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Implementasi Model Prototype Sebagai Media Digitalisasi Bank Sampah Berbasis Android Iqbal Al Fatah; Sulistyo Dwi Sancoko
Simpatik: Jurnal Sistem Informasi dan Informatika Vol. 3 No. 2 (2023): Desember 2023
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/simpatik.v3i2.2857

Abstract

Sampah adalah salah satu masalah yang serius. Pengolahan sampah dengan cara konvesional masih kurang membantu untuk mengubah pemikiran masyarakat tentang sampah. Adapun pengolahan sampah dengan cara yang lebih modern menggunakan sistem bank sampah. Bank sampah memiliki sistem jual dan beli sampah. Dengan membuat aplikasi berbasis android diharapkan ekosistem bank sampah akan lebih memudahkan pelanggan dan pengurus bank sampah. Rancangan aplikasi menggunakan metode prototype agar membermudah pengguna untuk menyamakan fitur sesuai yang diinginkan. Penelitian ini mengusulkan sistem pengajuan sampah agar masyarakat tidak perlu datang membawa sampah ke pengurus bank sampah terlebih dahulu sehingga meningkatkan efisiensi sistem bank sampah. Selain itu terdapat fitur pengambilan sampah dimana pengurus bank sampah akan mengambil sampah ke rumah Masyarakat sesuai jadwal yang sudah ditetapkan dan terdapat fitur untuk mencatat transaksi dari pengambilan sampah yang sudah dilakukan. Pada perancangan aplikasi yang digunakan yaitu use case dan activity diagram serta relasi database. Diharapkan aplikasi dapat membantu meningkatkan efisiensi serta efektifitas dari sistem bank sampah.
Digitalisasi Pelayanan Pos Pembinaan Terpadu Berbasis Android Untuk Peningkatan Kualitas Kesehatan Masyarakat Arief Dwi Yuliana; Sulistyo Dwi Sancoko
Simpatik: Jurnal Sistem Informasi dan Informatika Vol. 3 No. 2 (2023): Desember 2023
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/simpatik.v3i2.2858

Abstract

Posbindu Desa Ringinsari merupakan suatu bentuk pelayanan yang melibatkan peran serta masyarakat untuk mendeteksi dan mengendalikan secara dini faktor risiko PTM secara terpadu yang berlokasi di Desa Ringinsari, Maguwoharjo, Kecamatan Depok, Kabupaten Sleman. Dalam pelayanannya Posbindu masih menggunakan cara manual yaitu menggunakan kertas atau buku sebagai media penyimpanan data. Dengan pelayanan tersebut masih memiliki kelemahan yaitu belum adanya backup data sehingga rentan terjadi kehilangan data. Dengan demikian muncul sebuah ide untuk mengatasi masalah tersebut yaitu peneliti merancang aplikasi Pos Pembinaan Terpadu Berbasis Android. Aplikasi dapat memudahkan petugas untuk mencatat hasil pemeriksaan warga agar penyebaran penyakit dapat ditanggulangi dengan cepat, dan juga sebagai sarana untuk pelayanan kesehatan di Desa Ringinsari. Hasil penelitian didapatkan dengan adanya aplikasi Pos Pembinaan Terpadu sebagai media Pencatatan laporan kesehatan, dapat memudahkan dalam pelayanan kesehatan Masyarakat di Desa Ringinsari.
Sentiment Analysis of the Merah Putih Movie Using Naïve Bayes and Support Vector Machine Sulistyo Dwi Sancoko; Ulfah Nafiah; Yudit Manda; Novera Sari Mukti
bit-Tech Vol. 8 No. 3 (2026): bit-Tech
Publisher : Komunitas Dosen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32877/bt.v8i3.3823

Abstract

Public engagement on YouTube provides a valuable source for examining audience responses to film productions; however, sentiment classification of Indonesian-language comments remains methodologically challenging due to informal expressions, noisy text, and imbalanced class distributions. This study evaluates the robustness of a classical machine learning pipeline for sentiment classification of YouTube comments on the trailer of the Indonesian animated film Merah Putih: One for All. A total of 5,469 comments were collected using the YouTube Data API v3. After preprocessing and lexicon-based pseudo-labeling, 5,192 comments were retained, consisting of 4,006 negative and 1,186 positive instances. Text features were represented using TF-IDF, while SMOTE was applied only to the training set after a stratified 80:20 split to prevent data leakage. Two classifiers were compared under identical experimental conditions: Multinomial Naïve Bayes and linear Support Vector Machine. The SVM model achieved 81.59% accuracy, 83% precision, 82% recall, and 82% F1-score on the original held-out test set, outperforming Naïve Bayes, which obtained 76.82% accuracy. The findings suggest that margin-based classification is more suitable than probabilistic classification for sparse, high-dimensional Indonesian YouTube comments, particularly when feature independence assumptions are likely violated. The study contributes a leakage-controlled evaluation of classical sentiment classification under imbalanced social-media conditions and highlights the methodological implications of pseudo-labeling and synthetic oversampling in Indonesian film-related opinion mining.
Pengembangan Aplikasi Pengelolaan Bank Sampah Srikandi Mobile di Gunungkidul Muhammad Rossi Pratama; Sulistyo Dwi Sancoko
Jutisi : Jurnal Ilmiah Teknik Informatika dan Sistem Informasi Vol 14, No 3: Desember 2025
Publisher : STMIK Banjarbaru

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35889/jutisi.v14i3.3334

Abstract

The environmental sector is one area that is experiencing significant transformation thanks to advances in information technology. Digitalization of waste management through web-based and mobile applications can increase efficiency, transparency and community participation in supporting more modern waste management. This research aims to develop a management application for the Srikandi Mandiri Waste Bank. The system development method used is the Waterfall model. This method is applied linearly through the stages of needs analysis, design, implementation of the Srikandi Mobile application development based on Flutter and Laravel (equipped with registration, login, transaction history, cash deposit and withdrawal features, as well as trash pickup requests), testing, and integration with a Filament-based admin dashboard. The development results show that this application is able to facilitate real-time and safe two-way communication between residents and managers. Based on the test results, all the main features of the application, namely User Authentication, Balance Collection, Waste Collection, Waste Deposit, and Transaction History, have functioned well and in accordance with the expected results.Keywords: Waste Bank; Digitalization; Flutter; Laravel; Mobile AbstrakSektor lingkungan merupakan salah satu bidang yang mengalami transformasi signifikan berkat kemajuan teknologi informasi. Digitalisasi pengelolaan limbah melalui aplikasi berbasis web dan mobile dapat meningkatkan efisiensi, transparansi, serta partisipasi masyarakat dalam mendukung pengelolaan sampah yang lebih modern. Penelitian ini bertujuan untuk mengembangkan apllikasi pengelolaan Bank Sampah Srikandi Mandiri. Metode pengembangan sistem yang digunakan adalah model Waterfall. Metode ini diterapkan secara linier melalui tahapan analisis kebutuhan, perancangan, implementasi pembangunan aplikasi Srikandi Mobile berbasis Flutter dan Laravel (dilengkapi fitur registrasi, login, riwayat transaksi, setor dan tarik tunai, serta permintaan penjemputan sampah), pengujian, hingga integrasi dengan dashboard admin berbasis Filament. Hasil pengembangan menunjukkan bahwa aplikasi ini mampu memfasilitasi komunikasi dua arah secara real-time dan aman antara warga dan pengelola. Berdasarkan hasil pengujian, seluruh fitur utama aplikasi, yaitu Autentikasi Pengguna, Pengambilan Saldo, Pengambilan Sampah, Setor Sampah, dan Riwayat Transaksi, telah berfungsi dengan baik dan sesuai dengan hasil yang diharapkan. 
Sentiment Analysis of Customer Experience Based on Wordcloud Visualization at Kampung Inggris Bandung EPLC sulistyo dwi sancoko; Muhammad Rafi Al Basyari
Jurnal Inovatif : Inovasi Teknologi Informasi dan Informatika Vol. 9 No. 1 (2026)
Publisher : Universitas Ibn Khaldun Bogor

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Abstract

Information technology has significantly influenced various sectors, including education, where it is increasingly used to evaluate and improve teaching systems. However, traditional evaluation methods often yield superficial feedback that lacks specific, actionable insights. This study aims to deeply analyze the sentiment of the teaching system evaluation at Kampung Inggris Bandung EPLC and present the findings intuitively through visual analytics. Data were gathered from student feedback during the 79th learning period, collected via Google Forms between January 7 and January 26, 2025. A total of 2,590 raw data entries were preprocessed through rigorous Natural Language Processing (NLP) techniques and analyzed using the K-Nearest Neighbor (KNN) algorithm paired with Term Frequency-Inverse Document Frequency (TF-IDF) feature extraction. The classification resulted in 1,171 positive sentiments and 111 negative sentiments. The model evaluation demonstrated high effectiveness, achieving an accuracy of 90.66%, precision of 82.19%, recall of 90.66%, and an F1-score of 86.22%. Furthermore, data visualization using Wordclouds successfully mapped student response patterns across various class categories (Rookie, Speaking, Grammar, and TOEFL), highlighting institutional strengths in engaging teaching methods and pinpointing specific facility-related areas for improvement.
A Hybrid Fuzzy Multiple Criteria Decision-Making (FMCDM) Approach for Evaluating Quality Management Success Factors in SMEs in Bantul sulistyo dwi sancoko; Sanjaya Fadil Indra; Kalifia Anna Dina; Artika Selfi
Jurnal Inovatif : Inovasi Teknologi Informasi dan Informatika Vol. 9 No. 1 (2026)
Publisher : Universitas Ibn Khaldun Bogor

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Abstract

Quality Management (QM) plays an important role in improving product quality in handicraft SMEs. However, the implementation of QM in small and medium-scale handicraft businesses is still relatively low. Therefore, this study aims to evaluate the Critical Success Factors (CSFs) of QM in handicraft SMEs in Bantul by using a Hybrid Fuzzy Multiple Criteria Decision-Making (FMCDM) approach. The primary criteria for evaluating QM CSFs were obtained through a literature survey and then processed through the FDM approach by industry and academic experts. Through this approach, the importance of QM CSFs was categorized into three main factors and 16 sub-factors. Two fuzzy MCDM methods were applied, namely fuzzy AHP and TOPSIS, to produce priority rankings for each factor and sub-factor. The results showed that the human factor was ranked first among the three perspectives evaluated. Meanwhile, quality control became the most important sub-factor among the 16 sub-factors. This case study provides useful insights for handicraft SME entrepreneurs to improve the quality of their products. The FMCDM method used in this study can serve as a reference for future research in the field of quality management in SMEs. It is hoped that the results of this study can contribute to improving the quality of products in handicraft SMEs in Bantul and surrounding areas.
Determening Determining Learning Interest Directions of Students with Special Needs Using the Analytic Hierarchy Process (AHP) and Profile Matching: A Case Study at SLB Bangunputra Bantul: Penentuan Arah Minat Belajar Siswa Berkebutuhan Khusus Menggunakan Analytic Hierarchy Process (AHP) dan Profile Matching: Studi Kasus di SLB Bangunputra Bantul. Anna Kalifia; Sulistyo Dwi Sancoko Sancoko
Jurnal Inovatif : Inovasi Teknologi Informasi dan Informatika Vol. 8 No. 2 (2025)
Publisher : Universitas Ibn Khaldun Bogor

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Abstract

Determining the appropriate learning interest direction for students with special needs is a challenging process because each student has different characteristics, behaviors, communication patterns, and learning needs. At SLB Bangunputra Bantul, the determination of students’ learning interests still requires teachers to consider various aspects of student characteristics, making the decision process relatively subjective and dependent on the teacher’s experience. This study proposes a decision support approach to assist teachers in determining the learning interest direction of students with special needs by integrating the Analytic Hierarchy Process (AHP) and Profile Matching methods. AHP is applied to determine the relative weights of the assessment criteria, while Profile Matching is used to compare the actual student profile with the ideal profile for each learning interest direction through gap analysis. The criteria considered in the assessment include student behavior, daily activities, communication patterns, eye contact, and responses to situations encountered during learning activities. The combination of these methods provides a structured mechanism for processing student characteristics and generating recommendations for learning interest directions. The resulting decision support system is intended to assist teachers in making more consistent and objective decisions while still considering the individual characteristics of each student. The proposed approach can therefore serve as a supporting tool for teachers in identifying appropriate learning interest directions and facilitating the development of students’ potential according to their individual characteristics.