The clustering results show three student groups: Visual, Auditory-Reading, and Kinesthetic, with the highest average academic scores in the Auditory-Reading cluster. This study demonstrates that clustering based on learning styles can improve academic achievement, and it is recommended to implement personalized teaching strategies according to students' learning style clusters to enhance learning effectiveness.
Pengembangan Aplikasi Web Manajemen Iklan Radio dan Videotron di Kota Salatiga menggunakan MERN stack Putri, Tiara Syah Indra; Mailoa, Evangs
JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Vol 10, No 3 (2025)
Publisher : STKIP PGRI Tulungagung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29100/jipi.v10i3.6496

Abstract

Iklan radio dan videotron memainkan peran penting dalam periklanan modern, termasuk di Kota Salatiga, di mana kedua media ini turut berkontribusi dalam membentuk identitas kota dan mendukung strategi bisnis. Seiring dengan meningkatnya penggunaan media ini, muncul permasalahan dalam manajemen data iklan yang dilakukan secara manual menggunakan spreadsheet dan pencatatan manual, yang mengakibatkan ketidaksesuaian data. Untuk mengatasi masalah ini, penelitian ini bertujuan untuk mengembangkan aplikasi web manajemen iklan radio dan videotron menggunakan teknologi MERN Stack, yang terdiri dari MongoDB, ExpressJS, ReactJS, dan NodeJS. MERN Stack dipilih karena kemampuannya dalam membangun aplikasi dinamis dan skalabel dengan menggunakan JavaScript. Dengan menerapkan arsitektur MVC (Model, View, Controller), aplikasi ini diharapkan dapat meningkatkan efisiensi pengelolaan data iklan, mengotomatisasi proses manajemen, dan memperbaiki efektivitas sistem yang ada. Penelitian ini juga meninjau relevansi penggunaan MERN Stack dalam konteks aplikasi manajemen data lainnya dan membandingkannya dengan pendekatan yang telah ada sebelumnya
ANALISIS POLA MINAT KONSUMEN DENGAN ALGORITMA APRIORI Sugeng Ariyadi, Faisal Nuryawan; Mailoa, Evangs
JURNAL TEKNOLOGI INFORMASI DAN KOMUNIKASI Vol. 15 No. 2 (2024): September
Publisher : UNIVERSITAS STEKOM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/jtikp.v15i2.873

Abstract

Gunthem Coffee is a cafe located in Semarang as well as a foodtruck when there is an event. Gunthem Coffee provides 20 coffee menus. The large number of coffee menus that spoil consumers, Gunthem Coffee decided to make policies for marketing strategies. Based on the problems experienced by Gunthem Coffee, it is necessary to conduct research on consumer interest patterns so that it will benefit both Gunthem Coffee and consumers. This research uses the a priori algorithm based on field data that can be calculated objectively. The results obtained from the apriori algorithm calculation are to get two (2) association rules with a minimum support of 30% and a minimum confidence of 60%, namely if you buy Black Pink, you will buy Kopi Susu Sanger with a support value of 50% and a confidence value of 67% and if you buy Sanger Milk Coffee, you will buy Black Pink with a support value of 50% and a confidence value of 87%.
Pelatihan Data Science Pada 2024 Guru dan Siswa SMA/SMK Provinsi Nusa Tenggara Timur Manongga, Danny; Iriani, Ade; Kristianto, Budhi; Sembiring, Irwan; Hendry, -; Mailoa, Evangs; Setiyawati, Nina; Bangkalang, Dwi Hosanna
ABDIMASKU : JURNAL PENGABDIAN MASYARAKAT Vol 6, No 2 (2023): Mei 2023
Publisher : LPPM UNIVERSITAS DIAN NUSWANTORO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33633/ja.v6i2.1290

Abstract

Data menjadi aset paling berharga untuk organisasi mana pun karena dapat memandu pengambilan keputusan. Oleh karena itu kemampuan data science merupakan salah satu skill penting. Data science tergambarkan sebagai proses yang dimulai dari pengumpulan dan pengolahan, kemudian disajikan sebagai informasi yang berguna untuk pengambilan keputusan atau bermanfaat bagi pihak yang berkepentingan dengan data. Data science memiliki banyak fungsi dan manfaat dimana beberapa diantaranya adalah membantu menciptakan budaya keputusan berbasis data, mengurangi ketidakpastian dan meningkatkan konsistensi dan keandalan data. Melihat pentingnya kemampuan data science, maka Fakultas Teknologi Informasi bekerja sama dengan ASEAN Foundation serta Dinas Pendidikan dan Kebudayaan Provinsi Nusa Tenggara Timur (NTT) melakukan Pengabdian kepada Masyarakat (PkM) dalam bentuk pelatihan kepada 2024 guru dan siswa SMA/SMK Provinsi NTT sebagai bagian untuk mencetak talenta digital Indonesia. Pelatihan didukung oleh SAP yang merupakan perusahaan software dan teknologi yang berbasis di Jerman melalui platform SAP Analytics Cloud (SAC). PkM dilaksanakan secara daring dan luring. Guru dan siswa antusias mengikuti pelatihan ini terlihat dari hasil evaluasi yang bisa dikerjakan dengan baik oleh para peserta.
Pembekalan Design Thinking Untuk Pembentukan Karakter Wirausaha Muda Solutif-Inovatif Pada Murid SMA/K di Kota Palu Bangkalang, Dwi Hosanna; Setiyawati, Nina; Mailoa, Evangs; Carolina, Deasy; Pakereng, Magdalena Ariance Ineke; Mangoki, Willson
ABDIMASKU : JURNAL PENGABDIAN MASYARAKAT Vol 9, No 1 (2026): JANUARI 2026
Publisher : LPPM UNIVERSITAS DIAN NUSWANTORO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62411/ja.v9i1.3187

Abstract

Salah satu tantangan pada wirausaha muda adalah adanya persoalan pada tahap analisis pasar sebelum usaha mulai dirintis yakni produk yang dihasilkan tidak sesuai dengan kebutuhan pasar. Selain itu, minat siswa untuk berwirausaha masih cenderung rendah. Hal tersebut dipengaruhi oleh pola pikir yang kurang adaptif terhadap risiko dan ketidakpastian, serta ketakutan terhadap kegagalan. Kegiatan Pengabdian kepada Masyarakat (PkM) ini dilakukan di SMKN 1 Palu dan SMAN 2 Palu dengan memberikan workshop Design Thinking kepada siswa untuk membentuk karakter para siswa menjadi gigih, empati, peka, dan kreatif. Dimana karakter ini dibutuhkan untuk menjadi seorang wirausaha. Workshop dilakukan dengan metode praktik untuk meningkatkan partisipasi setiap peserta. Pendekatan berbasis praktik dan interaktif ini terbukti efektif dalam membangun kepercayaan diri, pola pikir kreatif, dan keterampilan wirausaha peserta. Hal ini dibuktikan dengan antusiasme aktif selama proses workshop berlangsung dan kualitas hasil kerja akhir yang disusun oleh siswa. Berdasarkan hasil evaluasi yang dilakukan setelah workshop, 79% peserta menilai bahwa Design Thinking merupakan materi penting untuk mereka.
Rancang Bangun Sistem Penjadwalan Kursus Musik Berbasis Website Wijanarko, Arief; Mailoa, Evangs
Smart Comp :Jurnalnya Orang Pintar Komputer Vol 12, No 1 (2023): Smart Comp: Jurnalnya Orang Pintar Komputer
Publisher : Politeknik Harapan Bersama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30591/smartcomp.v12i1.4592

Abstract

Salatiga Music Course is an institution that manages teaching and learning activities in terms of music and choir activities. So far, Salatiga Music Course institution in carrying out attendance and transaction activities is still done manually with a notebook so that problems occur such as frequent errors in the process of recording attendance and transactions caused by human error. Therefore, this study aims to provide a solution from problem that occurred with designing and building a website-based music course system. This music course system is designed using the waterfall method and built with the PHP programming language using the laravel framework and MySQL database. This music course system is expected can reduce human error so that it can increase effectiveness and efficiency in the attendance and transaction process and increase institutional performance.